{"after":"WzE3ODU4ODUxNzg3NzcsMTAuODc5MjIzLDEsIjkwNGIzNGFkLTEzOTgtNGNlZi04MTUyLTdmZDdhMTVkNTFkOSJd","results":[{"_score":56.707466,"_sort":[1786399550133,56.707466,0,"41081cb8-e7bd-429c-8f4e-86bff7c4e307"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","accrualPeriodicity":"R/P3M","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.orders@noaa.gov"},"describedByType":"application/octet-steam","description":"This data set provides a Climate Data Record (CDR) of sea ice concentration from passive microwave data at a 25 km resolution beginning in late October 1978. It is generated using daily gridded brightness temperatures from the GCOM-W Advanced Microwave Scanning Radiometer - 2 (AMSR2),  the Aqua AMSR-E sensor, the Defense Meteorological Satellite Program (DMSP) series of Special Sensor Microwave Imager/Sounder (SSMIS) and Special Sensor Microwave Imager (SSM/I) passive microwave radiometers onboard F-17, F-13, F-11, and F-8, and the Nimbus Scanning Multichannel Microwave Radiometer (SMMR). The sea ice concentrations are an estimate of the fraction of ocean area covered by sea ice for both the north and south Polar Regions.\n\nThe data are provided at daily and monthly resolutions from late October 1978 through most recent processing in NetCDF-4 CF 1.10 format. The data cover the Arctic and Antarctic regions.\n\nThe related Near-real-time (NRT) NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration is not included in this data submission to NCEI. The daily NRT product is considered to be preliminary data and hosted at NSIDC. The quarterly data submissions to NCEI consist of Final data only.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.ncdc.noaa:C01747","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://archive.data.noaa.gov/climatedatarecords#NSIDC/SIC/Daily/SIC-CDR-D_01B-11/access/","describedByType":"application/octet-stream","description":"S3 Bucket access for Daily SIC dataset files.","mediaType":"text/html","title":"AWS S3 Download (Daily)"},{"@type":"dcat:Distribution","accessURL":"https://archive.data.noaa.gov/climatedatarecords#NSIDC/SIC/Monthly/SIC-CDR-M_01B-11/access/","describedByType":"application/octet-stream","description":"S3 Bucket access for Monthly SIC dataset files.","mediaType":"text/html","title":"AWS S3 Download (Monthly)"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.7265/b18j-z797","describedByType":"application/octet-stream","description":"Dataset landing page with general information and data access links.","mediaType":"text/html","title":"NSIDC Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables","describedByType":"application/octet-stream","description":"Overview of the GCOS Essential Climate Variables.","mediaType":"text/html","title":"GCOS Essential Climate Variables"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov","describedByType":"application/octet-stream","description":"NCEI home page with information, data access and contact information.","mediaType":"text/html","title":"NOAA National Centers for Environmental Information (NCEI)"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01747.xml","issued":"2026-06-17T00:00:00.000+00:00","keyword":["Earth Science > Climate Indicators > Cryospheric Indicators > Sea Ice Concentration","Earth Science > Oceans > Sea Ice > Sea Ice Concentration","Oceanic - Surface - Sea Ice","Ocean > Arctic Ocean","Geographic Region > Polar","NOAA Climate Data Record (CDR) Program","SMMR > Scanning Multichannel Microwave Radiometer","SSM/I > Special Sensor Microwave/Imager","SSMIS > Special Sensor Microwave Imager/Sounder","AMSR-E > Advanced Microwave Scanning Radiometer-EOS","AMSR2 > Advanced Microwave Scanning Radiometer 2","NIMBUS > Nimbus-7","DMSP 5D-2/F8 > Defense Meteorological Satellite Program-F8","DMSP 5D-2/F11 > Defense Meteorological Satellite Program-F11","DMSP 5D-2/F13 > Defense Meteorological Satellite Program-F13","DMSP 5D-3/F17 > Defense Meteorological Satellite Program-F17","AQUA > Earth Observing System, AQUA","GCOM-W1 > Global Change Observation Mission 1st-Water","10 km - < 50 km or approximately .09 degree - < .5 degree","Daily - < Weekly","Weekly - < Monthly","National Centers for Environmental Information","National Oceanic and Atmospheric Administration at the National Snow and Ice Data Center"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2026-06-17T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://doi.org/10.7265/b18j-z797"],"rights":"otherRestrictions","spatial":"180.0,-89.84,-180.0,-31.1","temporal":"1978-10-25T00:00:00+00:00/1978-10-25T00:00:00+00:00","theme":["geospatial"],"title":"NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 6"},"description":"This data set provides a Climate Data Record (CDR) of sea ice concentration from passive microwave data at a 25 km resolution beginning in late October 1978. It is generated using daily gridded brightness temperatures from the GCOM-W Advanced Microwave Scanning Radiometer - 2 (AMSR2),  the Aqua AMSR-E sensor, the Defense Meteorological Satellite Program (DMSP) series of Special Sensor Microwave Imager/Sounder (SSMIS) and Special Sensor Microwave Imager (SSM/I) passive microwave radiometers onboard F-17, F-13, F-11, and F-8, and the Nimbus Scanning Multichannel Microwave Radiometer (SMMR). The sea ice concentrations are an estimate of the fraction of ocean area covered by sea ice for both the north and south Polar Regions.\n\nThe data are provided at daily and monthly resolutions from late October 1978 through most recent processing in NetCDF-4 CF 1.10 format. The data cover the Arctic and Antarctic regions.\n\nThe related Near-real-time (NRT) NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration is not included in this data submission to NCEI. The daily NRT product is considered to be preliminary data and hosted at NSIDC. The quarterly data submissions to NCEI consist of Final data only.","distribution_titles":["NCEI Dataset Landing Page","AWS S3 Download (Daily)","AWS S3 Download (Monthly)","NSIDC Landing Page","Global Change Master Directory (GCMD) Keywords","GCOS Essential Climate Variables","NOAA National Centers for Environmental Information (NCEI)"],"harvest_record":"https://catalog.data.gov/harvest_record/3aa67236-000a-45f2-8a55-1c54a29701af","harvest_record_raw":"https://catalog.data.gov/harvest_record/3aa67236-000a-45f2-8a55-1c54a29701af/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/3aa67236-000a-45f2-8a55-1c54a29701af/transformed","has_download":false,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01747.xml","keyword":["Earth Science > Climate Indicators > Cryospheric Indicators > Sea Ice Concentration","Earth Science > Oceans > Sea Ice > Sea Ice Concentration","Oceanic - Surface - Sea Ice","Ocean > Arctic Ocean","Geographic Region > Polar","NOAA Climate Data Record (CDR) Program","SMMR > Scanning Multichannel Microwave Radiometer","SSM/I > Special Sensor Microwave/Imager","SSMIS > Special Sensor Microwave Imager/Sounder","AMSR-E > Advanced Microwave Scanning Radiometer-EOS","AMSR2 > Advanced Microwave Scanning Radiometer 2","NIMBUS > Nimbus-7","DMSP 5D-2/F8 > Defense Meteorological Satellite Program-F8","DMSP 5D-2/F11 > Defense Meteorological Satellite Program-F11","DMSP 5D-2/F13 > Defense Meteorological Satellite Program-F13","DMSP 5D-3/F17 > Defense Meteorological Satellite Program-F17","AQUA > Earth Observing System, AQUA","GCOM-W1 > Global Change Observation Mission 1st-Water","10 km - < 50 km or approximately .09 degree - < .5 degree","Daily - < Weekly","Weekly - < Monthly","National Centers for Environmental Information","National Oceanic and Atmospheric Administration at the National Snow and Ice Data Center"],"last_harvested_date":"2026-08-10T22:05:50.133244","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":0,"publisher":"NOAA National Centers for Environmental Information","slug":"noaa-nsidc-climate-data-record-of-passive-microwave-sea-ice-concentration-version-6-3b76a","spatial_centroid":{"lat":-66.34400000000001,"lon":36.0},"spatial_shape":{"coordinates":[[[180.0,-89.84],[180.0,-31.1],[-180.0,-31.1],[-180.0,-89.84],[180.0,-89.84]]],"type":"Polygon"},"theme":["geospatial"],"title":"NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 6"},{"_score":7.208175,"_sort":[1786399547253,7.208175,19,"805be18f-8c33-4d0c-bae6-deed900dc918"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","accrualPeriodicity":"R/P1D","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.ghcnh@noaa.gov"},"describedByType":"application/octet-steam","description":"Local Climatological Data (LCD) v2 are summaries of climatological conditions from airport and other prominent weather stations managed by NWS, FAA, and DOD. The LCD has been provided for approximately 1000 U.S. stations since 2005. The product includes hourly observations and associated remarks, and a record of hourly precipitation for the entire month. Also included are daily summaries summarizing temperature extremes, degree days, precipitation amounts and winds. The tabulated monthly summaries in the product include maximum, minimum, and average temperature, temperature departure from normal, dew point temperature, average station pressure, ceiling, visibility, weather type, wet bulb temperature, relative humidity, degree days (heating and cooling), daily precipitation, average wind speed, fastest wind speed/direction, sky cover, and occurrences of sunshine, snowfall and snow depth.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/96dw-mb77","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/products/land-based-station/local-climatological-data","describedByType":"application/octet-stream","description":"Description of the data and related resources.","mediaType":"text/html","title":"NCEI Product Information Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/access/search/data-search/local-climatological-data-v2","describedByType":"application/octet-stream","description":"File search and access.","mediaType":"text/html","title":"NCEI Dataset Search"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/oa/local-climatological-data/index.html#v2/access/","describedByType":"application/octet-stream","description":"Direct download for yearly station files.","mediaType":"text/html","title":"NCEI Direct Download (Dataset Files)"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/oa/local-climatological-data/index.html#v2/archive/","describedByType":"application/octet-stream","description":"Direct download for tar.gz files.","mediaType":"text/html","title":"NCEI Direct Download (Dataset Files)"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/oa/local-climatological-data/index.html#v2/doc/","describedByType":"application/octet-stream","description":"Direct download for the documentation.","mediaType":"text/html","title":"NCEI Direct Download (Documentation Files)"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/metadata/geoportal/rest/metadata/item/dcd6f3ff32d04199bad6bd29a607411f/html#","describedByType":"application/octet-stream","description":"Superseded dataset landing page. This version should not be used as the primary research dataset. It may be appropriate to use for reproducing studies that used this earlier version.","mediaType":"text/html","title":"NCEI landing page for the superseded Version 1"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01689.xml","issued":"2023-11-01T00:00:00.000+00:00","keyword":["Earth Science > Atmosphere > Atmospheric Temperature","Earth Science > Atmosphere > Precipitation","Earth Science > Atmosphere > Atmospheric Pressure","Earth Science > Climate Indicators > Atmospheric/Ocean Indicators > Humidity Indices","Earth Science > Atmosphere > Atmospheric Pressure > Sea Level Pressure","Earth Science > Atmosphere > Atmospheric Winds","Earth Science > Atmosphere > Atmospheric Winds > Surface Winds > Wind Speed/Wind Direction"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2023-11-01T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://www.ncei.noaa.gov/metadata/geoportal/rest/metadata/item/dcd6f3ff32d04199bad6bd29a607411f/html#"],"rights":"otherRestrictions","spatial":"180.0,-90.0,-180.0,90.0","temporal":"2005-01-01T00:00:00+00:00/2005-01-01T00:00:00+00:00","theme":["geospatial"],"title":"Local Climatological Data (LCD), Version 2 (LCDv2)"},"description":"Local Climatological Data (LCD) v2 are summaries of climatological conditions from airport and other prominent weather stations managed by NWS, FAA, and DOD. The LCD has been provided for approximately 1000 U.S. stations since 2005. The product includes hourly observations and associated remarks, and a record of hourly precipitation for the entire month. Also included are daily summaries summarizing temperature extremes, degree days, precipitation amounts and winds. The tabulated monthly summaries in the product include maximum, minimum, and average temperature, temperature departure from normal, dew point temperature, average station pressure, ceiling, visibility, weather type, wet bulb temperature, relative humidity, degree days (heating and cooling), daily precipitation, average wind speed, fastest wind speed/direction, sky cover, and occurrences of sunshine, snowfall and snow depth.","distribution_titles":["NCEI Dataset Landing Page","NCEI Product Information Page","NCEI Dataset Search","NCEI Direct Download (Dataset Files)","NCEI Direct Download (Dataset Files)","NCEI Direct Download (Documentation Files)","NCEI landing page for the superseded Version 1","Global Change Master Directory (GCMD) Keywords"],"harvest_record":"https://catalog.data.gov/harvest_record/bb08b1d0-991e-4a64-86aa-fb8ef1b7693c","harvest_record_raw":"https://catalog.data.gov/harvest_record/bb08b1d0-991e-4a64-86aa-fb8ef1b7693c/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/bb08b1d0-991e-4a64-86aa-fb8ef1b7693c/transformed","has_download":false,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01689.xml","keyword":["Earth Science > Atmosphere > Atmospheric Temperature","Earth Science > Atmosphere > Precipitation","Earth Science > Atmosphere > Atmospheric Pressure","Earth Science > Climate Indicators > Atmospheric/Ocean Indicators > Humidity Indices","Earth Science > Atmosphere > Atmospheric Pressure > Sea Level Pressure","Earth Science > Atmosphere > Atmospheric Winds","Earth Science > Atmosphere > Atmospheric Winds > Surface Winds > Wind Speed/Wind Direction"],"last_harvested_date":"2026-08-10T22:05:47.253581","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":19,"publisher":"NOAA National Centers for Environmental Information","slug":"local-climatological-data-lcd-version-2-lcdv2","spatial_centroid":{"lat":-18.0,"lon":36.0},"spatial_shape":{"coordinates":[[[180.0,-90.0],[180.0,90.0],[-180.0,90.0],[-180.0,-90.0],[180.0,-90.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"Local Climatological Data (LCD), Version 2 (LCDv2)"},{"_score":5.2082767,"_sort":[1786399546297,5.2082767,3,"fad429ac-239e-4220-b26d-14b31d590ad2"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","accrualPeriodicity":"R/P1D","contactPoint":{"@type":"vcard:Contact","fn":"DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","hasEmail":"mailto:nodc.services@noaa.gov"},"describedByType":"application/octet-steam","description":"The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is the world's most extensive surface marine meteorological data collection. Building on national and international partnerships, ICOADS provides a variety of user communities with easy access to many different data sources in a consistent format. Data sources range from early historical ship observations to more modern, automated measurement systems including moored buoys and surface drifters. Past versions of the ICOADS dataset have been published as monthly files while holding a daily version of the product for internal use only. NCEI has since developed a reformatted daily product of the dataset that now aligns with the monthly, ready for public use. The objective of this initiative is to sustain the quality and usability of this high-profile ICOADS product for stakeholders that have requested the need for an expanded product. ICOADS R3.0.2 Daily is now developed and released.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/metadata/geoportal/rest/metadata/item/gov.noaa.ncdc:C01687/html","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/data/international-comprehensive-ocean-atmosphere/v3/archive/nrt/daily/","describedByType":"application/octet-stream","description":"Direct download for the dataset.","mediaType":"text/html","title":"Direct Download (Dataset Files)"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/thredds/catalog/international-comprehensive-ocean-atmosphere-dataset-icoads/daily/catalog.html","describedByType":"application/octet-stream","description":"THREDDS Data Service for this dataset (NetCDF).","mediaType":"text/html","title":"NCEI THREDDS Catalog"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/data/international-comprehensive-ocean-atmosphere/v3/doc/","describedByType":"application/octet-stream","description":"Direct download for the documentation.","mediaType":"text/html","title":"NCEI Direct Download (Documentation Files)"},{"@type":"dcat:Distribution","accessURL":"https://icoads.noaa.gov","describedByType":"application/octet-stream","description":"International Comprehensive Ocean-Atmosphere Data Set Program home page.","mediaType":"text/html","title":"International Comprehensive Ocean-Atmosphere Data Set Program"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","downloadURL":"https://doi.org/10.1175/JTECH-D-21-0182.1","mediaType":"placeholder/value","title":"Blending TAC and BUFR Marine In Situ Data for ICOADS Near-Real-Time Release 3.0.2"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/metadata/geoportal/rest/metadata/item/gov.noaa.ncdc%3AC01607/html","describedByType":"application/octet-stream","description":"Related dataset landing page.","mediaType":"text/html","title":"NCEI landing page for ICOADS R3.0.2 - Monthly"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables","describedByType":"application/octet-stream","description":"Overview of the GCOS Essential Climate Variables.","mediaType":"text/html","title":"GCOS Essential Climate Variables"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01687.xml","isPartOf":"International Comprehensive Ocean-Atmosphere Data Set Program","issued":"2023-05-15T00:00:00.000+00:00","keyword":["Earth Science > Atmosphere > Atmospheric Temperature","Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature","Earth Science > Atmosphere > Atmospheric Pressure","Earth Science > Atmosphere > Atmospheric Winds","Earth Science > Oceans > Ocean Waves > Wind Waves","Earth Science > Oceans > Ocean Waves > Swells","Earth Science > Atmosphere > Air Quality > Visibility","Earth Science > Atmosphere > Atmospheric Water Vapor > Water Vapor Indicators > Humidity","Earth Science > Atmosphere > Clouds","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Dew Point Temperature","Earth Science > Cryosphere > Sea Ice","Earth Science > Oceans > Salinity/Density","Earth Science > Oceans > Ocean Chemistry > Dissolved Gases","Earth Science > Oceans > Ocean Chemistry > Phosphate","Earth Science > Oceans > Ocean Chemistry > Silicate","Earth Science > Oceans > Ocean Chemistry > Nitrate","Earth Science > Oceans > Ocean Chemistry > Alkalinity","Earth Science > Oceans > Ocean Chemistry > Chlorophyll","Earth Science > Oceans > Ocean Chemistry > Carbon Dioxide","Earth Science > Oceans > Ocean Chemistry > Carbon","Atmospheric - Surface - Air Pressure","Atmospheric - Surface - Air Temperature","Oceanic - Surface - Sea-surface Temperature","Oceanic - Surface - Sea-surface Salinity","Atmospheric - Surface - Wind Speed and Direction","Oceanic - Surface - Sea Ice","Oceanic - Surface - Sea State","Oceanic - Sub-surface - Sub-surface Nutrients (including phosphates, nitrates, silicates and silicic acids)","Oceanic - Surface - Carbon Dioxide Partial Pressure","Oceanic - Sub-surface - Sub-surface Oxygen","Geographic Region > Global Ocean","Vertical Location > Sea Surface","ICOADS > International Comprehensive Ocean Atmosphere Data Set","Thermometers","Thermometers","Anemometers","Wind Vanes","Barometers","CTD > Conductivity, Temperature, Depth","XBT > Expendable Bathythermographs","Visual Observations","Buoys","MOORINGS","FLOATS","Ships","OCEAN PLATFORM/OCEAN STATIONS","Point Resolution","Point Resolution","1 minute - < 1 hour","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2023-05-15T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://icoads.noaa.gov","https://doi.org/10.1175/JTECH-D-21-0182.1","https://www.ncei.noaa.gov/metadata/geoportal/rest/metadata/item/gov.noaa.ncdc%3AC01607/html"],"rights":"otherRestrictions","spatial":"180.0,-90.0,-180.0,90.0","temporal":"2023-03-24T00:00:00+00:00/2023-03-24T00:00:00+00:00","theme":["geospatial"],"title":"International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Near-Real-Time (NRT) Release 3.0.2, 2015 to 2025 and Release 3.0.3, 2026 to present"},"description":"The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is the world's most extensive surface marine meteorological data collection. Building on national and international partnerships, ICOADS provides a variety of user communities with easy access to many different data sources in a consistent format. Data sources range from early historical ship observations to more modern, automated measurement systems including moored buoys and surface drifters. Past versions of the ICOADS dataset have been published as monthly files while holding a daily version of the product for internal use only. NCEI has since developed a reformatted daily product of the dataset that now aligns with the monthly, ready for public use. The objective of this initiative is to sustain the quality and usability of this high-profile ICOADS product for stakeholders that have requested the need for an expanded product. ICOADS R3.0.2 Daily is now developed and released.","distribution_titles":["NCEI Dataset Landing Page","Direct Download (Dataset Files)","NCEI THREDDS Catalog","NCEI Direct Download (Documentation Files)","International Comprehensive Ocean-Atmosphere Data Set Program","Blending TAC and BUFR Marine In Situ Data for ICOADS Near-Real-Time Release 3.0.2","NCEI landing page for ICOADS R3.0.2 - Monthly","Global Change Master Directory (GCMD) Keywords","GCOS Essential Climate Variables"],"harvest_record":"https://catalog.data.gov/harvest_record/976e0f45-e413-4e0b-8e80-44f29e113d72","harvest_record_raw":"https://catalog.data.gov/harvest_record/976e0f45-e413-4e0b-8e80-44f29e113d72/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/976e0f45-e413-4e0b-8e80-44f29e113d72/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01687.xml","keyword":["Earth Science > Atmosphere > Atmospheric Temperature","Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature","Earth Science > Atmosphere > Atmospheric Pressure","Earth Science > Atmosphere > Atmospheric Winds","Earth Science > Oceans > Ocean Waves > Wind Waves","Earth Science > Oceans > Ocean Waves > Swells","Earth Science > Atmosphere > Air Quality > Visibility","Earth Science > Atmosphere > Atmospheric Water Vapor > Water Vapor Indicators > Humidity","Earth Science > Atmosphere > Clouds","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Dew Point Temperature","Earth Science > Cryosphere > Sea Ice","Earth Science > Oceans > Salinity/Density","Earth Science > Oceans > Ocean Chemistry > Dissolved Gases","Earth Science > Oceans > Ocean Chemistry > Phosphate","Earth Science > Oceans > Ocean Chemistry > Silicate","Earth Science > Oceans > Ocean Chemistry > Nitrate","Earth Science > Oceans > Ocean Chemistry > Alkalinity","Earth Science > Oceans > Ocean Chemistry > Chlorophyll","Earth Science > Oceans > Ocean Chemistry > Carbon Dioxide","Earth Science > Oceans > Ocean Chemistry > Carbon","Atmospheric - Surface - Air Pressure","Atmospheric - Surface - Air Temperature","Oceanic - Surface - Sea-surface Temperature","Oceanic - Surface - Sea-surface Salinity","Atmospheric - Surface - Wind Speed and Direction","Oceanic - Surface - Sea Ice","Oceanic - Surface - Sea State","Oceanic - Sub-surface - Sub-surface Nutrients (including phosphates, nitrates, silicates and silicic acids)","Oceanic - Surface - Carbon Dioxide Partial Pressure","Oceanic - Sub-surface - Sub-surface Oxygen","Geographic Region > Global Ocean","Vertical Location > Sea Surface","ICOADS > International Comprehensive Ocean Atmosphere Data Set","Thermometers","Thermometers","Anemometers","Wind Vanes","Barometers","CTD > Conductivity, Temperature, Depth","XBT > Expendable Bathythermographs","Visual Observations","Buoys","MOORINGS","FLOATS","Ships","OCEAN PLATFORM/OCEAN STATIONS","Point Resolution","Point Resolution","1 minute - < 1 hour","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce"],"last_harvested_date":"2026-08-10T22:05:46.297215","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":3,"publisher":"NOAA National Centers for Environmental Information","slug":"international-comprehensive-ocean-atmosphere-data-set-icoads-near-real-time-nrt-daily-rele","spatial_centroid":{"lat":-18.0,"lon":36.0},"spatial_shape":{"coordinates":[[[180.0,-90.0],[180.0,90.0],[-180.0,90.0],[-180.0,-90.0],[180.0,-90.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Near-Real-Time (NRT) Release 3.0.2, 2015 to 2025 and Release 3.0.3, 2026 to present"},{"_score":68.63428,"_sort":[1786399545278,68.63428,2,"b8a8dc65-3ec5-45ee-b0a2-03a52b18e3b9"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-steam","description":"The U.S. Hourly Climate Normals for 2006 to 2020 provide users supplemental hourly normals for specialized applications for hundreds of U.S. stations located across the 50 states, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. These stations are now largely automated, and are usually part of the Automated Surface Observing System (ASOS) or Automated Weather Observing System (AWOS). The hourly normals include temperature, dew point, heat index, wind chill, wind, cloudiness, heating and cooling degree hours, pressure normals, and other statistics of these variables. Users can access the data either by product or by station. All data utilized in the computation of the 2006-2020 Climate Normals were taken from the Integrated Surface Dataset (ISD) Lite (a subset of NCEI's Integrated Surface Dataset). These source datasets (including intermediate datasets used in the computation of products) are also archived at the NOAA NCEI.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/vy7r-v505","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/products/land-based-station/us-climate-normals","describedByType":"application/octet-stream","description":"Product page with documentation and data access links.","mediaType":"text/html","title":"U.S. Climate Normals Product Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/data/normals-hourly/2006-2020","describedByType":"application/octet-stream","description":"Navigate directly to the URL for data access and direct download.","mediaType":"text/html","title":"Data Download"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/access/search/data-search/normals-hourly-2006-2020","describedByType":"application/octet-stream","description":"Search for data by geographic location, station, and data type.","mediaType":"text/html","title":"Data Search"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Normals User Guide that provides product descriptions and formats for all data and products produced and made available to users.","downloadURL":"https://www.ncei.noaa.gov/data/normals-hourly/2006-2020/doc/Normals_HLY_Documentation_2006-2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Hourly Documentation 2006-2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"The science and methodologies used to generate official climate normals for the United States.","downloadURL":"https://www.ncei.noaa.gov/data/normals-hourly/2006-2020/doc/Normals_Calculation_Methodology_2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Calculation Methodology 2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This document describes the technical layout of the CSV normals files in boththe individual, by-station, format and the grouped by-variable format.  It alsoprovides a guide to the location of the variables within the larger by-variabletar files.","downloadURL":"https://www.ncei.noaa.gov/data/normals-hourly/2006-2020/doc/Readme_By-Variable_By-Station_Normals_Files.txt","format":"TEXT","mediaType":"text/plain","title":"Readme By-Variable By-Station Normals Files"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in CSV and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-hourly/2006-2020/doc/Normals_HLY_2006-2020_sample.csv","format":"CSV","mediaType":"text/csv","title":"Normals Hourly CSV Sample 2006-2020"},{"@type":"dcat:Distribution","accessURL":"https://registry.opendata.aws/noaa-climate-normals/","describedByType":"application/octet-stream","description":"Information on AWS data access.","mediaType":"text/html","title":"Registry of Open Data on AWS"},{"@type":"dcat:Distribution","accessURL":"https://noaa-normals-pds.s3.amazonaws.com/index.html#normals-hourly/2006-2020/","describedByType":"application/octet-stream","description":"Browse view to explore the S3 bucket.","mediaType":"text/html","title":"AWS S3 Explorer (Region: us-east-1)"},{"@type":"dcat:Distribution","accessURL":"https://microsoft.github.io/AIforEarthDataSets/data/noaa-climatenormals.html","describedByType":"application/octet-stream","description":"Information on Microsoft Azure data access.","mediaType":"text/html","title":"Azure Landing Page (Region: us-east)"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/BAMS-D-11-00173.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/BAMS-D-11-00173.1"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.7289/V5PN93JP","describedByType":"application/octet-stream","description":"Older version.","mediaType":"text/html","title":"https://doi.org/10.7289/V5PN93JP"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables","describedByType":"application/octet-stream","description":"Overview of the GCOS Essential Climate Variables.","mediaType":"text/html","title":"GCOS Essential Climate Variables"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01626.xml","issued":"2021-05-04T00:00:00.000+00:00","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Earth Science > Atmosphere > Atmospheric Winds > Surface Winds > Wind Direction","Earth Science > Atmosphere > Atmospheric Winds > Surface Winds > Wind Speed","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Dew Point Temperature","Earth Science > Atmosphere > Clouds > Cloud Properties > Cloud Amount","Earth Science > Atmosphere > Atmospheric Pressure > Sea Level Pressure","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Wind Speed and Direction","Atmospheric - Surface - Water Vapour - Dew Point","Atmospheric - Upper-air - Cloud Properties","Atmospheric - Surface - Air Pressure","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2021-05-04T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://doi.org/10.1175/BAMS-D-11-00173.1","https://doi.org/10.7289/V5PN93JP"],"rights":"otherRestrictions","spatial":"-64.0,-15.0,134.0,72.0","temporal":"2006-01-01T00:00:00+00:00/2020-12-01T00:00:00+00:00","theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Hourly Climate Normals (2006-2020)"},"description":"The U.S. Hourly Climate Normals for 2006 to 2020 provide users supplemental hourly normals for specialized applications for hundreds of U.S. stations located across the 50 states, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. These stations are now largely automated, and are usually part of the Automated Surface Observing System (ASOS) or Automated Weather Observing System (AWOS). The hourly normals include temperature, dew point, heat index, wind chill, wind, cloudiness, heating and cooling degree hours, pressure normals, and other statistics of these variables. Users can access the data either by product or by station. All data utilized in the computation of the 2006-2020 Climate Normals were taken from the Integrated Surface Dataset (ISD) Lite (a subset of NCEI's Integrated Surface Dataset). These source datasets (including intermediate datasets used in the computation of products) are also archived at the NOAA NCEI.","distribution_titles":["NCEI Dataset Landing Page","U.S. Climate Normals Product Page","Data Download","Data Search","Normals Hourly Documentation 2006-2020","Normals Calculation Methodology 2020","Readme By-Variable By-Station Normals Files","Normals Hourly CSV Sample 2006-2020","Registry of Open Data on AWS","AWS S3 Explorer (Region: us-east-1)","Azure Landing Page (Region: us-east)","https://doi.org/10.1175/BAMS-D-11-00173.1","https://doi.org/10.7289/V5PN93JP","Global Change Master Directory (GCMD) Keywords","GCOS Essential Climate Variables"],"harvest_record":"https://catalog.data.gov/harvest_record/f1de1310-e89b-4e4c-a887-e11a3e78b51b","harvest_record_raw":"https://catalog.data.gov/harvest_record/f1de1310-e89b-4e4c-a887-e11a3e78b51b/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/f1de1310-e89b-4e4c-a887-e11a3e78b51b/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01626.xml","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Earth Science > Atmosphere > Atmospheric Winds > Surface Winds > Wind Direction","Earth Science > Atmosphere > Atmospheric Winds > Surface Winds > Wind Speed","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Dew Point Temperature","Earth Science > Atmosphere > Clouds > Cloud Properties > Cloud Amount","Earth Science > Atmosphere > Atmospheric Pressure > Sea Level Pressure","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Wind Speed and Direction","Atmospheric - Surface - Water Vapour - Dew Point","Atmospheric - Upper-air - Cloud Properties","Atmospheric - Surface - Air Pressure","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"last_harvested_date":"2026-08-10T22:05:45.278269","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":2,"publisher":"NOAA National Centers for Environmental Information","slug":"u-s-climate-normals-2020-u-s-hourly-climate-normals-2006-2020","spatial_centroid":{"lat":19.8,"lon":15.2},"spatial_shape":{"coordinates":[[[-64.0,-15.0],[-64.0,72.0],[134.0,72.0],[134.0,-15.0],[-64.0,-15.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Hourly Climate Normals (2006-2020)"},{"_score":70.531334,"_sort":[1786399544207,70.531334,1,"e4f7cf96-6021-44c5-bce7-a8a20f15d576"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-steam","description":"The U.S. Daily Climate Normals for 2006 to 2020 are 15-year averages of meteorological parameters that provide users supplemental normals for specialized applications for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Daily Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs)). All data utilized in the computation of the 2006-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily, but the Daily Normals are adjusted so that they are consistent with the Monthly Normals. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/zk2y-mf15","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/products/land-based-station/us-climate-normals","describedByType":"application/octet-stream","description":"Product page with documentation and data access links.","mediaType":"text/html","title":"U.S. Climate Normals Product Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/data/normals-daily/2006-2020","describedByType":"application/octet-stream","description":"Navigate directly to the URL for data access and direct download.","mediaType":"text/html","title":"Data Download"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/access/search/data-search/normals-daily-2006-2020","describedByType":"application/octet-stream","description":"Search for data by geographic location, station, and data type.","mediaType":"text/html","title":"Data Search"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Normals User Guide that provides product descriptions and formats for all data and products produced and made available to users.","downloadURL":"https://www.ncei.noaa.gov/data/normals-daily/2006-2020/doc/Normals_DLY_Documentation_2006-2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Daily Documentation 2006-2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"The science and methodologies used to generate official climate normals for the United States.","downloadURL":"https://www.ncei.noaa.gov/data/normals-daily/2006-2020/doc/Normals_Calculation_Methodology_2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Calculation Methodology 2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This document describes the technical layout of the CSV normals files in boththe individual, by-station, format and the grouped by-variable format.  It alsoprovides a guide to the location of the variables within the larger by-variabletar files.","downloadURL":"https://www.ncei.noaa.gov/data/normals-daily/2006-2020/doc/Readme_By-Variable_By-Station_Normals_Files.txt","format":"TEXT","mediaType":"text/plain","title":"Readme By-Variable By-Station Normals Files"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in PDF and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-daily/2006-2020/doc/Normals_DLY_2006-2020_sample.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Daily 2006-2020 PDF Sample"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in CSV and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-daily/2006-2020/doc/Normals_DLY_2006-2020_sample.csv","format":"CSV","mediaType":"text/csv","title":"Normals Daily 2006-2020 CSV Sample"},{"@type":"dcat:Distribution","accessURL":"https://registry.opendata.aws/noaa-climate-normals/","describedByType":"application/octet-stream","description":"Information on AWS data access.","mediaType":"text/html","title":"Registry of Open Data on AWS"},{"@type":"dcat:Distribution","accessURL":"https://noaa-normals-pds.s3.amazonaws.com/index.html#normals-daily/2006-2020/","describedByType":"application/octet-stream","description":"Browse view to explore the S3 bucket.","mediaType":"text/html","title":"AWS S3 Explorer (Region: us-east-1)"},{"@type":"dcat:Distribution","accessURL":"https://microsoft.github.io/AIforEarthDataSets/data/noaa-climatenormals.html","describedByType":"application/octet-stream","description":"Information on Microsoft Azure data access.","mediaType":"text/html","title":"Azure Landing Page (Region: us-east)"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/BAMS-D-11-00197.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/BAMS-D-11-00197.1"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/JTECH-D-12-00195.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/JTECH-D-12-00195.1"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/archive/accession/0259964","describedByType":"application/octet-stream","description":"Related dataset.","mediaType":"text/html","title":"https://www.ncei.noaa.gov/archive/accession/0259964"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.7289/V5PN93JP","describedByType":"application/octet-stream","description":"Older version.","mediaType":"text/html","title":"https://doi.org/10.7289/V5PN93JP"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables","describedByType":"application/octet-stream","description":"Overview of the GCOS Essential Climate Variables.","mediaType":"text/html","title":"GCOS Essential Climate Variables"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01625.xml","issued":"2021-05-04T00:00:00.000+00:00","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2023-05-15T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JTECH-D-12-00195.1","https://www.ncei.noaa.gov/archive/accession/0259964","https://doi.org/10.7289/V5PN93JP"],"rights":"otherRestrictions","spatial":"-64.0,-15.0,134.0,72.0","temporal":"2006-01-01T00:00:00+00:00/2020-12-01T00:00:00+00:00","theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Daily Climate Normals (2006-2020)"},"description":"The U.S. Daily Climate Normals for 2006 to 2020 are 15-year averages of meteorological parameters that provide users supplemental normals for specialized applications for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Daily Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs)). All data utilized in the computation of the 2006-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily, but the Daily Normals are adjusted so that they are consistent with the Monthly Normals. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution_titles":["NCEI Dataset Landing Page","U.S. Climate Normals Product Page","Data Download","Data Search","Normals Daily Documentation 2006-2020","Normals Calculation Methodology 2020","Readme By-Variable By-Station Normals Files","Normals Daily 2006-2020 PDF Sample","Normals Daily 2006-2020 CSV Sample","Registry of Open Data on AWS","AWS S3 Explorer (Region: us-east-1)","Azure Landing Page (Region: us-east)","https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JTECH-D-12-00195.1","https://www.ncei.noaa.gov/archive/accession/0259964","https://doi.org/10.7289/V5PN93JP","Global Change Master Directory (GCMD) Keywords","GCOS Essential Climate Variables"],"harvest_record":"https://catalog.data.gov/harvest_record/56738f62-7806-4367-83fe-92c57072b382","harvest_record_raw":"https://catalog.data.gov/harvest_record/56738f62-7806-4367-83fe-92c57072b382/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/56738f62-7806-4367-83fe-92c57072b382/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01625.xml","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"last_harvested_date":"2026-08-10T22:05:44.207472","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":1,"publisher":"NOAA National Centers for Environmental Information","slug":"u-s-climate-normals-2020-u-s-daily-climate-normals-2006-2020","spatial_centroid":{"lat":19.8,"lon":15.2},"spatial_shape":{"coordinates":[[[-64.0,-15.0],[-64.0,72.0],[134.0,72.0],[134.0,-15.0],[-64.0,-15.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Daily Climate Normals (2006-2020)"},{"_score":70.13121,"_sort":[1786399543107,70.13121,4,"b2fdfffc-3311-456f-a382-b5454c30aff6"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-steam","description":"The U.S. Monthly Climate Normals for 2006 to 2020 are 15-year averages of meteorological parameters that provide users supplemental normals for specialized applications for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Monthly Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs)). All data utilized in the computation of the 2006-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily and -Monthly datasets. Temperatures were homogenized, adjusted for time-of-observation, and made serially complete where possible based on information from nearby stations. Precipitation totals were also made serially complete where possible based using nearby stations. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/8v8d-np75","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/products/land-based-station/us-climate-normals","describedByType":"application/octet-stream","description":"Product page with documentation and data access links.","mediaType":"text/html","title":"U.S. Climate Normals Product Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/data/normals-monthly/2006-2020","describedByType":"application/octet-stream","description":"Navigate directly to the URL for data access and direct download.","mediaType":"text/html","title":"Data Download"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/access/search/data-search/normals-monthly-2006-2020","describedByType":"application/octet-stream","description":"Search for data by geographic location, station, and data type.","mediaType":"text/html","title":"Data Search"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Normals User Guide that provides product descriptions and formats for all data and products produced and made available to users.","downloadURL":"https://www.ncei.noaa.gov/data/normals-monthly/2006-2020/doc/Normals_MLY_Documentation_2006-2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Monthly Documentation 2006-2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"The science and methodologies used to generate official climate normals for the United States.","downloadURL":"https://www.ncei.noaa.gov/data/normals-monthly/2006-2020/doc/Normals_Calculation_Methodology_2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Calculation Methodology 2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This document describes the technical layout of the CSV normals files in boththe individual, by-station, format and the grouped by-variable format.  It alsoprovides a guide to the location of the variables within the larger by-variabletar files.","downloadURL":"https://www.ncei.noaa.gov/data/normals-monthly/2006-2020/doc/Readme_By-Variable_By-Station_Normals_Files.txt","format":"TEXT","mediaType":"text/plain","title":"Readme By-Variable By-Station Normals Files"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in PDF and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-monthly/2006-2020/doc/Normals_MLY_2006-2020_sample.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Monthly 2006-2020 PDF Sample"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in CSV and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-monthly/2006-2020/doc/Normals_MLY_2006-2020_sample.csv","format":"CSV","mediaType":"text/csv","title":"Normals Monthly 2006-2020 CSV Sample"},{"@type":"dcat:Distribution","accessURL":"https://registry.opendata.aws/noaa-climate-normals/","describedByType":"application/octet-stream","description":"Information on AWS data access.","mediaType":"text/html","title":"Registry of Open Data on AWS"},{"@type":"dcat:Distribution","accessURL":"https://noaa-normals-pds.s3.amazonaws.com/index.html#normals-monthly/2006-2020/","describedByType":"application/octet-stream","description":"Browse view to explore the S3 bucket.","mediaType":"text/html","title":"AWS S3 Explorer (Region: us-east-1)"},{"@type":"dcat:Distribution","accessURL":"https://microsoft.github.io/AIforEarthDataSets/data/noaa-climatenormals.html","describedByType":"application/octet-stream","description":"Information on Microsoft Azure data access.","mediaType":"text/html","title":"Azure Landing Page (Region: us-east)"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/BAMS-D-11-00197.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/BAMS-D-11-00197.1"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/JAMC-D-13-051.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/JAMC-D-13-051.1"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/n5tw-jb91","describedByType":"application/octet-stream","description":"Related dataset.","mediaType":"text/html","title":"https://doi.org/10.25921/n5tw-jb91"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.7289/V5PN93JP","describedByType":"application/octet-stream","description":"Older version.","mediaType":"text/html","title":"https://doi.org/10.7289/V5PN93JP"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables","describedByType":"application/octet-stream","description":"Overview of the GCOS Essential Climate Variables.","mediaType":"text/html","title":"GCOS Essential Climate Variables"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01624.xml","issued":"2021-05-04T00:00:00.000+00:00","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2023-05-15T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JAMC-D-13-051.1","https://doi.org/10.25921/n5tw-jb91","https://doi.org/10.7289/V5PN93JP"],"rights":"otherRestrictions","spatial":"-64.0,-15.0,134.0,72.0","temporal":"2006-01-01T00:00:00+00:00/2020-12-01T00:00:00+00:00","theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Monthly Climate Normals (2006-2020)"},"description":"The U.S. Monthly Climate Normals for 2006 to 2020 are 15-year averages of meteorological parameters that provide users supplemental normals for specialized applications for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Monthly Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs)). All data utilized in the computation of the 2006-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily and -Monthly datasets. Temperatures were homogenized, adjusted for time-of-observation, and made serially complete where possible based on information from nearby stations. Precipitation totals were also made serially complete where possible based using nearby stations. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution_titles":["NCEI Dataset Landing Page","U.S. Climate Normals Product Page","Data Download","Data Search","Normals Monthly Documentation 2006-2020","Normals Calculation Methodology 2020","Readme By-Variable By-Station Normals Files","Normals Monthly 2006-2020 PDF Sample","Normals Monthly 2006-2020 CSV Sample","Registry of Open Data on AWS","AWS S3 Explorer (Region: us-east-1)","Azure Landing Page (Region: us-east)","https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JAMC-D-13-051.1","https://doi.org/10.25921/n5tw-jb91","https://doi.org/10.7289/V5PN93JP","Global Change Master Directory (GCMD) Keywords","GCOS Essential Climate Variables"],"harvest_record":"https://catalog.data.gov/harvest_record/488dff13-13b4-4ae1-a168-7789a6540871","harvest_record_raw":"https://catalog.data.gov/harvest_record/488dff13-13b4-4ae1-a168-7789a6540871/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/488dff13-13b4-4ae1-a168-7789a6540871/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01624.xml","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"last_harvested_date":"2026-08-10T22:05:43.107377","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":4,"publisher":"NOAA National Centers for Environmental Information","slug":"u-s-climate-normals-2020-u-s-monthly-climate-normals-2006-2020","spatial_centroid":{"lat":19.8,"lon":15.2},"spatial_shape":{"coordinates":[[[-64.0,-15.0],[-64.0,72.0],[134.0,72.0],[134.0,-15.0],[-64.0,-15.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Monthly Climate Normals (2006-2020)"},{"_score":68.47645,"_sort":[1786399541993,68.47645,4,"6586ea52-e0cd-40ce-8e2d-5fced5c069d6"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-steam","description":"The U.S. Annual/Seasonal Climate Normals for 2006 to 2020 are 15-year averages of meteorological parameters that provide users supplemental normals for specialized applications for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Annual/Seasonal Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs), lengths of growing seasons, probabilities of first or last temperature threshold exceedances. All data utilized in the computation of the 2006-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily and -Monthly datasets. Temperatures were homogenized, adjusted for time-of-observation, and made serially complete where possible based on information from nearby stations. Precipitation totals were also made serially complete where possible based using nearby stations. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/ef12-ny58","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/products/land-based-station/us-climate-normals","describedByType":"application/octet-stream","description":"Product page with documentation and data access links.","mediaType":"text/html","title":"U.S. Climate Normals Product Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/2006-2020","describedByType":"application/octet-stream","description":"Navigate directly to the URL for data access and direct download.","mediaType":"text/html","title":"Data Download"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/access/search/data-search/normals-annualseasonal-2006-2020","describedByType":"application/octet-stream","description":"Search for data by geographic location, station, and data type.","mediaType":"text/html","title":"Data Search"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Normals User Guide that provides product descriptions and formats for all data and products produced and made available to users.","downloadURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/2006-2020/doc/Normals_ANN_Documentation_2006-2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Annual Documentation 2006-2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"The science and methodologies used to generate official climate normals for the United States.","downloadURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/2006-2020/doc/Normals_Calculation_Methodology_2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Calculation Methodology 2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This document describes the technical layout of the CSV normals files in boththe individual, by-station, format and the grouped by-variable format.  It alsoprovides a guide to the location of the variables within the larger by-variabletar files.","downloadURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/2006-2020/doc/Readme_By-Variable_By-Station_Normals_Files.txt","format":"TEXT","mediaType":"text/plain","title":"Readme By-Variable By-Station Normals Files"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in PDF and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/2006-2020/doc/Normals_ANN_2006-2020_sample.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Annual 2006-2020 PDF Sample"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in CSV and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/2006-2020/doc/Normals_ANN_2006-2020_sample.csv","format":"CSV","mediaType":"text/csv","title":"Normals Annual 2006-2020 CSV Sample"},{"@type":"dcat:Distribution","accessURL":"https://registry.opendata.aws/noaa-climate-normals/","describedByType":"application/octet-stream","description":"Information on AWS data access.","mediaType":"text/html","title":"Registry of Open Data on AWS"},{"@type":"dcat:Distribution","accessURL":"https://noaa-normals-pds.s3.amazonaws.com/index.html#normals-annualseasonal/2006-2020/","describedByType":"application/octet-stream","description":"Browse view to explore the S3 bucket.","mediaType":"text/html","title":"AWS S3 Explorer (Region: us-east-1)"},{"@type":"dcat:Distribution","accessURL":"https://microsoft.github.io/AIforEarthDataSets/data/noaa-climatenormals.html","describedByType":"application/octet-stream","description":"Information on Microsoft Azure data access.","mediaType":"text/html","title":"Azure Landing Page (Region: us-east)"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/BAMS-D-11-00197.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/BAMS-D-11-00197.1"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/JAMC-D-13-051.