{"after":"WzE3OTAxMjU1NDQ4NjUsMjAuNzc0MzAzLDEsImMyY2MyMjAzLWFiMzktNGVlMS05NjhlLTQwZmEyNmViNWEzYiJd","results":[{"_score":14.4546385,"_sort":[1790127215031,14.4546385,0,"1cadc744-8510-4ea1-b7e7-f4031921f8b6"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"NSIDC Services","hasEmail":"mailto:nsidc@nsidc.org"},"description":"This data set consists of daily, 5 km resolution precipitation and mean, near-surface air temperature projections from 2015 through 2100 for the High Mountain Asia (HMA) region. The data were generated by statistically downscaling 0.5\u00b0 resolution model data from the Geophysical Fluid Dynamic Laboratory (GFDL) Seamless System for Prediction and EArth System Research (SPEAR) 30-member ensemble climate model.\n\nProjections are provided for two Shared Socioeconomic Pathways (SSPs): SSP2-4.5 and SSP5 8.5. The historical model run (1990 through 2014) used to initialize the SPEAR projections is also available.","distribution":[{"@type":"dcat:Distribution","description":"Direct download via HTTPS protocol.","downloadURL":"https://n5eil01u.ecs.nsidc.org/HMA/HMA2_DSPAT.001/","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Includes a user's guide, supplemental documents like ATBDs and academic papers, How Tos, FAQs, etc.","downloadURL":"https://doi.org/10.5067/GXAA63DTMC34","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"NASA's newest search and order tool for subsetting, reprojecting, and reformatting data.","downloadURL":"https://search.earthdata.nasa.gov/search?q=HMA2_DSPAT+V001","format":"HTML","mediaType":"text/html","title":"Download this dataset through Earthdata Search"},{"@type":"dcat:Distribution","description":"Provides access to data, documentation, tools, citation information, support, and other resources.","downloadURL":"https://doi.org/10.5067/GXAA63DTMC34","format":"HTML","mediaType":"text/html","title":"This dataset's landing page"},{"@type":"dcat:Distribution","description":"Search and filter data files using a map-based interface","downloadURL":"https://nsidc.org/data/data-access-tool/HMA2_DSPAT/versions/1/","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Search results for publications that cite this dataset by its DOI.","downloadURL":"https://scholar.google.com/scholar?q=10.5067%2FGXAA63DTMC34","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"}],"identifier":"C2815757433-NSIDC_ECS","issued":"1990-01-01","keyword":["atmosphere","atmospheric-temperature","earth-science","precipitation"],"landingPage":"https://doi.org/10.5067/GXAA63DTMC34","language":["en-US"],"modified":"2025-03-31","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"NASA NSIDC DAAC"},"spatial":"60.025 20.025 110.975 45.975","temporal":"1990-01-01T00:00:00Z/2100-12-31T23:59:59.999Z","theme":["geospatial"],"title":"High Mountain Asia Daily 5 km Downscaled SPEAR Precipitation and Air Temperature Projections V001"},"description":"This data set consists of daily, 5 km resolution precipitation and mean, near-surface air temperature projections from 2015 through 2100 for the High Mountain Asia (HMA) region. The data were generated by statistically downscaling 0.5\u00b0 resolution model data from the Geophysical Fluid Dynamic Laboratory (GFDL) Seamless System for Prediction and EArth System Research (SPEAR) 30-member ensemble climate model.\n\nProjections are provided for two Shared Socioeconomic Pathways (SSPs): SSP2-4.5 and SSP5 8.5. The historical model run (1990 through 2014) used to initialize the SPEAR projections is also available.","distribution_titles":["Download this dataset","View documentation related to this dataset","Download this dataset through Earthdata Search","This dataset's landing page","Download this dataset","Google Scholar search results"],"harvest_record":"https://catalog.data.gov/harvest_record/0b6bbfd0-93e7-4857-b165-dcf84c80ae1a","harvest_record_raw":"https://catalog.data.gov/harvest_record/0b6bbfd0-93e7-4857-b165-dcf84c80ae1a/raw","has_download":true,"has_spatial":true,"identifier":"C2815757433-NSIDC_ECS","keyword":["atmosphere","atmospheric-temperature","earth-science","precipitation"],"last_harvested_date":"2026-09-23T01:33:35.031716","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":0,"publisher":"NASA NSIDC DAAC","slug":"high-mountain-asia-daily-5-km-downscaled-spear-precipitation-and-air-temperature-projectio","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"High Mountain Asia Daily 5 km Downscaled SPEAR Precipitation and Air Temperature Projections V001","type":"dataset"},{"_score":25.960907,"_sort":[1790127199443,25.960907,2,"43ae5a7d-875c-430a-904a-61df894dcf5a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Dalia Kirschbaum","hasEmail":"mailto:dalia.kirschbaum@nasa.gov"},"description":"This data set features seven standard annual mean extreme precipitation indices: Rx1day, Rx5day, CWD, R10mm, R20mm, R95pTOT, and R99pTOT. They were selected on the basis of potential relevance to landslide activity from the 27 indices established by the joint CCl/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI). The seven indices were simulated by the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-oriented Low Ocean Resolution version of CM2.5 (GFDL FLOR).","distribution":[{"@type":"dcat:Distribution","description":"Data Access link for ITSD project","downloadURL":"https://nsidc.org/data/data-access-tool/HMA_Precip_FLOR/versions/1/","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Direct download via HTTPS protocol.","downloadURL":"https://n5eil01u.ecs.nsidc.org/HMA/HMA_Precip_FLOR.001/","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Includes a user's guide, supplemental documents like ATBDs and academic papers, How Tos, FAQs, etc.","downloadURL":"https://doi.org/10.5067/W8DR3VBR27PX","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"NASA's newest search and order tool for subsetting, reprojecting, and reformatting data.","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1575810085-NSIDC_ECS&m=-1.265625%2183.25%212%211%210%210%2C2&tl=1528294886%214%21%21&q=hma&ok=hma","format":"HTML","mediaType":"text/html","title":"Download this dataset through Earthdata Search"},{"@type":"dcat:Distribution","description":"Provides access to data, documentation, tools, citation information, support, and other resources.","downloadURL":"https://doi.org/10.5067/W8DR3VBR27PX","format":"HTML","mediaType":"text/html","title":"This dataset's landing page"},{"@type":"dcat:Distribution","description":"Search results for publications that cite this dataset by its DOI.","downloadURL":"https://scholar.google.com/scholar?q=10.5067%2FW8DR3VBR27PX","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"}],"identifier":"C1575810085-NSIDC_ECS","issued":"2000-01-01","keyword":["atmospheric-ocean-indicators","climate-indicators","earth-science"],"landingPage":"https://doi.org/10.5067/W8DR3VBR27PX","language":["en-US"],"modified":"2025-03-31","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"NASA NSIDC DAAC"},"spatial":"34.375 -0.5 125.625 50.5","temporal":"2000-01-01T00:00:00Z/2016-12-31T23:59:59.999Z","theme":["geospatial"],"title":"High Mountain Asia GFDL FLOR Modeled Extreme Precipitation Indices V001"},"description":"This data set features seven standard annual mean extreme precipitation indices: Rx1day, Rx5day, CWD, R10mm, R20mm, R95pTOT, and R99pTOT. They were selected on the basis of potential relevance to landslide activity from the 27 indices established by the joint CCl/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI). The seven indices were simulated by the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-oriented Low Ocean Resolution version of CM2.5 (GFDL FLOR).","distribution_titles":["Download this dataset","Download this dataset","View documentation related to this dataset","Download this dataset through Earthdata Search","This dataset's landing page","Google Scholar search results"],"harvest_record":"https://catalog.data.gov/harvest_record/9e1076c5-8299-4350-a1d3-c313e81f7e76","harvest_record_raw":"https://catalog.data.gov/harvest_record/9e1076c5-8299-4350-a1d3-c313e81f7e76/raw","has_download":true,"has_spatial":true,"identifier":"C1575810085-NSIDC_ECS","keyword":["atmospheric-ocean-indicators","climate-indicators","earth-science"],"last_harvested_date":"2026-09-23T01:33:19.443906","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA NSIDC DAAC","slug":"high-mountain-asia-gfdl-flor-modeled-extreme-precipitation-indices-v001","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"High Mountain Asia GFDL FLOR Modeled Extreme Precipitation Indices V001","type":"dataset"},{"_score":10.535811,"_sort":[1790127170126,10.535811,1,"21ec6506-eb58-4d45-93e6-5168f6380549"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"NSIDC Services","hasEmail":"mailto:nsidc@nsidc.org"},"description":"This data set reports monthly, gridded winter sea ice thickness across the Arctic Ocean. Sea ice thickness is estimated using ATLAS/ICESat-2 L3A Sea Ice Freeboard (ATL10) Version 6 data and NASA Eulerian Snow On Sea Ice Model (NESOSIM) snow loading.","distribution":[{"@type":"dcat:Distribution","description":"Direct download via HTTPS protocol.","downloadURL":"https://n5eil01u.ecs.nsidc.org/ICESAT2_PO/IS2SITMOGR4.003/","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Includes a user's guide, supplemental documents like ATBDs and academic papers, How Tos, FAQs, etc.","downloadURL":"https://doi.org/10.5067/ZCSU8Y5U1BQW","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"NASA's newest search and order tool for subsetting, reprojecting, and reformatting data.","downloadURL":"https://search.earthdata.nasa.gov/search?q=IS2SITMOGR4+V003","format":"HTML","mediaType":"text/html","title":"Download this dataset through Earthdata Search"},{"@type":"dcat:Distribution","description":"Provides access to data, documentation, tools, citation information, support, and other resources.","downloadURL":"https://doi.org/10.5067/ZCSU8Y5U1BQW","format":"HTML","mediaType":"text/html","title":"This dataset's landing page"},{"@type":"dcat:Distribution","description":"Search and filter data files using a map-based interface","downloadURL":"https://nsidc.org/data/data-access-tool/IS2SITMOGR4/versions/3/","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Search results for publications that cite this dataset by its DOI.","downloadURL":"https://scholar.google.com/scholar?q=10.5067%2FZCSU8Y5U1BQW","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"}],"identifier":"C2817412114-NSIDC_ECS","issued":"2018-11-01","keyword":["climate-indicators","cryosphere","cryospheric-indicators","earth-science","sea-ice"],"landingPage":"https://doi.org/10.5067/ZCSU8Y5U1BQW","language":["en-US"],"modified":"2025-03-31","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"NASA NSIDC DAAC"},"spatial":"-180.0 30.0 180.0 88.0","temporal":"2018-11-01T00:00:00Z/2024-04-30T23:59:59.999Z","theme":["geospatial"],"title":"ICESat-2 L4 Monthly Gridded Sea Ice Thickness V003"},"description":"This data set reports monthly, gridded winter sea ice thickness across the Arctic Ocean. Sea ice thickness is estimated using ATLAS/ICESat-2 L3A Sea Ice Freeboard (ATL10) Version 6 data and NASA Eulerian Snow On Sea Ice Model (NESOSIM) snow loading.","distribution_titles":["Download this dataset","View documentation related to this dataset","Download this dataset through Earthdata Search","This dataset's landing page","Download this dataset","Google Scholar search results"],"harvest_record":"https://catalog.data.gov/harvest_record/9b46c479-2e6b-435e-81f1-03b5a083a517","harvest_record_raw":"https://catalog.data.gov/harvest_record/9b46c479-2e6b-435e-81f1-03b5a083a517/raw","has_download":true,"has_spatial":true,"identifier":"C2817412114-NSIDC_ECS","keyword":["climate-indicators","cryosphere","cryospheric-indicators","earth-science","sea-ice"],"last_harvested_date":"2026-09-23T01:32:50.126014","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA NSIDC DAAC","slug":"icesat-2-l4-monthly-gridded-sea-ice-thickness-v003","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"ICESat-2 L4 Monthly Gridded Sea Ice Thickness V003","type":"dataset"},{"_score":8.458166,"_sort":[1790127052842,8.458166,1,"283777eb-31ff-4bd9-834e-6bcb0368ab5e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"GREG STENSAAS","hasEmail":"mailto:stensaas@usgs.gov"},"description":"On the background of these requirements for sensor calibration, intercalibration and product validation, the subgroup on Calibration and Validation of the Committee on Earth Observing System (CEOS) formulated the following recommendation during the plenary session held in China at the end of 2004, with the goal of setting-up and operating an internet based system to provide sensor data, protocols and guidelines for these purposes:\r\n\r\nBackground:\r\n\r\nReference Datasets are required to support the understanding of climate change and quality assure operational services by Earth Observing satellites. The data from different sensors and the resulting synergistic data products require a high level of accuracy that can only be obtained through continuous traceable calibration and validation activities.\r\nRequirement:\r\n\r\nInitiate an activity to document a reference methodology to predict Top of Atmosphere (TOA) radiance for which currently flying and planned wide swath sensors can be intercompared, i.e. define a standard for traceability. Also create and maintain a fully accessible web page containing, on an instrument basis, links to all instrument characteristics needed for intercomparisons as specified above, ideally in a common format. In addition, create and maintain a database (e.g. SADE) of instrument data for specific vicarious calibration sites, including site characteristics, in a common format. Each agency is responsible for providing data for their instruments in this common format. Recommendation : The required activities described above should be supported for an implementation period of two years and a maintenance period over two subsequent years. The CEOS should encourage a member agency to accept the lead role in supporting this activity. CEOS should request all member agencies to support this activity by providing appropriate information and data in a timely manner.\r\n\r\nInstrumented Sites:\r\nDome C, Antarctica is one of eight instrumented sites that are CEOS Reference Test Sites. The CEOS instrumented sites are provisionally being called LANDNET. These instrumented sites are primarily used for field campaigns to obtain radiometric gain, and these sites can serve as a focus for international efforts, facilitating traceability and inter-comparison to evaluate biases of in-flight and future instruments in a harmonized manner.\u00a0 In the longer-term it is anticipated that these sites will all be fully automated and provide surface and atmospheric measurements to the WWW in an autonomous manner reducing some of the cost of a manned campaign, at present three can operate in this manner.","distribution":[{"@type":"dcat:Distribution","description":"Direct download via HTTPS protocol.","downloadURL":"https://n5eil01u.ecs.nsidc.org/PM/NSIDC-0079.004/","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Includes a user's guide, supplemental documents like ATBDs and academic papers, How Tos, FAQs, etc.","downloadURL":"https://doi.org/10.5067/X5LG68MH013O","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"NASA's newest search and order tool for subsetting, reprojecting, and reformatting data.","downloadURL":"https://search.earthdata.nasa.gov/search?q=NSIDC-0079+V004","format":"HTML","mediaType":"text/html","title":"Download this dataset through Earthdata Search"},{"@type":"dcat:Distribution","description":"Provides access to data, documentation, tools, citation information, support, and other resources.","downloadURL":"https://doi.org/10.5067/X5LG68MH013O","format":"HTML","mediaType":"text/html","title":"This dataset's landing page"},{"@type":"dcat:Distribution","description":"Search and filter data files using a map-based interface","downloadURL":"https://nsidc.org/data/data-access-tool/NSIDC-0079/versions/4/","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Search results for publications that cite this dataset by its DOI.","downloadURL":"https://scholar.google.com/scholar?q=10.5067%2FX5LG68MH013O","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"}],"identifier":"C1220566821-USGS_LTA","issued":"1972-12-06","keyword":["earth-science","land-surface","land-use-land-cover","national-geospatial-data-asset","ngda","sensor-characteristics","spectral-engineering","surface-radiative-properties","surface-thermal-properties"],"landingPage":"https://cmr.earthdata.nasa.gov:443/search/concepts/C1220566821-USGS_LTA.html","language":["en-US"],"modified":"2025-03-31","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"DOI/USGS/EROS"},"spatial":"123.0 -76.6 131.18 -74.5","temporal":"1972-12-06T00:00:00Z/2023-02-28T00:00:00Z","theme":["CWIC","geospatial"],"title":"CEOS Cal Val Test Site - Dome C, Antarctica - Instrumented Site"},"description":"On the background of these requirements for sensor calibration, intercalibration and product validation, the subgroup on Calibration and Validation of the Committee on Earth Observing System (CEOS) formulated the following recommendation during the plenary session held in China at the end of 2004, with the goal of setting-up and operating an internet based system to provide sensor data, protocols and guidelines for these purposes:\r\n\r\nBackground:\r\n\r\nReference Datasets are required to support the understanding of climate change and quality assure operational services by Earth Observing satellites. The data from different sensors and the resulting synergistic data products require a high level of accuracy that can only be obtained through continuous traceable calibration and validation activities.\r\nRequirement:\r\n\r\nInitiate an activity to document a reference methodology to predict Top of Atmosphere (TOA) radiance for which currently flying and planned wide swath sensors can be intercompared, i.e. define a standard for traceability. Also create and maintain a fully accessible web page containing, on an instrument basis, links to all instrument characteristics needed for intercomparisons as specified above, ideally in a common format. In addition, create and maintain a database (e.g. SADE) of instrument data for specific vicarious calibration sites, including site characteristics, in a common format. Each agency is responsible for providing data for their instruments in this common format. Recommendation : The required activities described above should be supported for an implementation period of two years and a maintenance period over two subsequent years. The CEOS should encourage a member agency to accept the lead role in supporting this activity. CEOS should request all member agencies to support this activity by providing appropriate information and data in a timely manner.\r\n\r\nInstrumented Sites:\r\nDome C, Antarctica is one of eight instrumented sites that are CEOS Reference Test Sites. The CEOS instrumented sites are provisionally being called LANDNET. These instrumented sites are primarily used for field campaigns to obtain radiometric gain, and these sites can serve as a focus for international efforts, facilitating traceability and inter-comparison to evaluate biases of in-flight and future instruments in a harmonized manner.\u00a0 In the longer-term it is anticipated that these sites will all be fully automated and provide surface and atmospheric measurements to the WWW in an autonomous manner reducing some of the cost of a manned campaign, at present three can operate in this manner.","distribution_titles":["Download this dataset","View documentation related to this dataset","Download this dataset through Earthdata Search","This dataset's landing page","Download this dataset","Google Scholar search results"],"harvest_record":"https://catalog.data.gov/harvest_record/f7a48065-32fa-48ce-94d3-435ef3e58d7d","harvest_record_raw":"https://catalog.data.gov/harvest_record/f7a48065-32fa-48ce-94d3-435ef3e58d7d/raw","has_download":true,"has_spatial":true,"identifier":"C1220566821-USGS_LTA","keyword":["earth-science","land-surface","land-use-land-cover","national-geospatial-data-asset","ngda","sensor-characteristics","spectral-engineering","surface-radiative-properties","surface-thermal-properties"],"last_harvested_date":"2026-09-23T01:30:52.842765","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"DOI/USGS/EROS","slug":"ceos-cal-val-test-site-dome-c-antarctica-instrumented-site","spatial_centroid":null,"spatial_shape":null,"theme":["CWIC","geospatial"],"title":"CEOS Cal Val Test Site - Dome C, Antarctica - Instrumented Site","type":"dataset"},{"_score":19.271696,"_sort":[1790127015453,19.271696,0,"95bda1fd-02e6-4ed6-aed8-373bef493cb9"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"undefined","hasEmail":"mailto:support-asdc@earthdata.nasa.gov"},"description":"ATTREX-Aircraft_navigational_meteorological_Measurements are in-situ navigational and meteorological measurements collected onboard the Global Hawk Unihabited Aerial System (UAS) during the Airborne Tropical TRopopause EXperiment (ATTREX) campaign. This collection consists of in-situ meteorological and navigational properties collected by the Meteorological Measurement System (MMS) during the 2011 and 2013 deployments over California, and 2014 deployment over Guam. Data collection is complete.\nEven though it is typically found in low concentrations, stratospheric water vapor has large impacts on the Earth\u2019s climate and energy budget. Studies have suggested that even relatively small changes in stratospheric humidity may have significant climate impacts and future changes in stratospheric humidity and ozone concentration in response to a changing climate are significant climate feedback. Tropospheric water vapor climate feedback is typically well represented in global models. However, predictions of future changes in stratospheric humidity are highly uncertain due to gaps in our understanding of physical processes occurring in the region of the atmosphere that controls the composition of the stratosphere, the Tropical Tropopause Layer (TTL, ~13-18 km). The ability to predict future changes in stratospheric ozone are also limited due to uncertainties in the chemical composition of the TTL. In order to address these uncertainties, the Airborne Tropical Tropopause Experiment (ATTREX) was completed. Instruments during ATTREX provided measurements to trace the movement of reactive halogen-containing compounds and other important chemical species, the size and shape of cirrus cloud particles, water vapor, and winds in three dimensions through the TTL. Bromine-containing gases were measured to improve understanding of stratospheric ozone. ATTREX consisted of four NASA Global Hawk Uninhabited Aerial System (UAS) campaigns deployed from NASA\u2019s Armstrong Flight Research Center (formally Dryden Flight Research Center). Campaigns were deployed over Edwards, CA, Guam, Hawaii, and Darwin, Australia in Boreal summer, winter, fall, and summer, respectively.","distribution":[{"@type":"dcat:Distribution","description":"ASDC Data and Information for ATTREX","downloadURL":"https://asdc.larc.nasa.gov/project/ATTREX","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"ASDC Direct Data Download for ATTREX-Aircraft_navigational_and_meteorological_Measurements_1","downloadURL":"https://asdc.larc.nasa.gov/data/ATTREX/Aircraft_navigational_and_meteorological_Measurements_1/","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"DOI data set landing page for ATTREX-Aircraft_navigational_and_meteorological_Measurements_1","downloadURL":"https://doi.org/10.5067/AIRCRAFT/ATTREX/CLOUD-H2O-TRACER-RADIATION","format":"HTML","mediaType":"text/html","title":"This dataset's landing page"},{"@type":"dcat:Distribution","description":"ESPO Data Archive for ATTREX","downloadURL":"https://espoarchive.nasa.gov/archive/browse/attrex","format":"HTML","mediaType":"text/html","title":"The dataset's project home page"},{"@type":"dcat:Distribution","description":"Earthdata Search for ATTREX-Aircraft_navigational_and_meteorological_Measurements_1 (NASA Application to search, discover, visualize, refine, and access NASA Earth Observation data)","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1536056463-LARC_ASDC","format":"HTML","mediaType":"text/html","title":"Download this dataset through Earthdata Search"},{"@type":"dcat:Distribution","description":"How to cite ASDC data","downloadURL":"https://asdc.larc.nasa.gov/citing-data","format":"HTML","mediaType":"text/html","title":"View this dataset's data citation policy"},{"@type":"dcat:Distribution","description":"Search results for publications that cite this dataset by its DOI.","downloadURL":"https://scholar.google.com/scholar?q=10.5067%2FAIRCRAFT%2FATTREX%2FCLOUD-H2O-TRACER-RADIATION","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"}],"identifier":"C1536056463-LARC_ASDC","issued":"2015-01-30","keyword":["altitude","atmosphere","atmospheric-pressure","atmospheric-temperature","atmospheric-winds","earth-science"],"landingPage":"https://doi.org/10.5067/AIRCRAFT/ATTREX/CLOUD-H2O-TRACER-RADIATION","language":["en-US"],"modified":"2025-04-01","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"-135.62 -12.33 -113.17 36.12","temporal":"2011-10-01T00:00:00Z/2013-03-01T23:59:59Z","theme":["ATTREX","geospatial"],"title":"ATTREX-Aircraft_navigational_and_meteorological_Measurements"},"description":"ATTREX-Aircraft_navigational_meteorological_Measurements are in-situ navigational and meteorological measurements collected onboard the Global Hawk Unihabited Aerial System (UAS) during the Airborne Tropical TRopopause EXperiment (ATTREX) campaign. This collection consists of in-situ meteorological and navigational properties collected by the Meteorological Measurement System (MMS) during the 2011 and 2013 deployments over California, and 2014 deployment over Guam. Data collection is complete.\nEven though it is typically found in low concentrations, stratospheric water vapor has large impacts on the Earth\u2019s climate and energy budget. Studies have suggested that even relatively small changes in stratospheric humidity may have significant climate impacts and future changes in stratospheric humidity and ozone concentration in response to a changing climate are significant climate feedback. Tropospheric water vapor climate feedback is typically well represented in global models. However, predictions of future changes in stratospheric humidity are highly uncertain due to gaps in our understanding of physical processes occurring in the region of the atmosphere that controls the composition of the stratosphere, the Tropical Tropopause Layer (TTL, ~13-18 km). The ability to predict future changes in stratospheric ozone are also limited due to uncertainties in the chemical composition of the TTL. In order to address these uncertainties, the Airborne Tropical Tropopause Experiment (ATTREX) was completed. Instruments during ATTREX provided measurements to trace the movement of reactive halogen-containing compounds and other important chemical species, the size and shape of cirrus cloud particles, water vapor, and winds in three dimensions through the TTL. Bromine-containing gases were measured to improve understanding of stratospheric ozone. ATTREX consisted of four NASA Global Hawk Uninhabited Aerial System (UAS) campaigns deployed from NASA\u2019s Armstrong Flight Research Center (formally Dryden Flight Research Center). Campaigns were deployed over Edwards, CA, Guam, Hawaii, and Darwin, Australia in Boreal summer, winter, fall, and summer, respectively.","distribution_titles":["View documentation related to this dataset","Download this dataset","This dataset's landing page","The dataset's project home page","Download this dataset through Earthdata Search","View this dataset's data citation policy","Google Scholar search results"],"harvest_record":"https://catalog.data.gov/harvest_record/02d38e11-16d1-40dd-af1a-c41fcfdd24a6","harvest_record_raw":"https://catalog.data.gov/harvest_record/02d38e11-16d1-40dd-af1a-c41fcfdd24a6/raw","has_download":true,"has_spatial":true,"identifier":"C1536056463-LARC_ASDC","keyword":["altitude","atmosphere","atmospheric-pressure","atmospheric-temperature","atmospheric-winds","earth-science"],"last_harvested_date":"2026-09-23T01:30:15.453777","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":0,"publisher":"NASA/LARC/SD/ASDC","slug":"attrex-aircraft_navigational_and_meteorological_measurements","spatial_centroid":null,"spatial_shape":null,"theme":["ATTREX","geospatial"],"title":"ATTREX-Aircraft_navigational_and_meteorological_Measurements","type":"dataset"},{"_score":8.449844,"_sort":[1790127007530,8.449844,2,"0f8e2faa-e973-41ca-8e58-b51ae15981bf"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"GREG STENSAAS","hasEmail":"mailto:stensaas@usgs.gov"},"description":"On the background of these requirements for sensor calibration, intercalibration and product validation, the subgroup on Calibration and Validation of the Committee on Earth Observing System (CEOS) formulated the following recommendation during the plenary session held in China at the end of 2004, with the goal of setting-up and operating an internet based system to provide sensor data, protocols and guidelines for these purposes:\n\nBackground:\n\nReference Datasets are required to support the understanding of climate change and quality assure operational services by Earth Observing satellites. The data from different sensors and the resulting synergistic data products require a high level of accuracy that can only be obtained through continuous traceable calibration and validation activities.\nRequirement:\n\nInitiate an activity to document a reference methodology to predict Top of Atmosphere (TOA) radiance for which currently flying and planned wide swath sensors can be intercompared, i.e. define a standard for traceability. Also create and maintain a fully accessible web page containing, on an instrument basis, links to all instrument characteristics needed for intercomparisons as specified above, ideally in a common format. In addition, create and maintain a database (e.g. SADE) of instrument data for specific vicarious calibration sites, including site characteristics, in a common format. Each agency is responsible for providing data for their instruments in this common format. Recommendation : The required activities described above should be supported for an implementation period of two years and a maintenance period over two subsequent years. The CEOS should encourage a member agency to accept the lead role in supporting this activity. CEOS should request all member agencies to support this activity by providing appropriate information and data in a timely manner.\n\nInstrumented Sites:\nLa Crau, France is one of eight instrumented sites that are CEOS Reference Test Sites. The CEOS instrumented sites are provisionally being called LANDNET. These instrumented sites are primarily used for field campaigns to obtain radiometric gain, and these sites can serve as a focus for international efforts, facilitating traceability and inter-comparison to evaluate biases of in-flight and future instruments in a harmonized manner.\u00a0 In the longer-term it is anticipated that these sites will all be fully automated and provide surface and atmospheric measurements to the WWW in an autonomous manner reducing some of the cost of a manned campaign, at present three can operate in this manner.","distribution":[{"@type":"dcat:Distribution","description":"Collection-specific granule Open Search Descriptor Document","downloadURL":"https://cmr.earthdata.nasa.gov/opensearch/granules/descriptor_document.xml?collectionConceptId=C1220566843-USGS_LTA","format":"application/opensearchdescription+xml","mediaType":"application/opensearchdescription+xml","title":"Retrieve the OpenSearch Get Capabilities document"},{"@type":"dcat:Distribution","description":"Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) Test Sites.","downloadURL":"http://calvalportal.ceos.org/web/guest/home","format":"HTML","mediaType":"text/html","title":"The dataset's project home page"}],"identifier":"C1220566843-USGS_LTA","issued":"1972-08-16","keyword":["earth-science","land-surface","land-use-land-cover","national-geospatial-data-asset","ngda","sensor-characteristics","spectral-engineering","surface-radiative-properties","surface-thermal-properties"],"landingPage":"https://cmr.earthdata.nasa.gov:443/search/concepts/C1220566843-USGS_LTA.html","language":["en-US"],"modified":"2025-04-01","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"DOI/USGS/EROS"},"spatial":"1.92 41.86 6.49 45.63","temporal":"1972-08-16T00:00:00Z/2023-03-01T00:00:00Z","theme":["CWIC","geospatial"],"title":"CEOS Cal Val Test Site - La Crau, France - Instrumented Site"},"description":"On the background of these requirements for sensor calibration, intercalibration and product validation, the subgroup on Calibration and Validation of the Committee on Earth Observing System (CEOS) formulated the following recommendation during the plenary session held in China at the end of 2004, with the goal of setting-up and operating an internet based system to provide sensor data, protocols and guidelines for these purposes:\n\nBackground:\n\nReference Datasets are required to support the understanding of climate change and quality assure operational services by Earth Observing satellites. The data from different sensors and the resulting synergistic data products require a high level of accuracy that can only be obtained through continuous traceable calibration and validation activities.\nRequirement:\n\nInitiate an activity to document a reference methodology to predict Top of Atmosphere (TOA) radiance for which currently flying and planned wide swath sensors can be intercompared, i.e. define a standard for traceability. Also create and maintain a fully accessible web page containing, on an instrument basis, links to all instrument characteristics needed for intercomparisons as specified above, ideally in a common format. In addition, create and maintain a database (e.g. SADE) of instrument data for specific vicarious calibration sites, including site characteristics, in a common format. Each agency is responsible for providing data for their instruments in this common format. Recommendation : The required activities described above should be supported for an implementation period of two years and a maintenance period over two subsequent years. The CEOS should encourage a member agency to accept the lead role in supporting this activity. CEOS should request all member agencies to support this activity by providing appropriate information and data in a timely manner.\n\nInstrumented Sites:\nLa Crau, France is one of eight instrumented sites that are CEOS Reference Test Sites. The CEOS instrumented sites are provisionally being called LANDNET. These instrumented sites are primarily used for field campaigns to obtain radiometric gain, and these sites can serve as a focus for international efforts, facilitating traceability and inter-comparison to evaluate biases of in-flight and future instruments in a harmonized manner.\u00a0 In the longer-term it is anticipated that these sites will all be fully automated and provide surface and atmospheric measurements to the WWW in an autonomous manner reducing some of the cost of a manned campaign, at present three can operate in this manner.","distribution_titles":["Retrieve the OpenSearch Get Capabilities document","The dataset's project home page"],"harvest_record":"https://catalog.data.gov/harvest_record/246abd23-5529-4bb3-8a54-4b49a9fb60f0","harvest_record_raw":"https://catalog.data.gov/harvest_record/246abd23-5529-4bb3-8a54-4b49a9fb60f0/raw","has_download":true,"has_spatial":true,"identifier":"C1220566843-USGS_LTA","keyword":["earth-science","land-surface","land-use-land-cover","national-geospatial-data-asset","ngda","sensor-characteristics","spectral-engineering","surface-radiative-properties","surface-thermal-properties"],"last_harvested_date":"2026-09-23T01:30:07.530173","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"DOI/USGS/EROS","slug":"ceos-cal-val-test-site-la-crau-france-instrumented-site","spatial_centroid":null,"spatial_shape":null,"theme":["CWIC","geospatial"],"title":"CEOS Cal Val Test Site - La Crau, France - Instrumented Site","type":"dataset"},{"_score":17.861115,"_sort":[1790126996078,17.861115,2,"351eaf24-b6dc-4db1-ac2c-45e72902897e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Brian Kumanchik","hasEmail":"mailto:brian.kumanchik@jpl.nasa.gov"},"description":"The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite provides new insight into the role that clouds and atmospheric aerosols (airborne particles) play in regulating Earth's weather, climate, and air quality.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://nasa3d.arc.nasa.gov/shared_assets/models/calipso/Calipso-v016-trip.fbx.zip","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"NASA-323","issued":"2018-06-25","keyword":["3d-model","a-train","calipso","eoss","eyes-on-the-earth-3d","eyes-on-the-solar-system","satellite","spacecraft"],"landingPage":"http://nasa3d.arc.nasa.gov/detail/calipso","modified":"2025-04-01","programCode":["026:007"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"references":["http://www-calipso.larc.nasa.gov/"],"theme":["Space Science"],"title":"NASA 3D Models: CALIPSO"},"description":"The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite provides new insight into the role that clouds and atmospheric aerosols (airborne particles) play in regulating Earth's weather, climate, and air quality.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/c97438d6-8b0d-4c52-8c7c-38f64444a166","harvest_record_raw":"https://catalog.data.gov/harvest_record/c97438d6-8b0d-4c52-8c7c-38f64444a166/raw","has_download":true,"has_spatial":false,"identifier":"NASA-323","keyword":["3d-model","a-train","calipso","eoss","eyes-on-the-earth-3d","eyes-on-the-solar-system","satellite","spacecraft"],"last_harvested_date":"2026-09-23T01:29:56.078004","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"National Aeronautics and Space Administration","slug":"nasa-3d-models-calipso","spatial_centroid":null,"spatial_shape":null,"theme":["Space Science"],"title":"NASA 3D Models: CALIPSO","type":"dataset"},{"_score":19.090155,"_sort":[1790126980016,19.090155,0,"f08c69e7-4085-4896-80ee-40027183f9a0"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"undefined","hasEmail":"mailto:support-asdc@earthdata.nasa.gov"},"description":"ATTREX-Aircraft_RemoteSensing_Temperature_Measurements are remotely sensed temperature profiles collected onboard the Global Hawk Unihabited Aerial System (UAS) during the Airborne Tropical TRopopause EXperiment (ATTREX) campaign. This collection consists of remotely sensed temperature profiles collected by the Microwave Temperature Profiler (MTP) during the 2011 and 2013 deployments over California, and 2014 deployment over Guam. Data collection is complete.\nEven though it is typically found in low concentrations, stratospheric water vapor has large impacts on the Earth\u2019s climate and energy budget. Studies have suggested that even relatively small changes in stratospheric humidity may have significant climate impacts and future changes in stratospheric humidity and ozone concentration in response to a changing climate are significant climate feedback. Tropospheric water vapor climate feedback is typically well represented in global models. However, predictions of future changes in stratospheric humidity are highly uncertain due to gaps in our understanding of physical processes occurring in the region of the atmosphere that controls the composition of the stratosphere, the Tropical Tropopause Layer (TTL, ~13-18 km). The ability to predict future changes in stratospheric ozone are also limited due to uncertainties in the chemical composition of the TTL. In order to address these uncertainties, the Airborne Tropical Tropopause Experiment (ATTREX) was completed. Instruments during ATTREX provided measurements to trace the movement of reactive halogen-containing compounds and other important chemical species, the size and shape of cirrus cloud particles, water vapor, and winds in three dimensions through the TTL. Bromine-containing gases were measured to improve understanding of stratospheric ozone. ATTREX consisted of four NASA Global Hawk Uninhabited Aerial System (UAS) campaigns deployed from NASA\u2019s Armstrong Flight Research Center (formally Dryden Flight Research Center). Campaigns were deployed over Edwards, CA, Guam, Hawaii, and Darwin, Australia in Boreal summer, winter, fall, and summer, respectively.","distribution":[{"@type":"dcat:Distribution","description":"Friday: Andrew Ptak, On-the-fly and Grid Analysis of Astronomical Images","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/4.30_AISRP-2009-ptak.pdf","format":"PDF","mediaType":"application/pdf","title":"4.30_AISRP-2009-ptak.pdf"},{"@type":"dcat:Distribution","description":"Friday: Brian Williams, Demonstration of Safe Human / Robot Coordination on the Athlete Lunar Rover","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/Wiliams_NASA_AISR_Talk_Oct_09.pdf","format":"PDF","mediaType":"application/pdf","title":"Wiliams_NASA_AISR_Talk_Oct_09.pdf"},{"@type":"dcat:Distribution","description":"Friday: Edward Belbruno, Controlling Sensitive Trajectories and Transfer Between Planetary Systems","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/Belbruno_AISR2009Conf.pdf","format":"PDF","mediaType":"application/pdf","title":"Belbruno_AISR2009Conf.pdf"},{"@type":"dcat:Distribution","description":"Friday: Gabor Toth Adding New Physics and Numerics into the BATSRUS MHD Code","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/talk.pdf","format":"PDF","mediaType":"application/pdf","title":"talk.pdf"},{"@type":"dcat:Distribution","description":"Friday: Jeffrey Gardner, Astronomy in the Cloud","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/JGardner-AISR09.pdf","format":"PDF","mediaType":"application/pdf","title":"JGardner-AISR09.pdf"},{"@type":"dcat:Distribution","description":"Friday: Jeffrey Jewell, Parallel-Processing Astrophysical Image-Analysis Tools","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/jewell_aisr_2009_fv.pdf","format":"PDF","mediaType":"application/pdf","title":"jewell_aisr_2009_fv.pdf"},{"@type":"dcat:Distribution","description":"Friday: Kenneith Mighell, Parallel-Processing Astrophysical Image-Analysis Tools","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/mighell2009OCT16.pdf","format":"PDF","mediaType":"application/pdf","title":"mighell2009OCT16.pdf"},{"@type":"dcat:Distribution","description":"Friday: Mario Juric, GPU\u2010based Tools for Computational Astrophysics: N\u2010Body Integrators for Planetary Systems","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/AISRP_-_Final.pdf","format":"PDF","mediaType":"application/pdf","title":"AISRP_-_Final.pdf"},{"@type":"dcat:Distribution","description":"Friday: Michael Burl, Directed Exploration of Complex Systems","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/20091016_AISR_BURL.pdf","format":"PDF","mediaType":"application/pdf","title":"20091016_AISR_BURL.pdf"},{"@type":"dcat:Distribution","description":"Friday: Robin Morris, How Well Do You Know That?","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/Morris_aisrp_pi_2009.pdf","format":"PDF","mediaType":"application/pdf","title":"Morris_aisrp_pi_2009.pdf"},{"@type":"dcat:Distribution","description":"Friday: Ron Li, Integration of Orbital, Descent and Ground Imagery for Topographic Capability Analysis in Mars Landed Missions","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/AISRP_PI_Meeting_Li_2009_pub.pdf","format":"PDF","mediaType":"application/pdf","title":"AISRP_PI_Meeting_Li_2009_pub.pdf"},{"@type":"dcat:Distribution","description":"Thrusday: Stephen Fong, An Integrated Systems for Creating and Evaluating Biological Models","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/08.30_SSF_10_15_09.pdf","format":"PDF","mediaType":"application/pdf","title":"08.30_SSF_10_15_09.pdf"},{"@type":"dcat:Distribution","description":"Thursday: Hillol Kargupta, Distributed and Peer-to-Peer Data Mining for Scalable Analysis of Data from Virtual Observatories","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/Kargupta-Slides.pdf","format":"PDF","mediaType":"application/pdf","title":"Kargupta-Slides.pdf"},{"@type":"dcat:Distribution","description":"Thursday: Joel Allred, Solar Magnetogram Synthesis: A Vital Data Analysis Component of A Space Weather Prediction Infrastructure","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/aisrp09.pdf","format":"PDF","mediaType":"application/pdf","title":"aisrp09.pdf"},{"@type":"dcat:Distribution","description":"Thursday: Ken Lang, NASA\u2019S COSMOS","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/LANG-AISR_2009.pdf","format":"PDF","mediaType":"application/pdf","title":"LANG-AISR_2009.pdf"},{"@type":"dcat:Distribution","description":"Thursday: Martin Lo, Science Discovery with MTool on Massive High Dimensional Data","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/AISR09InvstgWrkshpLo.Final.pdf","format":"PDF","mediaType":"application/pdf","title":"AISR09InvstgWrkshpLo.Final.pdf"},{"@type":"dcat:Distribution","description":"Thursday: Thomas Quinn, Visualizing Terascale Datasets with Impostors","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/Quinnaisr09.pdf","format":"PDF","mediaType":"application/pdf","title":"Quinnaisr09.pdf"},{"@type":"dcat:Distribution","description":"Thursday: Zachary Moratto, Automated Digital Terrain Model Generation from HiRISE & LROC Imagery","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/AISRP_moratto.pdf","format":"PDF","mediaType":"application/pdf","title":"AISRP_moratto.pdf"},{"@type":"dcat:Distribution","description":"Wednesday: Andrew Connolly, Streaming the Sky: Data Interfaces with Gadgets","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/connolly.pdf","format":"PDF","mediaType":"application/pdf","title":"connolly.pdf"},{"@type":"dcat:Distribution","description":"Wednesday: Ashit Talukder, GLYDER: Global Cyclone Detection and Tracking from Remote Satellite Data","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/Talukder-AISR_PIMeeting_Oct2009-7.pdf","format":"PDF","mediaType":"application/pdf","title":"Talukder-AISR_PIMeeting_Oct2009-7.pdf"},{"@type":"dcat:Distribution","description":"Wednesday: Chad Schafer, Stochastic Models for Nonstandard, High-Dimensional Data","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/4_AISR_Schafer.pdf","format":"PDF","mediaType":"application/pdf","title":"4_AISR_Schafer.pdf"},{"@type":"dcat:Distribution","description":"Wednesday: Istvan Szapudi, Algorithms for Higher Order Spatial Statistics","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/4.15Szapudi-AISR.pdf","format":"PDF","mediaType":"application/pdf","title":"4.15Szapudi-AISR.pdf"},{"@type":"dcat:Distribution","description":"Wednesday: James Tilton, Object-Based Image Analysis Utilizing Image Segmentation Hierarchies","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/3.45_Tilton_AISR_CIDU_2009.pdf","format":"PDF","mediaType":"application/pdf","title":"3.45_Tilton_AISR_CIDU_2009.pdf"},{"@type":"dcat:Distribution","description":"Wednesday: Jeff Scargle, Novel Methods for the Analysis of Photon-Limited Data","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/2.00_aisrp_pi_scargle.pdf","format":"PDF","mediaType":"application/pdf","title":"2.00_aisrp_pi_scargle.pdf"},{"@type":"dcat:Distribution","description":"Wednesday: John DolanAn Analytical Tool for Robot Mission Reliability Prediction","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/3_20091014_AISR_Dolan.pdf","format":"PDF","mediaType":"application/pdf","title":"3_20091014_AISR_Dolan.pdf"},{"@type":"dcat:Distribution","description":"Wednesday: Kiri Wagstaff, Detecting Transient Surface Features Via Dynamic Landmarking","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/wagstaff-oct14-PI-mtg.pdf","format":"PDF","mediaType":"application/pdf","title":"wagstaff-oct14-PI-mtg.pdf"},{"@type":"dcat:Distribution","description":"Wednesday: Martin Weinberg, UMass Bayesian Inference Engine","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/4.45_weinberg_aisr.pdf","format":"PDF","mediaType":"application/pdf","title":"4.45_weinberg_aisr.pdf"},{"@type":"dcat:Distribution","description":"Wednesday: SG Djorgovski, Automated, Dynamical Event Classification and Response in a Robotic Sensor Network","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/2.15_Djorgovski.pdf","format":"PDF","mediaType":"application/pdf","title":"2.15_Djorgovski.pdf"},{"@type":"dcat:Distribution","description":"Wednesday: Wei Ding, Automatic Detection of Sub-Kilometer craters in High Res Planetary Images","downloadURL":"https://c3.nasa.gov/dashlink/static/media/other/5_AISRP_2009_Ding.pdf","format":"PDF","mediaType":"application/pdf","title":"5_AISRP_2009_Ding.pdf"}],"identifier":"C1536056465-LARC_ASDC","issued":"2015-01-30","keyword":["altitude","atmosphere","atmospheric-temperature","earth-science"],"landingPage":"https://doi.org/10.5067/ASDC_DAAC/ATTREX/0001","language":["en-US"],"modified":"2025-04-01","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"-135.62 -12.33 -113.17 36.12","temporal":"2011-10-01T00:00:00Z/2013-03-01T23:59:59Z","theme":["ATTREX","geospatial"],"title":"ATTREX-Aircraft_RemoteSensing_Temperature_Measurements"},"description":"ATTREX-Aircraft_RemoteSensing_Temperature_Measurements are remotely sensed temperature profiles collected onboard the Global Hawk Unihabited Aerial System (UAS) during the Airborne Tropical TRopopause EXperiment (ATTREX) campaign. This collection consists of remotely sensed temperature profiles collected by the Microwave Temperature Profiler (MTP) during the 2011 and 2013 deployments over California, and 2014 deployment over Guam. Data collection is complete.