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/JAMC-D-13-051.1"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.7289/V5PN93JP","describedByType":"application/octet-stream","description":"Older version.","mediaType":"text/html","title":"https://doi.org/10.7289/V5PN93JP"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables","describedByType":"application/octet-stream","description":"Overview of the GCOS Essential Climate Variables.","mediaType":"text/html","title":"GCOS Essential Climate Variables"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01623.xml","issued":"2021-05-04T00:00:00.000+00:00","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2023-05-15T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JAMC-D-13-051.1","https://doi.org/10.7289/V5PN93JP"],"rights":"otherRestrictions","spatial":"-64.0,-15.0,134.0,72.0","temporal":"2006-01-01T00:00:00+00:00/2020-12-01T00:00:00+00:00","theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Annual/Seasonal Climate Normals (2006-2020)"},"description":"The U.S. Annual/Seasonal Climate Normals for 2006 to 2020 are 15-year averages of meteorological parameters that provide users supplemental normals for specialized applications for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Annual/Seasonal Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs), lengths of growing seasons, probabilities of first or last temperature threshold exceedances. All data utilized in the computation of the 2006-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily and -Monthly datasets. Temperatures were homogenized, adjusted for time-of-observation, and made serially complete where possible based on information from nearby stations. Precipitation totals were also made serially complete where possible based using nearby stations. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution_titles":["NCEI Dataset Landing Page","U.S. Climate Normals Product Page","Data Download","Data Search","Normals Annual Documentation 2006-2020","Normals Calculation Methodology 2020","Readme By-Variable By-Station Normals Files","Normals Annual 2006-2020 PDF Sample","Normals Annual 2006-2020 CSV Sample","Registry of Open Data on AWS","AWS S3 Explorer (Region: us-east-1)","Azure Landing Page (Region: us-east)","https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JAMC-D-13-051.1","https://doi.org/10.7289/V5PN93JP","Global Change Master Directory (GCMD) Keywords","GCOS Essential Climate Variables"],"harvest_record":"https://catalog.data.gov/harvest_record/babfafc0-7cce-46c9-8ba5-6e7968fe6ea7","harvest_record_raw":"https://catalog.data.gov/harvest_record/babfafc0-7cce-46c9-8ba5-6e7968fe6ea7/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/babfafc0-7cce-46c9-8ba5-6e7968fe6ea7/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01623.xml","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"last_harvested_date":"2026-08-10T22:05:41.993987","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":4,"publisher":"NOAA National Centers for Environmental Information","slug":"u-s-climate-normals-2020-u-s-annual-seasonal-climate-normals-2006-2020","spatial_centroid":{"lat":19.8,"lon":15.2},"spatial_shape":{"coordinates":[[[-64.0,-15.0],[-64.0,72.0],[134.0,72.0],[134.0,-15.0],[-64.0,-15.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Annual/Seasonal Climate Normals (2006-2020)"},{"_score":69.43989,"_sort":[1786399540907,69.43989,6,"db3acdc9-f077-41ff-8389-d0047f2a5fd5"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-steam","description":"The U.S. Hourly Climate Normals for 1991 to 2020 provides hourly meteorological parameters for hundreds of U.S. stations located across the 50 states, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. These stations are now largely automated, and are usually part of the Automated Surface Observing System (ASOS) or Automated Weather Observing System (AWOS). The hourly normals include temperature, dew point, heat index, wind chill, wind, cloudiness, heating and cooling degree hours, pressure normals, and other statistics of these variables. Users can access the data either by product or by station. All data utilized in the computation of the 1991-2020 Climate Normals were taken from the Integrated Surface Dataset (ISD) Lite (a subset of NCEI's Integrated Surface Dataset). These source datasets (including intermediate datasets used in the computation of products) are also archived at the NOAA NCEI.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/e3zh-ag77","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/products/land-based-station/us-climate-normals","describedByType":"application/octet-stream","description":"Product page with documentation and data access links.","mediaType":"text/html","title":"U.S. Climate Normals Product Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/data/normals-hourly/1991-2020","describedByType":"application/octet-stream","description":"Navigate directly to the URL for data access and direct download.","mediaType":"text/html","title":"Data Download"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/access/search/data-search/normals-hourly-1991-2020","describedByType":"application/octet-stream","description":"Search for data by geographic location, station, and data type.","mediaType":"text/html","title":"Data Search"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Normals User Guide that provides product descriptions and formats for all data and products produced and made available to users.","downloadURL":"https://www.ncei.noaa.gov/data/normals-hourly/1991-2020/doc/Normals_HLY_Documentation_1991-2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Hourly Documentation 1991-2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"The science and methodologies used to generate official climate normals for the United States.","downloadURL":"https://www.ncei.noaa.gov/data/normals-hourly/1991-2020/doc/Normals_Calculation_Methodology_2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Calculation Methodology 2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This document describes the technical layout of the CSV normals files in boththe individual, by-station, format and the grouped by-variable format.  It alsoprovides a guide to the location of the variables within the larger by-variabletar files.","downloadURL":"https://www.ncei.noaa.gov/data/normals-hourly/1991-2020/doc/Readme_By-Variable_By-Station_Normals_Files.txt","format":"TEXT","mediaType":"text/plain","title":"Readme By-Variable By-Station Normals Files"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in CSV and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-hourly/1991-2020/doc/Normals_HLY_1991-2020_sample.csv","format":"CSV","mediaType":"text/csv","title":"Normals Hourly 1991-2020 CSV Sample"},{"@type":"dcat:Distribution","accessURL":"https://registry.opendata.aws/noaa-climate-normals/","describedByType":"application/octet-stream","description":"Information on AWS data access.","mediaType":"text/html","title":"Registry of Open Data on AWS"},{"@type":"dcat:Distribution","accessURL":"https://noaa-normals-pds.s3.amazonaws.com/index.html#normals-hourly/1991-2020/","describedByType":"application/octet-stream","description":"Browse view to explore the S3 bucket.","mediaType":"text/html","title":"AWS S3 Explorer (Region: us-east-1)"},{"@type":"dcat:Distribution","accessURL":"https://microsoft.github.io/AIforEarthDataSets/data/noaa-climatenormals.html","describedByType":"application/octet-stream","description":"Information on Microsoft Azure data access.","mediaType":"text/html","title":"Azure Landing Page (Region: us-east)"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/BAMS-D-11-00173.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/BAMS-D-11-00173.1"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.7289/V5PN93JP","describedByType":"application/octet-stream","description":"Older version.","mediaType":"text/html","title":"https://doi.org/10.7289/V5PN93JP"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables","describedByType":"application/octet-stream","description":"Overview of the GCOS Essential Climate Variables.","mediaType":"text/html","title":"GCOS Essential Climate Variables"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01622.xml","issued":"2021-05-04T00:00:00.000+00:00","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Earth Science > Atmosphere > Atmospheric Winds > Surface Winds > Wind Direction","Earth Science > Atmosphere > Atmospheric Winds > Surface Winds > Wind Speed","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Dew Point Temperature","Earth Science > Atmosphere > Clouds > Cloud Properties > Cloud Amount","Earth Science > Atmosphere > Atmospheric Pressure > Sea Level Pressure","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Wind Speed and Direction","Atmospheric - Surface - Water Vapour - Dew Point","Atmospheric - Upper-air - Cloud Properties","Atmospheric - Surface - Air Pressure","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2021-05-04T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://doi.org/10.1175/BAMS-D-11-00173.1","https://doi.org/10.7289/V5PN93JP"],"rights":"otherRestrictions","spatial":"-64.0,-15.0,134.0,72.0","temporal":"1991-01-01T00:00:00+00:00/2020-12-01T00:00:00+00:00","theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Hourly Climate Normals (1991-2020)"},"description":"The U.S. Hourly Climate Normals for 1991 to 2020 provides hourly meteorological parameters for hundreds of U.S. stations located across the 50 states, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. These stations are now largely automated, and are usually part of the Automated Surface Observing System (ASOS) or Automated Weather Observing System (AWOS). The hourly normals include temperature, dew point, heat index, wind chill, wind, cloudiness, heating and cooling degree hours, pressure normals, and other statistics of these variables. Users can access the data either by product or by station. All data utilized in the computation of the 1991-2020 Climate Normals were taken from the Integrated Surface Dataset (ISD) Lite (a subset of NCEI's Integrated Surface Dataset). These source datasets (including intermediate datasets used in the computation of products) are also archived at the NOAA NCEI.","distribution_titles":["NCEI Dataset Landing Page","U.S. Climate Normals Product Page","Data Download","Data Search","Normals Hourly Documentation 1991-2020","Normals Calculation Methodology 2020","Readme By-Variable By-Station Normals Files","Normals Hourly 1991-2020 CSV Sample","Registry of Open Data on AWS","AWS S3 Explorer (Region: us-east-1)","Azure Landing Page (Region: us-east)","https://doi.org/10.1175/BAMS-D-11-00173.1","https://doi.org/10.7289/V5PN93JP","Global Change Master Directory (GCMD) Keywords","GCOS Essential Climate Variables"],"harvest_record":"https://catalog.data.gov/harvest_record/b20ac765-98aa-4e92-b665-fa4d2f0e5bf6","harvest_record_raw":"https://catalog.data.gov/harvest_record/b20ac765-98aa-4e92-b665-fa4d2f0e5bf6/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/b20ac765-98aa-4e92-b665-fa4d2f0e5bf6/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01622.xml","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Earth Science > Atmosphere > Atmospheric Winds > Surface Winds > Wind Direction","Earth Science > Atmosphere > Atmospheric Winds > Surface Winds > Wind Speed","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Dew Point Temperature","Earth Science > Atmosphere > Clouds > Cloud Properties > Cloud Amount","Earth Science > Atmosphere > Atmospheric Pressure > Sea Level Pressure","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Wind Speed and Direction","Atmospheric - Surface - Water Vapour - Dew Point","Atmospheric - Upper-air - Cloud Properties","Atmospheric - Surface - Air Pressure","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"last_harvested_date":"2026-08-10T22:05:40.907487","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":6,"publisher":"NOAA National Centers for Environmental Information","slug":"u-s-climate-normals-2020-u-s-hourly-climate-normals-1991-2020","spatial_centroid":{"lat":19.8,"lon":15.2},"spatial_shape":{"coordinates":[[[-64.0,-15.0],[-64.0,72.0],[134.0,72.0],[134.0,-15.0],[-64.0,-15.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Hourly Climate Normals (1991-2020)"},{"_score":71.749466,"_sort":[1786399539743,71.749466,8,"8cf2bbb6-d0e9-412f-bc1b-f00dc20f6d26"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-steam","description":"The Daily Climate Normals for 1991 to 2020 are 30-year averages of meteorological parameters that provide users the information needed to understand typical climate conditions for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Daily Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs)). All data utilized in the computation of the 1991-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily, but the Daily Normals are adjusted so that they are consistent with the Monthly Normals. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/d3w1-ef83","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/products/land-based-station/us-climate-normals","describedByType":"application/octet-stream","description":"Product page with documentation and data access links.","mediaType":"text/html","title":"U.S. Climate Normals Product Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/access/search/data-search/normals-daily-1991-2020","describedByType":"application/octet-stream","description":"Navigate directly to the URL for data access and direct download.","mediaType":"text/html","title":"Data Download"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/data/normals-daily/1991-2020","describedByType":"application/octet-stream","description":"Search for data by geographic location, station, and data type.","mediaType":"text/html","title":"Data Search"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Normals User Guide that provides product descriptions and formats for all data and products produced and made available to users.","downloadURL":"https://www.ncei.noaa.gov/data/normals-daily/1991-2020/doc/Normals_DLY_Documentation_1991-2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Daily Documentation 1991-2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"The science and methodologies used to generate official climate normals for the United States.","downloadURL":"https://www.ncei.noaa.gov/data/normals-daily/1991-2020/doc/Normals_Calculation_Methodology_2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Calcultation Methodology 2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This document describes the technical layout of the CSV normals files in boththe individual, by-station, format and the grouped by-variable format.  It alsoprovides a guide to the location of the variables within the larger by-variabletar files.","downloadURL":"https://www.ncei.noaa.gov/data/normals-daily/1991-2020/doc/Readme_By-Variable_By-Station_Normals_Files.txt","format":"TEXT","mediaType":"text/plain","title":"Readme By-Variable By-Station Normals Files"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in PDF and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-daily/1991-2020/doc/Normals_DLY_1991-2020_sample.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Daily 1991-2020 PDF Sample"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in CSV and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-daily/1991-2020/doc/Normals_DLY_1991-2020_sample.csv","format":"CSV","mediaType":"text/csv","title":"Normals Daily 1991-2020 CSV Sample"},{"@type":"dcat:Distribution","accessURL":"https://registry.opendata.aws/noaa-climate-normals/","describedByType":"application/octet-stream","description":"Information on AWS data access.","mediaType":"text/html","title":"Registry of Open Data on AWS"},{"@type":"dcat:Distribution","accessURL":"https://noaa-normals-pds.s3.amazonaws.com/index.html#normals-daily/1991-2020/","describedByType":"application/octet-stream","description":"Browse view to explore the S3 bucket.","mediaType":"text/html","title":"AWS S3 Explorer (Region: us-east-1)"},{"@type":"dcat:Distribution","accessURL":"https://microsoft.github.io/AIforEarthDataSets/data/noaa-climatenormals.html","describedByType":"application/octet-stream","description":"Information on Microsoft Azure data access.","mediaType":"text/html","title":"Azure Landing Page (Region: us-east)"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/BAMS-D-11-00197.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/BAMS-D-11-00197.1"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/JTECH-D-12-00195.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/JTECH-D-12-00195.1"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/4z0k-n484","describedByType":"application/octet-stream","description":"Related dataset.","mediaType":"text/html","title":"https://doi.org/10.25921/4z0k-n484"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.7289/V5PN93JP","describedByType":"application/octet-stream","description":"Older version.","mediaType":"text/html","title":"https://doi.org/10.7289/V5PN93JP"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables","describedByType":"application/octet-stream","description":"Overview of the GCOS Essential Climate Variables.","mediaType":"text/html","title":"GCOS Essential Climate Variables"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01621.xml","issued":"2021-05-04T00:00:00.000+00:00","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2023-05-15T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JTECH-D-12-00195.1","https://doi.org/10.25921/4z0k-n484","https://doi.org/10.7289/V5PN93JP"],"rights":"otherRestrictions","spatial":"-64.0,-15.0,134.0,72.0","temporal":"1991-01-01T00:00:00+00:00/2020-12-01T00:00:00+00:00","theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Daily Climate Normals (1991-2020)"},"description":"The Daily Climate Normals for 1991 to 2020 are 30-year averages of meteorological parameters that provide users the information needed to understand typical climate conditions for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Daily Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs)). All data utilized in the computation of the 1991-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily, but the Daily Normals are adjusted so that they are consistent with the Monthly Normals. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution_titles":["NCEI Dataset Landing Page","U.S. Climate Normals Product Page","Data Download","Data Search","Normals Daily Documentation 1991-2020","Normals Calcultation Methodology 2020","Readme By-Variable By-Station Normals Files","Normals Daily 1991-2020 PDF Sample","Normals Daily 1991-2020 CSV Sample","Registry of Open Data on AWS","AWS S3 Explorer (Region: us-east-1)","Azure Landing Page (Region: us-east)","https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JTECH-D-12-00195.1","https://doi.org/10.25921/4z0k-n484","https://doi.org/10.7289/V5PN93JP","Global Change Master Directory (GCMD) Keywords","GCOS Essential Climate Variables"],"harvest_record":"https://catalog.data.gov/harvest_record/00223db6-3885-443c-b504-a9ddf124ca93","harvest_record_raw":"https://catalog.data.gov/harvest_record/00223db6-3885-443c-b504-a9ddf124ca93/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/00223db6-3885-443c-b504-a9ddf124ca93/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01621.xml","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"last_harvested_date":"2026-08-10T22:05:39.743259","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":8,"publisher":"NOAA National Centers for Environmental Information","slug":"u-s-climate-normals-2020-u-s-daily-climate-normals-1991-2020","spatial_centroid":{"lat":19.8,"lon":15.2},"spatial_shape":{"coordinates":[[[-64.0,-15.0],[-64.0,72.0],[134.0,72.0],[134.0,-15.0],[-64.0,-15.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Daily Climate Normals (1991-2020)"},{"_score":72.05005,"_sort":[1786399538647,72.05005,33,"e0edfc49-9a0c-42bc-816e-1d405ae8e68b"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-steam","description":"The Monthly Climate Normals for 1991 to 2020 are 30-year averages of meteorological parameters that provide users the information needed to understand typical climate conditions for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Monthly Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs)). All data utilized in the computation of the 1991-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily and -Monthly datasets. Temperatures were homogenized, adjusted for time-of-observation, and made serially complete where possible based on information from nearby stations. Precipitation totals were also made serially complete where possible based using nearby stations. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/wck8-er13","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/products/land-based-station/us-climate-normals","describedByType":"application/octet-stream","description":"Product page with documentation and data access links.","mediaType":"text/html","title":"U.S. Climate Normals Product Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/data/normals-monthly/1991-2020","describedByType":"application/octet-stream","description":"Navigate directly to the URL for data access and direct download.","mediaType":"text/html","title":"Data Download"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/access/search/data-search/normals-monthly-1991-2020","describedByType":"application/octet-stream","description":"Search for data by geographic location, station, and data type.","mediaType":"text/html","title":"Data Search"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Normals User Guide that provides product descriptions and formats for all data and products produced and made available to users.","downloadURL":"https://www.ncei.noaa.gov/data/normals-monthly/1991-2020/doc/Normals_MLY_Documentation_1991-2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Monthly Documentation 1991-2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"The science and methodologies used to generate official climate normals for the United States.","downloadURL":"https://www.ncei.noaa.gov/data/normals-monthly/1991-2020/doc/Normals_Calculation_Methodology_2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Calculation Methodology 2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This document describes the technical layout of the CSV normals files in boththe individual, by-station, format and the grouped by-variable format.  It alsoprovides a guide to the location of the variables within the larger by-variabletar files.","downloadURL":"https://www.ncei.noaa.gov/data/normals-monthly/1991-2020/doc/Readme_By-Variable_By-Station_Normals_Files.txt","format":"TEXT","mediaType":"text/plain","title":"Readme By-Variable By-Station Normals File"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in PDF and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-monthly/1991-2020/doc/Normals_MLY_1991-2020_sample.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Monthly 1991-2020 PDF Sample"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in CSV and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-monthly/1991-2020/doc/Normals_MLY_1991-2020_sample.csv","format":"CSV","mediaType":"text/csv","title":"Normals Monthly 1991-2020 CSV Sample"},{"@type":"dcat:Distribution","accessURL":"https://registry.opendata.aws/noaa-climate-normals/","describedByType":"application/octet-stream","description":"Information on AWS data access.","mediaType":"text/html","title":"Registry of Open Data on AWS"},{"@type":"dcat:Distribution","accessURL":"https://noaa-normals-pds.s3.amazonaws.com/index.html#normals-monthly/1991-2020/","describedByType":"application/octet-stream","description":"Browse view to explore the S3 bucket.","mediaType":"text/html","title":"AWS S3 Explorer (Region: us-east-1)"},{"@type":"dcat:Distribution","accessURL":"https://microsoft.github.io/AIforEarthDataSets/data/noaa-climatenormals.html","describedByType":"application/octet-stream","description":"Information on Microsoft Azure data access.","mediaType":"text/html","title":"Azure Landing Page (Region: us-east)"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/BAMS-D-11-00197.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/BAMS-D-11-00197.1"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/JAMC-D-13-051.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/JAMC-D-13-051.1"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/yya9-9769","describedByType":"application/octet-stream","description":"Related dataset.","mediaType":"text/html","title":"https://doi.org/10.25921/yya9-9769"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.7289/V5PN93JP","describedByType":"application/octet-stream","description":"Older version.","mediaType":"text/html","title":"https://doi.org/10.7289/V5PN93JP"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables","describedByType":"application/octet-stream","description":"Overview of the GCOS Essential Climate Variables.","mediaType":"text/html","title":"GCOS Essential Climate Variables"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01620.xml","issued":"2021-05-04T00:00:00.000+00:00","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2023-05-15T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JAMC-D-13-051.1","https://doi.org/10.25921/yya9-9769","https://doi.org/10.7289/V5PN93JP"],"rights":"otherRestrictions","spatial":"-64.0,-15.0,134.0,72.0","temporal":"1991-01-01T00:00:00+00:00/2020-12-01T00:00:00+00:00","theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Monthly Climate Normals (1991-2020)"},"description":"The Monthly Climate Normals for 1991 to 2020 are 30-year averages of meteorological parameters that provide users the information needed to understand typical climate conditions for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Monthly Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs)). All data utilized in the computation of the 1991-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily and -Monthly datasets. Temperatures were homogenized, adjusted for time-of-observation, and made serially complete where possible based on information from nearby stations. Precipitation totals were also made serially complete where possible based using nearby stations. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution_titles":["NCEI Dataset Landing Page","U.S. Climate Normals Product Page","Data Download","Data Search","Normals Monthly Documentation 1991-2020","Normals Calculation Methodology 2020","Readme By-Variable By-Station Normals File","Normals Monthly 1991-2020 PDF Sample","Normals Monthly 1991-2020 CSV Sample","Registry of Open Data on AWS","AWS S3 Explorer (Region: us-east-1)","Azure Landing Page (Region: us-east)","https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JAMC-D-13-051.1","https://doi.org/10.25921/yya9-9769","https://doi.org/10.7289/V5PN93JP","Global Change Master Directory (GCMD) Keywords","GCOS Essential Climate Variables"],"harvest_record":"https://catalog.data.gov/harvest_record/c9ccc8ae-2edf-4230-b158-1246c3f343f7","harvest_record_raw":"https://catalog.data.gov/harvest_record/c9ccc8ae-2edf-4230-b158-1246c3f343f7/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/c9ccc8ae-2edf-4230-b158-1246c3f343f7/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01620.xml","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"last_harvested_date":"2026-08-10T22:05:38.647852","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":33,"publisher":"NOAA National Centers for Environmental Information","slug":"u-s-climate-normals-2020-u-s-monthly-climate-normals-1991-2020","spatial_centroid":{"lat":19.8,"lon":15.2},"spatial_shape":{"coordinates":[[[-64.0,-15.0],[-64.0,72.0],[134.0,72.0],[134.0,-15.0],[-64.0,-15.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Monthly Climate Normals (1991-2020)"},{"_score":72.39897,"_sort":[1786399537447,72.39897,38,"ca6bb944-3ab4-43fe-a005-6e1ee53bbefb"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-steam","description":"The U.S. Annual/Seasonal Climate Normals for 1991 to 2020 are 30-year averages of meteorological parameters that provide users the information needed to understand typical climate conditions for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Annual/Seasonal Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs), lengths of growing seasons, probabilities of first or last temperature threshold exceedances. All data utilized in the computation of the 1991-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily and -Monthly datasets. Temperatures were homogenized, adjusted for time-of-observation, and made serially complete where possible based on information from nearby stations. Precipitation totals were also made serially complete where possible based using nearby stations. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.25921/4ek7-fk11","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/products/land-based-station/us-climate-normals","describedByType":"application/octet-stream","description":"Product page with documentation and data access links.","mediaType":"text/html","title":"U.S. Climate Normals Product Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/1991-2020","describedByType":"application/octet-stream","description":"Navigate directly to the URL for data access and direct download.","mediaType":"text/html","title":"Data Download"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/access/search/data-search/normals-annualseasonal-1991-2020","describedByType":"application/octet-stream","description":"Search for data by geographic location, station, and data type.","mediaType":"text/html","title":"Data Search"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Normals User Guide that provides product descriptions and formats for all data and products produced and made available to users.","downloadURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/1991-2020/doc/Normals_ANN_Documentation_1991-2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Annual Documentation 1991-2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"The science and methodologies used to generate official climate normals for the United States.","downloadURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/1991-2020/doc/Normals_Calculation_Methodology_2020.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Calculation Methodology 1991-2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This document describes the technical layout of the CSV normals files in boththe individual, by-station, format and the grouped by-variable format.  It alsoprovides a guide to the location of the variables within the larger by-variabletar files.","downloadURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/1991-2020/doc/Readme_By-Variable_By-Station_Normals_Files.txt","format":"TEXT","mediaType":"text/plain","title":"Readme By-Variable By-Station Normals Files 1991-2020"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in CSV and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/1991-2020/doc/Normals_ANN_1991-2020_sample.csv","format":"CSV","mediaType":"text/csv","title":"Normals Annual 1991-2020 CSV Sample"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"This sample data file shows how the data are formatted in PDF and is for example purposes only.","downloadURL":"https://www.ncei.noaa.gov/data/normals-annualseasonal/1991-2020/doc/Normals_ANN_1991-2020_sample.pdf","format":"PDF","mediaType":"application/pdf","title":"Normals Annual 1991-2020 PDF Sample"},{"@type":"dcat:Distribution","accessURL":"https://registry.opendata.aws/noaa-climate-normals/","describedByType":"application/octet-stream","description":"Information on AWS data access.","mediaType":"text/html","title":"Registry of Open Data on AWS"},{"@type":"dcat:Distribution","accessURL":"https://noaa-normals-pds.s3.amazonaws.com/index.html#normals-annualseasonal/1991-2020/","describedByType":"application/octet-stream","description":"Browse view to explore the S3 bucket.","mediaType":"text/html","title":"AWS S3 Explorer (Region: us-east-1)"},{"@type":"dcat:Distribution","accessURL":"https://microsoft.github.io/AIforEarthDataSets/data/noaa-climatenormals.html","describedByType":"application/octet-stream","description":"Information on Microsoft Azure data access.","mediaType":"text/html","title":"Azure Landing Page (Region: us-east)"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/BAMS-D-11-00197.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/BAMS-D-11-00197.1"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Related journal article.","downloadURL":"https://doi.org/10.1175/JAMC-D-13-051.1","mediaType":"placeholder/value","title":"https://doi.org/10.1175/JAMC-D-13-051.1"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.7289/V5PN93JP","describedByType":"application/octet-stream","description":"Older version.","mediaType":"text/html","title":"https://doi.org/10.7289/V5PN93JP"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables","describedByType":"application/octet-stream","description":"Overview of the GCOS Essential Climate Variables.","mediaType":"text/html","title":"GCOS Essential Climate Variables"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01619.xml","issued":"2021-05-04T00:00:00.000+00:00","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2023-05-15T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JAMC-D-13-051.1","https://doi.org/10.7289/V5PN93JP"],"rights":"otherRestrictions","spatial":"-64.0,-15.0,134.0,72.0","temporal":"1991-01-01T00:00:00+00:00/2020-12-01T00:00:00+00:00","theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Annual/Seasonal Climate Normals (1991-2020)"},"description":"The U.S. Annual/Seasonal Climate Normals for 1991 to 2020 are 30-year averages of meteorological parameters that provide users the information needed to understand typical climate conditions for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Annual/Seasonal Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs), lengths of growing seasons, probabilities of first or last temperature threshold exceedances. All data utilized in the computation of the 1991-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily and -Monthly datasets. Temperatures were homogenized, adjusted for time-of-observation, and made serially complete where possible based on information from nearby stations. Precipitation totals were also made serially complete where possible based using nearby stations. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.","distribution_titles":["NCEI Dataset Landing Page","U.S. Climate Normals Product Page","Data Download","Data Search","Normals Annual Documentation 1991-2020","Normals Calculation Methodology 1991-2020","Readme By-Variable By-Station Normals Files 1991-2020","Normals Annual 1991-2020 CSV Sample","Normals Annual 1991-2020 PDF Sample","Registry of Open Data on AWS","AWS S3 Explorer (Region: us-east-1)","Azure Landing Page (Region: us-east)","https://doi.org/10.1175/BAMS-D-11-00197.1","https://doi.org/10.1175/JAMC-D-13-051.1","https://doi.org/10.7289/V5PN93JP","Global Change Master Directory (GCMD) Keywords","GCOS Essential Climate Variables"],"harvest_record":"https://catalog.data.gov/harvest_record/76dd3880-70e2-4fd7-bceb-2b53df464371","harvest_record_raw":"https://catalog.data.gov/harvest_record/76dd3880-70e2-4fd7-bceb-2b53df464371/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/76dd3880-70e2-4fd7-bceb-2b53df464371/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01619.xml","keyword":["Earth Science > Climate Indicators","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Air Temperature","Earth Science > Atmosphere > Precipitation > Precipitation Amount","Atmospheric - Surface - Air Temperature","Atmospheric - Surface - Precipitation","Continent > North America > United States Of America","Ocean > Pacific Ocean > Central Pacific Ocean","Vertical Location > Land Surface","Point Resolution","Point Resolution","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","Normals"],"last_harvested_date":"2026-08-10T22:05:37.447825","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":38,"publisher":"NOAA National Centers for Environmental Information","slug":"u-s-climate-normals-2020-u-s-annual-seasonal-climate-normals-1991-2020","spatial_centroid":{"lat":19.8,"lon":15.2},"spatial_shape":{"coordinates":[[[-64.0,-15.0],[-64.0,72.0],[134.0,72.0],[134.0,-15.0],[-64.0,-15.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"U.S. Climate Normals 2020: U.S. Annual/Seasonal Climate Normals (1991-2020)"},{"_score":9.412359,"_sort":[1786399536263,9.412359,2,"8d01377b-fdf9-43b3-aa9a-0a453c27c5f8"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","accrualPeriodicity":"R/P1M","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.orders@noaa.gov"},"describedByType":"application/octet-steam","description":"The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Near-Real-Time (NRT) product includes both versions 3.0.2 and 3.0.3. The new version includes blended preliminary NRT observations from ships and buoys and other platforms distributed in Traditional Alphanumeric Code (TAC) and Binary Universal Form for the Representation of meteorological data (BUFR) formats collected from the WMO Global Telecommunications System (GTS). The data are converted to the ICOADS common format, the International Maritime Meteorological Archive (IMMA) format, quality controlled, and duplicates removed for the final product.  Marine meteorological and near-surface oceanographic parameters are provided. Spatial coverage is global, and the current period of record for these files is from July 2025 to the most current, complete month.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/metadata/geoportal/rest/metadata/item/gov.noaa.ncdc:C01607/html","describedByType":"application/octet-stream","description":"Landing page for the dataset.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/data/international-comprehensive-ocean-atmosphere/v3/archive/nrt/monthly/","describedByType":"application/octet-stream","description":"Direct download links for the data files.","mediaType":"text/html","title":"NCEI Direct Download"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/thredds/catalog/international-comprehensive-ocean-atmosphere-dataset-icoads/monthly/catalog.html","describedByType":"application/octet-stream","description":"THREDDS Data Service for this dataset (NetCDF).","mediaType":"text/html","title":"NCEI THREDDS Catalog"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Freeman, E., Woodruff, S.D., Worley, S.J., Lubker, S.J., Kent, E.C., Angel, W.E., Berry, D.I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J., Rayner, N.A., Rosenhagen, G. and Smith, S.R. (2017), ICOADS Release 3.0: a major update to the historical marine climate record. Int. J. Climatol., 37: 2211-2232. https://doi.org/10.1002/joc.4775","downloadURL":"https://doi.org/10.1002/joc.4775","mediaType":"placeholder/value","title":"ICOADS Release 3.0: a major update to the historical marine climate record"},{"@type":"dcat:Distribution","accessURL":"https://icoads.noaa.gov","describedByType":"application/octet-stream","mediaType":"text/html","title":"International Comprehensive Ocean-Atmosphere Data Set Program"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables","describedByType":"application/octet-stream","description":"Overview of the GCOS Essential Climate Variables.","mediaType":"text/html","title":"GCOS Essential Climate Variables"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov","describedByType":"application/octet-stream","description":"NCEI home page with information, data access and contact information.","mediaType":"text/html","title":"NOAA National Centers for Environmental Information (NCEI)"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01607.xml","isPartOf":"ICOADS Release 3.0: a major update to the historical marine climate record","issued":"2022-03-01T00:00:00.000+00:00","keyword":["Earth Science > Atmosphere > Atmospheric Temperature","Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature","Earth Science > Atmosphere > Atmospheric Pressure","Earth Science > Atmosphere > Atmospheric Winds","Earth Science > Oceans > Ocean Waves > Wind Waves","Earth Science > Oceans > Ocean Waves > Swells","Earth Science > Atmosphere > Air Quality > Visibility","Earth Science > Atmosphere > Atmospheric Water Vapor > Water Vapor Indicators > Humidity","Earth Science > Atmosphere > Clouds","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Dew Point Temperature","Earth Science > Cryosphere > Sea Ice","Earth Science > Oceans > Salinity/Density","Earth Science > Oceans > Ocean Chemistry > Dissolved Gases","Earth Science > Oceans > Ocean Chemistry > Phosphate","Earth Science > Oceans > Ocean Chemistry > Silicate","Earth Science > Oceans > Ocean Chemistry > Nitrate","Earth Science > Oceans > Ocean Chemistry > Alkalinity","Earth Science > Oceans > Ocean Chemistry > Chlorophyll","Earth Science > Oceans > Ocean Chemistry > Carbon Dioxide","Earth Science > Oceans > Ocean Chemistry > Carbon","Atmospheric - Surface - Air Pressure","Atmospheric - Surface - Air Temperature","Oceanic - Surface - Sea-surface Temperature","Oceanic - Surface - Sea-surface Salinity","Atmospheric - Surface - Wind Speed and Direction","Oceanic - Surface - Sea Ice","Oceanic - Surface - Sea State","Oceanic - Sub-surface - Sub-surface Nutrients (including phosphates, nitrates, silicates and silicic acids)","Oceanic - Surface - Carbon Dioxide Partial Pressure","Oceanic - Sub-surface - Sub-surface Oxygen","Geographic Region > Global Ocean","Vertical Location > Sea Surface","ICOADS > International Comprehensive Ocean Atmosphere Data Set","Thermometers","Thermometers","Anemometers","Wind Vanes","Barometers","CTD > Conductivity, Temperature, Depth","XBT > Expendable Bathythermographs","Visual Observations","Buoys","MOORINGS","FLOATS","Ships","OCEAN PLATFORM/OCEAN STATIONS","Point Resolution","Point Resolution","1 minute - < 1 hour","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2022-03-01T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://doi.org/10.1002/joc.4775","https://icoads.noaa.gov"],"rights":"otherRestrictions","spatial":"180.0,-90.0,-180.0,90.0","temporal":"2015-01-01T00:00:00+00:00/2015-01-01T00:00:00+00:00","theme":["geospatial"],"title":"International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Near-Real-Time (NRT) - Monthly, Releases 3.0.2 and 3.0.3"},"description":"The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Near-Real-Time (NRT) product includes both versions 3.0.2 and 3.0.3. The new version includes blended preliminary NRT observations from ships and buoys and other platforms distributed in Traditional Alphanumeric Code (TAC) and Binary Universal Form for the Representation of meteorological data (BUFR) formats collected from the WMO Global Telecommunications System (GTS). The data are converted to the ICOADS common format, the International Maritime Meteorological Archive (IMMA) format, quality controlled, and duplicates removed for the final product.  Marine meteorological and near-surface oceanographic parameters are provided. Spatial coverage is global, and the current period of record for these files is from July 2025 to the most current, complete month.","distribution_titles":["NCEI Dataset Landing Page","NCEI Direct Download","NCEI THREDDS Catalog","ICOADS Release 3.0: a major update to the historical marine climate record","International Comprehensive Ocean-Atmosphere Data Set Program","Global Change Master Directory (GCMD) Keywords","GCOS Essential Climate Variables","NOAA National Centers for Environmental Information (NCEI)"],"harvest_record":"https://catalog.data.gov/harvest_record/aa1b431d-b790-4941-8d35-bcf3584eecf0","harvest_record_raw":"https://catalog.data.gov/harvest_record/aa1b431d-b790-4941-8d35-bcf3584eecf0/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/aa1b431d-b790-4941-8d35-bcf3584eecf0/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C01607.xml","keyword":["Earth Science > Atmosphere > Atmospheric Temperature","Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature","Earth Science > Atmosphere > Atmospheric Pressure","Earth Science > Atmosphere > Atmospheric Winds","Earth Science > Oceans > Ocean Waves > Wind Waves","Earth Science > Oceans > Ocean Waves > Swells","Earth Science > Atmosphere > Air Quality > Visibility","Earth Science > Atmosphere > Atmospheric Water Vapor > Water Vapor Indicators > Humidity","Earth Science > Atmosphere > Clouds","Earth Science > Atmosphere > Atmospheric Temperature > Surface Temperature > Dew Point Temperature","Earth Science > Cryosphere > Sea Ice","Earth Science > Oceans > Salinity/Density","Earth Science > Oceans > Ocean Chemistry > Dissolved Gases","Earth Science > Oceans > Ocean Chemistry > Phosphate","Earth Science > Oceans > Ocean Chemistry > Silicate","Earth Science > Oceans > Ocean Chemistry > Nitrate","Earth Science > Oceans > Ocean Chemistry > Alkalinity","Earth Science > Oceans > Ocean Chemistry > Chlorophyll","Earth Science > Oceans > Ocean Chemistry > Carbon Dioxide","Earth Science > Oceans > Ocean Chemistry > Carbon","Atmospheric - Surface - Air Pressure","Atmospheric - Surface - Air Temperature","Oceanic - Surface - Sea-surface Temperature","Oceanic - Surface - Sea-surface Salinity","Atmospheric - Surface - Wind Speed and Direction","Oceanic - Surface - Sea Ice","Oceanic - Surface - Sea State","Oceanic - Sub-surface - Sub-surface Nutrients (including phosphates, nitrates, silicates and silicic acids)","Oceanic - Surface - Carbon Dioxide Partial Pressure","Oceanic - Sub-surface - Sub-surface Oxygen","Geographic Region > Global Ocean","Vertical Location > Sea Surface","ICOADS > International Comprehensive Ocean Atmosphere Data Set","Thermometers","Thermometers","Anemometers","Wind Vanes","Barometers","CTD > Conductivity, Temperature, Depth","XBT > Expendable Bathythermographs","Visual Observations","Buoys","MOORINGS","FLOATS","Ships","OCEAN PLATFORM/OCEAN STATIONS","Point Resolution","Point Resolution","1 minute - < 1 hour","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce"],"last_harvested_date":"2026-08-10T22:05:36.263399","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":2,"publisher":"NOAA National Centers for Environmental Information","slug":"international-comprehensive-ocean-atmosphere-data-set-icoads-near-real-time-nrt-release-3-","spatial_centroid":{"lat":-18.0,"lon":36.0},"spatial_shape":{"coordinates":[[[180.0,-90.0],[180.0,90.0],[-180.0,90.0],[-180.0,-90.0],[180.0,-90.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Near-Real-Time (NRT) - Monthly, Releases 3.0.2 and 3.0.3"},{"_score":40.142715,"_sort":[1786399520550,40.142715,1,"39b160db-31dd-4084-a444-0f7419fe533b"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"National Centers for Environmental Information","hasEmail":"mailto:avhrr_patmosx_contacts@noaa.gov"},"describedByType":"application/octet-steam","description":"*Note: This dataset version has been superseded by a newer version. It is highly recommended that users access the current version. Users should only use this version for special cases, such as reproducing studies that used this version.* This NOAA Climate Data Record (CDR) of AVHRR reflectance and brightness temperatures was produced by the University of Wisconsin using the AVHRR Pathfinder Atmospheres - Extended (PATMOS-X) Version 5.3 processing system. The CDR spans from 1979 to the present with daily, global coverage generated from between two and ten NOAA and MetOp satellite passes per day. The source AVHRR data points, with a sensor resolution of 1.09 km near nadir, have been fitted to a 0.1 x 0.1 degree equal-angle grid in ascending and descending files. The calibrated reflectance channels in the visible spectrum (0.63, 0.86, and 1.6 microns) portion of the record were delivered as a CDR in Version 5.2 in 2010. This updated Version 5.3 extends the product to include brightness temperatures from the 3.75, 11 and 12 micron channels, as well as a suite of cloud products (the PATMOS-x Cloud Properties CDR). Version 5.3 also extends the period of record through the present and applies the newest calibration coefficients. In total, there are seven (7) AVHRR channel variables. Not counting the coordinate variables, there are 48 data and ancillary data variables in the netCDF data file to facilitate proper data usage. The file format was converted from HDF to netCDF-4 with metadata following the Climate and Forecast (CF) Conventions and Attribute Convention for Dataset Discovery (ACDD). The dataset is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.7289/V56W982J","describedByType":"application/octet-stream","description":"Dataset landing page with general information and access links for the dataset.","mediaType":"text/html","title":"NCEI landing page for this dataset"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/products/climate-data-records/avhrr-hirs-reflectance-patmos","describedByType":"application/octet-stream","description":"Access to the published CDR product, documentation and source code.","mediaType":"text/html","title":"NOAA CDR page"},{"@type":"dcat:Distribution","accessURL":"https://cimss.ssec.wisc.edu/patmosx/","describedByType":"application/octet-stream","description":"Project page with dataset information.","mediaType":"text/html","title":"CIMSS PATMOS-x project page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/contact","describedByType":"application/octet-stream","description":"This dataset is not available online. Please contact NCEI to request the dataset.","mediaType":"text/html","title":"Contact NCEI"},{"@type":"dcat:Distribution","describedByType":"application/octet-stream","description":"Heidinger, A.K., M.J. Foster, A. Walther, and X. Zhao, 2014: The Pathfinder Atmospheres-Extended AVHRR Climate Dataset. Bull. Amer. Meteor. Soc., 95, 909-922, https://doi.org/10.1175/BAMS-D-12-00246.1","downloadURL":"https://doi.org/10.1175/BAMS-D-12-00246.1","mediaType":"placeholder/value","title":"Journal Article published June 2014 by the American Meteorological Society"},{"@type":"dcat:Distribution","accessURL":"https://scholar.google.com/scholar?q=10.7289%2FV56W982J+OR+10.1175%2FBAMS-D-12-00246.1","describedByType":"application/octet-stream","description":"Search results for publications that cite this dataset by its DOI(s).","mediaType":"text/html","title":"Google Scholar search results"},{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.7289/V5X9287S","describedByType":"application/octet-stream","description":"Landing page for the Current Version.","mediaType":"text/html","title":"NCEI Dataset Landing Page for the Current Version"},{"@type":"dcat:Distribution","accessURL":"https://data.nodc.noaa.gov/cgi-bin/iso?id=gov.noaa.ncdc:C00831","describedByType":"application/octet-stream","description":"Superseded dataset landing page.","mediaType":"text/html","title":"NCEI landing page for the Version 5.2 dataset"},{"@type":"dcat:Distribution","accessURL":"https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords","describedByType":"application/octet-stream","description":"The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords.","mediaType":"text/html","title":"Global Change Master Directory (GCMD) Keywords"},{"@type":"dcat:Distribution","accessURL":"https://geo-ide.noaa.gov/wiki/index.php?title=MD_Keywords","describedByType":"application/octet-stream","description":"Instructions and examples for ISO keywords.","mediaType":"text/html","title":"NOAA Environmental Data Management Wiki: MD Keywords"},{"@type":"dcat:Distribution","accessURL":"https://www.ncdc.noaa.gov/cdr","describedByType":"application/octet-stream","description":"Contact information for the CDR Program.","mediaType":"text/html","title":"CDR Program Contacts"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C00837.xml","issued":"2014-07-03T00:00:00.000+00:00","keyword":["Earth Science > Spectral/Engineering > Visible Wavelengths > Visible Radiance","Earth Science > Spectral/Engineering > Infrared Wavelengths > Brightness Temperature","Satellite","Geographic Region > Global Land","NOAA Climate Data Record (CDR) Program","NOAA OneStop Project","AVHRR > Advanced Very High Resolution Radiometer","AVHRR-2 > Advanced Very High Resolution Radiometer-2","AVHRR-3 > Advanced Very High Resolution Radiometer-3","TIROS-N > Television Infrared Observation Satellite-N","NOAA-6 > National Oceanic & Atmospheric Administration - 6","NOAA-7 > National Oceanic & Atmospheric Administration - 7","NOAA-8 > National Oceanic & Atmospheric Administration - 8","NOAA-9 > National Oceanic & Atmospheric Administration - 9","NOAA-10 > National Oceanic & Atmospheric Administration - 10","NOAA-11 > National Oceanic & Atmospheric Administration - 11","NOAA-12 > National Oceanic & Atmospheric Administration - 12","NOAA-14 > National Oceanic & Atmospheric Administration - 14","NOAA-15 > National Oceanic & Atmospheric Administration - 15","NOAA-16 > National Oceanic & Atmospheric Administration - 16","NOAA-17 > National Oceanic & Atmospheric Administration - 17","NOAA-18 > National Oceanic & Atmospheric Administration - 18","NOAA-19 > National Oceanic & Atmospheric Administration - 19","MetOp-A > Meteorological Operational Satellite - A","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","DOC/NOAA/NESDIS/NCDC > National Climatic Data Center, NESDIS, NOAA, U.S. Department of Commerce","UWI-MAD/SSEC > Space Science and Engineering Center, University of Wisconsin, Madison"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2014-07-03T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"National Centers for Environmental Information"},"references":["https://doi.org/10.1175/BAMS-D-12-00246.1","https://scholar.google.com/scholar?q=10.7289%2FV56W982J+OR+10.1175%2FBAMS-D-12-00246.1","https://doi.org/10.7289/V5X9287S","https://data.nodc.noaa.gov/cgi-bin/iso?id=gov.noaa.ncdc:C00831"],"rights":"otherRestrictions","spatial":"180.0,-90.0,-180.0,90.0","temporal":"1979-01-01T00:00:00+00:00/2022-01-01T00:00:00+00:00","theme":["geospatial"],"title":"NOAA Climate Data Record (CDR) of Reflectance and Brightness Temperatures from AVHRR Pathfinder Atmospheres - Extended (PATMOS-x), Version 5.3 (Version Superseded)"},"description":"*Note: This dataset version has been superseded by a newer version. It is highly recommended that users access the current version. Users should only use this version for special cases, such as reproducing studies that used this version.* This NOAA Climate Data Record (CDR) of AVHRR reflectance and brightness temperatures was produced by the University of Wisconsin using the AVHRR Pathfinder Atmospheres - Extended (PATMOS-X) Version 5.3 processing system. The CDR spans from 1979 to the present with daily, global coverage generated from between two and ten NOAA and MetOp satellite passes per day. The source AVHRR data points, with a sensor resolution of 1.09 km near nadir, have been fitted to a 0.1 x 0.1 degree equal-angle grid in ascending and descending files. The calibrated reflectance channels in the visible spectrum (0.63, 0.86, and 1.6 microns) portion of the record were delivered as a CDR in Version 5.2 in 2010. This updated Version 5.3 extends the product to include brightness temperatures from the 3.75, 11 and 12 micron channels, as well as a suite of cloud products (the PATMOS-x Cloud Properties CDR). Version 5.3 also extends the period of record through the present and applies the newest calibration coefficients. In total, there are seven (7) AVHRR channel variables. Not counting the coordinate variables, there are 48 data and ancillary data variables in the netCDF data file to facilitate proper data usage. The file format was converted from HDF to netCDF-4 with metadata following the Climate and Forecast (CF) Conventions and Attribute Convention for Dataset Discovery (ACDD). The dataset is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program.","distribution_titles":["NCEI landing page for this dataset","NOAA CDR page","CIMSS PATMOS-x project page","Contact NCEI","Journal Article published June 2014 by the American Meteorological Society","Google Scholar search results","NCEI Dataset Landing Page for the Current Version","NCEI landing page for the Version 5.2 dataset","Global Change Master Directory (GCMD) Keywords","NOAA Environmental Data Management Wiki: MD Keywords","CDR Program Contacts"],"harvest_record":"https://catalog.data.gov/harvest_record/9dee2478-8734-4959-9578-d6e2f8ac0669","harvest_record_raw":"https://catalog.data.gov/harvest_record/9dee2478-8734-4959-9578-d6e2f8ac0669/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/9dee2478-8734-4959-9578-d6e2f8ac0669/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/aim/iso/xml/C00837.xml","keyword":["Earth Science > Spectral/Engineering > Visible Wavelengths > Visible Radiance","Earth Science > Spectral/Engineering > Infrared Wavelengths > Brightness Temperature","Satellite","Geographic Region > Global Land","NOAA Climate Data Record (CDR) Program","NOAA OneStop Project","AVHRR > Advanced Very High Resolution Radiometer","AVHRR-2 > Advanced Very High Resolution Radiometer-2","AVHRR-3 > Advanced Very High Resolution Radiometer-3","TIROS-N > Television Infrared Observation Satellite-N","NOAA-6 > National Oceanic & Atmospheric Administration - 6","NOAA-7 > National Oceanic & Atmospheric Administration - 7","NOAA-8 > National Oceanic & Atmospheric Administration - 8","NOAA-9 > National Oceanic & Atmospheric Administration - 9","NOAA-10 > National Oceanic & Atmospheric Administration - 10","NOAA-11 > National Oceanic & Atmospheric Administration - 11","NOAA-12 > National Oceanic & Atmospheric Administration - 12","NOAA-14 > National Oceanic & Atmospheric Administration - 14","NOAA-15 > National Oceanic & Atmospheric Administration - 15","NOAA-16 > National Oceanic & Atmospheric Administration - 16","NOAA-17 > National Oceanic & Atmospheric Administration - 17","NOAA-18 > National Oceanic & Atmospheric Administration - 18","NOAA-19 > National Oceanic & Atmospheric Administration - 19","MetOp-A > Meteorological Operational Satellite - A","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","DOC/NOAA/NESDIS/NCDC > National Climatic Data Center, NESDIS, NOAA, U.S. Department of Commerce","UWI-MAD/SSEC > Space Science and Engineering Center, University of Wisconsin, Madison"],"last_harvested_date":"2026-08-10T22:05:20.550711","organization":{"aliases":[""],"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"popularity":1,"publisher":"National Centers for Environmental Information","slug":"noaa-climate-data-record-cdr-of-reflectance-and-brightness-temperatures-from-avhrr-pathfin","spatial_centroid":{"lat":-18.0,"lon":36.0},"spatial_shape":{"coordinates":[[[180.0,-90.0],[180.0,90.0],[-180.0,90.0],[-180.0,-90.0],[180.0,-90.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"NOAA Climate Data Record (CDR) of Reflectance and Brightness Temperatures from AVHRR Pathfinder Atmospheres - Extended (PATMOS-x), Version 5.3 (Version Superseded)"},{"_score":8.208607,"_sort":[1786320907386,8.208607,3,"6fb3691a-55bc-462e-82ed-7db02769e05c"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Michael E. Wieczorek","hasEmail":"mailto:mewieczo@usgs.gov"},"description":"This data set represents the area of Hydrologic Landscape Regions (HLR) compiled for every catchment \nof NHDPlus for the conterminous United States. The source data set is a 100-meter version of Hydrologic \nLandscape Regions of the United States (Wolock, 2003). HLR groups watersheds on the basis of similarities \nin land-surface form, geologic texture, and climate characteristics.\n\t\t\nThe NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates \nmany of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset \n(NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, \nnaming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments \n(drainage areas) produced using a drainage enforcement technique first widely used in New England, \nand thus referred to as \"the New England Method.\" This technique involves \"burning in\" the 1:100,000-scale \nNHD and when available building \"walls\" using the National Watershed Boundary Dataset (WBD). The \nresulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree \nwith the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey \n(USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method \nproduces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus \ndataset is organized by 18 Production Units that cover the conterminous United States.\n\t\t\nThe NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's  Major River Basins (MRBs, \nCrawford and others, 2006).  MRB1, covering the New England and Mid-Atlantic River basins, contains \nNHDPlus Production Units 1 and 2.  MRB2, covering the South Atlantic-Gulf and Tennessee River basins, \ncontains NHDPlus Production Units 3 and 6.  MRB3, covering the Great Lakes, Ohio, Upper Mississippi, \nand Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9.  MRB4, covering \nthe Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper.  MRB5, covering \nthe Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production \nUnits 8, 11 and 12.  MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains \nNHDPlus Production Units 13, 14, 15 and 16.  MRB7, covering the Pacific Northwest River basins, \ncontains NHDPlus Production Unit 17.  MRB8, covering California River basins, contains NHDPlus \nProduction Unit 18.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9142BM0","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.93b2f75c-33bc-4cae-b48e-41b6f85d2e39.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_93b2f75c-33bc-4cae-b48e-41b6f85d2e39","keyword":["CALI","COGB","California","Catchment","Conterminous United States","GLMR","Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy","Hydrologic landscape regions","Inlandwaters","LMTG","Lower Mississippi, Arkansas-White-Red, and Texas-Gulf","MORI","MRB","MRB1","MRB2","MRB3","MRB4","MRB5","MRB6","MRB7","MRB8","Major River Basin","Missouri","NAWQA","NEMA","NHDPlus","New England and Mid-Atlantic","PANW","Pacific Northwest","Rio Grande, Colorado, and Great Basin","SAGT","SPARROW","South Atlantic-Gulf and Tennessee","USGS:93b2f75c-33bc-4cae-b48e-41b6f85d2e39","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-127.910792, 23.243486, -65.327751, 51.657387","theme":["geospatial"],"title":"Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Hydrologic Landscape Regions"},"description":"This data set represents the area of Hydrologic Landscape Regions (HLR) compiled for every catchment \nof NHDPlus for the conterminous United States. The source data set is a 100-meter version of Hydrologic \nLandscape Regions of the United States (Wolock, 2003). HLR groups watersheds on the basis of similarities \nin land-surface form, geologic texture, and climate characteristics.\n\t\t\nThe NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates \nmany of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset \n(NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, \nnaming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments \n(drainage areas) produced using a drainage enforcement technique first widely used in New England, \nand thus referred to as \"the New England Method.\" This technique involves \"burning in\" the 1:100,000-scale \nNHD and when available building \"walls\" using the National Watershed Boundary Dataset (WBD). The \nresulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree \nwith the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey \n(USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method \nproduces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus \ndataset is organized by 18 Production Units that cover the conterminous United States.\n\t\t\nThe NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's  Major River Basins (MRBs, \nCrawford and others, 2006).  MRB1, covering the New England and Mid-Atlantic River basins, contains \nNHDPlus Production Units 1 and 2.  MRB2, covering the South Atlantic-Gulf and Tennessee River basins, \ncontains NHDPlus Production Units 3 and 6.  MRB3, covering the Great Lakes, Ohio, Upper Mississippi, \nand Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9.  MRB4, covering \nthe Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper.  MRB5, covering \nthe Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production \nUnits 8, 11 and 12.  MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains \nNHDPlus Production Units 13, 14, 15 and 16.  MRB7, covering the Pacific Northwest River basins, \ncontains NHDPlus Production Unit 17.  MRB8, covering California River basins, contains NHDPlus \nProduction Unit 18.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/2a952601-f29d-415f-af76-ca51ac2aa2ab","harvest_record_raw":"https://catalog.data.gov/harvest_record/2a952601-f29d-415f-af76-ca51ac2aa2ab/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_93b2f75c-33bc-4cae-b48e-41b6f85d2e39","keyword":["CALI","COGB","California","Catchment","Conterminous United States","GLMR","Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy","Hydrologic landscape regions","Inlandwaters","LMTG","Lower Mississippi, Arkansas-White-Red, and Texas-Gulf","MORI","MRB","MRB1","MRB2","MRB3","MRB4","MRB5","MRB6","MRB7","MRB8","Major River Basin","Missouri","NAWQA","NEMA","NHDPlus","New England and Mid-Atlantic","PANW","Pacific Northwest","Rio Grande, Colorado, and Great Basin","SAGT","SPARROW","South Atlantic-Gulf and Tennessee","USGS:93b2f75c-33bc-4cae-b48e-41b6f85d2e39","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-08-10T00:15:07.386487","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":3,"publisher":"U.S. Geological Survey","slug":"attributes-for-nhdplus-catchments-version-1-1-for-the-conterminous-united-states-hydrologi","spatial_centroid":{"lat":34.6090464,"lon":-102.8775756},"spatial_shape":{"coordinates":[[[-127.910792,23.243486],[-127.910792,51.657387],[-65.327751,51.657387],[-65.327751,23.243486],[-127.910792,23.243486]]],"type":"Polygon"},"theme":["geospatial"],"title":"Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Hydrologic Landscape Regions"},{"_score":19.196514,"_sort":[1786320224666,19.196514,4,"e2714ff8-adf8-4a22-a8eb-601f30c5f482"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Virginia and West Virginia Water Science Center","hasEmail":"mailto:dlmoyer@usgs.gov"},"description":"1D transient numerical simulations with a modified version of the SUTRA model \n(preliminary code) that accounts for variably-saturated freeze-thaw dynamics \n(e.g. McKenzie and Voss, 2013) to predict annual alluvial aquifer temperature \ndynamics using coupled fluid and heat transport physics. The model simulations \nwere run with a modified version of SUTRA_ICE (unreleased) that accomadates \na time-variable sinusiodal upper temperature boundary. This data release also \nincludes the source code and Argus One GUI files used to build the models, \nthough this proprietary software is not needed to run the models as described \nin the upper-level \"readme\" file.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/F7F47M8Q","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.8ec2db4f-7c68-42da-8beb-0c4a7cb2d060.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_8ec2db4f-7c68-42da-8beb-0c4a7cb2d060","keyword":["Groundwater","InlandWaters","SUTRA","SUTRA-ice","Shenandoah National Park","Surface Water","Thermal","USGS:8ec2db4f-7c68-42da-8beb-0c4a7cb2d060","Virginia","environment","geoscientificInformation","inlandWaters","refugia"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-78.378933, 38.53969, -78.347222, 38.58403","theme":["geospatial"],"title":"Modeled temperature data developed for study of shallow mountain bedrock limits seepage-based headwater climate refugia, Shenandoah National Park, Virginia: U.S. Geological Survey data release"},"description":"1D transient numerical simulations with a modified version of the SUTRA model \n(preliminary code) that accounts for variably-saturated freeze-thaw dynamics \n(e.g. McKenzie and Voss, 2013) to predict annual alluvial aquifer temperature \ndynamics using coupled fluid and heat transport physics. The model simulations \nwere run with a modified version of SUTRA_ICE (unreleased) that accomadates \na time-variable sinusiodal upper temperature boundary. This data release also \nincludes the source code and Argus One GUI files used to build the models, \nthough this proprietary software is not needed to run the models as described \nin the upper-level \"readme\" file.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/41d89250-96b2-41f9-b38c-a881ceb6906e","harvest_record_raw":"https://catalog.data.gov/harvest_record/41d89250-96b2-41f9-b38c-a881ceb6906e/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_8ec2db4f-7c68-42da-8beb-0c4a7cb2d060","keyword":["Groundwater","InlandWaters","SUTRA","SUTRA-ice","Shenandoah National Park","Surface Water","Thermal","USGS:8ec2db4f-7c68-42da-8beb-0c4a7cb2d060","Virginia","environment","geoscientificInformation","inlandWaters","refugia"],"last_harvested_date":"2026-08-10T00:03:44.666118","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":4,"publisher":"U.S. Geological Survey","slug":"modeled-temperature-data-developed-for-study-of-shallow-mountain-bedrock-limits-seepage-ba","spatial_centroid":{"lat":38.557426,"lon":-78.3662486},"spatial_shape":{"coordinates":[[[-78.378933,38.53969],[-78.378933,38.58403],[-78.347222,38.58403],[-78.347222,38.53969],[-78.378933,38.53969]]],"type":"Polygon"},"theme":["geospatial"],"title":"Modeled temperature data developed for study of shallow mountain bedrock limits seepage-based headwater climate refugia, Shenandoah National Park, Virginia: U.S. Geological Survey data release"},{"_score":24.3112,"_sort":[1786319998730,24.3112,1,"cc1e5a35-411e-412b-ae24-a35459c2a5ee"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Fred D Tillman","hasEmail":"mailto:ftillman@usgs.gov"},"description":"hsg_UCRB_Maurer_resolution.asc is an Esri ASCII grid representing the hydrologic soil group \n(HSG) for the Upper Colorado River Basin.  The HSG for an area is determined by the least \nwater-transmitting layer in the soil column. The Natural Resources Conservation Service \n(NRCS) classifies four HSGs from Group A (high infiltration capacity and low overland flow \npotential) to Group D (low infiltration capacity and high overland flow potential). In Soil-Water \nBalance recharge simulations, a lookup table incorporates HSG and land-cover information \nfor each grid cell to define unique runoff curve numbers, vegetation rooting depths, interception \nvalues, and maximum daily recharge values.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9CRMCYQ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.54f57f83-ee11-44ce-82d7-bb5f1e06e86f.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_54f57f83-ee11-44ce-82d7-bb5f1e06e86f","keyword":["Arizona","California","Colorado","Nevada","New Mexico","USGS:54f57f83-ee11-44ce-82d7-bb5f1e06e86f","Upper Colorado River Basin","Utah","Wyoming","environment","geoscientificInformation","groundwater","groundwater recharge","hydrologic soil group","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-112.625, 35.125, -105.25, 43.75","theme":["geospatial"],"title":"Hydrologic Soil Group for the Upper Colorado River Basin in Maurer et al. (2002) Climate Data resolution (hsg_UCRB_Maurer_resolution.asc)"},"description":"hsg_UCRB_Maurer_resolution.asc is an Esri ASCII grid representing the hydrologic soil group \n(HSG) for the Upper Colorado River Basin.  The HSG for an area is determined by the least \nwater-transmitting layer in the soil column. The Natural Resources Conservation Service \n(NRCS) classifies four HSGs from Group A (high infiltration capacity and low overland flow \npotential) to Group D (low infiltration capacity and high overland flow potential). In Soil-Water \nBalance recharge simulations, a lookup table incorporates HSG and land-cover information \nfor each grid cell to define unique runoff curve numbers, vegetation rooting depths, interception \nvalues, and maximum daily recharge values.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/f7b2c98e-83c9-4a1b-b73a-db16d4bcad3d","harvest_record_raw":"https://catalog.data.gov/harvest_record/f7b2c98e-83c9-4a1b-b73a-db16d4bcad3d/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_54f57f83-ee11-44ce-82d7-bb5f1e06e86f","keyword":["Arizona","California","Colorado","Nevada","New Mexico","USGS:54f57f83-ee11-44ce-82d7-bb5f1e06e86f","Upper Colorado River Basin","Utah","Wyoming","environment","geoscientificInformation","groundwater","groundwater recharge","hydrologic soil group","inlandWaters"],"last_harvested_date":"2026-08-09T23:59:58.730291","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":1,"publisher":"U.S. Geological Survey","slug":"hydrologic-soil-group-for-the-upper-colorado-river-basin-in-maurer-et-al-2002-climate-data","spatial_centroid":{"lat":38.575,"lon":-109.675},"spatial_shape":{"coordinates":[[[-112.625,35.125],[-112.625,43.75],[-105.25,43.75],[-105.25,35.125],[-112.625,35.125]]],"type":"Polygon"},"theme":["geospatial"],"title":"Hydrologic Soil Group for the Upper Colorado River Basin in Maurer et al. (2002) Climate Data resolution (hsg_UCRB_Maurer_resolution.asc)"},{"_score":32.088684,"_sort":[1786319895912,32.088684,1,"bfcbbb22-7596-41f3-8562-e0d74b5eb014"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"John A Engott","hasEmail":"mailto:jaengott@usgs.gov"},"description":"The shapefile associated with this metadata file represents the spatial distribution of mean annual \nwater-budget components, in inches, for the Island of Oahu, Hawaii. The water-budget components \nin the shapefile were computed by a water-budget model for a scenario representative of average \nclimate conditions (1978\u20132007 rainfall) and 2010 land cover, as described in USGS Scientific \nInvestigations Report (SIR) 2015-5010. The model was developed for estimating groundwater \nrecharge and other water-budget components for each subarea of the model. The model subareas \nwere generated using Esri ArcGIS software by intersecting (merging) multiple spatial data sets \nthat characterize the spatial distribution of rainfall, fog interception, irrigation, reference \nevapotranspiration, direct runoff, soil type, and land cover. These spatial data sets characterize \nthe spatial distribution of hydrologic and physical conditions that the model uses to compute \ngroundwater recharge and other water-budget components.The model-subarea data set (387,533 \npolygons) was subsequently intersected with the 0-ft elevation contour of the top of the basalt \naquifer to produce the 395,955 polygons in this shapefile. This metadata file describes the process \nof merging these spatial data sets,  The shapefile attribute information associated with each \npolygon present an estimate of mean annual rainfall, fog interception, irrigation, septic-system \nleachate, runoff, canopy evaporation, actual evapotranspiration, storm-drain capture, net precipitation, \ntotal evapotranspiration, recharge, and seepage from reservoirs and cesspools. This shapefile also \nincludes select geographic and land-cover attributes of the polygons. Brief descriptions of the \nwater-budget components and attributes are included in this metadata file. Refer to USGS \nSIR 2015-5010 for further details of the methods and sources used to determine these \ncomponents and attributes.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9GO0SU1","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.38975e2a-b3ce-44cd-bf4c-9c827c0e1309.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_38975e2a-b3ce-44cd-bf4c-9c827c0e1309","keyword":["Hawaii","Oahu","Pacific islands","USGS:38975e2a-b3ce-44cd-bf4c-9c827c0e1309","canopy evaporation","environment","evapotranspiration","fog interception","geoscientificInformation","groundwater recharge","inlandWaters","irrigation","rainfall","runoff","soil-water balance","storm-drain capture","water-budget model"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-158.282291463, 21.253656969, -157.644933809, 21.714009852","theme":["geospatial"],"title":"Mean annual water-budget components for the Island of Oahu, Hawaii, for average climate conditions, 1978-2007 rainfall and 2010 land cover (version 2.0)"},"description":"The shapefile associated with this metadata file represents the spatial distribution of mean annual \nwater-budget components, in inches, for the Island of Oahu, Hawaii. The water-budget components \nin the shapefile were computed by a water-budget model for a scenario representative of average \nclimate conditions (1978\u20132007 rainfall) and 2010 land cover, as described in USGS Scientific \nInvestigations Report (SIR) 2015-5010. The model was developed for estimating groundwater \nrecharge and other water-budget components for each subarea of the model. The model subareas \nwere generated using Esri ArcGIS software by intersecting (merging) multiple spatial data sets \nthat characterize the spatial distribution of rainfall, fog interception, irrigation, reference \nevapotranspiration, direct runoff, soil type, and land cover. These spatial data sets characterize \nthe spatial distribution of hydrologic and physical conditions that the model uses to compute \ngroundwater recharge and other water-budget components.The model-subarea data set (387,533 \npolygons) was subsequently intersected with the 0-ft elevation contour of the top of the basalt \naquifer to produce the 395,955 polygons in this shapefile. This metadata file describes the process \nof merging these spatial data sets,  The shapefile attribute information associated with each \npolygon present an estimate of mean annual rainfall, fog interception, irrigation, septic-system \nleachate, runoff, canopy evaporation, actual evapotranspiration, storm-drain capture, net precipitation, \ntotal evapotranspiration, recharge, and seepage from reservoirs and cesspools. This shapefile also \nincludes select geographic and land-cover attributes of the polygons. Brief descriptions of the \nwater-budget components and attributes are included in this metadata file. Refer to USGS \nSIR 2015-5010 for further details of the methods and sources used to determine these \ncomponents and attributes.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/98636e4a-ce61-4a90-8e0c-2254bace4a94","harvest_record_raw":"https://catalog.data.gov/harvest_record/98636e4a-ce61-4a90-8e0c-2254bace4a94/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_38975e2a-b3ce-44cd-bf4c-9c827c0e1309","keyword":["Hawaii","Oahu","Pacific islands","USGS:38975e2a-b3ce-44cd-bf4c-9c827c0e1309","canopy evaporation","environment","evapotranspiration","fog interception","geoscientificInformation","groundwater recharge","inlandWaters","irrigation","rainfall","runoff","soil-water balance","storm-drain capture","water-budget model"],"last_harvested_date":"2026-08-09T23:58:15.912268","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":1,"publisher":"U.S. Geological Survey","slug":"mean-annual-water-budget-components-for-the-island-of-oahu-hawaii-for-average-climate-cond","spatial_centroid":{"lat":21.4377981222,"lon":-158.02734840140002},"spatial_shape":{"coordinates":[[[-158.282291463,21.253656969],[-158.282291463,21.714009852],[-157.644933809,21.714009852],[-157.644933809,21.253656969],[-158.282291463,21.253656969]]],"type":"Polygon"},"theme":["geospatial"],"title":"Mean annual water-budget components for the Island of Oahu, Hawaii, for average climate conditions, 1978-2007 rainfall and 2010 land cover (version 2.0)"},{"_score":14.791097,"_sort":[1786319103609,14.791097,2,"1b471c58-aa54-4375-b5df-778657a6849a"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Jennifer S. Stanton","hasEmail":"mailto:jstanton@usgs.gov"},"description":"The water-budget components geodatabase contains selected data from maps in the, \n\"Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 \nthrough 1949 and 2000 through 2009\" report (Stanton and others, 2011).Data were \ncollected and synthesized from existing climate models including the Parameter-Elevation \nRegressions on Independent Slopes Model (PRISM) (Daly and others, 1994), and the Snow \naccumulation and ablation model (SNOW-17) (Anderson, 2006), and used in soil-water \nbalance models to compute various components of a water budget. The methodologies \nused to compute the averages and volumes for the data in this geodatabase are slightly \ndifferent for different components and models.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P90XT1YP","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.fab4301e-91af-41bd-ae87-6e598372d09c.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_fab4301e-91af-41bd-ae87-6e598372d09c","keyword":["Colorado","Great Plains","High Plains","High Plains aquifer","Kansas","Nebraska","New Mexico","Ogallala aquifer","Oklahoma","SOil WATer (SOWAT) Balance Model","South Dakota","Texas","USGS:fab4301e-91af-41bd-ae87-6e598372d09c","Wyoming","aquifers","central High Plains","environment","geoscientificInformation","ground water","groundwater","inlandWaters","northern High Plains","recharge","southern High Plains"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-106.019428, 31.594384, -96.222657, 43.807131","theme":["geospatial"],"title":"DS-777 Average Annual Recharge, 2000 to 2009, in inches estimated from the SOil WATer (SOWAT) Balance Model for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming"},"description":"The water-budget components geodatabase contains selected data from maps in the, \n\"Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 \nthrough 1949 and 2000 through 2009\" report (Stanton and others, 2011).Data were \ncollected and synthesized from existing climate models including the Parameter-Elevation \nRegressions on Independent Slopes Model (PRISM) (Daly and others, 1994), and the Snow \naccumulation and ablation model (SNOW-17) (Anderson, 2006), and used in soil-water \nbalance models to compute various components of a water budget. The methodologies \nused to compute the averages and volumes for the data in this geodatabase are slightly \ndifferent for different components and models.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/7c2a798f-ea82-4398-8bf5-19db5e023dd9","harvest_record_raw":"https://catalog.data.gov/harvest_record/7c2a798f-ea82-4398-8bf5-19db5e023dd9/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_fab4301e-91af-41bd-ae87-6e598372d09c","keyword":["Colorado","Great Plains","High Plains","High Plains aquifer","Kansas","Nebraska","New Mexico","Ogallala aquifer","Oklahoma","SOil WATer (SOWAT) Balance Model","South Dakota","Texas","USGS:fab4301e-91af-41bd-ae87-6e598372d09c","Wyoming","aquifers","central High Plains","environment","geoscientificInformation","ground water","groundwater","inlandWaters","northern High Plains","recharge","southern High Plains"],"last_harvested_date":"2026-08-09T23:45:03.609074","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":2,"publisher":"U.S. Geological Survey","slug":"ds-777-average-annual-recharge-2000-to-2009-in-inches-estimated-from-the-soil-water-sowat-","spatial_centroid":{"lat":36.4794828,"lon":-102.1007196},"spatial_shape":{"coordinates":[[[-106.019428,31.594384],[-106.019428,43.807131],[-96.222657,43.807131],[-96.222657,31.594384],[-106.019428,31.594384]]],"type":"Polygon"},"theme":["geospatial"],"title":"DS-777 Average Annual Recharge, 2000 to 2009, in inches estimated from the SOil WATer (SOWAT) Balance Model for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming"},{"_score":14.857646,"_sort":[1786319035674,14.857646,6,"f07c05d7-519b-48b4-a4af-6dc7795e2151"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Jennifer S. Stanton","hasEmail":"mailto:jstanton@usgs.gov"},"description":"The water-budget-components geodatabase contains selected data from maps in the,\n\"Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 \nthrough 1949 and 2000 through 2009\" report (Stanton and others, 2011). Data were \ncollected and synthesized from existing climate models including the Parameter-Elevation \nRegressions on Independent Slopes Model (PRISM) (Daly and others, 1994), and the \nSnow accumulation and ablation model (SNOW-17) (Anderson, 2006), and used in \nsoil-water balance models to compute various components of a water budget. The \nmethodologies used to compute the averages and volumes for the data in this \ngeodatabase are slightly different for different components and models.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9UKMDQZ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.d8b44992-7421-4ee5-9da6-6172253cfc7b.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_d8b44992-7421-4ee5-9da6-6172253cfc7b","keyword":["Colorado","Evapotranspiration","Great Plains","High Plains","High Plains aquifer","Kansas","Nebraska","New Mexico","Ogallala aquifer","Oklahoma","Potential evapotranspiration","South Dakota","Texas","USGS:d8b44992-7421-4ee5-9da6-6172253cfc7b","Wyoming","aquifers","central High Plains","environment","geoscientificInformation","ground water","groundwater","inlandWaters","northern High Plains","southern High Plains"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-106.016870, 31.598356, -96.219992, 43.810915","theme":["geospatial"],"title":"DS-777 Average Annual Potential Evapotranspiration, 2000 to 2009, in inches estimated from the National Weather Service (NWS) Snow Accumulation and Ablation (SNOW-17) Model for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming"},"description":"The water-budget-components geodatabase contains selected data from maps in the,\n\"Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 \nthrough 1949 and 2000 through 2009\" report (Stanton and others, 2011). Data were \ncollected and synthesized from existing climate models including the Parameter-Elevation \nRegressions on Independent Slopes Model (PRISM) (Daly and others, 1994), and the \nSnow accumulation and ablation model (SNOW-17) (Anderson, 2006), and used in \nsoil-water balance models to compute various components of a water budget. The \nmethodologies used to compute the averages and volumes for the data in this \ngeodatabase are slightly different for different components and models.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/1f95179e-3982-445d-82d9-2709cd230247","harvest_record_raw":"https://catalog.data.gov/harvest_record/1f95179e-3982-445d-82d9-2709cd230247/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_d8b44992-7421-4ee5-9da6-6172253cfc7b","keyword":["Colorado","Evapotranspiration","Great Plains","High Plains","High Plains aquifer","Kansas","Nebraska","New Mexico","Ogallala aquifer","Oklahoma","Potential evapotranspiration","South Dakota","Texas","USGS:d8b44992-7421-4ee5-9da6-6172253cfc7b","Wyoming","aquifers","central High Plains","environment","geoscientificInformation","ground water","groundwater","inlandWaters","northern High Plains","southern High Plains"],"last_harvested_date":"2026-08-09T23:43:55.674760","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":6,"publisher":"U.S. Geological Survey","slug":"ds-777-average-annual-potential-evapotranspiration-2000-to-2009-in-inches-estimated-from-t","spatial_centroid":{"lat":36.4833796,"lon":-102.0981188},"spatial_shape":{"coordinates":[[[-106.01687,31.598356],[-106.01687,43.810915],[-96.219992,43.810915],[-96.219992,31.598356],[-106.01687,31.598356]]],"type":"Polygon"},"theme":["geospatial"],"title":"DS-777 Average Annual Potential Evapotranspiration, 2000 to 2009, in inches estimated from the National Weather Service (NWS) Snow Accumulation and Ablation (SNOW-17) Model for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming"},{"_score":14.857646,"_sort":[1786318107981,14.857646,2,"35dc6334-671e-49a3-99cf-836c81bd89bf"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"J. LaRue Smith","hasEmail":"mailto:jlsmith@usgs.gov"},"description":"Hydrologic landscape regions group areas according to their similarity in landscape and climate characteristics.  \nThese characteristics represent variables assumed to affect hydrologic processes in the environment.  Hydrologic \nlandscape regions in Nevada were delineated using geographic information system tools and statistical methods \nincluding cluster analysis. The data layers of hydrogeology, precipitation, soil permeability, land surface slope \nand aspect were used to identify the hydrologic landscape regions. Sixteen hydrologic landscape regions were \nidentified through cluster analysis. The hydrologic landscape regions are noncontiguous in nature and can range \nfrom small areas which tend to be in the mountain ranges to very large areas in the basins.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P92HOQMU","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.901db279-906b-489f-a960-85cf610dfc9e.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_901db279-906b-489f-a960-85cf610dfc9e","keyword":["Great Basin","Nevada","USGS:901db279-906b-489f-a960-85cf610dfc9e","environment","geoscientificInformation","hydrogeology","hydrologic landscape regions","inlandWaters","land surface aspect","land surface slope","precipitation","soil permeability"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-120.180324, 34.967066, -113.694509, 42.039355","theme":["geospatial"],"title":"Hydrologic landscape regions of Nevada"},"description":"Hydrologic landscape regions group areas according to their similarity in landscape and climate characteristics.  \nThese characteristics represent variables assumed to affect hydrologic processes in the environment.  Hydrologic \nlandscape regions in Nevada were delineated using geographic information system tools and statistical methods \nincluding cluster analysis. The data layers of hydrogeology, precipitation, soil permeability, land surface slope \nand aspect were used to identify the hydrologic landscape regions. Sixteen hydrologic landscape regions were \nidentified through cluster analysis. The hydrologic landscape regions are noncontiguous in nature and can range \nfrom small areas which tend to be in the mountain ranges to very large areas in the basins.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/f10f001f-c3c6-4dce-b846-209bb9afbfab","harvest_record_raw":"https://catalog.data.gov/harvest_record/f10f001f-c3c6-4dce-b846-209bb9afbfab/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_901db279-906b-489f-a960-85cf610dfc9e","keyword":["Great Basin","Nevada","USGS:901db279-906b-489f-a960-85cf610dfc9e","environment","geoscientificInformation","hydrogeology","hydrologic landscape regions","inlandWaters","land surface aspect","land surface slope","precipitation","soil permeability"],"last_harvested_date":"2026-08-09T23:28:27.981536","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":2,"publisher":"U.S. Geological Survey","slug":"hydrologic-landscape-regions-of-nevada","spatial_centroid":{"lat":37.795981600000005,"lon":-117.58599799999999},"spatial_shape":{"coordinates":[[[-120.180324,34.967066],[-120.180324,42.039355],[-113.694509,42.039355],[-113.694509,34.967066],[-120.180324,34.967066]]],"type":"Polygon"},"theme":["geospatial"],"title":"Hydrologic landscape regions of Nevada"},{"_score":35.357574,"_sort":[1786318030165,35.357574,1,"f9d2b5c2-2aca-4a63-95ec-c9d9e90267e6"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Oklahoma-Texas Water Science Center","hasEmail":"mailto:gs-w-txpublic-info@usgs.gov"},"description":"Estimates of area and aerial extent of land-use categories are an essential component \nfor computing the water budget of the High Plains aquifer. These raster land-use land \nclass data represent yearly simulated future land use for the High Plains from 2009 to \n2050 These data were developed using the FOREcasting SCEnarios (FORE-SCE) of \nfuture land cover model (Sohl and others, 2007; Sohl and Sayler 2008) for two (A2 and \nB2) of the four Intergovernmental Panel on Climate Change (IPCC) climate scenarios \nand then processed using a Geographic Information System (GIS). The GIS software \nused to process these data was Environmental Systems Research Institute (ESRI, Inc.) \nArcGIS Desktop 10.0.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9FEQ22K","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.ce171d76-dfc7-49ea-9375-3e0596ecc68e.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ce171d76-dfc7-49ea-9375-3e0596ecc68e","keyword":["Colorado","Great Plains","High Plains","High Plains aquifer","Kansas","LULC","Nebraska","New Mexico","Ogallala aquifer","Oklahoma","South Dakota","Texas","USGS:ce171d76-dfc7-49ea-9375-3e0596ecc68e","Wyoming","environment","geoscientificInformation","inlandWaters","land cover","land use","landcover","landuse"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-106.016217, 31.598356, -96.227959, 43.806414","theme":["geospatial"],"title":"DS-777 Annual Model-Forecasted Land-Use/Land-Cover Rasters from 2009 to 2050 for the B2 Climate Scenario for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming"},"description":"Estimates of area and aerial extent of land-use categories are an essential component \nfor computing the water budget of the High Plains aquifer. These raster land-use land \nclass data represent yearly simulated future land use for the High Plains from 2009 to \n2050 These data were developed using the FOREcasting SCEnarios (FORE-SCE) of \nfuture land cover model (Sohl and others, 2007; Sohl and Sayler 2008) for two (A2 and \nB2) of the four Intergovernmental Panel on Climate Change (IPCC) climate scenarios \nand then processed using a Geographic Information System (GIS). The GIS software \nused to process these data was Environmental Systems Research Institute (ESRI, Inc.) \nArcGIS Desktop 10.0.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/d93b4a7b-7b46-4b8c-840f-56f4e695c32a","harvest_record_raw":"https://catalog.data.gov/harvest_record/d93b4a7b-7b46-4b8c-840f-56f4e695c32a/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ce171d76-dfc7-49ea-9375-3e0596ecc68e","keyword":["Colorado","Great Plains","High Plains","High Plains aquifer","Kansas","LULC","Nebraska","New Mexico","Ogallala aquifer","Oklahoma","South Dakota","Texas","USGS:ce171d76-dfc7-49ea-9375-3e0596ecc68e","Wyoming","environment","geoscientificInformation","inlandWaters","land cover","land use","landcover","landuse"],"last_harvested_date":"2026-08-09T23:27:10.165406","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":1,"publisher":"U.S. Geological Survey","slug":"ds-777-annual-model-forecasted-land-use-land-cover-rasters-from-2009-to-2050-for-the-b2-cl","spatial_centroid":{"lat":36.4815792,"lon":-102.1009138},"spatial_shape":{"coordinates":[[[-106.016217,31.598356],[-106.016217,43.806414],[-96.227959,43.806414],[-96.227959,31.598356],[-106.016217,31.598356]]],"type":"Polygon"},"theme":["geospatial"],"title":"DS-777 Annual Model-Forecasted Land-Use/Land-Cover Rasters from 2009 to 2050 for the B2 Climate Scenario for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming"},{"_score":17.647568,"_sort":[1786317611747,17.647568,1,"b9eaecc3-857d-495c-ab5f-5a4d22188160"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Randall J. Hunt","hasEmail":"mailto:rjhunt@usgs.gov"},"description":"A GFLOW model was constructed of the Park Falls Unit as part of a larger study of the \nChequamegon-Nicolet National Forest. The model supports the goals of the project by \nproviding improved characterization of the groundwater/surface-water system and a tool \nto evaluate the sensitivity of hydrologic flows and temperature to future climate and land \nuse changes.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/F7RV0KTV","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.f01ef6df-e461-43e1-b9cb-af561c85cfca.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_f01ef6df-e461-43e1-b9cb-af561c85cfca","keyword":["Ashland County","Chequamegon-Nicolet National Forest","GFLOW","Groundwater","Groundwater Model","InlandWaters","Iron County","Oneida County","PEST","Park Falls Unit","Precambrian bedrock","Price County","Soil-Water-Balance Code","USGS:f01ef6df-e461-43e1-b9cb-af561c85cfca","Vilas County","Wisconsin","environment","geoscientificInformation","inlandWaters","usgsgroundwatermodel"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-90.532320, 45.573894, -89.884892, 46.041184","theme":["geospatial"],"title":"GFLOW groundwater flow model for the Park Falls Unit of the Chequamegon-Nicolet National Forest, Wisconsin"},"description":"A GFLOW model was constructed of the Park Falls Unit as part of a larger study of the \nChequamegon-Nicolet National Forest. The model supports the goals of the project by \nproviding improved characterization of the groundwater/surface-water system and a tool \nto evaluate the sensitivity of hydrologic flows and temperature to future climate and land \nuse changes.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/8e754595-9cdd-462f-be4f-d20ffff64871","harvest_record_raw":"https://catalog.data.gov/harvest_record/8e754595-9cdd-462f-be4f-d20ffff64871/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_f01ef6df-e461-43e1-b9cb-af561c85cfca","keyword":["Ashland County","Chequamegon-Nicolet National Forest","GFLOW","Groundwater","Groundwater Model","InlandWaters","Iron County","Oneida County","PEST","Park Falls Unit","Precambrian bedrock","Price County","Soil-Water-Balance Code","USGS:f01ef6df-e461-43e1-b9cb-af561c85cfca","Vilas County","Wisconsin","environment","geoscientificInformation","inlandWaters","usgsgroundwatermodel"],"last_harvested_date":"2026-08-09T23:20:11.747858","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":1,"publisher":"U.S. Geological Survey","slug":"gflow-groundwater-flow-model-for-the-park-falls-unit-of-the-chequamegon-nicolet-national-f","spatial_centroid":{"lat":45.760810000000006,"lon":-90.2733488},"spatial_shape":{"coordinates":[[[-90.53232,45.573894],[-90.53232,46.041184],[-89.884892,46.041184],[-89.884892,45.573894],[-90.53232,45.573894]]],"type":"Polygon"},"theme":["geospatial"],"title":"GFLOW groundwater flow model for the Park Falls Unit of the Chequamegon-Nicolet National Forest, Wisconsin"},{"_score":42.604645,"_sort":[1786316715374,42.604645,0,"67da1920-9cf7-45ae-afa7-0fe84b62dcbb"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Diana Zamora-Reyes","hasEmail":"mailto:dzamora-reyes@usgs.gov"},"description":"This data release includes the revised downscaled climate inputs and hydrologic outputs from the Basin Characterization Model (BCM) version 8 (v8), described in Flint and others (2021a), in a 30 by 30-meter spatial resolution at a monthly time step from water years 1896 to 2025 for the upper Feather River watershed. This data release includes six child items: 1. 30-year summaries, 2. Model Archive, 3. Monthly BCM hydrology variables (1896-2024), 4. Monthly climate variables (1896-2024), 5. Climate inputs and BCM outputs for water year 2025, and 6. Water year summaries (1896-2025). \nVERSION HISTORY:\nVersion 2.0: August 4, 2026; Added water year 2025 data\nRevised: February 27, 2026; Data release corrected to fix error in the original model parameters\nFirst posted: March 25, 2025 at https://doi.org/10.5066/P1QA5FLG (deprecated data release)","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P138MUCW","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.686f08f2d4be020e5c01cbbe.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_686f08f2d4be020e5c01cbbe","keyword":["Atmospheric and Climatic Processes","California","Evaporation","Hydrology","Mathematical Modeling","Modeling","Permeability","Precipitation (atmospheric)","Snow and Ice Cover","Soil Moisture","Streamflow","Surface Water (non-marine)","Transpiration","USGS:686f08f2d4be020e5c01cbbe","United States","Water Budget","Water Cycle","Water Resources","Watershed Management","climatologyMeteorologyAtmosphere","environment","geoscientificInformation","inlandWaters"],"modified":"2026-08-07T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-121.5992, 39.4865, -120.1005, 40.5051","theme":["geospatial"],"title":"Upper Feather River Watershed 30-meter Basin Characterization Model - Monthly Historical Climate and Hydrology (ver. 2.0, August 2026)"},"description":"This data release includes the revised downscaled climate inputs and hydrologic outputs from the Basin Characterization Model (BCM) version 8 (v8), described in Flint and others (2021a), in a 30 by 30-meter spatial resolution at a monthly time step from water years 1896 to 2025 for the upper Feather River watershed. This data release includes six child items: 1. 30-year summaries, 2. Model Archive, 3. Monthly BCM hydrology variables (1896-2024), 4. Monthly climate variables (1896-2024), 5. Climate inputs and BCM outputs for water year 2025, and 6. Water year summaries (1896-2025). \nVERSION HISTORY:\nVersion 2.0: August 4, 2026; Added water year 2025 data\nRevised: February 27, 2026; Data release corrected to fix error in the original model parameters\nFirst posted: March 25, 2025 at https://doi.org/10.5066/P1QA5FLG (deprecated data release)","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/ed050b66-1f5c-4d3a-915b-0025cb4eaa09","harvest_record_raw":"https://catalog.data.gov/harvest_record/ed050b66-1f5c-4d3a-915b-0025cb4eaa09/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_686f08f2d4be020e5c01cbbe","keyword":["Atmospheric and Climatic Processes","California","Evaporation","Hydrology","Mathematical Modeling","Modeling","Permeability","Precipitation (atmospheric)","Snow and Ice Cover","Soil Moisture","Streamflow","Surface Water (non-marine)","Transpiration","USGS:686f08f2d4be020e5c01cbbe","United States","Water Budget","Water Cycle","Water Resources","Watershed Management","climatologyMeteorologyAtmosphere","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-08-09T23:05:15.374490","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"upper-feather-river-watershed-30-meter-basin-characterization-model-monthly-historical-cli","spatial_centroid":{"lat":39.89394,"lon":-120.99972},"spatial_shape":{"coordinates":[[[-121.5992,39.4865],[-121.5992,40.5051],[-120.1005,40.5051],[-120.1005,39.4865],[-121.5992,39.4865]]],"type":"Polygon"},"theme":["geospatial"],"title":"Upper Feather River Watershed 30-meter Basin Characterization Model - Monthly Historical Climate and Hydrology (ver. 2.0, August 2026)"},{"_score":11.89814,"_sort":[1786316317427,11.89814,4,"23fb65b1-2292-45b4-bea7-34516f2cfd4d"],"dcat":{"accessLevel":"public","bureauCode":["010:76"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Indian Affairs Branch of Geospatial Support","hasEmail":"mailto:geospatial@bia.gov"},"description":"<p>Tribal Colleges and Universities (TCUs) are chartered by their respective tribal governments, including the ten tribes within the largest reservations in the United States. The 33 accredited TCUs operate more than 90 campuses and sites in 15 states\u2014covering most of Indian Country\u2014and serve students from well more than 250 federally recognized Indian tribes. TCUs vary in enrollment (size), focus (liberal arts, sciences, workforce development/training), location (woodlands, desert, frozen tundra, rural, urban), and student population (predominantly American Indian). However, tribal identity is the core of every TCU, and they all share the mission of tribal self-determination and service to their respective communities.</p><p>These academically rigorous institutions engage in partnerships with organizations including U.S. Department of the Interior, U.S. Department of Agriculture, U.S. Department of Housing and Urban Development, the National Science Foundation, National Aeronautics and Space Administration, and universities nationwide to support research and education programs that focus on issues such as climate change, sustainable agriculture, water quality, wildlife population dynamics, and diabetes prevention. Many support distance learning involving state-of-the-art learning environments.</p>","distribution":[{"@type":"dcat:Distribution","accessURL":"https://onemap-bia-geospatial.hub.arcgis.com/api/download/v1/items/607ecde42f634f70ac56a61342de0870/csv?layers=0","format":"CSV","mediaType":"text/csv","title":"CSV"},{"@type":"dcat:Distribution","accessURL":"https://onemap-bia-geospatial.hub.arcgis.com/api/download/v1/items/607ecde42f634f70ac56a61342de0870/geojson?layers=0","format":"GeoJSON","mediaType":"application/vnd.geo+json","title":"GeoJSON"},{"@type":"dcat:Distribution","accessURL":"https://onemap-bia-geospatial.hub.arcgis.com/api/download/v1/items/607ecde42f634f70ac56a61342de0870/kml?layers=0","format":"KML","mediaType":"application/vnd.google-earth.kml+xml","title":"KML"},{"@type":"dcat:Distribution","accessURL":"https://onemap-bia-geospatial.hub.arcgis.com/api/download/v1/items/607ecde42f634f70ac56a61342de0870/shapefile?layers=0","format":"ZIP","mediaType":"application/zip","title":"Shapefile"},{"@type":"dcat:Distribution","accessURL":"https://onemap-bia-geospatial.hub.arcgis.com/datasets/BIA-Geospatial::tribal-colleges-and-universities-tcu","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://services1.arcgis.com/UxqqIfhng71wUT9x/arcgis/rest/services/TCU_Colleges/FeatureServer/0","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"},{"@type":"dcat:Distribution","accessURL":"https://services1.arcgis.com/UxqqIfhng71wUT9x/arcgis/rest/services/TCU_Colleges/FeatureServer/0/metadata?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"}],"identifier":"https://www.arcgis.com/home/item.html?id=607ecde42f634f70ac56a61342de0870&sublayer=0","issued":"2023-06-26T19:50:25Z","keyword":["BOGS","Pathways"],"landingPage":"https://onemap-bia-geospatial.hub.arcgis.com/datasets/BIA-Geospatial::tribal-colleges-and-universities-tcu","license":"https://www.idmanagement.gov/license/","modified":"2026-08-07T10:09:09.853Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Indian Affairs"},"spatial":"-158.5303,55.3158,-131.5278,71.2952","theme":["geospatial"],"title":"Tribal Colleges and Universities (TCU)"},"description":"<p>Tribal Colleges and Universities (TCUs) are chartered by their respective tribal governments, including the ten tribes within the largest reservations in the United States. The 33 accredited TCUs operate more than 90 campuses and sites in 15 states\u2014covering most of Indian Country\u2014and serve students from well more than 250 federally recognized Indian tribes. TCUs vary in enrollment (size), focus (liberal arts, sciences, workforce development/training), location (woodlands, desert, frozen tundra, rural, urban), and student population (predominantly American Indian). However, tribal identity is the core of every TCU, and they all share the mission of tribal self-determination and service to their respective communities.</p><p>These academically rigorous institutions engage in partnerships with organizations including U.S. Department of the Interior, U.S. Department of Agriculture, U.S. Department of Housing and Urban Development, the National Science Foundation, National Aeronautics and Space Administration, and universities nationwide to support research and education programs that focus on issues such as climate change, sustainable agriculture, water quality, wildlife population dynamics, and diabetes prevention. Many support distance learning involving state-of-the-art learning environments.</p>","distribution_titles":["CSV","GeoJSON","KML","Shapefile","ArcGIS Hub Dataset","ArcGIS GeoService","ISO-19139 metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/ed6e75d5-683d-47f7-8c42-7b85fb895771","harvest_record_raw":"https://catalog.data.gov/harvest_record/ed6e75d5-683d-47f7-8c42-7b85fb895771/raw","has_download":false,"has_spatial":true,"identifier":"https://www.arcgis.com/home/item.html?id=607ecde42f634f70ac56a61342de0870&sublayer=0","keyword":["BOGS","Pathways"],"last_harvested_date":"2026-08-09T22:58:37.427408","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":4,"publisher":"Bureau of Indian Affairs","slug":"tribal-colleges-and-universities-tcu","spatial_centroid":{"lat":61.70756,"lon":-147.72930000000002},"spatial_shape":{"coordinates":[[[-158.5303,55.3158],[-158.5303,71.2952],[-131.5278,71.2952],[-131.5278,55.3158],[-158.5303,55.3158]]],"type":"Polygon"},"theme":["geospatial"],"title":"Tribal Colleges and Universities (TCU)"},{"_score":12.314944,"_sort":[1786315963964,12.314944,3,"c5c0860e-eada-4094-92be-0d582f10ed06"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Michael E. Wieczorek","hasEmail":"mailto:mewieczo@usgs.gov"},"description":"This tabular data set represents the average daily minimum temperature in Celsius multiplied by 100 for 2002, \ncompiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). \nThe source data were the Near-Real-Time High-Resolution Monthly Average Maximum/Minimum Temperature for \nthe Conterminous United States for 2002 raster data set produced by the Spatial Climate Analysis Service at \nOregon State University.\n\t\t\nThe MRB_E2RF1 catchments are based on a modified version of the Environmental Protection Agency's (USEPA) \nERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling \n(Nolan and others, 2002; Brakebill and others, 2011).\n\t\t\nData were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and \nMid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and \nSouris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), \nthe Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9EKKOEN","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.aaf1493e-d284-4b81-b5b3-a7bca1c13c63.