\nEven though it is typically found in low concentrations, stratospheric water vapor has large impacts on the Earth\u2019s climate and energy budget. Studies have suggested that even relatively small changes in stratospheric humidity may have significant climate impacts and future changes in stratospheric humidity and ozone concentration in response to a changing climate are significant climate feedback. Tropospheric water vapor climate feedback is typically well represented in global models. However, predictions of future changes in stratospheric humidity are highly uncertain due to gaps in our understanding of physical processes occurring in the region of the atmosphere that controls the composition of the stratosphere, the Tropical Tropopause Layer (TTL, ~13-18 km). The ability to predict future changes in stratospheric ozone are also limited due to uncertainties in the chemical composition of the TTL. In order to address these uncertainties, the Airborne Tropical Tropopause Experiment (ATTREX) was completed. Instruments during ATTREX provided measurements to trace the movement of reactive halogen-containing compounds and other important chemical species, the size and shape of cirrus cloud particles, water vapor, and winds in three dimensions through the TTL. Bromine-containing gases were measured to improve understanding of stratospheric ozone. ATTREX consisted of four NASA Global Hawk Uninhabited Aerial System (UAS) campaigns deployed from NASA\u2019s Armstrong Flight Research Center (formally Dryden Flight Research Center). Campaigns were deployed over Edwards, CA, Guam, Hawaii, and Darwin, Australia in Boreal summer, winter, fall, and summer, respectively.","distribution_titles":["4.30_AISRP-2009-ptak.pdf","Wiliams_NASA_AISR_Talk_Oct_09.pdf","Belbruno_AISR2009Conf.pdf","talk.pdf","JGardner-AISR09.pdf","jewell_aisr_2009_fv.pdf","mighell2009OCT16.pdf","AISRP_-_Final.pdf","20091016_AISR_BURL.pdf","Morris_aisrp_pi_2009.pdf","AISRP_PI_Meeting_Li_2009_pub.pdf","08.30_SSF_10_15_09.pdf","Kargupta-Slides.pdf","aisrp09.pdf","LANG-AISR_2009.pdf","AISR09InvstgWrkshpLo.Final.pdf","Quinnaisr09.pdf","AISRP_moratto.pdf","connolly.pdf","Talukder-AISR_PIMeeting_Oct2009-7.pdf","4_AISR_Schafer.pdf","4.15Szapudi-AISR.pdf","3.45_Tilton_AISR_CIDU_2009.pdf","2.00_aisrp_pi_scargle.pdf","3_20091014_AISR_Dolan.pdf","wagstaff-oct14-PI-mtg.pdf","4.45_weinberg_aisr.pdf","2.15_Djorgovski.pdf","5_AISRP_2009_Ding.pdf"],"harvest_record":"https://catalog.data.gov/harvest_record/12f9c3a0-5320-43aa-8931-4b7bc4e35323","harvest_record_raw":"https://catalog.data.gov/harvest_record/12f9c3a0-5320-43aa-8931-4b7bc4e35323/raw","has_download":true,"has_spatial":true,"identifier":"C1536056465-LARC_ASDC","keyword":["altitude","atmosphere","atmospheric-temperature","earth-science"],"last_harvested_date":"2026-09-23T01:29:40.016847","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":0,"publisher":"NASA/LARC/SD/ASDC","slug":"attrex-aircraft_remotesensing_temperature_measurements","spatial_centroid":null,"spatial_shape":null,"theme":["ATTREX","geospatial"],"title":"ATTREX-Aircraft_RemoteSensing_Temperature_Measurements","type":"dataset"},{"_score":10.535811,"_sort":[1790126947770,10.535811,1,"52dae406-a967-4e6d-a1a2-ad7b0a899e28"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Svetla M Hristova-Veleva","hasEmail":"mailto:svetia.hristova@jpl.nasa.gov"},"description":"The JPL Tropical Cyclone Information System (TCIS) brings together satellite and in situ data sets from various sources to help you find information for a particular tropical cyclone over the world's oceans.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://tropicalcyclone.jpl.nasa.gov/","format":"HTML","mediaType":"text/html"}],"identifier":"NASA-0000058","issued":"2018-06-25","keyword":["apps","biochemistry","climate","g1sst","geophysics","h5","hurricanes","meteorology","temperature"],"landingPage":"https://data.nasa.gov/dataset/jpl-tropical-cyclone-information-system","modified":"2025-04-23","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"temporal":"1970-01-01/2014-01-01","title":"JPL Tropical Cyclone Information System"},"description":"The JPL Tropical Cyclone Information System (TCIS) brings together satellite and in situ data sets from various sources to help you find information for a particular tropical cyclone over the world's oceans.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/fb661494-42e0-43da-a64f-6fcb8d03dbe6","harvest_record_raw":"https://catalog.data.gov/harvest_record/fb661494-42e0-43da-a64f-6fcb8d03dbe6/raw","has_download":true,"has_spatial":false,"identifier":"NASA-0000058","keyword":["apps","biochemistry","climate","g1sst","geophysics","h5","hurricanes","meteorology","temperature"],"last_harvested_date":"2026-09-23T01:29:07.770197","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"National Aeronautics and Space Administration","slug":"jpl-tropical-cyclone-information-system","spatial_centroid":null,"spatial_shape":null,"theme":[],"title":"JPL Tropical Cyclone Information System","type":"dataset"},{"_score":10.440588,"_sort":[1790126826941,10.440588,0,"a7a8b2b4-7477-4ea8-8e30-3ddf11eb615e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"NSIDC Services","hasEmail":"mailto:nsidc@nsidc.org"},"description":"This ITS_LIVE data set, part of the Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, consists of 240 m Antarctic Ice Sheet extent masks at roughly annual resolution from 1997 through 2021. The ice masks were generated by combining data acquired by multiple satellite-borne optical, thermal, and radar sensors. The ice thickness and velocity data used to determine the presence of ice are also provided.","identifier":"C3179071550-NSIDC_ECS","issued":"1997-10-01","keyword":["climate-indicators","cryosphere","cryospheric-indicators","earth-science","snow-ice"],"landingPage":"https://doi.org/10.5067/9ZFX84T5GI6D","language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"NASA NSIDC DAAC"},"spatial":"-180.0 -90.0 180.0 -57.6","temporal":"1997-10-01T00:00:00Z/2021-03-14T23:59:59.999Z","theme":["geospatial"],"title":"MEaSUREs ITS_LIVE Antarctic Annual 240 m Ice Sheet Extent Masks, 1997-2021 V001"},"description":"This ITS_LIVE data set, part of the Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, consists of 240 m Antarctic Ice Sheet extent masks at roughly annual resolution from 1997 through 2021. The ice masks were generated by combining data acquired by multiple satellite-borne optical, thermal, and radar sensors. The ice thickness and velocity data used to determine the presence of ice are also provided.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/32ce1169-0365-49b9-8c05-cb2dd4d19f1a","harvest_record_raw":"https://catalog.data.gov/harvest_record/32ce1169-0365-49b9-8c05-cb2dd4d19f1a/raw","has_download":false,"has_spatial":true,"identifier":"C3179071550-NSIDC_ECS","keyword":["climate-indicators","cryosphere","cryospheric-indicators","earth-science","snow-ice"],"last_harvested_date":"2026-09-23T01:27:06.941228","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":0,"publisher":"NASA NSIDC DAAC","slug":"measures-its_live-antarctic-annual-240-m-ice-sheet-extent-masks-1997-2021-v001","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"MEaSUREs ITS_LIVE Antarctic Annual 240 m Ice Sheet Extent Masks, 1997-2021 V001","type":"dataset"},{"_score":10.278671,"_sort":[1790126738239,10.278671,0,"d087edc7-0d01-49b0-bf61-19809db8c749"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Thomas Morgan","hasEmail":"mailto:thomas.h.morgan@nasa.gov"},"description":"These data consist of soil moisture, soil temperature and precipitation measurements recorded in 2016 by the permanent soil moisture network; SMAPVEX16-Iowa. The sites were spread out over the experiment domain of about 30km by 40 km located about 30 km north of Ames, Iowa, USA.\n\nThe data file contains the soil moisture, soil temperature and\u00a0precipitation measurements for each station located at the site.","identifier":"C2011917772-NSIDC_ECS","issued":"2016-05-01","keyword":["atmospheric-ocean-indicators","climate-indicators","earth-science","land-surface-agriculture-indicators"],"landingPage":"https://doi.org/10.5067/P3ZUS77FW7JL","language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"NASA NSIDC DAAC"},"spatial":"-94.0 42.33 -93.22 42.82","temporal":"2016-05-01T00:00:00Z/2016-09-30T23:59:59.999Z","theme":["geospatial"],"title":"SMAPVEX16 Iowa Permanent Soil Moisture Network V001"},"description":"These data consist of soil moisture, soil temperature and precipitation measurements recorded in 2016 by the permanent soil moisture network; SMAPVEX16-Iowa. The sites were spread out over the experiment domain of about 30km by 40 km located about 30 km north of Ames, Iowa, USA.\n\nThe data file contains the soil moisture, soil temperature and\u00a0precipitation measurements for each station located at the site.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/61a5f42c-73ac-41ca-92b7-c829c8992a26","harvest_record_raw":"https://catalog.data.gov/harvest_record/61a5f42c-73ac-41ca-92b7-c829c8992a26/raw","has_download":false,"has_spatial":true,"identifier":"C2011917772-NSIDC_ECS","keyword":["atmospheric-ocean-indicators","climate-indicators","earth-science","land-surface-agriculture-indicators"],"last_harvested_date":"2026-09-23T01:25:38.239807","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":0,"publisher":"NASA NSIDC DAAC","slug":"smapvex16-iowa-permanent-soil-moisture-network-v001","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"SMAPVEX16 Iowa Permanent Soil Moisture Network V001","type":"dataset"},{"_score":18.400194,"_sort":[1790126730688,18.400194,0,"252f1f96-2227-4c0e-98ca-eff4654b180b"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"EUGENE FOSNIGHT","hasEmail":"mailto:fosnight@usgs.gov"},"description":"The Global Forest Observations Initiative (GFOI) is an initiative of the inter-governmental Group on Earth Observations (GEO) that aims to:\n\nfoster the sustained availability of observations for national forest monitoring systems; support governments that are establishing national systems by providing a platform for coordinating observations, providing assistance and guidance on utilising observations, developing accepted methods and protocols, and promoting ongoing research and development; and work with national governments that report into international forest assessments (such as the global Forest Resources Assessment (FRA) of the Food and Agriculture Organization, FAO) and the national greenhouse gas inventories reported to the UN Framework Convention on Climate Change (UNFCCC) using methods of the Intergovernmental Panel on Climate Change (IPCC).","identifier":"C1220567933-USGS_LTA","issued":"2019-09-20","keyword":["agriculture","biosphere","earth-science","forest-science","habitat-conversion-fragmentation","human-dimensions","terrestrial-ecosystems","vegetation"],"landingPage":"https://cmr.earthdata.nasa.gov:443/search/concepts/C1220567933-USGS_LTA.html","language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"DOI/USGS/EROS"},"spatial":"174.0 -22.0 -176.0 -13.0","temporal":"1970-01-01T00:00:00Z/2022-01-17T00:00:00Z","theme":["CWIC","geospatial"],"title":"Global Forest Observations Initiative (GFOI) - Fiji"},"description":"The Global Forest Observations Initiative (GFOI) is an initiative of the inter-governmental Group on Earth Observations (GEO) that aims to:\n\nfoster the sustained availability of observations for national forest monitoring systems; support governments that are establishing national systems by providing a platform for coordinating observations, providing assistance and guidance on utilising observations, developing accepted methods and protocols, and promoting ongoing research and development; and work with national governments that report into international forest assessments (such as the global Forest Resources Assessment (FRA) of the Food and Agriculture Organization, FAO) and the national greenhouse gas inventories reported to the UN Framework Convention on Climate Change (UNFCCC) using methods of the Intergovernmental Panel on Climate Change (IPCC).","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/0bb667ff-7d90-4708-a3b9-d5c25c59208d","harvest_record_raw":"https://catalog.data.gov/harvest_record/0bb667ff-7d90-4708-a3b9-d5c25c59208d/raw","has_download":false,"has_spatial":true,"identifier":"C1220567933-USGS_LTA","keyword":["agriculture","biosphere","earth-science","forest-science","habitat-conversion-fragmentation","human-dimensions","terrestrial-ecosystems","vegetation"],"last_harvested_date":"2026-09-23T01:25:30.688849","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":0,"publisher":"DOI/USGS/EROS","slug":"global-forest-observations-initiative-gfoi-fiji","spatial_centroid":null,"spatial_shape":null,"theme":["CWIC","geospatial"],"title":"Global Forest Observations Initiative (GFOI) - Fiji","type":"dataset"},{"_score":13.595976,"_sort":[1790126658623,13.595976,3,"e88fe799-ff7f-467a-8a5f-b0f861b47fa6"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"DR. PAUL STACKHOUSE","hasEmail":"mailto:paul.w.stackhouse@nasa.gov"},"description":"FLASH_SSF_NOAA20-FM6-VIIRS_Version1A data are near real-time CERES observed TOA fluxes, clouds, and parameterized surface fluxes, not officially calibrated. The Fast Longwave and SHortwave Flux (FLASHFlux) data are a product line of the Clouds and the Earth's Radiant Energy Systems (CERES) project designed for processing and release of top-of-atmosphere (TOA) and surface radiative fluxes within one week of CERES instrument measurement. The FLASHFlux data product is a rapid-release product based on the algorithms developed for and data collected by the CERES project. CERES is currently producing world-class climate data products derived from measurements taken aboard NASA's Terra and Aqua spacecraft. While of exceptional fidelity, these data products require considerable processing time to assure quality, verify accuracy, and assess precision. The result is that CERES data are typically released up to six months after acquiring the initial measurements. Such delays are of little consequence for climate studies, especially considering the improved quality of the released data products. Thus, FLASHFlux products are not intended to achieve climate quality.FLASHFlux data products were envisioned as a resource whereby CERES data could be provided to the community within a week of the initial measurements, with some calibration accuracy requirements relaxed to gain speed. The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Fast Longwave And SHortwave Fluxes (FLASHFlux) data for a single Clouds and the Earth's Radiant Energy Systems (CERES) scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as the Visible Infrared Imaging Radiometer Suite (VIIRS) on the NOAA-20 satellite and meteorological and ozone information from The Goddard Earth Observing System GEOS-5 FP-IT Atmospheric Data Assimilation System (GEOS-5 ADAS). Scene identification and cloud properties are defined at the higher imager resolution, and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains Top-of-Atmosphere fluxes in SW, LW, and incoming NET, surface fluxes using the Langley parameterized shortwave and longwave algorithms, and cloud information.CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES mission is a follow-up to the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument (PFM) was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the EOS flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board EOS Aqua on May 4, 2002. CERES instrument Flight Model 5 (FM5) was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The latest CERES instrument (FM6) was launched on board NOAA-20 on November 18, 2017.","distribution":[{"@type":"dcat:Distribution","description":"CERES Data Products Browse, Subset, and Order: Fast Longwave and Shortwave Flux (FLASHFlux)","downloadURL":"https://ceres.larc.nasa.gov/data/#fast-longwave-and-shortwave-flux-flashflux","format":"HTML","mediaType":"text/html","title":"Subset this dataset using a web based subsetter"},{"@type":"dcat:Distribution","description":"CERES Project Landing Page","downloadURL":"https://ceres.larc.nasa.gov/","format":"HTML","mediaType":"text/html","title":"The dataset's project home page"},{"@type":"dcat:Distribution","description":"Earthdata Search for FLASH_SSF_NOAA20-FM6-VIIRS_Version1A (NASA Application to search, discover, visualize, refine, and access NASA Earth Observation data)","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2569832691-LARC_ASDC","format":"HTML","mediaType":"text/html","title":"Download this dataset through Earthdata Search"},{"@type":"dcat:Distribution","description":"Mission Logo","downloadURL":"https://asdc.larc.nasa.gov/static/images/project_logos/ceres.png","format":"PNG","mediaType":"image/png","title":"Get a related visualization through WORLDVIEW"},{"@type":"dcat:Distribution","description":"OPeNDAP data access for FLASH_SSF_NOAA20-FM6-VIIRS_Version1A","downloadURL":"https://opendap.larc.nasa.gov/opendap/CERES/FLASH/SSF/NOAA20-FM6-VIIRS_Version1A/contents.html","format":"HTML","mediaType":"text/html","title":"Use OPeNDAP to access the dataset's data"}],"identifier":"C2569832691-LARC_ASDC","issued":"2022-12-13","keyword":["atmosphere","atmospheric-radiation","atmospheric-temperature","atmospheric-water-vapor","clouds","earth-science","land-surface","surface-radiative-properties"],"landingPage":"https://cmr.earthdata.nasa.gov:443/search/concepts/C2569832691-LARC_ASDC.html","language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"<?xml version=\"1.0\" encoding=\"UTF-8\"?><gml:Polygon xmlns:gml=\"http://www.opengis.net/gml/3.2\" srsName=\"EPSG:9825\"><gml:outerBoundaryIs><gml:LinearRing><gml:posList>-90.0 -180.0 -90.0 180.0 90.0 180.0 90.0 -180.0 -90.0 -180.0</gml:posList></gml:LinearRing></gml:outerBoundaryIs><gml:innerBoundaryIs></gml:innerBoundaryIs></gml:Polygon>","temporal":"2021-12-21T00:00:00Z/2024-04-08T00:00:00Z","theme":["FLASHFLUX","geospatial"],"title":"Fast Longwave And SHortwave Fluxes (FLASHflux) Clouds and Radiative Swath (SSF) data in netCDF"},"description":"FLASH_SSF_NOAA20-FM6-VIIRS_Version1A data are near real-time CERES observed TOA fluxes, clouds, and parameterized surface fluxes, not officially calibrated. The Fast Longwave and SHortwave Flux (FLASHFlux) data are a product line of the Clouds and the Earth's Radiant Energy Systems (CERES) project designed for processing and release of top-of-atmosphere (TOA) and surface radiative fluxes within one week of CERES instrument measurement. The FLASHFlux data product is a rapid-release product based on the algorithms developed for and data collected by the CERES project. CERES is currently producing world-class climate data products derived from measurements taken aboard NASA's Terra and Aqua spacecraft. While of exceptional fidelity, these data products require considerable processing time to assure quality, verify accuracy, and assess precision. The result is that CERES data are typically released up to six months after acquiring the initial measurements. Such delays are of little consequence for climate studies, especially considering the improved quality of the released data products. Thus, FLASHFlux products are not intended to achieve climate quality.FLASHFlux data products were envisioned as a resource whereby CERES data could be provided to the community within a week of the initial measurements, with some calibration accuracy requirements relaxed to gain speed. The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Fast Longwave And SHortwave Fluxes (FLASHFlux) data for a single Clouds and the Earth's Radiant Energy Systems (CERES) scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as the Visible Infrared Imaging Radiometer Suite (VIIRS) on the NOAA-20 satellite and meteorological and ozone information from The Goddard Earth Observing System GEOS-5 FP-IT Atmospheric Data Assimilation System (GEOS-5 ADAS). Scene identification and cloud properties are defined at the higher imager resolution, and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains Top-of-Atmosphere fluxes in SW, LW, and incoming NET, surface fluxes using the Langley parameterized shortwave and longwave algorithms, and cloud information.CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES mission is a follow-up to the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument (PFM) was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the EOS flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board EOS Aqua on May 4, 2002. CERES instrument Flight Model 5 (FM5) was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The latest CERES instrument (FM6) was launched on board NOAA-20 on November 18, 2017.","distribution_titles":["Subset this dataset using a web based subsetter","The dataset's project home page","Download this dataset through Earthdata Search","Get a related visualization through WORLDVIEW","Use OPeNDAP to access the dataset's data"],"harvest_record":"https://catalog.data.gov/harvest_record/75b2fd01-2b41-4f90-8376-3627c7671734","harvest_record_raw":"https://catalog.data.gov/harvest_record/75b2fd01-2b41-4f90-8376-3627c7671734/raw","has_download":true,"has_spatial":true,"identifier":"C2569832691-LARC_ASDC","keyword":["atmosphere","atmospheric-radiation","atmospheric-temperature","atmospheric-water-vapor","clouds","earth-science","land-surface","surface-radiative-properties"],"last_harvested_date":"2026-09-23T01:24:18.623764","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":3,"publisher":"NASA/LARC/SD/ASDC","slug":"fast-longwave-and-shortwave-fluxes-flashflux-clouds-and-radiative-swath-ssf-data-in-netcdf","spatial_centroid":null,"spatial_shape":null,"theme":["FLASHFLUX","geospatial"],"title":"Fast Longwave And SHortwave Fluxes (FLASHflux) Clouds and Radiative Swath (SSF) data in netCDF","type":"dataset"},{"_score":14.374138,"_sort":[1790126631660,14.374138,1,"4ca5cb5d-16d0-47d6-b78c-b33d105baa3d"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"undefined","hasEmail":"mailto:metadata@ciesin.columbia.edu"},"description":"The Anthropogenic Biomes of the World, Version 2: 1700 data set describes anthropogenic transformations within the terrestrial biosphere caused by sustained direct human interaction with ecosystems, including agriculture and urbanization circa 1700. Potential natural vegetation biomes, such as tropical rainforests or grasslands, are based on global vegetation patterns related to climate and geology. Anthropogenic transformation within each biome is approximated using population density, agricultural intensity (cropland and pasture) and urbanization. This data set is part of a time series for the years 1700, 1800, 1900, and 2000 that provides global patterns of historical transformation of the terrestrial biosphere during the Industrial Revolution.","distribution":[{"@type":"dcat:Distribution","description":"Data Download Page","downloadURL":"https://sedac.ciesin.columbia.edu/data/set/anthromes-anthropogenic-biomes-world-v2-1700/data-download","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Sample browse graphic of the data set.","downloadURL":"https://sedac.ciesin.columbia.edu/downloads/maps/anthromes/anthromes-anthropogenic-biomes-world-v2-1700/anthromes-v2-1700-global-thumbnail.jpg","format":"JPEG","mediaType":"image/jpeg","title":"Get a related visualization"},{"@type":"dcat:Distribution","description":"Search results for publications that cite this dataset by its DOI.","downloadURL":"https://scholar.google.com/scholar?q=10.7927%2FH4SF2T3M","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"},{"@type":"dcat:Distribution","description":"Web Map Service Page","downloadURL":"https://sedac.ciesin.columbia.edu/data/set/anthromes-anthropogenic-biomes-world-v2-1700/maps/services","format":"HTML","mediaType":"text/html","title":"Use Web Map Service (WMS) to download the dataset's data"}],"identifier":"C1000000280-SEDAC","issued":"2014-04-14","keyword":["biosphere","earth-science","ecosystems"],"language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"SEDAC"},"references":["https://doi.org/10.7927/H4D798B9","https://doi.org/10.7927/H4H12ZXD","https://doi.org/10.7927/H4J1012K","https://doi.org/10.7927/H4NP22C8"],"spatial":"-180.0 -90.0 180.0 90.0","temporal":"1700-01-01T00:00:00Z/1700-12-31T00:00:00Z","theme":["ANTHROMES","geospatial"],"title":"Anthropogenic Biomes of the World, Version 2: 1700"},"description":"The Anthropogenic Biomes of the World, Version 2: 1700 data set describes anthropogenic transformations within the terrestrial biosphere caused by sustained direct human interaction with ecosystems, including agriculture and urbanization circa 1700. Potential natural vegetation biomes, such as tropical rainforests or grasslands, are based on global vegetation patterns related to climate and geology. Anthropogenic transformation within each biome is approximated using population density, agricultural intensity (cropland and pasture) and urbanization. This data set is part of a time series for the years 1700, 1800, 1900, and 2000 that provides global patterns of historical transformation of the terrestrial biosphere during the Industrial Revolution.","distribution_titles":["Download this dataset","Get a related visualization","Google Scholar search results","Use Web Map Service (WMS) to download the dataset's data"],"harvest_record":"https://catalog.data.gov/harvest_record/a6f904ea-ef45-40b6-9507-5cb4f062cef6","harvest_record_raw":"https://catalog.data.gov/harvest_record/a6f904ea-ef45-40b6-9507-5cb4f062cef6/raw","has_download":true,"has_spatial":true,"identifier":"C1000000280-SEDAC","keyword":["biosphere","earth-science","ecosystems"],"last_harvested_date":"2026-09-23T01:23:51.660804","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"SEDAC","slug":"anthropogenic-biomes-of-the-world-version-2-1700","spatial_centroid":null,"spatial_shape":null,"theme":["ANTHROMES","geospatial"],"title":"Anthropogenic Biomes of the World, Version 2: 1700","type":"dataset"},{"_score":18.582897,"_sort":[1790126451221,18.582897,3,"5b226a7f-facb-4271-9a3b-0357c5f15656"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Thomas Morgan","hasEmail":"mailto:thomas.h.morgan@nasa.gov"},"description":"The Global Forest Observations Initiative (GFOI) is an initiative of the inter-governmental Group on Earth Observations (GEO) that aims to:\n\nfoster the sustained availability of observations for national forest monitoring systems; support governments that are establishing national systems by providing a platform for coordinating observations, providing assistance and guidance on utilizing observations, developing accepted methods and protocols, and promoting ongoing research and development; and work with national governments that report into international forest assessments (such as the global Forest Resources Assessment (FRA) of the Food and Agriculture Organization, FAO) and the national greenhouse gas inventories reported to the UN Framework Convention on Climate Change (UNFCCC) using methods of the Intergovernmental Panel on Climate Change (IPCC).","identifier":"C1220567235-USGS_LTA","issued":"1972-10-31","keyword":["agriculture","biosphere","earth-science","forest-science","habitat-conversion-fragmentation","human-dimensions","terrestrial-ecosystems","vegetation"],"landingPage":"https://cmr.earthdata.nasa.gov:443/search/concepts/C1220567235-USGS_LTA.html","language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"DOI/USGS/EROS"},"spatial":"6.31 0.46 17.86 14.17","temporal":"1972-10-31T00:00:00Z/2022-01-17T00:00:00Z","theme":["CWIC","geospatial"],"title":"USGS Global Forest Observations Initiative (GFOI) Cameroon"},"description":"The Global Forest Observations Initiative (GFOI) is an initiative of the inter-governmental Group on Earth Observations (GEO) that aims to:\n\nfoster the sustained availability of observations for national forest monitoring systems; support governments that are establishing national systems by providing a platform for coordinating observations, providing assistance and guidance on utilizing observations, developing accepted methods and protocols, and promoting ongoing research and development; and work with national governments that report into international forest assessments (such as the global Forest Resources Assessment (FRA) of the Food and Agriculture Organization, FAO) and the national greenhouse gas inventories reported to the UN Framework Convention on Climate Change (UNFCCC) using methods of the Intergovernmental Panel on Climate Change (IPCC).","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/794ef750-e155-4466-a16c-775be39f27e1","harvest_record_raw":"https://catalog.data.gov/harvest_record/794ef750-e155-4466-a16c-775be39f27e1/raw","has_download":false,"has_spatial":true,"identifier":"C1220567235-USGS_LTA","keyword":["agriculture","biosphere","earth-science","forest-science","habitat-conversion-fragmentation","human-dimensions","terrestrial-ecosystems","vegetation"],"last_harvested_date":"2026-09-23T01:20:51.221262","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":3,"publisher":"DOI/USGS/EROS","slug":"usgs-global-forest-observations-initiative-gfoi-cameroon","spatial_centroid":null,"spatial_shape":null,"theme":["CWIC","geospatial"],"title":"USGS Global Forest Observations Initiative (GFOI) Cameroon","type":"dataset"},{"_score":44.87847,"_sort":[1790126349362,44.87847,1,"6a49b410-5383-4c1a-9d93-815f77b5f50b"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Thomas Morgan","hasEmail":"mailto:thomas.h.morgan@nasa.gov"},"description":"The objective of this work includes the coastal scenario, risks and development of coastal paleoclimatology through landscape mapping; by highlighting the devastating climate change impacts that might result in tsunami in South-East Asian sea basin with short or no-awareness period; despite the facts that the Southeast Asia region is generally poor being encompassed by twelve countries along with the Indian and Pacific Oceans. Special payable concern to the Bay of Bengal has been paid that can dictate region\u2019s climate to certain extent. The ecosystems\u2019 impact due to climate change and global warming -can bring direct variables and affects in \u2013salinity, temperature, river flow, runoff, soil characteristics, erosion, nutrition level and water quality. The landscape mapping can address the system infrastructure requirements to the SEAR\u2019s sea basin attainable by the annual monsoons, the Southwest and the Northeast Monsoons. How recent meteorological and geodynamic-genetic events can result in adverse economical damages and significant losses of lives are also drawn. This work monitors on Sea-level rise gets projected under global warming. The most brainstorming findings from climate change issues are how the high latitudes for SEAR Sea Basins\u2019 are likely to experience greater warming than the global mean and warming,- And how the hydrological cycle gets found responsible for bringing more floods and more droughts in- causing huge devastating changes for environmental factors in coastal zones","identifier":"DASHLINK_720","issued":"2013-05-08","keyword":["ames","dashlink","nasa"],"landingPage":"https://c3.nasa.gov/dashlink/resources/720/","modified":"2025-07-17","programCode":["026:029"],"publisher":{"@type":"org:Organization","name":"Dashlink"},"title":"South-East Asian Region (SEAR): Sea Basin Landscape Mapping for Paleoclimatology & Recent Climate Change Impacts"},"description":"The objective of this work includes the coastal scenario, risks and development of coastal paleoclimatology through landscape mapping; by highlighting the devastating climate change impacts that might result in tsunami in South-East Asian sea basin with short or no-awareness period; despite the facts that the Southeast Asia region is generally poor being encompassed by twelve countries along with the Indian and Pacific Oceans. Special payable concern to the Bay of Bengal has been paid that can dictate region\u2019s climate to certain extent. The ecosystems\u2019 impact due to climate change and global warming -can bring direct variables and affects in \u2013salinity, temperature, river flow, runoff, soil characteristics, erosion, nutrition level and water quality. The landscape mapping can address the system infrastructure requirements to the SEAR\u2019s sea basin attainable by the annual monsoons, the Southwest and the Northeast Monsoons. How recent meteorological and geodynamic-genetic events can result in adverse economical damages and significant losses of lives are also drawn. This work monitors on Sea-level rise gets projected under global warming. The most brainstorming findings from climate change issues are how the high latitudes for SEAR Sea Basins\u2019 are likely to experience greater warming than the global mean and warming,- And how the hydrological cycle gets found responsible for bringing more floods and more droughts in- causing huge devastating changes for environmental factors in coastal zones","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/b899fd32-1c7f-46e5-9025-8119a71856ac","harvest_record_raw":"https://catalog.data.gov/harvest_record/b899fd32-1c7f-46e5-9025-8119a71856ac/raw","has_download":false,"has_spatial":false,"identifier":"DASHLINK_720","keyword":["ames","dashlink","nasa"],"last_harvested_date":"2026-09-23T01:19:09.362239","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"Dashlink","slug":"south-east-asian-region-sear-sea-basin-landscape-mapping-for-paleoclimatology-recent-clima","spatial_centroid":null,"spatial_shape":null,"theme":[],"title":"South-East Asian Region (SEAR): Sea Basin Landscape Mapping for Paleoclimatology & Recent Climate Change Impacts","type":"dataset"},{"_score":47.10308,"_sort":[1790126305193,47.10308,7,"4ddd6b8f-568e-4541-9540-7f348aa86bec"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Thomas Morgan","hasEmail":"mailto:thomas.h.morgan@nasa.gov"},"description":"The Trends in Global Freshwater Availability from the Gravity Recovery and Climate Experiment (GRACE), 2002-2016, is a global gridded data set at a spatial resolution of 0.5 degrees that presents trends (rate of change measured in centimeters per year) in freshwater availability based on data obtained from 2002 to 2016 by NASA GRACE. Terrestrial water availability storage is the sum of groundwater, soil moisture, snow and ice, surface waters, and wet biomass, expressed as an equivalent height of water. GRACE measures changes in the terrestrial water cycle by assessing small changes in Earth's gravity field. This observation-based assessment of how the world's water cycle is responding to human impacts and climate variations provides an important tool for evaluating and predicting emerging threats to water and food security.","identifier":"C1617586061-SEDAC","issued":"2019-05-22","keyword":["earth-science","ground-water","snow-ice","surface-water","terrestrial-hydrosphere"],"language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"SEDAC"},"references":["https://doi.org/10.7927/h4q23xbz"],"spatial":"-180.0 -90.0 180.0 90.0","temporal":"2002-01-01T00:00:00Z/2016-12-31T00:00:00Z","theme":["SDEI","geospatial"],"title":"Trends in Global Freshwater Availability from the Gravity Recovery and Climate Experiment (GRACE)"},"description":"The Trends in Global Freshwater Availability from the Gravity Recovery and Climate Experiment (GRACE), 2002-2016, is a global gridded data set at a spatial resolution of 0.5 degrees that presents trends (rate of change measured in centimeters per year) in freshwater availability based on data obtained from 2002 to 2016 by NASA GRACE. Terrestrial water availability storage is the sum of groundwater, soil moisture, snow and ice, surface waters, and wet biomass, expressed as an equivalent height of water. GRACE measures changes in the terrestrial water cycle by assessing small changes in Earth's gravity field. This observation-based assessment of how the world's water cycle is responding to human impacts and climate variations provides an important tool for evaluating and predicting emerging threats to water and food security.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/71a1e562-5275-4810-ae1f-3d9465754214","harvest_record_raw":"https://catalog.data.gov/harvest_record/71a1e562-5275-4810-ae1f-3d9465754214/raw","has_download":false,"has_spatial":true,"identifier":"C1617586061-SEDAC","keyword":["earth-science","ground-water","snow-ice","surface-water","terrestrial-hydrosphere"],"last_harvested_date":"2026-09-23T01:18:25.193287","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":7,"publisher":"SEDAC","slug":"trends-in-global-freshwater-availability-from-the-gravity-recovery-and-climate-experiment-","spatial_centroid":null,"spatial_shape":null,"theme":["SDEI","geospatial"],"title":"Trends in Global Freshwater Availability from the Gravity Recovery and Climate Experiment (GRACE)","type":"dataset"},{"_score":10.217232,"_sort":[1790125857618,10.217232,1,"491783b8-72d9-4482-b578-56a0051426c1"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"undefined","hasEmail":"mailto:uso@daac.ornl.gov"},"description":"This dataset provides annual maps of the snowoff (SO) date from 1988-2018 across Alaska and parts of Far East Russia and northwest Canada at a resolution of 6.25 km. SO date is defined as the last day of persistent snow and was derived from the MEaSUREs Calibrated Enhanced-Resolution Passive Microwave (PMW) EASE-Grid Brightness Temperature (Tb) Earth System Data Record (ESDR) product. The spatial domain was intended to match MODIS Alaska Snow Metrics and extend its temporal fidelity beyond the MODIS era. SO date estimates were compared to snow depth measurements collected at SNOTEL stations across Alaska and to three SO datasets derived from MODIS, Landsat, and the Interactive Multisensor Snow and Ice Mapping System (IMS). The data from 1988-2016 included a coastal mask removing coastal pixels due to potential water contamination from coarse brightness temperature observations (Dersken et al., 2012). There is not a coastal mask for the 2017-2018 data. The full data are included, and data users should be aware that coastal values can be adversely affected by adjacent water bodies.","distribution":[{"@type":"dcat:Distribution","description":"ABoVE project site","downloadURL":"https://above.nasa.gov","format":"HTML","mediaType":"text/html","title":"The dataset's project home page"},{"@type":"dcat:Distribution","description":"ABoVE: Passive Microwave-derived Annual Snowoff Date Maps, 1988-2018: Passive_Microwave_Snowoff_Data.pdf","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/public/above/Passive_Microwave_Snowoff_Data/comp/Passive_Microwave_Snowoff_Data.pdf","format":"PDF","mediaType":"application/pdf","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"Data set Landing Page DOI URL","downloadURL":"https://doi.org/10.3334/ORNLDAAC/1711","format":"HTML","mediaType":"text/html","title":"This dataset's landing page"},{"@type":"dcat:Distribution","description":"ORNL DAAC Data Set Documentation","downloadURL":"https://daac.ornl.gov/ABOVE/guides/Passive_Microwave_Snowoff_Data.html","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"Search results for publications that cite this dataset by its DOI.","downloadURL":"https://scholar.google.com/scholar?q=10.3334%2FORNLDAAC%2F1711","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"},{"@type":"dcat:Distribution","description":"Summary statistics for the snowoff date from 1988-2016 across the study domain: mean (left), standard deviation (middle), and coefficient of variation (right). Dates expressed as day of year (DOY).","downloadURL":"https://daac.ornl.gov/ABOVE/guides/Passive_Microwave_Snowoff_Data_Fig1.png","format":"PNG","mediaType":"image/png","title":"Get a related visualization"}],"identifier":"C2221862177-ORNL_CLOUD","issued":"2022-02-21","keyword":["climate-indicators","cryosphere","cryospheric-indicators","earth-science","snow-ice","terrestrial-hydrosphere"],"landingPage":"https://doi.org/10.3334/ORNLDAAC/1711","language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"ORNL_DAAC"},"spatial":"-180.0 37.98 180.0 90.0","temporal":"1988-01-01T00:00:00Z/2018-12-31T23:59:59Z","theme":["ABoVE","geospatial"],"title":"ABoVE: Passive Microwave-derived Annual Snowoff Date Maps, 1988-2018"},"description":"This dataset provides annual maps of the snowoff (SO) date from 1988-2018 across Alaska and parts of Far East Russia and northwest Canada at a resolution of 6.25 km. SO date is defined as the last day of persistent snow and was derived from the MEaSUREs Calibrated Enhanced-Resolution Passive Microwave (PMW) EASE-Grid Brightness Temperature (Tb) Earth System Data Record (ESDR) product. The spatial domain was intended to match MODIS Alaska Snow Metrics and extend its temporal fidelity beyond the MODIS era. SO date estimates were compared to snow depth measurements collected at SNOTEL stations across Alaska and to three SO datasets derived from MODIS, Landsat, and the Interactive Multisensor Snow and Ice Mapping System (IMS). The data from 1988-2016 included a coastal mask removing coastal pixels due to potential water contamination from coarse brightness temperature observations (Dersken et al., 2012). There is not a coastal mask for the 2017-2018 data. The full data are included, and data users should be aware that coastal values can be adversely affected by adjacent water bodies.","distribution_titles":["The dataset's project home page","View documentation related to this dataset","This dataset's landing page","View documentation related to this dataset","Google Scholar search results","Get a related visualization"],"harvest_record":"https://catalog.data.gov/harvest_record/c3fe8c80-87e1-4c7a-8ded-dd40054e5d80","harvest_record_raw":"https://catalog.data.gov/harvest_record/c3fe8c80-87e1-4c7a-8ded-dd40054e5d80/raw","has_download":true,"has_spatial":true,"identifier":"C2221862177-ORNL_CLOUD","keyword":["climate-indicators","cryosphere","cryospheric-indicators","earth-science","snow-ice","terrestrial-hydrosphere"],"last_harvested_date":"2026-09-23T01:10:57.618680","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"ORNL_DAAC","slug":"above-passive-microwave-derived-annual-snowoff-date-maps-1988-2018-a2ab7","spatial_centroid":null,"spatial_shape":null,"theme":["ABoVE","geospatial"],"title":"ABoVE: Passive Microwave-derived Annual Snowoff Date Maps, 1988-2018","type":"dataset"},{"_score":8.458166,"_sort":[1790125711136,8.458166,1,"ba81a21b-a06b-4103-ac10-0d48e4d9e9c6"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data (ACEPOL_AircraftRemoteSensing_CPL_Data) are remotely sensed measurements collected by the Cloud Physics Lidar (CPL) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA\u2019s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3880543402-LARC_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://airbornescience.nasa.gov/acepwg/content/ACE_Polarimeter_Working_Group_ACEPWG_ACEPOL_field_campaign","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/citing-data","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/project/ACEPOL/pdocuments","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/soot/power-user/ACEPOL/2017","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3880543402-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/SUBORBITAL/ACEPOL2017/AircraftRemoteSensing_CPL_Data_1","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://gmao.gsfc.nasa.gov/field-campaigns/past-campaigns/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3880543402-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www-air.larc.nasa.gov/missions/acepol/index.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://www.nwo.nl/en/projects/alw-go16-09/","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/SUBORBITAL/ACEPOL2017/AircraftRemoteSensing_CPL_Data_1","keyword":["earth-science-aerosols-atmosphere","earth-science-aerosols-atmosphere-aerosol-backscatter","earth-science-aerosols-atmosphere-aerosol-extinction","earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness","earth-science-clouds-atmosphere","earth-science-clouds-atmosphere-cloud-microphysics","earth-science-clouds-atmosphere-cloud-properties","earth-science-clouds-atmosphere-cloud-radiative-transfer"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -130, \"EastBoundingCoordinate\": -100, \"SouthBoundingCoordinate\": 25, \"NorthBoundingCoordinate\": 45}]], Maximum Altitude, 9999.9 Meters","temporal":"2017-10-19/2017-11-09","theme":["Earth Science"],"title":"ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data Version 1"},"description":"ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data (ACEPOL_AircraftRemoteSensing_CPL_Data) are remotely sensed measurements collected by the Cloud Physics Lidar (CPL) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA\u2019s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/2917c125-b6f8-45be-993d-a663c6190ac1","harvest_record_raw":"https://catalog.data.gov/harvest_record/2917c125-b6f8-45be-993d-a663c6190ac1/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/SUBORBITAL/ACEPOL2017/AircraftRemoteSensing_CPL_Data_1","keyword":["earth-science-aerosols-atmosphere","earth-science-aerosols-atmosphere-aerosol-backscatter","earth-science-aerosols-atmosphere-aerosol-extinction","earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness","earth-science-clouds-atmosphere","earth-science-clouds-atmosphere-cloud-microphysics","earth-science-clouds-atmosphere-cloud-properties","earth-science-clouds-atmosphere-cloud-radiative-transfer"],"last_harvested_date":"2026-09-23T01:08:31.136280","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/LARC/SD/ASDC","slug":"acepol-cloud-physics-lidar-cpl-remotely-sensed-data-version-1","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data Version 1","type":"dataset"},{"_score":8.793062,"_sort":[1790125710786,8.793062,1,"980e5d30-6f90-451a-a1e9-b68b1c2d615f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"ACEPOL_MetNav_AircraftInSitu_Data are in situ meteorological and navigational measurements collected onboard the ER-2 during the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA\u2019s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3880543606-LARC_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://airbornescience.nasa.gov/acepwg/content/ACE_Polarimeter_Working_Group_ACEPWG_ACEPOL_field_campaign","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/citing-data","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/project/ACEPOL/pdocuments","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/soot/power-user/ACEPOL/2017","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3880543606-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/SUBORBITAL/ACEPOL2017/MetNav_AircraftInSitu_Data_1","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://gmao.gsfc.nasa.gov/field-campaigns/past-campaigns/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3880543606-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www-air.larc.nasa.gov/missions/acepol/index.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://www.nwo.nl/en/projects/alw-go16-09/","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/SUBORBITAL/ACEPOL2017/MetNav_AircraftInSitu_Data_1","keyword":["earth-science-altitude-atmosphere","earth-science-atmospheric-pressure-atmosphere","earth-science-atmospheric-pressure-atmosphere-static-pressure","earth-science-atmospheric-temperature-atmosphere","earth-science-atmospheric-water-vapor-atmosphere","earth-science-atmospheric-winds-atmosphere","earth-science-atmospheric-winds-atmosphere-upper-level-winds","earth-science-platform-characteristics-spectral-engineering"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -130, \"EastBoundingCoordinate\": -100, \"SouthBoundingCoordinate\": 25, \"NorthBoundingCoordinate\": 45}]], Maximum Altitude, 9999.9 Meters","temporal":"2017-10-19/2017-11-09","theme":["Earth Science"],"title":"ACEPOL ER-2 Meteorological and Navigational Data Version 1"},"description":"ACEPOL_MetNav_AircraftInSitu_Data are in situ meteorological and navigational measurements collected onboard the ER-2 during the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA\u2019s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/ce56ee87-0e8d-46fd-b9b6-27fe2a538f1c","harvest_record_raw":"https://catalog.data.gov/harvest_record/ce56ee87-0e8d-46fd-b9b6-27fe2a538f1c/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/SUBORBITAL/ACEPOL2017/MetNav_AircraftInSitu_Data_1","keyword":["earth-science-altitude-atmosphere","earth-science-atmospheric-pressure-atmosphere","earth-science-atmospheric-pressure-atmosphere-static-pressure","earth-science-atmospheric-temperature-atmosphere","earth-science-atmospheric-water-vapor-atmosphere","earth-science-atmospheric-winds-atmosphere","earth-science-atmospheric-winds-atmosphere-upper-level-winds","earth-science-platform-characteristics-spectral-engineering"],"last_harvested_date":"2026-09-23T01:08:30.786166","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/LARC/SD/ASDC","slug":"acepol-er-2-meteorological-and-navigational-data-version-1","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ACEPOL ER-2 Meteorological and Navigational Data Version 1","type":"dataset"},{"_score":12.396011,"_sort":[1790125709829,12.396011,1,"7a410a11-8742-4c70-8044-bb2a48ceeadc"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The MCD43D06 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the [MCD43D06 Version 6.1](https://doi.org/10.5067/MODIS/MCD43D06.061) data product.