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_aaf1493e-d284-4b81-b5b3-a7bca1c13c63","keyword":["Average monthly minimum temperature","CALI","COGB","California","Catchment","Conterminous United States","GLMR","Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy","Inland waters","LMTG","Lower Mississippi, Arkansas-White-Red, and Texas-Gulf","MORI","MRB","MRB1","MRB2","MRB3","MRB4","MRB5","MRB6","MRB7","MRB8","MRB_E2RF1","MRB_E2RF1WS","Major River Basins","Missouri","NAWQA","NEMA","New England and Mid-Atlantic","PANW","Pacific Northwest","Rio Grande, Colorado, and Great Basin","SAGT","SPARROW","South Atlantic-Gulf and Tennessee","USGS:aaf1493e-d284-4b81-b5b3-a7bca1c13c63","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-127.910792, 23.243486, -65.327751, 51.657387","theme":["geospatial"],"title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Average Daily Minimum Temperature, 2002"},"description":"This tabular data set represents the average daily minimum temperature in Celsius multiplied by 100 for 2002, \ncompiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). \nThe source data were the Near-Real-Time High-Resolution Monthly Average Maximum/Minimum Temperature for \nthe Conterminous United States for 2002 raster data set produced by the Spatial Climate Analysis Service at \nOregon State University.\n\t\t\nThe MRB_E2RF1 catchments are based on a modified version of the Environmental Protection Agency's (USEPA) \nERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling \n(Nolan and others, 2002; Brakebill and others, 2011).\n\t\t\nData were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and \nMid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and \nSouris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), \nthe Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/aa5a68d1-ddd3-4569-9d37-39a238426b9e","harvest_record_raw":"https://catalog.data.gov/harvest_record/aa5a68d1-ddd3-4569-9d37-39a238426b9e/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_aaf1493e-d284-4b81-b5b3-a7bca1c13c63","keyword":["Average monthly minimum temperature","CALI","COGB","California","Catchment","Conterminous United States","GLMR","Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy","Inland waters","LMTG","Lower Mississippi, Arkansas-White-Red, and Texas-Gulf","MORI","MRB","MRB1","MRB2","MRB3","MRB4","MRB5","MRB6","MRB7","MRB8","MRB_E2RF1","MRB_E2RF1WS","Major River Basins","Missouri","NAWQA","NEMA","New England and Mid-Atlantic","PANW","Pacific Northwest","Rio Grande, Colorado, and Great Basin","SAGT","SPARROW","South Atlantic-Gulf and Tennessee","USGS:aaf1493e-d284-4b81-b5b3-a7bca1c13c63","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-08-09T22:52:43.964829","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":3,"publisher":"U.S. Geological Survey","slug":"attributes-for-mrb_e2rf1-catchments-by-major-river-basins-in-the-conterminous-united--2002","spatial_centroid":{"lat":34.6090464,"lon":-102.8775756},"spatial_shape":{"coordinates":[[[-127.910792,23.243486],[-127.910792,51.657387],[-65.327751,51.657387],[-65.327751,23.243486],[-127.910792,23.243486]]],"type":"Polygon"},"theme":["geospatial"],"title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Average Daily Minimum Temperature, 2002"},{"_score":11.995712,"_sort":[1786315505291,11.995712,4,"d17743ff-0310-40cb-87e2-831dda5dbf61"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Fred D Tillman","hasEmail":"mailto:ftillman@usgs.gov"},"description":"The Colorado River and its tributaries supply water to more than 35 million people in the United States \nand 3 million people in Mexico, irrigating more than 4.5 million acres of farmland, and generating about \n12 billion kilowatt hours of hydroelectric power annually. Planning for the sustainable management of \nthe Colorado River in future climates requires an understanding of the Upper Colorado River Basin \ngroundwater system. The Upper Colorado River Basin, encompassing more than 110,000 square \nmiles (mi2), contains the headwaters of the Colorado River and is an important source of snowmelt \nrunoff to the River. Groundwater discharge also is an important source of water in the River and its \ntributaries, with estimates ranging from 21 to 58 percent of streamflow in the upper basin.\n\t\t\t\nA study by Castle and others (2014) using remotely sensed gravity observations from the NASA \nGravity Recovery and Climate Experiment (GRACE) mission found that UCRB groundwater was \ndepleted by more than 17 million acre-feet (ft) from December 2004 to November 2013. Understanding \ngroundwater-budget components, including groundwater recharge, is important to sustainably \nmanage both groundwater and surface-water supplies in the Colorado River Basin.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9ZFQFJD","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.850b5cf3-7b38-4a2e-bb0a-4b91f6b6332f.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_850b5cf3-7b38-4a2e-bb0a-4b91f6b6332f","keyword":["Arizona","California","Colorado","DCHP","Daymet","Nevada","New Mexico","USGS:850b5cf3-7b38-4a2e-bb0a-4b91f6b6332f","Upper Colorado River Basin","Utah","Wyoming","environment","geoscientificInformation","groundwater","groundwater recharge","inlandWaters","soil-water balance"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-113.920363928, 34.965779618, -105.25, 43.986766736","theme":["geospatial"],"title":"Input Digital Datasets for the Soil-Water Balance Groundwater Recharge Model of the Upper Colorado River Basin"},"description":"The Colorado River and its tributaries supply water to more than 35 million people in the United States \nand 3 million people in Mexico, irrigating more than 4.5 million acres of farmland, and generating about \n12 billion kilowatt hours of hydroelectric power annually. Planning for the sustainable management of \nthe Colorado River in future climates requires an understanding of the Upper Colorado River Basin \ngroundwater system. The Upper Colorado River Basin, encompassing more than 110,000 square \nmiles (mi2), contains the headwaters of the Colorado River and is an important source of snowmelt \nrunoff to the River. Groundwater discharge also is an important source of water in the River and its \ntributaries, with estimates ranging from 21 to 58 percent of streamflow in the upper basin.\n\t\t\t\nA study by Castle and others (2014) using remotely sensed gravity observations from the NASA \nGravity Recovery and Climate Experiment (GRACE) mission found that UCRB groundwater was \ndepleted by more than 17 million acre-feet (ft) from December 2004 to November 2013. Understanding \ngroundwater-budget components, including groundwater recharge, is important to sustainably \nmanage both groundwater and surface-water supplies in the Colorado River Basin.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/0282d8b7-6d97-4f8c-8231-28a6b32033b3","harvest_record_raw":"https://catalog.data.gov/harvest_record/0282d8b7-6d97-4f8c-8231-28a6b32033b3/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_850b5cf3-7b38-4a2e-bb0a-4b91f6b6332f","keyword":["Arizona","California","Colorado","DCHP","Daymet","Nevada","New Mexico","USGS:850b5cf3-7b38-4a2e-bb0a-4b91f6b6332f","Upper Colorado River Basin","Utah","Wyoming","environment","geoscientificInformation","groundwater","groundwater recharge","inlandWaters","soil-water balance"],"last_harvested_date":"2026-08-09T22:45:05.291691","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":4,"publisher":"U.S. Geological Survey","slug":"input-digital-datasets-for-the-soil-water-balance-groundwater-recharge-model-of-the-upper-","spatial_centroid":{"lat":38.574174465199995,"lon":-110.45221835679999},"spatial_shape":{"coordinates":[[[-113.920363928,34.965779618],[-113.920363928,43.986766736],[-105.25,43.986766736],[-105.25,34.965779618],[-113.920363928,34.965779618]]],"type":"Polygon"},"theme":["geospatial"],"title":"Input Digital Datasets for the Soil-Water Balance Groundwater Recharge Model of the Upper Colorado River Basin"},{"_score":24.519958,"_sort":[1786315471060,24.519958,3,"ce120dc2-fe52-439c-b58d-ed71cb442150"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Fred D Tillman","hasEmail":"mailto:ftillman@usgs.gov"},"description":"overland_flow_direction_UCRB_Maurer_resolution.asc is an Esri ASCII grid representing overland \nflow direction in the Upper Colorado River Basin using the D8 flow-routing convention.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9DW3W86","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.f4f235c4-7666-4ba3-bd7d-0b9b56ae1fda.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_f4f235c4-7666-4ba3-bd7d-0b9b56ae1fda","keyword":["Arizona","California","Colorado","Nevada","New Mexico","USGS:f4f235c4-7666-4ba3-bd7d-0b9b56ae1fda","Upper Colorado River Basin","Utah","Wyoming","environment","geoscientificInformation","groundwater","groundwater recharge","inlandWaters","overland flow direction"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-112.625, 35.125, -105.25, 43.75","theme":["geospatial"],"title":"Overland Flow Direction Information for the Upper Colorado River Basin in Maurer et al. (2002) Climate Data resolution (overland_flow_direction_UCRB_Maurer_resolution.asc)"},"description":"overland_flow_direction_UCRB_Maurer_resolution.asc is an Esri ASCII grid representing overland \nflow direction in the Upper Colorado River Basin using the D8 flow-routing convention.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/c805e514-cfcb-467f-9a31-475ce6050444","harvest_record_raw":"https://catalog.data.gov/harvest_record/c805e514-cfcb-467f-9a31-475ce6050444/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_f4f235c4-7666-4ba3-bd7d-0b9b56ae1fda","keyword":["Arizona","California","Colorado","Nevada","New Mexico","USGS:f4f235c4-7666-4ba3-bd7d-0b9b56ae1fda","Upper Colorado River Basin","Utah","Wyoming","environment","geoscientificInformation","groundwater","groundwater recharge","inlandWaters","overland flow direction"],"last_harvested_date":"2026-08-09T22:44:31.060666","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":3,"publisher":"U.S. Geological Survey","slug":"overland-flow-direction-information-for-the-upper-colorado-river-basin-in-maurer-et-al-200","spatial_centroid":{"lat":38.575,"lon":-109.675},"spatial_shape":{"coordinates":[[[-112.625,35.125],[-112.625,43.75],[-105.25,43.75],[-105.25,35.125],[-112.625,35.125]]],"type":"Polygon"},"theme":["geospatial"],"title":"Overland Flow Direction Information for the Upper Colorado River Basin in Maurer et al. (2002) Climate Data resolution (overland_flow_direction_UCRB_Maurer_resolution.asc)"},{"_score":15.274948,"_sort":[1786315395734,15.274948,1,"dd7e3233-6c6b-4728-ac90-38cd1dcd82fa"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Water Mission Area","hasEmail":"mailto:GS-W-model-data@usgs.gov"},"description":"This is a polygon coverage of the Land Resource Regions and Major Land\nResource Areas of the conterminous United States.  Land resource regions\nare geographic areas that are characterized by a particular pattern of\nsoils, climate, water resources and land uses. (USDA, Soil Conservation\nService, 1981).  Major land resource areas are subregions of the\nland resource regions and comprise smaller homogeneous areas. The\nscale of this coverage is 1:2,000,000.\n\t\t\nNote:  The Soil Conservation Service now (1995) is called the Natural\nResources Conservation Service.\n\t\t\nDescriptors:\n\t\t\nLand Resource Regions\nMajor Land Resource Areas\nUnited States","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9C2I3VQ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.9b1592e8-a33b-4ec4-8e54-33a4bf74c17c.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_9b1592e8-a33b-4ec4-8e54-33a4bf74c17c","keyword":["Land Resource Regions","Major Land Resource Areas","USGS:9b1592e8-a33b-4ec4-8e54-33a4bf74c17c","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-128.07002717, 22.67774911, -65.25698378, 48.26194027","theme":["geospatial"],"title":"Major Land Resource Areas (MLRA)"},"description":"This is a polygon coverage of the Land Resource Regions and Major Land\nResource Areas of the conterminous United States.  Land resource regions\nare geographic areas that are characterized by a particular pattern of\nsoils, climate, water resources and land uses. (USDA, Soil Conservation\nService, 1981).  Major land resource areas are subregions of the\nland resource regions and comprise smaller homogeneous areas. The\nscale of this coverage is 1:2,000,000.\n\t\t\nNote:  The Soil Conservation Service now (1995) is called the Natural\nResources Conservation Service.\n\t\t\nDescriptors:\n\t\t\nLand Resource Regions\nMajor Land Resource Areas\nUnited States","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/abadc57f-1134-421d-873c-9d79a96c819d","harvest_record_raw":"https://catalog.data.gov/harvest_record/abadc57f-1134-421d-873c-9d79a96c819d/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_9b1592e8-a33b-4ec4-8e54-33a4bf74c17c","keyword":["Land Resource Regions","Major Land Resource Areas","USGS:9b1592e8-a33b-4ec4-8e54-33a4bf74c17c","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-08-09T22:43:15.734226","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":1,"publisher":"U.S. Geological Survey","slug":"major-land-resource-areas-mlra-2f668","spatial_centroid":{"lat":32.911425574,"lon":-102.944809814},"spatial_shape":{"coordinates":[[[-128.07002717,22.67774911],[-128.07002717,48.26194027],[-65.25698378,48.26194027],[-65.25698378,22.67774911],[-128.07002717,22.67774911]]],"type":"Polygon"},"theme":["geospatial"],"title":"Major Land Resource Areas (MLRA)"},{"_score":6.348119,"_sort":[1786234050467,6.348119,6,"f9fdc2d3-1f78-4197-bdb8-9895248bb19b"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"David M. Mushet","hasEmail":"mailto:dmushet@usgs.gov"},"description":"TNote: this data release has been superseded by version 2.0, available here: https://doi.org/10.5066/P94LIJU5\nThis dataset contains the number of breeding pairs of bird species surveyed in all Cottonwood Lake Study Area wetlands.","distribution":[{"@type":"dcat:Distribution","accessURL":"http://dx.doi.org/10.5066/F77W69D4","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.587e57e7e4b0a765aab5eb81.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_587e57e7e4b0a765aab5eb81","keyword":["Aquatic birds","Biota","Birds","Birds of prey","Breeding","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Cottonwood Lake Study Area","Effects of climate change","Game birds","Game species","Land use change","North Dakota","Northern Great Plains","Prairie Pothole Region","Songbirds","Stutsman County","USGS:587e57e7e4b0a765aab5eb81","United States of America","Wading birds","Waterfowl","Wetland functions","Wildlife"],"modified":"2026-08-06T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-99.10625, 47.09547, -99.09115, 47.10265","theme":["geospatial"],"title":"Cottonwood Lake Study Area - Breeding Birds"},"description":"TNote: this data release has been superseded by version 2.0, available here: https://doi.org/10.5066/P94LIJU5\nThis dataset contains the number of breeding pairs of bird species surveyed in all Cottonwood Lake Study Area wetlands.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/94644ccd-230c-4b77-9938-b63694478ba3","harvest_record_raw":"https://catalog.data.gov/harvest_record/94644ccd-230c-4b77-9938-b63694478ba3/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_587e57e7e4b0a765aab5eb81","keyword":["Aquatic birds","Biota","Birds","Birds of prey","Breeding","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Cottonwood Lake Study Area","Effects of climate change","Game birds","Game species","Land use change","North Dakota","Northern Great Plains","Prairie Pothole Region","Songbirds","Stutsman County","USGS:587e57e7e4b0a765aab5eb81","United States of America","Wading birds","Waterfowl","Wetland functions","Wildlife"],"last_harvested_date":"2026-08-09T00:07:30.467157","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":6,"publisher":"U.S. Geological Survey","slug":"cottonwood-lake-study-area-breeding-birds-95c74","spatial_centroid":{"lat":47.098341999999995,"lon":-99.10021},"spatial_shape":{"coordinates":[[[-99.10625,47.09547],[-99.10625,47.10265],[-99.09115,47.10265],[-99.09115,47.09547],[-99.10625,47.09547]]],"type":"Polygon"},"theme":["geospatial"],"title":"Cottonwood Lake Study Area - Breeding Birds"},{"_score":6.209199,"_sort":[1786233565176,6.209199,0,"562e5974-2173-4464-be84-b7c67a533ad4"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"David M. Mushet","hasEmail":"mailto:dmushet@usgs.gov"},"description":"This dataset contains discrete groundwater elevation measurements for wells in the Cottonwood Lake Study Area, Stutsman County, North Dakota.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9YKWWSZ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.624c75fad34e21f82764df1e.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_624c75fad34e21f82764df1e","keyword":["CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Climatic change","Cottonwood Lake Study Area","Effects of climate change","Ground water","Groundwater level","Hydrology","Inland Waters","North Dakota","Northern Great Plains","Prairie Pothole Region","Stutsman County","USGS:624c75fad34e21f82764df1e","United States of America","Water sampling","Wells","Wetland ecosystems","Wetland functions","Wetlands","geoscientificInformation","inlandWaters"],"modified":"2026-08-06T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-99.10625, 47.09547, -99.09115, 47.10265","theme":["geospatial"],"title":"Cottonwood Lake Study Area - Groundwater Elevations (ver. 2.0, April 2022)"},"description":"This dataset contains discrete groundwater elevation measurements for wells in the Cottonwood Lake Study Area, Stutsman County, North Dakota.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/b769efb5-9b34-465a-bf5e-9aa69f564f78","harvest_record_raw":"https://catalog.data.gov/harvest_record/b769efb5-9b34-465a-bf5e-9aa69f564f78/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_624c75fad34e21f82764df1e","keyword":["CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Climatic change","Cottonwood Lake Study Area","Effects of climate change","Ground water","Groundwater level","Hydrology","Inland Waters","North Dakota","Northern Great Plains","Prairie Pothole Region","Stutsman County","USGS:624c75fad34e21f82764df1e","United States of America","Water sampling","Wells","Wetland ecosystems","Wetland functions","Wetlands","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-08-08T23:59:25.176903","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"cottonwood-lake-study-area-groundwater-elevations-ver-2-0","spatial_centroid":{"lat":47.098341999999995,"lon":-99.10021},"spatial_shape":{"coordinates":[[[-99.10625,47.09547],[-99.10625,47.10265],[-99.09115,47.10265],[-99.09115,47.09547],[-99.10625,47.09547]]],"type":"Polygon"},"theme":["geospatial"],"title":"Cottonwood Lake Study Area - Groundwater Elevations (ver. 2.0, April 2022)"},{"_score":6.032176,"_sort":[1786233315870,6.032176,2,"3821eca1-37c0-4661-bc7f-1859ba0baf61"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"David M. Mushet","hasEmail":"mailto:dmushet@usgs.gov"},"description":"Note: this data release has been superseded by version 2.0, available here: https://doi.org/10.5066/P9GTOFCW\nThis dataset contains the specific conductance values for all wetlands in the Cottonwood Lake Study Area, Stutsman County, North Dakota.","distribution":[{"@type":"dcat:Distribution","accessURL":"http://dx.doi.org/10.5066/F7BP00XQ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.579bcae8e4b0589fa1c982d8.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_579bcae8e4b0589fa1c982d8","keyword":["CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Climatic change","Cottonwood Lake Study Area","Effects of climate change","Hydrodynamics","Hydrology","Land use","Land use change","North Dakota","Northern Great Plains","Prairie Pothole Region","Stutsman County","USGS:579bcae8e4b0589fa1c982d8","United States of America","Water properties","Water resources","Water sampling","Wetland agriculture","Wetland functions","Wetlands","inlandWaters"],"modified":"2026-08-06T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-99.10625, 47.09547, -99.09115, 47.10265","theme":["geospatial"],"title":"Cottonwood Lake Study Area - Specific Conductance"},"description":"Note: this data release has been superseded by version 2.0, available here: https://doi.org/10.5066/P9GTOFCW\nThis dataset contains the specific conductance values for all wetlands in the Cottonwood Lake Study Area, Stutsman County, North Dakota.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/57ff2570-609e-4827-a0de-e494d8514c4a","harvest_record_raw":"https://catalog.data.gov/harvest_record/57ff2570-609e-4827-a0de-e494d8514c4a/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_579bcae8e4b0589fa1c982d8","keyword":["CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Climatic change","Cottonwood Lake Study Area","Effects of climate change","Hydrodynamics","Hydrology","Land use","Land use change","North Dakota","Northern Great Plains","Prairie Pothole Region","Stutsman County","USGS:579bcae8e4b0589fa1c982d8","United States of America","Water properties","Water resources","Water sampling","Wetland agriculture","Wetland functions","Wetlands","inlandWaters"],"last_harvested_date":"2026-08-08T23:55:15.870693","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":2,"publisher":"U.S. Geological Survey","slug":"cottonwood-lake-study-area-specific-conductance","spatial_centroid":{"lat":47.098341999999995,"lon":-99.10021},"spatial_shape":{"coordinates":[[[-99.10625,47.09547],[-99.10625,47.10265],[-99.09115,47.10265],[-99.09115,47.09547],[-99.10625,47.09547]]],"type":"Polygon"},"theme":["geospatial"],"title":"Cottonwood Lake Study Area - Specific Conductance"},{"_score":6.032176,"_sort":[1786232532714,6.032176,2,"1c0264d2-924f-4919-9d8a-436dd911e897"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"David M. Mushet","hasEmail":"mailto:dmushet@usgs.gov"},"description":"Note: this data release has been superseded by version 2.0, available here: https://doi.org/10.5066/P9YKWWSZ\nThis dataset contains discrete groundwater elevation measurements for wells in the Cottonwood Lake Study Area, Stutsman County, North Dakota.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9IX7A27","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.5ade04e0e4b0e2c2dd2b7e4a.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5ade04e0e4b0e2c2dd2b7e4a","keyword":["CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Climatic change","Cottonwood Lake Study Area","Effects of climate change","Ground water","Groundwater level","Hydrology","Land use change","North Dakota","Northern Great Plains","Prairie Pothole Region","Stutsman County","USGS:5ade04e0e4b0e2c2dd2b7e4a","United States of America","Water sampling","Wells","Wetland ecosystems","Wetland functions","Wetlands","geoscientificInformation","inlandWaters"],"modified":"2026-08-06T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-99.10625, 47.09547, -99.09115, 47.10265","theme":["geospatial"],"title":"Cottonwood Lake Study Area - Groundwater Elevations"},"description":"Note: this data release has been superseded by version 2.0, available here: https://doi.org/10.5066/P9YKWWSZ\nThis dataset contains discrete groundwater elevation measurements for wells in the Cottonwood Lake Study Area, Stutsman County, North Dakota.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/5e5c15eb-1878-4a76-879b-ff4bd28d22fd","harvest_record_raw":"https://catalog.data.gov/harvest_record/5e5c15eb-1878-4a76-879b-ff4bd28d22fd/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5ade04e0e4b0e2c2dd2b7e4a","keyword":["CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Climatic change","Cottonwood Lake Study Area","Effects of climate change","Ground water","Groundwater level","Hydrology","Land use change","North Dakota","Northern Great Plains","Prairie Pothole Region","Stutsman County","USGS:5ade04e0e4b0e2c2dd2b7e4a","United States of America","Water sampling","Wells","Wetland ecosystems","Wetland functions","Wetlands","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-08-08T23:42:12.714882","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":2,"publisher":"U.S. Geological Survey","slug":"cottonwood-lake-study-area-groundwater-elevations","spatial_centroid":{"lat":47.098341999999995,"lon":-99.10021},"spatial_shape":{"coordinates":[[[-99.10625,47.09547],[-99.10625,47.10265],[-99.09115,47.10265],[-99.09115,47.09547],[-99.10625,47.09547]]],"type":"Polygon"},"theme":["geospatial"],"title":"Cottonwood Lake Study Area - Groundwater Elevations"},{"_score":6.2307873,"_sort":[1786232288274,6.2307873,1,"b050a839-fe18-466b-a65c-d929158ea415"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"David M. Mushet","hasEmail":"mailto:dmushet@usgs.gov"},"description":"This dataset contains the specific conductance values of water for all wetlands in the Cottonwood Lake Study Area, Stutsman County, North Dakota.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9GTOFCW","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.624c73b1d34e21f82764df06.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_624c73b1d34e21f82764df06","keyword":["CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Climatic change","Cottonwood Lake Study Area","Effects of climate change","Hydrodynamics","Hydrology","Land use","Land use change","Northern Great Plains","Prairie Pothole Region","State of North Dakota","Stutsman County","USGS:624c73b1d34e21f82764df06","Water properties","Water resources","Water sampling","Wetland agriculture","Wetland functions","Wetlands","inlandWaters"],"modified":"2026-08-06T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-99.10625, 47.09547, -99.09115, 47.10265","theme":["geospatial"],"title":"Cottonwood Lake Study Area - Specific Conductance (ver. 2.0, April 2022)"},"description":"This dataset contains the specific conductance values of water for all wetlands in the Cottonwood Lake Study Area, Stutsman County, North Dakota.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/07c00220-f8f5-460a-9900-dcb3c392b563","harvest_record_raw":"https://catalog.data.gov/harvest_record/07c00220-f8f5-460a-9900-dcb3c392b563/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_624c73b1d34e21f82764df06","keyword":["CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Climatic change","Cottonwood Lake Study Area","Effects of climate change","Hydrodynamics","Hydrology","Land use","Land use change","Northern Great Plains","Prairie Pothole Region","State of North Dakota","Stutsman County","USGS:624c73b1d34e21f82764df06","Water properties","Water resources","Water sampling","Wetland agriculture","Wetland functions","Wetlands","inlandWaters"],"last_harvested_date":"2026-08-08T23:38:08.274967","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":1,"publisher":"U.S. Geological Survey","slug":"cottonwood-lake-study-area-specific-conductance-ver-2-0","spatial_centroid":{"lat":47.098341999999995,"lon":-99.10021},"spatial_shape":{"coordinates":[[[-99.10625,47.09547],[-99.10625,47.10265],[-99.09115,47.10265],[-99.09115,47.09547],[-99.10625,47.09547]]],"type":"Polygon"},"theme":["geospatial"],"title":"Cottonwood Lake Study Area - Specific Conductance (ver. 2.0, April 2022)"},{"_score":6.423381,"_sort":[1786231959788,6.423381,1,"f72fcf05-e77c-4810-9c6b-5e8be0840f93"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"David M. Mushet","hasEmail":"mailto:dmushet@usgs.gov"},"description":"This dataset contains the number of breeding pairs of bird species surveyed in all Cottonwood Lake Study Area wetlands.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P94LIJU5","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.624c74e6d34e21f82764df0e.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_624c74e6d34e21f82764df0e","keyword":["Aquatic birds","Biota","Birds","Birds of prey","Breeding","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Cottonwood Lake Study Area","Effects of climate change","Game birds","Game species","Inland Waters","North Dakota","Northern Great Plains","Prairie Pothole Region","Songbirds","Stutsman County","USGS:624c74e6d34e21f82764df0e","United States of America","Wading birds","Waterfowl","Wetland functions","Wildlife"],"modified":"2026-08-06T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-99.10625, 47.09547, -99.09115, 47.10265","theme":["geospatial"],"title":"Cottonwood Lake Study Area - Breeding Birds (ver. 2.0, April 2022)"},"description":"This dataset contains the number of breeding pairs of bird species surveyed in all Cottonwood Lake Study Area wetlands.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/22bb2295-e743-4b8d-9b24-909ad6c56797","harvest_record_raw":"https://catalog.data.gov/harvest_record/22bb2295-e743-4b8d-9b24-909ad6c56797/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_624c74e6d34e21f82764df0e","keyword":["Aquatic birds","Biota","Birds","Birds of prey","Breeding","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Eddy","CHASE LAKE WETLAND MANAGEMENT DISTRICT&gt;STUTSMAN COUNTY WATERFOWL PRODUCTION AREA&gt;Shuler","Cottonwood Lake Study Area","Effects of climate change","Game birds","Game species","Inland Waters","North Dakota","Northern Great Plains","Prairie Pothole Region","Songbirds","Stutsman County","USGS:624c74e6d34e21f82764df0e","United States of America","Wading birds","Waterfowl","Wetland functions","Wildlife"],"last_harvested_date":"2026-08-08T23:32:39.788240","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":1,"publisher":"U.S. Geological Survey","slug":"cottonwood-lake-study-area-breeding-birds","spatial_centroid":{"lat":47.098341999999995,"lon":-99.10021},"spatial_shape":{"coordinates":[[[-99.10625,47.09547],[-99.10625,47.10265],[-99.09115,47.10265],[-99.09115,47.09547],[-99.10625,47.09547]]],"type":"Polygon"},"theme":["geospatial"],"title":"Cottonwood Lake Study Area - Breeding Birds (ver. 2.0, April 2022)"},{"_score":10.949829,"_sort":[1786146481227,10.949829,0,"9629f28f-83e2-4500-9b09-3f9e8c5a4fa5"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Jessika McFarland","hasEmail":"mailto:jessika.mcfarland@berkeley.edu"},"description":"Extreme fire spread events rapidly burn large areas with disproportionate impacts on people and ecosystems. Such events are associated with warmer and drier fire seasons and are expected to increase in the future. Our understanding of the landscape outcomes of extreme events is limited, particularly whether or not they burn more severely or produce spatial patterns less conducive to ecosystem recovery. To assess relationships between fire spread rates and landscape burn severity patterns, we used satellite fire detections to create day-of-burning (DOB) maps for 623 fires comprising 4,267 single-day events within forested ecoregions of the southwestern United States. We related satellite-measured burn severity and a suite of high-severity patch metrics to the daily area burned.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5061/dryad.9kd51c5sr","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.CASC-9kd51c5sr.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_CASC-9kd51c5sr","keyword":["Burn Severity","Climate","USGS:CASC-9kd51c5sr","Wildfire","environment"],"modified":"2026-08-05T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-124.4800, 31.2700, -102.0000, 42.0000","theme":["geospatial"],"title":"Day of burning maps and burn severity landscape metrics in the southwestern United States 2002-2020"},"description":"Extreme fire spread events rapidly burn large areas with disproportionate impacts on people and ecosystems. Such events are associated with warmer and drier fire seasons and are expected to increase in the future. Our understanding of the landscape outcomes of extreme events is limited, particularly whether or not they burn more severely or produce spatial patterns less conducive to ecosystem recovery. To assess relationships between fire spread rates and landscape burn severity patterns, we used satellite fire detections to create day-of-burning (DOB) maps for 623 fires comprising 4,267 single-day events within forested ecoregions of the southwestern United States. We related satellite-measured burn severity and a suite of high-severity patch metrics to the daily area burned.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/7e4437b9-6026-4bce-b931-b790a1886086","harvest_record_raw":"https://catalog.data.gov/harvest_record/7e4437b9-6026-4bce-b931-b790a1886086/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_CASC-9kd51c5sr","keyword":["Burn Severity","Climate","USGS:CASC-9kd51c5sr","Wildfire","environment"],"last_harvested_date":"2026-08-07T23:48:01.227632","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"day-of-burning-maps-and-burn-severity-landscape-metrics-in-the-southwestern-unit-2002-2020","spatial_centroid":{"lat":35.562,"lon":-115.48800000000001},"spatial_shape":{"coordinates":[[[-124.48,31.27],[-124.48,42.0],[-102.0,42.0],[-102.0,31.27],[-124.48,31.27]]],"type":"Polygon"},"theme":["geospatial"],"title":"Day of burning maps and burn severity landscape metrics in the southwestern United States 2002-2020"},{"_score":30.15336,"_sort":[1786142628810,30.15336,0,"48faf3f1-8fb4-488a-9eb5-fd3149cfeaf5"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Emilie Henderson","hasEmail":"mailto:emilie.henderson@oregonstate.edu"},"description":"Collection of model inputs and outputs examining different combinations of management and climate scenarios run in southwestern Oregon. The objectives of this project are to explore how climate and land management might interact to shape future vegetation and wildlife habitat, and determine what management actions will likely maximize habitats for key species. Climate scenarios include HadGEM global circulation model, representative concentration pathway 8.5 (Hadley), NorESM global circulation model, representative concentration pathway 8.5 (NorESM); MRI global circulation model, representative concentration pathway 8.5 (MRI).\n","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P13M8XUP","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.4c8882da-76b8-4ee9-a697-f9d3062d20da.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_4c8882da-76b8-4ee9-a697-f9d3062d20da","keyword":["Pacific Northwest","Southwest Oregon","USGS:4c8882da-76b8-4ee9-a697-f9d3062d20da","biota","climate change","environment","external research support","geospatial datasets","habitats","land management","modeling","state and transition modeling","vegetation change","vulnerability assessment","wildlife habitat"],"modified":"2026-08-05T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-125.1537, 41.4077, -121.3906, 44.0356","theme":["geospatial"],"title":"Future Spotted Owl Habitat Scenarios, Southwest Oregon Study Area, 2007-2096"},"description":"Collection of model inputs and outputs examining different combinations of management and climate scenarios run in southwestern Oregon. The objectives of this project are to explore how climate and land management might interact to shape future vegetation and wildlife habitat, and determine what management actions will likely maximize habitats for key species. Climate scenarios include HadGEM global circulation model, representative concentration pathway 8.5 (Hadley), NorESM global circulation model, representative concentration pathway 8.5 (NorESM); MRI global circulation model, representative concentration pathway 8.5 (MRI).\n","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/18eca055-195a-4560-9fc7-442cf1679f57","harvest_record_raw":"https://catalog.data.gov/harvest_record/18eca055-195a-4560-9fc7-442cf1679f57/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_4c8882da-76b8-4ee9-a697-f9d3062d20da","keyword":["Pacific Northwest","Southwest Oregon","USGS:4c8882da-76b8-4ee9-a697-f9d3062d20da","biota","climate change","environment","external research support","geospatial datasets","habitats","land management","modeling","state and transition modeling","vegetation change","vulnerability assessment","wildlife habitat"],"last_harvested_date":"2026-08-07T22:43:48.810448","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"future-spotted-owl-habitat-scenarios-southwest-oregon-study-area-2007-2096","spatial_centroid":{"lat":42.45886,"lon":-123.64846},"spatial_shape":{"coordinates":[[[-125.1537,41.4077],[-125.1537,44.0356],[-121.3906,44.0356],[-121.3906,41.4077],[-125.1537,41.4077]]],"type":"Polygon"},"theme":["geospatial"],"title":"Future Spotted Owl Habitat Scenarios, Southwest Oregon Study Area, 2007-2096"},{"_score":15.78957,"_sort":[1786141650368,15.78957,6,"3e9816f7-7eb8-455e-8ff5-81a80c9e1763"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accessRights":"public","bureauCode":["014:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Harwood, Jennifer","hasEmail":"mailto:HarwoodJA@state.gov"},"description":"Based on the survey results of OECD's PISA 2000 programme, this report looks at: the extent to which the schools that students attend make a difference in performance; the relative impact of school climate, school policies and school resources on quality and equity; the relationship between the structure of education systems and educational quality and equity; and the effect of decentralisation and privatisation to school performance.  It concludes with a summary of how school factors relate to quality and equity, and the implications for policy.  The analysis and data cover almost all OECD countries and 14 additional non-OECD countries.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://www.oecd-ilibrary.org/school-factors-related-to-quality-and-equity_5lh201g0qczx.pdf?itemId=%2Fcontent%2Fpublication%2F9789264008199-en&mimeType=pdf","format":"pdf"},{"@type":"dcat:Distribution","downloadURL":"https://www.oecd-ilibrary.org/school-factors-related-to-quality-and-equity_5lh201g0qczx.pdf?itemId=%2Fcontent%2Fpublication%2F9789264008199-en&mimeType=pdf","mediaType":"application/pdf"}],"identifier":"014D000422","keyword":["unspecified"],"modified":"2005-04-14","programCode":["014:000"],"publisher":{"@type":"org:Organization","name":"U.S. Department of State"},"temporal":"[{'@type': 'PeriodOfTime', 'endDate': '2005-12-31', 'startDate': '2004-01-01'}]","title":"School Factors Related to Quality and Equity Results from PISA 2000"},"description":"Based on the survey results of OECD's PISA 2000 programme, this report looks at: the extent to which the schools that students attend make a difference in performance; the relative impact of school climate, school policies and school resources on quality and equity; the relationship between the structure of education systems and educational quality and equity; and the effect of decentralisation and privatisation to school performance.  It concludes with a summary of how school factors relate to quality and equity, and the implications for policy.  The analysis and data cover almost all OECD countries and 14 additional non-OECD countries.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/6bd398b4-490e-4b30-9add-76a6f330b8f8","harvest_record_raw":"https://catalog.data.gov/harvest_record/6bd398b4-490e-4b30-9add-76a6f330b8f8/raw","has_download":true,"has_spatial":false,"identifier":"014D000422","keyword":["unspecified"],"last_harvested_date":"2026-08-07T22:27:30.368893","organization":{"aliases":["dept","dos"],"description":null,"id":"441a7317-0631-4d27-b8bb-dcfaa6be5915","logo":"https://raw.githubusercontent.com/GSA/logo/master/state.png","name":"Department of State","organization_type":"Federal Government","slug":"state"},"popularity":6,"publisher":"U.S. Department of State","slug":"school-factors-related-to-quality-and-equity-results-from-pisa-2000","spatial_centroid":null,"spatial_shape":null,"theme":[],"title":"School Factors Related to Quality and Equity Results from PISA 2000"},{"_score":31.779898,"_sort":[1786060148147,31.779898,0,"27260d4e-b244-4273-b8bb-9cd206a6238e"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Emilie Henderson","hasEmail":"mailto:emilie.henderson@oregonstate.edu"},"description":"Collection of model inputs and outputs examining different combinations of management and climate scenarios run in northwest Washington. The objectives of this project are to explore how climate and land management in southwestern Oregon and coastal Washington might interact to shape future vegetation and wildlife habitat, and determine what management actions will likely maximize habitats for key species. Climate scenarios include no climate change, Hadley global circulation model, and RegCM3 regional circulation model.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P145U26M","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.b94832e2-05db-4f08-9790-3273d96fbf2f.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_b94832e2-05db-4f08-9790-3273d96fbf2f","keyword":["Pacific Coast","Pacific Northwest","Stream temperature","USGS:b94832e2-05db-4f08-9790-3273d96fbf2f","Washington","biota","climate change","economy","external research support","habitats","land management","modeling","state and transition modeling","vegetation change","vulnerability assessment","wildlife habitat"],"modified":"2026-08-04T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-124.7534, 46.0432, -122.4771, 48.4548","theme":["geospatial"],"title":"Future Spotted Owl Habitat Projections, Northwest Washington Study Area, 2007-2096"},"description":"Collection of model inputs and outputs examining different combinations of management and climate scenarios run in northwest Washington. The objectives of this project are to explore how climate and land management in southwestern Oregon and coastal Washington might interact to shape future vegetation and wildlife habitat, and determine what management actions will likely maximize habitats for key species. Climate scenarios include no climate change, Hadley global circulation model, and RegCM3 regional circulation model.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/5b6dbbb0-0161-4581-ade6-c5416361ca3c","harvest_record_raw":"https://catalog.data.gov/harvest_record/5b6dbbb0-0161-4581-ade6-c5416361ca3c/raw","has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_b94832e2-05db-4f08-9790-3273d96fbf2f","keyword":["Pacific Coast","Pacific Northwest","Stream temperature","USGS:b94832e2-05db-4f08-9790-3273d96fbf2f","Washington","biota","climate change","economy","external research support","habitats","land management","modeling","state and transition modeling","vegetation change","vulnerability assessment","wildlife habitat"],"last_harvested_date":"2026-08-06T23:49:08.147500","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"future-spotted-owl-habitat-projections-northwest-washington-study-area-2007-2096","spatial_centroid":{"lat":47.00784,"lon":-123.84288},"spatial_shape":{"coordinates":[[[-124.7534,46.0432],[-124.7534,48.4548],[-122.4771,48.4548],[-122.4771,46.0432],[-124.7534,46.0432]]],"type":"Polygon"},"theme":["geospatial"],"title":"Future Spotted Owl Habitat Projections, Northwest Washington Study Area, 2007-2096"},{"_score":13.321173,"_sort":[1786059953278,13.321173,0,"fc99d37e-317f-400c-b81b-3b88036ce98e"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Alma L Anides Morales","hasEmail":"mailto:aanidesmorales@usgs.gov"},"description":"This dataset contains a 6\u2011class soils map (30-meter) for the Los Planes basin in Baja California Sur, Mexico. The map was generated using a digital soil mapping approach that incorporates environmental covariables following the SCORPAN (soil, climate, organisms, topography, parent material, age, and time) framework. The data release also includes a point feature class representing multiple soil sampling campaigns across the watershed, including a dedicated field effort led by collaborators in the Universidad Aut\u00f3noma de Baja California Sur (UABCS) Earth Sciences Department that emerged directly from this research. Photographs from the field sampling campaign are provided. The accompanying attribute table supplies detailed qualitative and quantitative descriptions of each sampled profile. Spatially, these point data served both as an independent validation dataset for the predicted 6\u2011class soil map, and they provided the physical measurements required to parameterize the companion usersoil table (provided in .xlsx format).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1BTDY6A","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.6a3352141ba49b742637d5b5.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a3352141ba49b742637d5b5","keyword":["Baja California Sur","Los Planes Watershed","Mexico","USGS:6a3352141ba49b742637d5b5","conceptual modeling","environment","geomorphology","geoscientificInformation","remote sensing","soil sciences"],"modified":"2026-08-04T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-110.1703, 23.6942, -109.8669, 24.2398","theme":["geospatial"],"title":"General Soils Map of Los Planes Basin, Baja California Sur Mexico"},"description":"This dataset contains a 6\u2011class soils map (30-meter) for the Los Planes basin in Baja California Sur, Mexico. The map was generated using a digital soil mapping approach that incorporates environmental covariables following the SCORPAN (soil, climate, organisms, topography, parent material, age, and time) framework. The data release also includes a point feature class representing multiple soil sampling campaigns across the watershed, including a dedicated field effort led by collaborators in the Universidad Aut\u00f3noma de Baja California Sur (UABCS) Earth Sciences Department that emerged directly from this research. Photographs from the field sampling campaign are provided. The accompanying attribute table supplies detailed qualitative and quantitative descriptions of each sampled profile. Spatially, these point data served both as an independent validation dataset for the predicted 6\u2011class soil map, and they provided the physical measurements required to parameterize the companion usersoil table (provided in .xlsx format).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/e2b54ba1-7d6e-45f2-8f55-33251fbf98dd","harvest_record_raw":"https://catalog.data.gov/harvest_record/e2b54ba1-7d6e-45f2-8f55-33251fbf98dd/raw","has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a3352141ba49b742637d5b5","keyword":["Baja California Sur","Los Planes Watershed","Mexico","USGS:6a3352141ba49b742637d5b5","conceptual modeling","environment","geomorphology","geoscientificInformation","remote sensing","soil sciences"],"last_harvested_date":"2026-08-06T23:45:53.278074","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"general-soils-map-of-los-planes-basin-baja-california-sur-mexico","spatial_centroid":{"lat":23.912439999999997,"lon":-110.04893999999999},"spatial_shape":{"coordinates":[[[-110.1703,23.6942],[-110.1703,24.2398],[-109.8669,24.2398],[-109.8669,23.6942],[-110.1703,23.6942]]],"type":"Polygon"},"theme":["geospatial"],"title":"General Soils Map of Los Planes Basin, Baja California Sur Mexico"},{"_score":9.549301,"_sort":[1785949066797,9.549301,4,"8c435260-c8b1-4fce-8df3-f80182fae9f5"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Miguel Villarreal","hasEmail":"mailto:mvillarreal@usgs.gov"},"description":"The data release contains  spatial data sets in raster and vector formats that are used to quantify, analyze and visualize recent fire regimes for the Mogollon Rim-Colorado Plateau (also called the Mogollon Highlands), the Sky Islands, or Madrean Archipelago and the Northern Sierra Madre Occidental regions of the United States and Mexico. The data were generated as part of the Southwest Climate Adaptation Science Center-funded project titled \"Assessing Vulnerability of Vegetation and Wildlife Communities to Post-Fire Transformations to Guide Management of Southwestern Pine Forests and Woodlands.\" Specifically, the data release is comprised of 3 different compressed (zip) files containing the following data:\nDataset 1 Fire Perimeters - A fire perimeter (burned area) dataset ranging in years from 1985-2022 that was created by merging fire information from existing wildfire databases available in the United States, and custom Landsat burned area mapping products generated for areas in Mexico. The zip file contains separate polygon files for each ecoregion. \nDataset 2 Burn Severity \u2013 Fire severity rasters calculated as the differenced Normalized Burn Ratio (dNBR) from Landsat data for each fire perimeter. This dataset contains dNBR images of all individual fires in a zipped folder. \nDataset 3 Fire Regimes and Land Use Variables \u2013 Fire regime metrics were generated from the above data sets including: 1) number of times burned raster @ 100m, 2) Fire deficit/surplus layers based on the expected number of fires for each vegetation class, 3) maximum fire severity, mean fire severity and fire order-weighted burn severity all @ 30 m, 4) fire order-weighted seasonality (ignition date) surface high resolution, 5) Anthropogenic Biomes (Anthromes) describing biotic community type and population density within a 1km focal window and 6) roadless volume rasters at 100 m resolution.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14BHA49","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.6920ef6dd4be025bc609c70e.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6920ef6dd4be025bc609c70e","keyword":["Arizona","Chihuahua, Mexico","Landsat","New Mexico","Sonora, Mexico","USGS:6920ef6dd4be025bc609c70e","burn severity","economy","fire regime","fires","geospatial datasets","remote sensing","wildfire"],"modified":"2026-08-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-113.4027, 26.2138, -106.2330, 36.0541","theme":["geospatial"],"title":"Fire perimeter, burn severity (dNBR), spatial fire regime and land use data for the North American Cordillera of the southwestern United States and northern Mexico, 1985-2022"},"description":"The data release contains  spatial data sets in raster and vector formats that are used to quantify, analyze and visualize recent fire regimes for the Mogollon Rim-Colorado Plateau (also called the Mogollon Highlands), the Sky Islands, or Madrean Archipelago and the Northern Sierra Madre Occidental regions of the United States and Mexico. The data were generated as part of the Southwest Climate Adaptation Science Center-funded project titled \"Assessing Vulnerability of Vegetation and Wildlife Communities to Post-Fire Transformations to Guide Management of Southwestern Pine Forests and Woodlands.\" Specifically, the data release is comprised of 3 different compressed (zip) files containing the following data:\nDataset 1 Fire Perimeters - A fire perimeter (burned area) dataset ranging in years from 1985-2022 that was created by merging fire information from existing wildfire databases available in the United States, and custom Landsat burned area mapping products generated for areas in Mexico. The zip file contains separate polygon files for each ecoregion. \nDataset 2 Burn Severity \u2013 Fire severity rasters calculated as the differenced Normalized Burn Ratio (dNBR) from Landsat data for each fire perimeter. This dataset contains dNBR images of all individual fires in a zipped folder. \nDataset 3 Fire Regimes and Land Use Variables \u2013 Fire regime metrics were generated from the above data sets including: 1) number of times burned raster @ 100m, 2) Fire deficit/surplus layers based on the expected number of fires for each vegetation class, 3) maximum fire severity, mean fire severity and fire order-weighted burn severity all @ 30 m, 4) fire order-weighted seasonality (ignition date) surface high resolution, 5) Anthropogenic Biomes (Anthromes) describing biotic community type and population density within a 1km focal window and 6) roadless volume rasters at 100 m resolution.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/7a4b85c6-699c-4c1f-8c76-b026bed24115","harvest_record_raw":"https://catalog.data.gov/harvest_record/7a4b85c6-699c-4c1f-8c76-b026bed24115/raw","has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6920ef6dd4be025bc609c70e","keyword":["Arizona","Chihuahua, Mexico","Landsat","New Mexico","Sonora, Mexico","USGS:6920ef6dd4be025bc609c70e","burn severity","economy","fire regime","fires","geospatial datasets","remote sensing","wildfire"],"last_harvested_date":"2026-08-05T16:57:46.797567","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":4,"publisher":"U.S. Geological Survey","slug":"fire-perimeter-burn-severity-dnbr-spatial-fire-regime-and-land-use-data-for-the--1985-2022","spatial_centroid":{"lat":30.149919999999998,"lon":-110.53482},"spatial_shape":{"coordinates":[[[-113.4027,26.2138],[-113.4027,36.0541],[-106.233,36.0541],[-106.233,26.2138],[-113.4027,26.2138]]],"type":"Polygon"},"theme":["geospatial"],"title":"Fire perimeter, burn severity (dNBR), spatial fire regime and land use data for the North American Cordillera of the southwestern United States and northern Mexico, 1985-2022"},{"_score":11.410219,"_sort":[1785948415753,11.410219,4,"7df1f3dd-f565-48bb-a12e-c48d3bf25862"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["009:20"],"contactPoint":{"@type":"vcard:Contact","fn":"Craig Kassinger","hasEmail":"mailto:nephtrackingsupport@cdc.gov"},"description":"This dataset provides data at the county level for the contiguous United States. It includes weekly United States Drought Monitor (USDM) data from 2000-2016 provided by the Cooperative Institute for Climate and Satellites - North Carolina. Please refer to the metadata attachment for more information.\r\n\r\nThese data are used by the CDC's National Environmental Public Health Tracking Network to generate drought measures. Learn more about drought on the Tracking Network's website: https://ephtracking.cdc.gov/showDroughtLanding.\r\n\r\nBy using these data, you signify your agreement to comply with the following requirements: \r\n1.\tUse the data for statistical reporting and analysis only. \r\n2.\tDo not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. \r\n3.\tDo not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov. \r\n4.\tDo not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating. \r\n5.\tAcknowledge, in all reports or presentations based on these data, the original source of the data and CDC. \r\n6.\tSuggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking. \r\n\r\nProblems or Questions? \r\nEmail trackingsupport@cdc.gov.","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/spsk-9jj6/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/spsk-9jj6/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/spsk-9jj6/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"}],"identifier":"https://data.cdc.gov/api/views/spsk-9jj6","issued":"2018-08-08","keyword":["drought","environmental health"],"landingPage":"https://data.cdc.gov/d/spsk-9jj6","license":"http://opendefinition.org/licenses/odc-odbl/","modified":"2018-11-27","programCode":["009:032"],"publisher":{"@type":"org:Organization","name":"Centers for Disease Control and Prevention"},"theme":["Environmental Health & Toxicology"],"title":"United States Drought Monitor, 2000-2016"},"description":"This dataset provides data at the county level for the contiguous United States. It includes weekly United States Drought Monitor (USDM) data from 2000-2016 provided by the Cooperative Institute for Climate and Satellites - North Carolina. Please refer to the metadata attachment for more information.\r\n\r\nThese data are used by the CDC's National Environmental Public Health Tracking Network to generate drought measures. Learn more about drought on the Tracking Network's website: https://ephtracking.cdc.gov/showDroughtLanding.\r\n\r\nBy using these data, you signify your agreement to comply with the following requirements: \r\n1.\tUse the data for statistical reporting and analysis only. \r\n2.\tDo not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. \r\n3.\tDo not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov. \r\n4.\tDo not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating. \r\n5.\tAcknowledge, in all reports or presentations based on these data, the original source of the data and CDC. \r\n6.\tSuggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking. \r\n\r\nProblems or Questions? \r\nEmail trackingsupport@cdc.gov.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/ee66ee02-d517-491d-a733-e1ab3659abd3","harvest_record_raw":"https://catalog.data.gov/harvest_record/ee66ee02-d517-491d-a733-e1ab3659abd3/raw","has_spatial":false,"identifier":"https://data.cdc.gov/api/views/spsk-9jj6","keyword":["drought","environmental health"],"last_harvested_date":"2026-08-05T16:46:55.753933","organization":{"aliases":["US","dept"],"description":null,"id":"2c2fc21f-21d0-4450-af01-cf8c69b44156","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/hhs.png","name":"U.S. Department of Health & Human Services","organization_type":"Federal Government","slug":"hhs"},"popularity":4,"publisher":"Centers for Disease Control and Prevention","slug":"united-states-drought-monitor-2000-2016","spatial_centroid":null,"spatial_shape":null,"theme":["Environmental Health & Toxicology"],"title":"United States Drought Monitor, 2000-2016"},{"_score":11.66356,"_sort":[1785948084185,11.66356,1,"10c99b34-3ebb-4e06-b280-b0c0eb592f62"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["009:20"],"contactPoint":{"@type":"vcard:Contact","fn":"Craig Kassinger","hasEmail":"mailto:nephtrackingsupport@cdc.gov"},"description":"This dataset provides data at the county level for the contiguous United States. It includes monthly Standardized Precipitation Index (SPI) data from 1895-2016 provided by the Cooperative Institute for Climate and Satellites - North Carolina. Please refer to the metadata attachment for more information.\r\n\r\nLearn more about drought on the Tracking Network's website: https://ephtracking.cdc.gov/showDroughtLanding.\r\n\r\nBy using these data, you signify your agreement to comply with the following requirements: \r\n1.\tUse the data for statistical reporting and analysis only. \r\n2.\tDo not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. \r\n3.\tDo not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov. \r\n4.\tDo not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating. \r\n5.\tAcknowledge, in all reports or presentations based on these data, the original source of the data and CDC. \r\n6.\tSuggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking. \r\n\r\nProblems or Questions? \r\nEmail trackingsupport@cdc.gov.","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/xbk2-5i4e/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/xbk2-5i4e/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/xbk2-5i4e/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"}],"identifier":"https://data.cdc.gov/api/views/xbk2-5i4e","issued":"2018-07-26","keyword":["drought","environmental health"],"landingPage":"https://data.cdc.gov/d/xbk2-5i4e","license":"http://opendefinition.org/licenses/odc-odbl/","modified":"2018-11-27","programCode":["009:032"],"publisher":{"@type":"org:Organization","name":"Centers for Disease Control and Prevention"},"theme":["Environmental Health & Toxicology"],"title":"Standardized Precipitation Index, 1895-2016"},"description":"This dataset provides data at the county level for the contiguous United States. It includes monthly Standardized Precipitation Index (SPI) data from 1895-2016 provided by the Cooperative Institute for Climate and Satellites - North Carolina. Please refer to the metadata attachment for more information.\r\n\r\nLearn more about drought on the Tracking Network's website: https://ephtracking.cdc.gov/showDroughtLanding.\r\n\r\nBy using these data, you signify your agreement to comply with the following requirements: \r\n1.\tUse the data for statistical reporting and analysis only. \r\n2.\tDo not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. \r\n3.\tDo not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov. \r\n4.\tDo not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating. \r\n5.\tAcknowledge, in all reports or presentations based on these data, the original source of the data and CDC. \r\n6.\tSuggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking. \r\n\r\nProblems or Questions? \r\nEmail trackingsupport@cdc.gov.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/ad88d1fc-f579-45f5-ad01-47a8104ecfc8","harvest_record_raw":"https://catalog.data.gov/harvest_record/ad88d1fc-f579-45f5-ad01-47a8104ecfc8/raw","has_spatial":false,"identifier":"https://data.cdc.gov/api/views/xbk2-5i4e","keyword":["drought","environmental health"],"last_harvested_date":"2026-08-05T16:41:24.185806","organization":{"aliases":["US","dept"],"description":null,"id":"2c2fc21f-21d0-4450-af01-cf8c69b44156","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/hhs.png","name":"U.S. Department of Health & Human Services","organization_type":"Federal Government","slug":"hhs"},"popularity":1,"publisher":"Centers for Disease Control and Prevention","slug":"standardized-precipitation-index-1895-2016","spatial_centroid":null,"spatial_shape":null,"theme":["Environmental Health & Toxicology"],"title":"Standardized Precipitation Index, 1895-2016"},{"_score":11.380339,"_sort":[1785947822914,11.380339,0,"0080c477-c38c-4b7e-bc4d-8878a5b6eeea"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["009:20"],"contactPoint":{"@type":"vcard:Contact","fn":"Craig Kassinger","hasEmail":"mailto:nephtrackingsupport@cdc.gov"},"description":"This dataset provides data at the county level for the contiguous United States. It includes monthly Standardized Precipitation Evapotranspiration Index (SPEI)  data from 1895-2016 provided by the Cooperative Institute for Climate and Satellites - North Carolina. Please refer to the metadata attachment for more information.\r\n\r\nThese data are used by the CDC's National Environmental Public Health Tracking Network to generate drought measures. Learn more about drought on the Tracking Network's website: https://ephtracking.cdc.gov/showDroughtLanding.\r\n\r\nBy using these data, you signify your agreement to comply with the following requirements: \r\n1.\tUse the data for statistical reporting and analysis only. \r\n2.\tDo not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. \r\n3.\tDo not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov. \r\n4.\tDo not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating. \r\n5.\tAcknowledge, in all reports or presentations based on these data, the original source of the data and CDC. \r\n6.\tSuggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking. \r\n\r\nProblems or Questions? \r\nEmail trackingsupport@cdc.gov.","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/6nbv-ifib/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/6nbv-ifib/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/6nbv-ifib/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"}],"identifier":"https://data.cdc.gov/api/views/6nbv-ifib","issued":"2018-07-26","keyword":["drought","environmental health"],"landingPage":"https://data.cdc.gov/d/6nbv-ifib","license":"http://opendefinition.org/licenses/odc-odbl/","modified":"2026-07-28","programCode":["009:032"],"publisher":{"@type":"org:Organization","name":"Centers for Disease Control and Prevention"},"theme":["Environmental Health & Toxicology"],"title":"Standardized Precipitation Evapotranspiration Index, 1895-2016"},"description":"This dataset provides data at the county level for the contiguous United States. It includes monthly Standardized Precipitation Evapotranspiration Index (SPEI)  data from 1895-2016 provided by the Cooperative Institute for Climate and Satellites - North Carolina. Please refer to the metadata attachment for more information.\r\n\r\nThese data are used by the CDC's National Environmental Public Health Tracking Network to generate drought measures. Learn more about drought on the Tracking Network's website: https://ephtracking.cdc.gov/showDroughtLanding.\r\n\r\nBy using these data, you signify your agreement to comply with the following requirements: \r\n1.\tUse the data for statistical reporting and analysis only. \r\n2.\tDo not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. \r\n3.\tDo not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov. \r\n4.\tDo not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating. \r\n5.\tAcknowledge, in all reports or presentations based on these data, the original source of the data and CDC. \r\n6.\tSuggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking. \r\n\r\nProblems or Questions? \r\nEmail trackingsupport@cdc.gov.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/3459ab8a-c776-4810-88f6-6a7ce80082a8","harvest_record_raw":"https://catalog.data.gov/harvest_record/3459ab8a-c776-4810-88f6-6a7ce80082a8/raw","has_spatial":false,"identifier":"https://data.cdc.gov/api/views/6nbv-ifib","keyword":["drought","environmental health"],"last_harvested_date":"2026-08-05T16:37:02.914528","organization":{"aliases":["US","dept"],"description":null,"id":"2c2fc21f-21d0-4450-af01-cf8c69b44156","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/hhs.png","name":"U.S. Department of Health & Human Services","organization_type":"Federal Government","slug":"hhs"},"popularity":0,"publisher":"Centers for Disease Control and Prevention","slug":"standardized-precipitation-evapotranspiration-index-1895-2016","spatial_centroid":null,"spatial_shape":null,"theme":["Environmental Health & Toxicology"],"title":"Standardized Precipitation Evapotranspiration Index, 1895-2016"},{"_score":11.374559,"_sort":[1785947107706,11.374559,2,"d2326e31-844d-4985-b6ea-fb083f16cf14"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["009:20"],"contactPoint":{"@type":"vcard:Contact","fn":"Craig Kassinger","hasEmail":"mailto:nephtrackingsupport@cdc.gov"},"description":"This dataset provides data at the county level for the contiguous United States. It includes monthly Palmer Drought Severity Index (PDSI) data from 1895-2016 provided by the Cooperative Institute for Climate and Satellites - North Carolina. Please refer to the metadata attachment for more information.\r\n\r\nLearn more about drought on the Tracking Network's website: https://ephtracking.cdc.gov/showDroughtLanding.\r\n\r\nBy using these data, you signify your agreement to comply with the following requirements: \r\n1.\tUse the data for statistical reporting and analysis only. \r\n2.\tDo not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. \r\n3.\tDo not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov. \r\n4.\tDo not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating. \r\n5.\tAcknowledge, in all reports or presentations based on these data, the original source of the data and CDC. \r\n6.\tSuggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking. \r\n\r\nProblems or Questions? \r\nEmail trackingsupport@cdc.gov.","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/en5r-5ds4/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/en5r-5ds4/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","downloadURL":"https://data.cdc.gov/api/v3/views/en5r-5ds4/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"}],"identifier":"https://data.cdc.gov/api/views/en5r-5ds4","issued":"2018-07-26","keyword":["drought","environmental health"],"landingPage":"https://data.cdc.gov/d/en5r-5ds4","license":"http://opendefinition.org/licenses/odc-odbl/","modified":"2026-07-28","programCode":["009:032"],"publisher":{"@type":"org:Organization","name":"Centers for Disease Control and Prevention"},"theme":["Environmental Health & Toxicology"],"title":"Palmer Drought Severity Index, 1895-2016"},"description":"This dataset provides data at the county level for the contiguous United States. It includes monthly Palmer Drought Severity Index (PDSI) data from 1895-2016 provided by the Cooperative Institute for Climate and Satellites - North Carolina. Please refer to the metadata attachment for more information.\r\n\r\nLearn more about drought on the Tracking Network's website: https://ephtracking.cdc.gov/showDroughtLanding.\r\n\r\nBy using these data, you signify your agreement to comply with the following requirements: \r\n1.\tUse the data for statistical reporting and analysis only. \r\n2.\tDo not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. \r\n3.\tDo not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov. \r\n4.\tDo not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating. \r\n5.\tAcknowledge, in all reports or presentations based on these data, the original source of the data and CDC. \r\n6.\tSuggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking. \r\n\r\nProblems or Questions? \r\nEmail trackingsupport@cdc.gov.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/5ba1eb49-e52a-4d09-9081-df26c2bd25a0","harvest_record_raw":"https://catalog.data.gov/harvest_record/5ba1eb49-e52a-4d09-9081-df26c2bd25a0/raw","has_spatial":false,"identifier":"https://data.cdc.gov/api/views/en5r-5ds4","keyword":["drought","environmental health"],"last_harvested_date":"2026-08-05T16:25:07.706081","organization":{"aliases":["US","dept"],"description":null,"id":"2c2fc21f-21d0-4450-af01-cf8c69b44156","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/hhs.png","name":"U.S. Department of Health & Human Services","organization_type":"Federal Government","slug":"hhs"},"popularity":2,"publisher":"Centers for Disease Control and Prevention","slug":"palmer-drought-severity-index-1895-2016","spatial_centroid":null,"spatial_shape":null,"theme":["Environmental Health & Toxicology"],"title":"Palmer Drought Severity Index, 1895-2016"},{"_score":8.20603,"_sort":[1785945545528,8.20603,0,"7cabad6e-bd43-43a5-8765-f83a2f0ddbf0"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Kaitlyn Strickfaden","hasEmail":"mailto:kstrickfaden@uidaho.edu"},"description":"Snow conditions are changing dramatically in the mountains of the interior Pacific Northwest, including eastern Washington, northern Idaho, and western Montana. These changes can both benefit and hinder a variety of wildlife species. The timing and extent of seasonal snowpacks, in addition to snow depth, density, and hardness, can impact the ability of wildlife to access forage, their ability to move across the landscape, and their vulnerability to predators, to name a few. In order to respond effectively to changes in snow conditions, wildlife managers need tools to identify areas and promote conditions that maintain late spring and early summer snowpack for some sensitive species. Managers also require an index of winter severity that includes information on temperature, snow depth, and snow hardness at relevant spatial and temporal scales to adapt management strategies for seasonal conditions. \n \nThis project seeks to advance the understanding of how snow conditions vary and how such variation affects both species of greatest conservation need (e.g., wolverine, hoary marmot, western bumble bee, and mountain goat) and species of economic and recreational importance (e.g., elk and moose) in forests spanning the rain-snow transition zone in the interior Pacific Northwest. To do this, researchers created new tools that managers can use to estimate snow depth, map areas of late season snow (known as \u201csnow refugia\u201d), and estimate winter severity for ungulate species such as elk and moose. Researchers used these novel datasets to predict winter range habitat use by deer and elk in Idaho and to identify linkages between ungulate survival and winter severity. These data were used to create a model predicting snow disappearance dates (SDD) at camera sites and across our entire study area to identify priority areas of conservation for snow-dependent wildlife. The model predicted high-elevation areas, north-facing aspects, and cold-air pools retained snow latest. These data were also used to model the probability of deer presence at camera sites dependent on snow conditions, and it was determined that deer respond negatively to increased snow density and respond slightly positively to increased snow hardness.\n \nThe results of this project will be directly applicable to federal (U.S. Fish and Wildlife Service), state (Idaho Department of Fish and Game), and tribal (Coeur D\u2019Alene Tribe) managers in the region. Providing natural resource managers with tools to identify locations of snow retention for sensitive and listed species is critical for identifying habitats to conserve or modify in order to facilitate species recovery. Lastly, a winter severity model will provide wildlife managers with a much-needed tool for predicting future climate change effects on ungulates and adjusting management strategies accordingly.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.21429/bma6-xn17","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.4bc80965-54cf-4bb0-a1f0-4c52a23769b0.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_4bc80965-54cf-4bb0-a1f0-4c52a23769b0","keyword":["Idaho","Latah","Moscow Mountain","USGS:4bc80965-54cf-4bb0-a1f0-4c52a23769b0","biota","external research support","snow and ice cover"],"modified":"2026-08-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-116.86000, 46.78000, -116.83000, 46.82000","theme":["geospatial"],"title":"Estimating the Spatial and Temporal Extent of Snowpack Properties in Complex Terrain: Data Release"},"description":"Snow conditions are changing dramatically in the mountains of the interior Pacific Northwest, including eastern Washington, northern Idaho, and western Montana. These changes can both benefit and hinder a variety of wildlife species. The timing and extent of seasonal snowpacks, in addition to snow depth, density, and hardness, can impact the ability of wildlife to access forage, their ability to move across the landscape, and their vulnerability to predators, to name a few. In order to respond effectively to changes in snow conditions, wildlife managers need tools to identify areas and promote conditions that maintain late spring and early summer snowpack for some sensitive species. Managers also require an index of winter severity that includes information on temperature, snow depth, and snow hardness at relevant spatial and temporal scales to adapt management strategies for seasonal conditions. \n \nThis project seeks to advance the understanding of how snow conditions vary and how such variation affects both species of greatest conservation need (e.g., wolverine, hoary marmot, western bumble bee, and mountain goat) and species of economic and recreational importance (e.g., elk and moose) in forests spanning the rain-snow transition zone in the interior Pacific Northwest. To do this, researchers created new tools that managers can use to estimate snow depth, map areas of late season snow (known as \u201csnow refugia\u201d), and estimate winter severity for ungulate species such as elk and moose. Researchers used these novel datasets to predict winter range habitat use by deer and elk in Idaho and to identify linkages between ungulate survival and winter severity. These data were used to create a model predicting snow disappearance dates (SDD) at camera sites and across our entire study area to identify priority areas of conservation for snow-dependent wildlife. The model predicted high-elevation areas, north-facing aspects, and cold-air pools retained snow latest. These data were also used to model the probability of deer presence at camera sites dependent on snow conditions, and it was determined that deer respond negatively to increased snow density and respond slightly positively to increased snow hardness.\n \nThe results of this project will be directly applicable to federal (U.S. Fish and Wildlife Service), state (Idaho Department of Fish and Game), and tribal (Coeur D\u2019Alene Tribe) managers in the region. Providing natural resource managers with tools to identify locations of snow retention for sensitive and listed species is critical for identifying habitats to conserve or modify in order to facilitate species recovery. Lastly, a winter severity model will provide wildlife managers with a much-needed tool for predicting future climate change effects on ungulates and adjusting management strategies accordingly.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/6dd82e7a-9d8b-4f8b-85cd-5e625108a4c8","harvest_record_raw":"https://catalog.data.gov/harvest_record/6dd82e7a-9d8b-4f8b-85cd-5e625108a4c8/raw","has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_4bc80965-54cf-4bb0-a1f0-4c52a23769b0","keyword":["Idaho","Latah","Moscow Mountain","USGS:4bc80965-54cf-4bb0-a1f0-4c52a23769b0","biota","external research support","snow and ice cover"],"last_harvested_date":"2026-08-05T15:59:05.528306","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"estimating-the-spatial-and-temporal-extent-of-snowpack-properties-in-complex-terrain-data-","spatial_centroid":{"lat":46.79600000000001,"lon":-116.848},"spatial_shape":{"coordinates":[[[-116.86,46.78],[-116.86,46.82],[-116.83,46.82],[-116.83,46.78],[-116.86,46.78]]],"type":"Polygon"},"theme":["geospatial"],"title":"Estimating the Spatial and Temporal Extent of Snowpack Properties in Complex Terrain: Data Release"},{"_score":16.629984,"_sort":[1785945081100,16.629984,0,"6851921e-4e7d-47c2-aec8-62423287e152"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Danelle M. Larson","hasEmail":"mailto:dmlarson@usgs.gov"},"description":"The data is a compilation of long-term resource monitoring (LTRM) data, hydrology data, and weather data across the Upper Mississippi River, USA. The intent is to better understand the relationships of the macrophyte (aquatic vegetation) community diversity to basic weather/climate, hydrologic, and water quality variables at multiple spatial scales (e.g., plot, aquatic area, stratum, and pool) across time (specifically, years 1998-2019).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1JGFM76","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.68b9ebe5d4be021c5e4c9dd1.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_68b9ebe5d4be021c5e4c9dd1","keyword":["Midwestern United States","USGS:68b9ebe5d4be021c5e4c9dd1","atmospheric and climatic processes","biogeography","biota","nonvascular plants","surface water quality","upper Mississippi River","vascular plants"],"modified":"2026-08-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.8894, 41.7549, -90.1000, 44.7155","theme":["geospatial"],"title":"Macrophyte Communities and Environmental Data for the Upper Mississippi River from 1998\u20132019"},"description":"The data is a compilation of long-term resource monitoring (LTRM) data, hydrology data, and weather data across the Upper Mississippi River, USA. The intent is to better understand the relationships of the macrophyte (aquatic vegetation) community diversity to basic weather/climate, hydrologic, and water quality variables at multiple spatial scales (e.g., plot, aquatic area, stratum, and pool) across time (specifically, years 1998-2019).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/79c46a4a-a1ee-4922-90cc-894a0f6c0840","harvest_record_raw":"https://catalog.data.gov/harvest_record/79c46a4a-a1ee-4922-90cc-894a0f6c0840/raw","has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_68b9ebe5d4be021c5e4c9dd1","keyword":["Midwestern United States","USGS:68b9ebe5d4be021c5e4c9dd1","atmospheric and climatic processes","biogeography","biota","nonvascular plants","surface water quality","upper Mississippi River","vascular plants"],"last_harvested_date":"2026-08-05T15:51:21.100156","organization":{"aliases":["dept"],"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"macrophyte-communities-and-environmental-data-for-the-upper-mississippi-river-from-1998201","spatial_centroid":{"lat":42.939139999999995,"lon":-91.77364},"spatial_shape":{"coordinates":[[[-92.8894,41.7549],[-92.8894,44.7155],[-90.1,44.7155],[-90.1,41.7549],[-92.8894,41.7549]]],"type":"Polygon"},"theme":["geospatial"],"title":"Macrophyte Communities and Environmental Data for the Upper Mississippi River from 1998\u20132019"},{"_score":63.817837,"_sort":[1785888589184,63.817837,1,"bbdadcfb-4435-43ee-b8e3-236bf0ed1082"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Scott Goodwin","hasEmail":"mailto:scott.goodwin@nasa.gov"},"description":"CLAIRE MONTELEONI*, GAVIN SCHMIDT**, AND SHAILESH SAROHA***\r\n\r\nClimate models are complex mathematical models designed by meteorologists, geophysicists,\r\nand climate scientists to simulate and predict climate. Given temperature predictions\r\nfrom the top 20 climate models worldwide, and over 100 years of historical temperature data, we\r\ntrack the changing sequence of which model currently predicts best. We use an algorithm due to\r\nMonteleoni and Jaakkola that models the sequence of observations using a hierarchical learner,\r\nbased on a set of generalized Hidden Markov Models (HMM), where the identity of the current\r\nbest climate model is the hidden variable. The transition probabilities between climate models\r\nare learned online, simultaneous to tracking the temperature predictions. On historical data, our\r\nonline learning algorithm\u2019s average prediction loss nearly matches that of the best performing\r\nclimate model in hindsight. Moreover its performance surpasses that of the average model prediction,\r\nwhich was the current state-of-the-art in climate science, the median prediction, and least\r\nsquares linear regression. We also experimented on climate model predictions through the year\r\n2098. Simulating labels with the predictions of any one climate model, we found significantly improved\r\nperformance using our online learning algorithm with respect to the other climate models,\r\nand techniques.","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_OEM/ISS.OEM_J2K_EPH.txt","format":"TXT","mediaType":"text/plain","title":"Public Distribution File"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_OEM/ISS.OEM_J2K_EPH.xml","format":"XML","mediaType":"application/xml","title":"Public Distribution File"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesINT01.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesINT01"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesINT02.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesINT02"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesINT03.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesINT03"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesINT04.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesINT04"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesINT05.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesINT05"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesUSA01.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesUSA01"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesUSA02.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesUSA02"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesUSA03.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesUSA03"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesUSA04.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesUSA04"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesUSA05.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesUSA05"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesUSA06.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesUSA06"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesUSA07.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesUSA07"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesUSA08.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesUSA08"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesUSA09.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesUSA09"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesUSA10.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesUSA10"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_citiesUSA11.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_citiesUSA11"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_natparksUSA01.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_natparksUSA01"},{"@type":"dcat:Distribution","downloadURL":"https://nasa-public-data.s3.amazonaws.com/iss-coords/2021-11-08/ISS_sightings/XMLsightingData_natparksUSA02.xml","format":"XML","mediaType":"application/xml","title":"XMLsightingData_natparksUSA02"}],"identifier":"DASHLINK_223","issued":"2010-10-13","keyword":["ames","dashlink","nasa"],"landingPage":"https://c3.nasa.gov/dashlink/resources/223/","modified":"2025-03-31","programCode":["026:029"],"publisher":{"@type":"org:Organization","name":"Dashlink"},"title":"TRACKING CLIMATE MODELS"},"description":"CLAIRE MONTELEONI*, GAVIN SCHMIDT**, AND SHAILESH SAROHA***\r\n\r\nClimate models are complex mathematical models designed by meteorologists, geophysicists,\r\nand climate scientists to simulate and predict climate. Given temperature predictions\r\nfrom the top 20 climate models worldwide, and over 100 years of historical temperature data, we\r\ntrack the changing sequence of which model currently predicts best. We use an algorithm due to\r\nMonteleoni and Jaakkola that models the sequence of observations using a hierarchical learner,\r\nbased on a set of generalized Hidden Markov Models (HMM), where the identity of the current\r\nbest climate model is the hidden variable. The transition probabilities between climate models\r\nare learned online, simultaneous to tracking the temperature predictions. On historical data, our\r\nonline learning algorithm\u2019s average prediction loss nearly matches that of the best performing\r\nclimate model in hindsight. Moreover its performance surpasses that of the average model prediction,\r\nwhich was the current state-of-the-art in climate science, the median prediction, and least\r\nsquares linear regression. We also experimented on climate model predictions through the year\r\n2098. Simulating labels with the predictions of any one climate model, we found significantly improved\r\nperformance using our online learning algorithm with respect to the other climate models,\r\nand techniques.","distribution_titles":["Public Distribution File","Public Distribution File","XMLsightingData_citiesINT01","XMLsightingData_citiesINT02","XMLsightingData_citiesINT03","XMLsightingData_citiesINT04","XMLsightingData_citiesINT05","XMLsightingData_citiesUSA01","XMLsightingData_citiesUSA02","XMLsightingData_citiesUSA03","XMLsightingData_citiesUSA04","XMLsightingData_citiesUSA05","XMLsightingData_citiesUSA06","XMLsightingData_citiesUSA07","XMLsightingData_citiesUSA08","XMLsightingData_citiesUSA09","XMLsightingData_citiesUSA10","XMLsightingData_citiesUSA11","XMLsightingData_natparksUSA01","XMLsightingData_natparksUSA02"],"harvest_record":"https://catalog.data.gov/harvest_record/4d2aa1fc-d25b-407d-8be2-025726ebe13b","harvest_record_raw":"https://catalog.data.gov/harvest_record/4d2aa1fc-d25b-407d-8be2-025726ebe13b/raw","has_spatial":false,"identifier":"DASHLINK_223","keyword":["ames","dashlink","nasa"],"last_harvested_date":"2026-08-05T00:09:49.184913","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"Dashlink","slug":"tracking-climate-models","spatial_centroid":null,"spatial_shape":null,"theme":[],"title":"TRACKING CLIMATE MODELS"},{"_score":12.552855,"_sort":[1785888556884,12.552855,0,"92034f5d-77af-4247-a72c-ffc44ef666cf"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"undefined","hasEmail":"mailto:support-ghrc@earthdata.nasa.gov"},"description":"Understanding the mean and variability of the Earth\u2019s radiation budget (ERB) at the Top-of-Atmosphere (TOA) and surface is a fundamental quantity governing climate variability and, for that reason, NASA has been making concerted efforts to observe the ERB since1984 through two projects: ERBE and CERES, that span nearly 30 years to date.\r\rThe proposed project utilizes knowledge gained in the last 10 years through CERES data analyses and apply the knowledge to existing data to develop long-term (nearly 30 years) consistent and calibrated data product (TOA irradiances at the same radiometric scale) from multiple missions (ERBS and CERES). This project proposes to produce level 3 surface irradiance products that are consistent with observed TOA irradiances in a framework of 1D radiative transfer theory. Based on these TOA and surface irradiance products, a data product will be developed which contains the contribution of atmospheric and cloud property variability to TOA and surface irradiance variability. All algorithms used in the process are based on existing CERES algorithms. All data sets produced by this project will be available from the Atmospheric Science Data Center.","distribution":[{"@type":"dcat:Distribution","description":"A comparison of Near Concurrent Measurements from the SSMIS and CoSMIR for some Selected Channels over the Frequency Range of 50-183 GHz","downloadURL":"https://doi.org/10.1109/TGRS.2007.904038","format":"HTML","mediaType":"text/html","title":"View this dataset's publications"},{"@type":"dcat:Distribution","description":"Airborne CoSMIR Observations Between 50 and 183 GHz over Snow-Covered Sierra Mountains","downloadURL":"https://doi.org/10.1109/TGRS.2006.885410","format":"HTML","mediaType":"text/html","title":"View this dataset's publications"},{"@type":"dcat:Distribution","description":"Files may be downloaded directly to your workstation from this link","downloadURL":"https://search.earthdata.nasa.gov/search?q=gpmcosmirolyx","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"GHRC OLYMPEX project web page","downloadURL":"https://ghrc.nsstc.nasa.gov/home/field-campaigns/olympex","format":"HTML","mediaType":"text/html","title":"The dataset's project home page"},{"@type":"dcat:Distribution","description":"Instructions for citing GHRC data","downloadURL":"https://ghrc.nsstc.nasa.gov/home/about-ghrc/citing-ghrc-daac-data","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"OLYMPEX CoSMIR data ReadMe file","downloadURL":"https://ghrc.nsstc.nasa.gov/pub/fieldCampaigns/gpmValidation/olympex/CoSMIR/doc/readme_cosmir_olympex.txt","format":"HTML","mediaType":"text/html","title":"View the primary investigator's documentation for this dataset"},{"@type":"dcat:Distribution","description":"OLYMPEX Field Campaign Collection DOI","downloadURL":"http://dx.doi.org/10.5067/GPMGV/OLYMPEX/DATA101","format":"HTML","mediaType":"text/html","title":"View information related to this dataset"},{"@type":"dcat:Distribution","description":"Observations of Storm Signatures by the Recently Modified Conical Scanning Millimeter-Wave Imaging Radiometer","downloadURL":"https://doi.org/10.1109/TGRS.2012.2200690","format":"HTML","mediaType":"text/html","title":"View this dataset's publications"},{"@type":"dcat:Distribution","description":"Olympic Mountains Experiment (OLYMPEX) Micro Article","downloadURL":"https://ghrc.nsstc.nasa.gov/home/micro-articles/olympic-mountains-experiment-olympex","format":"HTML","mediaType":"text/html","title":"View a micro article on this dataset"},{"@type":"dcat:Distribution","description":"Sample Browse Image","downloadURL":"https://ghrc.nsstc.nasa.gov/pub/fieldCampaigns/gpmValidation/olympex/CoSMIR/browse/Conical_20151205.png","format":"PNG","mediaType":"image/png","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=10.5067%2FGPMGV%2FOLYMPEX%2FCOSMIR%2FDATA301","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"},{"@type":"dcat:Distribution","description":"The Olympic Mountains Experiment (OLYMPEX)","downloadURL":"https://dx.doi.org/10.1175/BAMS-D-16-0182.1","format":"HTML","mediaType":"text/html","title":"View this dataset's publications"},{"@type":"dcat:Distribution","description":"The guide document contains detailed information about the dataset","downloadURL":"https://ghrc.nsstc.nasa.gov/pub/fieldCampaigns/gpmValidation/olympex/CoSMIR/doc/gpmcosmirolyx_dataset.pdf","format":"PDF","mediaType":"application/pdf","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"University of Washington OLYMPEX project web site","downloadURL":"http://olympex.atmos.washington.edu/","format":"HTML","mediaType":"text/html","title":"View information related to this dataset"}],"identifier":"C1407077722-LARC_ASDC","issued":"2017-05-08","keyword":["atmosphere","atmospheric-radiation","earth-science"],"landingPage":"https://doi.org/10.5067/ERBE/S10N_WFOV_SF_ERBS_Regional_Edition4","language":["en-US"],"modified":"2025-03-31","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"-180.0 -90.0 180.0 90.0","temporal":"1985-01-01T00:00:00Z/1998-12-31T23:59:59Z","theme":["ERBE MEaSUREs","geospatial"],"title":"Earth Radiation area average time series through Wide-field-of-view nonscanner abroad Earth Radiation Budget Satellite"},"description":"Understanding the mean and variability of the Earth\u2019s radiation budget (ERB) at the Top-of-Atmosphere (TOA) and surface is a fundamental quantity governing climate variability and, for that reason, NASA has been making concerted efforts to observe the ERB since1984 through two projects: ERBE and CERES, that span nearly 30 years to date.\r\rThe proposed project utilizes knowledge gained in the last 10 years through CERES data analyses and apply the knowledge to existing data to develop long-term (nearly 30 years) consistent and calibrated data product (TOA irradiances at the same radiometric scale) from multiple missions (ERBS and CERES). This project proposes to produce level 3 surface irradiance products that are consistent with observed TOA irradiances in a framework of 1D radiative transfer theory. Based on these TOA and surface irradiance products, a data product will be developed which contains the contribution of atmospheric and cloud property variability to TOA and surface irradiance variability. All algorithms used in the process are based on existing CERES algorithms. All data sets produced by this project will be available from the Atmospheric Science Data Center.","distribution_titles":["View this dataset's publications","View this dataset's publications","Download this dataset","The dataset's project home page","View documentation related to this dataset","View the primary investigator's documentation for this dataset","View information related to this dataset","View this dataset's publications","View a micro article on this dataset","Get a related visualization","Google Scholar search results","View this dataset's publications","View documentation related to this dataset","View information related to this dataset"],"harvest_record":"https://catalog.data.gov/harvest_record/effca2c1-58cc-490e-8202-a1b1a79879a3","harvest_record_raw":"https://catalog.data.gov/harvest_record/effca2c1-58cc-490e-8202-a1b1a79879a3/raw","has_spatial":true,"identifier":"C1407077722-LARC_ASDC","keyword":["atmosphere","atmospheric-radiation","earth-science"],"last_harvested_date":"2026-08-05T00:09:16.884258","organization":{"aliases":[""],"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"},"popularity":0,"publisher":"NASA/LARC/SD/ASDC","slug":"earth-radiation-area-average-time-series-through-wide-field-of-view-nonscanner-abroad-eart","spatial_centroid":null,"spatial_shape":null,"theme":["ERBE MEaSUREs","geospatial"],"title":"Earth Radiation area average time series through Wide-field-of-view nonscanner abroad Earth Radiation Budget Satellite"},{"_score":8.507204,"_sort":[1785888555931,8.507204,2,"4fc3a05e-b168-4130-9d32-1e801e1860a0"],"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\nPseudo-Invariant Calibration Sites (PICS):\nLibya 4 is one of six CEOS reference Pseudo-Invariant Calibration Sites (PICS) that are CEOS Reference Test Sites. Besides the nominally good site characteristics (temporal stability, uniformity, homogeneity, etc.), these six PICS were selected by also taking into account their heritage and the large number of datasets from multiple instruments that already existed in the EO archives and the long history of characterization performed over these sites. The PICS have high reflectance and are usually made up of sand dunes with climatologically low aerosol loading and practically no vegetation. Consequently, these PICS can be used to evaluate the long-term stability of instrument and facilitate inter-comparison of multiple instruments.","distribution":[{"@type":"dcat:Distribution","description":"Data Access link for ITSD project","downloadURL":"https://nsidc.org/data/data-access-tool/HMA_DTE/versions/1/","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Data Access link for ITSD project","downloadURL":"https://nsidc.org/data/data-access-tool/HMA_DTE/versions/1/","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Data Access link for ITSD project","downloadURL":"https://nsidc.org/data/data-access-tool/HMA_DTE/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_DTE.001/","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_DTE.001/","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_DTE.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/10.5067/8DQKWY03KJWT","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=C2028568967-NSIDC_ECS&tl=1602012627%214%21%21&m=24.884853055007127%2118.480051040649414%212%211%210%210%2C2","format":"HTML","mediaType":"text/html","title":"Download this dataset through Earthdata Search"},{"@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=C2028568967-NSIDC_ECS&tl=1602012627%214%21%21&m=24.884853055007127%2118.480051040649414%212%211%210%210%2C2","format":"HTML","mediaType":"text/html","title":"Download this dataset through Earthdata Search"},{"@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=C2028568967-NSIDC_ECS&tl=1602012627%214%21%21&m=24.884853055007127%2118.480051040649414%212%211%210%210%2C2","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/10.5067/8DQKWY03KJWT","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%2F8DQKWY03KJWT","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"}],"identifier":"C1220566678-USGS_LTA","issued":"1972-11-16","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/C1220566678-USGS_LTA.html","language":["en-US"],"modified":"2025-03-31","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"DOI/USGS/EROS"},"spatial":"23.3 28.45 23.5 28.65","temporal":"1972-11-16T00:00:00Z/2023-02-28T00:00:00Z","theme":["CWIC","geospatial"],"title":"CEOS Cal Val Test Site - Libya 4 - Pseudo-Invariant Calibration Site (PICS)"},"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\nPseudo-Invariant Calibration Sites (PICS):\nLibya 4 is one of six CEOS reference Pseudo-Invariant Calibration Sites (PICS) that are CEOS Reference Test Sites. Besides the nominally good site characteristics (temporal stability, uniformity, homogeneity, etc.), these six PICS were selected by also taking into account their heritage and the large number of datasets from multiple instruments that already existed in the EO archives and the long history of characterization performed over these sites. The PICS have high reflectance and are usually made up of sand dunes with climatologically low aerosol loading and practically no vegetation. Consequently, these PICS can be used to evaluate the long-term stability of instrument and facilitate inter-comparison of multiple instruments.","distribution_titles":["Download this dataset","Download this dataset","Download this dataset","Download this dataset","Download this dataset","Download this dataset","View documentation related to this dataset","Download this dataset through Earthdata Search","Download this dataset through Earthdata Search","Download this dataset through Earthdata Search","This dataset's landing page","Google Scholar search results"],"harvest_record":"https://catalog.data.gov/harvest_record/52e9818b-3a5d-428a-b30a-db12c45e825a","harvest_record_raw":"https://catalog.data.gov/harvest_record/52e9818b-3a5d-428a-b30a-db12c45e825a/raw","has_spatial":true,"identifier":"C1220566678-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":"2026-08-05T00:09:15.931339","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"DOI/USGS/EROS","slug":"ceos-cal-val-test-site-libya-4-pseudo-invariant-calibration-site-pics","spatial_centroid":null,"spatial_shape":null,"theme":["CWIC","geospatial"],"title":"CEOS Cal Val Test Site - Libya 4 - Pseudo-Invariant Calibration Site (PICS)"},{"_score":47.467186,"_sort":[1785888525774,47.467186,2,"740213fe-ad35-4e14-af14-c37875ec9f95"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"undefined","hasEmail":"mailto:sdps@oceancolor.gsfc.nasa.gov"},"description":"This data set provides modeled surface and atmospheric fields from the Mod\u00e8le Atmosph\u00e9rique R\u00e9gionale (MAR) regional climate model (version 3.5) over the Himalayan region at 10 km spatial resolution. Modeled parameters include surface mass and energy balance components, near-surface atmospheric properties, and snowpack properties.","distribution":[{"@type":"dcat:Distribution","description":"NASA Ocean Color Web - Algorithm Description Documentation","downloadURL":"https://oceancolor.gsfc.nasa.gov/resources/atbd/","format":"HTML","mediaType":"text/html","title":"View this dataset's algorithm theoretical basis document"},{"@type":"dcat:Distribution","description":"NASA Ocean Color Web - Data Citation Guidelines","downloadURL":"https://oceancolor.gsfc.nasa.gov/resources/how-to-cite/","format":"HTML","mediaType":"text/html","title":"View information related to this dataset"},{"@type":"dcat:Distribution","description":"NASA Ocean Color Web - Processing History","downloadURL":"https://oceancolor.gsfc.nasa.gov/data/reprocessing/","format":"HTML","mediaType":"text/html","title":"View this dataset's processing history"},{"@type":"dcat:Distribution","description":"Search results for publications that cite this dataset by its DOI.","downloadURL":"https://scholar.google.com/scholar?q=10.5067%2FS3A%2FOLCI%2FL4B%2FAVW%2F2022.0","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"}],"identifier":"C1618449579-NSIDC_ECS","issued":"2000-01-01","keyword":["atmosphere","atmospheric-radiation","atmospheric-winds","earth-science","land-surface","snow-ice","surface-thermal-properties","terrestrial-hydrosphere"],"landingPage":"https://doi.org/10.5067/4DISDZEYDMGT","language":["en-US"],"modified":"2025-03-31","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"NASA NSIDC DAAC"},"spatial":"65.2 22.41 87.92 38.84","temporal":"2000-01-01T00:00:00Z/2015-12-31T23:59:59.999Z","theme":["geospatial"],"title":"High Mountain Asia MAR V3.5 Regional Climate Model Output V001"},"description":"This data set provides modeled surface and atmospheric fields from the Mod\u00e8le Atmosph\u00e9rique R\u00e9gionale (MAR) regional climate model (version 3.5) over the Himalayan region at 10 km spatial resolution. Modeled parameters include surface mass and energy balance components, near-surface atmospheric properties, and snowpack properties.","distribution_titles":["View this dataset's algorithm theoretical basis document","View information related to this dataset","View this dataset's processing history","Google Scholar search results"],"harvest_record":"https://catalog.data.gov/harvest_record/a25a3ade-fda9-43e1-b46c-684a0c438c81","harvest_record_raw":"https://catalog.data.gov/harvest_record/a25a3ade-fda9-43e1-b46c-684a0c438c81/raw","has_spatial":true,"identifier":"C1618449579-NSIDC_ECS","keyword":["atmosphere","atmospheric-radiation","atmospheric-winds","earth-science","land-surface","snow-ice","surface-thermal-properties","terrestrial-hydrosphere"],"last_harvested_date":"2026-08-05T00:08:45.774355","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"NASA NSIDC DAAC","slug":"high-mountain-asia-mar-v3-5-regional-climate-model-output-v001","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"High Mountain Asia MAR V3.5 Regional Climate Model Output V001"},{"_score":9.064884,"_sort":[1785888464891,9.064884,2,"b50d5846-2012-469f-943e-d82413160cf9"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"undefined","hasEmail":"mailto:cmr-support@earthdata.nasa.gov"},"describedBy":"https://eosweb.larc.nasa.gov/project/ceres/ceres_table","description":"The CEOS IDN is an international effort developed to assist researchers in locating information on available datasets and services.  The directory is sponsored as a service to the Earth science community.","distribution":[{"@type":"dcat:Distribution","description":"Algorithm Theoretical Basis Document (ATBD)","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/swot_mission_docs/atbd/D-105502_SWOT_ATBD_L2_LR_SSH_20230724a_cite.pdf","format":"PDF","mediaType":"application/pdf","title":"View this dataset's algorithm theoretical basis document"},{"@type":"dcat:Distribution","description":"Browse granule search results in Earthdata Search","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2799465428-POCLOUD","format":"HTML","mediaType":"text/html","title":"Download this dataset through Earthdata Search"},{"@type":"dcat:Distribution","description":"Data Subscriber","downloadURL":"https://github.com/podaac/data-subscriber","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","description":"Data Use and Citation Policy","downloadURL":"https://podaac.jpl.nasa.gov/CitingPODAAC","format":"HTML","mediaType":"text/html","title":"View this dataset's data citation policy"},{"@type":"dcat:Distribution","description":"HTTPS endpoint for data browse and download","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2799465428-POCLOUD","format":"HTML","mediaType":"text/html","title":"Download this dataset through a directory map"},{"@type":"dcat:Distribution","description":"Product Description Document (PDD)","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/swot_mission_docs/pdd/D-56407_SWOT_Product_Description_L2_LR_SSH_20231026_RevBcite.pdf","format":"PDF","mediaType":"application/pdf","title":"View this dataset's user's guide"},{"@type":"dcat:Distribution","description":"Release Note","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/swot_mission_docs/releases/SWOT_VersionC_KaRIn_Products_Release_Note.pdf","format":"PDF","mediaType":"application/pdf","title":"View information related to this dataset"},{"@type":"dcat:Distribution","description":"SWOT Mission Page","downloadURL":"https://swot.jpl.nasa.gov","format":"HTML","mediaType":"text/html","title":"The dataset's project home page"},{"@type":"dcat:Distribution","description":"SWOT Mission Page at AVISO","downloadURL":"https://www.aviso.altimetry.fr/en/missions/current-missions/swot.html","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"SWOT Mission Page at JPL","downloadURL":"https://www.jpl.nasa.gov/missions/surface-water-and-ocean-topography-swot","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"SWOT Mission Page at NASA","downloadURL":"https://www.nasa.gov/swot","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"SWOT Mission Page at PO.DAAC","downloadURL":"https://podaac.jpl.nasa.gov/swot","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"Search Granules from Bulk Reprocessing (PGC0)","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2799465428-POCLOUD&pg%5B0%5D%5Bid%5D=*PGC0*","format":"HTML","mediaType":"text/html","title":"Download this dataset"},{"@type":"dcat:Distribution","description":"Search Granules from Forward Processing (PIC0)","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2799465428-POCLOUD&pg%5B0%5D%5Bid%5D=*PIC0*","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%2FSWOT-SSH-2.0","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"},{"@type":"dcat:Distribution","description":"Thumbnail","downloadURL":"https://podaac.jpl.nasa.gov/Podaac/thumbnails/SWOT_L2_LR_SSH_2.0.jpg","format":"JPEG","mediaType":"image/jpeg","title":"Get a related visualization"}],"identifier":"NASA-0000029","issued":"2018-06-25","keyword":["agriculture","atmosphere","biological","biosphere","classification","climate-indicators","cryosphere","earth-science","human-dimensions","land-surface","oceans","paleoclimate","solid-earth","spectral-engineering","sun-earth-interactions","terrestrial-hydrosphere"],"landingPage":"http://idn.ceos.org/portals/Home.do?Portal=idn_ceos&MetadataType=0","modified":"2025-04-01","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"title":"Committee on Earth Observation Satellites (CEOS) International Directory Portal"},"description":"The CEOS IDN is an international effort developed to assist researchers in locating information on available datasets and services.  