\n\nThe MCD43D06 Version 6 Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) Model Parameter dataset is produced daily using 16 days of Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data at 30 arc second (1,000 meter) resolution. Data are temporally weighted to the ninth day which is reflected in the Julian date in the file name. This Climate Modeling Grid (CMG) product covers the entire globe for use in climate simulation models. Due to the large file size, each MCD43D product contains just one data layer. Each of the three model parameters (isotropic, volumetric, and geometric) for each of the MODIS bands 1 through 7 and the visible, near-infrared (NIR), and shortwave bands included in [MCD43C1](https://doi.org/10.5067/MODIS/MCD43C1.006) are stored in a separate file as MCD43D01 through MCD43D30. \n\nMCD43D06 is the BRDF geometric parameter for MODIS band 2. The geometric parameter, in conjunction with the isotropic and volumetric parameters, is used to derive the BRDF/Albedo values for MODIS band 2. \n\nUsers are urged to use the band specific quality flags to isolate the highest quality full inversion results for their own science applications as described in the [User Guide](https://www.umb.edu/spectralmass/modis-user-guide-v006-and-v0061/mcd43d-cmg-30-arc-second-products/).\n\nKnown Issues\n* The incorrect representation of the aerosol quantities (low average high) [in the C6 MYD09 and MOD09 surface reflectance products](https://landweb.modaps.eosdis.nasa.gov/displayissue?id=86) may have impacted downstream products particularly over arid bright surfaces. This (and a few other issues) have been corrected for C6.1. Therefore users should avoid substantive use of the C6 MCD43 products and wait for the C6.1 products. In any event, users are always strongly encouraged to download and use the extensive QA data provided in MCD43A2, in addition to the briefer mandatory QAs provided as part of the MCD43A1, 3, and 4 products.\n* [Corrections](https://landweb.modaps.eosdis.nasa.gov/data/userguide/LSRHighAerosolFlagFinal.pdf) were implemented in Collection 6.1 reprocessing.\n* For complete information about MCD43D06 known issues refer to the [MODIS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&as=6).","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2763289547-LPCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/MODIS/MCD43D06.006","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ladsweb.modaps.eosdis.nasa.gov/filespec/MODIS/6/MCD43D06","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://landweb.modaps.eosdis.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/documents/97/MCD43_ATBD.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/centers/lp-daac","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.umb.edu/spectralmass/modis-user-guide-v006-and-v0061/mcd43d-cmg-30-arc-second-products/","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/MODIS/MCD43D06.006","keyword":["earth-science-surface-radiative-properties-land-surface-albedo","earth-science-surface-radiative-properties-land-surface-anisotropy","earth-science-surface-radiative-properties-land-surface-reflectance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"LP DAAC;NASA/GSFC/SED/ESD/TISL/MODAPS;UMASS-B/SFE"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90, \"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2000-02-16/2023-02-17","theme":["Earth Science"],"title":"MODIS/Terra+Aqua BRDF/Albedo Parameter3 Band2 Daily L3 Global 30ArcSec CMG V006"},"description":"The MCD43D06 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the [MCD43D06 Version 6.1](https://doi.org/10.5067/MODIS/MCD43D06.061) data product.\n\nThe MCD43D06 Version 6 Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) Model Parameter dataset is produced daily using 16 days of Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data at 30 arc second (1,000 meter) resolution. Data are temporally weighted to the ninth day which is reflected in the Julian date in the file name. This Climate Modeling Grid (CMG) product covers the entire globe for use in climate simulation models. Due to the large file size, each MCD43D product contains just one data layer. Each of the three model parameters (isotropic, volumetric, and geometric) for each of the MODIS bands 1 through 7 and the visible, near-infrared (NIR), and shortwave bands included in [MCD43C1](https://doi.org/10.5067/MODIS/MCD43C1.006) are stored in a separate file as MCD43D01 through MCD43D30. \n\nMCD43D06 is the BRDF geometric parameter for MODIS band 2. The geometric parameter, in conjunction with the isotropic and volumetric parameters, is used to derive the BRDF/Albedo values for MODIS band 2. \n\nUsers are urged to use the band specific quality flags to isolate the highest quality full inversion results for their own science applications as described in the [User Guide](https://www.umb.edu/spectralmass/modis-user-guide-v006-and-v0061/mcd43d-cmg-30-arc-second-products/).\n\nKnown Issues\n* The incorrect representation of the aerosol quantities (low average high) [in the C6 MYD09 and MOD09 surface reflectance products](https://landweb.modaps.eosdis.nasa.gov/displayissue?id=86) may have impacted downstream products particularly over arid bright surfaces. This (and a few other issues) have been corrected for C6.1. Therefore users should avoid substantive use of the C6 MCD43 products and wait for the C6.1 products. In any event, users are always strongly encouraged to download and use the extensive QA data provided in MCD43A2, in addition to the briefer mandatory QAs provided as part of the MCD43A1, 3, and 4 products.\n* [Corrections](https://landweb.modaps.eosdis.nasa.gov/data/userguide/LSRHighAerosolFlagFinal.pdf) were implemented in Collection 6.1 reprocessing.\n* For complete information about MCD43D06 known issues refer to the [MODIS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&as=6).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/06097794-62e1-445f-85b6-1fa00fba218c","harvest_record_raw":"https://catalog.data.gov/harvest_record/06097794-62e1-445f-85b6-1fa00fba218c/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/MODIS/MCD43D06.006","keyword":["earth-science-surface-radiative-properties-land-surface-albedo","earth-science-surface-radiative-properties-land-surface-anisotropy","earth-science-surface-radiative-properties-land-surface-reflectance"],"last_harvested_date":"2026-09-23T01:08:29.829152","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"LP DAAC;NASA/GSFC/SED/ESD/TISL/MODAPS;UMASS-B/SFE","slug":"modis-terraaqua-brdf-albedo-parameter3-band2-daily-l3-global-30arcsec-cmg-v006","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"MODIS/Terra+Aqua BRDF/Albedo Parameter3 Band2 Daily L3 Global 30ArcSec CMG V006","type":"dataset"},{"_score":12.119004,"_sort":[1790125696339,12.119004,1,"c644d19e-0935-4962-9601-bd734dbed4d2"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The coastal marine system of the Gulf of Alaska (GoA) is connected hydrologically, biogeochemically and biologically with the upriver systems of the Copper River basin. Glacially weathered rock yields highly reactive particulate iron (Fe) into rivers that yields an important flux of bioavailable iron to the open ocean. North Pacific deep water is extremely nutrient-rich, and upwelling of deep water in estuaries and at river plumes results in very high biological productivity. The world-renowned fisheries in the vicinity of the Copper River region of the GoA thrive, in part, due to pristine riparian and lacustrine habitats for spawning and rearing. Pacific salmon spawn in the upper reaches of coastal watersheds, and their progeny spend a significant amount of time in freshwater habitats before migrating to the ocean. Prior to making the transition to a fully marine lifestyle, salmon smolts benefit from the enhanced biological productivity at plumes and within estuaries.The coastal GoA region is currently experiencing rapid and accelerating climate change as manifested by rapid recession of glaciers; climate models predict up to a 40% increase in river runoff from Alaska rivers by 2050. Over the coming decades an increase in glacier-dominated river discharge is likely, followed by decreases as glaciers recede. In addition, there will be a change in the seasonality of river discharge. Changes in freshwater discharge are likely to alter the flux of reactive particulate Fe, as well as dissolved organic and inorganic carbon (DIC and DOC) from glacier-dominated rivers, as well as the nitrate flux to surface water from estuarine upwelling, with cascading effects throughout the ecosystem. Furthermore, the freshwater supply of dissolved organic nitrogen (DON) and nitrate may increase over time due to recolonization of deglaciated watersheds by opportunistic nitrogen-fixing plants. New habitats for salmon and other members of the headwater ecosystem are likely to become available as glaciers retreat and as permafrost melts in the upper watershed. Conversely, decreased permafrost and decreased river flows may lead to the loss of habitat as freshwater sources dry seasonally or permanently. In addition, the positive or negative feedbacks to rising atmospheric CO2 concentrations, which are responsible for the warming and the subsequent melting of the glaciers, have not been addressed. As landscapes become ice free, the evolution of vegetation on these areas may act as net C sinks./The specific changes that will be manifested in the Copper River watershed and associated marine systems are difficult to predict and monitor. Using NASA products and a combination of remote sensing and field-based studies, this project seeks to establish a framework to document and monitor physical, biogeochemical biological changes in the coastal Gulf of Alaska adjacent to the Copper River.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1633360197-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://seabass.gsfc.nasa.gov/experiment/CRP/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1633360197-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/SeaBASS/CRP/DATA001","keyword":["earth-science-ocean-chemistry-oceans","earth-science-ocean-optics-oceans","earth-science-ocean-temperature-oceans","earth-science-salinity-density-oceans"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;NASA/GSFC/SED/ESD/GCDC/SeaBASS"},"spatial":"[\"CARTESIAN\", [{\"EastBoundingCoordinate\": 180.0, \"NorthBoundingCoordinate\": 90.0, \"SouthBoundingCoordinate\": -90.0, \"WestBoundingCoordinate\": -180.0}]]","temporal":"2010-03-27/2026-09-07","theme":["Earth Science"],"title":"Remote sensing and field-based studies in the coastal Gulf of Alaska adjacent to the Copper River"},"description":"The coastal marine system of the Gulf of Alaska (GoA) is connected hydrologically, biogeochemically and biologically with the upriver systems of the Copper River basin. Glacially weathered rock yields highly reactive particulate iron (Fe) into rivers that yields an important flux of bioavailable iron to the open ocean. North Pacific deep water is extremely nutrient-rich, and upwelling of deep water in estuaries and at river plumes results in very high biological productivity. The world-renowned fisheries in the vicinity of the Copper River region of the GoA thrive, in part, due to pristine riparian and lacustrine habitats for spawning and rearing. Pacific salmon spawn in the upper reaches of coastal watersheds, and their progeny spend a significant amount of time in freshwater habitats before migrating to the ocean. Prior to making the transition to a fully marine lifestyle, salmon smolts benefit from the enhanced biological productivity at plumes and within estuaries.The coastal GoA region is currently experiencing rapid and accelerating climate change as manifested by rapid recession of glaciers; climate models predict up to a 40% increase in river runoff from Alaska rivers by 2050. Over the coming decades an increase in glacier-dominated river discharge is likely, followed by decreases as glaciers recede. In addition, there will be a change in the seasonality of river discharge. Changes in freshwater discharge are likely to alter the flux of reactive particulate Fe, as well as dissolved organic and inorganic carbon (DIC and DOC) from glacier-dominated rivers, as well as the nitrate flux to surface water from estuarine upwelling, with cascading effects throughout the ecosystem. Furthermore, the freshwater supply of dissolved organic nitrogen (DON) and nitrate may increase over time due to recolonization of deglaciated watersheds by opportunistic nitrogen-fixing plants. New habitats for salmon and other members of the headwater ecosystem are likely to become available as glaciers retreat and as permafrost melts in the upper watershed. Conversely, decreased permafrost and decreased river flows may lead to the loss of habitat as freshwater sources dry seasonally or permanently. In addition, the positive or negative feedbacks to rising atmospheric CO2 concentrations, which are responsible for the warming and the subsequent melting of the glaciers, have not been addressed. As landscapes become ice free, the evolution of vegetation on these areas may act as net C sinks./The specific changes that will be manifested in the Copper River watershed and associated marine systems are difficult to predict and monitor. Using NASA products and a combination of remote sensing and field-based studies, this project seeks to establish a framework to document and monitor physical, biogeochemical biological changes in the coastal Gulf of Alaska adjacent to the Copper River.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/1892d794-7026-4658-97f9-d441ac2f1ea9","harvest_record_raw":"https://catalog.data.gov/harvest_record/1892d794-7026-4658-97f9-d441ac2f1ea9/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/SeaBASS/CRP/DATA001","keyword":["earth-science-ocean-chemistry-oceans","earth-science-ocean-optics-oceans","earth-science-ocean-temperature-oceans","earth-science-salinity-density-oceans"],"last_harvested_date":"2026-09-23T01:08:16.339706","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;NASA/GSFC/SED/ESD/GCDC/SeaBASS","slug":"remote-sensing-and-field-based-studies-in-the-coastal-gulf-of-alaska-adjacent-to-the-coppe","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Remote sensing and field-based studies in the coastal Gulf of Alaska adjacent to the Copper River","type":"dataset"},{"_score":17.75177,"_sort":[1790125694757,17.75177,1,"9eab9a49-35d6-4120-b1fd-7307c86a162d"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"AEROSE is an internationally recognized series of trans-Atlantic field campaigns conducted onboard the NOAA Ship Ronald H. Brown designed to explore African air mass outflows and their impacts on climate, weather, and environmental health.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2108358203-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://seabass.gsfc.nasa.gov/experiment/AEROSE/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2108358203-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/SeaBASS/AEROSE/DATA001","keyword":["earth-science-ocean-chemistry-oceans","earth-science-ocean-optics-oceans","earth-science-ocean-temperature-oceans","earth-science-salinity-density-oceans"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;NASA/GSFC/SED/ESD/GCDC/SeaBASS"},"spatial":"[\"CARTESIAN\", [{\"EastBoundingCoordinate\": 180.0, \"NorthBoundingCoordinate\": 90.0, \"SouthBoundingCoordinate\": -90.0, \"WestBoundingCoordinate\": -180.0}]]","temporal":"2004-03-02/2017-04-01","theme":["Earth Science"],"title":"Saharan Dust AERosols and Ocean Science Expeditions"},"description":"AEROSE is an internationally recognized series of trans-Atlantic field campaigns conducted onboard the NOAA Ship Ronald H. Brown designed to explore African air mass outflows and their impacts on climate, weather, and environmental health.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/cf4e0c0b-e5bf-4540-bde0-f2669755ce51","harvest_record_raw":"https://catalog.data.gov/harvest_record/cf4e0c0b-e5bf-4540-bde0-f2669755ce51/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/SeaBASS/AEROSE/DATA001","keyword":["earth-science-ocean-chemistry-oceans","earth-science-ocean-optics-oceans","earth-science-ocean-temperature-oceans","earth-science-salinity-density-oceans"],"last_harvested_date":"2026-09-23T01:08:14.757483","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;NASA/GSFC/SED/ESD/GCDC/SeaBASS","slug":"saharan-dust-aerosols-and-ocean-science-expeditions","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Saharan Dust AERosols and Ocean Science Expeditions","type":"dataset"},{"_score":12.46037,"_sort":[1790125683937,12.46037,1,"3c0a39ea-db09-4cd8-8f07-9cc8e8e06436"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this projects describes a multi-decadal Fundamental Climate Data Record (FCDR) of calibrated radiances as well as an Earth System Data Record (ESDR) of aerosol properties over the continents derived from a 32-year record of satellite near-UV observations by three sensors.  \n\nThe OMI/Aura Near UV (version 1) Aerosol Index, Optical Depth and Single Scattering Albedo data product consists of aerosol absorption optical depth, aerosol optical depth, aerosol single scattering albedo, cloud fraction, cloud optical depth, refractive index, radiance, reflectivity and residue at approximately 13x24km. This product also contains ancillary data for ocean corrected surface albedo and terrain pressure.\n\nThese Level-2 data are stored in the Hierarchical Data Format 5 (HDF5) and are available from the Goddard Earth Sciences (GES) Data and Information Services Center (DISC).","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1460503190-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/OMIAuraAER_1.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/OMIAuraAER_001.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://earthdata.nasa.gov/about/competitive-programs/measures","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://measures.gesdisc.eosdis.nasa.gov/data/AER/OMIAuraAER.1/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://measures.gesdisc.eosdis.nasa.gov/data/AER/OMIAuraAER.1/doc/README.MEaSUREs_Aerosols.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://measures.gesdisc.eosdis.nasa.gov/opendap/AER/OMIAuraAER.1","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1460503190-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/MEASURES/AER/DATA203","keyword":["earth-science-aerosols-atmosphere-aerosol-extinction","earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2004-10-01/2023-05-04","theme":["Earth Science"],"title":"OMI/Aura Near UV Aerosol Index, Optical Depth and Single Scattering Albedo 1-Orbit L2 13x24km"},"description":"As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this projects describes a multi-decadal Fundamental Climate Data Record (FCDR) of calibrated radiances as well as an Earth System Data Record (ESDR) of aerosol properties over the continents derived from a 32-year record of satellite near-UV observations by three sensors.  \n\nThe OMI/Aura Near UV (version 1) Aerosol Index, Optical Depth and Single Scattering Albedo data product consists of aerosol absorption optical depth, aerosol optical depth, aerosol single scattering albedo, cloud fraction, cloud optical depth, refractive index, radiance, reflectivity and residue at approximately 13x24km. This product also contains ancillary data for ocean corrected surface albedo and terrain pressure.\n\nThese Level-2 data are stored in the Hierarchical Data Format 5 (HDF5) and are available from the Goddard Earth Sciences (GES) Data and Information Services Center (DISC).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/4614ce0a-5330-4ba8-bfdb-628c763cf6ea","harvest_record_raw":"https://catalog.data.gov/harvest_record/4614ce0a-5330-4ba8-bfdb-628c763cf6ea/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/MEASURES/AER/DATA203","keyword":["earth-science-aerosols-atmosphere-aerosol-extinction","earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness"],"last_harvested_date":"2026-09-23T01:08:03.937835","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"omi-aura-near-uv-aerosol-index-optical-depth-and-single-scattering-albedo-1-orbit-l2-13x24","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"OMI/Aura Near UV Aerosol Index, Optical Depth and Single Scattering Albedo 1-Orbit L2 13x24km","type":"dataset"},{"_score":12.380676,"_sort":[1790125678199,12.380676,1,"6df084cb-0017-407b-bf70-0e1a523c59fb"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"SST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- bias_sst \u2014 Sea Surface Temperature bias (\u00b0C)\n- flags_sst \u2014 Product-specific flags, Sea Surface Temperature (integer bitmask)\n- l2_flags \u2014 Level-2 Processing Flags (integer bitmask; see bit definitions)\n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)\n- sst \u2014 Sea Surface Temperature (\u00b0C)\n- sstref \u2014 Sea Surface Temperature reference (\u00b0C)\n- stdv_sst \u2014 Sea Surface Temperature standard deviation (\u00b0C)","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1658475743-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://nasa.github.io/oceandata-notebooks/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/data/reprocessing/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/atbd/legacy/atbd-obdaac-long-wave-sea-surface-temperature.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/obdaac-ancillary-data-sources.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/directdataaccess/Level-2/SNPP-VIIRS/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1658475743-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/instruments/VIIRS","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/platforms/space-based-platforms/Suomi-NPP","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"/SDE/CMR_API/|C1658475743-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"NorthBoundingCoordinate\": 90, \"SouthBoundingCoordinate\": -90}]]","temporal":"2012-01-02/2026-09-07","theme":["Earth Science"],"title":"Suomi-NPP VIIRS Level-2 Regional  11\u00b5m Daytime Sea Surface Temperature (SST) Data, version 2016.2"},"description":"SST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- bias_sst \u2014 Sea Surface Temperature bias (\u00b0C)\n- flags_sst \u2014 Product-specific flags, Sea Surface Temperature (integer bitmask)\n- l2_flags \u2014 Level-2 Processing Flags (integer bitmask; see bit definitions)\n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)\n- sst \u2014 Sea Surface Temperature (\u00b0C)\n- sstref \u2014 Sea Surface Temperature reference (\u00b0C)\n- stdv_sst \u2014 Sea Surface Temperature standard deviation (\u00b0C)","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/d963035d-b000-42a6-bef6-7946eb90acda","harvest_record_raw":"https://catalog.data.gov/harvest_record/d963035d-b000-42a6-bef6-7946eb90acda/raw","has_download":true,"has_spatial":true,"identifier":"/SDE/CMR_API/|C1658475743-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:07:58.199196","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG","slug":"suomi-npp-viirs-level-regional-regional-11m-day-night-sea-surface-temperature-sst-data-ver-a2d97","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Suomi-NPP VIIRS Level-2 Regional  11\u00b5m Daytime Sea Surface Temperature (SST) Data, version 2016.2","type":"dataset"},{"_score":11.48639,"_sort":[1790125677876,11.48639,5,"c24dd0b4-ace6-4043-8206-c9464c5ec555"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this project entitled \u201cMulti-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS)\u201d will develop consistent long-term global trend-quality data records spanning the last two decades, over which remarkable changes in nitrogen oxides (NOx) emissions have occurred. The objective of the project Is to adapt Ozone Monitoring Instrument (OMI) operational algorithms to other satellite instruments and create consistent multi-satellite L2 and L3 nitrogen dioxide (NO2) columns and value-added L4 surface NO2 concentrations and NOx emissions data products, systematically accounting for instrumental differences. The instruments include Global Ozone Monitoring Experiment (GOME, 1996-2011), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY, 2002-2012), OMI (2004-present), GOME-2 (2007-present), and TROPOspheric Monitoring Instrument (TROPOMI, 2018-present). The quality assured L2-L4 products will be made available to the scientific community via the NASA GES DISC website in Climate and Forecast (CF)-compliant Hierarchical Data Format (HDF5) and netCDF formats.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2232479983-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://aura.gsfc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/OMI_MINDS_NO2G_1.1.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/OMI_MINDS_NO2G_1.1.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/MEaSUREs/MINDS/README.MEaSUREs_MINDS_NO2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://earthdata.nasa.gov/esds/competitive-programs/measures/minds","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://measures.gesdisc.eosdis.nasa.gov/data/MINDS/OMI_MINDS_NO2G.1.1/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://measures.gesdisc.eosdis.nasa.gov/opendap/MINDS/OMI_MINDS_NO2G.1.1/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2232479983-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/MEASURES/MINDS/DATA214","keyword":["earth-science-atmospheric-chemistry-atmosphere-nitrogen-compounds"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2004-10-01/2026-09-07","theme":["Earth Science"],"title":"OMI/Aura NO2 Tropospheric, Stratospheric & Total Columns MINDS Daily L2 Global Gridded 0.25 degree x 0.25 degree V1.1 (OMI_MINDS_NO2G)"},"description":"As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this project entitled \u201cMulti-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS)\u201d will develop consistent long-term global trend-quality data records spanning the last two decades, over which remarkable changes in nitrogen oxides (NOx) emissions have occurred. The objective of the project Is to adapt Ozone Monitoring Instrument (OMI) operational algorithms to other satellite instruments and create consistent multi-satellite L2 and L3 nitrogen dioxide (NO2) columns and value-added L4 surface NO2 concentrations and NOx emissions data products, systematically accounting for instrumental differences. The instruments include Global Ozone Monitoring Experiment (GOME, 1996-2011), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY, 2002-2012), OMI (2004-present), GOME-2 (2007-present), and TROPOspheric Monitoring Instrument (TROPOMI, 2018-present). The quality assured L2-L4 products will be made available to the scientific community via the NASA GES DISC website in Climate and Forecast (CF)-compliant Hierarchical Data Format (HDF5) and netCDF formats.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/c89d0413-99d6-4981-b7ce-5324f4d82e36","harvest_record_raw":"https://catalog.data.gov/harvest_record/c89d0413-99d6-4981-b7ce-5324f4d82e36/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/MEASURES/MINDS/DATA214","keyword":["earth-science-atmospheric-chemistry-atmosphere-nitrogen-compounds"],"last_harvested_date":"2026-09-23T01:07:57.876027","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":5,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"omi-aura-no2-tropospheric-stratospheric-total-columns-minds-daily-l2-global-gridded-0-25-d","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"OMI/Aura NO2 Tropospheric, Stratospheric & Total Columns MINDS Daily L2 Global Gridded 0.25 degree x 0.25 degree V1.1 (OMI_MINDS_NO2G)","type":"dataset"},{"_score":14.242385,"_sort":[1790125675918,14.242385,1,"2bc8f874-1e32-4b6e-8ba5-74abe9bcbabc"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"SST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- sst \u2014 Sea Surface Temperature (\u00b0C)\n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1658475760-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://nasa.github.io/oceandata-notebooks/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/data/reprocessing/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/atbd/legacy/atbd-obdaac-long-wave-sea-surface-temperature.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/obdaac-ancillary-data-sources.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/directdataaccess/Level-3%20Binned/SNPP-VIIRS/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1658475760-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/instruments/VIIRS","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/platforms/space-based-platforms/Suomi-NPP","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"/SDE/CMR_API/|C1658475760-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG"},"spatial":"[\"CARTESIAN\", [{\"SouthBoundingCoordinate\": -90, \"EastBoundingCoordinate\": 180, \"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90}]]","temporal":"2012-01-02/2026-09-07","theme":["Earth Science"],"title":"Suomi-NPP VIIRS Level-3 Global Binned 11\u00b5m Daytime Sea Surface Temperature (SST) Data, version 2016.2"},"description":"SST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- sst \u2014 Sea Surface Temperature (\u00b0C)\n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/8cf87209-58e3-49fb-9d05-7a5096ca97f6","harvest_record_raw":"https://catalog.data.gov/harvest_record/8cf87209-58e3-49fb-9d05-7a5096ca97f6/raw","has_download":true,"has_spatial":true,"identifier":"/SDE/CMR_API/|C1658475760-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:07:55.918844","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG","slug":"suomi-npp-viirs-level-3-global-binned-11m-daytime-sea-surface-temperature-sst-data-version-09f1a","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Suomi-NPP VIIRS Level-3 Global Binned 11\u00b5m Daytime Sea Surface Temperature (SST) Data, version 2016.2","type":"dataset"},{"_score":12.444707,"_sort":[1790125672681,12.444707,1,"5514db9c-8072-46f6-ad4a-a7afe2eef7d0"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Ocean Biology DAAC produces near real-time (NRT) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Near real-time products provide a snapshot of the data during a short time period within a single orbit. \n\nSST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- sst \u2014 Sea Surface Temperature (\u00b0C) \n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1658475773-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://nasa.github.io/oceandata-notebooks/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/data/reprocessing/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/atbd/legacy/atbd-obdaac-long-wave-sea-surface-temperature.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/obdaac-ancillary-data-sources.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/directdataaccess/Level-3%20Mapped/SNPP-VIIRS/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/opendap/VIIRS/L3SMI/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1658475773-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/instruments/VIIRS","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/platforms/space-based-platforms/Suomi-NPP","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"/SDE/CMR_API/|C1658475773-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90, \"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2012-01-02/2026-09-07","theme":["Earth Science"],"title":"Suomi-NPP VIIRS Level-3 Global Mapped 11\u00b5m Datime Sea Surface Temperature(SST) - Near Real-time (NRT) Data, version 2016.2"},"description":"The Ocean Biology DAAC produces near real-time (NRT) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Near real-time products provide a snapshot of the data during a short time period within a single orbit. \n\nSST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- sst \u2014 Sea Surface Temperature (\u00b0C) \n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/c05b7adf-1538-4add-bbfc-5d47dc3a169d","harvest_record_raw":"https://catalog.data.gov/harvest_record/c05b7adf-1538-4add-bbfc-5d47dc3a169d/raw","has_download":true,"has_spatial":true,"identifier":"/SDE/CMR_API/|C1658475773-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:07:52.681445","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG","slug":"suomi-npp-viirs-level-3-global-mapped-11m-day-night-sea-surface-temperature-sst-near-real--6b1e4","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Suomi-NPP VIIRS Level-3 Global Mapped 11\u00b5m Datime Sea Surface Temperature(SST) - Near Real-time (NRT) Data, version 2016.2","type":"dataset"},{"_score":12.380676,"_sort":[1790125663757,12.380676,1,"f67f3821-3d44-40a0-a363-8d1b83faef17"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"SST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- bias_sst \u2014 Sea Surface Temperature bias (\u00b0C)\n- flags_sst \u2014 Product-specific flags, Sea Surface Temperature (integer bitmask)\n- l2_flags \u2014 Level-2 Processing Flags (integer bitmask; see bit definitions)\n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)\n- sst \u2014 Sea Surface Temperature (\u00b0C)\n- sstref \u2014 Sea Surface Temperature reference (\u00b0C)\n- stdv_sst \u2014 Sea Surface Temperature standard deviation (\u00b0C)","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1615934250-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://nasa.github.io/oceandata-notebooks/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/data/reprocessing/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/atbd/legacy/atbd-obdaac-long-wave-sea-surface-temperature.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/obdaac-ancillary-data-sources.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/directdataaccess/Level-2/Terra-MODIS/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1615934250-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/instruments/MODIS","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/platforms/space-based-platforms/Terra","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"/SDE/CMR_API/|C1615934250-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG"},"spatial":"[\"CARTESIAN\", [{\"SouthBoundingCoordinate\": -90, \"EastBoundingCoordinate\": 180, \"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90}]]","temporal":"2000-02-24/2026-09-07","theme":["Earth Science"],"title":"Terra MODIS Level-2 Regional  11\u00b5m Daytime Sea Surface Temperature (SST) Data, version R2019.0"},"description":"SST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- bias_sst \u2014 Sea Surface Temperature bias (\u00b0C)\n- flags_sst \u2014 Product-specific flags, Sea Surface Temperature (integer bitmask)\n- l2_flags \u2014 Level-2 Processing Flags (integer bitmask; see bit definitions)\n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)\n- sst \u2014 Sea Surface Temperature (\u00b0C)\n- sstref \u2014 Sea Surface Temperature reference (\u00b0C)\n- stdv_sst \u2014 Sea Surface Temperature standard deviation (\u00b0C)","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/6346f66e-02aa-4f8b-8f88-40ccce0cc15a","harvest_record_raw":"https://catalog.data.gov/harvest_record/6346f66e-02aa-4f8b-8f88-40ccce0cc15a/raw","has_download":true,"has_spatial":true,"identifier":"/SDE/CMR_API/|C1615934250-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:07:43.757686","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG","slug":"terra-modis-level-regional-regional-11m-day-night-sea-surface-temperature-sst-data-version-393af","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Terra MODIS Level-2 Regional  11\u00b5m Daytime Sea Surface Temperature (SST) Data, version R2019.0","type":"dataset"},{"_score":12.498274,"_sort":[1790125661497,12.498274,3,"fa87102e-6200-4f9b-8dff-eecba59b802b"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Ocean Biology DAAC produces near real-time (NRT) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Near real-time products provide a snapshot of the data during a short time period within a single orbit. \n\nSST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- sst \u2014 Sea Surface Temperature (\u00b0C) \n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1641915272-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://nasa.github.io/oceandata-notebooks/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/data/reprocessing/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/atbd/legacy/atbd-obdaac-long-wave-sea-surface-temperature.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/obdaac-ancillary-data-sources.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/directdataaccess/Level-3%20Binned/Terra-MODIS/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1641915272-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/instruments/MODIS","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/platforms/space-based-platforms/Terra","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"/SDE/CMR_API/|C1641915272-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90, \"WestBoundingCoordinate\": -180, \"SouthBoundingCoordinate\": -90, \"EastBoundingCoordinate\": 180}]]","temporal":"2000-02-24/2026-09-07","theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Binned 11\u00b5m Datime Sea Surface Temperature(SST) - Near Real-time (NRT) Data, version R2019.0"},"description":"The Ocean Biology DAAC produces near real-time (NRT) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Near real-time products provide a snapshot of the data during a short time period within a single orbit. \n\nSST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- sst \u2014 Sea Surface Temperature (\u00b0C) \n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/4216cd5c-0fd3-4958-9c36-8230848264f4","harvest_record_raw":"https://catalog.data.gov/harvest_record/4216cd5c-0fd3-4958-9c36-8230848264f4/raw","has_download":true,"has_spatial":true,"identifier":"/SDE/CMR_API/|C1641915272-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:07:41.497916","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":3,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG","slug":"terra-modis-level-3-global-binned-11m-day-night-sea-surface-temperature-sst-near-real-time-9d7be","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Binned 11\u00b5m Datime Sea Surface Temperature(SST) - Near Real-time (NRT) Data, version R2019.0","type":"dataset"},{"_score":14.146361,"_sort":[1790125660825,14.146361,1,"97a9cb38-b3de-423b-b636-00b158eebc94"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"SST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- sst \u2014 Sea Surface Temperature (\u00b0C)\n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1615934268-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://nasa.github.io/oceandata-notebooks/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/data/reprocessing/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/atbd/legacy/atbd-obdaac-long-wave-sea-surface-temperature.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/obdaac-ancillary-data-sources.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/directdataaccess/Level-3%20Binned/Terra-MODIS/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1615934268-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/instruments/MODIS","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/platforms/space-based-platforms/Terra","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"/SDE/CMR_API/|C1615934268-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG"},"spatial":"[\"CARTESIAN\", [{\"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90, \"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90}]]","temporal":"2000-02-24/2026-09-07","theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Binned 11\u00b5m Daytime Sea Surface Temperature (SST) Data, version R2019.0"},"description":"SST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- sst \u2014 Sea Surface Temperature (\u00b0C)\n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/87163180-4d4c-48b4-b1e2-cbde795dd2f7","harvest_record_raw":"https://catalog.data.gov/harvest_record/87163180-4d4c-48b4-b1e2-cbde795dd2f7/raw","has_download":true,"has_spatial":true,"identifier":"/SDE/CMR_API/|C1615934268-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:07:40.825292","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG","slug":"terra-modis-level-3-global-binned-11m-daytime-sea-surface-temperature-sst-data-version-r20-56c08","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Binned 11\u00b5m Daytime Sea Surface Temperature (SST) Data, version R2019.0","type":"dataset"},{"_score":13.803689,"_sort":[1790125660190,13.803689,2,"249a3397-491b-4492-bf8f-f2c810a45e52"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"NSST provides global nighttime sea surface temperature estimates derived from thermal infrared observations acquired during local night to minimize diurnal warming and sun glint. Nighttime SST is widely used to detect ocean fronts, support fisheries habitat models (when paired with chlor_a, Kd_490, PAR), and provide stable inputs for air\u2013sea fluxes and climate analyses. As with all IR-based SST, uncertainties increase under thin clouds, heavy aerosols/dust, or strong thermal gradients\u2014refer to per-file flags and documentation before analysis.\n\n Geophysical variables in this suite include:\n  - sst \u2014 Sea Surface Temperature (\u00b0C) \n  - qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1615934256-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://nasa.github.io/oceandata-notebooks/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/data/reprocessing/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/atbd/legacy/atbd-obdaac-long-wave-sea-surface-temperature.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/obdaac-ancillary-data-sources.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/directdataaccess/Level-3%20Binned/Terra-MODIS/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1615934256-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/instruments/MODIS","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/platforms/space-based-platforms/Terra","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"/SDE/CMR_API/|C1615934256-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG"},"spatial":"[\"CARTESIAN\", [{\"EastBoundingCoordinate\": 180, \"NorthBoundingCoordinate\": 90, \"SouthBoundingCoordinate\": -90, \"WestBoundingCoordinate\": -180}]]","temporal":"2000-02-24/2026-09-07","theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Binned 11\u00b5m Nighttime Sea Surface Temperature (NSST) Data, version R2019.0"},"description":"NSST provides global nighttime sea surface temperature estimates derived from thermal infrared observations acquired during local night to minimize diurnal warming and sun glint. Nighttime SST is widely used to detect ocean fronts, support fisheries habitat models (when paired with chlor_a, Kd_490, PAR), and provide stable inputs for air\u2013sea fluxes and climate analyses. As with all IR-based SST, uncertainties increase under thin clouds, heavy aerosols/dust, or strong thermal gradients\u2014refer to per-file flags and documentation before analysis.\n\n Geophysical variables in this suite include:\n  - sst \u2014 Sea Surface Temperature (\u00b0C) \n  - qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/677fc19d-e7d0-4168-a1d9-7f56382aae57","harvest_record_raw":"https://catalog.data.gov/harvest_record/677fc19d-e7d0-4168-a1d9-7f56382aae57/raw","has_download":true,"has_spatial":true,"identifier":"/SDE/CMR_API/|C1615934256-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:07:40.190923","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG","slug":"terra-modis-level-3-global-binned-11m-nighttime-sea-surface-temperature-nsst-data-version--a41d0","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Binned 11\u00b5m Nighttime Sea Surface Temperature (NSST) Data, version R2019.0","type":"dataset"},{"_score":12.136149,"_sort":[1790125659515,12.136149,1,"328b06de-6989-49fc-ac49-21a505d05338"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Ocean Biology DAAC produces near real-time (NRT) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Near real-time products provide a snapshot of the data during a short time period within a single orbit. \n\nNSST provides global nighttime sea surface temperature estimates derived from thermal infrared observations acquired during local night to minimize diurnal warming and sun glint. Nighttime SST is widely used to detect ocean fronts, support fisheries habitat models (when paired with chlor_a, Kd_490, PAR), and provide stable inputs for air\u2013sea fluxes and climate analyses. As with all IR-based SST, uncertainties increase under thin clouds, heavy aerosols/dust, or strong thermal gradients\u2014refer to per-file flags and documentation before analysis.\n\n Geophysical variables in this suite include:\n  - sst \u2014 Sea Surface Temperature (\u00b0C)\n  - qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1641916383-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://nasa.github.io/oceandata-notebooks/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/data/reprocessing/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/atbd/legacy/atbd-obdaac-long-wave-sea-surface-temperature.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/obdaac-ancillary-data-sources.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/directdataaccess/Level-3%20Binned/Terra-MODIS/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1641916383-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/instruments/MODIS","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/platforms/space-based-platforms/Terra","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"/SDE/CMR_API/|C1641916383-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90, \"NorthBoundingCoordinate\": 90}]]","temporal":"2000-02-24/2026-09-07","theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Binned 11\u00b5m Nighttime Sea Surface Temperature NSST) - Near Real-time (NRT) Data, version R2019.0"},"description":"The Ocean Biology DAAC produces near real-time (NRT) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Near real-time products provide a snapshot of the data during a short time period within a single orbit. \n\nNSST provides global nighttime sea surface temperature estimates derived from thermal infrared observations acquired during local night to minimize diurnal warming and sun glint. Nighttime SST is widely used to detect ocean fronts, support fisheries habitat models (when paired with chlor_a, Kd_490, PAR), and provide stable inputs for air\u2013sea fluxes and climate analyses. As with all IR-based SST, uncertainties increase under thin clouds, heavy aerosols/dust, or strong thermal gradients\u2014refer to per-file flags and documentation before analysis.\n\n Geophysical variables in this suite include:\n  - sst \u2014 Sea Surface Temperature (\u00b0C)\n  - qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/7ef9c49a-e0e5-459f-a1c4-8f34571f8d1f","harvest_record_raw":"https://catalog.data.gov/harvest_record/7ef9c49a-e0e5-459f-a1c4-8f34571f8d1f/raw","has_download":true,"has_spatial":true,"identifier":"/SDE/CMR_API/|C1641916383-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:07:39.515259","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG","slug":"terra-modis-level-3-global-binned-11m-nighttime-sea-surface-temperature-nsst-near-real-tim-ffdf6","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Binned 11\u00b5m Nighttime Sea Surface Temperature NSST) - Near Real-time (NRT) Data, version R2019.0","type":"dataset"},{"_score":12.498274,"_sort":[1790125656892,12.498274,1,"b0db618c-689d-4867-86cd-b4c3f3613f6a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Ocean Biology DAAC produces near real-time (NRT) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Near real-time products provide a snapshot of the data during a short time period within a single orbit. \n\nSST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- sst \u2014 Sea Surface Temperature (\u00b0C) \n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1641913601-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://nasa.github.io/oceandata-notebooks/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/data/reprocessing/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/atbd/legacy/atbd-obdaac-long-wave-sea-surface-temperature.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/obdaac-ancillary-data-sources.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/directdataaccess/Level-3%20Mapped/Terra-MODIS/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/opendap/MODIST/L3SMI/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1641913601-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/instruments/MODIS","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/platforms/space-based-platforms/Terra","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"/SDE/CMR_API/|C1641913601-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG"},"spatial":"[\"CARTESIAN\", [{\"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90, \"NorthBoundingCoordinate\": 90, \"WestBoundingCoordinate\": -180}]]","temporal":"2000-02-24/2026-09-07","theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Mapped 11\u00b5m Datime Sea Surface Temperature(SST) - Near Real-time (NRT) Data, version R2019.0"},"description":"The Ocean Biology DAAC produces near real-time (NRT) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Near real-time products provide a snapshot of the data during a short time period within a single orbit. \n\nSST provides global sea surface temperature derived primarily from thermal infrared observations during daytime. Users apply SST to detect fronts and eddies, monitor marine heatwaves, drive ecosystem and habitat models (when paired with chlor_a, Kd_490, PAR), and provide boundary conditions for biogeochemical and climate analyses. Note that IR-based SST is sensitive to clouds, aerosols, and diurnal warming; for minimum diurnal effects, pair with NSST (nighttime SST) and refer to per-file flags before analysis.