The directory is sponsored as a service to the Earth science community.","distribution_titles":["View this dataset's algorithm theoretical basis document","Download this dataset through Earthdata Search","View this dataset's data citation policy","Download this dataset through a directory map","View this dataset's user's guide","View information related to this dataset","The dataset's project home page","View documentation related to this dataset","View documentation related to this dataset","View documentation related to this dataset","View documentation related to this dataset","Download this dataset","Download this dataset","Google Scholar search results","Get a related visualization"],"harvest_record":"https://catalog.data.gov/harvest_record/936f68ba-a349-42c9-8626-daf83dbf112d","harvest_record_raw":"https://catalog.data.gov/harvest_record/936f68ba-a349-42c9-8626-daf83dbf112d/raw","has_spatial":false,"identifier":"NASA-0000029","keyword":["agriculture","atmosphere","biological","biosphere","classification","climate-indicators","cryosphere","earth-science","human-dimensions","land-surface","oceans","paleoclimate","solid-earth","spectral-engineering","sun-earth-interactions","terrestrial-hydrosphere"],"last_harvested_date":"2026-08-05T00:07:44.891263","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"National Aeronautics and Space Administration","slug":"committee-on-earth-observation-satellites-ceos-international-directory-portal","spatial_centroid":null,"spatial_shape":null,"theme":[],"title":"Committee on Earth Observation Satellites (CEOS) International Directory Portal"},{"_score":26.626717,"_sort":[1785888389264,26.626717,4,"c3562287-22ba-44fd-98ba-1740ce28cc9d"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"GeneLab Outreach","hasEmail":"mailto:genelab-outreach@lists.nasa.gov"},"description":"Global surface temperatures in 2010 tied 2005 as the warmest on record. The International Satellite Cloud Climatology Project (ISCCP) was established in 1982 as part of the World Climate Research Programme (WCRP) to collect and analyze the global distribution of clouds, their properties, and their diurnal, seasonal, and interannual variations. The LAS provides data for Monthly Near-Surface Air Temperature Averages from 1994 to 2008.","distribution":[{"@type":"dcat:Distribution","description":"GeneLab Study Page","downloadURL":"https://genelab-data.ndc.nasa.gov/genelab/accession/GLDS-354","format":"HTML","mediaType":"text/html","title":"['\"Molecular Transducers of Human Skeletal Muscle Remodeling under Different Loading States\"']"}],"identifier":"NASA-0000046","issued":"2018-06-25","keyword":["apps","arctic-sea-ice","carbon-dioxide","climate","electricity","ephemerides","geodetics","land-ice","news","radar","waves"],"landingPage":"https://data.nasa.gov/dataset/monthly-near-surface-air-temperature-averages","modified":"2025-04-23","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"spatial":"global","temporal":"1994-01-01/2008-01-01","theme":["Earth Science"],"title":"Monthly Near-Surface Air Temperature Averages"},"description":"Global surface temperatures in 2010 tied 2005 as the warmest on record. The International Satellite Cloud Climatology Project (ISCCP) was established in 1982 as part of the World Climate Research Programme (WCRP) to collect and analyze the global distribution of clouds, their properties, and their diurnal, seasonal, and interannual variations. The LAS provides data for Monthly Near-Surface Air Temperature Averages from 1994 to 2008.","distribution_titles":["['\"Molecular Transducers of Human Skeletal Muscle Remodeling under Different Loading States\"']"],"harvest_record":"https://catalog.data.gov/harvest_record/0c91d5d4-726b-4678-a796-2b35a4034e60","harvest_record_raw":"https://catalog.data.gov/harvest_record/0c91d5d4-726b-4678-a796-2b35a4034e60/raw","has_spatial":true,"identifier":"NASA-0000046","keyword":["apps","arctic-sea-ice","carbon-dioxide","climate","electricity","ephemerides","geodetics","land-ice","news","radar","waves"],"last_harvested_date":"2026-08-05T00:06:29.264208","organization":{"aliases":[""],"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"},"popularity":4,"publisher":"National Aeronautics and Space Administration","slug":"monthly-near-surface-air-temperature-averages","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Monthly Near-Surface Air Temperature Averages"},{"_score":17.48338,"_sort":[1785888358278,17.48338,4,"8d7da15d-a96e-414a-81f4-af6b6427c074"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Charles Ichoku","hasEmail":"mailto:Charles.Ichoku@nasa.gov"},"description":"Our mission is to help you picture climate change and environmental changes happening on our home planet. Here you can search for and retrieve satellite images of Earth. Download them; export them to GoogleEarth; perform basic analysis. Tracking regional and global changes around the world just got easier.","distribution":[{"@type":"dcat:Distribution","description":"API of NASA facilities.","downloadURL":"https://data.nasa.gov/docs/legacy/gvk9-iz74.json","format":"HTML","mediaType":"text/html","title":"NASA Facilities API"}],"identifier":"NASA-0000087__2","issued":"2018-06-25","keyword":["atmosphere","earth-science","energy","eos","land","life","ocean","raw","web-mapping"],"modified":"2025-07-14","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"theme":["Earth Science"],"title":"NASA Earth Observations (NEO)"},"description":"Our mission is to help you picture climate change and environmental changes happening on our home planet. Here you can search for and retrieve satellite images of Earth. Download them; export them to GoogleEarth; perform basic analysis. Tracking regional and global changes around the world just got easier.","distribution_titles":["NASA Facilities API"],"harvest_record":"https://catalog.data.gov/harvest_record/4080b2a3-fe70-45bb-bdab-30cbc770cfe5","harvest_record_raw":"https://catalog.data.gov/harvest_record/4080b2a3-fe70-45bb-bdab-30cbc770cfe5/raw","has_spatial":false,"identifier":"NASA-0000087__2","keyword":["atmosphere","earth-science","energy","eos","land","life","ocean","raw","web-mapping"],"last_harvested_date":"2026-08-05T00:05:58.278166","organization":{"aliases":[""],"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"},"popularity":4,"publisher":"National Aeronautics and Space Administration","slug":"nasa-earth-observations-neo-a6d58","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"NASA Earth Observations (NEO)"},{"_score":16.198883,"_sort":[1785888326152,16.198883,5,"de4458d9-0042-4e82-b5d0-4ddb4e7d9ced"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"undefined","hasEmail":"mailto:metadata@ciesin.columbia.edu"},"description":"The Intergovernmental Panel on Climate Change (IPCC) Socio-Economic Baseline Dataset consists of population, human development, economic, water resources, land cover, land use, agriculture, food, energy and biodiversity data . This dataset was collated by IPCC from a variety of sources such as The World Bank, United Nations Environment Programme (UNEP), and Food and Agriculture Organization of the United Nations (FAO), and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).","distribution":[{"@type":"dcat:Distribution","description":"Sample browse graphic of the data set.","downloadURL":"https://sedac.ciesin.columbia.edu/downloads/maps/ipcc/ipcc-socio-economic-baseline/sedac-logo.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%2FH4WM1BB7","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"}],"identifier":"C179001801-SEDAC","issued":"1998-12-31","keyword":["earth-science","economic-resources","human-dimensions","socioeconomics"],"language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"SEDAC"},"references":["https://doi.org/10.7927/H41C1TT4","https://doi.org/10.7927/H4542KJV","https://doi.org/10.7927/H4FT8J0X","https://doi.org/10.7927/H4HD7SKJ","https://doi.org/10.7927/H4N29TWJ","https://doi.org/10.7927/H4RV0KMH","https://doi.org/10.7927/H4XG9P2R"],"spatial":"-180.0 -90.0 180.0 90.0","temporal":"1980-01-01T00:00:00Z/2025-01-01T00:00:00Z","theme":["IPCC","geospatial"],"title":"IPCC Socio-Economic Baseline Dataset"},"description":"The Intergovernmental Panel on Climate Change (IPCC) Socio-Economic Baseline Dataset consists of population, human development, economic, water resources, land cover, land use, agriculture, food, energy and biodiversity data . This dataset was collated by IPCC from a variety of sources such as The World Bank, United Nations Environment Programme (UNEP), and Food and Agriculture Organization of the United Nations (FAO), and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).","distribution_titles":["Get a related visualization","Google Scholar search results"],"harvest_record":"https://catalog.data.gov/harvest_record/a642d2d0-6c51-4e98-9295-6b09d1a4f8bd","harvest_record_raw":"https://catalog.data.gov/harvest_record/a642d2d0-6c51-4e98-9295-6b09d1a4f8bd/raw","has_spatial":true,"identifier":"C179001801-SEDAC","keyword":["earth-science","economic-resources","human-dimensions","socioeconomics"],"last_harvested_date":"2026-08-05T00:05:26.152090","organization":{"aliases":[""],"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"},"popularity":5,"publisher":"SEDAC","slug":"ipcc-socio-economic-baseline-dataset","spatial_centroid":null,"spatial_shape":null,"theme":["IPCC","geospatial"],"title":"IPCC Socio-Economic Baseline Dataset"},{"_score":9.224371,"_sort":[1785888276901,9.224371,89,"6deb8b9e-28d8-407a-a0f4-3fad649807dc"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Gerald Steeman","hasEmail":"mailto:Gerald.Steeman@nasa.gov"},"description":"The NTRS is a valuable resource for researchers, students, educators, and the public to access NASA's current and historical technical literature and engineering results. Over 500,000 aerospace-related citations, over 200,000 full-text online documents, and over 500,000 images and videos are available. NTRS content continues to grow as new scientific and technical information (STI) is created or funded by NASA. The types of information found in the NTRS include: conference papers, journal articles, meeting papers, patents, research reports, images, movies, and technical videos.  NTRS is&#160;Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) enabled","identifier":"NASA-0000091","issued":"2018-06-25","keyword":["aeronautics","apollo","climate","earth-science","google","imagery","institutional","journal-papers","literature","moon","naca","nix","ntrs","operations","pdf","space-science","sti","technical-reports"],"landingPage":"https://data.nasa.gov/dataset/nasa-technical-reports-server-ntrs","modified":"2025-07-17","programCode":["026:046"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"theme":["Management/Operations"],"title":"NASA Technical Reports Server (NTRS)"},"description":"The NTRS is a valuable resource for researchers, students, educators, and the public to access NASA's current and historical technical literature and engineering results. Over 500,000 aerospace-related citations, over 200,000 full-text online documents, and over 500,000 images and videos are available. NTRS content continues to grow as new scientific and technical information (STI) is created or funded by NASA. The types of information found in the NTRS include: conference papers, journal articles, meeting papers, patents, research reports, images, movies, and technical videos.  NTRS is&#160;Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) enabled","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/7555e814-1227-4f88-adfb-11e4b0b2723e","harvest_record_raw":"https://catalog.data.gov/harvest_record/7555e814-1227-4f88-adfb-11e4b0b2723e/raw","has_spatial":false,"identifier":"NASA-0000091","keyword":["aeronautics","apollo","climate","earth-science","google","imagery","institutional","journal-papers","literature","moon","naca","nix","ntrs","operations","pdf","space-science","sti","technical-reports"],"last_harvested_date":"2026-08-05T00:04:36.901240","organization":{"aliases":[""],"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"},"popularity":89,"publisher":"National Aeronautics and Space Administration","slug":"nasa-technical-reports-server-ntrs","spatial_centroid":null,"spatial_shape":null,"theme":["Management/Operations"],"title":"NASA Technical Reports Server (NTRS)"},{"_score":9.584406,"_sort":[1785888153469,9.584406,11,"21ebd88a-6234-463c-90a5-135a6b01fdaf"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Gerald Steeman","hasEmail":"mailto:Gerald.Steeman@nasa.gov"},"description":"The NASA Thesaurus contains the authorized NASA subject terms used to index and retrieve materials in the NASA Technical Reports Server (NTRS) and the NTRS Registered (Formerly NA&SD). The scope of this controlled vocabulary includes not only aerospace engineering, but all supporting areas of engineering and physics, the natural space sciences (astronomy, astrophysics, planetary science), Earth sciences, and the biological sciences. The NASA Thesaurus contains over 18,400 subject terms, 4,300 definitions, and more than 4,500 USE cross references.","identifier":"NASA-0000092","issued":"2018-06-25","keyword":["aeronautics","climate","earth-science","engineering","geology","institutional","journal-papers","operations","photomicrographs","space-science","technical-reports","wise"],"landingPage":"https://data.nasa.gov/dataset/nasa-thesaurus","modified":"2025-07-17","programCode":["026:046"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"theme":["Management/Operations"],"title":"NASA Thesaurus"},"description":"The NASA Thesaurus contains the authorized NASA subject terms used to index and retrieve materials in the NASA Technical Reports Server (NTRS) and the NTRS Registered (Formerly NA&SD). The scope of this controlled vocabulary includes not only aerospace engineering, but all supporting areas of engineering and physics, the natural space sciences (astronomy, astrophysics, planetary science), Earth sciences, and the biological sciences. The NASA Thesaurus contains over 18,400 subject terms, 4,300 definitions, and more than 4,500 USE cross references.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/2f3c631b-472c-432d-8047-defc6d8733cd","harvest_record_raw":"https://catalog.data.gov/harvest_record/2f3c631b-472c-432d-8047-defc6d8733cd/raw","has_spatial":false,"identifier":"NASA-0000092","keyword":["aeronautics","climate","earth-science","engineering","geology","institutional","journal-papers","operations","photomicrographs","space-science","technical-reports","wise"],"last_harvested_date":"2026-08-05T00:02:33.469991","organization":{"aliases":[""],"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"},"popularity":11,"publisher":"National Aeronautics and Space Administration","slug":"nasa-thesaurus","spatial_centroid":null,"spatial_shape":null,"theme":["Management/Operations"],"title":"NASA Thesaurus"},{"_score":26.12393,"_sort":[1785888102904,26.12393,3,"3ab3465f-af76-48c8-b15a-4a5804328c0e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"John M. Kusterer","hasEmail":"mailto:john.m.kusterer@nasa.gov"},"description":"Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth\u2019s radiation budget and climate. It flies in formation with five other satellites in the international \u201cA-Train\u201d (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.","identifier":"NASA-0000206","issued":"2018-06-25","keyword":["aerosol","atmospheric-science","climate","cloud","eos","radiation","satellite"],"landingPage":"https://data.nasa.gov/dataset/calipso-wide-field-camera-wfc-l1b-science-1-km-registered-science-data-v3-01","modified":"2025-07-17","programCode":["026:004"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"temporal":"2006-06-13/2011-10-31","theme":["Earth Science"],"title":"CALIPSO Wide Field Camera (WFC)  L1B Science 1 km Registered  Science Data V3-01"},"description":"Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth\u2019s radiation budget and climate. It flies in formation with five other satellites in the international \u201cA-Train\u201d (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/d9dbc83c-2b5c-4ab0-b4e6-d455c270ff65","harvest_record_raw":"https://catalog.data.gov/harvest_record/d9dbc83c-2b5c-4ab0-b4e6-d455c270ff65/raw","has_spatial":false,"identifier":"NASA-0000206","keyword":["aerosol","atmospheric-science","climate","cloud","eos","radiation","satellite"],"last_harvested_date":"2026-08-05T00:01:42.904877","organization":{"aliases":[""],"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"},"popularity":3,"publisher":"National Aeronautics and Space Administration","slug":"calipso-wide-field-camera-wfc-l1b-science-1-km-registered-science-data-v3-01","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CALIPSO Wide Field Camera (WFC)  L1B Science 1 km Registered  Science Data V3-01"},{"_score":14.124092,"_sort":[1785888091407,14.124092,1,"189e934f-7c4e-4a6c-b31a-fcc9715793ef"],"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 GPM Ground Validation NOAA CPC Morphing Technique (CMORPH) IPHEx dataset consists of global precipitation analyses data produced by the NOAA Climate Prediction Center (CPC) during the Global Precipitation Mission (GPM) Integrated Precipitation and Hydrology Experiment (IPHEx) field campaign in North Carolina. The goal of IPHEx was to evaluate the accuracy of satellite precipitation measurements and use the collected data for hydrology models in the region.  The CPC morphing technique uses precipitation estimates from low orbiter satellite microwave observations to produce global precipitation analyses at a high temporal and spatial resolution. CMORPH data has been selected from May 1, 2014 through June 14, 2014, during the IPHEx field campaign. These data files are available in raw binary and netCDF-4 file format.","identifier":"C1979134074-GHRC_DAAC","issued":"2016-04-19","keyword":["atmosphere","earth-science","precipitation"],"landingPage":"https://doi.org/10.5067/GPMGV/IPHEX/CMORPH/DATA201","language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"NASA/MSFC/GHRC"},"spatial":"-179.964 -59.9636 179.964 59.9636","temporal":"2014-05-01T00:00:00Z/2014-06-14T23:59:59Z","theme":["IPHEx","geospatial"],"title":"GPM GROUND VALIDATION NOAA CPC MORPHING TECHNIQUE (CMORPH) IPHEX V1"},"description":"The GPM Ground Validation NOAA CPC Morphing Technique (CMORPH) IPHEx dataset consists of global precipitation analyses data produced by the NOAA Climate Prediction Center (CPC) during the Global Precipitation Mission (GPM) Integrated Precipitation and Hydrology Experiment (IPHEx) field campaign in North Carolina. The goal of IPHEx was to evaluate the accuracy of satellite precipitation measurements and use the collected data for hydrology models in the region.  The CPC morphing technique uses precipitation estimates from low orbiter satellite microwave observations to produce global precipitation analyses at a high temporal and spatial resolution. CMORPH data has been selected from May 1, 2014 through June 14, 2014, during the IPHEx field campaign. These data files are available in raw binary and netCDF-4 file format.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/a7e4ecea-1ef1-456a-bde4-0d170e5f659e","harvest_record_raw":"https://catalog.data.gov/harvest_record/a7e4ecea-1ef1-456a-bde4-0d170e5f659e/raw","has_spatial":true,"identifier":"C1979134074-GHRC_DAAC","keyword":["atmosphere","earth-science","precipitation"],"last_harvested_date":"2026-08-05T00:01:31.407857","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"NASA/MSFC/GHRC","slug":"gpm-ground-validation-noaa-cpc-morphing-technique-cmorph-iphex-v1","spatial_centroid":null,"spatial_shape":null,"theme":["IPHEx","geospatial"],"title":"GPM GROUND VALIDATION NOAA CPC MORPHING TECHNIQUE (CMORPH) IPHEX V1"},{"_score":25.982845,"_sort":[1785888020083,25.982845,0,"bc0f391e-7bcb-4cee-ae1d-e44739561de1"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Vlad Popescu","hasEmail":"mailto:vmpopescu@gmail.com"},"description":"Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth\u2019s radiation budget and climate. It flies in formation with five other satellites in the international \u201cA-Train\u201d (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.","identifier":"NASA-0000196","issued":"2018-06-25","keyword":["aerosol","atmospheric-science","climate","cloud","eos","radiation","satellite"],"landingPage":"https://data.nasa.gov/dataset/calipso-lidar-l1b-profile-data-v2-01","modified":"2025-07-17","programCode":["026:004"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"temporal":"2006-06-13/2008-09-13","theme":["Earth Science"],"title":"CALIPSO Lidar L1B Profile Data V2-01"},"description":"Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth\u2019s radiation budget and climate. It flies in formation with five other satellites in the international \u201cA-Train\u201d (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/24e4e31a-5038-4407-a0e4-ca2c9254f8b2","harvest_record_raw":"https://catalog.data.gov/harvest_record/24e4e31a-5038-4407-a0e4-ca2c9254f8b2/raw","has_spatial":false,"identifier":"NASA-0000196","keyword":["aerosol","atmospheric-science","climate","cloud","eos","radiation","satellite"],"last_harvested_date":"2026-08-05T00:00:20.083639","organization":{"aliases":[""],"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"},"popularity":0,"publisher":"National Aeronautics and Space Administration","slug":"calipso-lidar-l1b-profile-data-v2-01","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CALIPSO Lidar L1B Profile Data V2-01"},{"_score":26.067225,"_sort":[1785887991139,26.067225,0,"ddf98d6a-48d8-4819-a307-7f9643e1de67"],"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":"Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth\u2019s radiation budget and climate. It flies in formation with five other satellites in the international \u201cA-Train\u201d (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.","identifier":"NASA-0000153","issued":"2018-06-25","keyword":["aerosol","atmospheric-science","climate","cloud","eos","radiation","satellite"],"modified":"2025-07-17","programCode":["026:004"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"temporal":"2011-11-01/2013-02-28","theme":["Earth Science"],"title":"CALIPSO Lidar L2 1/3 km Cloud Layer Data V3-02"},"description":"Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth\u2019s radiation budget and climate. It flies in formation with five other satellites in the international \u201cA-Train\u201d (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/96dc39b3-8bfc-4ead-b15d-e8a26bc30d40","harvest_record_raw":"https://catalog.data.gov/harvest_record/96dc39b3-8bfc-4ead-b15d-e8a26bc30d40/raw","has_spatial":false,"identifier":"NASA-0000153","keyword":["aerosol","atmospheric-science","climate","cloud","eos","radiation","satellite"],"last_harvested_date":"2026-08-04T23:59:51.139981","organization":{"aliases":[""],"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"},"popularity":0,"publisher":"National Aeronautics and Space Administration","slug":"calipso-lidar-l2-1-3-km-cloud-layer-data-v3-02","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CALIPSO Lidar L2 1/3 km Cloud Layer Data V3-02"},{"_score":19.332027,"_sort":[1785887931240,19.332027,2,"7a46d8bf-f377-4ba9-aecb-00e532d6703b"],"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":"C1220567944-USGS_LTA","issued":"1972-01-01","keyword":["agriculture","biosphere","earth-science","forest-science","habitat-conversion-fragmentation","human-dimensions","terrestrial-ecosystems","vegetation"],"landingPage":"https://cmr.earthdata.nasa.gov:443/search/concepts/C1220567944-USGS_LTA.html","language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"DOI/USGS/EROS"},"spatial":"-89.25 16.0 -88.0 19.0","temporal":"1972-01-01T00:00:00Z/2022-01-17T00:00:00Z","theme":["CWIC","geospatial"],"title":"USGS Global Forest Observations Initiative (GFOI) Belize"},"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/43909416-2953-4410-a460-d4fde12f8627","harvest_record_raw":"https://catalog.data.gov/harvest_record/43909416-2953-4410-a460-d4fde12f8627/raw","has_spatial":true,"identifier":"C1220567944-USGS_LTA","keyword":["agriculture","biosphere","earth-science","forest-science","habitat-conversion-fragmentation","human-dimensions","terrestrial-ecosystems","vegetation"],"last_harvested_date":"2026-08-04T23:58:51.240297","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"DOI/USGS/EROS","slug":"usgs-global-forest-observations-initiative-gfoi-belize","spatial_centroid":null,"spatial_shape":null,"theme":["CWIC","geospatial"],"title":"USGS Global Forest Observations Initiative (GFOI) Belize"},{"_score":9.070789,"_sort":[1785887765489,9.070789,22,"da30da05-9880-478d-becf-5fd037f94d01"],"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 GCMD database holds more than 30,000 descriptions of Earth science data sets and services covering all aspects of Earth and environmental sciences.  The mission of the GCMD is to (1) Assist the scientific community in the discovery of Earth science data, related services, and ancillary information (platforms, instruments, projects, data centers/service providers); and (2) Provide discovery/collection-level metadata of Earth science resources and provide scientists a comprehensive and high quality database to reduce overall expenditures for scientific data collection and dissemination.","identifier":"NASA-0000042","issued":"2018-06-25","keyword":["agriculture","atmosphere","biology","biosphere","climate","cryosphere","earth-science","engineering","geospatial","hydrosphere","land","oceans","operations","paleoclimate","spectrometry","sun-earth-interaction","wise","wwhgd"],"landingPage":"https://data.nasa.gov/dataset/global-change-master-directory-gcmd","modified":"2025-07-17","programCode":["026:001","026:005"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"theme":["Earth Science"],"title":"Global Change Master Directory (GCMD)"},"description":"The GCMD database holds more than 30,000 descriptions of Earth science data sets and services covering all aspects of Earth and environmental sciences.  The mission of the GCMD is to (1) Assist the scientific community in the discovery of Earth science data, related services, and ancillary information (platforms, instruments, projects, data centers/service providers); and (2) Provide discovery/collection-level metadata of Earth science resources and provide scientists a comprehensive and high quality database to reduce overall expenditures for scientific data collection and dissemination.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/5b6f9247-0491-4312-92db-493047f89f5e","harvest_record_raw":"https://catalog.data.gov/harvest_record/5b6f9247-0491-4312-92db-493047f89f5e/raw","has_spatial":false,"identifier":"NASA-0000042","keyword":["agriculture","atmosphere","biology","biosphere","climate","cryosphere","earth-science","engineering","geospatial","hydrosphere","land","oceans","operations","paleoclimate","spectrometry","sun-earth-interaction","wise","wwhgd"],"last_harvested_date":"2026-08-04T23:56:05.489228","organization":{"aliases":[""],"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"},"popularity":22,"publisher":"National Aeronautics and Space Administration","slug":"global-change-master-directory-gcmd","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Global Change Master Directory (GCMD)"},{"_score":19.332027,"_sort":[1785887748975,19.332027,4,"8f71de5e-00c8-46fd-8759-d9dcc22d8eaa"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"NSIDC Services","hasEmail":"mailto:nsidc@nsidc.org"},"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":[{"@type":"dcat:Distribution","description":"Direct download via HTTPS protocol.","downloadURL":"https://n5eil01u.ecs.nsidc.org/SMAP/SPL2SMAP_S.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/ASB0EQO2LYJV","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=SPL2SMAP_S+V003","format":"HTML","mediaType":"text/html","title":"Download this dataset through Earthdata Search"},{"@type":"dcat:Distribution","description":"Search and filter data files using a map-based interface","downloadURL":"https://nsidc.org/data/data-access-tool/SPL2SMAP_S/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%2FASB0EQO2LYJV","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"},{"@type":"dcat:Distribution","description":"This application allows you to interactively browse global satellite imagery within hours of it being acquired. You can also save it, share it, and download the underlying data.","downloadURL":"https://worldview.earthdata.nasa.gov/?v=-198%2C-80%2C167%2C89&l=SMAP_Sentinel-1_L2_Active_Passive_Soil_Moisture%2CCoastlines_15m%2CMODIS_Terra_CorrectedReflectance_TrueColor","format":"HTML","mediaType":"text/html","title":"Get a related visualization through WORLDVIEW"}],"identifier":"C1220567925-USGS_LTA","issued":"1972-01-01","keyword":["agriculture","earth-science","forest-science"],"landingPage":"https://cmr.earthdata.nasa.gov:443/search/concepts/C1220567925-USGS_LTA.html","language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"DOI/USGS/EROS"},"spatial":"-87.5 10.75 -83.0 16.0","temporal":"1972-01-01T00:00:00Z/2022-01-17T00:00:00Z","theme":["CWIC","geospatial"],"title":"USGS Global Forest Observations Initiative (GFOI) Nicaragua"},"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":["Download this dataset","View documentation related to this dataset","Download this dataset through Earthdata Search","Download this dataset","Google Scholar search results","Get a related visualization through WORLDVIEW"],"harvest_record":"https://catalog.data.gov/harvest_record/b758e114-58ae-4a39-8394-c3dfa3395247","harvest_record_raw":"https://catalog.data.gov/harvest_record/b758e114-58ae-4a39-8394-c3dfa3395247/raw","has_spatial":true,"identifier":"C1220567925-USGS_LTA","keyword":["agriculture","earth-science","forest-science"],"last_harvested_date":"2026-08-04T23:55:48.975073","organization":{"aliases":[""],"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"},"popularity":4,"publisher":"DOI/USGS/EROS","slug":"usgs-global-forest-observations-initiative-gfoi-nicaragua","spatial_centroid":null,"spatial_shape":null,"theme":["CWIC","geospatial"],"title":"USGS Global Forest Observations Initiative (GFOI) Nicaragua"},{"_score":26.50022,"_sort":[1785887634390,26.50022,1,"785a68d1-5c16-4c3c-a0e0-e98ec53ace42"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"John M. Kusterer","hasEmail":"mailto:support-asdc@earthdata.nasa.gov"},"describedBy":"https://eosweb.larc.nasa.gov/project/calipso/calipso_table","description":"Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth\u2019s radiation budget and climate. It flies in formation with five other satellites in the international 'A-Train' (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.","identifier":"NASA-0000027","issued":"2018-06-25","keyword":["aerosols","climate","clouds","eos","radiation","satellite"],"modified":"2025-07-17","programCode":["026:004"],"publisher":{"@type":"org:Organization","name":"National Aeronautics and Space Administration"},"theme":["Earth Science"],"title":"Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)"},"description":"Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth\u2019s radiation budget and climate. It flies in formation with five other satellites in the international 'A-Train' (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/209558a1-6a33-4e64-ba04-d329a4f8cb04","harvest_record_raw":"https://catalog.data.gov/harvest_record/209558a1-6a33-4e64-ba04-d329a4f8cb04/raw","has_spatial":false,"identifier":"NASA-0000027","keyword":["aerosols","climate","clouds","eos","radiation","satellite"],"last_harvested_date":"2026-08-04T23:53:54.390167","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"National Aeronautics and Space Administration","slug":"cloud-aerosol-lidar-and-infrared-pathfinder-satellite-observations-calipso","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)"},{"_score":13.609723,"_sort":[1785887569463,13.609723,1,"2aee0772-ae90-4d32-bb13-9b62e07ca09b"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Sawaengphokhai Parnchai","hasEmail":"mailto:parnchai.k.sawaengphokhai@nasa.gov"},"description":"FLASH_TISA_Terra-NOAA20_Version4B is the Fast Longwave And SHortwave Fluxes (FLASHFlux) Daily Gridded Single Satellite Top-of-Atmosphere (TOA) and Surfaces/Clouds Version 4B data product. This product contains low latency (< 7 days from observations) combined Terra and NOAA-20 FLASHFlux Single Scanner Footprint (SSF) globally gridded TOA and parameterized surface radiative fluxes for applied science uses. Data collection for this product is in progress.\r\n\r\nFLASHFlux data are a product line of the Clouds and the Earth's Radiant Energy Systems (CERES) project designed for processing and release of TOA and surface radiative fluxes for applied sciences and educations uses. The FLASHFlux data product is a rapid release product based upon 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, Aqua, and NOAA-20 spacecrafts. While of exceptional fidelity, these data products require a considerable amount of processing time to assure quality, verify accuracy, and assess precision. The result is that CERES data are typically released up to six months after acquisition of the initial measurements. For climate studies, such delays are of little consequence 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 few days of the initial measurements, with some calibration accuracy requirements relaxed to gain speed. \r\n\r\nThe SSF TOA/Surface Fluxes and Clouds product contains one hour of instantaneous FLASHFlux data for a single CERES scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Moderate-Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites and meteorological and ozone information from the GEOS-5 FP-IT Atmospheric Data Assimilation System (GEOS-5 ADAS). NOAA-20 SSF combine instantneous CERES data with scene information from the Visible Infrared Imaging Radiameter Suite (VIIRS) with 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 NET, surface fluxes using the Langley parameterized shortwave and longwave algorithms, and clouds information. CERES is a key component of the Earth Observing System (EOS) program. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES mission is a follow on 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 (FM5) was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite and CERES instrument (FM6) was launched on board NOAA's next generation of polar-orbiting satellites on November 18, 2017.","distribution":[{"@type":"dcat:Distribution","description":"ASDC Data and Information for CERES","downloadURL":"https://asdc.larc.nasa.gov/project/CERES","format":"HTML","mediaType":"text/html","title":"View documentation related to this dataset"},{"@type":"dcat:Distribution","description":"Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth\u2019s Radiant Energy System Instrument on the Terra Satellite. Part II: Validation","downloadURL":"https://asdc.larc.nasa.gov/documents/ceres/readme/JTECHA_2590.pdf","format":"PDF","mediaType":"application/pdf","title":"View this dataset's publications"},{"@type":"dcat:Distribution","description":"CERES Data Page","downloadURL":"https://ceres.larc.nasa.gov/data/#flashflux-gridded-fluxes-level-3","format":"HTML","mediaType":"text/html","title":"Subset this dataset using a web based subsetter"},{"@type":"dcat:Distribution","description":"CERES project home page","downloadURL":"https://ceres.larc.nasa.gov/","format":"HTML","mediaType":"text/html","title":"The dataset's project home page"},{"@type":"dcat:Distribution","description":"CERES/Terra Regional Mean TOA Flux Uncertainties","downloadURL":"https://asdc.larc.nasa.gov/documents/ceres/readme/region_mean_attach_C.pdf","format":"PDF","mediaType":"application/pdf","title":"View this dataset's documented anomalies"},{"@type":"dcat:Distribution","description":"DOI data set landing page for FLASH_TISA_Terra-Aqua_Version4A","downloadURL":"https://doi.org/10.5067/TERRA-AQUA/CERES/FLASH_TISA_L3.004A","format":"HTML","mediaType":"text/html","title":"This dataset's landing page"},{"@type":"dcat:Distribution","description":"Earthdata Search for FLASH_TISA_Terra-Aqua_Version4A (NASA Application to search, discover, visualize, refine, and access NASA Earth Observation data)","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1719147151-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%2FTERRA-NOAA20%2FCERES%2FFLASH_TISA_L3.004B","format":"HTML","mediaType":"text/html","title":"Google Scholar search results"},{"@type":"dcat:Distribution","downloadURL":"https://ceres-tool.larc.nasa.gov/ord-tool/jsp/FLASH_TISASelection.jsp","format":"HTML","mediaType":"text/html","title":"Download this dataset through the CERES Ordering Tool"}],"identifier":"C2634012953-LARC_ASDC","issued":"2022-10-01","keyword":["aerosols","atmosphere","atmospheric-radiation","clouds","earth-science"],"landingPage":"https://doi.org/10.5067/TERRA-NOAA20/CERES/FLASH_TISA_L3.004B","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":"2022-10-01T00:00:00Z/2023-03-20T00:00:00Z","theme":["FLASHFLUX","geospatial"],"title":"FLASHFlux Daily Gridded Single Satellite TOA and Surfaces/Clouds data Version 4B"},"description":"FLASH_TISA_Terra-NOAA20_Version4B is the Fast Longwave And SHortwave Fluxes (FLASHFlux) Daily Gridded Single Satellite Top-of-Atmosphere (TOA) and Surfaces/Clouds Version 4B data product. This product contains low latency (< 7 days from observations) combined Terra and NOAA-20 FLASHFlux Single Scanner Footprint (SSF) globally gridded TOA and parameterized surface radiative fluxes for applied science uses. Data collection for this product is in progress.\r\n\r\nFLASHFlux data are a product line of the Clouds and the Earth's Radiant Energy Systems (CERES) project designed for processing and release of TOA and surface radiative fluxes for applied sciences and educations uses. The FLASHFlux data product is a rapid release product based upon 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, Aqua, and NOAA-20 spacecrafts. While of exceptional fidelity, these data products require a considerable amount of processing time to assure quality, verify accuracy, and assess precision. The result is that CERES data are typically released up to six months after acquisition of the initial measurements. For climate studies, such delays are of little consequence 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 few days of the initial measurements, with some calibration accuracy requirements relaxed to gain speed. \r\n\r\nThe SSF TOA/Surface Fluxes and Clouds product contains one hour of instantaneous FLASHFlux data for a single CERES scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Moderate-Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites and meteorological and ozone information from the GEOS-5 FP-IT Atmospheric Data Assimilation System (GEOS-5 ADAS). NOAA-20 SSF combine instantneous CERES data with scene information from the Visible Infrared Imaging Radiameter Suite (VIIRS) with 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 NET, surface fluxes using the Langley parameterized shortwave and longwave algorithms, and clouds information. CERES is a key component of the Earth Observing System (EOS) program. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES mission is a follow on 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 (FM5) was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite and CERES instrument (FM6) was launched on board NOAA's next generation of polar-orbiting satellites on November 18, 2017.","distribution_titles":["View documentation related to this dataset","View this dataset's publications","Subset this dataset using a web based subsetter","The dataset's project home page","View this dataset's documented anomalies","This dataset's landing page","Download this dataset through Earthdata Search","View this dataset's data citation policy","Google Scholar search results","Download this dataset through the CERES Ordering Tool"],"harvest_record":"https://catalog.data.gov/harvest_record/6de42fb2-d064-4e5a-b0e6-27ccb4284e43","harvest_record_raw":"https://catalog.data.gov/harvest_record/6de42fb2-d064-4e5a-b0e6-27ccb4284e43/raw","has_spatial":true,"identifier":"C2634012953-LARC_ASDC","keyword":["aerosols","atmosphere","atmospheric-radiation","clouds","earth-science"],"last_harvested_date":"2026-08-04T23:52:49.463978","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"NASA/LARC/SD/ASDC","slug":"flashflux-daily-gridded-single-satellite-toa-and-surfaces-clouds-data-version-4b","spatial_centroid":null,"spatial_shape":null,"theme":["FLASHFLUX","geospatial"],"title":"FLASHFlux Daily Gridded Single Satellite TOA and Surfaces/Clouds data Version 4B"},{"_score":19.444536,"_sort":[1785887077551,19.444536,3,"cbea61b8-4f67-4d14-ad5d-660fc6d3b743"],"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 One-Eighth Degree Urban Land Extent Projection and Base Year Grids by SSP Scenarios, 2000-2100 consists of global SSP-consistent spatial urban land fraction data for the base year 2000 and projections at ten-year intervals for 2010-2100 at a resolution of one-eighth degree (7.5 arc-minutes). Spatial urban land projections are key inputs for the analysis of land use, energy use, and emissions, as well as for the assessment of climate change vulnerability, impacts and adaptation. This data set presents a set of global, spatially explicit urban land scenarios that are consistent with the Shared Socioeconomic Pathways (SSPs) to produce an empirically-grounded set of urban land spatial distributions over the 21st century. A data-science approach is used exploiting 15 diverse data sets, including a newly available 40-year global time series of fine-spatial-resolution remote sensing observations from the Landsat satellite series. The SSPs are developed to support future climate and global change research, the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6), along with Special Reports.","identifier":"C2205031324-SEDAC","issued":"2021-04-05","keyword":["earth-science","land-surface","land-use-land-cover"],"language":["en-US"],"modified":"2025-07-17","programCode":["026:001"],"publisher":{"@type":"org:Organization","name":"SEDAC"},"spatial":"-180.0 -90.0 180.0 90.0","temporal":"2000-01-01T00:00:00Z/2100-12-31T00:00:00Z","theme":["SSP","geospatial"],"title":"Global One-Eighth Degree Urban Land Extent Projection and Base Year Grids by SSP Scenarios, 2000-2100"},"description":"The Global One-Eighth Degree Urban Land Extent Projection and Base Year Grids by SSP Scenarios, 2000-2100 consists of global SSP-consistent spatial urban land fraction data for the base year 2000 and projections at ten-year intervals for 2010-2100 at a resolution of one-eighth degree (7.5 arc-minutes). Spatial urban land projections are key inputs for the analysis of land use, energy use, and emissions, as well as for the assessment of climate change vulnerability, impacts and adaptation. This data set presents a set of global, spatially explicit urban land scenarios that are consistent with the Shared Socioeconomic Pathways (SSPs) to produce an empirically-grounded set of urban land spatial distributions over the 21st century. A data-science approach is used exploiting 15 diverse data sets, including a newly available 40-year global time series of fine-spatial-resolution remote sensing observations from the Landsat satellite series. The SSPs are developed to support future climate and global change research, the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6), along with Special Reports.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/f5eac6ba-b42b-4665-bc70-fa90783af4f9","harvest_record_raw":"https://catalog.data.gov/harvest_record/f5eac6ba-b42b-4665-bc70-fa90783af4f9/raw","has_spatial":true,"identifier":"C2205031324-SEDAC","keyword":["earth-science","land-surface","land-use-land-cover"],"last_harvested_date":"2026-08-04T23:44:37.551307","organization":{"aliases":[""],"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"},"popularity":3,"publisher":"SEDAC","slug":"global-one-eighth-degree-urban-land-extent-projection-and-base-year-grids-by-ssp-2000-2100","spatial_centroid":null,"spatial_shape":null,"theme":["SSP","geospatial"],"title":"Global One-Eighth Degree Urban Land Extent Projection and Base Year Grids by SSP Scenarios, 2000-2100"},{"_score":10.372822,"_sort":[1785887007579,10.372822,2,"0f54a40f-4385-413a-9dc0-4587d3148b07"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"IRSA Support","hasEmail":"mailto:irsasupport@ipac.caltech.edu"},"description":"The MODIS/Aqua Aerosol Cloud Water Vapor Ozone 8-Day L3 Global 1Deg CMG product (MYD08_E3) contains 8-Day 1 degree 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. \r\n\r\nThe MYD08_E3 contains nearly 1000 statistical datasets (SDS's) that are derived from the Level-3 MODIS Atmosphere Daily Global Product. Statistics are computed over a 1 degree equal-angle lat-lon grid that spans an 8-Day 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.\r\n\r\nMYD08_E3 product files are stored in Hierarchical Data Format (HDF-EOS). Each gridded global parameter is stored as Scientific Data Sets (SDS) within the file. \r\n\r\nThe MODIS 8-Day 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.\r\n\r\nFor more information about the MYD08_E3 product, please visit the MODIS-Atmosphere site at:\r\nhttps://modis-atmos.gsfc.nasa.gov/products/eight-day","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://irsa.ipac.caltech.edu/SCS?table=dustingsfull&","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://irsa.ipac.caltech.edu/data/SPITZER/DUSTiNGS/gator_docs/dustings_colDescriptions.html","format":"HTML","mediaType":"text/html"}],"identifier":"10.5067/MODIS/MYD08_E3.061","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":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS;NASA/GSFC/SED/ESD/HBSL/BISB/MODAPS"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90, \"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2002-07-04/2026-06-15","theme":["Earth Science"],"title":"MODIS/Aqua Aerosol Cloud Water Vapor Ozone 8-Day L3 Global 1Deg CMG"},"description":"The MODIS/Aqua Aerosol Cloud Water Vapor Ozone 8-Day L3 Global 1Deg CMG product (MYD08_E3) contains 8-Day 1 degree 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. \r\n\r\nThe MYD08_E3 contains nearly 1000 statistical datasets (SDS's) that are derived from the Level-3 MODIS Atmosphere Daily Global Product. Statistics are computed over a 1 degree equal-angle lat-lon grid that spans an 8-Day 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.\r\n\r\nMYD08_E3 product files are stored in Hierarchical Data Format (HDF-EOS). Each gridded global parameter is stored as Scientific Data Sets (SDS) within the file. \r\n\r\nThe MODIS 8-Day 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.\r\n\r\nFor more information about the MYD08_E3 product, please visit the MODIS-Atmosphere site at:\r\nhttps://modis-atmos.gsfc.nasa.gov/products/eight-day","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/f7362c32-76c0-4d9b-97d2-b0994ac1bda8","harvest_record_raw":"https://catalog.data.gov/harvest_record/f7362c32-76c0-4d9b-97d2-b0994ac1bda8/raw","has_spatial":true,"identifier":"10.5067/MODIS/MYD08_E3.061","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":"2026-08-04T23:43:27.579740","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS;NASA/GSFC/SED/ESD/HBSL/BISB/MODAPS","slug":"modis-aqua-aerosol-cloud-water-vapor-ozone-8-day-l3-global-1deg-cmg","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"MODIS/Aqua Aerosol Cloud Water Vapor Ozone 8-Day L3 Global 1Deg CMG"},{"_score":13.042262,"_sort":[1785886992909,13.042262,4,"f373d476-b36b-4a55-8554-501bd20603a3"],"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 Cloud Properties COSP Level 3 daily, 1x1 degree grid product is a new L3 CLDPROP COSP Cloud product with short-name CLDPROPCOSP_D3_MODIS_Aqua.  It contains MODIS Aqua cloud mask, cloud top, and cloud optical retrieval data over daily timeframe. It provides a set of custom cloud-related parameters for better comparison with climate model output. The \u201cCOSP\u201d acronym in the short-name stands for  Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. \nProvided in netCDF4 format, it contains 32 aggregated science data sets (SDS/parameters).\n\nConsult the CLDPROPCOSP User Guide for details regarding how the L3 daily statistics are computed, and to learn more about the gridding and sampling protocols specific to this product and a number of other topics germane to the user community. The collection of this product starts from July 4, 2002 and includes 365 granules each calendar 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/C1426616847-LANCEMODIS.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"http://modis.gsfc.nasa.gov/sci_team/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthdata.nasa.gov/s3fs-public/2026-04/LANCE_MODAPS_Operational_Data_Flow_Diagram_4.16.26.pdf?VersionId=auDDcXbLWd7lDM.IyBmsuVfguIP64vnr","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://nrt3.modaps.eosdis.nasa.gov/archive/allData/61/MYD021KM/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1426616847-LANCEMODIS","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/instruments/modis/near-real-time-data","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/MODIS/CLDPROPCOSP_D3_MODIS_Aqua.011","keyword":["earth-science-atmospheric-radiation-atmosphere-optical-depth-thickness","earth-science-clouds-atmosphere","earth-science-clouds-atmosphere-cloud-microphysics","earth-science-clouds-atmosphere-cloud-properties"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS;UWI-MAD/SSEC/ASIPS"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90, \"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2002-07-04/2026-06-15","theme":["Earth Science"],"title":"MODIS/Aqua Cloud Properties COSP Level 3 daily, 1x1 deg. grid"},"description":"The MODIS/Aqua Cloud Properties COSP Level 3 daily, 1x1 degree grid product is a new L3 CLDPROP COSP Cloud product with short-name CLDPROPCOSP_D3_MODIS_Aqua.  It contains MODIS Aqua cloud mask, cloud top, and cloud optical retrieval data over daily timeframe. It provides a set of custom cloud-related parameters for better comparison with climate model output. The \u201cCOSP\u201d acronym in the short-name stands for  Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. \nProvided in netCDF4 format, it contains 32 aggregated science data sets (SDS/parameters).\n\nConsult the CLDPROPCOSP User Guide for details regarding how the L3 daily statistics are computed, and to learn more about the gridding and sampling protocols specific to this product and a number of other topics germane to the user community. The collection of this product starts from July 4, 2002 and includes 365 granules each calendar year.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/98fcbc46-99be-4251-abf9-2ff3c00f9365","harvest_record_raw":"https://catalog.data.gov/harvest_record/98fcbc46-99be-4251-abf9-2ff3c00f9365/raw","has_spatial":true,"identifier":"10.5067/MODIS/CLDPROPCOSP_D3_MODIS_Aqua.011","keyword":["earth-science-atmospheric-radiation-atmosphere-optical-depth-thickness","earth-science-clouds-atmosphere","earth-science-clouds-atmosphere-cloud-microphysics","earth-science-clouds-atmosphere-cloud-properties"],"last_harvested_date":"2026-08-04T23:43:12.909845","organization":{"aliases":[""],"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"},"popularity":4,"publisher":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS;UWI-MAD/SSEC/ASIPS","slug":"modis-aqua-cloud-properties-cosp-level-3-daily-1x1-deg-grid","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"MODIS/Aqua Cloud Properties COSP Level 3 daily, 1x1 deg. grid"},{"_score":12.953,"_sort":[1785886896120,12.953,5,"b73af599-d4ee-4ae9-9e36-1cc464c9418a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"HEASARC Help Desk","hasEmail":"mailto:andrew.ptak@nasa.gov"},"description":"This dataset provides modeled estimates of monthly hydrological fluxes at 0.25-degree resolution over Alaska and Canada for the years 1979-2018. The estimates were derived from the Variable Infiltration Capacity (VIC) macroscale hydrological model version 4.1.2 with water and energy balance schemes at 0.25-degree spatial and daily temporal resolution for this 38-year period. The gridded output data products are monthly average water balance variables including precipitation (P), evapotranspiration (E), 'P minus E', evaporation, soil moisture in three soil layers, base flow and runoff, snow depth, snow water equivalent (SWE), and snow sublimation, and energy balance variables including surface temperature, albedo, latent and sensible heat flux, ground heat flux, short- and long-wave and other radiative fluxes. The daily modeled values for precipitation and evapotranspiration were also aggregated to water years and precipitation was also aggregated to a 30-year climate normal average.","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://heasarc.gsfc.nasa.gov/W3Browse/all/m31xmm2.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://heasarc.gsfc.nasa.gov/xamin/vo/cone?showoffsets&table=m31xmm2&","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.3334/ORNLDAAC/1647","keyword":["earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-ground-water-terrestrial-hydrosphere-ground-water-processes-measurements","earth-science-precipitation-atmosphere-precipitation-amount","earth-science-snow-ice-terrestrial-hydrosphere-snow-depth","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-heat-budget","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-surface-radiative-properties-land-surface-albedo","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":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"ORNL_DAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -172.25, \"NorthBoundingCoordinate\": 83.125, \"EastBoundingCoordinate\": -53.4255, \"SouthBoundingCoordinate\": 41.7508}]]","temporal":"1979-01-01/2018-04-01","theme":["Earth Science"],"title":"ABoVE: Monthly Hydrological Fluxes for Canada and Alaska, 1979-2018"},"description":"This dataset provides modeled estimates of monthly hydrological fluxes at 0.25-degree resolution over Alaska and Canada for the years 1979-2018. The estimates were derived from the Variable Infiltration Capacity (VIC) macroscale hydrological model version 4.1.2 with water and energy balance schemes at 0.25-degree spatial and daily temporal resolution for this 38-year period. The gridded output data products are monthly average water balance variables including precipitation (P), evapotranspiration (E), 'P minus E', evaporation, soil moisture in three soil layers, base flow and runoff, snow depth, snow water equivalent (SWE), and snow sublimation, and energy balance variables including surface temperature, albedo, latent and sensible heat flux, ground heat flux, short- and long-wave and other radiative fluxes. The daily modeled values for precipitation and evapotranspiration were also aggregated to water years and precipitation was also aggregated to a 30-year climate normal average.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/1f474143-c7af-4ebd-aad6-8b2e76879f80","harvest_record_raw":"https://catalog.data.gov/harvest_record/1f474143-c7af-4ebd-aad6-8b2e76879f80/raw","has_spatial":true,"identifier":"10.3334/ORNLDAAC/1647","keyword":["earth-science-atmospheric-radiation-atmosphere-heat-flux","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-ground-water-terrestrial-hydrosphere-ground-water-processes-measurements","earth-science-precipitation-atmosphere-precipitation-amount","earth-science-snow-ice-terrestrial-hydrosphere-snow-depth","earth-science-snow-ice-terrestrial-hydrosphere-snow-water-equivalent","earth-science-soils-land-surface-soil-heat-budget","earth-science-soils-land-surface-soil-moisture-water-content","earth-science-surface-radiative-properties-land-surface-albedo","earth-science-surface-thermal-properties-land-surface-land-surface-temperature","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"last_harvested_date":"2026-08-04T23:41:36.120978","organization":{"aliases":[""],"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"},"popularity":5,"publisher":"ORNL_DAAC","slug":"above-monthly-hydrological-fluxes-for-canada-and-alaska-1979-2018","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ABoVE: Monthly Hydrological Fluxes for Canada and Alaska, 1979-2018"},{"_score":10.967561,"_sort":[1785886889652,10.967561,3,"acda8cb6-a639-415c-b65c-9d6b1f5ee1f4"],"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 estimates of river ice breakup and freeze-up stages along selected reaches of the Yukon and Tanana Rivers in the Yukon River Basin in interior Alaska from 1972-2016. Time series of Landsat satellite images were visually interpreted to identify the day of year and characteristics of the different stages of river ice seasonality. The stages of breakup or freeze-up were distinguished from one another based on the spatial extent and patterns of open water and ice cover. Images were displayed as false color composites, with the shortwave infrared (SWIR), near infrared (NIR), and green bands represented by red, green, and blue.","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/C2143403517-ORNL_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://above.nasa.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://daac.ornl.gov/ABOVE/guides/River_Ice_Breakup_Freezeup_Fig1.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/protected/bundle/River_Ice_Breakup_Freezeup_1697.zip","format":"ZIP","mediaType":"application/zip"},{"@type":"dcat:Distribution","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/public/above/River_Ice_Breakup_Freezeup/comp/River_Ice_Breakup_Freezeup.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.3334/ORNLDAAC/1697","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2143403517-ORNL_CLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.3334/ORNLDAAC/1697","keyword":["earth-science-cryospheric-indicators-climate-indicators-river-ice-depth-extent","earth-science-human-settlements-human-dimensions-rural-areas","earth-science-snow-ice-terrestrial-hydrosphere-river-ice","earth-science-terrestrial-hydrosphere-indicators-climate-indicators-river-lake-ice-breakup","earth-science-terrestrial-hydrosphere-indicators-climate-indicators-river-lake-ice-freeze"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"ORNL_DAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -160.065, \"NorthBoundingCoordinate\": 66.3594, \"EastBoundingCoordinate\": -142.986, \"SouthBoundingCoordinate\": 62.9036}]]","temporal":"1972-11-04/2016-11-30","theme":["Earth Science"],"title":"ABoVE: River Ice Breakup and Freeze-up Stages, Yukon River Basin, Alaska, 1972-2016"},"description":"This dataset provides estimates of river ice breakup and freeze-up stages along selected reaches of the Yukon and Tanana Rivers in the Yukon River Basin in interior Alaska from 1972-2016. Time series of Landsat satellite images were visually interpreted to identify the day of year and characteristics of the different stages of river ice seasonality. The stages of breakup or freeze-up were distinguished from one another based on the spatial extent and patterns of open water and ice cover. Images were displayed as false color composites, with the shortwave infrared (SWIR), near infrared (NIR), and green bands represented by red, green, and blue.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/15818558-8c00-4d46-8564-77bacae27071","harvest_record_raw":"https://catalog.data.gov/harvest_record/15818558-8c00-4d46-8564-77bacae27071/raw","has_spatial":true,"identifier":"10.3334/ORNLDAAC/1697","keyword":["earth-science-cryospheric-indicators-climate-indicators-river-ice-depth-extent","earth-science-human-settlements-human-dimensions-rural-areas","earth-science-snow-ice-terrestrial-hydrosphere-river-ice","earth-science-terrestrial-hydrosphere-indicators-climate-indicators-river-lake-ice-breakup","earth-science-terrestrial-hydrosphere-indicators-climate-indicators-river-lake-ice-freeze"],"last_harvested_date":"2026-08-04T23:41:29.652097","organization":{"aliases":[""],"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"},"popularity":3,"publisher":"ORNL_DAAC","slug":"above-river-ice-breakup-and-freeze-up-stages-yukon-river-basin-alaska-1972-2016","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ABoVE: River Ice Breakup and Freeze-up Stages, Yukon River Basin, Alaska, 1972-2016"},{"_score":16.074627,"_sort":[1785886846037,16.074627,2,"f6f708b9-5456-4616-824d-802bd53f64bf"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Planetary Data System","hasEmail":"mailto:pds-operator@jpl.nasa.gov"},"description":"The MCD43D62 Version 6.1 Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) Nadir BRDF-Adjusted Reflectance (NBAR) dataset is produced daily using 16 days of Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data at 30 arc second (1,000 meter (m)) 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. \n\nMCD43D62 through MCD43D68 are the NBAR products of the MCD43D BRDF/Albedo product suite for MODIS bands 1 through 7. The NBAR algorithm removes view angle effects from directional reflectances to model the values as if they were collected from a nadir view at local solar noon.\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\nMCD43D62 is the NBAR for MODIS band 1. \n\nKnown Issues\n\n* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=TerraAqua&as=61).","identifier":"10.5067/MODIS/MCD43D62.061","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":"2026-06-22","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":"2000-02-16/2026-06-15","theme":["Earth Science"],"title":"MODIS/Terra+Aqua BRDF/Albedo Nadir BRDF-Adjusted Ref Band1 Daily L3 Global 30ArcSec CMG V061"},"description":"The MCD43D62 Version 6.1 Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) Nadir BRDF-Adjusted Reflectance (NBAR) dataset is produced daily using 16 days of Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data at 30 arc second (1,000 meter (m)) 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. \n\nMCD43D62 through MCD43D68 are the NBAR products of the MCD43D BRDF/Albedo product suite for MODIS bands 1 through 7. The NBAR algorithm removes view angle effects from directional reflectances to model the values as if they were collected from a nadir view at local solar noon.\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\nMCD43D62 is the NBAR for MODIS band 1. \n\nKnown Issues\n\n* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=TerraAqua&as=61).","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/33f961be-cf9e-4eb9-afe5-bc7f0be484bb","harvest_record_raw":"https://catalog.data.gov/harvest_record/33f961be-cf9e-4eb9-afe5-bc7f0be484bb/raw","has_spatial":true,"identifier":"10.5067/MODIS/MCD43D62.061","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":"2026-08-04T23:40:46.037973","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"LP DAAC;NASA/GSFC/SED/ESD/TISL/MODAPS;UMASS-B/SFE","slug":"modis-terraaqua-brdf-albedo-nadir-brdf-adjusted-ref-band1-daily-l3-global-30arcsec-cmg-v06","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"MODIS/Terra+Aqua BRDF/Albedo Nadir BRDF-Adjusted Ref Band1 Daily L3 Global 30ArcSec CMG V061"},{"_score":15.619901,"_sort":[1785886841549,15.619901,2,"bbdcbed0-d349-426d-b8d1-5cc4d31f5174"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The MCD43D01 Version 6.1 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/MCD43C1.061) are stored in a separate file as MCD43D01 through MCD43D30. \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\nMCD43D01 is the BRDF isotropic parameter for MODIS band 1. The isotropic parameter, in conjunction with the volumetric and geometric parameters, is used to derive the BRDF/Albedo values for MODIS band 1. \n\nKnown Issues\n\n* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=TerraAqua&as=61).","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/C2532021230-LPCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/MODIS/MCD43D01.061","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ladsweb.modaps.eosdis.nasa.gov/filespec/MODIS/61/MCD43D01","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://modis-land.gsfc.nasa.gov/MODLAND_val.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD43D01","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2532021230-LPCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@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/MCD43D01.061","keyword":["earth-science-surface-radiative-properties-land-surface-albedo","earth-science-surface-radiative-properties-land-surface-anisotropy"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","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":"2000-02-16/2026-06-15","theme":["Earth Science"],"title":"MODIS/Terra+Aqua BRDF/Albedo Parameter 1 Band 1 Daily L3 Global 30 ArcSec CMG V061"},"description":"The MCD43D01 Version 6.1 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/MCD43C1.061) are stored in a separate file as MCD43D01 through MCD43D30. \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\nMCD43D01 is the BRDF isotropic parameter for MODIS band 1. The isotropic parameter, in conjunction with the volumetric and geometric parameters, is used to derive the BRDF/Albedo values for MODIS band 1. \n\nKnown Issues\n\n* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=TerraAqua&as=61).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/0a54eeec-3c39-4bbc-af37-d282094df7b4","harvest_record_raw":"https://catalog.data.gov/harvest_record/0a54eeec-3c39-4bbc-af37-d282094df7b4/raw","has_spatial":true,"identifier":"10.5067/MODIS/MCD43D01.061","keyword":["earth-science-surface-radiative-properties-land-surface-albedo","earth-science-surface-radiative-properties-land-surface-anisotropy"],"last_harvested_date":"2026-08-04T23:40:41.549703","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"LP DAAC;NASA/GSFC/SED/ESD/TISL/MODAPS;UMASS-B/SFE","slug":"modis-terraaqua-brdf-albedo-parameter-1-band-1-daily-l3-global-30-arcsec-cmg-v061","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"MODIS/Terra+Aqua BRDF/Albedo Parameter 1 Band 1 Daily L3 Global 30 ArcSec CMG V061"},{"_score":12.974313,"_sort":[1785886838907,12.974313,2,"e8b65268-f8f0-4bd0-8f35-1e6201dde1e4"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The MCD43D01 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the [MCD43D01 Version 6.1](https://doi.org/10.5067/MODIS/MCD43D01.061) data product.\n\nThe MCD43D01 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\nMCD43D01 is the BRDF isotropic parameter for MODIS band 1. The isotropic parameter, in conjunction with the volumetric and geometric parameters, is used to derive the BRDF/Albedo values for MODIS band 1. \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 MCD43D01 known issues refer to the [MODIS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&as=6).","identifier":"10.5067/MODIS/MCD43D01.006","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":"2026-06-22","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 Parameter1 Band1 Daily L3 Global 30ArcSec CMG V006"},"description":"The MCD43D01 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the [MCD43D01 Version 6.1](https://doi.org/10.5067/MODIS/MCD43D01.061) data product.\n\nThe MCD43D01 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\nMCD43D01 is the BRDF isotropic parameter for MODIS band 1. The isotropic parameter, in conjunction with the volumetric and geometric parameters, is used to derive the BRDF/Albedo values for MODIS band 1. \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 MCD43D01 known issues refer to the [MODIS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&as=6).","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/f4ac5f67-3f75-4c18-bd62-f290feba34c2","harvest_record_raw":"https://catalog.data.gov/harvest_record/f4ac5f67-3f75-4c18-bd62-f290feba34c2/raw","has_spatial":true,"identifier":"10.5067/MODIS/MCD43D01.006","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":"2026-08-04T23:40:38.907718","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"LP DAAC;NASA/GSFC/SED/ESD/TISL/MODAPS;UMASS-B/SFE","slug":"modis-terraaqua-brdf-albedo-parameter1-band1-daily-l3-global-30arcsec-cmg-v006","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"MODIS/Terra+Aqua BRDF/Albedo Parameter1 Band1 Daily L3 Global 30ArcSec CMG V006"},{"_score":9.174681,"_sort":[1785886838288,9.174681,6,"7842cf92-3015-4a8b-befb-fa7954da2197"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Planetary Data System","hasEmail":"mailto:pds-operator@jpl.nasa.gov"},"description":"ACTIVATE_Cloud_AircraftInSitu_Falcon_Data is the cloud data collected onboard the HU-25 Falcon aircraft via in-situ instrumentation during the ACTIVATE project. ACTIVATE was a 5-year NASA Earth-Venture Sub-Orbital (EVS-3) field campaign. Marine boundary layer clouds play a critical role in Earth\u2019s energy balance and water cycle. These clouds cover more than 45% of the ocean surface and exert a net cooling effect. The Aerosol Cloud meTeorology Interactions oVer the western Atlantic Experiment (ACTIVATE) project was a five-year project that provides important globally-relevant data about changes in marine boundary layer cloud systems, atmospheric aerosols and multiple feedbacks that warm or cool the climate. ACTIVATE studied the atmosphere over the western North Atlantic and sampled its broad range of aerosol, cloud and meteorological conditions using two aircraft, the UC-12 King Air and HU-25 Falcon. The UC-12 King Air was primarily used for remote sensing measurements while the HU-25 Falcon will contain a comprehensive instrument payload for detailed in-situ measurements of aerosol, cloud properties, and atmospheric state. A few trace gas measurements were also onboard the HU-25 Falcon for the measurements of pollution traces, which will contribute to airmass classification analysis. A total of 150 coordinated flights over the western North Atlantic occurred through 6 deployments from 2020-2022. The ACTIVATE science observing strategy intensively targets the shallow cumulus cloud regime and aims to collect sufficient statistics over a broad range of aerosol and weather conditions which enables robust characterization of aerosol-cloud-meteorology interactions. This strategy was implemented by two nominal flight patterns: Statistical Survey and Process Study. The statistical survey pattern involves close coordination between the remote sensing and in-situ aircraft to conduct near coincident sampling at and below cloud base as well as above and within cloud top. The process study pattern involves extensive vertical profiling to characterize the target cloud and surrounding aerosol and meteorological conditions.","identifier":"10.5067/ASDC/ACTIVATE_Cloud_AircraftInSitu_Falcon_Data_1","keyword":["earth-science-clouds-atmosphere","earth-science-clouds-atmosphere-cloud-droplet-distribution","earth-science-clouds-atmosphere-cloud-microphysics"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"[\"CARTESIAN\", [{\"Boundary\": {\"Points\": [{\"Latitude\": 25, \"Longitude\": -85}, {\"Latitude\": 25, \"Longitude\": -58.5}, {\"Latitude\": 50, \"Longitude\": -58.5}, {\"Latitude\": 50, \"Longitude\": -85}, {\"Latitude\": 25, \"Longitude\": -85}]}}]], Maximum Altitude, 9999.9 Meters","temporal":"2020-02-14/2022-06-30","theme":["Earth Science"],"title":"ACTIVATE Falcon In Situ Cloud Data"},"description":"ACTIVATE_Cloud_AircraftInSitu_Falcon_Data is the cloud data collected onboard the HU-25 Falcon aircraft via in-situ instrumentation during the ACTIVATE project. ACTIVATE was a 5-year NASA Earth-Venture Sub-Orbital (EVS-3) field campaign. Marine boundary layer clouds play a critical role in Earth\u2019s energy balance and water cycle. These clouds cover more than 45% of the ocean surface and exert a net cooling effect. The Aerosol Cloud meTeorology Interactions oVer the western Atlantic Experiment (ACTIVATE) project was a five-year project that provides important globally-relevant data about changes in marine boundary layer cloud systems, atmospheric aerosols and multiple feedbacks that warm or cool the climate. ACTIVATE studied the atmosphere over the western North Atlantic and sampled its broad range of aerosol, cloud and meteorological conditions using two aircraft, the UC-12 King Air and HU-25 Falcon. The UC-12 King Air was primarily used for remote sensing measurements while the HU-25 Falcon will contain a comprehensive instrument payload for detailed in-situ measurements of aerosol, cloud properties, and atmospheric state. A few trace gas measurements were also onboard the HU-25 Falcon for the measurements of pollution traces, which will contribute to airmass classification analysis. A total of 150 coordinated flights over the western North Atlantic occurred through 6 deployments from 2020-2022. The ACTIVATE science observing strategy intensively targets the shallow cumulus cloud regime and aims to collect sufficient statistics over a broad range of aerosol and weather conditions which enables robust characterization of aerosol-cloud-meteorology interactions. This strategy was implemented by two nominal flight patterns: Statistical Survey and Process Study. The statistical survey pattern involves close coordination between the remote sensing and in-situ aircraft to conduct near coincident sampling at and below cloud base as well as above and within cloud top. The process study pattern involves extensive vertical profiling to characterize the target cloud and surrounding aerosol and meteorological conditions.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/7f8e16f3-1c11-4749-9fd9-9db35a90bbd6","harvest_record_raw":"https://catalog.data.gov/harvest_record/7f8e16f3-1c11-4749-9fd9-9db35a90bbd6/raw","has_spatial":true,"identifier":"10.5067/ASDC/ACTIVATE_Cloud_AircraftInSitu_Falcon_Data_1","keyword":["earth-science-clouds-atmosphere","earth-science-clouds-atmosphere-cloud-droplet-distribution","earth-science-clouds-atmosphere-cloud-microphysics"],"last_harvested_date":"2026-08-04T23:40:38.288460","organization":{"aliases":[""],"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"},"popularity":6,"publisher":"NASA/LARC/SD/ASDC","slug":"activate-falcon-in-situ-cloud-data","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ACTIVATE Falcon In Situ Cloud Data"},{"_score":12.974313,"_sort":[1785886829373,12.974313,1,"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","downloadURL":"https://irsa.ipac.caltech.edu/SCS?table=glimpse2_v2arc&","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://irsa.ipac.caltech.edu/data/SPITZER/GLIMPSE/gator_docs/GLIMPSE_colDescriptions.html","format":"HTML","mediaType":"text/html"}],"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":"2026-06-22","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":[],"harvest_record":"https://catalog.data.gov/harvest_record/2552e4fc-f0e5-4c8e-95fb-8a1852b19d13","harvest_record_raw":"https://catalog.data.gov/harvest_record/2552e4fc-f0e5-4c8e-95fb-8a1852b19d13/raw","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":"2026-08-04T23:40:29.373201","organization":{"aliases":[""],"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"},"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"},{"_score":11.695644,"_sort":[1785886804383,11.695644,2,"e8f97e28-9c15-4919-bdaf-73e2d0d4e086"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) (MCD12C1) Version 6.1 data product provides a spatially aggregated and reprojected version of the tiled [MCD12Q1 Version 6.1](https://doi.org/10.5067/MODIS/MCD12Q1.061) data product. Maps of the International Geosphere-Biosphere Programme (IGBP), University of Maryland (UMD), and Leaf Area Index (LAI) classification schemes are provided at yearly intervals at 0.05 degree (5,600 meter) spatial resolution for the entire globe. Additionally, sub-pixel proportions of each land cover class in each 0.05 degree pixel is provided along with the aggregated quality assessment information for each of the three land classification schemes. \n\nProvided in each MCD12C1 Version 6.1 Hierarchical Data Format 4 (HDF4) file are layers for Majority Land Cover Type 1-3, Majority Land Cover Type 1-3 Assessment, and Majority Land Cover Type 1-3 Percent.\n\nKnown Issues\n* Known issues are described in Section 2.2 of the User Guide.\n* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&as=61).","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/C2484078896-LPCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://data.lpdaac.earthdatacloud.nasa.gov/lp-prod-public/MCD12C1.061/MCD12C1.A2021001.061.2022217040006/BROWSE.MCD12C1.A2021001.061.2022217040006.1.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/MODIS/MCD12C1.061","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/1409/MCD12_User_Guide_V61.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/documents/86/MCD12_ATBD.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://modis-land.gsfc.nasa.gov/MODLAND_val.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD12","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2484078896-LPCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/centers/lp-daac","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/MODIS/MCD12C1.061","keyword":["earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"LP DAAC;NASA/GSFC/SED/ESD/TISL/MODAPS"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90, \"WestBoundingCoordinate\": -180, \"EastBoundingCoordinate\": 180, \"SouthBoundingCoordinate\": -90}]]","temporal":"2001-01-01/2026-06-15","theme":["Earth Science"],"title":"MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V061"},"description":"The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) (MCD12C1) Version 6.1 data product provides a spatially aggregated and reprojected version of the tiled [MCD12Q1 Version 6.1](https://doi.org/10.5067/MODIS/MCD12Q1.061) data product. Maps of the International Geosphere-Biosphere Programme (IGBP), University of Maryland (UMD), and Leaf Area Index (LAI) classification schemes are provided at yearly intervals at 0.05 degree (5,600 meter) spatial resolution for the entire globe. Additionally, sub-pixel proportions of each land cover class in each 0.05 degree pixel is provided along with the aggregated quality assessment information for each of the three land classification schemes. \n\nProvided in each MCD12C1 Version 6.1 Hierarchical Data Format 4 (HDF4) file are layers for Majority Land Cover Type 1-3, Majority Land Cover Type 1-3 Assessment, and Majority Land Cover Type 1-3 Percent.\n\nKnown Issues\n* Known issues are described in Section 2.2 of the User Guide.\n* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&as=61).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/c2512ee5-7bff-4bfb-ada3-d8769b72f2c8","harvest_record_raw":"https://catalog.data.gov/harvest_record/c2512ee5-7bff-4bfb-ada3-d8769b72f2c8/raw","has_spatial":true,"identifier":"10.5067/MODIS/MCD12C1.061","keyword":["earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification"],"last_harvested_date":"2026-08-04T23:40:04.383545","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"LP DAAC;NASA/GSFC/SED/ESD/TISL/MODAPS","slug":"modis-terraaqua-land-cover-type-yearly-l3-global-0-05deg-cmg-v061","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V061"},{"_score":10.085001,"_sort":[1785886715119,10.085001,1,"12bcafe7-1a8a-4896-ba67-31dddf186971"],"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 environmental data that have been standardized and aggregated for use as input to carbon cycle models at global (0.5-degree resolution) and regional (North America at 0.25-degree resolution) scales. \r\n\r\nThe data were compiled from selected sources (Table 2) and integrated into gridded global and regional collections of climatology variables (precipitation, air temperature, air specific humidity, air relative humidity (NA only), pressure, downward longwave radiation, downward shortwave radiation, and wind speed), time-varying atmospheric CO2 concentrations, time-varying nitrogen deposition, biome fraction and type, land-use and land-cover change, C3/C4 grasses fractions, major crop distribution, phenology, multiple soil characteristics, and a land-water mask. The temporal ranges of the data are sufficient for carbon cycle model simulations from 1801 to 2010. \r\n\r\nThese data were compiled specifically for the North American Carbon Program (NACP) Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) as the prescribed model input driver data (Huntzinger et al., 2013). The driver data were used by 22 terrestrial biosphere models to run baseline and sensitivity simulations. The standardized data provided consistent model inputs to minimize the inter-model variability caused by differences in environmental drivers and initial conditions. Together with the sensitivity simulations, the standardized input data enable better interpretation and quantification of structural and parameter uncertainties of model estimates. \r\n\r\nData are provided in Climate and Forecast (CF) metadata convention compliant (version 1.4) netCDF-4 file formats. There are 3,152 *.nc4 data files with this data set.","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/C2552206090-ORNL_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://daac.ornl.gov/graphics/browse/sdat-tds/1220_1_fit.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/public/nacp/NACP_MsTMIP_Model_Driver/comp/NACP_MsTMIP_Model_Driver.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.3334/ORNLDAAC/1220","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://opendap.earthdata.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2552206090-ORNL_CLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.3334/ORNLDAAC/1220","keyword":["earth-science-atmospheric-chemistry-atmosphere-carbon-and-hydrocarbon-compounds","earth-science-atmospheric-chemistry-atmosphere-nitrogen-compounds","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-ecosystems-biosphere-anthropogenic-human-influenced-ecosystems","earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification","earth-science-precipitation-atmosphere-precipitation-amount","earth-science-soils-land-surface-soil-chemistry","earth-science-soils-land-surface-soil-classification","earth-science-vegetation-biosphere-leaf-characteristics"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"ORNL_DAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -178.75, \"NorthBoundingCoordinate\": 89.75, \"EastBoundingCoordinate\": 179.95, \"SouthBoundingCoordinate\": -78.25}]]","temporal":"1700-01-01/2010-12-31","theme":["Earth Science"],"title":"NACP MsTMIP: Global and North American Driver Data for Multi-Model Intercomparison"},"description":"This data set provides environmental data that have been standardized and aggregated for use as input to carbon cycle models at global (0.5-degree resolution) and regional (North America at 0.25-degree resolution) scales. \r\n\r\nThe data were compiled from selected sources (Table 2) and integrated into gridded global and regional collections of climatology variables (precipitation, air temperature, air specific humidity, air relative humidity (NA only), pressure, downward longwave radiation, downward shortwave radiation, and wind speed), time-varying atmospheric CO2 concentrations, time-varying nitrogen deposition, biome fraction and type, land-use and land-cover change, C3/C4 grasses fractions, major crop distribution, phenology, multiple soil characteristics, and a land-water mask. The temporal ranges of the data are sufficient for carbon cycle model simulations from 1801 to 2010. \r\n\r\nThese data were compiled specifically for the North American Carbon Program (NACP) Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) as the prescribed model input driver data (Huntzinger et al., 2013). The driver data were used by 22 terrestrial biosphere models to run baseline and sensitivity simulations. The standardized data provided consistent model inputs to minimize the inter-model variability caused by differences in environmental drivers and initial conditions. Together with the sensitivity simulations, the standardized input data enable better interpretation and quantification of structural and parameter uncertainties of model estimates. \r\n\r\nData are provided in Climate and Forecast (CF) metadata convention compliant (version 1.4) netCDF-4 file formats. There are 3,152 *.nc4 data files with this data set.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/dd6b848c-272d-4639-91a8-ac37fbd08e71","harvest_record_raw":"https://catalog.data.gov/harvest_record/dd6b848c-272d-4639-91a8-ac37fbd08e71/raw","has_spatial":true,"identifier":"10.3334/ORNLDAAC/1220","keyword":["earth-science-atmospheric-chemistry-atmosphere-carbon-and-hydrocarbon-compounds","earth-science-atmospheric-chemistry-atmosphere-nitrogen-compounds","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-ecosystems-biosphere-anthropogenic-human-influenced-ecosystems","earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification","earth-science-precipitation-atmosphere-precipitation-amount","earth-science-soils-land-surface-soil-chemistry","earth-science-soils-land-surface-soil-classification","earth-science-vegetation-biosphere-leaf-characteristics"],"last_harvested_date":"2026-08-04T23:38:35.119790","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"ORNL_DAAC","slug":"nacp-mstmip-global-and-north-american-driver-data-for-multi-model-intercomparison","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"NACP MsTMIP: Global and North American Driver Data for Multi-Model Intercomparison"},{"_score":39.768394,"_sort":[1785886711578,39.768394,2,"2677931b-53b8-433a-a7f6-2e69a6026498"],"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 sub-daily, high-resolution, climate data inputs including temperature, precipitation, near surface specific humidity, incoming short-wave radiation, and near-surface wind speed over 11 states of the western USA. States included are Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. These data were derived for use in the Community Land Model (CLM v4.5) and are at 3-hourly temporal and 4 x 4 km spatial resolutions for the 1979 through 2015 time period. The source for observational data was METDATA (now called GRIDMET), at a daily resolution. Modeling efforts using these data estimated annual carbon stocks, fluxes, and productivity across the western United States.","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/C2517710454-ORNL_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://daac.ornl.gov/NACP/guides/VPRM_North_America_Parameters_Fig1.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/protected/bundle/VPRM_North_America_Parameters_1349.zip","format":"ZIP","mediaType":"application/zip"},{"@type":"dcat:Distribution","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/public/nacp/VPRM_North_America_Parameters/comp/VPRM_North_America_Parameters.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.3334/ORNLDAAC/1349","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2517710454-ORNL_CLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.3334/ORNLDAAC/1682","keyword":["earth-science-atmospheric-radiation-atmosphere-solar-irradiance","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-precipitation-atmosphere-precipitation-amount"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"ORNL_DAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -124.812, \"NorthBoundingCoordinate\": 49.0208, \"EastBoundingCoordinate\": -101.979, \"SouthBoundingCoordinate\": 31.1875}]]","temporal":"1979-01-01/2016-01-01","theme":["Earth Science"],"title":"NACP: Climate Data Inputs (3-hourly) for Community Land Model, Western USA, 1979-2015"},"description":"This dataset provides sub-daily, high-resolution, climate data inputs including temperature, precipitation, near surface specific humidity, incoming short-wave radiation, and near-surface wind speed over 11 states of the western USA. States included are Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. These data were derived for use in the Community Land Model (CLM v4.5) and are at 3-hourly temporal and 4 x 4 km spatial resolutions for the 1979 through 2015 time period. The source for observational data was METDATA (now called GRIDMET), at a daily resolution. Modeling efforts using these data estimated annual carbon stocks, fluxes, and productivity across the western United States.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/15c727c5-031b-4f5f-a4c1-6cc980a2d049","harvest_record_raw":"https://catalog.data.gov/harvest_record/15c727c5-031b-4f5f-a4c1-6cc980a2d049/raw","has_spatial":true,"identifier":"10.3334/ORNLDAAC/1682","keyword":["earth-science-atmospheric-radiation-atmosphere-solar-irradiance","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-precipitation-atmosphere-precipitation-amount"],"last_harvested_date":"2026-08-04T23:38:31.578950","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"ORNL_DAAC","slug":"nacp-climate-data-inputs-3-hourly-for-community-land-model-western-usa-1979-2015","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"NACP: Climate Data Inputs (3-hourly) for Community Land Model, Western USA, 1979-2015"},{"_score":5.503994,"_sort":[1785886678487,5.503994,1,"b8c8d998-c551-4e41-8fec-c38f7c8eb586"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The AIRMISR_MORGAN_MONROE_2003 data were acquired during a flight over the Morgan Monroe State Forest, Indiana, USA, target as part of the AirMISR deployments from the Wallops Flight Facility during the August 2003 campaign. This particular flight took place on August 19, 2003. The Jet Propulsion Laboratory (JPL) in Pasadena, California provided the data. There were a total of two runs during this flight. A run comprises data collected from nine view angles acquired on a fixed flight azimuth angle. Each data file from one run contains either: a) Level 1B1 Radiometric product from one of the 9 camera angles or b) Level 1B2 Georectified radiance product from one of the 9 camera angles. Browse images in PNG format are available for the Level 1B1 product and browse images in JPEG format are available for the Level 1B2 product. The Airborne Multi-angle Imaging SpectroRadiometer (AirMISR) is an airborne instrument for obtaining multi-angle imagery similar to that of the satellite-borne Multi-angle Imaging SpectroRadiometer (MISR) instrument, which is designed to contribute to studies of the Earth's ecology and climate. AirMISR flies on the NASA ER-2 aircraft. The Jet Propulsion Laboratory in Pasadena, California built the instrument for NASA. Unlike the satellite-borne MISR instrument, which has nine cameras oriented at various angles, AirMISR uses a single camera in a pivoting gimbal mount. A data run by the ER-2 aircraft is divided into nine segments, each with the camera positioned to a MISR look angle. The gimbal rotates between successive segments, such that each segment acquires data over the same area on the ground as the previous segment. This process is repeated until all nine angles of the target area are collected. The swath width, which varies from 11 km in the nadir to 32 km at the most oblique angle, is governed by the camera's instantaneous field-of-view of 7 meters cross-track x 6 meters along-track in the nadir view and 21 meters x 55 meters at the most oblique angle. The along-track image length at each angle is dictated by the timing required to obtain overlap imagery at all angles, and varies from about 9 km in the nadir to 26 km at the most oblique angle. Thus, the nadir image dictates the area of overlap that is obtained from all nine angles. A complete flight run takes approximately 13 minutes. The 9 camera viewing angles are: 0 degrees or nadir 26.1 degrees, fore and aft 45.6 degrees, fore and aft 60.0 degrees, fore and aft 70.5 degrees, fore and aft. For each of the camera angles, images are obtained at 4 spectral bands. The spectral bands can be used to identify vegetation and aerosols, estimate surface reflectance and for ocean color studies. The center wavelengths of the 4 spectral bands are: 443 nanometers, blue 555 nanometers, green 670 nanometers, red 865 nanometers, near-infrared. Two types of AirMISR data products are available - the Level 1 Radiometric product (L1B1) and the Level 1 Georectified radiance product (L1B2). The Level 1 Radiometric product contains data that are scaled to convert the digital output of the cameras to radiances and are conditioned to remove instrument-dependent effects. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the detector elements of each spectral band. These data have a 7-meter spatial resolution at nadir and around 30-meter at the most oblique 70.5 degree angles. The Level 1 Georectified radiance product contains the Level 1 radiometric product resampled to a 27.5 meter spatial resolution and mapped into a standard Universal Transverse Mercator (UTM) map projection. Initially the data are registered to each camera angle and to the ground. This processing is necessary because the nine views of each point on the ground are not acquired simultaneously. Once the map grid center points are located in the AirMISR imagery through the process of georectification, a radiance value obtained from the surrounding AirMISR pixels is assigned to that map grid center. Bilinear interpolation is used as the basis for computing the new radiance. A UTM grid point falling somewhere in the image data will have up to 4 surrounding points. The bilinear interpolated value is obtained using the fractional distance of the interpolation point in the cross-track direction and the fractional distance in the along-track direction.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://wise2.ipac.caltech.edu/docs/release/allsky/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://irsa.ipac.caltech.edu/SCS?table=allsky_4band_p1bs_psd&","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/ASDC_DAAC/AIRMISR_MORGAN_MONROE_2003_1","keyword":["earth-science-infrared-wavelengths-spectral-engineering-infrared-radiance","earth-science-visible-wavelengths-spectral-engineering-visible-radiance"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"[\"CARTESIAN\", [{\"Boundary\": {\"Points\": [{\"Latitude\": 39.05, \"Longitude\": -86.76}, {\"Latitude\": 39.05, \"Longitude\": -86.03}, {\"Latitude\": 39.6, \"Longitude\": -86.03}, {\"Latitude\": 39.6, \"Longitude\": -86.76}, {\"Latitude\": 39.05, \"Longitude\": -86.76}]}}]]","temporal":"2003-08-19/2003-08-19","theme":["Earth Science"],"title":"Airborne Multi-angle Imaging SpectroRadiometer (AirMISR) Data from the Morgan Monore 2003 Campaign"},"description":"The AIRMISR_MORGAN_MONROE_2003 data were acquired during a flight over the Morgan Monroe State Forest, Indiana, USA, target as part of the AirMISR deployments from the Wallops Flight Facility during the August 2003 campaign. This particular flight took place on August 19, 2003. The Jet Propulsion Laboratory (JPL) in Pasadena, California provided the data. There were a total of two runs during this flight. A run comprises data collected from nine view angles acquired on a fixed flight azimuth angle. Each data file from one run contains either: a) Level 1B1 Radiometric product from one of the 9 camera angles or b) Level 1B2 Georectified radiance product from one of the 9 camera angles. Browse images in PNG format are available for the Level 1B1 product and browse images in JPEG format are available for the Level 1B2 product. The Airborne Multi-angle Imaging SpectroRadiometer (AirMISR) is an airborne instrument for obtaining multi-angle imagery similar to that of the satellite-borne Multi-angle Imaging SpectroRadiometer (MISR) instrument, which is designed to contribute to studies of the Earth's ecology and climate. AirMISR flies on the NASA ER-2 aircraft. The Jet Propulsion Laboratory in Pasadena, California built the instrument for NASA. Unlike the satellite-borne MISR instrument, which has nine cameras oriented at various angles, AirMISR uses a single camera in a pivoting gimbal mount. A data run by the ER-2 aircraft is divided into nine segments, each with the camera positioned to a MISR look angle. The gimbal rotates between successive segments, such that each segment acquires data over the same area on the ground as the previous segment. This process is repeated until all nine angles of the target area are collected. The swath width, which varies from 11 km in the nadir to 32 km at the most oblique angle, is governed by the camera's instantaneous field-of-view of 7 meters cross-track x 6 meters along-track in the nadir view and 21 meters x 55 meters at the most oblique angle. The along-track image length at each angle is dictated by the timing required to obtain overlap imagery at all angles, and varies from about 9 km in the nadir to 26 km at the most oblique angle. Thus, the nadir image dictates the area of overlap that is obtained from all nine angles. A complete flight run takes approximately 13 minutes. The 9 camera viewing angles are: 0 degrees or nadir 26.1 degrees, fore and aft 45.6 degrees, fore and aft 60.0 degrees, fore and aft 70.5 degrees, fore and aft. For each of the camera angles, images are obtained at 4 spectral bands. The spectral bands can be used to identify vegetation and aerosols, estimate surface reflectance and for ocean color studies. The center wavelengths of the 4 spectral bands are: 443 nanometers, blue 555 nanometers, green 670 nanometers, red 865 nanometers, near-infrared. Two types of AirMISR data products are available - the Level 1 Radiometric product (L1B1) and the Level 1 Georectified radiance product (L1B2). The Level 1 Radiometric product contains data that are scaled to convert the digital output of the cameras to radiances and are conditioned to remove instrument-dependent effects. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the detector elements of each spectral band. These data have a 7-meter spatial resolution at nadir and around 30-meter at the most oblique 70.5 degree angles. The Level 1 Georectified radiance product contains the Level 1 radiometric product resampled to a 27.5 meter spatial resolution and mapped into a standard Universal Transverse Mercator (UTM) map projection. Initially the data are registered to each camera angle and to the ground. This processing is necessary because the nine views of each point on the ground are not acquired simultaneously. Once the map grid center points are located in the AirMISR imagery through the process of georectification, a radiance value obtained from the surrounding AirMISR pixels is assigned to that map grid center. Bilinear interpolation is used as the basis for computing the new radiance. A UTM grid point falling somewhere in the image data will have up to 4 surrounding points. The bilinear interpolated value is obtained using the fractional distance of the interpolation point in the cross-track direction and the fractional distance in the along-track direction.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/cba9d510-919b-4511-a026-a51118d7bf71","harvest_record_raw":"https://catalog.data.gov/harvest_record/cba9d510-919b-4511-a026-a51118d7bf71/raw","has_spatial":true,"identifier":"10.5067/ASDC_DAAC/AIRMISR_MORGAN_MONROE_2003_1","keyword":["earth-science-infrared-wavelengths-spectral-engineering-infrared-radiance","earth-science-visible-wavelengths-spectral-engineering-visible-radiance"],"last_harvested_date":"2026-08-04T23:37:58.487068","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"NASA/LARC/SD/ASDC","slug":"airborne-multi-angle-imaging-spectroradiometer-airmisr-data-from-the-morgan-monore-2003-ca","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"Airborne Multi-angle Imaging SpectroRadiometer (AirMISR) Data from the Morgan Monore 2003 Campaign"},{"_score":45.925926,"_sort":[1785886656379,45.925926,4,"4420f414-d697-4c7f-a217-b6e5233ec454"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"NVAP_CLIMATE_Total-Precipitable-Water data set is designed to provide the most stable water vapor dataset over time for use in climate applications. NASA Water Vapor Project MEaSUREs (NVAP-M) Climate only includes data from stable instruments that have undergone intercalibration efforts to ensure consistency between data from the same instrument flying on multiple satellite platforms. The new NVAP data sets are produced under the NASA Making Earth Science Data Records for Use in Research Environments (MEaSUREs) program and is named NVAP-M. It supersedes the previous NVAP data set. NVAP-M continues the legacy of providing high-quality, model-independent global estimates of total column and layered water vapor. The use of improved, intercalibrated data sets and algorithms that were not available for the heritage NVAP data set results in an improved and extended water vapor data set that is stable enough for climate research and of a resolution appropriate for studies on smaller spatial and temporal scales. The true value of NVAP-M will be seen in outcomes from applied and research users of the data set in various fields. Some initial NVAP-M findings are presented in Vonder Haar et al. (2012). In addition to the time-dependent artifacts present in the previous NVAP data set, a wealth of new data has become available since the last NVAP processing in 2003. These include an additional SSM/I instrument, additional NOAA satellites, the NASA Earth Observing System (EOS)-Aqua Satellite, which carries the Atmospheric Infrared Sounder (AIRS), as well as water vapor information from Global Positioning System (GPS) satellites. This extension and reprocessing effort increases the temporal coverage from 14 to 22 (1988-2009) years, making the data set more useful and consistent for investigation of the long-term trends which are hypothesized to occur as Earth warms. In addition to the long-standing daily, 1-degree gridded Total Precipitable Water (TPW) and layered Precipitable Water (PW) products, NVAP-M includes additional products geared towards different scientific needs. Three separate processing streams produced products directed towards specific research goals. These are NVAP-M Climate, designed to provide the most stable water vapor data set over time for use in climate applications, and NVAP-M Weather, designed to provide higher spatial and temporal resolution products for use in studies on shorter time scales as well as weather case studies. Additionally, an ocean-only (NVAP-M Ocean) version includes only data from the SSM/I and is intended to mirror other available SSM/I-only water vapor data sets.","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/C3880790136-LARC_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@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/documents/nvap/NVAP_M_ATBD_Feb2013.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/nvap/guide/NVAPM_User_Guide.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/nvap/read_software/read_nvapm.pro.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/project/NVAP-M","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3880790136-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/NVAP-M/NVAP_CLIMATE_TOTAL-PRECIPITABLE-WATER_L3.001","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3880790136-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/NVAP-M/NVAP_CLIMATE_TOTAL-PRECIPITABLE-WATER_L3.001","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"[\"CARTESIAN\", [{\"Boundary\": {\"Points\": [{\"Latitude\": -90, \"Longitude\": -179.9}, {\"Latitude\": -90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": -179.9}, {\"Latitude\": -90, \"Longitude\": -179.9}]}}]]","temporal":"1988-01-01/2009-12-01","theme":["Earth Science"],"title":"NASA Water Vapor Project MEaSUREs (NVAP-M) CLIMATE Total Precipitable Water"},"description":"NVAP_CLIMATE_Total-Precipitable-Water data set is designed to provide the most stable water vapor dataset over time for use in climate applications. NASA Water Vapor Project MEaSUREs (NVAP-M) Climate only includes data from stable instruments that have undergone intercalibration efforts to ensure consistency between data from the same instrument flying on multiple satellite platforms. The new NVAP data sets are produced under the NASA Making Earth Science Data Records for Use in Research Environments (MEaSUREs) program and is named NVAP-M. It supersedes the previous NVAP data set. NVAP-M continues the legacy of providing high-quality, model-independent global estimates of total column and layered water vapor. The use of improved, intercalibrated data sets and algorithms that were not available for the heritage NVAP data set results in an improved and extended water vapor data set that is stable enough for climate research and of a resolution appropriate for studies on smaller spatial and temporal scales. The true value of NVAP-M will be seen in outcomes from applied and research users of the data set in various fields. Some initial NVAP-M findings are presented in Vonder Haar et al. (2012). In addition to the time-dependent artifacts present in the previous NVAP data set, a wealth of new data has become available since the last NVAP processing in 2003. These include an additional SSM/I instrument, additional NOAA satellites, the NASA Earth Observing System (EOS)-Aqua Satellite, which carries the Atmospheric Infrared Sounder (AIRS), as well as water vapor information from Global Positioning System (GPS) satellites. This extension and reprocessing effort increases the temporal coverage from 14 to 22 (1988-2009) years, making the data set more useful and consistent for investigation of the long-term trends which are hypothesized to occur as Earth warms. In addition to the long-standing daily, 1-degree gridded Total Precipitable Water (TPW) and layered Precipitable Water (PW) products, NVAP-M includes additional products geared towards different scientific needs. Three separate processing streams produced products directed towards specific research goals. These are NVAP-M Climate, designed to provide the most stable water vapor data set over time for use in climate applications, and NVAP-M Weather, designed to provide higher spatial and temporal resolution products for use in studies on shorter time scales as well as weather case studies. Additionally, an ocean-only (NVAP-M Ocean) version includes only data from the SSM/I and is intended to mirror other available SSM/I-only water vapor data sets.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/76331545-2422-452b-8486-7742d815f17b","harvest_record_raw":"https://catalog.data.gov/harvest_record/76331545-2422-452b-8486-7742d815f17b/raw","has_spatial":true,"identifier":"10.5067/NVAP-M/NVAP_CLIMATE_TOTAL-PRECIPITABLE-WATER_L3.001","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators"],"last_harvested_date":"2026-08-04T23:37:36.379585","organization":{"aliases":[""],"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"},"popularity":4,"publisher":"NASA/LARC/SD/ASDC","slug":"nasa-water-vapor-project-measures-nvap-m-climate-total-precipitable-water","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"NASA Water Vapor Project MEaSUREs (NVAP-M) CLIMATE Total Precipitable Water"},{"_score":15.398365,"_sort":[1785886653366,15.398365,4,"23081632-efd9-4c98-8742-0e327548bcb5"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"NVAP_WEATHER_Layered-Precipitable-Water data set is designed to provide higher spatial and temporal resolution products for use in studies on shorter time scales as well as weather case studies. Land GPS sites were added beginning in 1997. The new NASA Water Vapor Project (NVAP) data sets are produced under the NASA Making Earth Science Data Records for Use in Research Environments (MEaSUREs) program and is named NVAP-M. It supersedes the previous NVAP data set. NVAP-M continues the legacy of providing high-quality, model-independent global estimates of total column and layered water vapor. The use of improved, intercalibrated data sets and algorithms that were not available for the heritage NVAP data set results in an improved and extended water vapor data set that is stable enough for climate research and of a resolution appropriate for studies on smaller spatial and temporal scales. The true value of NVAP-M will be seen in outcomes from applied and research users of the data set in various fields. Some initial NVAP-M findings are presented in Vonder Haar et al. (2012). In addition to the time-dependent artifacts present in the previous NVAP data set, a wealth of new data has become available since the last NVAP processing in 2003. These include an additional SSM/I instrument, additional NOAA satellites, the NASA Earth Observing System (EOS)-Aqua Satellite, which carries the Atmospheric Infrared Sounder (AIRS), as well as water vapor information from Global Positioning System (GPS) satellites. This extension and reprocessing effort increases the temporal coverage from 14 to 22 (1988-2009) years, making the data set more useful and consistent for investigation of the long-term trends which are hypothesized to occur as Earth warms. In addition to the long-standing daily, 1-degree gridded Total Precipitable Water (TPW) and layered Precipitable Water (PW) products, NVAP-M includes additional products geared towards different scientific needs. Three separate processing streams produced products directed towards specific research goals. These are NVAP-M Climate, designed to provide the most stable water vapor data set over time for use in climate applications, and NVAP-M Weather, designed to provide higher spatial and temporal resolution products for use in studies on shorter time scales as well as weather case studies. Additionally, an ocean-only (NVAP-M Ocean) version includes only data from the SSM/I and is intended to mirror other available SSM/I-only water vapor data sets.","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/C3880790177-LARC_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@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/documents/nvap/NVAP_M_ATBD_Feb2013.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/nvap/guide/NVAPM_User_Guide.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/nvap/read_software/read_nvapm.pro.