\n\n Geophysical variables in this suite include:\n- sst \u2014 Sea Surface Temperature (\u00b0C) \n- qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/48cc677e-23de-4101-8748-ad28617d83d9","harvest_record_raw":"https://catalog.data.gov/harvest_record/48cc677e-23de-4101-8748-ad28617d83d9/raw","has_download":true,"has_spatial":true,"identifier":"/SDE/CMR_API/|C1641913601-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:07:36.892844","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG","slug":"terra-modis-level-3-global-mapped-11m-day-night-sea-surface-temperature-sst-near-real-time-dced3","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Mapped 11\u00b5m Datime Sea Surface Temperature(SST) - Near Real-time (NRT) Data, version R2019.0","type":"dataset"},{"_score":12.107982,"_sort":[1790125656571,12.107982,1,"486fbb10-659f-4f50-b515-d9677b7f69a0"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Ocean Biology DAAC produces near real-time (NRT) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Near real-time products provide a snapshot of the data during a short time period within a single orbit. \n\nNSST provides global nighttime sea surface temperature estimates derived from thermal infrared observations acquired during local night to minimize diurnal warming and sun glint. Nighttime SST is widely used to detect ocean fronts, support fisheries habitat models (when paired with chlor_a, Kd_490, PAR), and provide stable inputs for air\u2013sea fluxes and climate analyses. As with all IR-based SST, uncertainties increase under thin clouds, heavy aerosols/dust, or strong thermal gradients\u2014refer to per-file flags and documentation before analysis.\n\n Geophysical variables in this suite include:\n  - sst \u2014 Sea Surface Temperature (\u00b0C)\n  - qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1641914526-OB_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://nasa.github.io/oceandata-notebooks/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/data/reprocessing/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/atbd/legacy/atbd-obdaac-long-wave-sea-surface-temperature.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceancolor.gsfc.nasa.gov/files/obdaac-ancillary-data-sources.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/directdataaccess/Level-3%20Mapped/Terra-MODIS/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://oceandata.sci.gsfc.nasa.gov/opendap/MODIST/L3SMI/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1641914526-OB_DAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/instruments/MODIS","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/platforms/space-based-platforms/Terra","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"/SDE/CMR_API/|C1641914526-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90, \"WestBoundingCoordinate\": -180}]]","temporal":"2000-02-24/2026-09-07","theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Mapped 11\u00b5m Nighttime Sea Surface Temperature NSST) - Near Real-time (NRT) Data, version R2019.0"},"description":"The Ocean Biology DAAC produces near real-time (NRT) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Near real-time products provide a snapshot of the data during a short time period within a single orbit. \n\nNSST provides global nighttime sea surface temperature estimates derived from thermal infrared observations acquired during local night to minimize diurnal warming and sun glint. Nighttime SST is widely used to detect ocean fronts, support fisheries habitat models (when paired with chlor_a, Kd_490, PAR), and provide stable inputs for air\u2013sea fluxes and climate analyses. As with all IR-based SST, uncertainties increase under thin clouds, heavy aerosols/dust, or strong thermal gradients\u2014refer to per-file flags and documentation before analysis.\n\n Geophysical variables in this suite include:\n  - sst \u2014 Sea Surface Temperature (\u00b0C)\n  - qual_sst \u2014 Quality levels for Sea Surface Temperature (integer quality flag)","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/09b1649e-cfc0-42c8-9b65-110396347748","harvest_record_raw":"https://catalog.data.gov/harvest_record/09b1649e-cfc0-42c8-9b65-110396347748/raw","has_download":true,"has_spatial":true,"identifier":"/SDE/CMR_API/|C1641914526-OB_DAAC","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:07:36.571569","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/GCDC/OB.DAAC;OBPG","slug":"terra-modis-level-3-global-mapped-11m-nighttime-sea-surface-temperature-nsst-near-real-tim-45bad","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Terra MODIS Level-3 Global Mapped 11\u00b5m Nighttime Sea Surface Temperature NSST) - Near Real-time (NRT) Data, version R2019.0","type":"dataset"},{"_score":9.529512,"_sort":[1790125644138,9.529512,3,"bb93be24-4170-425b-8116-c4975923d204"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. The AIRS Infrared (IR) level 1C data set contains AIRS infrared calibrated and geolocated radiances in W/m2/micron/ster. This data set is generated from AIRS level 1B data. The spectral coverage of L1C data is from 3.74 to 15.4 mm. The nominal spectral resolution lambda / delta lambda = 1200. The spectrum is sampled twice per spectral resolution element in a total of 2645 spectral channels. A day of AIRS data is divided into 240 granules (scenes) each of 6-minute duration. For the AIRS IR measurements, an individual granule contains 135 pixels across-track and 90 along-track pixels; there are total of 135 x 90 = 12,150 pixels per granule. AIRS employs a 49.5 degree crosstrack scanning with a 1.1 degree instantaneous field of view (IFOV) to provide twice daily coverage of essentially the entire globe in a 1:30 PM sun synchronous orbit with the 13.5 x 13.5 km2 spatial resolution at nadir. The L1C swath products are derived from the L1B swath products. The primary purpose of the level 1C is to generate the spectra of radiances without spectral gaps caused by the instrument design and bad spectral points. The AIRS L1C data can be used for comparative (with other IR measurements) studies and for weather-climate research.\n\nThis is the latest version of this collection. The DOIs assigned to previous versions, which are no longer available, now direct\nto this page. For this collection the switchover occurred on June 1, 2020.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1701805625-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://airs.jpl.nasa.gov/index.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/AIRS2RET_NRT_7.0.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://discnrt1.gesdisc.eosdis.nasa.gov/data/Aqua_AIRS_NRT/AIRS2RET_NRT.7.0/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/AIRS/AIRS_Documentation.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/AIRS/Overview_of_the_AIRS_Mission.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/AIRS/V7_L2_Product_User_Guide.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/AIRS2RET_7.0.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1701805625-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://worldview.earthdata.nasa.gov/?l=Reference_Labels_15m%28hidden%29%2CReference_Features_15m%28hidden%29%2CCoastlines_15m%2CAIRS_L2_Carbon_Monoxide_500hPa_Volume_Mixing_Ratio_Night%2CAIRS_L2_Carbon_Monoxide_500hPa_Volume_Mixing_Ratio_Day%2COCI_PACE_True_Color%28hidden%29%2CVIIRS_NOAA21_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_NOAA20_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_SNPP_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Aqua_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Terra_CorrectedReflectance_TrueColor&lg=true&t=2026-03-02-T14%253A13%253A59Z","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://worldview.earthdata.nasa.gov/?l=Reference_Labels_15m%28hidden%29%2CReference_Features_15m%28hidden%29%2CCoastlines_15m%2CAIRS_L2_RelativeHumidity_850hPa_Night%2CAIRS_L2_RelativeHumidity_850hPa_Day%2CAIRS_L2_RelativeHumidity_700hPa_Night%2CAIRS_L2_RelativeHumidity_700hPa_Day%2CAIRS_L2_RelativeHumidity_500hPa_Night%2CAIRS_L2_RelativeHumidity_500hPa_Day%2COCI_PACE_True_Color%28hidden%29%2CVIIRS_NOAA21_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_NOAA20_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_SNPP_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Aqua_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Terra_CorrectedReflectance_TrueColor&lg=true&t=2026-03-05-T16%253A43%253A04Z","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://worldview.earthdata.nasa.gov/?l=Reference_Labels_15m%28hidden%29%2CReference_Features_15m%28hidden%29%2CCoastlines_15m%2CAIRS_L2_Temperature_850hPa_Night%2CAIRS_L2_Temperature_850hPa_Day%2CAIRS_L2_Temperature_700hPa_Night%2CAIRS_L2_Temperature_700hPa_Day%2CAIRS_L2_Temperature_500hPa_Night%2CAIRS_L2_Temperature_500hPa_Day%2COCI_PACE_True_Color%28hidden%29%2CVIIRS_NOAA21_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_NOAA20_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_SNPP_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Aqua_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Terra_CorrectedReflectance_TrueColor&lg=true&t=2026-03-05-T16%253A43%253A04Z","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://worldview.earthdata.nasa.gov/?l=Reference_Labels_15m%28hidden%29%2CReference_Features_15m%28hidden%29%2CCoastlines_15m%2CAIRS_L2_Total_Cloud_Fraction_Night%2CAIRS_L2_Total_Cloud_Fraction_Day%2COCI_PACE_True_Color%28hidden%29%2CVIIRS_NOAA21_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_NOAA20_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_SNPP_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Aqua_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Terra_CorrectedReflectance_TrueColor&lg=true&t=2026-03-05-T16%253A43%253A04Z","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://worldview.earthdata.nasa.gov/?z=1&l=Reference_Labels_15m%28hidden%29%2CReference_Features_15m%28hidden%29%2CCoastlines_15m%2CAIRS_L2_Cloud_Top_Height_Night%2CAIRS_L2_Cloud_Top_Height_Day%2COCI_PACE_True_Color%28hidden%29%2CVIIRS_NOAA21_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_NOAA20_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_SNPP_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Aqua_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Terra_CorrectedReflectance_TrueColor&lg=true&t=2026-03-02-T14%253A13%253A59Z","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://worldview.earthdata.nasa.gov/?z=1&l=Reference_Labels_15m%28hidden%29%2CReference_Features_15m%28hidden%29%2CCoastlines_15m%2CAIRS_L2_Methane_400hPa_Volume_Mixing_Ratio_Night%2CAIRS_L2_Methane_400hPa_Volume_Mixing_Ratio_Day%2COCI_PACE_True_Color%28hidden%29%2CVIIRS_NOAA21_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_NOAA20_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_SNPP_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Aqua_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Terra_CorrectedReflectance_TrueColor&lg=true&t=2026-03-02-T14%253A13%253A59Z","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://worldview.earthdata.nasa.gov/?z=1&l=Reference_Labels_15m%28hidden%29%2CReference_Features_15m%28hidden%29%2CCoastlines_15m%2CAIRS_L2_Surface_Relative_Humidity_Night%2CAIRS_L2_Surface_Relative_Humidity_Day%2COCI_PACE_True_Color%28hidden%29%2CVIIRS_NOAA21_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_NOAA20_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_SNPP_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Aqua_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Terra_CorrectedReflectance_TrueColor&lg=true&t=2026-03-02-T14%253A13%253A59Z","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://worldview.earthdata.nasa.gov/?z=1&l=Reference_Labels_15m%28hidden%29%2CReference_Features_15m%28hidden%29%2CCoastlines_15m%2CAIRS_L2_Surface_Skin_Temperature_Night%2CAIRS_L2_Surface_Skin_Temperature_Day%2CAIRS_L2_Surface_Air_Temperature_Night%2CAIRS_L2_Surface_Air_Temperature_Day%2COCI_PACE_True_Color%28hidden%29%2CVIIRS_NOAA21_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_NOAA20_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_SNPP_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Aqua_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Terra_CorrectedReflectance_TrueColor&lg=true&t=2026-03-02-T14%253A13%253A59Z","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/VWD3DRC07UEN","keyword":["earth-science-aerosols-atmosphere-dust-ash-smoke","earth-science-atmospheric-chemistry-atmosphere-sulfur-compounds","earth-science-infrared-wavelengths-spectral-engineering-infrared-radiance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2002-08-30/2026-09-07","theme":["Earth Science"],"title":"AIRS/Aqua L1C Infrared (IR) resampled and corrected radiances V6.7 (AIRICRAD)"},"description":"The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. The AIRS Infrared (IR) level 1C data set contains AIRS infrared calibrated and geolocated radiances in W/m2/micron/ster. This data set is generated from AIRS level 1B data. The spectral coverage of L1C data is from 3.74 to 15.4 mm. The nominal spectral resolution lambda / delta lambda = 1200. The spectrum is sampled twice per spectral resolution element in a total of 2645 spectral channels. A day of AIRS data is divided into 240 granules (scenes) each of 6-minute duration. For the AIRS IR measurements, an individual granule contains 135 pixels across-track and 90 along-track pixels; there are total of 135 x 90 = 12,150 pixels per granule. AIRS employs a 49.5 degree crosstrack scanning with a 1.1 degree instantaneous field of view (IFOV) to provide twice daily coverage of essentially the entire globe in a 1:30 PM sun synchronous orbit with the 13.5 x 13.5 km2 spatial resolution at nadir. The L1C swath products are derived from the L1B swath products. The primary purpose of the level 1C is to generate the spectra of radiances without spectral gaps caused by the instrument design and bad spectral points. The AIRS L1C data can be used for comparative (with other IR measurements) studies and for weather-climate research.\n\nThis is the latest version of this collection. The DOIs assigned to previous versions, which are no longer available, now direct\nto this page. For this collection the switchover occurred on June 1, 2020.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/2d5dacb5-af15-40c1-8465-158c7cb516aa","harvest_record_raw":"https://catalog.data.gov/harvest_record/2d5dacb5-af15-40c1-8465-158c7cb516aa/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/VWD3DRC07UEN","keyword":["earth-science-aerosols-atmosphere-dust-ash-smoke","earth-science-atmospheric-chemistry-atmosphere-sulfur-compounds","earth-science-infrared-wavelengths-spectral-engineering-infrared-radiance"],"last_harvested_date":"2026-09-23T01:07:24.138806","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":3,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"airs-aqua-l1c-infrared-ir-resampled-and-corrected-radiances-v6-7-airicrad-at-ges-disc","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"AIRS/Aqua L1C Infrared (IR) resampled and corrected radiances V6.7 (AIRICRAD)","type":"dataset"},{"_score":8.781483,"_sort":[1790125643499,8.781483,1,"54e67944-52f5-483a-a17c-7b0c71f188c3"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. The AIRS Infrared (IR) level 1C data set contains AIRS infrared calibrated and geolocated radiances in W/m2/micron/ster. This data set is generated from AIRS level 1B data. The spectral coverage of L1C data is from 3.74 to 15.4 mm. The nominal spectral resolution lambda / delta lambda = 1200. The spectrum is sampled twice per spectral resolution element in a total of 2645 spectral channels. A day of AIRS data is divided into 240 granules (scenes) each of 6-minute duration. For the AIRS IR measurements, an individual granule contains 135 pixels across-track and 90 along-track pixels; there are total of 135 x 90 = 12,150 pixels per granule. AIRS employs a 49.5 degree crosstrack scanning with a 1.1 degree instantaneous field of view (IFOV) to provide twice daily coverage of essentially the entire globe in a 1:30 PM sun synchronous orbit with the 13.5 x 13.5 km2 spatial resolution at nadir. The L1C swath products are derived from the L1B swath products. The primary purpose of the level 1C is to generate the spectra of radiances without spectral gaps caused by the instrument design and bad spectral points. The AIRS L1C data can be used for comparative (with other IR measurements) studies and for weather-climate research.\n\nAs a Near Real Time (NRT) product this differs from AIRICRAD.6.7 AIRS differ from routine processing in 2 ways to meet the three hour latency requirements of the Land Atmosphere NRT Capability Earth Observing System (LANCE): (1) The NRT granules are produced without previous or subsequent granules if those granules are not available within 5 minutes, (2) the predictive ephemeris/attitude data are used rather than the definitive ephemeris/attitude.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1712047294-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://airs.jpl.nasa.gov/index.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/AIRICRAD_NRT_6.7.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://discnrt1.gesdisc.eosdis.nasa.gov/data/Aqua_AIRS_NRT/AIRICRAD_NRT.6.7/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/AIRS/AIRS_Documentation.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/AIRS/AIRS_V6.7_L1C_ATBD.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/AIRICRAD.v6.7.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/AIRS/3.3_ScienceDataProductDocumentation/3.3.4_ProductGenerationAlgorithms/README.AIRS_V6.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1712047294-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/LJSDHD3RLTII","keyword":["earth-science-aerosols-atmosphere-dust-ash-smoke","earth-science-atmospheric-chemistry-atmosphere-sulfur-compounds","earth-science-infrared-wavelengths-spectral-engineering-infrared-radiance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2002-09-06/2026-09-07","theme":["Earth Science"],"title":"AIRS/Aqua L1C Near Real Time (NRT) Infrared (IR) resampled and corrected radiances V6.7 (AIRICRAD_NRT)"},"description":"The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. The AIRS Infrared (IR) level 1C data set contains AIRS infrared calibrated and geolocated radiances in W/m2/micron/ster. This data set is generated from AIRS level 1B data. The spectral coverage of L1C data is from 3.74 to 15.4 mm. The nominal spectral resolution lambda / delta lambda = 1200. The spectrum is sampled twice per spectral resolution element in a total of 2645 spectral channels. A day of AIRS data is divided into 240 granules (scenes) each of 6-minute duration. For the AIRS IR measurements, an individual granule contains 135 pixels across-track and 90 along-track pixels; there are total of 135 x 90 = 12,150 pixels per granule. AIRS employs a 49.5 degree crosstrack scanning with a 1.1 degree instantaneous field of view (IFOV) to provide twice daily coverage of essentially the entire globe in a 1:30 PM sun synchronous orbit with the 13.5 x 13.5 km2 spatial resolution at nadir. The L1C swath products are derived from the L1B swath products. The primary purpose of the level 1C is to generate the spectra of radiances without spectral gaps caused by the instrument design and bad spectral points. The AIRS L1C data can be used for comparative (with other IR measurements) studies and for weather-climate research.\n\nAs a Near Real Time (NRT) product this differs from AIRICRAD.6.7 AIRS differ from routine processing in 2 ways to meet the three hour latency requirements of the Land Atmosphere NRT Capability Earth Observing System (LANCE): (1) The NRT granules are produced without previous or subsequent granules if those granules are not available within 5 minutes, (2) the predictive ephemeris/attitude data are used rather than the definitive ephemeris/attitude.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/8f86d2dc-f653-4e71-b729-1ec70c55a6a5","harvest_record_raw":"https://catalog.data.gov/harvest_record/8f86d2dc-f653-4e71-b729-1ec70c55a6a5/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/LJSDHD3RLTII","keyword":["earth-science-aerosols-atmosphere-dust-ash-smoke","earth-science-atmospheric-chemistry-atmosphere-sulfur-compounds","earth-science-infrared-wavelengths-spectral-engineering-infrared-radiance"],"last_harvested_date":"2026-09-23T01:07:23.499740","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"airs-aqua-l1c-near-real-time-nrt-infrared-ir-resampled-and-corrected-radiances-v6-7-airicr","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"AIRS/Aqua L1C Near Real Time (NRT) Infrared (IR) resampled and corrected radiances V6.7 (AIRICRAD_NRT)","type":"dataset"},{"_score":14.955326,"_sort":[1790125631827,14.955326,1,"831f1f61-b7c9-4927-b610-b7b9a9523478"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"ARCTAS focuses on advancing understanding of the factors driving current changes in the Arctic region including transport of mid-latitude pollution, boreal forest fires, aerosol radiative forcing, and chemical processes. ARCTAS aimed to use detailed observations from aircraft to provide the validation, retrieval constraints, correlative data, and process information needed to better achieve the potential of satellites for Arctic research. The plan is for the combination of satellite and aircraft data to provide together powerful information for constraining and evaluating models of Arctic atmospheric composition and climate, and thus improve model projections of future change.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1442068281-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_ARCTAS_L1C.1/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_ARCTAS_L1C.1/doc/CAR_README.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gsfc.nasa.gov/opendap/CAR/CAR_ARCTAS_L1C.1/contents.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://car.gsfc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/CAR_ARCTAS_L1C_1.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/CAR_ARCTAS_L1C_1.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1442068281-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/CAR/DATA104","keyword":["earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-clouds-atmosphere-cloud-properties","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -163.5979, \"NorthBoundingCoordinate\": 80.6613, \"EastBoundingCoordinate\": -69.2484, \"SouthBoundingCoordinate\": 32.93152}]]","temporal":"2008-04-06/2008-07-12","theme":["Earth Science"],"title":"CAR ARCTAS Arctic Research of the Composition of the Troposphere from Aircraft and Satellites L1 V1 (CAR_ARCTAS_L1C)"},"description":"ARCTAS focuses on advancing understanding of the factors driving current changes in the Arctic region including transport of mid-latitude pollution, boreal forest fires, aerosol radiative forcing, and chemical processes. ARCTAS aimed to use detailed observations from aircraft to provide the validation, retrieval constraints, correlative data, and process information needed to better achieve the potential of satellites for Arctic research. The plan is for the combination of satellite and aircraft data to provide together powerful information for constraining and evaluating models of Arctic atmospheric composition and climate, and thus improve model projections of future change.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/3515f272-0a49-4a0b-a8e7-72e1730e13a9","harvest_record_raw":"https://catalog.data.gov/harvest_record/3515f272-0a49-4a0b-a8e7-72e1730e13a9/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/CAR/DATA104","keyword":["earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-clouds-atmosphere-cloud-properties","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"last_harvested_date":"2026-09-23T01:07:11.827630","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"car-arctas-arctic-research-of-the-composition-of-the-troposphere-from-aircraft-and-satelli","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CAR ARCTAS Arctic Research of the Composition of the Troposphere from Aircraft and Satellites L1 V1 (CAR_ARCTAS_L1C)","type":"dataset"},{"_score":12.475199,"_sort":[1790125630432,12.475199,1,"09f8fd3d-8e82-4683-a45e-c5f58e43777f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"CLASIC (Cloud and Land Surface Interaction Campaign) focuses on advancing the understanding of how land surface processes influence cumulus convection. CLASIC was conducted in the Southern Great Plains (SGP &#8211; a region comprising Kansas, Oklahoma, and Texas) of the United States during June 2007. The SGP site consists of in situ and remote-sensing instrument clusters arrayed across approximately 55,000 square miles (143,000 square kilometers) in north-central Oklahoma, making it the largest and most extensive climate research field site in the world. The CAR flew aboard Sky Research Jetstream-31 and measured spectral and angular distribution of scattered light by clouds and aerosols, and provided bidirectional reflectance of various surfaces, and imagery of cloud and Earth surface features. By making such diverse measurements, our goal is to widen the audience of potential end-users and to foster collaborations among campaign participants and with outside users.\n\nThis data set consists of observations made with the CAR instrument and includes values for bidirectional reflectance factor at varying spectral bands.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1617621682-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_CLASIC_BRDF.2/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/opendap/hyrax/CAR/CAR_CLASIC_BRDF.2/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://car.gsfc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/CAR_CLASIC_BRDF_2.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/CAR/CAR_BRDF_README-v2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/CAR_CLASIC_L1C_1.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1617621682-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/0JRNK6HDB9ZG","keyword":["earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -98.0795, \"NorthBoundingCoordinate\": 36.8193, \"EastBoundingCoordinate\": -97.0694, \"SouthBoundingCoordinate\": 34.9401}]]","temporal":"2007-06-13/2007-06-25","theme":["Earth Science"],"title":"CAR CLASIC BRDF Measurements V2 (CAR_CLASIC_BRDF)"},"description":"CLASIC (Cloud and Land Surface Interaction Campaign) focuses on advancing the understanding of how land surface processes influence cumulus convection. CLASIC was conducted in the Southern Great Plains (SGP &#8211; a region comprising Kansas, Oklahoma, and Texas) of the United States during June 2007. The SGP site consists of in situ and remote-sensing instrument clusters arrayed across approximately 55,000 square miles (143,000 square kilometers) in north-central Oklahoma, making it the largest and most extensive climate research field site in the world. The CAR flew aboard Sky Research Jetstream-31 and measured spectral and angular distribution of scattered light by clouds and aerosols, and provided bidirectional reflectance of various surfaces, and imagery of cloud and Earth surface features. By making such diverse measurements, our goal is to widen the audience of potential end-users and to foster collaborations among campaign participants and with outside users.\n\nThis data set consists of observations made with the CAR instrument and includes values for bidirectional reflectance factor at varying spectral bands.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/7e972cb7-f95a-4d33-843f-fe8dff226af3","harvest_record_raw":"https://catalog.data.gov/harvest_record/7e972cb7-f95a-4d33-843f-fe8dff226af3/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/0JRNK6HDB9ZG","keyword":["earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"last_harvested_date":"2026-09-23T01:07:10.432199","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"car-clasic-brdf-measurements-v2-car_clasic_brdf-at-ges-disc","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CAR CLASIC BRDF Measurements V2 (CAR_CLASIC_BRDF)","type":"dataset"},{"_score":17.664043,"_sort":[1790125630097,17.664043,1,"69c1619e-51c9-4ae6-8662-c830c3d0187e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The scientific objectives of FIRE/ACE are to study impact of Arctic clouds on radiation exchange between surface, atmosphere, and space, and the influence of surface characteristics of sea ice, leads, and ice melt ponds on these clouds. FIRE/ACE will attempt to document, understand, and predict the Arctic cloud-radiation feedbacks, including changes in cloud fraction and vertical distribution, water vapor cloud content, cloud particle concentration and size, and cloud phase as atmospheric temperature and chemical composition change. FIRE/ACE uses the data to focus on improving current climate model simulations of the Arctic climate, especially with respect to clouds and their effects on the surface energy budget. In addition, FIRE/ACE addresses a number of scientific questions dealing with radiation, cloud microphysics, and atmospheric chemistry.\n\nThis data set consists of observations made with the CAR instrument and includes values for bidirectional reflectance factor at varying spectral bands.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1617621687-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_FIREACE_BRDF.2/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gsfc.nasa.gov/opendap/CAR/CAR_FIREACE_BRDF.2/contents.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://car.gsfc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/CAR_FIREACE_BRDF_2.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/CAR/CAR_BRDF_README-v2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/CAR_FIREACE_L1C_1.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1617621687-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/KHFVLOHOCSWU","keyword":["earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-clouds-atmosphere-cloud-properties","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -168.4984, \"NorthBoundingCoordinate\": 76.7114, \"EastBoundingCoordinate\": 1.3825699, \"SouthBoundingCoordinate\": 71.7758}]]","temporal":"1998-05-20/1998-05-30","theme":["Earth Science"],"title":"CAR FIREACE Arctic Ice and Cloud Radiation BRDF V2 (CAR_FIREACE_BRDF)"},"description":"The scientific objectives of FIRE/ACE are to study impact of Arctic clouds on radiation exchange between surface, atmosphere, and space, and the influence of surface characteristics of sea ice, leads, and ice melt ponds on these clouds. FIRE/ACE will attempt to document, understand, and predict the Arctic cloud-radiation feedbacks, including changes in cloud fraction and vertical distribution, water vapor cloud content, cloud particle concentration and size, and cloud phase as atmospheric temperature and chemical composition change. FIRE/ACE uses the data to focus on improving current climate model simulations of the Arctic climate, especially with respect to clouds and their effects on the surface energy budget. In addition, FIRE/ACE addresses a number of scientific questions dealing with radiation, cloud microphysics, and atmospheric chemistry.\n\nThis data set consists of observations made with the CAR instrument and includes values for bidirectional reflectance factor at varying spectral bands.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/8b5cd031-4696-4759-8a71-5bfc21fc1dc0","harvest_record_raw":"https://catalog.data.gov/harvest_record/8b5cd031-4696-4759-8a71-5bfc21fc1dc0/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/KHFVLOHOCSWU","keyword":["earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-clouds-atmosphere-cloud-properties","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"last_harvested_date":"2026-09-23T01:07:10.097781","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"car-fireace-arctic-ice-and-cloud-radiation-brdf-v2-car_fireace_brdf-at-ges-disc","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CAR FIREACE Arctic Ice and Cloud Radiation BRDF V2 (CAR_FIREACE_BRDF)","type":"dataset"},{"_score":14.002337,"_sort":[1790125629755,14.002337,1,"6e98cd79-f95d-440a-8240-05021761cb41"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"This study provide critical measurements on 3-dimensional structure of vegetation, which is important for quantifying the amount of carbon stored in biomass. It promotes the understanding of vegetation response to changing forcing factors such as climate, storm frequency, and management practices, and is directly traceable to missions such as MODIS, MISR, and ICESat-2.During the ECO-3D mission in 2011, the CAR instrument was flown aboard the NASA P-3 and obtained measurements of bidirectional reflectance distribution function (BRDF) over forests ranging from Boreal to tropical wetlands covering sites from Quebec to Southern Florida.\n\nThis data set consists of observations made with the CAR instrument and includes values for bidirectional reflectance factor at varying spectral bands.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1617621686-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_ECO3D_BRDF.2/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/opendap/CAR/CAR_ECO3D_BRDF.2/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://car.gsfc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/CAR_ECO3D_BRDF_2.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/CAR/CAR_BRDF_README-v2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/CAR_ECO3D_L1C_1.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1617621686-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/Z9SJNDOW30XI","keyword":["earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -81.1112, \"NorthBoundingCoordinate\": 45.2482, \"EastBoundingCoordinate\": -68.6791, \"SouthBoundingCoordinate\": 25.3171}]]","temporal":"2011-08-22/2011-09-19","theme":["Earth Science"],"title":"CAR ECO3D BRDF Measurements V2 (CAR_ECO3D_BRDF)"},"description":"This study provide critical measurements on 3-dimensional structure of vegetation, which is important for quantifying the amount of carbon stored in biomass. It promotes the understanding of vegetation response to changing forcing factors such as climate, storm frequency, and management practices, and is directly traceable to missions such as MODIS, MISR, and ICESat-2.During the ECO-3D mission in 2011, the CAR instrument was flown aboard the NASA P-3 and obtained measurements of bidirectional reflectance distribution function (BRDF) over forests ranging from Boreal to tropical wetlands covering sites from Quebec to Southern Florida.\n\nThis data set consists of observations made with the CAR instrument and includes values for bidirectional reflectance factor at varying spectral bands.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/ad4e896a-10a8-48ec-bf88-d279ef3d8f5f","harvest_record_raw":"https://catalog.data.gov/harvest_record/ad4e896a-10a8-48ec-bf88-d279ef3d8f5f/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/Z9SJNDOW30XI","keyword":["earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"last_harvested_date":"2026-09-23T01:07:09.755311","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"car-eco3d-brdf-measurements-v2-car_eco3d_brdf-at-ges-disc","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CAR ECO3D BRDF Measurements V2 (CAR_ECO3D_BRDF)","type":"dataset"},{"_score":18.028603,"_sort":[1790125629414,18.028603,2,"488f0f66-bdec-47b6-9815-f2d0abc0330e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The scientific objectives of FIRE/ACE are to study impact of Arctic clouds on radiation exchange between surface, atmosphere, and space, and the influence of surface characteristics of sea ice, leads, and ice melt ponds on these clouds. FIRE/ACE will attempt to document, understand, and predict the Arctic cloud-radiation feedbacks, including changes in cloud fraction and vertical distribution, water vapor cloud content, cloud particle concentration and size, and cloud phase as atmospheric temperature and chemical composition change. FIRE/ACE uses the data to focus on improving current climate model simulations of the Arctic climate, especially with respect to clouds and their effects on the surface energy budget. In addition, FIRE/ACE addresses a number of scientific questions dealing with radiation, cloud microphysics, and atmospheric chemistry.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1442068295-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_FIREACE_L1C.1/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_FIREACE_L1C.1/doc/CAR_README.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gsfc.nasa.gov/opendap/CAR/CAR_FIREACE_L1C.1/contents.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://car.gsfc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/CAR_FIREACE_L1C_1.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/CAR_FIREACE_L1C_1.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1442068295-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/CAR/DATA110","keyword":["earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-clouds-atmosphere-cloud-properties","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -171.705, \"NorthBoundingCoordinate\": 77.7766, \"EastBoundingCoordinate\": -154.102, \"SouthBoundingCoordinate\": 69.8396}]]","temporal":"1998-05-21/1998-06-24","theme":["Earth Science"],"title":"CAR FIREACE Arctic Ice and Cloud Radiation L1 V1 (CAR_FIREACE_L1C)"},"description":"The scientific objectives of FIRE/ACE are to study impact of Arctic clouds on radiation exchange between surface, atmosphere, and space, and the influence of surface characteristics of sea ice, leads, and ice melt ponds on these clouds. FIRE/ACE will attempt to document, understand, and predict the Arctic cloud-radiation feedbacks, including changes in cloud fraction and vertical distribution, water vapor cloud content, cloud particle concentration and size, and cloud phase as atmospheric temperature and chemical composition change. FIRE/ACE uses the data to focus on improving current climate model simulations of the Arctic climate, especially with respect to clouds and their effects on the surface energy budget. In addition, FIRE/ACE addresses a number of scientific questions dealing with radiation, cloud microphysics, and atmospheric chemistry.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/1d3f2938-418e-407b-b3ec-3b1a120b4eb6","harvest_record_raw":"https://catalog.data.gov/harvest_record/1d3f2938-418e-407b-b3ec-3b1a120b4eb6/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/CAR/DATA110","keyword":["earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-clouds-atmosphere-cloud-properties","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"last_harvested_date":"2026-09-23T01:07:09.414952","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"car-fireace-arctic-ice-and-cloud-radiation-l1-v1-car_fireace_l1c-at-ges-disc","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CAR FIREACE Arctic Ice and Cloud Radiation L1 V1 (CAR_FIREACE_L1C)","type":"dataset"},{"_score":16.054373,"_sort":[1790125629063,16.054373,2,"6c57d321-ad30-4617-81c9-4cc08caf2658"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"INTEX-B (Intercontinental Chemical Transport Experiment-Phase B) focuses on the long-range transport of pollution, global atmospheric photochemistry, and the effects of aerosols and clouds on radiation and climate. It has two phases: phase 1 of the study was performed in Mexico from March 1-20, 2006, and phase 2 was performed in April and May and focused on Asian City pollution outflow over the western Pacific.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1442068297-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_INTEXB_L1C.1/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_INTEXB_L1C.1/doc/CAR_README.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gsfc.nasa.gov/opendap/CAR/CAR_INTEXB_L1C.1/contents.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://car.gsfc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/CAR_INTEXB_L1C_1.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/CAR_INTEXB_L1C_1.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1442068297-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/CAR/DATA106","keyword":["earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-clouds-atmosphere-cloud-properties","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -99.451, \"NorthBoundingCoordinate\": 22.3245, \"EastBoundingCoordinate\": -93.5934, \"SouthBoundingCoordinate\": 19.0542}]]","temporal":"2006-03-03/2006-03-19","theme":["Earth Science"],"title":"CAR INTEX-B Long-range Pollution Transportation L1 V1 (CAR_INTEXB_L1C)"},"description":"INTEX-B (Intercontinental Chemical Transport Experiment-Phase B) focuses on the long-range transport of pollution, global atmospheric photochemistry, and the effects of aerosols and clouds on radiation and climate. It has two phases: phase 1 of the study was performed in Mexico from March 1-20, 2006, and phase 2 was performed in April and May and focused on Asian City pollution outflow over the western Pacific.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/52c70bac-6f4a-47b7-b1d3-ac5192e05612","harvest_record_raw":"https://catalog.data.gov/harvest_record/52c70bac-6f4a-47b7-b1d3-ac5192e05612/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/CAR/DATA106","keyword":["earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-clouds-atmosphere-cloud-properties","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"last_harvested_date":"2026-09-23T01:07:09.063125","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"car-intex-b-long-range-pollution-transportation-l1-v1-car_intexb_l1c-at-ges-disc","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CAR INTEX-B Long-range Pollution Transportation L1 V1 (CAR_INTEXB_L1C)","type":"dataset"},{"_score":15.2091055,"_sort":[1790125628402,15.2091055,1,"f2292494-f008-4d06-ac41-dafaef90f2e3"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"INTEX-B (Intercontinental Chemical Transport Experiment-Phase B) focuses on the long-range transport of pollution, global atmospheric photochemistry, and the effects of aerosols and clouds on radiation and climate. It has two phases: phase 1 of the study was performed in Mexico from March 1-20, 2006, and phase 2 was performed in April and May and focused on Asian City pollution outflow over the western Pacific.\n\nThis data set consists of observations made with the CAR instrument and includes values for bidirectional reflectance factor at varying spectral bands.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1617621688-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_INTEXB_BRDF.2/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/opendap/CAR/CAR_INTEXB_BRDF.2/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://car.gsfc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/CAR_INTEXB_BRDF_2.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/CAR/CAR_BRDF_README-v2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/CAR_INTEXB_L1C_1.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1617621688-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/W92WIC96B2CZ","keyword":["earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -99.451, \"NorthBoundingCoordinate\": 22.1784, \"EastBoundingCoordinate\": -93.9624, \"SouthBoundingCoordinate\": 19.1145}]]","temporal":"2006-03-03/2006-03-19","theme":["Earth Science"],"title":"CAR INTEXB BRDF Measurements L1 V2 (CAR_INTEXB_BRDF)"},"description":"INTEX-B (Intercontinental Chemical Transport Experiment-Phase B) focuses on the long-range transport of pollution, global atmospheric photochemistry, and the effects of aerosols and clouds on radiation and climate. It has two phases: phase 1 of the study was performed in Mexico from March 1-20, 2006, and phase 2 was performed in April and May and focused on Asian City pollution outflow over the western Pacific.\n\nThis data set consists of observations made with the CAR instrument and includes values for bidirectional reflectance factor at varying spectral bands.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/083375b0-a6bb-4b93-80f8-abbe0155ced6","harvest_record_raw":"https://catalog.data.gov/harvest_record/083375b0-a6bb-4b93-80f8-abbe0155ced6/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/W92WIC96B2CZ","keyword":["earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-ocean-optics-oceans-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"last_harvested_date":"2026-09-23T01:07:08.402210","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"car-intexb-brdf-measurements-l1-v2-car_intexb_brdf-at-ges-disc","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CAR INTEXB BRDF Measurements L1 V2 (CAR_INTEXB_BRDF)","type":"dataset"},{"_score":14.146361,"_sort":[1790125627744,14.146361,3,"cd972193-79c4-4deb-a09a-208924da43c0"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Southern African Regional Science Initiative (SAFARI) 2000 is an international science field campaign aimed at developing a better understanding of the southern Africa earth-atmosphere-human system. The goal of SAFARI 2000 is to identify and understand the relationship between the physical, chemical, biological, and anthropogenic processes that underlie the biogeophysical and biogeochemical systems of southern Africa. Particular emphasis will be placed upon biogenic, pyrogenic, and anthropogenic emissions - their characterization and quantification, their transport and transformations in the atmosphere, their influence on regional climate and meteorology, their eventual deposition, and the effects of this deposition on ecosystems.\n\nThis data set consists of observations made with the CAR instrument and includes values for bidirectional reflectance factor at varying spectral bands.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1617621691-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_SAFARI_BRDF.2/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/opendap/CAR/CAR_SAFARI_BRDF.2/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://car.gsfc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/CAR_SAFARI_BRDF_2.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/CAR/CAR_BRDF_README-v2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/CAR_SAFARI_L1C_1.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1617621691-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/RAQCJ0SV90IE","keyword":["earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": 13.0812, \"NorthBoundingCoordinate\": -14.8019, \"EastBoundingCoordinate\": 32.9708, \"SouthBoundingCoordinate\": -26.025}]]","temporal":"2000-08-20/2000-09-16","theme":["Earth Science"],"title":"CAR Safari BRDF Measurements L1 V2 (CAR_SAFARI_BRDF)"},"description":"The Southern African Regional Science Initiative (SAFARI) 2000 is an international science field campaign aimed at developing a better understanding of the southern Africa earth-atmosphere-human system. The goal of SAFARI 2000 is to identify and understand the relationship between the physical, chemical, biological, and anthropogenic processes that underlie the biogeophysical and biogeochemical systems of southern Africa. Particular emphasis will be placed upon biogenic, pyrogenic, and anthropogenic emissions - their characterization and quantification, their transport and transformations in the atmosphere, their influence on regional climate and meteorology, their eventual deposition, and the effects of this deposition on ecosystems.\n\nThis data set consists of observations made with the CAR instrument and includes values for bidirectional reflectance factor at varying spectral bands.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/218ebf58-ee53-4e09-8baa-0898ce122446","harvest_record_raw":"https://catalog.data.gov/harvest_record/218ebf58-ee53-4e09-8baa-0898ce122446/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/RAQCJ0SV90IE","keyword":["earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-surface-radiative-properties-land-surface-reflectance"],"last_harvested_date":"2026-09-23T01:07:07.744071","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":3,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"car-safari-brdf-measurements-l1-v2-car_safari_brdf-at-ges-disc","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CAR Safari BRDF Measurements L1 V2 (CAR_SAFARI_BRDF)","type":"dataset"},{"_score":15.10371,"_sort":[1790125627066,15.10371,2,"7f20d832-767b-42cd-87e3-8cdfd6879278"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Southern African Regional Science Initiative (SAFARI) 2000 is an international science field campaign aimed at developing a better understanding of the southern Africa earth-atmosphere-human system. The goal of SAFARI 2000 is to identify and understand the relationship between the physical, chemical, biological, and anthropogenic processes that underlie the biogeophysical and biogeochemical systems of southern Africa. Particular emphasis will be placed upon biogenic, pyrogenic, and anthropogenic emissions - their characterization and quantification, their transport and transformations in the atmosphere, their influence on regional climate and meteorology, their eventual deposition, and the effects of this deposition on ecosystems.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1442068302-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_SAFARI_L1C.1/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gesdisc.eosdis.nasa.gov/data/CAR/CAR_SAFARI_L1C.1/doc/CAR_README.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://acdisc.gsfc.nasa.gov/opendap/CAR/CAR_SAFARI_L1C.1/contents.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://car.gsfc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/CAR_SAFARI_L1C_1.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/CAR_SAFARI_L1C_1.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1442068302-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/CAR/DATA109","keyword":["earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-clouds-atmosphere-cloud-properties","earth-science-surface-radiative-properties-land-surface-reflectance"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": 11.9202, \"NorthBoundingCoordinate\": -14.6484, \"EastBoundingCoordinate\": 35.3494, \"SouthBoundingCoordinate\": -26.6243}]]","temporal":"2000-08-20/2000-09-16","theme":["Earth Science"],"title":"CAR Safari South African Biogeophysics and Biogeochemistry L1 V1 (CAR_SAFARI_L1C)"},"description":"The Southern African Regional Science Initiative (SAFARI) 2000 is an international science field campaign aimed at developing a better understanding of the southern Africa earth-atmosphere-human system. The goal of SAFARI 2000 is to identify and understand the relationship between the physical, chemical, biological, and anthropogenic processes that underlie the biogeophysical and biogeochemical systems of southern Africa. Particular emphasis will be placed upon biogenic, pyrogenic, and anthropogenic emissions - their characterization and quantification, their transport and transformations in the atmosphere, their influence on regional climate and meteorology, their eventual deposition, and the effects of this deposition on ecosystems.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/4e25a9f9-3d00-46a8-b4c8-d9884d03b001","harvest_record_raw":"https://catalog.data.gov/harvest_record/4e25a9f9-3d00-46a8-b4c8-d9884d03b001/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/CAR/DATA109","keyword":["earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-clouds-atmosphere-cloud-properties","earth-science-surface-radiative-properties-land-surface-reflectance"],"last_harvested_date":"2026-09-23T01:07:07.066925","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"car-safari-south-african-biogeophysics-and-biogeochemistry-l1-v1-car_safari_l1c-at-ges-dis","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CAR Safari South African Biogeophysics and Biogeochemistry L1 V1 (CAR_SAFARI_L1C)","type":"dataset"},{"_score":12.8337345,"_sort":[1790125620004,12.8337345,2,"c602b6a7-2047-4cda-a896-5050964a28b7"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"This dataset contains a series of land surface parameters simulated from the Noah 3.6.1 model in the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), adapted from Land Information System (LIS7).  The dataset contains 28 parameters in a 0.10 degree spatial resolution and from January 2019 to present. The temporal resolution is monthly and the spatial coverage is global (60S, 180W, 90N, 180E).  \n\nThe simulation was forced by a combination of the Global Data Assimilation System (GDAS) data and Climate Hazards Group InfraRed Precipitation with Station Preliminary (CHIRPS-PRELIM) 6-hourly rainfall data that has been downscaled using the NASA Land Data Toolkit, restarted from CHIRPS-FINAL of the previous month.  The simulation was initialized on January 1, 2019 using soil moisture and other state fields from a FLDAS/Noah model climatology for that day of the year.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2020765110-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2020765110-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/FLDAS_NOAH01_CP_GL_M_001.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/documents?title=Hydrology%2520Documentation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/howto?tags=hydrology","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/FLDAS_NOAH01_CP_GL_M_001.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/hydrology/README_FLDAS.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://giovanni.gsfc.nasa.gov/giovanni/#dataKeyword=FLDAS_NOAH01_CP_GL_M","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://hydro1.gesdisc.eosdis.nasa.gov/data/FLDAS/FLDAS_NOAH01_CP_GL_M.001/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ldas.gsfc.nasa.gov/FLDAS/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ldas.gsfc.nasa.gov/fldas/vegetation-class","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2020765110-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/L8GPRQWAWHE3","keyword":["earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-snow-ice-terrestrial-hydrosphere-snow-cover","earth-science-snow-ice-terrestrial-hydrosphere-snow-depth","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-soils-land-surface-soil-temperature","earth-science-surface-thermal-properties-land-surface-land-surface-temperature","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -60}]]","temporal":"2019-01-01/2026-09-07","theme":["Earth Science"],"title":"FLDAS Noah Land Surface Model L4 Global Monthly 0.1 x 0.1 degree (GDAS and CHIRPS-PRELIM) V001 (FLDAS_NOAH01_CP_GL_M)"},"description":"This dataset contains a series of land surface parameters simulated from the Noah 3.6.1 model in the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), adapted from Land Information System (LIS7).  The dataset contains 28 parameters in a 0.10 degree spatial resolution and from January 2019 to present. The temporal resolution is monthly and the spatial coverage is global (60S, 180W, 90N, 180E).  \n\nThe simulation was forced by a combination of the Global Data Assimilation System (GDAS) data and Climate Hazards Group InfraRed Precipitation with Station Preliminary (CHIRPS-PRELIM) 6-hourly rainfall data that has been downscaled using the NASA Land Data Toolkit, restarted from CHIRPS-FINAL of the previous month.  The simulation was initialized on January 1, 2019 using soil moisture and other state fields from a FLDAS/Noah model climatology for that day of the year.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/b92e0050-1466-441e-9160-14a0a170d6c5","harvest_record_raw":"https://catalog.data.gov/harvest_record/b92e0050-1466-441e-9160-14a0a170d6c5/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/L8GPRQWAWHE3","keyword":["earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-snow-ice-terrestrial-hydrosphere-snow-cover","earth-science-snow-ice-terrestrial-hydrosphere-snow-depth","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-soils-land-surface-soil-temperature","earth-science-surface-thermal-properties-land-surface-land-surface-temperature","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"last_harvested_date":"2026-09-23T01:07:00.004686","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"fldas-noah-land-surface-model-l4-global-monthly-0-1-x-0-1-degree-gdas-and-chirps-prelim-v0","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"FLDAS Noah Land Surface Model L4 Global Monthly 0.1 x 0.1 degree (GDAS and CHIRPS-PRELIM) V001 (FLDAS_NOAH01_CP_GL_M)","type":"dataset"},{"_score":7.8236275,"_sort":[1790125617753,7.8236275,1,"037fcfeb-1b7e-463b-b767-ffd509e4ec75"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2.  GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014.  GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present.  GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are \"open-loop\" (i.e., no data assimilation).  The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.\n\nThis data set, GLDAS-2.0 1.0 degree 3-hourly, contains a series of land surface variables simulated from the Catchment Land Surface Model 3.6 in Land Information System (LIS) Version 7.  The data set currently cover from January 1948 to December 2014, but will be extended as the forcing data becomes available. The GLDAS-2.0 data are archived and distributed in netCDF format. \n\nThe GLDAS-2.0 model simulations were initialized on January 1, 1948, using soil moisture and other state fields from the LSM climatology for that day of the year. The simulations were forced by the global meteorological forcing data set from Princeton University (Sheffield et al., 2006). Each simulation uses the common GLDAS data sets for land water mask (MOD44W: Carroll et al., 2009) and elevation (GTOPO30) along with the model default land cover and soils datasets. Catchment model uses the Mosaic land cover classification and soils, topographic, and other model-specific parameters were derived in a consistent manner as in the NASA/GMAO\u2019s GEOS-5 climate modeling system. The MODIS based land surface parameters are used in the current GLDAS-2.0 and GLDAS-2.1 products.\n\nIn October 2020, all 3-hourly and monthly GLDAS-2 data were post-processed with the MOD44W MODIS land mask.  Previously, some grid boxes over inland water were considered as over land and, thus, had non-missing values.  The post-processing corrected this issue and masked out all model output data over inland water; the post-processing did not affect the meteorological forcing variables. More information can be found in the GLDAS-2 README.  The MOD44W MODIS land mask is available on the GLDAS Project site.\n\nIf you had downloaded the GLDAS data prior to November 2020, please download the data again to receive the post-processed data.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1933574500-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C1933574500-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GLDAS_CLSM10_3H_2.0.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/documents?title=Hydrology%2520Documentation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/howto?tags=hydrology","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/GLDAS_CLSM10_3H_2.0.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/hydrology/README_GLDAS2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/GLDAS/GLDAS_CLM10SUBP_3H_Status_and_Related_Data_Collections.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/GLDAS/GLDAS_LSM_Description.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://hydro1.gesdisc.eosdis.nasa.gov/data/GLDAS/GLDAS_CLSM10_3H.2.0/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ldas.gsfc.nasa.gov/gldas/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1933574500-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/T3BX5Y6QK5FO","keyword":["earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-soils-land-surface-soil-temperature","earth-science-surface-thermal-properties-land-surface-land-surface-temperature","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -60}]]","temporal":"1948-01-01/2014-12-31","theme":["Earth Science"],"title":"GLDAS Catchment Land Surface Model L4 3 hourly 1.0 x 1.0 degree V2.0 (GLDAS_CLSM10_3H)"},"description":"NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2.  GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014.  GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present.  GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are \"open-loop\" (i.e., no data assimilation).  The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.\n\nThis data set, GLDAS-2.0 1.0 degree 3-hourly, contains a series of land surface variables simulated from the Catchment Land Surface Model 3.6 in Land Information System (LIS) Version 7.  The data set currently cover from January 1948 to December 2014, but will be extended as the forcing data becomes available. The GLDAS-2.0 data are archived and distributed in netCDF format. \n\nThe GLDAS-2.0 model simulations were initialized on January 1, 1948, using soil moisture and other state fields from the LSM climatology for that day of the year. The simulations were forced by the global meteorological forcing data set from Princeton University (Sheffield et al., 2006). Each simulation uses the common GLDAS data sets for land water mask (MOD44W: Carroll et al., 2009) and elevation (GTOPO30) along with the model default land cover and soils datasets. Catchment model uses the Mosaic land cover classification and soils, topographic, and other model-specific parameters were derived in a consistent manner as in the NASA/GMAO\u2019s GEOS-5 climate modeling system. The MODIS based land surface parameters are used in the current GLDAS-2.0 and GLDAS-2.1 products.\n\nIn October 2020, all 3-hourly and monthly GLDAS-2 data were post-processed with the MOD44W MODIS land mask.  Previously, some grid boxes over inland water were considered as over land and, thus, had non-missing values.  The post-processing corrected this issue and masked out all model output data over inland water; the post-processing did not affect the meteorological forcing variables. More information can be found in the GLDAS-2 README.  The MOD44W MODIS land mask is available on the GLDAS Project site.\n\nIf you had downloaded the GLDAS data prior to November 2020, please download the data again to receive the post-processed data.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/d6293a01-b9bc-4427-8f20-7bd8276f2b1b","harvest_record_raw":"https://catalog.data.gov/harvest_record/d6293a01-b9bc-4427-8f20-7bd8276f2b1b/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/T3BX5Y6QK5FO","keyword":["earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-soils-land-surface-soil-temperature","earth-science-surface-thermal-properties-land-surface-land-surface-temperature","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"last_harvested_date":"2026-09-23T01:06:57.753658","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gldas-catchment-land-surface-model-l4-3-hourly-1-0-x-1-0-degree-v2-0-gldas_clsm10_3h-at-ge","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GLDAS Catchment Land Surface Model L4 3 hourly 1.0 x 1.0 degree V2.0 (GLDAS_CLSM10_3H)","type":"dataset"},{"_score":8.458166,"_sort":[1790125617420,8.458166,3,"0c2980d2-72a4-400e-a2ef-fb7fee5dfc33"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2.  GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014.  GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present.  GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are \"open-loop\" (i.e., no data assimilation).  The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.\n\nGLDAS-2.2 is new to the GES DISC archive and currently includes a main product from CLSM-F2.5 with Data Assimilation for the Gravity Recovery and Climate Experiment (GRACE-DA) from February 2003 to present.  The GLDAS-2.2 data are available in two production streams: one with GRACE data assimilation outputs (the main production stream), and one without GRACE-DA (the early production stream).  Since the GRACE data have a 2-6 month latency, the GLDAS-2.2 data are first created without GRACE-DA, and are designated as the Early Product (EP), with about 1 month latency.  Once the GRACE data become available, the GLDAS-2.2 data are processed with GRACE-DA in the main production stream and are removed from the Early Product archive.  \n\nThe GLDAS-2.2 GRACE-DA product was simulated with Catchment-F2.5 in Land Information System (LIS) Version 7. The data product contains 24 land surface fields from February 1, 2003 to present.\n\nThe simulation started on February 1, 2003 using the conditions from the GLDAS-2.0 Daily Catchment model simulation, forced with the meteorological analysis fields from the operational European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System.  The total terrestrial water anomaly observation from GRACE satellite was assimilated (Li et al, 2019). Due to the data agreement with ECMWF, this GLDAS-2.2 daily product does not include the meteorological forcing fields.\n\nThe GLDAS-2.2 data are archived and distributed in NetCDF format.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1700900796-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C1700900796-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GLDAS_CLSM025_DA1_D_2.2.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/documents?title=Hydrology%2520Documentation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/howto?tags=hydrology","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/GLDAS_CLSM025_DA1_D_2.2.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/hydrology/README_GLDAS2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/GLDAS/GLDAS_CLM10SUBP_3H_Status_and_Related_Data_Collections.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/GLDAS/GLDAS_LSM_Description.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://giovanni.gsfc.nasa.gov/giovanni/#dataKeyword=GLDAS_CLSM025_DA1_D_2_2","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://hydro1.gesdisc.eosdis.nasa.gov/data/GLDAS/GLDAS_CLSM025_DA1_D.2.2/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ldas.gsfc.nasa.gov/gldas/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1700900796-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/TXBMLX370XX8","keyword":["earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-ground-water-terrestrial-hydrosphere","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-soils-land-surface-soil-temperature","earth-science-surface-thermal-properties-land-surface-land-surface-temperature","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -60}]]","temporal":"2003-02-01/2026-09-07","theme":["Earth Science"],"title":"GLDAS Catchment Land Surface Model L4 daily 0.25 x 0.25 degree GRACE-DA1 V2.2 (GLDAS_CLSM025_DA1_D)"},"description":"NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2.  GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014.  GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present.  GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are \"open-loop\" (i.e., no data assimilation).  The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.\n\nGLDAS-2.2 is new to the GES DISC archive and currently includes a main product from CLSM-F2.5 with Data Assimilation for the Gravity Recovery and Climate Experiment (GRACE-DA) from February 2003 to present.  The GLDAS-2.2 data are available in two production streams: one with GRACE data assimilation outputs (the main production stream), and one without GRACE-DA (the early production stream).  Since the GRACE data have a 2-6 month latency, the GLDAS-2.2 data are first created without GRACE-DA, and are designated as the Early Product (EP), with about 1 month latency.  Once the GRACE data become available, the GLDAS-2.2 data are processed with GRACE-DA in the main production stream and are removed from the Early Product archive.  \n\nThe GLDAS-2.2 GRACE-DA product was simulated with Catchment-F2.5 in Land Information System (LIS) Version 7. The data product contains 24 land surface fields from February 1, 2003 to present.\n\nThe simulation started on February 1, 2003 using the conditions from the GLDAS-2.0 Daily Catchment model simulation, forced with the meteorological analysis fields from the operational European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System.  The total terrestrial water anomaly observation from GRACE satellite was assimilated (Li et al, 2019). Due to the data agreement with ECMWF, this GLDAS-2.2 daily product does not include the meteorological forcing fields.\n\nThe GLDAS-2.2 data are archived and distributed in NetCDF format.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/edea1c9a-05fc-4bde-921c-37313cd80e53","harvest_record_raw":"https://catalog.data.gov/harvest_record/edea1c9a-05fc-4bde-921c-37313cd80e53/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/TXBMLX370XX8","keyword":["earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-ground-water-terrestrial-hydrosphere","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-soils-land-surface-soil-temperature","earth-science-surface-thermal-properties-land-surface-land-surface-temperature","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"last_harvested_date":"2026-09-23T01:06:57.420540","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":3,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gldas-catchment-land-surface-model-l4-daily-0-25-x-0-25-degree-grace-da1-v2-2-gldas_clsm02-959a4","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GLDAS Catchment Land Surface Model L4 daily 0.25 x 0.25 degree GRACE-DA1 V2.2 (GLDAS_CLSM025_DA1_D)","type":"dataset"},{"_score":10.367707,"_sort":[1790125616719,10.367707,1,"7f6e2b85-11c6-40b2-8cb4-551b31a2f04e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"With the upgraded Land Surface Models (LSMs) and updated forcing data sets, the GLDAS version 2.1 (GLDAS-2.1) production stream serves as a replacement for GLDAS-001. The entire GLDAS-001 collection from January 1979 through March 2020 was decommissioned on June 30, 2020 and removed from the GES DISC system. For more information, please see the IMPORTANT NOTICE document.\n\nThis data set contains a series of land surface parameters simulated from the Common Land Model (CLM) V2.0 model in the Global Land Data Assimilation System (GLDAS). The data are in 1.0 degree resolution and range from January 1979 to present. The temporal resolution is 3-hourly. \n\nThis simulation was forced by a combination of NOAA/GDAS atmospheric analysis fields, spatially and temporally disaggregated NOAA Climate Prediction Center Merged Analysis of Precipitation (CMAP) fields, and observation based downward shortwave and longwave radiation fields derived using the method of the Air Force Weather Agency's AGRicultural METeorological modeling system (AGRMET). The simulation was initialized on 1 January 1979 using soil moisture and other state fields from a GLDAS/CLM model climatology for that day of the year. \n\nWGRIB or another GRIB reader is required to read the files. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1279404074-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GLDAS_CLM10SUBP_3H_001.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/documents?title=Hydrology%2520Documentation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/howto?tags=hydrology","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/GLDAS_CLM10SUBP_3H_001.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/GLDAS/GLDAS_CLM10SUBP_3H_Status_and_Related_Data_Collections.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/GLDAS/GLDAS_LSM_Description.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://ldas.gsfc.nasa.gov/gldas/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1279404074-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/83NO2QDLG6M0","keyword":["earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-soils-land-surface-soil-temperature","earth-science-surface-thermal-properties-land-surface-land-surface-temperature","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -60}]]","temporal":"1979-01-02/2020-03-31","theme":["Earth Science"],"title":"GLDAS CLM Land Surface Model L4 3 hourly 1.0 x 1.0 degree Subsetted V001 (GLDAS_CLM10SUBP_3H)"},"description":"With the upgraded Land Surface Models (LSMs) and updated forcing data sets, the GLDAS version 2.1 (GLDAS-2.1) production stream serves as a replacement for GLDAS-001. The entire GLDAS-001 collection from January 1979 through March 2020 was decommissioned on June 30, 2020 and removed from the GES DISC system. For more information, please see the IMPORTANT NOTICE document.\n\nThis data set contains a series of land surface parameters simulated from the Common Land Model (CLM) V2.0 model in the Global Land Data Assimilation System (GLDAS). The data are in 1.0 degree resolution and range from January 1979 to present. The temporal resolution is 3-hourly. \n\nThis simulation was forced by a combination of NOAA/GDAS atmospheric analysis fields, spatially and temporally disaggregated NOAA Climate Prediction Center Merged Analysis of Precipitation (CMAP) fields, and observation based downward shortwave and longwave radiation fields derived using the method of the Air Force Weather Agency's AGRicultural METeorological modeling system (AGRMET). The simulation was initialized on 1 January 1979 using soil moisture and other state fields from a GLDAS/CLM model climatology for that day of the year. \n\nWGRIB or another GRIB reader is required to read the files. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/e2be7b3d-6fc4-4853-a67d-614976bd65d5","harvest_record_raw":"https://catalog.data.gov/harvest_record/e2be7b3d-6fc4-4853-a67d-614976bd65d5/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/83NO2QDLG6M0","keyword":["earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-soils-land-surface-soil-temperature","earth-science-surface-thermal-properties-land-surface-land-surface-temperature","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"last_harvested_date":"2026-09-23T01:06:56.719064","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gldas-clm-land-surface-model-l4-3-hourly-1-0-x-1-0-degree-subsetted-v001-gldas_clm10subp_3","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GLDAS CLM Land Surface Model L4 3 hourly 1.0 x 1.0 degree Subsetted V001 (GLDAS_CLM10SUBP_3H)","type":"dataset"},{"_score":7.340906,"_sort":[1790125614781,7.340906,1,"4c36c73f-b402-4012-a823-06c81ec1e75a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2.  GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014.  GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present.  GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are \"open-loop\" (i.e., no data assimilation).  The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.\n\nThis data set,  GLDAS-2.0 VIC monthly 1.0 degree, contains a series of land surface variables generated through temporal averaging of GLDAS-2.0 3-hourly data simulated with the VIC 4.1.2 Land Surface Model in Land Information System (LIS) Version 7. The data set currently cover from January 1948 to December 2014, but will be extended as the forcing data becomes available. The GLDAS-2.0 data are archived and distributed in NetCDF format.\n\nThe GLDAS-2.0 model simulations were initialized on January 1, 1948, using soil moisture and other state fields from the LSM climatology for that day of the year. The simulations were forced by the global meteorological forcing data set from Princeton University (Sheffield et al., 2006). Each simulation uses the common GLDAS data sets for land water mask (MOD44W: Carroll et al., 2009) and elevation (GTOPO30) along with the model default land cover and soils datasets. Catchment model uses the Mosaic land cover classification and soils, topographic, and other model-specific parameters were derived in a consistent manner as in the NASA/GMAO\u2019s GEOS-5 climate modeling system. The MODIS based land surface parameters are used in the current GLDAS-2.0 and GLDAS-2.1 products.\n\nIn October 2020, all 3-hourly and monthly GLDAS-2 data were post-processed with the MOD44W MODIS land mask.  Previously, some grid boxes over inland water were considered as over land and, thus, had non-missing values.  The post-processing corrected this issue and masked out all model output data over inland water; the post-processing did not affect the meteorological forcing variables. More information can be found in the GLDAS-2 README.  The MOD44W MODIS land mask is available on the GLDAS Project site.\n\nIf you had downloaded the GLDAS data prior to November 2020, please download the data again to receive the post-processed data.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1933574565-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C1933574565-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GLDAS_VIC10_M_2.0.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/documents?title=Hydrology%2520Documentation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/howto?tags=hydrology","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/GLDAS_VIC10_M_2.0.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/hydrology/README_GLDAS2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/GLDAS/GLDAS_CLM10SUBP_3H_Status_and_Related_Data_Collections.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/repository/Mission/GLDAS/GLDAS_LSM_Description.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://hydro1.gesdisc.eosdis.nasa.gov/data/GLDAS/GLDAS_VIC10_M.2.0/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ldas.gsfc.nasa.gov/gldas/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1933574565-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/ZRIHVF29X43C","keyword":["earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-soils-land-surface-soil-temperature","earth-science-surface-thermal-properties-land-surface-land-surface-temperature","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -60}]]","temporal":"1948-01-01/2014-12-31","theme":["Earth Science"],"title":"GLDAS VIC Land Surface Model L4 monthly 1.0 x 1.0 degree V2.0 (GLDAS_VIC10_M)"},"description":"NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2.  GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014.  GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present.  GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are \"open-loop\" (i.e., no data assimilation).  The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.\n\nThis data set,  GLDAS-2.0 VIC monthly 1.0 degree, contains a series of land surface variables generated through temporal averaging of GLDAS-2.0 3-hourly data simulated with the VIC 4.1.2 Land Surface Model in Land Information System (LIS) Version 7. The data set currently cover from January 1948 to December 2014, but will be extended as the forcing data becomes available. The GLDAS-2.0 data are archived and distributed in NetCDF format.\n\nThe GLDAS-2.0 model simulations were initialized on January 1, 1948, using soil moisture and other state fields from the LSM climatology for that day of the year. The simulations were forced by the global meteorological forcing data set from Princeton University (Sheffield et al., 2006). Each simulation uses the common GLDAS data sets for land water mask (MOD44W: Carroll et al., 2009) and elevation (GTOPO30) along with the model default land cover and soils datasets. Catchment model uses the Mosaic land cover classification and soils, topographic, and other model-specific parameters were derived in a consistent manner as in the NASA/GMAO\u2019s GEOS-5 climate modeling system. The MODIS based land surface parameters are used in the current GLDAS-2.0 and GLDAS-2.1 products.\n\nIn October 2020, all 3-hourly and monthly GLDAS-2 data were post-processed with the MOD44W MODIS land mask.  Previously, some grid boxes over inland water were considered as over land and, thus, had non-missing values.  The post-processing corrected this issue and masked out all model output data over inland water; the post-processing did not affect the meteorological forcing variables. More information can be found in the GLDAS-2 README.  The MOD44W MODIS land mask is available on the GLDAS Project site.\n\nIf you had downloaded the GLDAS data prior to November 2020, please download the data again to receive the post-processed data.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/5c1bc323-c1b1-4949-87a6-d04848999dc1","harvest_record_raw":"https://catalog.data.gov/harvest_record/5c1bc323-c1b1-4949-87a6-d04848999dc1/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/ZRIHVF29X43C","keyword":["earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-soils-land-surface-soil-temperature","earth-science-surface-thermal-properties-land-surface-land-surface-temperature","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"last_harvested_date":"2026-09-23T01:06:54.781393","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gldas-vic-land-surface-model-l4-monthly-1-0-x-1-0-degree-v2-0-gldas_vic10_m-at-ges-disc","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GLDAS VIC Land Surface Model L4 monthly 1.0 x 1.0 degree V2.0 (GLDAS_VIC10_M)","type":"dataset"},{"_score":11.536358,"_sort":[1790125613478,11.536358,1,"69d65c0a-8578-4140-a725-6fdd0d388e67"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this project entitled \u201cMulti-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS)\u201d will develop consistent long-term global trend-quality data records spanning the last two decades, over which remarkable changes in nitrogen oxides (NOx) emissions have occurred. The objective of the project Is to adapt Ozone Monitoring Instrument (OMI) operational algorithms to other satellite instruments and create consistent multi-satellite L2 and L3 nitrogen dioxide (NO2) columns and value-added L4 surface NO2 concentrations and NOx emissions data products, systematically accounting for instrumental differences. The instruments include Global Ozone Monitoring Experiment (GOME, 1996-2003), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY, 2002-2012), OMI (2004-present), GOME-2 (2007-present), and TROPOspheric Monitoring Instrument (TROPOMI, 2018-present). The quality assured L2-L4 products will be made available to the scientific community via the NASA GES DISC website in Climate and Forecast (CF)-compliant Hierarchical Data Format (HDF5) and netCDF formats.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2539362687-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GOME_MINDS_NO2_1.1.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/GOME_MINDS_NO2_1.1.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://earthdata.nasa.gov/esds/competitive-programs/measures/minds","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://measures.gesdisc.eosdis.nasa.gov/data/MINDS/GOME_MINDS_NO2.1.1/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://measures.gesdisc.eosdis.nasa.gov/data/MINDS/GOME_MINDS_NO2.1.1/doc/README.MEaSUREs_MINDS_NO2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://measures.gesdisc.eosdis.nasa.gov/opendap/hyrax/MINDS/GOME_MINDS_NO2.1.1/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2539362687-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/MEASURES/MINDS/DATA202","keyword":["earth-science-atmospheric-chemistry-atmosphere-nitrogen-compounds"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"1995-06-30/2003-06-22","theme":["Earth Science"],"title":"GOME/ERS-2 NO2 Tropospheric, Stratospheric and Total Columns MINDS 1-Orbit L2 Swath 40 km x 320 km V1.1 (GOME_MINDS_NO2)"},"description":"As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this project entitled \u201cMulti-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS)\u201d will develop consistent long-term global trend-quality data records spanning the last two decades, over which remarkable changes in nitrogen oxides (NOx) emissions have occurred. The objective of the project Is to adapt Ozone Monitoring Instrument (OMI) operational algorithms to other satellite instruments and create consistent multi-satellite L2 and L3 nitrogen dioxide (NO2) columns and value-added L4 surface NO2 concentrations and NOx emissions data products, systematically accounting for instrumental differences. The instruments include Global Ozone Monitoring Experiment (GOME, 1996-2003), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY, 2002-2012), OMI (2004-present), GOME-2 (2007-present), and TROPOspheric Monitoring Instrument (TROPOMI, 2018-present). The quality assured L2-L4 products will be made available to the scientific community via the NASA GES DISC website in Climate and Forecast (CF)-compliant Hierarchical Data Format (HDF5) and netCDF formats.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/0af89032-4f52-4ede-b6c8-5affb30c8047","harvest_record_raw":"https://catalog.data.gov/harvest_record/0af89032-4f52-4ede-b6c8-5affb30c8047/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/MEASURES/MINDS/DATA202","keyword":["earth-science-atmospheric-chemistry-atmosphere-nitrogen-compounds"],"last_harvested_date":"2026-09-23T01:06:53.478916","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gome-ers-2-no2-tropospheric-stratospheric-and-total-columns-minds-1-orbit-l2-swath-40-km-x","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GOME/ERS-2 NO2 Tropospheric, Stratospheric and Total Columns MINDS 1-Orbit L2 Swath 40 km x 320 km V1.1 (GOME_MINDS_NO2)","type":"dataset"},{"_score":10.416845,"_sort":[1790125611873,10.416845,1,"1e70fac7-417d-442e-97b9-6eca9c3b6826"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 3.3 is the current version. Older versions have been superseded by Version 3.3.\n\nProduct latency/update: The products are currently paused at September 2024 because the IR input dataset from NCEI requires a new calibration scheme to extend past that point. Once NCEI irons out the calibration, we expect to return to quarterly updates.\n\nThe Global Precipitation Climatology Project (GPCP) is the precipitation component of an internationally coordinated set of (mainly) satellite-based global products dealing with the Earth's water and energy cycles, under the auspices of the Global Water and Energy Exchange (GEWEX) Data and Assessment Panel (GDAP) of the World Climate Research Program.  As the follow on to the GPCP Version 1.3 One Degree Daily product, GPCP Version 3 (GPCP V3.3) seeks to continue the long, homogeneous precipitation record using modern merging techniques and input data sets.  The GPCPV3 suite currently consists of the 0.5-degree Monthly and 0.5-degree Daily. Additional products may be added, which consist of (1) 0.5-degree pentad and (2) 0.1-degree 3-hourly.  All GPCPV3 products will be internally consistent.  Inputs consist of GPM IMERG in the span 55\u00b0N-S, and TOVS/AIRS estimates, adjusted climatologically to IMERG, outside 55\u00b0N-S.  The Daily estimates are scaled to approximately sum to the Monthly value at each 0.5\u00b0 grid box.  In addition to the final precipitation field, probability of liquid phase estimates are provided globally.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3405928682-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPCPDAY_3.3.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/GPCPDAY_V33.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/MEaSUREs/GPCP/GPCP_ATBD_V3.3_Daily.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/MEaSUREs/GPCP/Release_Notes.GPCPV3.3.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://giovanni.gsfc.nasa.gov/giovanni/#dataKeyword=GPCP%20daily%20V3.3","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://measures.gesdisc.eosdis.nasa.gov/data/GPCP/GPCPDAY.3.3/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://measures.gesdisc.eosdis.nasa.gov/data/GPCP/GPCPDAY.3.3/doc/README.GPCPV3.3_Daily.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://measures.gesdisc.eosdis.nasa.gov/opendap/GPCP/GPCPDAY.3.3/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3405928682-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/MEASURES/GPCP/DATA307","keyword":["earth-science-precipitation-atmosphere","earth-science-precipitation-atmosphere-precipitation-rate"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"1998-01-01/2025-12-31","theme":["Earth Science"],"title":"GPCP Precipitation Level 3 Daily 0.5-Degree V3.3 (GPCPDAY)"},"description":"Version 3.3 is the current version. Older versions have been superseded by Version 3.3.\n\nProduct latency/update: The products are currently paused at September 2024 because the IR input dataset from NCEI requires a new calibration scheme to extend past that point. Once NCEI irons out the calibration, we expect to return to quarterly updates.\n\nThe Global Precipitation Climatology Project (GPCP) is the precipitation component of an internationally coordinated set of (mainly) satellite-based global products dealing with the Earth's water and energy cycles, under the auspices of the Global Water and Energy Exchange (GEWEX) Data and Assessment Panel (GDAP) of the World Climate Research Program.  As the follow on to the GPCP Version 1.3 One Degree Daily product, GPCP Version 3 (GPCP V3.3) seeks to continue the long, homogeneous precipitation record using modern merging techniques and input data sets.  The GPCPV3 suite currently consists of the 0.5-degree Monthly and 0.5-degree Daily. Additional products may be added, which consist of (1) 0.5-degree pentad and (2) 0.1-degree 3-hourly.  All GPCPV3 products will be internally consistent.  Inputs consist of GPM IMERG in the span 55\u00b0N-S, and TOVS/AIRS estimates, adjusted climatologically to IMERG, outside 55\u00b0N-S.  The Daily estimates are scaled to approximately sum to the Monthly value at each 0.5\u00b0 grid box.  In addition to the final precipitation field, probability of liquid phase estimates are provided globally.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/04682e7b-e53a-4067-adeb-30a067304902","harvest_record_raw":"https://catalog.data.gov/harvest_record/04682e7b-e53a-4067-adeb-30a067304902/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/MEASURES/GPCP/DATA307","keyword":["earth-science-precipitation-atmosphere","earth-science-precipitation-atmosphere-precipitation-rate"],"last_harvested_date":"2026-09-23T01:06:51.873495","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpcp-precipitation-level-3-daily-0-5-degree-v3-3-gpcpday-at-ges-disc","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPCP Precipitation Level 3 Daily 0.5-Degree V3.3 (GPCPDAY)","type":"dataset"},{"_score":18.043762,"_sort":[1790125608569,18.043762,1,"7dd71175-8de8-4724-9ebb-e10749d8fde2"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 08 is the current version of the data set. Older versions are no longer available and have been superseded by the current version.\n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\nThe 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: GMI, SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18) AMSR2 (GCOM-W1), TMI MHS (NOAA 18&19, METOP A&B), ATMS (NPP), SAPHIR (MT1) This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 16 x 18 km  (cross-track x along-track nominal at nadir).","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C4054954559-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/L1C_ATBD_GPM_V08.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/V08_L1C_Release_Notes.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954559-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954559-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_1CGCOMW1AMSR2_08.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_1CGCOMW1AMSR2_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C4054954559-GES_DISC&q=GPM_1CGCOMW1AMSR2_08","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://suzaku.eorc.jaxa.jp/GCOM_W/w_amsr2/amsr2_body_main.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/amsr2.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/MHS/NOAA18/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2005-05-25/2018-10-20","theme":["Earth Science"],"title":"GPM MHS on NOAA-18 (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V08 (GPM_2AGPROFNOAA18MHS_CLIM)"},"description":"Version 08 is the current version of the data set. Older versions are no longer available and have been superseded by the current version.\n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\nThe 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: GMI, SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18) AMSR2 (GCOM-W1), TMI MHS (NOAA 18&19, METOP A&B), ATMS (NPP), SAPHIR (MT1) This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 16 x 18 km  (cross-track x along-track nominal at nadir).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/a1d2aa43-e31c-4567-8303-55225d1d16dc","harvest_record_raw":"https://catalog.data.gov/harvest_record/a1d2aa43-e31c-4567-8303-55225d1d16dc/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/MHS/NOAA18/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:48.569924","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-noaa-18-gprof-radiometer-precipitation-profiling-l2a-1-5-hours-17-km-v08-gpm_2a","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM MHS on NOAA-18 (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V08 (GPM_2AGPROFNOAA18MHS_CLIM)","type":"dataset"},{"_score":40.660015,"_sort":[1790125607907,40.660015,1,"a1cd5cb5-a1c2-4c4a-bb91-09970d5b89ca"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 08 is the current version of the data set. Older versions will no longer be available and have been superseded by the current version.\n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 13 x 13 km (nominal at nadir).","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C4054954520-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/GPROFV08A_releasenotes.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954520-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954520-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFF08SSMI_CLIM_08.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFF08SSMI_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C4054954520-GES_DISC&q=GPM_2AGPROFF08SSMI_CLIM_08","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.wmo-sat.info/oscar/instruments/view/533","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/SSMI/F08/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"1987-07-09/1991-12-31","theme":["Earth Science"],"title":"GPM SSM/I on F08 (GPROF) Climate-based Radiometer Precipitation Profiling L2 1.5 hours 12 km V08 (GPM_2AGPROFF08SSMI_CLIM)"},"description":"Version 08 is the current version of the data set. Older versions will no longer be available and have been superseded by the current version.\n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 13 x 13 km (nominal at nadir).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/02fcede5-2233-46ef-b85b-aa56d1c0b268","harvest_record_raw":"https://catalog.data.gov/harvest_record/02fcede5-2233-46ef-b85b-aa56d1c0b268/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/SSMI/F08/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:47.907203","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-ssm-i-on-f08-gprof-climate-based-radiometer-precipitation-profiling-l2-1-5-hours-12-km-d01d2","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM SSM/I on F08 (GPROF) Climate-based Radiometer Precipitation Profiling L2 1.5 hours 12 km V08 (GPM_2AGPROFF08SSMI_CLIM)","type":"dataset"},{"_score":40.56013,"_sort":[1790125607585,40.56013,2,"752af18c-0c69-4034-8bb6-a0e7e923efa8"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 08 is the current version of the data set. Older versions will no longer be available and have been superseded by the current version.\n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 13 x 13 km (nominal at nadir).","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C4054954946-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/GPROFV08A_releasenotes.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954946-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954946-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFF10SSMI_CLIM_08.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFF10SSMI_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C4054954946-GES_DISC&q=GPM_2AGPROFF10SSMI_CLIM_08","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.wmo-sat.info/oscar/instruments/view/533","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/SSMI/F10/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"1990-12-08/1997-11-14","theme":["Earth Science"],"title":"GPM SSM/I on F10 (GPROF) Climate-based Radiometer Precipitation Profiling L2 1.5 hours 12 km V08 (GPM_2AGPROFF10SSMI_CLIM)"},"description":"Version 08 is the current version of the data set. Older versions will no longer be available and have been superseded by the current version.\n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 13 x 13 km (nominal at nadir).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/883a5688-18f8-4017-ab35-e63e53512cf4","harvest_record_raw":"https://catalog.data.gov/harvest_record/883a5688-18f8-4017-ab35-e63e53512cf4/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/SSMI/F10/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:47.585208","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-ssm-i-on-f10-gprof-climate-based-radiometer-precipitation-profiling-l2-1-5-hours-12-km-48d11","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM SSM/I on F10 (GPROF) Climate-based Radiometer Precipitation Profiling L2 1.5 hours 12 km V08 (GPM_2AGPROFF10SSMI_CLIM)","type":"dataset"},{"_score":40.660015,"_sort":[1790125607273,40.660015,1,"6fa9640e-4fc0-415f-8c0f-584f5d63d476"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 08 is the current version of the data set. Older versions will no longer be available and have been superseded by the current version.\n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 13 x 13 km (nominal at nadir).","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C4054954932-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/GPROFV08A_releasenotes.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954932-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954932-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFF11SSMI_CLIM_08.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFF11SSMI_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C4054954932-GES_DISC&q=GPM_2AGPROFF11SSMI_CLIM_08","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.wmo-sat.info/oscar/instruments/view/533","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/SSMI/F11/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"1991-12-03/2000-05-16","theme":["Earth Science"],"title":"GPM SSM/I on F11 (GPROF) Climate-based Radiometer Precipitation Profiling L2 1.5 hours 13 km V08 (GPM_2AGPROFF11SSMI_CLIM)"},"description":"Version 08 is the current version of the data set. Older versions will no longer be available and have been superseded by the current version.\n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 13 x 13 km (nominal at nadir).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/c9793d3c-2f74-43e7-a47f-0edcabd1a6c7","harvest_record_raw":"https://catalog.data.gov/harvest_record/c9793d3c-2f74-43e7-a47f-0edcabd1a6c7/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/SSMI/F11/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:47.273329","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-ssm-i-on-f11-gprof-climate-based-radiometer-precipitation-profiling-l2-1-5-hours-13-km-29e91","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM SSM/I on F11 (GPROF) Climate-based Radiometer Precipitation Profiling L2 1.5 hours 13 km V08 (GPM_2AGPROFF11SSMI_CLIM)","type":"dataset"},{"_score":40.478935,"_sort":[1790125606946,40.478935,1,"a489dbc3-7694-421d-8b77-eb3a9d9fe5b4"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 08 is the current version of the data set. Older versions will no longer be available and have been superseded by the current version.\n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 13 x 13 km (nominal at nadir).","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C4054954554-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/GPROFV08A_releasenotes.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954554-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954554-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFF13SSMI_CLIM_08.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFF13SSMI_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C4054954554-GES_DISC&q=GPM_2AGPROFF13SSMI_CLIM_08","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.wmo-sat.info/oscar/instruments/view/533","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/SSMI/F13/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"1995-05-03/2009-11-20","theme":["Earth Science"],"title":"GPM SSM/I on F13 (GPROF) Climate-based Radiometer Precipitation Profiling L2 1.5 hours 12 km V08 (GPM_2AGPROFF13SSMI_CLIM)"},"description":"Version 08 is the current version of the data set. Older versions will no longer be available and have been superseded by the current version.\n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 13 x 13 km (nominal at nadir).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/7967b784-11a7-45a4-907a-85d1bf5639d0","harvest_record_raw":"https://catalog.data.gov/harvest_record/7967b784-11a7-45a4-907a-85d1bf5639d0/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/SSMI/F13/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:46.946353","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-ssm-i-on-f13-gprof-climate-based-radiometer-precipitation-profiling-l2-1-5-hours-12-km-77a73","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM SSM/I on F13 (GPROF) Climate-based Radiometer Precipitation Profiling L2 1.5 hours 12 km V08 (GPM_2AGPROFF13SSMI_CLIM)","type":"dataset"},{"_score":41.050385,"_sort":[1790125606634,41.050385,0,"6527116e-1204-47df-a848-94c4ab9671f7"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 08 is the current version of the data set. Older versions will no longer be available and have been superseded by the current version.\n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 13 x 13 km (nominal at nadir).","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C4054954885-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/GPROFV08A_releasenotes.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954885-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4054954885-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFF15SSMI_CLIM_08.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFF15SSMI_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C4054954885-GES_DISC&q=GPM_2AGPROFF15SSMI_CLIM_08","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.wmo-sat.info/oscar/instruments/view/533","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/SSMI/F15/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2000-02-23/2006-08-14","theme":["Earth Science"],"title":"GPM SSM/I on F15 (GPROF) Climate-based Radiometer Precipitation Profiling L2 1.5 hours 12 km V08 (GPM_2AGPROFF15SSMI_CLIM)"},"description":"Version 08 is the current version of the data set. Older versions will no longer be available and have been superseded by the current version.\n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.\n\n GPM Project generated these data at spatial sampling of 13 x 13 km (nominal at nadir).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/2113bfb3-a19c-4e7c-b5be-daa878705f53","harvest_record_raw":"https://catalog.data.gov/harvest_record/2113bfb3-a19c-4e7c-b5be-daa878705f53/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/SSMI/F15/GPROFCLIM/2A/08","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:46.634787","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":0,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-ssm-i-on-f15-gprof-climate-based-radiometer-precipitation-profiling-l2-1-5-hours-12-km-ae7cd","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM SSM/I on F15 (GPROF) Climate-based Radiometer Precipitation Profiling L2 1.5 hours 12 km V08 (GPM_2AGPROFF15SSMI_CLIM)","type":"dataset"},{"_score":9.571857,"_sort":[1790125592680,9.571857,1,"00654222-f9b3-462b-b60c-acef5bf791a0"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Sentinel-5P TROPOMI Near Real Time (NRT)  Tropospheric NO2 1-Orbit L2 5.5km x 3.5km V2 (S5P_L2__NO2____HiR_NRT)  is the near real time version of the offline S5P_L2__NO2____HiR data product. These data are typically available within three hours of measurement as required by the Land Atmosphere NRT Capability Earth Observing System (LANCE). These data are intended for a rapid turnaround assessment and are only archived for up to ten days. Users who require a longer data record, or wish to conduct rigorous analysis should use the offline version of this product S5P_L2__NO2____HiR.\n\nThe Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.\n\nThe TROPOMI retrieval of total and tropospheric NO2, is based on the DOMINO approach, a DOAS retrieval, a pre-calculated air-mass factor (AMF) look-up table, and a data assimilation/chemistry transport model for the separation of the stratospheric and tropospheric contributions to the NO2 column. It also include many retrieval developments of the European Quality Assurance for Essential Climate Variables (QA4ECV) project. Data are stored in individual files, or granules, that contain one orbit of information. The data are stored in netCDF4 data format and files and complete files are ~60 MB.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3412185684-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3412185684-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/S5P_L2__NO2____HiR_NRT_2.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/glossary?title=Sentinel-5P","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/S5P_OFFL_L2__NO2____HiR_1.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/S5P/S5P-KNMI-L2-0005-RP-Sentinel-5P-TROPOMI-ATBD-NO2-data-products-2024-2.8.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/S5P/S5P-L2-DLR-PUM-400E-Sentinel-5P-Level-2-Product-User-Manual-Sulphur-Dioxide-SO2-2024-2.8.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/S5P/S5P-MPC-KNMI-PRF-NO2-Sentinel-5P-Nitrogen-Dioxide-Level-2-Product-Readme-File-2025-2.8.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/S5P/sentinel-eula.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3412185684-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://sentinels.copernicus.eu/web/sentinel/copernicus/sentinel-5p","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://sentiwiki.copernicus.eu/web/document-library#DocumentLibrary-LatestMissionStatusReports.3","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"/SDE/CMR_API/|C3412185684-GES_DISC","keyword":["earth-science-atmospheric-chemistry-atmosphere","earth-science-atmospheric-chemistry-atmosphere-nitrogen-compounds"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2025-01-27/2026-09-07","theme":["Earth Science"],"title":"Sentinel-5P TROPOMI Near-Real-Time (NRT) Tropospheric NO2 1-Orbit L2 5.5km x 3.5km V2 (S5P_L2__NO2____HiR_NRT)"},"description":"The Sentinel-5P TROPOMI Near Real Time (NRT)  Tropospheric NO2 1-Orbit L2 5.5km x 3.5km V2 (S5P_L2__NO2____HiR_NRT)  is the near real time version of the offline S5P_L2__NO2____HiR data product. These data are typically available within three hours of measurement as required by the Land Atmosphere NRT Capability Earth Observing System (LANCE). These data are intended for a rapid turnaround assessment and are only archived for up to ten days. Users who require a longer data record, or wish to conduct rigorous analysis should use the offline version of this product S5P_L2__NO2____HiR.\n\nThe Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.\n\nThe TROPOMI retrieval of total and tropospheric NO2, is based on the DOMINO approach, a DOAS retrieval, a pre-calculated air-mass factor (AMF) look-up table, and a data assimilation/chemistry transport model for the separation of the stratospheric and tropospheric contributions to the NO2 column. It also include many retrieval developments of the European Quality Assurance for Essential Climate Variables (QA4ECV) project. Data are stored in individual files, or granules, that contain one orbit of information. The data are stored in netCDF4 data format and files and complete files are ~60 MB.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/8894309d-bcc7-4f1c-9412-f9d096894760","harvest_record_raw":"https://catalog.data.gov/harvest_record/8894309d-bcc7-4f1c-9412-f9d096894760/raw","has_download":true,"has_spatial":true,"identifier":"/SDE/CMR_API/|C3412185684-GES_DISC","keyword":["earth-science-atmospheric-chemistry-atmosphere","earth-science-atmospheric-chemistry-atmosphere-nitrogen-compounds"],"last_harvested_date":"2026-09-23T01:06:32.680480","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"sentinel-5p-tropomi-near-real-time-nrt-tropospheric-no2-1-orbit-l2-5-5km-x-3-5km-v2-s5p_l2-9d33e","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Sentinel-5P TROPOMI Near-Real-Time (NRT) Tropospheric NO2 1-Orbit L2 5.5km x 3.5km V2 (S5P_L2__NO2____HiR_NRT)","type":"dataset"},{"_score":10.973324,"_sort":[1790125583962,10.973324,7,"67c4b413-92be-4d80-9462-b7f700c6a28a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented.\nFor data before August 6th of 2019, please check S5P_L2__NO2____1 data collection.\n\nThe Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.\n\nThe TROPOMI retrieval of total and tropospheric NO2, is based on the DOMINO approach, a DOAS retrieval, a pre-calculated air-mass factor (AMF) look-up table, and a data assimilation/chemistry transport model for the separation of the stratospheric and tropospheric contributions to the NO2 column. It also include many retrieval developments of the European Quality Assurance for Essential Climate Variables (QA4ECV) project.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2089270961-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2089270961-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/S5P_L2__NO2____HiR_2.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/information/glossary?title=Sentinel-5P","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/S5P_OFFL_L2__NO2____HiR_1.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/S5P/S5P-KNMI-L2-0005-RP-Sentinel-5P-TROPOMI-ATBD-NO2-data-products-2024-2.8.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/S5P/S5P-L2-DLR-PUM-400E-Sentinel-5P-Level-2-Product-User-Manual-Sulphur-Dioxide-SO2-2024-2.8.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/S5P/S5P-MPC-KNMI-PRF-NO2-Sentinel-5P-Nitrogen-Dioxide-Level-2-Product-Readme-File-2025-2.8.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/S5P/sentinel-eula.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2089270961-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://sentinels.copernicus.eu/web/sentinel/copernicus/sentinel-5p","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://sentiwiki.copernicus.eu/web/document-library#DocumentLibrary-LatestMissionStatusReports.3","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://worldview.earthdata.nasa.gov/?l=Reference_Labels_15m%28hidden%29%2CReference_Features_15m%28hidden%29%2CCoastlines_15m%2CTROPOMI_L2_Nitrogen_Dioxide_Tropospheric_Column%2CTROPOMI_L2_Sulfur_Dioxide_Total_Vertical_Column%2CAIRS_L3_Carbon_Monoxide_500hPa_Volume_Mixing_Ratio_Daily_Day%2COCI_PACE_True_Color%28hidden%29%2CVIIRS_NOAA21_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_NOAA20_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_SNPP_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Aqua_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Terra_CorrectedReflectance_TrueColor&lg=true&t=2026-02-25-T18%253A24%253A48Z","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5270/S5P-9bnp8q8","keyword":["earth-science-atmospheric-chemistry-atmosphere","earth-science-atmospheric-chemistry-atmosphere-nitrogen-compounds"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2018-04-30/2026-09-07","theme":["Earth Science"],"title":"Sentinel-5P TROPOMI Tropospheric NO2 1-Orbit L2 5.5km x 3.5km V2 (S5P_L2__NO2____HiR)"},"description":"Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented.\nFor data before August 6th of 2019, please check S5P_L2__NO2____1 data collection.\n\nThe Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.\n\nThe TROPOMI retrieval of total and tropospheric NO2, is based on the DOMINO approach, a DOAS retrieval, a pre-calculated air-mass factor (AMF) look-up table, and a data assimilation/chemistry transport model for the separation of the stratospheric and tropospheric contributions to the NO2 column. It also include many retrieval developments of the European Quality Assurance for Essential Climate Variables (QA4ECV) project.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/3ee1522a-8db2-4302-ad04-063ac102c7fb","harvest_record_raw":"https://catalog.data.gov/harvest_record/3ee1522a-8db2-4302-ad04-063ac102c7fb/raw","has_download":true,"has_spatial":true,"identifier":"10.5270/S5P-9bnp8q8","keyword":["earth-science-atmospheric-chemistry-atmosphere","earth-science-atmospheric-chemistry-atmosphere-nitrogen-compounds"],"last_harvested_date":"2026-09-23T01:06:23.962031","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":7,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"sentinel-5p-tropomi-tropospheric-no2-1-orbit-l2-5-5km-x-3-5km-v2-s5p_l2__no2____hir-at-ges","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Sentinel-5P TROPOMI Tropospheric NO2 1-Orbit L2 5.5km x 3.5km V2 (S5P_L2__NO2____HiR)","type":"dataset"},{"_score":7.8236275,"_sort":[1790125581250,7.8236275,2,"e440417c-0eb0-44a0-8827-451935472dfc"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The objective of this limited edition data collection is to examine products generated by the Climate Heritage AIRS Retrieval Technique (CHART) algorithm to analyze Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite).  The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.\n \nThe CHART algorithm is uses the  basic cloud clearing and retrieval methodologies used including the definition and derivation of Jacobians, the channel noise covariance matrix, and the use of constraints including the background term, are essentially identical to those of AIRS Version-6.6 and previous AIRS Science Team retrieval algorithms.  As with the Version-6.6 AIRS system, the CHART algorithm uses a Neural Network system as an initial guess. The sounding retrieval methodology characterizes the full atmospheric state and the retrievals contains a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; outgoing longwave radiation (OLR); and an infrared-based precipitation estimate.\n\n\nThe monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the specific quality control (QC) methodology to form a level-2 daily gridded product. Specific QC is defined per retrieved geophysical parameter at a given level within a profile. It accepts profile level data from the top of the atmosphere down to the level where the QC algorithm determines that the retrieval is good. Below this level, the data is rejected. This is the same methodology used by the AIRS Version 6 processing system. The daily level-3 gridded products are averaged to create the monthly average. \n\n\nThe CHART system was designed to serve as a seamless follow on to the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU) instrument processing system. For comparison, the AIRS/AMSU data collection from AIRX3STM contains similar meteorological information to this CHART data collection.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1633993925-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/SNDRSNIML3SMCHTN_1.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/SNDRSNIML3SMCHTN_01.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/SNPP/SNPP_limited_edition/SNPP.CrIMSS.CHART.CLIMCAPS.v1.L3.README.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/SNPP/SNPP_limited_edition/SNPP.CrIMSS.CHART_V1.ATBD.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1633993925-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://sounder.gesdisc.eosdis.nasa.gov/data/limited_editions/SNPP_CHART/SNDRSNIML3SMCHTN.1/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://sounder.gesdisc.eosdis.nasa.gov/opendap/limited_editions/SNPP_CHART/SNDRSNIML3SMCHTN.1/","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/N86VFPX4N62N","keyword":["earth-science-air-quality-atmosphere-tropospheric-ozone","earth-science-altitude-atmosphere-tropopause","earth-science-atmospheric-chemistry-atmosphere-carbon-and-hydrocarbon-compounds","earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds","earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-outgoing-longwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-temperature-atmosphere-upper-air-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-profiles","earth-science-clouds-atmosphere-cloud-properties","earth-science-ocean-temperature-oceans-sea-surface-temperature","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-surface-radiative-properties-land-surface-emissivity","earth-science-surface-thermal-properties-land-surface-skin-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2013-01-01/2015-11-01","theme":["Earth Science"],"title":"Sounder SIPS: Suomi NPP CrIMSS Level 3 Specific Quality Control Gridded Monthly CHART Normal Spectral Resolution V1"},"description":"The objective of this limited edition data collection is to examine products generated by the Climate Heritage AIRS Retrieval Technique (CHART) algorithm to analyze Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite).  The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.\n \nThe CHART algorithm is uses the  basic cloud clearing and retrieval methodologies used including the definition and derivation of Jacobians, the channel noise covariance matrix, and the use of constraints including the background term, are essentially identical to those of AIRS Version-6.6 and previous AIRS Science Team retrieval algorithms.  As with the Version-6.6 AIRS system, the CHART algorithm uses a Neural Network system as an initial guess. The sounding retrieval methodology characterizes the full atmospheric state and the retrievals contains a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; outgoing longwave radiation (OLR); and an infrared-based precipitation estimate.\n\n\nThe monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the specific quality control (QC) methodology to form a level-2 daily gridded product. Specific QC is defined per retrieved geophysical parameter at a given level within a profile. It accepts profile level data from the top of the atmosphere down to the level where the QC algorithm determines that the retrieval is good. Below this level, the data is rejected. This is the same methodology used by the AIRS Version 6 processing system. The daily level-3 gridded products are averaged to create the monthly average. \n\n\nThe CHART system was designed to serve as a seamless follow on to the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU) instrument processing system. For comparison, the AIRS/AMSU data collection from AIRX3STM contains similar meteorological information to this CHART data collection.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/9864cd7a-ccc9-4259-a43b-d616a10135d1","harvest_record_raw":"https://catalog.data.gov/harvest_record/9864cd7a-ccc9-4259-a43b-d616a10135d1/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/N86VFPX4N62N","keyword":["earth-science-air-quality-atmosphere-tropospheric-ozone","earth-science-altitude-atmosphere-tropopause","earth-science-atmospheric-chemistry-atmosphere-carbon-and-hydrocarbon-compounds","earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds","earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-outgoing-longwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-temperature-atmosphere-upper-air-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-profiles","earth-science-clouds-atmosphere-cloud-properties","earth-science-ocean-temperature-oceans-sea-surface-temperature","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-surface-radiative-properties-land-surface-emissivity","earth-science-surface-thermal-properties-land-surface-skin-temperature"],"last_harvested_date":"2026-09-23T01:06:21.250471","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"sounder-sips-suomi-npp-crimss-level-3-specific-quality-control-gridded-monthly-chart-norma","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Sounder SIPS: Suomi NPP CrIMSS Level 3 Specific Quality Control Gridded Monthly CHART Normal Spectral Resolution V1","type":"dataset"},{"_score":9.968727,"_sort":[1790125579565,9.968727,1,"880443e8-aa4d-4fd3-b513-f2a18a45ad52"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The MODIS/Aqua Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG product (MYD08_D3) contains daily 1 x 1 degree grid average values of atmospheric parameters related to atmospheric aerosol particle properties, total ozone burden, atmospheric water vapor, cloud optical and physical properties, and atmospheric stability indices. This product also provides standard deviations, quality assurance weighted means and other statistically derived quantities for each parameter. \n\nThe MYD08_D3 contains roughly 600 statistical datasets that are derived from approximately 80 scientific parameters from four Level-2 MODIS Atmosphere Products: MOD04_L2, MOD05_L2, MOD06_L2, and MOD07_L2. Statistics are computed over a 1 degree equal-angle lat-lon grid that spans a 24-hour (0000 to 2400 Greenwich Mean Time) interval. Since the grid cells are 1 degree by 1 degree, the output grid is always 360 pixels in width and 180 pixels in length.\n\nMYD08_D3 product files are stored in Hierarchical Data Format (HDF-EOS). Each gridded global parameter is stored as Scientific Data Sets (SDS) within the file. \n\nThe MODIS Daily Product will be used in the simultaneously study of clouds, water vapor, aerosol , trace gases, land surface and oceanic properties, as well as the interaction between them and their effect on the Earth's energy budget and climate. This product will also be used to investigate seasonal and inter-annual changes in cirrus (semi-transparent) global cloud cover and cloud phase with multispectral observations at high spatial resolution.\n\nFor more information about the MYD08_D3 product, please visit the [MODIS Atmosphere site](https://modis-atmos.gsfc.nasa.gov/products/daily).","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1443729298-LAADS.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/MODIS/MYD08_D3.061","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/61/MYD08_D3/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ladsweb.modaps.eosdis.nasa.gov/opendap/RemoteResources/laads/allData/61/MYD08_D3/contents.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://ladsweb.modaps.eosdis.nasa.gov/search/order/2/MYD08_D3--61","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://modis-atmos.gsfc.nasa.gov/products/daily","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://modis-atmos.gsfc.nasa.gov/sites/default/files/ModAtmo/L3_ATBD_C6_C61_2019_02_20.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://modis-atmos.gsfc.nasa.gov/sites/default/files/ModAtmo/L3_C61_Changes_v2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1443729298-LAADS","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/MODIS/MYD08_D3.061","keyword":["earth-science-aerosols-atmosphere-aerosol-backscatter","earth-science-aerosols-atmosphere-aerosol-extinction","earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness","earth-science-aerosols-atmosphere-aerosol-particle-properties","earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-aerosols-atmosphere-carbonaceous-aerosols","earth-science-aerosols-atmosphere-cloud-condensation-nuclei","earth-science-aerosols-atmosphere-dust-ash-smoke","earth-science-aerosols-atmosphere-nitrate-particles","earth-science-aerosols-atmosphere-organic-particles","earth-science-aerosols-atmosphere-particulate-matter","earth-science-aerosols-atmosphere-sulfate-particles","earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds","earth-science-atmospheric-chemistry-atmosphere-trace-gases-trace-species","earth-science-atmospheric-radiation-atmosphere-atmospheric-emitted-radiation","earth-science-atmospheric-radiation-atmosphere-emissivity","earth-science-atmospheric-radiation-atmosphere-optical-depth-thickness","earth-science-atmospheric-radiation-atmosphere-radiative-flux","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-atmospheric-radiation-atmosphere-transmittance","earth-science-atmospheric-temperature-atmosphere-atmospheric-stability","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-profiles","earth-science-clouds-atmosphere-cloud-microphysics","earth-science-clouds-atmosphere-cloud-properties","earth-science-clouds-atmosphere-cloud-radiative-transfer","earth-science-weather-events-atmosphere-rain-storms"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90, \"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2002-07-04/2026-09-07","theme":["Earth Science"],"title":"MODIS/Aqua Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG"},"description":"The MODIS/Aqua Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG product (MYD08_D3) contains daily 1 x 1 degree grid average values of atmospheric parameters related to atmospheric aerosol particle properties, total ozone burden, atmospheric water vapor, cloud optical and physical properties, and atmospheric stability indices. This product also provides standard deviations, quality assurance weighted means and other statistically derived quantities for each parameter. \n\nThe MYD08_D3 contains roughly 600 statistical datasets that are derived from approximately 80 scientific parameters from four Level-2 MODIS Atmosphere Products: MOD04_L2, MOD05_L2, MOD06_L2, and MOD07_L2. Statistics are computed over a 1 degree equal-angle lat-lon grid that spans a 24-hour (0000 to 2400 Greenwich Mean Time) interval. Since the grid cells are 1 degree by 1 degree, the output grid is always 360 pixels in width and 180 pixels in length.\n\nMYD08_D3 product files are stored in Hierarchical Data Format (HDF-EOS). Each gridded global parameter is stored as Scientific Data Sets (SDS) within the file. \n\nThe MODIS Daily Product will be used in the simultaneously study of clouds, water vapor, aerosol , trace gases, land surface and oceanic properties, as well as the interaction between them and their effect on the Earth's energy budget and climate. This product will also be used to investigate seasonal and inter-annual changes in cirrus (semi-transparent) global cloud cover and cloud phase with multispectral observations at high spatial resolution.\n\nFor more information about the MYD08_D3 product, please visit the [MODIS Atmosphere site](https://modis-atmos.gsfc.nasa.gov/products/daily).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/3e4f14a6-9c44-4eb4-9d39-2e3155e30b24","harvest_record_raw":"https://catalog.data.gov/harvest_record/3e4f14a6-9c44-4eb4-9d39-2e3155e30b24/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/MODIS/MYD08_D3.061","keyword":["earth-science-aerosols-atmosphere-aerosol-backscatter","earth-science-aerosols-atmosphere-aerosol-extinction","earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness","earth-science-aerosols-atmosphere-aerosol-particle-properties","earth-science-aerosols-atmosphere-aerosol-radiance","earth-science-aerosols-atmosphere-carbonaceous-aerosols","earth-science-aerosols-atmosphere-cloud-condensation-nuclei","earth-science-aerosols-atmosphere-dust-ash-smoke","earth-science-aerosols-atmosphere-nitrate-particles","earth-science-aerosols-atmosphere-organic-particles","earth-science-aerosols-atmosphere-particulate-matter","earth-science-aerosols-atmosphere-sulfate-particles","earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds","earth-science-atmospheric-chemistry-atmosphere-trace-gases-trace-species","earth-science-atmospheric-radiation-atmosphere-atmospheric-emitted-radiation","earth-science-atmospheric-radiation-atmosphere-emissivity","earth-science-atmospheric-radiation-atmosphere-optical-depth-thickness","earth-science-atmospheric-radiation-atmosphere-radiative-flux","earth-science-atmospheric-radiation-atmosphere-reflectance","earth-science-atmospheric-radiation-atmosphere-transmittance","earth-science-atmospheric-temperature-atmosphere-atmospheric-stability","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-profiles","earth-science-clouds-atmosphere-cloud-microphysics","earth-science-clouds-atmosphere-cloud-properties","earth-science-clouds-atmosphere-cloud-radiative-transfer","earth-science-weather-events-atmosphere-rain-storms"],"last_harvested_date":"2026-09-23T01:06:19.565443","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS","slug":"modis-aqua-aerosol-cloud-water-vapor-ozone-daily-l3-global-1deg-cmg","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"MODIS/Aqua Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG","type":"dataset"},{"_score":6.5896416,"_sort":[1790125572012,6.5896416,1,"d3e2fa7a-d8ba-48f7-91c0-e2ac5a62734a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"This dataset provides absolute water level elevations derived for 10 locations across the Wax Lake Delta, Atchafalaya Basin, in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. Field measurements were made during the Pre-Delta-X campaign on October 13-20, 2016. Relative water level measurements were recorded every five minutes during a one-week period using in situ pressure transducers (Solinst) to measure water surface elevation change with millimeter accuracy. The Solinst system combines a total pressure transducer (TPT) and a temperature detector. Once underwater, the TPT measures the sum of the atmosphere and water pressure above the sensor. Atmospheric pressure fluctuations must be accounted for to obtain the height of the water column above the TPT. An absolute elevation correction was applied to the water level data using an iterative approach with the USGS Calumet Station water level height and Airborne Snow Observatory (ASO) lidar water level profiles. These Pre-Delta-X water level measurements served to calibrate and validate the campaign's remote sensing observations and hydrodynamic models.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2025123345-ORNL_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://daac.ornl.gov/DELTAX/guides/PreDeltaX_Water_Level_Data_Fig1.PNG","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/protected/bundle/PreDeltaX_Water_Level_Data_1801.zip","format":"ZIP","mediaType":"application/zip"},{"@type":"dcat:Distribution","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/public/deltax/PreDeltaX_Water_Level_Data/comp/PreDeltaX_Water_Level_Data.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://deltax.jpl.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.3334/ORNLDAAC/1801","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2025123345-ORNL_CLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.3334/ORNLDAAC/1801","keyword":["earth-science-atmospheric-ocean-indicators-climate-indicators-sea-level-rise","earth-science-coastal-processes-oceans-sea-level-rise","earth-science-ecosystems-biosphere-freshwater-ecosystems","earth-science-ecosystems-biosphere-terrestrial-ecosystems","earth-science-geomorphic-landforms-processes-land-surface-coastal-landforms","earth-science-surface-water-terrestrial-hydrosphere-surface-water-features","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"ORNL_DAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -91.446, \"NorthBoundingCoordinate\": 29.7429, \"EastBoundingCoordinate\": -91.3573, \"SouthBoundingCoordinate\": 29.5057}]]","temporal":"2016-10-13/2016-10-20","theme":["Earth Science"],"title":"Pre-Delta-X: Water Levels across Wax Lake Outlet, Atchafalaya Basin, LA, USA, 2016"},"description":"This dataset provides absolute water level elevations derived for 10 locations across the Wax Lake Delta, Atchafalaya Basin, in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. Field measurements were made during the Pre-Delta-X campaign on October 13-20, 2016. Relative water level measurements were recorded every five minutes during a one-week period using in situ pressure transducers (Solinst) to measure water surface elevation change with millimeter accuracy. The Solinst system combines a total pressure transducer (TPT) and a temperature detector. Once underwater, the TPT measures the sum of the atmosphere and water pressure above the sensor. Atmospheric pressure fluctuations must be accounted for to obtain the height of the water column above the TPT. An absolute elevation correction was applied to the water level data using an iterative approach with the USGS Calumet Station water level height and Airborne Snow Observatory (ASO) lidar water level profiles. These Pre-Delta-X water level measurements served to calibrate and validate the campaign's remote sensing observations and hydrodynamic models.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/cabbb6c2-7146-445d-ab7b-4e29b43e2b49","harvest_record_raw":"https://catalog.data.gov/harvest_record/cabbb6c2-7146-445d-ab7b-4e29b43e2b49/raw","has_download":true,"has_spatial":true,"identifier":"10.3334/ORNLDAAC/1801","keyword":["earth-science-atmospheric-ocean-indicators-climate-indicators-sea-level-rise","earth-science-coastal-processes-oceans-sea-level-rise","earth-science-ecosystems-biosphere-freshwater-ecosystems","earth-science-ecosystems-biosphere-terrestrial-ecosystems","earth-science-geomorphic-landforms-processes-land-surface-coastal-landforms","earth-science-surface-water-terrestrial-hydrosphere-surface-water-features","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"last_harvested_date":"2026-09-23T01:06:12.012706","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"ORNL_DAAC","slug":"pre-delta-x-water-levels-across-wax-lake-outlet-atchafalaya-basin-la-usa-2016","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Pre-Delta-X: Water Levels across Wax Lake Outlet, Atchafalaya Basin, LA, USA, 2016","type":"dataset"},{"_score":10.438219,"_sort":[1790125571342,10.438219,1,"d3bd8606-8636-4652-91c2-83d009fe3eb0"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"TOLNet_JPL_Data are lidar data collected by several ozone Differential Absorption Lidar instruments developed at the NASA Jet Propulsion Laboratory Table Mountain Facility (JPL-TMF). A fixed location instrument named TMTOL has been contributing ozone profiles to the Network for the Detection of Atmospheric Composition Change (NDACC), and the Tropospheric Ozone Lidar Network (TOLNet) since 2000. Five mobile instruments (SMOL-1, SMOL-2, SMOL-3, SMOL-4 and SMOL-5) started contributing ozone profiles to TOLNet in 2023, 2024 and 2025, depending on the instrument. Data collection for this product from all lidar instruments is ongoing.\n\nIn the troposphere, ozone is considered a pollutant and is important to understand due to its harmful effects on human health and vegetation. Tropospheric ozone is also significant for its impact on climate as a greenhouse gas. Operating since 2011, TOLNet is an interagency collaboration between NASA, NOAA, and the EPA designed to perform studies of air quality and atmospheric modeling as well as validation and interpretation of satellite observations. TOLNet is currently comprised of seven Differential Absorption Lidars (DIAL). Each of the lidars are unique, and some have had a long history of ozone observations prior to joining the network. Five lidars are mobile systems that can be deployed at remote locations to support field campaigns. This includes the Langley Mobile Ozone Lidar (LMOL) at NASA Langley Research Center (LaRC), the Tropospheric Ozone (TROPOZ) lidar at the Goddard Space Flight Center (GSFC), the Tunable Optical Profile for Aerosol and oZone (TOPAZ) lidar at the NOAA Chemical Sciences Laboratory (CSL) in Boulder, Colorado, the Autonomous Mobile Ozone LIDAR instrument for Tropospheric Experiments (AMOLITE) lidar at Environment and Climate Change Canada (ECCC) in Toronto, Canada, and the Rocket-city O3 Quality Evaluation in the Troposphere (RO3QET) lidar at the University of Alabama in Huntsville, Alabama. The remaining lidars, the Table Mountain Facility (TMF) tropospheric ozone lidar system located at the NASA Jet Propulsion Laboratory (JPL), and City College of New York (CCNY) New York Tropospheric Ozone Lidar System (NYTOLS) are fixed systems.\n\nTOLNet seeks to address three science objectives. The primary objective of the network is to provide high spatio-temporal measurements of ozone from near the surface to the top of the troposphere. Detailed observations of ozone structure allow science teams and the modeling community to better understand ozone in the lower-atmosphere and to assess the accuracy and vertical resolution with which geosynchronous instruments could retrieve the observed laminar ozone structures. Another objective of TOLNet is to identify an ozone lidar instrument design that would be suitable to address the needs of NASA, NOAA, and EPA air quality scientists who express a desire for these ozone profiles. The third objective of TOLNET is to perform basic scientific research into the processes create and destroy the ubiquitously observed ozone laminae and other ozone features in the troposphere. To help fulfill these objectives, lidars that are a part of TOLNet have been deployed to support nearly ten campaigns thus far. This includes campaigns such as the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission, the Korea United States Air Quality Study (KORUS-AQ), the Tracking Aerosol Convection ExpeRiment \u2013 Air Quality (TRACER-AQ) campaign, the Front Range Air Pollution and Photochemistry \u00c9xperiment (FRAPP\u00c9), the Long Island Sound Tropospheric Ozone Study (LISTOS), and the Ozone Water\u2013Land Environmental Transition Study (OWLETS).","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3880797717-LARC_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://amt.copernicus.org/articles/18/405/2025/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/citing-data","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/outreach-material/introduction-to-tolnet-storymap","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/outreach-material/tolnet-stratospheric-intrusion-storymap","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/wagdocuments/473/TOLNet_Lidars_and_Corresponding_Campaigns.docx","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3880797717-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1175/JTECH-D-10-05043.1","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1175/JTECH-D-10-05044.1","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1364/AO.41.007550","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/Lidar/Ozone/TOLNet/NASA-JPL","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5194/amt-10-3865-2017","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5194/amt-6-801-2013","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5194/amt-7-3529-2014","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://dx.doi.org/10.1364/AO.52.003557","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3880797717-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/Lidar/Ozone/TOLNet/NASA-JPL","keyword":["earth-science-air-quality-atmosphere-tropospheric-ozone","earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds","earth-science-atmospheric-chemistry-atmosphere-trace-gases-trace-species"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -118.2, \"EastBoundingCoordinate\": 4.93, \"SouthBoundingCoordinate\": 29.71, \"NorthBoundingCoordinate\": 51.98}]]","temporal":"2000-01-04/2026-09-07","theme":["Earth Science"],"title":"TOLNet NASA Jet Propulsion Laboratory Data"},"description":"TOLNet_JPL_Data are lidar data collected by several ozone Differential Absorption Lidar instruments developed at the NASA Jet Propulsion Laboratory Table Mountain Facility (JPL-TMF). A fixed location instrument named TMTOL has been contributing ozone profiles to the Network for the Detection of Atmospheric Composition Change (NDACC), and the Tropospheric Ozone Lidar Network (TOLNet) since 2000. Five mobile instruments (SMOL-1, SMOL-2, SMOL-3, SMOL-4 and SMOL-5) started contributing ozone profiles to TOLNet in 2023, 2024 and 2025, depending on the instrument. Data collection for this product from all lidar instruments is ongoing.\n\nIn the troposphere, ozone is considered a pollutant and is important to understand due to its harmful effects on human health and vegetation. Tropospheric ozone is also significant for its impact on climate as a greenhouse gas. Operating since 2011, TOLNet is an interagency collaboration between NASA, NOAA, and the EPA designed to perform studies of air quality and atmospheric modeling as well as validation and interpretation of satellite observations. TOLNet is currently comprised of seven Differential Absorption Lidars (DIAL). Each of the lidars are unique, and some have had a long history of ozone observations prior to joining the network. Five lidars are mobile systems that can be deployed at remote locations to support field campaigns. This includes the Langley Mobile Ozone Lidar (LMOL) at NASA Langley Research Center (LaRC), the Tropospheric Ozone (TROPOZ) lidar at the Goddard Space Flight Center (GSFC), the Tunable Optical Profile for Aerosol and oZone (TOPAZ) lidar at the NOAA Chemical Sciences Laboratory (CSL) in Boulder, Colorado, the Autonomous Mobile Ozone LIDAR instrument for Tropospheric Experiments (AMOLITE) lidar at Environment and Climate Change Canada (ECCC) in Toronto, Canada, and the Rocket-city O3 Quality Evaluation in the Troposphere (RO3QET) lidar at the University of Alabama in Huntsville, Alabama. The remaining lidars, the Table Mountain Facility (TMF) tropospheric ozone lidar system located at the NASA Jet Propulsion Laboratory (JPL), and City College of New York (CCNY) New York Tropospheric Ozone Lidar System (NYTOLS) are fixed systems.\n\nTOLNet seeks to address three science objectives. The primary objective of the network is to provide high spatio-temporal measurements of ozone from near the surface to the top of the troposphere. Detailed observations of ozone structure allow science teams and the modeling community to better understand ozone in the lower-atmosphere and to assess the accuracy and vertical resolution with which geosynchronous instruments could retrieve the observed laminar ozone structures. Another objective of TOLNet is to identify an ozone lidar instrument design that would be suitable to address the needs of NASA, NOAA, and EPA air quality scientists who express a desire for these ozone profiles. The third objective of TOLNET is to perform basic scientific research into the processes create and destroy the ubiquitously observed ozone laminae and other ozone features in the troposphere. To help fulfill these objectives, lidars that are a part of TOLNet have been deployed to support nearly ten campaigns thus far. This includes campaigns such as the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission, the Korea United States Air Quality Study (KORUS-AQ), the Tracking Aerosol Convection ExpeRiment \u2013 Air Quality (TRACER-AQ) campaign, the Front Range Air Pollution and Photochemistry \u00c9xperiment (FRAPP\u00c9), the Long Island Sound Tropospheric Ozone Study (LISTOS), and the Ozone Water\u2013Land Environmental Transition Study (OWLETS).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/2d561162-8f35-47cf-b75b-aef3f08de501","harvest_record_raw":"https://catalog.data.gov/harvest_record/2d561162-8f35-47cf-b75b-aef3f08de501/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/Lidar/Ozone/TOLNet/NASA-JPL","keyword":["earth-science-air-quality-atmosphere-tropospheric-ozone","earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds","earth-science-atmospheric-chemistry-atmosphere-trace-gases-trace-species"],"last_harvested_date":"2026-09-23T01:06:11.342306","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/LARC/SD/ASDC","slug":"tolnet-nasa-jet-propulsion-laboratory-data","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"TOLNet NASA Jet Propulsion Laboratory Data","type":"dataset"},{"_score":18.77826,"_sort":[1790125570073,18.77826,2,"7e3ebe07-4f76-4b9d-ac65-c8dd80fef64f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The VIIRS/JPSS1 Aerosol Daily L3 Global 0.05 Deg CMG, Short-name  VJ104ANC product provides VIIRS aerosol, air temperature, ozone and water vapor data at 0.05-degree resolution. This product is based on a Climate Modeling Grid (CMG) for the purpose of being used in climate simulation models. This is derived by using a weighted average of the best quality observation form only daytime data from Level 2 product, VJ104_L2.  \n  This daily product record starts from January 5th, 2018. This L3 daily product, in HDF5 file format , contains 5 Science Data Set (SDS) layers.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3432246804-LAADS.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://ladsweb.modaps.eosdis.nasa.gov/opendap/RemoteResources/laads/allData/5200/VNP04ANC/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ladsweb.modaps.eosdis.nasa.gov/search/order/1/VJ104ANC--5200","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3432246804-LAADS","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/VIIRS/VJ104ANC.002","keyword":["earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness","earth-science-air-quality-atmosphere-tropospheric-ozone"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90, \"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2018-01-05/2026-09-07","theme":["Earth Science"],"title":"VIIRS/JPSS1 Aerosol Daily L3 Global 0.05 Deg CMG"},"description":"The VIIRS/JPSS1 Aerosol Daily L3 Global 0.05 Deg CMG, Short-name  VJ104ANC product provides VIIRS aerosol, air temperature, ozone and water vapor data at 0.05-degree resolution. This product is based on a Climate Modeling Grid (CMG) for the purpose of being used in climate simulation models. This is derived by using a weighted average of the best quality observation form only daytime data from Level 2 product, VJ104_L2.  \n  This daily product record starts from January 5th, 2018. This L3 daily product, in HDF5 file format , contains 5 Science Data Set (SDS) layers.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/92ae2943-42ce-4ca4-ae22-e558b33a4046","harvest_record_raw":"https://catalog.data.gov/harvest_record/92ae2943-42ce-4ca4-ae22-e558b33a4046/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/VIIRS/VJ104ANC.002","keyword":["earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness","earth-science-air-quality-atmosphere-tropospheric-ozone"],"last_harvested_date":"2026-09-23T01:06:10.073925","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS","slug":"viirs-jpss1-aerosol-daily-l3-global-0-05-deg-cmg","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"VIIRS/JPSS1 Aerosol Daily L3 Global 0.05 Deg CMG","type":"dataset"},{"_score":39.830406,"_sort":[1790125568792,39.830406,1,"511f0d32-52aa-4362-8419-7b3f97d8b0b9"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: \n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. \n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264134168-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/GPROFV07A_releasenotes.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264134168-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFGCOMW1AMSR2_CLIM_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFGCOMW1AMSR2_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L2/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264134168-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://suzaku.eorc.jaxa.jp/GCOM_W/w_amsr2/amsr2_body_main.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/amsr2.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/AMSR2/GCOMW1/GPROFCLIM/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2012-07-02/2025-12-01","theme":["Earth Science"],"title":"GPM AMSR-2 on GCOM-W1 (GPROF) Climate-based Radiometer Precipitation Profiling L2A 1.5 hours 10 km V07 (GPM_2AGPROFGCOMW1AMSR2_CLIM)"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\nThe 'CLIM'  products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n\nThe 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: \n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. \n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/c5718d4e-356b-4d89-8534-ccf8c5ee753a","harvest_record_raw":"https://catalog.data.gov/harvest_record/c5718d4e-356b-4d89-8534-ccf8c5ee753a/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/AMSR2/GCOMW1/GPROFCLIM/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:08.792450","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-amsr-2-on-gcom-w1-gprof-climate-based-radiometer-precipitation-profiling-l2a-1-5-hours","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM AMSR-2 on GCOM-W1 (GPROF) Climate-based Radiometer Precipitation Profiling L2A 1.5 hours 10 km V07 (GPM_2AGPROFGCOMW1AMSR2_CLIM)","type":"dataset"},{"_score":18.781055,"_sort":[1790125568473,18.781055,1,"2eb50476-e320-4bc2-8be9-1c15b7c109b6"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The VIIRS/NPP Aerosol Daily L3 Global 0.05 Deg CMG, Short-name  VNP04ANC product provides VIIRS aerosol, air temperature, ozone and water vapor data at 0.05-degree resolution. This product is based on a Climate Modeling Grid (CMG) for the purpose of being used in climate simulation models. This is derived by using a weighted average of the best quality observation form only daytime data from Level 2 product, VNP04_L2.  \n  This daily product record starts from January 5th, 2018. This L3 daily product, in HDF5 file format , contains 5 Science Data Set (SDS) layers.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3432263716-LAADS.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://ladsweb.modaps.eosdis.nasa.gov/opendap/RemoteResources/laads/allData/5200/VNP04ANC/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ladsweb.modaps.eosdis.nasa.gov/search/order/1/VNP04ANC--5200","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3432263716-LAADS","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/VIIRS/VNP04ANC.002","keyword":["earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness","earth-science-air-quality-atmosphere-tropospheric-ozone"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90, \"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2012-01-18/2026-09-07","theme":["Earth Science"],"title":"VIIRS/NPP Aerosol Daily L3 Global 0.05 Deg CMG"},"description":"The VIIRS/NPP Aerosol Daily L3 Global 0.05 Deg CMG, Short-name  VNP04ANC product provides VIIRS aerosol, air temperature, ozone and water vapor data at 0.05-degree resolution. This product is based on a Climate Modeling Grid (CMG) for the purpose of being used in climate simulation models. This is derived by using a weighted average of the best quality observation form only daytime data from Level 2 product, VNP04_L2.  \n  This daily product record starts from January 5th, 2018. This L3 daily product, in HDF5 file format , contains 5 Science Data Set (SDS) layers.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/052fa09b-21b9-4b0c-a5f9-566d917dbe0b","harvest_record_raw":"https://catalog.data.gov/harvest_record/052fa09b-21b9-4b0c-a5f9-566d917dbe0b/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/VIIRS/VNP04ANC.002","keyword":["earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness","earth-science-air-quality-atmosphere-tropospheric-ozone"],"last_harvested_date":"2026-09-23T01:06:08.473348","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS","slug":"viirs-npp-aerosol-daily-l3-global-0-05-deg-cmg","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"VIIRS/NPP Aerosol Daily L3 Global 0.05 Deg CMG","type":"dataset"},{"_score":40.640507,"_sort":[1790125568152,40.640507,1,"437be35b-da0a-4b43-bb60-7f0048296b7c"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264135548-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264135548-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFGCOMW1AMSR2_DAY_CLIM_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFGCOMW1AMSR2_DAY_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264135548-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://suzaku.eorc.jaxa.jp/GCOM_W/w_amsr2/amsr2_body_main.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/amsr2.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/AMSR2/GCOMW1/GPROFCLIM/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2012-07-02/2025-11-30","theme":["Earth Science"],"title":"GPM AMSR-2 on GCOM-W1 (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFGCOMW1AMSR2_DAY_CLIM)"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/163a0037-f96f-4938-a8a3-3d62751dc1b7","harvest_record_raw":"https://catalog.data.gov/harvest_record/163a0037-f96f-4938-a8a3-3d62751dc1b7/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/AMSR2/GCOMW1/GPROFCLIM/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:08.152556","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-amsr-2-on-gcom-w1-gprof-climate-based-radiometer-precipitation-profiling-l3-1-day-0-25","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM AMSR-2 on GCOM-W1 (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFGCOMW1AMSR2_DAY_CLIM)","type":"dataset"},{"_score":41.53498,"_sort":[1790125567516,41.53498,1,"fc263b11-fac6-4ebc-9854-720486ed4527"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264135524-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264135524-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFGCOMW1AMSR2_CLIM_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFGCOMW1AMSR2_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264135524-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://suzaku.eorc.jaxa.jp/GCOM_W/w_amsr2/amsr2_body_main.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/amsr2.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/AMSR2/GCOMW1/GPROFCLIM/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2012-07-01/2025-11-30","theme":["Earth Science"],"title":"GPM AMSR-2 on GCOM-W1 (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFGCOMW1AMSR2_CLIM)"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/07546fcd-5f3e-4fb3-9520-ff270573ba10","harvest_record_raw":"https://catalog.data.gov/harvest_record/07546fcd-5f3e-4fb3-9520-ff270573ba10/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/AMSR2/GCOMW1/GPROFCLIM/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:07.516533","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-amsr-2-on-gcom-w1-gprof-climate-based-radiometer-precipitation-profiling-l3-1-month-0-","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM AMSR-2 on GCOM-W1 (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFGCOMW1AMSR2_CLIM)","type":"dataset"},{"_score":14.051196,"_sort":[1790125567184,14.051196,0,"5c1167ac-1b35-44ea-add1-bc993c7ff16b"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. \n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264133757-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/GPROFV07A_releasenotes.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264133757-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFGCOMW1AMSR2_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFGCOMW1AMSR2_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L2/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264133757-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://suzaku.eorc.jaxa.jp/GCOM_W/w_amsr2/amsr2_body_main.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/amsr2.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/AMSR2/GCOMW1/GPROF/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2022-04-30/2026-03-01","theme":["Earth Science"],"title":"GPM AMSR-2 on GCOM-W1 (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 10 km V07 (GPM_2AGPROFGCOMW1AMSR2)"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19) \n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. \n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/2ba7071d-d702-460c-9d0a-e6f1c988ae26","harvest_record_raw":"https://catalog.data.gov/harvest_record/2ba7071d-d702-460c-9d0a-e6f1c988ae26/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/AMSR2/GCOMW1/GPROF/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:07.184716","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":0,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-amsr-2-on-gcom-w1-gprof-radiometer-precipitation-profiling-l2a-1-5-hours-10-km-v07-gpm","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM AMSR-2 on GCOM-W1 (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 10 km V07 (GPM_2AGPROFGCOMW1AMSR2)","type":"dataset"},{"_score":16.065857,"_sort":[1790125566857,16.065857,1,"4264bff2-5ce0-4b7f-8b76-9b64dfb1121f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264134685-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264134685-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFGCOMW1AMSR2_DAY_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFGCOMW1AMSR2_DAY_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264134685-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://suzaku.eorc.jaxa.jp/GCOM_W/w_amsr2/amsr2_body_main.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/amsr2.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/AMSR2/GCOMW1/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2022-05-01/2026-02-28","theme":["Earth Science"],"title":"GPM AMSR-2 on GCOM-W1 (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFGCOMW1AMSR2_DAY)"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/649242aa-8542-4ea6-bc36-812386703845","harvest_record_raw":"https://catalog.data.gov/harvest_record/649242aa-8542-4ea6-bc36-812386703845/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/AMSR2/GCOMW1/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:06.857169","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-amsr-2-on-gcom-w1-gprof-radiometer-precipitation-profiling-l3-1-day-0-25-degree-x-0-25","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM AMSR-2 on GCOM-W1 (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFGCOMW1AMSR2_DAY)","type":"dataset"},{"_score":16.005674,"_sort":[1790125566542,16.005674,1,"05938f61-9233-4b40-985c-f859b204b78f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2712827642-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2712827642-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFNOAA21ATMS_DAY_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFNOAA21ATMS_DAY_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2712827642-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/snppatms.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/ATMS/NOAA21/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2023-02-01/2026-02-28","theme":["Earth Science"],"title":"GPM ATMS on NOAA-21 (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree  V07 (GPM_3GPROFNOAA21ATMS_DAY)"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/eae97529-1de3-4d61-8921-274fb969fa1a","harvest_record_raw":"https://catalog.data.gov/harvest_record/eae97529-1de3-4d61-8921-274fb969fa1a/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/ATMS/NOAA21/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:06.542167","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-atms-on-noaa-21-gprof-radiometer-precipitation-profiling-l3-1-day-0-25-degree-x-0-25-d","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM ATMS on NOAA-21 (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree  V07 (GPM_3GPROFNOAA21ATMS_DAY)","type":"dataset"},{"_score":16.576042,"_sort":[1790125566176,16.576042,1,"c1642ce3-fe7d-49c2-be7d-55da8b060634"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. \n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2712827638-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2712827638-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFNOAA21ATMS_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFNOAA21ATMS_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2712827638-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/snppatms.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/ATMS/NOAA21/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2023-02-01/2026-02-28","theme":["Earth Science"],"title":"GPM ATMS on NOAA-21 (GPROF) Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFNOAA21ATMS)"},"description":"Version 07 is the current version of the data set. \n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/0411fd62-8e5a-4646-9d61-abc8f1d19171","harvest_record_raw":"https://catalog.data.gov/harvest_record/0411fd62-8e5a-4646-9d61-abc8f1d19171/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/ATMS/NOAA21/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:06.176214","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-atms-on-noaa-21-gprof-radiometer-precipitation-profiling-l3-1-month-0-25-degree-x-0-25","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM ATMS on NOAA-21 (GPROF) Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFNOAA21ATMS)","type":"dataset"},{"_score":20.927843,"_sort":[1790125565842,20.927843,2,"9c29df4d-0767-4b86-a226-78b6ace161a4"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07.\n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264136081-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264136081-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFNPPATMS_CLIM_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFNPPATMS_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264136081-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/snppatms.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/ATMS/NPP/GPROFCLIM/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2011-11-01/2025-11-30","theme":["Earth Science"],"title":"GPM ATMS on SUOMI-NPP (GPROF) Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFNPPATMS_CLIM)"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07.\n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/04410f0e-64c4-4be4-8205-cdb207be8a7a","harvest_record_raw":"https://catalog.data.gov/harvest_record/04410f0e-64c4-4be4-8205-cdb207be8a7a/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/ATMS/NPP/GPROFCLIM/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:05.842082","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-atms-on-suomi-npp-gprof-radiometer-precipitation-profiling-l3-1-month-0-25-degree-x-0-","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM ATMS on SUOMI-NPP (GPROF) Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFNPPATMS_CLIM)","type":"dataset"},{"_score":18.283875,"_sort":[1790125565502,18.283875,1,"9db0c93f-0ce1-4542-929d-7f153292343e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19)\n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264134428-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264134428-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFNPPATMS_CLIM_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFNPPATMS_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L2/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264134428-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/snppatms.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/ATMS/NPP/GPROFCLIM/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2011-11-08/2025-12-01","theme":["Earth Science"],"title":"GPM ATMS on SUOMI-NPP (GPROF) Radiometer Precipitation Profiling L2 1.5 hours 16 km V07 (GPM_2AGPROFNPPATMS_CLIM)"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19)\n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/faf46ad8-006f-447e-b737-63d039284fe3","harvest_record_raw":"https://catalog.data.gov/harvest_record/faf46ad8-006f-447e-b737-63d039284fe3/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/ATMS/NPP/GPROFCLIM/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:06:05.502896","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-atms-on-suomi-npp-gprof-radiometer-precipitation-profiling-l2-1-5-hours-16-km-v07-gpm_","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM ATMS on SUOMI-NPP (GPROF) Radiometer Precipitation Profiling L2 1.5 hours 16 km V07 (GPM_2AGPROFNPPATMS_CLIM)","type":"dataset"},{"_score":44.98731,"_sort":[1790125562040,44.98731,1,"bd50cd56-5a03-473b-9d6d-a6580a231733"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"These data are the standard error calculated from the AVISO Level 4 Absolute Dynamic Topography for Climate Model Comparison Number of Observations data set ( in PO.DAAC Drive at https://podaac-tools.jpl.nasa.gov/drive/files/allData/aviso/L4/abs_dynamic_topo ).  This data set is not  meant to be used alone, but with the absolute dynamic topography data. These data were generated to help support the CMIP5 (Coupled Model Intercomparison Project Phase 5) portion of PCMDI (Program for Climate Model Diagnosis and Intercomparison).  The dynamic topograhy are from sea surface height measured by several satellites, Envisat, TOPEX/Poseidon, Jason-1 and OSTM/Jason-2 and referenced to the geoid.  These data were provided by AVISO (French space agency data provider), which are based on a similar dynamic topography data set they already produce( http://www.aviso.oceanobs.com/index.php?id=1271 ).","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3234111485-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3234111485-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/CitingPODAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3234111485-POCLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/DYNTO-SERR1","keyword":["earth-science-sea-surface-topography-oceans-sea-surface-height"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"AVISO;NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"SouthBoundingCoordinate\": -90, \"EastBoundingCoordinate\": 180, \"NorthBoundingCoordinate\": 90}]]","temporal":"1992-10-01/2010-12-31","theme":["Earth Science"],"title":"AVISO Level 4 Absolute Dynamic Topography for Climate Model Comparison Standard Error"},"description":"These data are the standard error calculated from the AVISO Level 4 Absolute Dynamic Topography for Climate Model Comparison Number of Observations data set ( in PO.DAAC Drive at https://podaac-tools.jpl.nasa.gov/drive/files/allData/aviso/L4/abs_dynamic_topo ).  This data set is not  meant to be used alone, but with the absolute dynamic topography data. These data were generated to help support the CMIP5 (Coupled Model Intercomparison Project Phase 5) portion of PCMDI (Program for Climate Model Diagnosis and Intercomparison).  The dynamic topograhy are from sea surface height measured by several satellites, Envisat, TOPEX/Poseidon, Jason-1 and OSTM/Jason-2 and referenced to the geoid.  These data were provided by AVISO (French space agency data provider), which are based on a similar dynamic topography data set they already produce( http://www.aviso.oceanobs.com/index.php?id=1271 ).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/3ebbf956-9f8f-44d3-ad5b-d54c77d4f292","harvest_record_raw":"https://catalog.data.gov/harvest_record/3ebbf956-9f8f-44d3-ad5b-d54c77d4f292/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/DYNTO-SERR1","keyword":["earth-science-sea-surface-topography-oceans-sea-surface-height"],"last_harvested_date":"2026-09-23T01:06:02.040804","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"AVISO;NASA/JPL/PODAAC","slug":"aviso-level-4-absolute-dynamic-topography-for-climate-model-comparison-standard-error","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"AVISO Level 4 Absolute Dynamic Topography for Climate Model Comparison Standard Error","type":"dataset"},{"_score":9.152218,"_sort":[1790125559326,9.152218,2,"f0a0be89-9059-4767-8469-d1e68fde372f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"This data set is produced by the Center for Space Research (CSR) GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the ocean bottom pressure (OBP) anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents sea floor pressure changes due to the integral effect of ocean and atmosphere processes, including global mean ocean bottom pressure changes (mean ocean mass and mean atmosphere mass over the global oceans). A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats. \n\nGRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 \u2013 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the ocean bottom pressure data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this release 06.3 is an updated version of the Level 3 products in coordination with the release of the analogous Level 2 products used to generate them. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3193289116-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L3_Handbook_JPL.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3193289116-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/podaac/data-subscriber","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gracefo.jpl.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://opendap.earthdata.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/CitingPODAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/GRACE-FO","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/Podaac/thumbnails/TELLUS_GRFO_L3_CSR_RL06.3_OCN_v04.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/gravity/gracefo-documentation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3193289116-POCLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GFOCN-3C634","keyword":["earth-science-ocean-pressure-oceans-water-pressure"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/GRACE-TELLUS-0001;NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"SouthBoundingCoordinate\": -89.5, \"EastBoundingCoordinate\": 180, \"NorthBoundingCoordinate\": 89.5}]]","theme":["Earth Science"],"title":"CSR TELLUS GRACE-FO Level-3 Monthly Ocean Bottom Pressure Anomaly Release 6.3 version 04"},"description":"This data set is produced by the Center for Space Research (CSR) GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the ocean bottom pressure (OBP) anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents sea floor pressure changes due to the integral effect of ocean and atmosphere processes, including global mean ocean bottom pressure changes (mean ocean mass and mean atmosphere mass over the global oceans). A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats. \n\nGRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 \u2013 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the ocean bottom pressure data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this release 06.3 is an updated version of the Level 3 products in coordination with the release of the analogous Level 2 products used to generate them. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/da0f3824-311d-441b-9115-ee1141fc660a","harvest_record_raw":"https://catalog.data.gov/harvest_record/da0f3824-311d-441b-9115-ee1141fc660a/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GFOCN-3C634","keyword":["earth-science-ocean-pressure-oceans-water-pressure"],"last_harvested_date":"2026-09-23T01:05:59.326342","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/JPL/GRACE-TELLUS-0001;NASA/JPL/PODAAC","slug":"csr-tellus-grace-fo-level-3-monthly-ocean-bottom-pressure-anomaly-release-6-3-version-04","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CSR TELLUS GRACE-FO Level-3 Monthly Ocean Bottom Pressure Anomaly Release 6.3 version 04","type":"dataset"},{"_score":14.051196,"_sort":[1790125556067,14.051196,10,"fd7fa214-dcc3-4d0f-be34-a8f28f6759d8"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19)\n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2259345545-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/GPROFV07A_releasenotes.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2259345545-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFGPMGMI_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFGPMGMI_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L2/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://pps.gsfc.nasa.gov/gpminstruments.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2259345545-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://worldview.earthdata.nasa.gov/?l=Reference_Labels_15m%28hidden%29%2CReference_Features_15m%28hidden%29%2CCoastlines_15m%2CGMI_Precipitation_Rate_Asc%2CGMI_Precipitation_Rate_Dsc%2COCI_PACE_True_Color%28hidden%29%2CVIIRS_NOAA21_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_NOAA20_CorrectedReflectance_TrueColor%28hidden%29%2CVIIRS_SNPP_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Aqua_CorrectedReflectance_TrueColor%28hidden%29%2CMODIS_Terra_CorrectedReflectance_TrueColor&lg=true&t=2026-02-24-T16%253A33%253A59Z","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/GMI/GPM/GPROF/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 70, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -70}]]","temporal":"2014-03-04/2026-03-01","theme":["Earth Science"],"title":"GPM GMI (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 13 km V07 (GPM_2AGPROFGPMGMI)"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\nThe 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:\n+ TMI (TRMM)\n+ GMI, (GPM)\n+ SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18, F19)\n+ AMSR2 (GCOM-W1)\n+ MHS (NOAA 18,19)\n+ MHS (METOP A,B)\n+ ATMS (NPP)\n+ SAPHIR (MT1)\n\nThis provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.\n\nThe GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/4d3479a4-3bf1-4ae2-95e1-62a64f8eb74e","harvest_record_raw":"https://catalog.data.gov/harvest_record/4d3479a4-3bf1-4ae2-95e1-62a64f8eb74e/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/GMI/GPM/GPROF/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:56.067609","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":10,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-gmi-gprof-radiometer-precipitation-profiling-l2a-1-5-hours-13-km-v07-gpm_2agprofgpmgmi","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM GMI (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 13 km V07 (GPM_2AGPROFGPMGMI)","type":"dataset"},{"_score":16.065857,"_sort":[1790125555395,16.065857,1,"f4c6c3ad-5ebc-45a9-b822-abda86a0e956"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2259345611-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/GPROFV07A_releasenotes.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2259345611-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFGPMGMI_DAY_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFGPMGMI_DAY_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://pps.gsfc.nasa.gov/gpminstruments.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2259345611-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/GMI/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 70, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -70}]]","temporal":"2014-03-04/2026-02-28","theme":["Earth Science"],"title":"GPM GMI (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFGPMGMI_DAY)"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/d0a0b49a-2675-40d2-b6d8-d6491083c73c","harvest_record_raw":"https://catalog.data.gov/harvest_record/d0a0b49a-2675-40d2-b6d8-d6491083c73c/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/GMI/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:55.395697","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-gmi-gprof-radiometer-precipitation-profiling-l3-1-day-0-25-degree-x-0-25-degree-v07-gp","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM GMI (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFGPMGMI_DAY)","type":"dataset"},{"_score":16.07185,"_sort":[1790125555076,16.07185,1,"a4d78e25-41dd-4db4-ba18-fddc0b68ad54"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2259345585-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/GPROFV07A_releasenotes.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2259345585-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFGPMGMI_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFGPMGMI_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://pps.gsfc.nasa.gov/gpminstruments.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2259345585-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/GMI/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 70, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -70}]]","temporal":"2014-03-01/2026-02-28","theme":["Earth Science"],"title":"GPM GMI (GPROF) Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFGPMGMI)"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/aff4ce9e-ac99-464e-bdbd-c7558bb81aa0","harvest_record_raw":"https://catalog.data.gov/harvest_record/aff4ce9e-ac99-464e-bdbd-c7558bb81aa0/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/GMI/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:55.076549","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-gmi-gprof-radiometer-precipitation-profiling-l3-1-month-0-25-degree-x-0-25-degree-v07-","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM GMI (GPROF) Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFGPMGMI)","type":"dataset"},{"_score":9.541962,"_sort":[1790125553452,9.541962,2,"33aec057-cd4f-4965-8fbc-3e09d4d6c80e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"This data set is produced by the German Research Centre for Geosciences (GFZ) as part of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the terrestrial water storage anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents the total terrestrial water storage anomalies from soil moisture, snow, surface water (incl. rivers, lakes, reservoirs etc.), as well as groundwater and aquifers. A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats. \n\nGRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 \u2013 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the terrestrial water storage data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this release 06.3 is an updated version of the Level 3 products in coordination with the release of the analogous Level 2 products used to generate them. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3193293825-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L3_Handbook_JPL.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3193293825-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/podaac/data-subscriber","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gracefo.jpl.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://opendap.earthdata.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/CitingPODAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/GRACE-FO","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/Podaac/thumbnails/TELLUS_GRFO_L3_GFZ_RL063_LND_v04.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/gravity/gracefo-documentation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3193293825-POCLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GFLND-3G634","keyword":["earth-science-water-budget-terrestrial-hydrosphere-terrestrial-water-storage"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/GRACE-TELLUS-0001;NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"SouthBoundingCoordinate\": -89.5, \"EastBoundingCoordinate\": 180, \"NorthBoundingCoordinate\": 89.5}]]","theme":["Earth Science"],"title":"GFZ TELLUS GRACE-FO Level-3 Monthly Land Water-Equivalent-Thickness Surface Mass Anomaly Release 6.3 version 04"},"description":"This data set is produced by the German Research Centre for Geosciences (GFZ) as part of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the terrestrial water storage anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents the total terrestrial water storage anomalies from soil moisture, snow, surface water (incl. rivers, lakes, reservoirs etc.), as well as groundwater and aquifers. A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats. \n\nGRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 \u2013 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the terrestrial water storage data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this release 06.3 is an updated version of the Level 3 products in coordination with the release of the analogous Level 2 products used to generate them. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/80187f24-f8c4-4b97-8620-45f7286a418d","harvest_record_raw":"https://catalog.data.gov/harvest_record/80187f24-f8c4-4b97-8620-45f7286a418d/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GFLND-3G634","keyword":["earth-science-water-budget-terrestrial-hydrosphere-terrestrial-water-storage"],"last_harvested_date":"2026-09-23T01:05:53.452088","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/JPL/GRACE-TELLUS-0001;NASA/JPL/PODAAC","slug":"gfz-tellus-grace-fo-level-3-monthly-land-water-equivalent-thickness-surface-mass-anomal-04","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GFZ TELLUS GRACE-FO Level-3 Monthly Land Water-Equivalent-Thickness Surface Mass Anomaly Release 6.3 version 04","type":"dataset"},{"_score":9.152218,"_sort":[1790125553129,9.152218,3,"85a49452-c0d6-42df-89c9-a03ea7f2124b"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"This data set is produced by the German Research Centre for Geosciences (GFZ) as part of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the ocean bottom pressure (OBP) anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents sea floor pressure changes due to the integral effect of ocean and atmosphere processes, including global mean ocean bottom pressure changes (mean ocean mass and mean atmosphere mass over the global oceans). A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats. \n\nGRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 \u2013 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the ocean bottom pressure data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this release 06.3 is an updated version of the Level 3 products in coordination with the release of the analogous Level 2 products used to generate them. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3193298027-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L3_Handbook_JPL.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3193298027-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/podaac/data-subscriber","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gracefo.jpl.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://opendap.earthdata.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/CitingPODAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/GRACE-FO","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/Podaac/thumbnails/TELLUS_GRFO_L3_GFZ_RL063_OCN_v04.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/gravity/gracefo-documentation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3193298027-POCLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GFOCN-3G634","keyword":["earth-science-ocean-pressure-oceans-water-pressure"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/GRACE-TELLUS-0001;NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"SouthBoundingCoordinate\": -89.5, \"EastBoundingCoordinate\": 180, \"NorthBoundingCoordinate\": 89.5}]]","theme":["Earth Science"],"title":"GFZ TELLUS GRACE-FO Level-3 Monthly Ocean Bottom Pressure Anomaly Release 6.3 version 04"},"description":"This data set is produced by the German Research Centre for Geosciences (GFZ) as part of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the ocean bottom pressure (OBP) anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents sea floor pressure changes due to the integral effect of ocean and atmosphere processes, including global mean ocean bottom pressure changes (mean ocean mass and mean atmosphere mass over the global oceans). A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats. \n\nGRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 \u2013 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the ocean bottom pressure data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this release 06.3 is an updated version of the Level 3 products in coordination with the release of the analogous Level 2 products used to generate them. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/2e480f1c-916d-412c-b993-08b382ef0806","harvest_record_raw":"https://catalog.data.gov/harvest_record/2e480f1c-916d-412c-b993-08b382ef0806/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GFOCN-3G634","keyword":["earth-science-ocean-pressure-oceans-water-pressure"],"last_harvested_date":"2026-09-23T01:05:53.129291","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":3,"publisher":"NASA/JPL/GRACE-TELLUS-0001;NASA/JPL/PODAAC","slug":"gfz-tellus-grace-fo-level-3-monthly-ocean-bottom-pressure-anomaly-release-6-3-version-04","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GFZ TELLUS GRACE-FO Level-3 Monthly Ocean Bottom Pressure Anomaly Release 6.3 version 04","type":"dataset"},{"_score":7.856436,"_sort":[1790125552476,7.856436,2,"01b44601-78bb-4f6f-978b-0e0c7ae8956b"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The H09-AHI-L2P-ACSPO-v2.90 dataset contains the Subskin Sea Surface Temperature (SST) produced by the NOAA ACSPO system from the Advanced Himawari Imager (AHI; largely identical to GOES-R/ABI) onboard the Himawari-9 (H09) satellite. The H09 is a Japanese weather satellite, the 9th of the Himawari geostationary weather satellite operated by the Japan Meteorological Agency. It was launched on November 2, 2016 into its nominal position at 140.7-deg E, and declared operational on December 13, 2022, replacing the Himawari-8. The AHI is the primary instrument on the Himawari Series for imaging Earth\u2019s weather, oceans, and environment with high temporal and spatial resolutions.  \n\nThe H08/AHI maps SST in a Full Disk (FD) area from 80E-160W and 60S-60N, with spatial resolution 2km at nadir to 15km/VZA (view zenith angle) 67-deg, and 10-min temporal sampling. The 10-min FD data are subsequently collated in time, to produce the 1-hr product, with improved coverage and reduced cloud leakages and image noise. The L2P data is produced in GHRSST compliant netCDF4 GDS2 format, with 24 granules per day, and a total data volume 1.2 GB/day. The near-real time (NRT) data are updated hourly, with several hours latency. The NRT files are replaced with Delayed Mode (DM) files, with a latency of approximately 2-months. File names remain unchanged, and DM vs NRT can be identified by different time stamps and global attributes inside the files (MERRA instead of GFS for atmospheric profiles, and same day CMC L4 analyses in DM instead of one-day delayed in NRT processing).  \n\nPixel earth locations are not reported in the granules, as they remain unchanged from granule to granule. Pixel locations  can be obtained using a flat lat/lon file or a Python script available via Documents tab from the dataset landing page. Climate and Forecast (CF) metadata aware software (e.g., Panoply, xarray) can detect and map the data as is via the granule CF projection attributes and variables. The ACSPO H09 HAI SSTs are validated against quality controlled in situ data from the NOAA iQuam system (Xu and Ignatov, 2014) and continuously monitored in the NOAA SQUAM system (Dash et al, 2010). A 0.02-deg equal-angle gridded L3C product 0.7GB/day) is available at https://podaac.jpl.nasa.gov/dataset/H09-AHI-L3C-ACSPO-v2.90","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2744808497-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"http://www.ghrsst.org","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/ghrsst/open/data/GDS2/L2P/H09/STAR/docs/H09_140_7_E.nc","format":"NetCDF","mediaType":"application/netcdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/ghrsst/open/data/GDS2/L2P/H09/STAR/docs/geo_nav.py","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/ghrsst/open/docs/GDS20r5.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2744808497-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ghrsst.jpl.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/podaac/data-readers","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/podaac/data-subscriber","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://opendap.earthdata.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/CitingPODAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2744808497-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/sod/sst/iquam/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/sod/sst/squam/","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GHH09-2P290","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"DOC/NOAA/NESDIS/STAR;NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 60.0, \"WestBoundingCoordinate\": 80.0, \"EastBoundingCoordinate\": -160.0, \"SouthBoundingCoordinate\": -60.0}]]","theme":["Earth Science"],"title":"GHRSST L2P NOAA/ACSPO Himawari-09 AHI Pacific Ocean Region Sea Surface Temperature v2.90 dataset"},"description":"The H09-AHI-L2P-ACSPO-v2.90 dataset contains the Subskin Sea Surface Temperature (SST) produced by the NOAA ACSPO system from the Advanced Himawari Imager (AHI; largely identical to GOES-R/ABI) onboard the Himawari-9 (H09) satellite. The H09 is a Japanese weather satellite, the 9th of the Himawari geostationary weather satellite operated by the Japan Meteorological Agency. It was launched on November 2, 2016 into its nominal position at 140.7-deg E, and declared operational on December 13, 2022, replacing the Himawari-8. The AHI is the primary instrument on the Himawari Series for imaging Earth\u2019s weather, oceans, and environment with high temporal and spatial resolutions.  \n\nThe H08/AHI maps SST in a Full Disk (FD) area from 80E-160W and 60S-60N, with spatial resolution 2km at nadir to 15km/VZA (view zenith angle) 67-deg, and 10-min temporal sampling. The 10-min FD data are subsequently collated in time, to produce the 1-hr product, with improved coverage and reduced cloud leakages and image noise. The L2P data is produced in GHRSST compliant netCDF4 GDS2 format, with 24 granules per day, and a total data volume 1.2 GB/day. The near-real time (NRT) data are updated hourly, with several hours latency. The NRT files are replaced with Delayed Mode (DM) files, with a latency of approximately 2-months. File names remain unchanged, and DM vs NRT can be identified by different time stamps and global attributes inside the files (MERRA instead of GFS for atmospheric profiles, and same day CMC L4 analyses in DM instead of one-day delayed in NRT processing).  \n\nPixel earth locations are not reported in the granules, as they remain unchanged from granule to granule. Pixel locations  can be obtained using a flat lat/lon file or a Python script available via Documents tab from the dataset landing page. Climate and Forecast (CF) metadata aware software (e.g., Panoply, xarray) can detect and map the data as is via the granule CF projection attributes and variables. The ACSPO H09 HAI SSTs are validated against quality controlled in situ data from the NOAA iQuam system (Xu and Ignatov, 2014) and continuously monitored in the NOAA SQUAM system (Dash et al, 2010). A 0.02-deg equal-angle gridded L3C product 0.7GB/day) is available at https://podaac.jpl.nasa.gov/dataset/H09-AHI-L3C-ACSPO-v2.90","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/bc647bbc-662e-47f7-89ee-36405edfd735","harvest_record_raw":"https://catalog.data.gov/harvest_record/bc647bbc-662e-47f7-89ee-36405edfd735/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GHH09-2P290","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:05:52.476494","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"DOC/NOAA/NESDIS/STAR;NASA/JPL/PODAAC","slug":"ghrsst-l2p-noaa-acspo-himawari-09-ahi-pacific-ocean-region-sea-surface-temperature-v2-90-d","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GHRSST L2P NOAA/ACSPO Himawari-09 AHI Pacific Ocean Region Sea Surface Temperature v2.90 dataset","type":"dataset"},{"_score":5.8226395,"_sort":[1790125552160,5.8226395,1,"65d6b691-a339-44f1-ac0a-66c2eebe7d44"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07B is the current version of the IMERG data sets. Older versions will no longer be available and have been superseded by Version 07.\n\nThe Integrated Multi-satellitE Retrievals for GPM (IMERG) is the unified U.S. algorithm that provides the multi-satellite precipitation product for the U.S. GPM team.\n\nThe precipitation estimates from the various precipitation-relevant satellite passive microwave (PMW) sensors comprising the GPM constellation are computed using the 2021 version of the Goddard Profiling Algorithm (GPROF2021), then gridded, intercalibrated to the GPM Combined Ku Radar-Radiometer Algorithm (CORRA) product, and merged into half-hourly 0.1\u00b0x0.1\u00b0 (roughly 10x10 km) fields. Note that CORRA is adjusted to the monthly Global Precipitation Climatology Project (GPCP) Satellite-Gauge (SG) product over high-latitude ocean to correct known biases.\n\nThe half-hourly intercalibrated merged PMW estimates are then input to both a Morphing-Kalman Filter (KF) Lagrangian time interpolation scheme based on work by the Climate Prediction Center (CPC) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Dynamic Infrared\u2013Rain Rate (PDIR) re-calibration scheme. In parallel, CPC assembles the zenith-angle-corrected, intercalibrated merged geo-IR fields and forwards them to PPS for input to the PERSIANN-CCS algorithm (supported by an asynchronous re-calibration cycle) which are then input to the KF morphing (quasi-Lagrangian time interpolation) scheme.\n\nThe KF morphing (supported by an asynchronous KF weights updating cycle) uses the PMW and IR estimates to create half-hourly estimates. Motion vectors for the morphing are computed by maximizing the pattern correlation of successive hours within each of the precipitation (PRECTOT), total precipitable liquid water (TQL), and vertically integrated vapor (TQV) data fields provided by the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) and Goddard Earth Observing System model Version 5 (GEOS-5) Forward Processing (FP) for the post-real-time (Final) Run and the near-real-time (Early and Late) Runs, respectively. The vectors from PRECTOT are chosen if available, else from TQL, if available, else from TQV. The KF uses the morphed data as the \u201cforecast\u201d and the IR estimates as the \u201cobservations\u201d, with weighting that depends on the time interval(s) away from the microwave overpass time. The IR becomes important after about \u00b190 minutes away from the overpass time. Variable averaging in the KF is accounted for in a routine (Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood, or SHARPEN) that compares the local histogram of KF morphed precipitation to the local histogram of forward- and backward-morphed microwave data and the IR.\n\nThe IMERG system is run twice in near-real time:\n\n\"Early\" multi-satellite product ~4 hr after observation time using only forward morphing and\n\"Late\" multi-satellite product ~14 hr after observation time, using both forward and backward morphing\nand once after the monthly gauge analysis is received:\n\n\"Final\", satellite-gauge product ~4 months after the observation month, using both forward and backward morphing and including monthly gauge analyses.\n\nIn V07, the near-real-time Early and Late half-hourly estimates have a monthly climatological concluding calibration based on averaging the concluding calibrations computed in the Final, while in the post-real-time Final Run the multi-satellite half-hourly estimates are adjusted so that they sum to the Final Run monthly satellite-gauge combination. In all cases the output contains multiple fields that provide information on the input data, selected intermediate fields, and estimation quality. In general, the complete calibrated precipitation, precipitation, is the data field of choice for most users.\n\nPrecipitation phase is a diagnostic variable computed using analyses of surface temperature, humidity, and pressure.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2723754845-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/IMERG_TechnicalDocumentation_final.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/IMERG_V07_ATBD_final.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2723754845-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3IMERGHHL_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/IMERGV06_QI.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/MorphingInV06IMERG.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3IMERGHHL_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://giovanni.gsfc.nasa.gov/#dataKeyword=IMERGHHL","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov/resources/documents/imerg-v07-release-notes","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2723754845-GES_DISC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/IMERG/3B-HH-L/07","keyword":["earth-science-precipitation-atmosphere","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-amount","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","theme":["Earth Science"],"title":"GPM IMERG Late Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07 (GPM_3IMERGHHL)"},"description":"Version 07B is the current version of the IMERG data sets. Older versions will no longer be available and have been superseded by Version 07.\n\nThe Integrated Multi-satellitE Retrievals for GPM (IMERG) is the unified U.S. algorithm that provides the multi-satellite precipitation product for the U.S. GPM team.\n\nThe precipitation estimates from the various precipitation-relevant satellite passive microwave (PMW) sensors comprising the GPM constellation are computed using the 2021 version of the Goddard Profiling Algorithm (GPROF2021), then gridded, intercalibrated to the GPM Combined Ku Radar-Radiometer Algorithm (CORRA) product, and merged into half-hourly 0.1\u00b0x0.1\u00b0 (roughly 10x10 km) fields. Note that CORRA is adjusted to the monthly Global Precipitation Climatology Project (GPCP) Satellite-Gauge (SG) product over high-latitude ocean to correct known biases.\n\nThe half-hourly intercalibrated merged PMW estimates are then input to both a Morphing-Kalman Filter (KF) Lagrangian time interpolation scheme based on work by the Climate Prediction Center (CPC) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Dynamic Infrared\u2013Rain Rate (PDIR) re-calibration scheme. In parallel, CPC assembles the zenith-angle-corrected, intercalibrated merged geo-IR fields and forwards them to PPS for input to the PERSIANN-CCS algorithm (supported by an asynchronous re-calibration cycle) which are then input to the KF morphing (quasi-Lagrangian time interpolation) scheme.\n\nThe KF morphing (supported by an asynchronous KF weights updating cycle) uses the PMW and IR estimates to create half-hourly estimates. Motion vectors for the morphing are computed by maximizing the pattern correlation of successive hours within each of the precipitation (PRECTOT), total precipitable liquid water (TQL), and vertically integrated vapor (TQV) data fields provided by the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) and Goddard Earth Observing System model Version 5 (GEOS-5) Forward Processing (FP) for the post-real-time (Final) Run and the near-real-time (Early and Late) Runs, respectively. The vectors from PRECTOT are chosen if available, else from TQL, if available, else from TQV. The KF uses the morphed data as the \u201cforecast\u201d and the IR estimates as the \u201cobservations\u201d, with weighting that depends on the time interval(s) away from the microwave overpass time. The IR becomes important after about \u00b190 minutes away from the overpass time. Variable averaging in the KF is accounted for in a routine (Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood, or SHARPEN) that compares the local histogram of KF morphed precipitation to the local histogram of forward- and backward-morphed microwave data and the IR.\n\nThe IMERG system is run twice in near-real time:\n\n\"Early\" multi-satellite product ~4 hr after observation time using only forward morphing and\n\"Late\" multi-satellite product ~14 hr after observation time, using both forward and backward morphing\nand once after the monthly gauge analysis is received:\n\n\"Final\", satellite-gauge product ~4 months after the observation month, using both forward and backward morphing and including monthly gauge analyses.\n\nIn V07, the near-real-time Early and Late half-hourly estimates have a monthly climatological concluding calibration based on averaging the concluding calibrations computed in the Final, while in the post-real-time Final Run the multi-satellite half-hourly estimates are adjusted so that they sum to the Final Run monthly satellite-gauge combination. In all cases the output contains multiple fields that provide information on the input data, selected intermediate fields, and estimation quality. In general, the complete calibrated precipitation, precipitation, is the data field of choice for most users.\n\nPrecipitation phase is a diagnostic variable computed using analyses of surface temperature, humidity, and pressure.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/fe3959da-4411-49be-9b45-38e1d99cd462","harvest_record_raw":"https://catalog.data.gov/harvest_record/fe3959da-4411-49be-9b45-38e1d99cd462/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/IMERG/3B-HH-L/07","keyword":["earth-science-precipitation-atmosphere","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-amount","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation"],"last_harvested_date":"2026-09-23T01:05:52.160319","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-imerg-late-precipitation-l3-half-hourly-0-1-degree-x-0-1-degree-v07-gpm_3imerghhl-at-g","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM IMERG Late Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07 (GPM_3IMERGHHL)","type":"dataset"},{"_score":40.773266,"_sort":[1790125551176,40.773266,2,"cf06ebcd-1e09-474a-9a33-95375463e2f7"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\nThe 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: GMI, SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18) AMSR2 (GCOM-W1), TMI MHS (NOAA 18&19, METOP A&B), ATMS (NPP), SAPHIR (MT1) This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty. ABSTRACT","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264134219-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264134219-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFMETOPBMHS_CLIM_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFMETOPBMHS_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L2/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264134219-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/mhs.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/MHS/METOPB/GPROFCLIM/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2012-09-25/2025-12-01","theme":["Earth Science"],"title":"GPM MHS on METOP-B (GPROF) Climate-based Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07 (GPM_2AGPROFMETOPBMHS_CLIM)"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\nThe 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: GMI, SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18) AMSR2 (GCOM-W1), TMI MHS (NOAA 18&19, METOP A&B), ATMS (NPP), SAPHIR (MT1) This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty. ABSTRACT","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/01aa0225-3280-424c-a511-48fb6e68f850","harvest_record_raw":"https://catalog.data.gov/harvest_record/01aa0225-3280-424c-a511-48fb6e68f850/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/MHS/METOPB/GPROFCLIM/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:51.176531","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-metop-b-gprof-climate-based-radiometer-precipitation-profiling-l2a-1-5-hours-17","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM MHS on METOP-B (GPROF) Climate-based Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07 (GPM_2AGPROFMETOPBMHS_CLIM)","type":"dataset"},{"_score":42.09796,"_sort":[1790125550481,42.09796,1,"5100c56a-2cc6-4d8b-ac80-c1b24a51176d"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264135750-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264135750-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFMETOPBMHS_DAY_CLIM_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFMETOPBMHS_DAY_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264135750-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/mhs.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/MHS/METOPB/GPROFCLIM/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2012-09-25/2025-11-30","theme":["Earth Science"],"title":"GPM MHS on METOP-B (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFMETOPBMHS_DAY_CLIM)"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/9241d318-2d94-423b-9bfa-62e82fda156b","harvest_record_raw":"https://catalog.data.gov/harvest_record/9241d318-2d94-423b-9bfa-62e82fda156b/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/MHS/METOPB/GPROFCLIM/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:50.481909","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-metop-b-gprof-climate-based-radiometer-precipitation-profiling-l3-1-day-0-25-de","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM MHS on METOP-B (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFMETOPBMHS_DAY_CLIM)","type":"dataset"},{"_score":15.911303,"_sort":[1790125550146,15.911303,1,"8296b57d-2b2f-4577-aa6f-b7194264daeb"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264134788-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264134788-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFMETOPBMHS_DAY_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFMETOPBMHS_DAY_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264134788-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/mhs.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/MHS/METOPB/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2022-05-01/2026-02-28","theme":["Earth Science"],"title":"GPM MHS on METOP-B (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFMETOPBMHS_DAY)"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. \n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/16f61b77-db83-415b-971b-2a3ee66dcec9","harvest_record_raw":"https://catalog.data.gov/harvest_record/16f61b77-db83-415b-971b-2a3ee66dcec9/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/MHS/METOPB/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:50.146993","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-metop-b-gprof-radiometer-precipitation-profiling-l3-1-day-0-25-degree-x-0-25-de","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM MHS on METOP-B (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFMETOPBMHS_DAY)","type":"dataset"},{"_score":42.09796,"_sort":[1790125549099,42.09796,2,"570fcd5c-61ab-4c30-920d-a41775c7ff5a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264135780-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264135780-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFMETOPCMHS_DAY_CLIM_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFMETOPCMHS_DAY_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264135780-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/mhs.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/MHS/METOPC/GPROFCLIM/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2018-11-16/2025-11-30","theme":["Earth Science"],"title":"GPM MHS on METOP-C (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFMETOPCMHS_DAY_CLIM)"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/ab81b537-6fbb-4951-99e9-2e28da47a82a","harvest_record_raw":"https://catalog.data.gov/harvest_record/ab81b537-6fbb-4951-99e9-2e28da47a82a/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/MHS/METOPC/GPROFCLIM/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:49.099662","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-metop-c-gprof-climate-based-radiometer-precipitation-profiling-l3-1-day-0-25-de","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM MHS on METOP-C (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree V07 (GPM_3GPROFMETOPCMHS_DAY_CLIM)","type":"dataset"},{"_score":9.5426655,"_sort":[1790125548772,9.5426655,2,"2badf5f5-fc91-446c-a95c-d528cd5b3176"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The GOES-19 Advanced Baseline Imager (ABI) Level 3C Sea Surface Temperature (SST) dataset, produced by the National Oceanic and Atmospheric Administration (NOAA), provides gridded observations of sea surface temperature derived from satellite-based thermal infrared measurements acquired by the ABI instrument aboard the GOES-19 geostationary satellite. Originally launched as GOES-U on 25 June 2024 and renamed GOES-19 after reaching geostationary orbit, the satellite operates at an altitude of approximately 35,800 km and continuously observes a Full Disk domain spanning approximately 15\u00b0W\u2013135\u00b0W and 60\u00b0S\u201360\u00b0N. The ABI is a 16-band multispectral imager designed to provide enhanced SST retrieval capability through improved radiometric calibration, image navigation, co-registration accuracy, spectral fidelity, and advanced preprocessing. SST retrievals are derived from thermal infrared observations acquired every 10 minutes and provide near-continuous monitoring of ocean surface thermal conditions across the GOES Full Disk domain.\n\nThe Level 3C SST product is generated by the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) system from collated Level 2 Preprocessed (L2P) SST retrievals. The Level 3C product provides hourly gridded SST fields on a regular 0.02-degree equal-angle grid and is distributed in netCDF4 format compliant with the GHRSST Data Specification Version 2 (GDS2). Compared with the source L2P product, the L3C product offers reduced data volume and a regularly gridded representation that simplifies visualization, analysis, and data assimilation workflows. The dataset supports applications including operational oceanography, weather forecasting, marine environmental monitoring, climate studies, ecosystem assessments, and satellite data assimilation.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C4155452419-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"http://www.ghrsst.org","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/ghrsst/open/docs/GDS20r5.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C4155452419-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://coastwatch.noaa.gov/pub/socd2/coastwatch/sst/documents/ACSPO_SST_ATBD_v2p00.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/podaac/data-subscriber","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://opendap.earthdata.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/CitingPODAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/Podaac/thumbnails/ABI_G16-STAR-L3C-v2.70.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C4155452419-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/sod/sst/iquam/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/sod/sst/squam/","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GHG19-3C300","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"DOC/NOAA/NESDIS/STAR;NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 81, \"WestBoundingCoordinate\": -156, \"EastBoundingCoordinate\": 6, \"SouthBoundingCoordinate\": -81}]]","theme":["Earth Science"],"title":"GHRSST NOAA/STAR GOES-19 ABI L3C America Region SST v3.0 dataset"},"description":"The GOES-19 Advanced Baseline Imager (ABI) Level 3C Sea Surface Temperature (SST) dataset, produced by the National Oceanic and Atmospheric Administration (NOAA), provides gridded observations of sea surface temperature derived from satellite-based thermal infrared measurements acquired by the ABI instrument aboard the GOES-19 geostationary satellite. Originally launched as GOES-U on 25 June 2024 and renamed GOES-19 after reaching geostationary orbit, the satellite operates at an altitude of approximately 35,800 km and continuously observes a Full Disk domain spanning approximately 15\u00b0W\u2013135\u00b0W and 60\u00b0S\u201360\u00b0N. The ABI is a 16-band multispectral imager designed to provide enhanced SST retrieval capability through improved radiometric calibration, image navigation, co-registration accuracy, spectral fidelity, and advanced preprocessing. SST retrievals are derived from thermal infrared observations acquired every 10 minutes and provide near-continuous monitoring of ocean surface thermal conditions across the GOES Full Disk domain.\n\nThe Level 3C SST product is generated by the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) system from collated Level 2 Preprocessed (L2P) SST retrievals. The Level 3C product provides hourly gridded SST fields on a regular 0.02-degree equal-angle grid and is distributed in netCDF4 format compliant with the GHRSST Data Specification Version 2 (GDS2). Compared with the source L2P product, the L3C product offers reduced data volume and a regularly gridded representation that simplifies visualization, analysis, and data assimilation workflows. The dataset supports applications including operational oceanography, weather forecasting, marine environmental monitoring, climate studies, ecosystem assessments, and satellite data assimilation.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/7c50eac7-0ba9-44c0-9746-64d43d6f9c6e","harvest_record_raw":"https://catalog.data.gov/harvest_record/7c50eac7-0ba9-44c0-9746-64d43d6f9c6e/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GHG19-3C300","keyword":["earth-science-ocean-temperature-oceans-sea-surface-temperature"],"last_harvested_date":"2026-09-23T01:05:48.772351","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"DOC/NOAA/NESDIS/STAR;NASA/JPL/PODAAC","slug":"ghrsst-noaa-star-goes-19-abi-l3c-america-region-sst-v3-0-dataset","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GHRSST NOAA/STAR GOES-19 ABI L3C America Region SST v3.0 dataset","type":"dataset"},{"_score":41.584248,"_sort":[1790125548455,41.584248,1,"cc3dc08a-26c8-4d45-89fe-e77e440a8143"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264135766-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264135766-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFMETOPCMHS_CLIM_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFMETOPCMHS_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264135766-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/mhs.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/MHS/METOPC/GPROFCLIM/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2018-11-01/2025-11-30","theme":["Earth Science"],"title":"GPM MHS on METOP-C (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFMETOPCMHS_CLIM)"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/4f251b18-4918-4dc4-a611-d5d6db1c75b1","harvest_record_raw":"https://catalog.data.gov/harvest_record/4f251b18-4918-4dc4-a611-d5d6db1c75b1/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/MHS/METOPC/GPROFCLIM/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:48.455287","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-metop-c-gprof-climate-based-radiometer-precipitation-profiling-l3-1-month-0-25-","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM MHS on METOP-C (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFMETOPCMHS_CLIM)","type":"dataset"},{"_score":13.19408,"_sort":[1790125548130,13.19408,6,"10b393b5-670b-41ff-94d7-f380f917cc3d"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"This dataset contains the Global Mean Sea Level (GMSL) trend generated from the Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.2. The GMSL trend is a 1-dimensional time series of globally averaged Sea Surface Height Anomalies (SSHA) from TOPEX/Poseidon, Jason-1, OSTM/Jason-2, Jason-3, and Sentinel-6A that covers September 1992 to present with a lag of up to 4 months. The data are reported as variations relative to a 20-year TOPEX/Jason collinear mean. Bias adjustments and cross-calibrations were applied to ensure SSHA data are consistent across the missions; Glacial Isostatic Adjustment (GIA) was also applied. The data are available as a table in ASCII format. Changes between the version 5.1 and version 5.2 releases are described in detail in the user handbook.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2902359309-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2902359309-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1002/2017JC013090","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1016/j.asr.2010.02.020","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1016/j.asr.2010.05.007","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1016/j.asr.2010.05.008","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1029/2007GL030002","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1073/pnas.1717312115","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1080/01490410490465643","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1109/TGRS.2006.888098","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1109/TGRS.2009.2037220","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1175/2009JTECHA1305.1","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1175/JTECH1993.1","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/ALTUG-TJ152","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/podaac/data-subscriber","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ntrs.nasa.gov/citations/19990089548","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/CitingPODAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/NASA-SSH","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/Podaac/thumbnails/MERGED_TP_J1_OSTM_OST_GMSL_ASCII_V52.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2902359309-POCLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GMSLM-TJ152","keyword":["earth-science-sea-surface-topography-oceans-sea-surface-height"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD;NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"SouthBoundingCoordinate\": -66, \"EastBoundingCoordinate\": 180, \"NorthBoundingCoordinate\": 66}]]","theme":["Earth Science"],"title":"Global Mean Sea Level Trend from Integrated Multi-Mission Ocean Altimeters TOPEX/Poseidon, Jason-1, OSTM/Jason-2, Jason-3, and Sentinel-6 Version 5.2"},"description":"This dataset contains the Global Mean Sea Level (GMSL) trend generated from the Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.2. The GMSL trend is a 1-dimensional time series of globally averaged Sea Surface Height Anomalies (SSHA) from TOPEX/Poseidon, Jason-1, OSTM/Jason-2, Jason-3, and Sentinel-6A that covers September 1992 to present with a lag of up to 4 months. The data are reported as variations relative to a 20-year TOPEX/Jason collinear mean. Bias adjustments and cross-calibrations were applied to ensure SSHA data are consistent across the missions; Glacial Isostatic Adjustment (GIA) was also applied. The data are available as a table in ASCII format. Changes between the version 5.1 and version 5.2 releases are described in detail in the user handbook.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/03f95572-e902-4d68-8c3c-fc5de9812744","harvest_record_raw":"https://catalog.data.gov/harvest_record/03f95572-e902-4d68-8c3c-fc5de9812744/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GMSLM-TJ152","keyword":["earth-science-sea-surface-topography-oceans-sea-surface-height"],"last_harvested_date":"2026-09-23T01:05:48.130992","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":6,"publisher":"NASA/GSFC/SED/ESD;NASA/JPL/PODAAC","slug":"global-mean-sea-level-trend-from-integrated-multi-mission-ocean-altimeters-topex-poseidon-","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Global Mean Sea Level Trend from Integrated Multi-Mission Ocean Altimeters TOPEX/Poseidon, Jason-1, OSTM/Jason-2, Jason-3, and Sentinel-6 Version 5.2","type":"dataset"},{"_score":14.017084,"_sort":[1790125547484,14.017084,1,"21259a24-6df1-41ad-82eb-5cc8800b5619"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set.  \n\nThe 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: GMI, SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18) AMSR2 (GCOM-W1), TMI MHS (NOAA 18&19, METOP A;B;C), ATMS (NPP), SAPHIR (MT1) This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty. ABSTRACT","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264133834-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264133834-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFMETOPCMHS_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFMETOPCMHS_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L2/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264133834-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/mhs.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/MHS/METOPC/GPROF/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2022-04-30/2026-03-01","theme":["Earth Science"],"title":"GPM MHS on METOP-C (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07 (GPM_2AGPROFMETOPCMHS)"},"description":"Version 07 is the current version of the data set.  \n\nThe 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: GMI, SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18) AMSR2 (GCOM-W1), TMI MHS (NOAA 18&19, METOP A;B;C), ATMS (NPP), SAPHIR (MT1) This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty. ABSTRACT","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/26e0998e-d80d-443e-a187-7a60a3e318c8","harvest_record_raw":"https://catalog.data.gov/harvest_record/26e0998e-d80d-443e-a187-7a60a3e318c8/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/MHS/METOPC/GPROF/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:47.484397","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-metop-c-gprof-radiometer-precipitation-profiling-l2a-1-5-hours-17-km-v07-gpm_2a","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM MHS on METOP-C (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07 (GPM_2AGPROFMETOPCMHS)","type":"dataset"},{"_score":16.676727,"_sort":[1790125547138,16.676727,2,"6627ee7a-7c09-4ced-8f97-20af023b176c"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set.  \n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264134803-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264134803-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFMETOPCMHS_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFMETOPCMHS_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264134803-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/mhs.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/MHS/METOPC/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2022-05-01/2026-02-28","theme":["Earth Science"],"title":"GPM MHS on METOP-C (GPROF) Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFMETOPCMHS)"},"description":"Version 07 is the current version of the data set.  \n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/02ef9508-c1f3-4888-ace4-4dae33f2ca50","harvest_record_raw":"https://catalog.data.gov/harvest_record/02ef9508-c1f3-4888-ace4-4dae33f2ca50/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/MHS/METOPC/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:47.138534","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-metop-c-gprof-radiometer-precipitation-profiling-l3-1-month-0-25-degree-x-0-25-","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM MHS on METOP-C (GPROF) Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFMETOPCMHS)","type":"dataset"},{"_score":16.697327,"_sort":[1790125546490,16.697327,6,"cd43e4b3-01c6-4f10-8732-cdddce812d8c"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"FOR EXPERT USE ONLY. This dataset contains estimates of the total month-by-month geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission measurements, produced by the NASA Jet Propulsion Laboratory (JPL). The data are provided as spherical harmonic coefficients, averaged over approximately a month, and available from 2018 onward. These coefficients are derived from the Microwave Instrument (MWI) measured intersatellite range changes between the twin spacecraft of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) mission. The GRACE-FO mission, a joint partnership between NASA and the German Research Centre for Geosciences (GFZ), launched on 22 May 2018. It uses twin satellites to accurately map variations in the Earth's gravity field and surface mass distribution. It is designed as a successor to the Gravity Recovery and Climate Experiment (GRACE) mission. \n\nThis GRACE-FO RL06.3 data is an updated version of the GRACE-FO RL06.1 Level-2 data products. RL06.3 differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 satellite: Level-2 RL06.3 uses ACH1B RL04 that is contained within the ACX2 Level-1 bundle, which replaces ACH1B RL04 contained within the ACX Level-1 bundle that was used for Level-2 RL06.1 (note: ACX2-L1B is only applicable for 01/2023 onwards in wide-pointing operational mode; from 6/2018 through 12/2022, RL06.1 and RL06.3 GRACE-FO data are identical and based on ACX; ACX2 is not available for 03/2023-06/2023 as the satellites were not in wide-pointing mode during that period). All GRACE-FO RL06.3 Level-2 products are fully compatible with the GRACE RL06 level-2 fields. Refer to the mission page for more information.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3059700062-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L2-JPL_ProcStds.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L2-ReleaseNotes_JPL_RL06.3.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L2_UserHandbook.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/TN-13_GEOC_JPL_RL0601.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/TN-14_C30_C20_GSFC_SLR.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3059700062-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/podaac/data-subscriber","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gracefo.jpl.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/CitingPODAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/GRACE-FO","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/Podaac/thumbnails/GRACEFO_L2_JPL_MONTHLY_0063.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/gravity/gracefo-documentation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3059700062-POCLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GFL20-MJ063","keyword":["earth-science-gravity-gravitational-field-solid-earth-gravity"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/GRACE-TELLUS-0001;NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 89, \"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -89}]]","temporal":"2018-05-22/2026-09-07","theme":["Earth Science"],"title":"GRACE-FO Level-2  Monthly Geopotential Spherical Harmonics JPL Release 6.3 (RL06.3)"},"description":"FOR EXPERT USE ONLY. This dataset contains estimates of the total month-by-month geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission measurements, produced by the NASA Jet Propulsion Laboratory (JPL). The data are provided as spherical harmonic coefficients, averaged over approximately a month, and available from 2018 onward. These coefficients are derived from the Microwave Instrument (MWI) measured intersatellite range changes between the twin spacecraft of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) mission. The GRACE-FO mission, a joint partnership between NASA and the German Research Centre for Geosciences (GFZ), launched on 22 May 2018. It uses twin satellites to accurately map variations in the Earth's gravity field and surface mass distribution. It is designed as a successor to the Gravity Recovery and Climate Experiment (GRACE) mission. \n\nThis GRACE-FO RL06.3 data is an updated version of the GRACE-FO RL06.1 Level-2 data products. RL06.3 differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 satellite: Level-2 RL06.3 uses ACH1B RL04 that is contained within the ACX2 Level-1 bundle, which replaces ACH1B RL04 contained within the ACX Level-1 bundle that was used for Level-2 RL06.1 (note: ACX2-L1B is only applicable for 01/2023 onwards in wide-pointing operational mode; from 6/2018 through 12/2022, RL06.1 and RL06.3 GRACE-FO data are identical and based on ACX; ACX2 is not available for 03/2023-06/2023 as the satellites were not in wide-pointing mode during that period). All GRACE-FO RL06.3 Level-2 products are fully compatible with the GRACE RL06 level-2 fields. Refer to the mission page for more information.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/adbbd6dc-7bcd-4158-8672-76e8e8c494d7","harvest_record_raw":"https://catalog.data.gov/harvest_record/adbbd6dc-7bcd-4158-8672-76e8e8c494d7/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GFL20-MJ063","keyword":["earth-science-gravity-gravitational-field-solid-earth-gravity"],"last_harvested_date":"2026-09-23T01:05:46.490243","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":6,"publisher":"NASA/JPL/GRACE-TELLUS-0001;NASA/JPL/PODAAC","slug":"grace-fo-level-2-monthly-geopotential-spherical-harmonics-jpl-release-6-3-rl06-3","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GRACE-FO Level-2  Monthly Geopotential Spherical Harmonics JPL Release 6.3 (RL06.3)","type":"dataset"},{"_score":16.677713,"_sort":[1790125546177,16.677713,2,"b4bea2a0-3c25-41b0-a474-5024879787bc"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"FOR EXPERT USE ONLY. This dataset contains estimates of the total month-by-month geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission measurements, produced by the University of Texas (at Austin) Center for Space Research (CSR). The data are provided as spherical harmonic coefficients, averaged over approximately a month, and available from 2018 onward. These coefficients are derived from the Microwave Instrument (MWI) measured intersatellite range changes between the twin spacecraft of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) mission. The GRACE-FO mission, a joint partnership between NASA and the German Research Centre for Geosciences (GFZ), launched on 22 May 2018. It uses twin satellites to accurately map variations in the Earth's gravity field and surface mass distribution. It is designed as a successor to the Gravity Recovery and Climate Experiment (GRACE) mission. \n\nThis GRACE-FO RL06.3 data is an updated version of the GRACE-FO RL06.1 Level-2 data products. RL06.3 differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 satellite: Level-2 RL06.3 uses ACH1B RL04 that is contained within the ACX2 Level-1 bundle, which replaces ACH1B RL04 contained within the ACX Level-1 bundle that was used for Level-2 RL06.1 (note: ACX2-L1B is only applicable for 01/2023 onwards in wide-pointing operational mode; from 6/2018 through 12/2022, RL06.1 and RL06.3 GRACE-FO data are identical and based on ACX; ACX2 is not available for 03/2023-06/2023 as the satellites were not in wide-pointing mode during that period). All GRACE-FO RL06.3 Level-2 products are fully compatible with the GRACE RL06 level-2 fields. Refer to the mission page for more information.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3059656222-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L2-CSR_ProcStds_v1.1.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L2-ReleaseNotes_CSR_RL06.3.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L2_UserHandbook.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/TN-13_GEOC_CSR_RL0603.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/TN-14_C30_C20_GSFC_SLR.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3059656222-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/podaac/data-subscriber","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gracefo.jpl.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/CitingPODAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/GRACE-FO","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/Podaac/thumbnails/GRACEFO_L2_CSR_MONTHLY_0063.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/gravity/gracefo-documentation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3059656222-POCLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GFL20-MC063","keyword":["earth-science-gravity-gravitational-field-solid-earth-gravity"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/PODAAC;UTX-AUSTIN/CSR"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 89, \"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -89}]]","theme":["Earth Science"],"title":"GRACE-FO Level-2 Monthly Geopotential Spherical Harmonics CSR Release 06.3 (RL06.3)"},"description":"FOR EXPERT USE ONLY. This dataset contains estimates of the total month-by-month geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission measurements, produced by the University of Texas (at Austin) Center for Space Research (CSR). The data are provided as spherical harmonic coefficients, averaged over approximately a month, and available from 2018 onward. These coefficients are derived from the Microwave Instrument (MWI) measured intersatellite range changes between the twin spacecraft of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) mission. The GRACE-FO mission, a joint partnership between NASA and the German Research Centre for Geosciences (GFZ), launched on 22 May 2018. It uses twin satellites to accurately map variations in the Earth's gravity field and surface mass distribution. It is designed as a successor to the Gravity Recovery and Climate Experiment (GRACE) mission. \n\nThis GRACE-FO RL06.3 data is an updated version of the GRACE-FO RL06.1 Level-2 data products. RL06.3 differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 satellite: Level-2 RL06.3 uses ACH1B RL04 that is contained within the ACX2 Level-1 bundle, which replaces ACH1B RL04 contained within the ACX Level-1 bundle that was used for Level-2 RL06.1 (note: ACX2-L1B is only applicable for 01/2023 onwards in wide-pointing operational mode; from 6/2018 through 12/2022, RL06.1 and RL06.3 GRACE-FO data are identical and based on ACX; ACX2 is not available for 03/2023-06/2023 as the satellites were not in wide-pointing mode during that period). All GRACE-FO RL06.3 Level-2 products are fully compatible with the GRACE RL06 level-2 fields. Refer to the mission page for more information.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/f95038f5-1a56-4cc2-abb5-e6731ce8ddb9","harvest_record_raw":"https://catalog.data.gov/harvest_record/f95038f5-1a56-4cc2-abb5-e6731ce8ddb9/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GFL20-MC063","keyword":["earth-science-gravity-gravitational-field-solid-earth-gravity"],"last_harvested_date":"2026-09-23T01:05:46.177580","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA/JPL/PODAAC;UTX-AUSTIN/CSR","slug":"grace-fo-level-2-monthly-geopotential-spherical-harmonics-csr-release-06-3-rl06-3","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GRACE-FO Level-2 Monthly Geopotential Spherical Harmonics CSR Release 06.3 (RL06.3)","type":"dataset"},{"_score":13.608549,"_sort":[1790125545857,13.608549,1,"f2fd7817-005e-4446-b2d4-3999936c4b24"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.\n\nThe 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: GMI, SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18) AMSR2 (GCOM-W1), TMI MHS (NOAA 18&19, METOP A&B), ATMS (NPP), SAPHIR (MT1) This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264133875-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264133875-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_2AGPROFNOAA19MHS_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_2AGPROFNOAA19MHS_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L2/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264133875-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/mhs.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/MHS/NOAA19/GPROF/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"GEODETIC\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2022-04-30/2025-06-16","theme":["Earth Science"],"title":"GPM MHS on NOAA-19 (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07 (GPM_2AGPROFNOAA19MHS)"},"description":"Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.\n\nThe 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: GMI, SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18) AMSR2 (GCOM-W1), TMI MHS (NOAA 18&19, METOP A&B), ATMS (NPP), SAPHIR (MT1) This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/acdfc604-5dc1-45be-86b4-757297550d85","harvest_record_raw":"https://catalog.data.gov/harvest_record/acdfc604-5dc1-45be-86b4-757297550d85/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/MHS/NOAA19/GPROF/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:45.857126","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-noaa-19-gprof-radiometer-precipitation-profiling-l2a-1-5-hours-17-km-v07-gpm_2a","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM MHS on NOAA-19 (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07 (GPM_2AGPROFNOAA19MHS)","type":"dataset"},{"_score":10.872794,"_sort":[1790125545517,10.872794,2,"eb3df786-38b2-4aa0-bafa-d1daefa23871"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"FOR EXPERT USE ONLY. This dataset contains estimates of the total month-by-month geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission measurements, produced by the German Research Centre for Geosciences (GFZ). The data are provided as spherical harmonic coefficients, averaged over approximately a month. These coefficients are derived from the Microwave Instrument (MWI) measured intersatellite range changes between the twin spacecraft of the GRACE-FO mission. Refer to the mission page for more information. \n\nThis GRACE-FO RL06.3 data is an updated version of the GRACE-FO RL06.1 Level-2 data products. RL06.3 differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 satellite: Level-2 RL06.3 uses ACH1B RL04 that is contained within the ACX2 Level-1 bundle, which replaces ACH1B RL04 contained within the ACX Level-1 bundle that was used for Level-2 RL06.1 (note: ACX2-L1B is only applicable for 01/2023 onwards in wide-deadband operational mode; from 6/2018 through 12/2022, RL06.1 and RL06.3 GRACE-FO data are identical). All GRACE-FO RL06.3 Level-2 products are fully compatible with the GRACE RL06 level-2 fields. Refer to the mission page for more information.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C3059674861-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L2-GFZ_ProcStds_v1.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L2-ReleaseNotes_GFZ_RL06.3.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/GRACE-FO_L2_UserHandbook.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/TN-13_GEOC_GFZ_RL0603.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/gracefo/open/docs/TN-14_C30_C20_GSFC_SLR.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3059674861-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/podaac/data-subscriber","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gracefo.jpl.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/CitingPODAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/GRACE-FO","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/Podaac/thumbnails/GRACEFO_L2_GFZ_MONTHLY_0063.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/gravity/gracefo-documentation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3059674861-POCLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GFL20-MG063","keyword":["earth-science-gravity-gravitational-field-solid-earth-gravity"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"DE/GFZ/ISDC;NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 89, \"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -89}]]","theme":["Earth Science"],"title":"GRACE-FO Level-2 Monthly Geopotential Spherical Harmonics GFZ Release 6.3 (RL06.3)"},"description":"FOR EXPERT USE ONLY. This dataset contains estimates of the total month-by-month geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission measurements, produced by the German Research Centre for Geosciences (GFZ). The data are provided as spherical harmonic coefficients, averaged over approximately a month. These coefficients are derived from the Microwave Instrument (MWI) measured intersatellite range changes between the twin spacecraft of the GRACE-FO mission. Refer to the mission page for more information. \n\nThis GRACE-FO RL06.3 data is an updated version of the GRACE-FO RL06.1 Level-2 data products. RL06.3 differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 satellite: Level-2 RL06.3 uses ACH1B RL04 that is contained within the ACX2 Level-1 bundle, which replaces ACH1B RL04 contained within the ACX Level-1 bundle that was used for Level-2 RL06.1 (note: ACX2-L1B is only applicable for 01/2023 onwards in wide-deadband operational mode; from 6/2018 through 12/2022, RL06.1 and RL06.3 GRACE-FO data are identical). All GRACE-FO RL06.3 Level-2 products are fully compatible with the GRACE RL06 level-2 fields. Refer to the mission page for more information.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/872ac69c-1903-4947-ba5a-57a5ca151b34","harvest_record_raw":"https://catalog.data.gov/harvest_record/872ac69c-1903-4947-ba5a-57a5ca151b34/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GFL20-MG063","keyword":["earth-science-gravity-gravitational-field-solid-earth-gravity"],"last_harvested_date":"2026-09-23T01:05:45.517765","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"DE/GFZ/ISDC;NASA/JPL/PODAAC","slug":"grace-fo-level-2-monthly-geopotential-spherical-harmonics-gfz-release-6-3-rl06-3","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GRACE-FO Level-2 Monthly Geopotential Spherical Harmonics GFZ Release 6.3 (RL06.3)","type":"dataset"},{"_score":42.70272,"_sort":[1790125545196,42.70272,2,"6bdb8d62-96b9-4563-aff7-55f0d40843bb"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"This data set provides incoming shortwave radiation measurements from fourteen stations of the Greenland Climate Network (GC-Net) distributed over the Greenland Ice Sheet. The original data were obtained from the GC-Net and subsequently quality controlled. The data span from 01 January 1995 through 09 May 2008. The data set is approximately 15 MB comprised of fourteen Network Common Data Form (netCDF) files.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C1386205153-NSIDCV0.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://daacdata.apps.nsidc.org/pub/DATASETS/GCNet/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/6S7UHUH2K5RI","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://nsidc.org/sites/default/files/nsidc-0437-v001-userguide.pdf","format":"PDF","mediaType":"application/pdf"}],"identifier":"10.5067/6S7UHUH2K5RI","keyword":["earth-science-atmospheric-radiation-atmosphere-solar-radiation"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA NSIDC DAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -61.09, \"NorthBoundingCoordinate\": 80.75, \"EastBoundingCoordinate\": -42.5, \"SouthBoundingCoordinate\": 63.15}]]","temporal":"1995-01-01/2008-05-09","theme":["Earth Science"],"title":"Greenland Climate Network (GC-Net) Radiation for Arctic System Reanalysis, Version 1"},"description":"This data set provides incoming shortwave radiation measurements from fourteen stations of the Greenland Climate Network (GC-Net) distributed over the Greenland Ice Sheet. The original data were obtained from the GC-Net and subsequently quality controlled. The data span from 01 January 1995 through 09 May 2008. The data set is approximately 15 MB comprised of fourteen Network Common Data Form (netCDF) files.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/15a74b0d-8f6a-4559-a4ad-5ef765a6d38d","harvest_record_raw":"https://catalog.data.gov/harvest_record/15a74b0d-8f6a-4559-a4ad-5ef765a6d38d/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/6S7UHUH2K5RI","keyword":["earth-science-atmospheric-radiation-atmosphere-solar-radiation"],"last_harvested_date":"2026-09-23T01:05:45.196824","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":2,"publisher":"NASA NSIDC DAAC","slug":"greenland-climate-network-gc-net-radiation-for-arctic-system-reanalysis-version-1","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Greenland Climate Network (GC-Net) Radiation for Arctic System Reanalysis, Version 1","type":"dataset"},{"_score":20.774303,"_sort":[1790125544865,20.774303,1,"c2cc2203-ab39-4ee1-968e-40fa26eb5a3b"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution":[{"@type":"dcat:Distribution","conformsTo":"http://www.isotc211.org/2005/gmi","description":"The metadata's original source.","downloadURL":"https://cmr.earthdata.nasa.gov/search/concepts/C2264136015-GES_DISC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://arthurhou.pps.eosdis.nasa.gov/Documents/ATBD_GPM_V7_GPROF.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2264136015-GES_DISC/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFNOAA19MHS_DAY_CLIM_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFNOAA19MHS_DAY_CLIM_07.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://gpm.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/doc/README.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/pub/GPMfilespec/filespec.GPM.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://gpmweb2https.pps.eosdis.nasa.gov/tsdis/AB/docs/gpm_anomalous.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2264136015-GES_DISC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.star.nesdis.noaa.gov/mirs/mhs.php","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/MHS/NOAA19/GPROFCLIM/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-09-15","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/TISL/GESDISC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180, \"NorthBoundingCoordinate\": 90, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2009-02-12/2025-06-16","theme":["Earth Science"],"title":"GPM MHS on NOAA19 (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree  V07 (GPM_3GPROFNOAA19MHS_DAY_CLIM)"},"description":"Version 07 is the current version of the data set. Older versions are no longer available and have been superseded by Version 07. \n\nThe \"CLIM\"  products differ from their \"regular\" counterparts (without the \"CLIM\" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series.  Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the \"CLIM\" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.\n\n3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/798aa0f0-8a8f-4746-929e-0bd2692cc9f6","harvest_record_raw":"https://catalog.data.gov/harvest_record/798aa0f0-8a8f-4746-929e-0bd2692cc9f6/raw","has_download":true,"has_spatial":true,"identifier":"10.5067/GPM/MHS/NOAA19/GPROFCLIM/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-09-23T01:05:44.865351","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"f4ca4614-8901-409b-8553-2e994ad10023","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png","name":"National Aeronautics and Space Administration","organization_type":"Federal Government","slug":"nasa"},"parent_identifier":null,"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-noaa19-gprof-radiometer-precipitation-profiling-l3-1-day-0-25-degree-x-0-25-deg","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM MHS on NOAA19 (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree  V07 (GPM_3GPROFNOAA19MHS_DAY_CLIM)","type":"dataset"}],"sort":"last_harvested_date"}