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/project/NVAP-M","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3880790177-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/NVAP-M/NVAP_WEATHER_LAYERED-PRECIPITABLE-WATER_L3.001","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3880790177-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/NVAP-M/NVAP_WEATHER_LAYERED-PRECIPITABLE-WATER_L3.001","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"[\"CARTESIAN\", [{\"Boundary\": {\"Points\": [{\"Latitude\": -90, \"Longitude\": -179.9}, {\"Latitude\": -90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": -179.9}, {\"Latitude\": -90, \"Longitude\": -179.9}]}}]]","temporal":"1988-01-01/2009-12-01","theme":["Earth Science"],"title":"NASA Water Vapor Project MEaSUREs (NVAP-M) WEATHER Layered Precipitable Water"},"description":"NVAP_WEATHER_Layered-Precipitable-Water data set is designed to provide higher spatial and temporal resolution products for use in studies on shorter time scales as well as weather case studies. Land GPS sites were added beginning in 1997. The new NASA Water Vapor Project (NVAP) data sets are produced under the NASA Making Earth Science Data Records for Use in Research Environments (MEaSUREs) program and is named NVAP-M. It supersedes the previous NVAP data set. NVAP-M continues the legacy of providing high-quality, model-independent global estimates of total column and layered water vapor. The use of improved, intercalibrated data sets and algorithms that were not available for the heritage NVAP data set results in an improved and extended water vapor data set that is stable enough for climate research and of a resolution appropriate for studies on smaller spatial and temporal scales. The true value of NVAP-M will be seen in outcomes from applied and research users of the data set in various fields. Some initial NVAP-M findings are presented in Vonder Haar et al. (2012). In addition to the time-dependent artifacts present in the previous NVAP data set, a wealth of new data has become available since the last NVAP processing in 2003. These include an additional SSM/I instrument, additional NOAA satellites, the NASA Earth Observing System (EOS)-Aqua Satellite, which carries the Atmospheric Infrared Sounder (AIRS), as well as water vapor information from Global Positioning System (GPS) satellites. This extension and reprocessing effort increases the temporal coverage from 14 to 22 (1988-2009) years, making the data set more useful and consistent for investigation of the long-term trends which are hypothesized to occur as Earth warms. In addition to the long-standing daily, 1-degree gridded Total Precipitable Water (TPW) and layered Precipitable Water (PW) products, NVAP-M includes additional products geared towards different scientific needs. Three separate processing streams produced products directed towards specific research goals. These are NVAP-M Climate, designed to provide the most stable water vapor data set over time for use in climate applications, and NVAP-M Weather, designed to provide higher spatial and temporal resolution products for use in studies on shorter time scales as well as weather case studies. Additionally, an ocean-only (NVAP-M Ocean) version includes only data from the SSM/I and is intended to mirror other available SSM/I-only water vapor data sets.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/53525028-bd2a-43db-a256-03194c1642e1","harvest_record_raw":"https://catalog.data.gov/harvest_record/53525028-bd2a-43db-a256-03194c1642e1/raw","has_spatial":true,"identifier":"10.5067/NVAP-M/NVAP_WEATHER_LAYERED-PRECIPITABLE-WATER_L3.001","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators"],"last_harvested_date":"2026-08-04T23:37:33.366016","organization":{"aliases":[""],"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"},"popularity":4,"publisher":"NASA/LARC/SD/ASDC","slug":"nasa-water-vapor-project-measures-nvap-m-weather-layered-precipitable-water","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"NASA Water Vapor Project MEaSUREs (NVAP-M) WEATHER Layered Precipitable Water"},{"_score":50.454903,"_sort":[1785886386970,50.454903,2,"6d8a8059-5d5e-480e-9078-420aed1db71d"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The VCO IR1 EDR data set contains products acquired by the IR1 instrument onboard the Venus Climate Orbiter (VCO, also known as PLANET-C and AKATSUKI) spacecraft. The data files are provided in FITS format with an HDU as IMAGE extension, and it also contains metadata to the header of the HDU.","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/C2491756266-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://aquarius.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-010-UG-0008_AquariusUserGuide_DatasetV5.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0006_ProposalForFlags%26Masks_DatasetVersion3.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0016_AquariusSalinityDataValidationAnalysis_DatasetVersion5.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0017_AquariusATBD_Level2_Addendum5_DatasetVersion5.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0017_AquariusATBD_Level2_EndofMission_DatasetVersion5.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0017_AquariusScatterometerCalibrationReview.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0017_Aquarius_ATBD-EndOfMission.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0017_Aquarius_ATBD-EndOfMission_Supplements.zip","format":"ZIP","mediaType":"application/zip"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0017_Aquarius_AntennaPatternCoefficientUpdates_DatasetVersion3.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0017_Aquarius_L2toL3ATBD_DatasetVersion5.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0017_Performance_Degradation_and_QC_Flagging_of_Aquarius_L2_Salinity_Retrievals_V4.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0018_AquariusLevel2specification_DatasetVersion5.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0018_Ocean_Level-3_Standard_Mapped_Image_Products.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0028_V5_AVDS_Tech_Memo.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0029_Aquarius_counts_to_TA.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-014-PS-0030_Full_Range_Cal_27Feb18.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AQ-017-AquariusMissionSummary.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/AquariusATBDdocuments_10.5067-DOCUM-AQR04.zip","format":"ZIP","mediaType":"application/zip"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/Aquarius_RFI_products_UserGuide.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/Aquarius_V5.0-V4.0_SummaryOfChanges.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/EDinnat_etal_Paper_SkyTBMap_Lband.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/aquarius/open/docs/v5/UserGuideAquariusCelestialSkyMicrowaveEmissionMapProduct.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2491756266-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://oceancolor.gsfc.nasa.gov/sdpscgi/public/aquarius_report.cgi","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/AQUARIUS_L3_SPICINESS_SMIA_28DAY-RUNNINGMEAN_V5.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/aquarius","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2491756266-POCLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"urn:nasa:pds:context_pds3:data_set:data_set.vco-v-ir1-2-edr-v1.0;urn:nasa:pds:context_pds3:data_set:data_set.vco-v-ir1-2-edr-v1.0::1.0","keyword":["__"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"Planetary Atmospheres"},"theme":["Planetary Science"],"title":"VENUS CLIMATE ORBITER IR1 RAW DATA V1.0"},"description":"The VCO IR1 EDR data set contains products acquired by the IR1 instrument onboard the Venus Climate Orbiter (VCO, also known as PLANET-C and AKATSUKI) spacecraft. The data files are provided in FITS format with an HDU as IMAGE extension, and it also contains metadata to the header of the HDU.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/03f7ae49-acf8-43a3-bdc7-b758f6e4bba0","harvest_record_raw":"https://catalog.data.gov/harvest_record/03f7ae49-acf8-43a3-bdc7-b758f6e4bba0/raw","has_spatial":false,"identifier":"urn:nasa:pds:context_pds3:data_set:data_set.vco-v-ir1-2-edr-v1.0;urn:nasa:pds:context_pds3:data_set:data_set.vco-v-ir1-2-edr-v1.0::1.0","keyword":["__"],"last_harvested_date":"2026-08-04T23:33:06.970746","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"Planetary Atmospheres","slug":"venus-climate-orbiter-ir1-raw-data-v1-0-e7035","spatial_centroid":null,"spatial_shape":null,"theme":["Planetary Science"],"title":"VENUS CLIMATE ORBITER IR1 RAW DATA V1.0"},{"_score":17.285107,"_sort":[1785886385590,17.285107,3,"2e0bb52e-97ae-4571-a507-afb6fa1f41f8"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present.   The CDR is critically important to studying global climate change.  The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions.  The LTDR draws from the following eight AVHRR missions: \r\nNOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B.\r\n\r\nCurrently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR).  LAI/fPAR was developed as an experimental product.\r\n\r\nThe NOAA-16 AVHRR Atmospherically Corrected Surface Reflectance Daily L3 Global 0.05Deg CMG, short-name N16_ AVH09C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (AVH01C1). The N16_ AVH09C1 consist of BRDF-corrected surface reflectance for bands 1, 2, and 3, data Quality flags, angles (solar zenith, view zenith, and relative azimuth), and thermal data (thermal bands 3, 4, and 5). The AVH09C1 product is available in HDF4 file 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/C2736726119-LAADS.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/466/N16_AVH09C1/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ladsweb.modaps.eosdis.nasa.gov/search/order/1/N16_AVH09C1--466","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://landweb.modaps.eosdis.nasa.gov/QA_WWW/forPage/user_guide/avhrr/LTDR_Ver5_Products_UserGuide_v1.0.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://ltdr.modaps.eosdis.nasa.gov/cgi-bin/ltdr/ltdrPage.cgi?fileName=docs","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2736726119-LAADS","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/AVHRR/N16_AVH09C1.006","keyword":["earth-science-infrared-wavelengths-spectral-engineering-brightness-temperature","earth-science-infrared-wavelengths-spectral-engineering-reflected-infrared","earth-science-surface-radiative-properties-land-surface-reflectance"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90.0, \"WestBoundingCoordinate\": -180.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]","temporal":"2000-11-01/2008-01-02","theme":["Earth Science"],"title":"NOAA-16 AVHRR Atmospherically Corrected Surface Reflectance Daily L3 Global 0.05 Deg. CMG"},"description":"The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present.   The CDR is critically important to studying global climate change.  The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions.  The LTDR draws from the following eight AVHRR missions: \r\nNOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B.\r\n\r\nCurrently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR).  LAI/fPAR was developed as an experimental product.\r\n\r\nThe NOAA-16 AVHRR Atmospherically Corrected Surface Reflectance Daily L3 Global 0.05Deg CMG, short-name N16_ AVH09C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (AVH01C1). The N16_ AVH09C1 consist of BRDF-corrected surface reflectance for bands 1, 2, and 3, data Quality flags, angles (solar zenith, view zenith, and relative azimuth), and thermal data (thermal bands 3, 4, and 5). The AVH09C1 product is available in HDF4 file format.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/7abbfc2e-ad57-48fa-a9c4-75d1b20583b8","harvest_record_raw":"https://catalog.data.gov/harvest_record/7abbfc2e-ad57-48fa-a9c4-75d1b20583b8/raw","has_spatial":true,"identifier":"10.5067/AVHRR/N16_AVH09C1.006","keyword":["earth-science-infrared-wavelengths-spectral-engineering-brightness-temperature","earth-science-infrared-wavelengths-spectral-engineering-reflected-infrared","earth-science-surface-radiative-properties-land-surface-reflectance"],"last_harvested_date":"2026-08-04T23:33:05.590404","organization":{"aliases":[""],"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"},"popularity":3,"publisher":"NASA/GSFC/SED/ESD/HBSL/BISB/LAADS","slug":"noaa-16-avhrr-atmospherically-corrected-surface-reflectance-daily-l3-global-0-05-deg-cmg","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"NOAA-16 AVHRR Atmospherically Corrected Surface Reflectance Daily L3 Global 0.05 Deg. CMG"},{"_score":10.882347,"_sort":[1785885729346,10.882347,0,"d8727706-2848-47fa-b327-43a9ac99a9e0"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"NASA Space Physics Data Facility","hasEmail":"mailto:NASA-SPDF-Support@nasa.onmicrosoft.com"},"description":"CAL_LID_L2_PSCMask-Standard-V3-00 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 Polar Stratospheric Clouds (PSC) data product. This data product was collected using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument and describes the spatial distribution, optical properties, and composition of PSC layers observed. The product contains profiles of PSC presence, composition, optical properties, and meteorological information on a uniform 5-km horizontal x 180-m vertical grid along CALIPSO orbit tracks. Aura Microwave Limb Sounder (MLS) measurements of the primary PSC condensable vapors HNO3 and H2O and a number of parameters from the Aura MLS V2 Derived Meteorological Products (DMPs) are also included in this product. \n\nCALIPSO was a partnership between NASA and the French Space Agency, CNES. \n\nCALIPSO was launched on April 28, 2006 to study the many roles played by clouds and aerosols in Earth\u2019s climate and weather. It flew in the international A-Train constellation for coincident Earth observations from launch until September 13, 2018, when CALIPSO began lowering its orbit from 705 km to 688 km (428 miles) above the Earth to resume formation flying with CloudSat as part of the \u201cC-Train\u201d. The CALIPSO satellite carried three remote sensing instruments: the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field-of-View Camera (WFC). By mutual agreement between NASA and CNES, the CALIPSO science mission concluded on August 1, 2023.","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://ibex.princeton.edu/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ibex.princeton.edu/DataRelease","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/CALIOP/CALIPSO/CAL_LID_L2_PSCMask-Standard-V3-00","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-atmospheric-radiation-atmosphere-scattering","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-profiles","earth-science-clouds-atmosphere-cloud-types","earth-science-clouds-atmosphere-stratospheric-clouds-observed-analyzed","earth-science-lidar-spectral-engineering-lidar-depolarization-ratio"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"[\"CARTESIAN\", [{\"Boundary\": {\"Points\": [{\"Latitude\": -90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": -180}]}}]], Minimum Altitude, Maximum Altitude, 8.3 km, 30.1 km","temporal":"2006-06-12/2023-06-30","theme":["Earth Science"],"title":"CALIPSO Lidar Level 2 Polar Stratospheric Cloud (PSC), V3-00"},"description":"CAL_LID_L2_PSCMask-Standard-V3-00 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Lidar Level 2 Polar Stratospheric Clouds (PSC) data product. This data product was collected using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument and describes the spatial distribution, optical properties, and composition of PSC layers observed. The product contains profiles of PSC presence, composition, optical properties, and meteorological information on a uniform 5-km horizontal x 180-m vertical grid along CALIPSO orbit tracks. Aura Microwave Limb Sounder (MLS) measurements of the primary PSC condensable vapors HNO3 and H2O and a number of parameters from the Aura MLS V2 Derived Meteorological Products (DMPs) are also included in this product. \n\nCALIPSO was a partnership between NASA and the French Space Agency, CNES. \n\nCALIPSO was launched on April 28, 2006 to study the many roles played by clouds and aerosols in Earth\u2019s climate and weather. It flew in the international A-Train constellation for coincident Earth observations from launch until September 13, 2018, when CALIPSO began lowering its orbit from 705 km to 688 km (428 miles) above the Earth to resume formation flying with CloudSat as part of the \u201cC-Train\u201d. The CALIPSO satellite carried three remote sensing instruments: the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field-of-View Camera (WFC). By mutual agreement between NASA and CNES, the CALIPSO science mission concluded on August 1, 2023.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/ae91f13f-cb18-464a-8a29-84e4a620cefb","harvest_record_raw":"https://catalog.data.gov/harvest_record/ae91f13f-cb18-464a-8a29-84e4a620cefb/raw","has_spatial":true,"identifier":"10.5067/CALIOP/CALIPSO/CAL_LID_L2_PSCMask-Standard-V3-00","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-atmospheric-radiation-atmosphere-scattering","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-profiles","earth-science-clouds-atmosphere-cloud-types","earth-science-clouds-atmosphere-stratospheric-clouds-observed-analyzed","earth-science-lidar-spectral-engineering-lidar-depolarization-ratio"],"last_harvested_date":"2026-08-04T23:22:09.346927","organization":{"aliases":[""],"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"},"popularity":0,"publisher":"NASA/LARC/SD/ASDC","slug":"calipso-lidar-level-2-polar-stratospheric-cloud-psc-v3-00","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CALIPSO Lidar Level 2 Polar Stratospheric Cloud (PSC), V3-00"},{"_score":9.647497,"_sort":[1785885721543,9.647497,0,"31c451a8-1811-40f6-a343-ec32a2ed5904"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"CAL_LID_L3_Tropospheric_APro_CloudFree-Standard-V5-00 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation(CALIPSO) Lidar Level 3 Tropospheric Aerosol, Cloud-Free, data product. This data product was collected using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. This data product, generated separately between day and night, reports monthly mean profiles of aerosol optical properties on a uniform spatial grid. It is a tropospheric product, so data are only reported below altitudes of 12 km. All parameters are derived from the version 5.00 CALIOP Level 2 data and have been quality screened prior to averaging. The primary quantities reported are vertical profiles of the aerosol extinction coefficient at 532 nm and its vertical integral, the aerosol optical depth (AOD). Aerosol type and spatial distributional information are also included. The Cloud-Free designate indicates that only cloud-free level 2 columns are averaged. \n\nCALIPSO was a partnership between NASA and the French Space Agency, CNES. CALIPSO was launched on April 28, 2006 to study the many roles played by clouds and aerosols in Earth\u2019s climate and weather. It flew in the international A-Train constellation for coincident Earth observations from launch until September 13, 2018, when CALIPSO began lowering its orbit from705 km to 688 km (428 miles) above the Earth to resume formation flying with CloudSat as part of the \u201cC-Train\u201d. The CALIPSO satellite carried three remote sensing instruments: the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field-of-View Camera (WFC). By mutual agreement between NASA and CNES, the CALIPSO science mission concluded on August 1, 2023.","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/C3964849262-LARC_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@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/documents/calipso/CALIPSO_DPC_Rev5x00.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/calipso/quality_summaries/cal_lid_l3_tropoaero_V5-00_desc_qs.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/calipso/user_guides/CALIPSO_Data_Users_Guide_FAQ_mod2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/calipso/user_guides/CALIPSO_Data_Users_Guide_Payload.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/calipso/user_guides/CALIPSO_Data_Users_Guide_Peer_Reviewed_Bibliography.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/project/CALIPSO","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/static/images/project_logos/calipso.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://calipso.cnes.fr/fr","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3964849262-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/CALIOP/CALIPSO/LID_L3_Tropospheric_APro_CloudFree-Standard-V5-00","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://ntrs.nasa.gov/citations/20260000771","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://science.nasa.gov/mission/calipso/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3964849262-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/CALIOP/CALIPSO/LID_L3_Tropospheric_APro_CloudFree-Standard-V5-00","keyword":["earth-science-aerosols-atmosphere","earth-science-aerosols-atmosphere-aerosol-extinction","earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"[\"CARTESIAN\", [{\"Boundary\": {\"Points\": [{\"Latitude\": -90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": -180}]}}]], Minimum Altitude, Maximum Altitude, -0.4 km, 12.1 km","temporal":"2006-06-01/2023-07-01","theme":["Earth Science"],"title":"CALIPSO Lidar Level 3 Tropospheric Aerosol Profiles, Cloud Free Data, Standard V5-00"},"description":"CAL_LID_L3_Tropospheric_APro_CloudFree-Standard-V5-00 is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation(CALIPSO) Lidar Level 3 Tropospheric Aerosol, Cloud-Free, data product. This data product was collected using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. This data product, generated separately between day and night, reports monthly mean profiles of aerosol optical properties on a uniform spatial grid. It is a tropospheric product, so data are only reported below altitudes of 12 km. All parameters are derived from the version 5.00 CALIOP Level 2 data and have been quality screened prior to averaging. The primary quantities reported are vertical profiles of the aerosol extinction coefficient at 532 nm and its vertical integral, the aerosol optical depth (AOD). Aerosol type and spatial distributional information are also included. The Cloud-Free designate indicates that only cloud-free level 2 columns are averaged. \n\nCALIPSO was a partnership between NASA and the French Space Agency, CNES. CALIPSO was launched on April 28, 2006 to study the many roles played by clouds and aerosols in Earth\u2019s climate and weather. It flew in the international A-Train constellation for coincident Earth observations from launch until September 13, 2018, when CALIPSO began lowering its orbit from705 km to 688 km (428 miles) above the Earth to resume formation flying with CloudSat as part of the \u201cC-Train\u201d. The CALIPSO satellite carried three remote sensing instruments: the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field-of-View Camera (WFC). By mutual agreement between NASA and CNES, the CALIPSO science mission concluded on August 1, 2023.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/c82116a4-4ffc-42c1-8850-9d239090dee8","harvest_record_raw":"https://catalog.data.gov/harvest_record/c82116a4-4ffc-42c1-8850-9d239090dee8/raw","has_spatial":true,"identifier":"10.5067/CALIOP/CALIPSO/LID_L3_Tropospheric_APro_CloudFree-Standard-V5-00","keyword":["earth-science-aerosols-atmosphere","earth-science-aerosols-atmosphere-aerosol-extinction","earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness"],"last_harvested_date":"2026-08-04T23:22:01.543114","organization":{"aliases":[""],"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"},"popularity":0,"publisher":"NASA/LARC/SD/ASDC","slug":"calipso-lidar-level-3-tropospheric-aerosol-profiles-cloud-free-data-standard-v5-00","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CALIPSO Lidar Level 3 Tropospheric Aerosol Profiles, Cloud Free Data, Standard V5-00"},{"_score":10.260059,"_sort":[1785885622518,10.260059,2,"d5809819-8faf-40b7-b8a4-afceabded7a9"],"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 ground in situ flux and meteorological science data from fixed instruments at three eddy covariance tower sites located in the Alaskan Arctic tundra. Real and gap-filled observations of carbon dioxide, methane, water vapor, and latent energy flux in addition to standard meteorological and environmental variables are reported at half-hourly intervals between 2011 and 2015 for sites at Atqasuk, Barrow, and Ivotuk, Alaska. The three sites form a 300-km north-south transect on the North Slope of Alaska, each site representing distinct Arctic vegetation communities. These tower measurements create a long-term record of one of the largest, most volatile carbon stocks on the planet. Observations from these towers are being used to determine the seasonal and inter-annual patterns of CO2 and CH4 flux, and their relationship to changes in environmental factors.","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/C2236316255-ORNL_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://carve.ornl.gov","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://daac.ornl.gov/CARVE/guides/CARVE_L1_Ground_Flux_Fig1.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/protected/bundle/CARVE_L1_Ground_Flux_1424.zip","format":"ZIP","mediaType":"application/zip"},{"@type":"dcat:Distribution","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/public/carve/campaign/CARVE_L1_Ground_Flux/comp/CARVE_L1_Ground_Flux.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.3334/ORNLDAAC/1424","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2236316255-ORNL_CLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.3334/ORNLDAAC/1424","keyword":["earth-science-atmospheric-chemistry-atmosphere-carbon-and-hydrocarbon-compounds","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-ecological-dynamics-biosphere-ecosystem-functions","earth-science-land-surface-agriculture-indicators-climate-indicators-soil-moisture","earth-science-land-surface-agriculture-indicators-climate-indicators-soil-temperature"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"ORNL_DAAC"},"spatial":"[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -157.409, \"NorthBoundingCoordinate\": 71.3225, \"EastBoundingCoordinate\": -155.748, \"SouthBoundingCoordinate\": 68.4865}]]","temporal":"2011-05-30/2016-01-07","theme":["Earth Science"],"title":"CARVE: L1 In-situ Carbon and CH4 Flux and Meteorology at EC Towers, Alaska, 2011-2015"},"description":"This data set provides ground in situ flux and meteorological science data from fixed instruments at three eddy covariance tower sites located in the Alaskan Arctic tundra. Real and gap-filled observations of carbon dioxide, methane, water vapor, and latent energy flux in addition to standard meteorological and environmental variables are reported at half-hourly intervals between 2011 and 2015 for sites at Atqasuk, Barrow, and Ivotuk, Alaska. The three sites form a 300-km north-south transect on the North Slope of Alaska, each site representing distinct Arctic vegetation communities. These tower measurements create a long-term record of one of the largest, most volatile carbon stocks on the planet. Observations from these towers are being used to determine the seasonal and inter-annual patterns of CO2 and CH4 flux, and their relationship to changes in environmental factors.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/ce96f047-7109-4bba-9a65-fb93b0091ef9","harvest_record_raw":"https://catalog.data.gov/harvest_record/ce96f047-7109-4bba-9a65-fb93b0091ef9/raw","has_spatial":true,"identifier":"10.3334/ORNLDAAC/1424","keyword":["earth-science-atmospheric-chemistry-atmosphere-carbon-and-hydrocarbon-compounds","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-ecological-dynamics-biosphere-ecosystem-functions","earth-science-land-surface-agriculture-indicators-climate-indicators-soil-moisture","earth-science-land-surface-agriculture-indicators-climate-indicators-soil-temperature"],"last_harvested_date":"2026-08-04T23:20:22.518638","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"ORNL_DAAC","slug":"carve-l1-in-situ-carbon-and-ch4-flux-and-meteorology-at-ec-towers-alaska-2011-2015","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CARVE: L1 In-situ Carbon and CH4 Flux and Meteorology at EC Towers, Alaska, 2011-2015"},{"_score":9.17189,"_sort":[1785885512900,9.17189,1,"5e75f4c6-c63c-47c9-a2fd-f262e0052d64"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"CER_SSF1deg-Day_NOAA20-VIIRS_Edition1C is the NOAA-20 Clouds and the Earth's Radiant Energy System (CERES) Level 3 Single Scanner Footprint (SSF) Edition1C Top of Atmosphere (ToA) flux data product. The SSF One Degree (SSF1deg) Day provides daily averages on a 1-degree latitude and longitude global grid from the NOAA-20 CERES Flight Model 6 (FM-6) data. The last CERES instrument, FM-6, was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now known as NOAA-20, on November 18, 2017. The data product begins May 1, 2018. The product is distributed in monthly Hierarchical Data Format (HDF) 4 files. The file contains the daily mean for each day of the month and provides global coverage over a day.\r\nThe SSF1deg-Day granule contains daily averages of regional CERES FM6 Earth-viewing Top of Atmosphere (ToA) shortwave and longwave fluxes. The fluxes are converted from the unfiltered CERES radiances at the footprint level using the co-located Visible Infrared Imaging Radiometer Suite (VIIRS) imager-defined scene. The footprint fluxes are gridded at hourly periods and then temporally interpolated assuming constant meteorology between measurements. The ToA fluxes are provided for both clear-sky and total sky conditions. The incoming daily solar irradiance is from the Solar Radiation and Climate Experiment (SORCE) and Total Solar Irradiance (TSI). The VIIRS radiances are used with CERES-specific cloud mask and cloud property retrievals and are stratified into four atmospheric layers: surface to 700 mb, 700 mb to 500 mb, 500 to 300 mb, and above 300 mb along with the total. Each cloud layer has properties such as amount, height, temperature, pressure, optical depth, emissivity, phase, water path, and water particle size. The cloud properties are averaged for day and night (24-hour) and day-only periods.\r\nThis product uses the instantaneous gridded product, CER_SSF1deg-Hour_NOAA20-VIIRS_Edition1C, as input.","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/C3880505426-LARC_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@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/documents/ceres/CERES_ATBDs.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/ceres/examples.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/ceres/guide/cer_fsw.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/ceres/quality_summaries/CER_FSW_TRMM_Edition2C.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/ceres/read_software/cer_fsw_SampleRead_R3-521.zip","format":"ZIP","mediaType":"application/zip"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/ceres/readme/DPC_FSW_R4V3.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/ceres/readme/README.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/ceres/readme/aqua_rev.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/ceres/readme/terra_rev.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/project/CERES","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/static/images/project_logos/ceres.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/tools-and-services","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ceres.larc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ceres.larc.nasa.gov/data/documentation/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ceres.larc.nasa.gov/data/documentation/#data-products-catalog","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ceres.larc.nasa.gov/data/general-product-info/#ceres-input-data-sources","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ceres.larc.nasa.gov/instruments/satellite-missions/#trmm","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3880505426-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/TRMM/CERES/FSW-PFM-VIRS_L3.002C","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/features/AM1/terra_animations.php","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/features/CloudsInBalance","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/features/DelicateBalance/balance2.php","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/features/Iris/iris3.php","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/features/Observing/obs_5.php","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/features/Water/page4.php","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/global-maps/CERES_NETFLUX_M","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/images/2654/aqua-ceres-first-light","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/images/2984/tropical-cloud-systems-and-ceres","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/images/36518/ceres-global-cloud-fraction","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/images/535/ceres-first-light-images","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/images/563/ceres-detects-earths-heat-and-energy","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/images/600/first-monthly-ceres-global-longwave-and-shortwave-radiation","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earthobservatory.nasa.gov/images/84930/the-arctic-is-absorbing-more-sunlight","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3880505426-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://terra.nasa.gov/?section=60","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/NOAA20/CERES/SSF1DEGDAY_L3.001C","keyword":["earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness","earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-albedo","earth-science-atmospheric-radiation-atmosphere-incoming-solar-radiation","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-net-radiation","earth-science-atmospheric-radiation-atmosphere-outgoing-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-radiative-flux","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-radiation-atmosphere-solar-irradiance","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-winds-atmosphere-surface-winds","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":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"[\"CARTESIAN\", [{\"Boundary\": {\"Points\": [{\"Latitude\": -90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": -180}]}}]]","temporal":"2018-05-01/2026-06-15","theme":["Earth Science"],"title":"CERES Time-Interpolated TOA Fluxes, Clouds and Aerosols Daily NOAA-20 Edition1C"},"description":"CER_SSF1deg-Day_NOAA20-VIIRS_Edition1C is the NOAA-20 Clouds and the Earth's Radiant Energy System (CERES) Level 3 Single Scanner Footprint (SSF) Edition1C Top of Atmosphere (ToA) flux data product. The SSF One Degree (SSF1deg) Day provides daily averages on a 1-degree latitude and longitude global grid from the NOAA-20 CERES Flight Model 6 (FM-6) data. The last CERES instrument, FM-6, was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now known as NOAA-20, on November 18, 2017. The data product begins May 1, 2018. The product is distributed in monthly Hierarchical Data Format (HDF) 4 files. The file contains the daily mean for each day of the month and provides global coverage over a day.\r\nThe SSF1deg-Day granule contains daily averages of regional CERES FM6 Earth-viewing Top of Atmosphere (ToA) shortwave and longwave fluxes. The fluxes are converted from the unfiltered CERES radiances at the footprint level using the co-located Visible Infrared Imaging Radiometer Suite (VIIRS) imager-defined scene. The footprint fluxes are gridded at hourly periods and then temporally interpolated assuming constant meteorology between measurements. The ToA fluxes are provided for both clear-sky and total sky conditions. The incoming daily solar irradiance is from the Solar Radiation and Climate Experiment (SORCE) and Total Solar Irradiance (TSI). The VIIRS radiances are used with CERES-specific cloud mask and cloud property retrievals and are stratified into four atmospheric layers: surface to 700 mb, 700 mb to 500 mb, 500 to 300 mb, and above 300 mb along with the total. Each cloud layer has properties such as amount, height, temperature, pressure, optical depth, emissivity, phase, water path, and water particle size. The cloud properties are averaged for day and night (24-hour) and day-only periods.\r\nThis product uses the instantaneous gridded product, CER_SSF1deg-Hour_NOAA20-VIIRS_Edition1C, as input.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/f595f532-8fee-425b-870f-3253df73e43c","harvest_record_raw":"https://catalog.data.gov/harvest_record/f595f532-8fee-425b-870f-3253df73e43c/raw","has_spatial":true,"identifier":"10.5067/NOAA20/CERES/SSF1DEGDAY_L3.001C","keyword":["earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness","earth-science-atmospheric-pressure-atmosphere-surface-pressure","earth-science-atmospheric-radiation-atmosphere-albedo","earth-science-atmospheric-radiation-atmosphere-incoming-solar-radiation","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-net-radiation","earth-science-atmospheric-radiation-atmosphere-outgoing-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-radiative-flux","earth-science-atmospheric-radiation-atmosphere-shortwave-radiation","earth-science-atmospheric-radiation-atmosphere-solar-irradiance","earth-science-atmospheric-temperature-atmosphere-surface-temperature","earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators","earth-science-atmospheric-winds-atmosphere-surface-winds","earth-science-clouds-atmosphere-cloud-microphysics","earth-science-clouds-atmosphere-cloud-properties","earth-science-clouds-atmosphere-cloud-radiative-transfer"],"last_harvested_date":"2026-08-04T23:18:32.900293","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"NASA/LARC/SD/ASDC","slug":"ceres-time-interpolated-toa-fluxes-clouds-and-aerosols-daily-noaa-20-edition1c","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"CERES Time-Interpolated TOA Fluxes, Clouds and Aerosols Daily NOAA-20 Edition1C"},{"_score":11.961238,"_sort":[1785885271961,11.961238,2,"1b426b8b-ad50-491f-a3e1-2dfeae7f74ef"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"GEWEXSRB_Rel4-IP_Longwave_3hrlymonthly_utc is theGlobal Energy and Water Exchanges (GEWEX) Surface Radiation Budget (SRB) Integrated Product (Rel-4) Longwave 3-hourly Monthly Average (also known as diurnal average) by UTC data product. It contains global fields of 26 longwave surface, Top of Atmosphere (TOA), and atmospheric profile radiative parameters derived with the Longwave algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. This version is known as Release 4-Integrated Product. The fluxes include all-sky, clear-sky and pristine-sky TOA upward fluxes (outgoing longwave radiation, OLR), all-sky, clear-sky and pristine-sky upward and downward fluxes at: tropopause, 200hPa, 500hPa and surface. A status flag of filled cloud properties is also included. Inputs to the longwave algorithm are cloud information based on ISCCP HXS, meteorology from ISCCP nnHIRS, SeaFlux SST and surface, LandFlux meteorology, and MERRA-2 conditionally. The temporal range is January 1988 through December 2009, with the ends bound by input constraints. These data are averaged by UTC from 3-hourly values. Data collection for this product is complete.","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/C3880691757-LARC_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@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/documents/srb/SRB_Rel4-IP_ATBD.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/documents/srb/SRB_Rel4-IP_Public_Release_Announcement.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://asdc.larc.nasa.gov/project/SRB","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3880691757-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/GEWEXSRB/Rel4-IP_Longwave_3hrlymonthly_utc_1","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://gewex-srb.larc.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C3880691757-LARC_CLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/data/projects/gewex","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GEWEXSRB/Rel4-IP_Longwave_3hrlymonthly_utc_1","keyword":["earth-science-atmospheric-radiation-atmosphere","earth-science-atmospheric-radiation-atmosphere-absorption","earth-science-atmospheric-radiation-atmosphere-atmospheric-emitted-radiation","earth-science-atmospheric-radiation-atmosphere-atmospheric-heating","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-net-radiation","earth-science-atmospheric-radiation-atmosphere-outgoing-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-radiative-flux","earth-science-atmospheric-radiation-atmosphere-radiative-forcing","earth-science-atmospheric-radiation-atmosphere-scattering","earth-science-atmospheric-radiation-atmosphere-transmittance","earth-science-clouds-atmosphere","earth-science-clouds-atmosphere-cloud-radiative-transfer"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/LARC/SD/ASDC"},"spatial":"[\"CARTESIAN\", [{\"Boundary\": {\"Points\": [{\"Latitude\": -90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": -180}]}}]]","temporal":"1988-01-01/2009-12-31","theme":["Earth Science"],"title":"GEWEX SRB Integrated Product (Rel-4) Longwave 3-Hourly Monthly Average by UTC Fluxes"},"description":"GEWEXSRB_Rel4-IP_Longwave_3hrlymonthly_utc is theGlobal Energy and Water Exchanges (GEWEX) Surface Radiation Budget (SRB) Integrated Product (Rel-4) Longwave 3-hourly Monthly Average (also known as diurnal average) by UTC data product. It contains global fields of 26 longwave surface, Top of Atmosphere (TOA), and atmospheric profile radiative parameters derived with the Longwave algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. This version is known as Release 4-Integrated Product. The fluxes include all-sky, clear-sky and pristine-sky TOA upward fluxes (outgoing longwave radiation, OLR), all-sky, clear-sky and pristine-sky upward and downward fluxes at: tropopause, 200hPa, 500hPa and surface. A status flag of filled cloud properties is also included. Inputs to the longwave algorithm are cloud information based on ISCCP HXS, meteorology from ISCCP nnHIRS, SeaFlux SST and surface, LandFlux meteorology, and MERRA-2 conditionally. The temporal range is January 1988 through December 2009, with the ends bound by input constraints. These data are averaged by UTC from 3-hourly values. Data collection for this product is complete.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/5bf78865-890e-4f6f-aa2e-b2a16eb62fe4","harvest_record_raw":"https://catalog.data.gov/harvest_record/5bf78865-890e-4f6f-aa2e-b2a16eb62fe4/raw","has_spatial":true,"identifier":"10.5067/GEWEXSRB/Rel4-IP_Longwave_3hrlymonthly_utc_1","keyword":["earth-science-atmospheric-radiation-atmosphere","earth-science-atmospheric-radiation-atmosphere-absorption","earth-science-atmospheric-radiation-atmosphere-atmospheric-emitted-radiation","earth-science-atmospheric-radiation-atmosphere-atmospheric-heating","earth-science-atmospheric-radiation-atmosphere-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-net-radiation","earth-science-atmospheric-radiation-atmosphere-outgoing-longwave-radiation","earth-science-atmospheric-radiation-atmosphere-radiative-flux","earth-science-atmospheric-radiation-atmosphere-radiative-forcing","earth-science-atmospheric-radiation-atmosphere-scattering","earth-science-atmospheric-radiation-atmosphere-transmittance","earth-science-clouds-atmosphere","earth-science-clouds-atmosphere-cloud-radiative-transfer"],"last_harvested_date":"2026-08-04T23:14:31.961321","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"NASA/LARC/SD/ASDC","slug":"gewex-srb-integrated-product-rel-4-longwave-3-hourly-monthly-average-by-utc-fluxes","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GEWEX SRB Integrated Product (Rel-4) Longwave 3-Hourly Monthly Average by UTC Fluxes"},{"_score":41.84295,"_sort":[1785885264783,41.84295,1,"0f71adc0-8cb4-460b-a4b6-cccb4dfd0620"],"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/C2683433889-GHRC_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1016/j.atmosres.2004.11.035","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1029/1999GL010856","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1029/2004JD004549","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1029/JC076i006p01478","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1029/JC086iC05p04041","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1029/JD093iD10p12683","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://ghrc.earthdata.nasa.gov/browseui/#pub/nalma__1/docs/nalma_dataset.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://ghrc.nsstc.nasa.gov/home/about-ghrc/citing-ghrc-daac-data","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://journals.ametsoc.org/view/journals/atot/21/4/1520-0426_2004_021_0543_nalmal_2_0_co_2.xml","format":"XML","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2683433889-GHRC_DAAC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/AMSRE/AQUA/GPROFCLIM/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","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":"2002-06-01/2011-10-31","theme":["Earth Science"],"title":"GPM AMSR-E on Aqua (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFAQUAAMSRE_CLIM) at GES DISC"},"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/8b111c8a-d4bf-40bf-af14-aee2731fc6e6","harvest_record_raw":"https://catalog.data.gov/harvest_record/8b111c8a-d4bf-40bf-af14-aee2731fc6e6/raw","has_spatial":true,"identifier":"10.5067/GPM/AMSRE/AQUA/GPROFCLIM/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-08-04T23:14:24.783692","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-amsr-e-on-aqua-gprof-climate-based-radiometer-precipitation-profiling-l3-1-month-0-25-","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM AMSR-E on Aqua (GPROF) Climate-based Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFAQUAAMSRE_CLIM) at GES DISC"},{"_score":16.684204,"_sort":[1785885262965,16.684204,1,"0a0d5cc6-78ad-410c-8d9d-24ab644858d7"],"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/C2264136034-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://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFNOAA20ATMS_CLIM_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFNOAA20ATMS_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/GPM_3GPROFNOAA20ATMS_CLIM.07/","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://gpm1.gesdisc.eosdis.nasa.gov/opendap/GPM_L3/GPM_3GPROFNOAA20ATMS_CLIM.07/contents.html","format":"HTML","mediaType":"text/html"},{"@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=C2264136034-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/NOAA20/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","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":"2022-05-01/2026-06-15","theme":["Earth Science"],"title":"GPM ATMS on NOAA-20 (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree  V07 (GPM_3GPROFNOAA20ATMS_DAY) at GES DISC"},"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/3762ed6a-be99-4663-a2b5-a81426b683e4","harvest_record_raw":"https://catalog.data.gov/harvest_record/3762ed6a-be99-4663-a2b5-a81426b683e4/raw","has_spatial":true,"identifier":"10.5067/GPM/ATMS/NOAA20/3A-DAY/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-08-04T23:14:22.965212","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-atms-on-noaa-20-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-20 (GPROF) Radiometer Precipitation Profiling L3 1 day 0.25 degree x 0.25 degree  V07 (GPM_3GPROFNOAA20ATMS_DAY) at GES DISC"},{"_score":19.06869,"_sort":[1785885240064,19.06869,3,"ca78d3b9-653c-4030-b7c5-a1efcffff4b5"],"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/C1979128995-GHRC_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"http://dx.doi.org/10.5067/GPMGV/IFLOODS/DATA101","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1175/JHM-D-14-0145.1","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ghrc.earthdata.nasa.gov/browseui/#pub/gpmarsifld__1/docs/gpmarsifld_dataset.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://ghrc.nsstc.nasa.gov/home/about-ghrc/citing-ghrc-daac-data","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://journals.ametsoc.org/view/journals/atot/20/5/1520-0426_2003_20_752_lreitb_2_0_co_2.xml","format":"XML","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1979128995-GHRC_DAAC","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/GPM/MHS/METOPA/GPROFCLIM/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","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":"2006-11-23/2019-12-23","theme":["Earth Science"],"title":"GPM MHS on METOP-A (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07 (GPM_2AGPROFMETOPAMHS_CLIM) at GES DISC"},"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/0cff310e-058b-4d91-a7ab-3c55f191daa1","harvest_record_raw":"https://catalog.data.gov/harvest_record/0cff310e-058b-4d91-a7ab-3c55f191daa1/raw","has_spatial":true,"identifier":"10.5067/GPM/MHS/METOPA/GPROFCLIM/2A/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-08-04T23:14:00.064972","organization":{"aliases":[""],"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"},"popularity":3,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-metop-a-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-A (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07 (GPM_2AGPROFMETOPAMHS_CLIM) at GES DISC"},{"_score":16.716103,"_sort":[1785885238568,16.716103,2,"b5a48a22-2fd7-480f-a768-1b9f91d0af3b"],"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/C2264134845-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://disc.gsfc.nasa.gov/datacollection/GPM_3GPROFNOAA19MHS_07.html","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/browse/GPM_3GPROFNOAA19MHS_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/GPM_3GPROFNOAA19MHS.07/","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://gpm1.gesdisc.eosdis.nasa.gov/opendap/GPM_L3/GPM_3GPROFNOAA19MHS.07/contents.html","format":"HTML","mediaType":"text/html"},{"@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=C2264134845-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/NOAA19/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","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":"2022-05-01/2026-06-15","theme":["Earth Science"],"title":"GPM MHS on NOAA19 (GPROF) Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFNOAA19MHS) at GES DISC"},"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/9143f130-15a3-40ec-b630-928b8286a03b","harvest_record_raw":"https://catalog.data.gov/harvest_record/9143f130-15a3-40ec-b630-928b8286a03b/raw","has_spatial":true,"identifier":"10.5067/GPM/MHS/NOAA19/3A-MONTH/07","keyword":["earth-science-atmospheric-water-vapor-atmosphere","earth-science-precipitation-atmosphere"],"last_harvested_date":"2026-08-04T23:13:58.568156","organization":{"aliases":[""],"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"},"popularity":2,"publisher":"NASA/GSFC/SED/ESD/TISL/GESDISC","slug":"gpm-mhs-on-noaa19-gprof-radiometer-precipitation-profiling-l3-1-month-0-25-degree-x-0-25-d-1994b","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"GPM MHS on NOAA19 (GPROF) Radiometer Precipitation Profiling L3 1 month 0.25 degree x 0.25 degree V07 (GPM_3GPROFNOAA19MHS) at GES DISC"},{"_score":6.975919,"_sort":[1785885201400,6.975919,6,"073c7116-b1ed-4f0e-9f8b-bca85e6360af"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Earthdata Forum","hasEmail":"mailto:earthdata-support@nasa.gov"},"description":"The High Impact Weather Assessment Toolkit (HIWAT) uses a mesoscale numerical weather prediction model and the Global Precipitation Measurement (GPM) constellation of satellites. The toolkit includes a suite of ensemble model forecasts to constrain uncertainties and provide a probabilistic forecast for improved decision-making. The toolkit provides outlooks for lightning strikes, high-impact winds, high rainfall rates, hail damage, and other weather events. The toolkit provides a 54-hour probabilistic forecast over Nepal and Bangladesh along with parts of northeast India (i.e., the Hindu Kush Himalayan region). HIWAT will also support threat assessments, such as thunderstorm intensity, using GPM and impact assessments using Landsat/MODIS land imagery to identify damage scars. The dataset files are available from April 2, 2017, through October 2, 2022, in netCDF-3 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/C2756158683-GHRC_DAAC.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.1175/BAMS-D-21-0260.1","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ghrc.earthdata.nasa.gov/browseui/#pub/hiwat__1/docs/hiwat_dataset.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://ghrc.nsstc.nasa.gov/home/about-ghrc/citing-ghrc-daac-data","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ntrs.nasa.gov/api/citations/20210000535/downloads/CH15_SHKH-2020-0601_accepted.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2756158683-GHRC_DAAC","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://servir.icimod.org/science-applications/high-impact-weather-assessment-toolkit/","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/MODEL/HIWAT/DATA101","keyword":["earth-science-atmospheric-ocean-indicators-climate-indicators-cloud-indicators","earth-science-atmospheric-winds-atmosphere-upper-level-winds","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-amount","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-oceans-liquid-precipitation","earth-science-weather-events-atmosphere-stability-severe-weather-indices"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/MSFC/GHRC"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 45.951, \"WestBoundingCoordinate\": 60.562, \"EastBoundingCoordinate\": 111.438, \"SouthBoundingCoordinate\": 10.632}]]","temporal":"2017-04-02/2022-10-02","theme":["Earth Science"],"title":"High-Impact Weather Assessment Toolkit (HIWAT)"},"description":"The High Impact Weather Assessment Toolkit (HIWAT) uses a mesoscale numerical weather prediction model and the Global Precipitation Measurement (GPM) constellation of satellites. The toolkit includes a suite of ensemble model forecasts to constrain uncertainties and provide a probabilistic forecast for improved decision-making. The toolkit provides outlooks for lightning strikes, high-impact winds, high rainfall rates, hail damage, and other weather events. The toolkit provides a 54-hour probabilistic forecast over Nepal and Bangladesh along with parts of northeast India (i.e., the Hindu Kush Himalayan region). HIWAT will also support threat assessments, such as thunderstorm intensity, using GPM and impact assessments using Landsat/MODIS land imagery to identify damage scars. The dataset files are available from April 2, 2017, through October 2, 2022, in netCDF-3 format.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/0bc26993-1853-4287-ba4d-edbdba6fe527","harvest_record_raw":"https://catalog.data.gov/harvest_record/0bc26993-1853-4287-ba4d-edbdba6fe527/raw","has_spatial":true,"identifier":"10.5067/MODEL/HIWAT/DATA101","keyword":["earth-science-atmospheric-ocean-indicators-climate-indicators-cloud-indicators","earth-science-atmospheric-winds-atmosphere-upper-level-winds","earth-science-precipitation-atmosphere-liquid-precipitation","earth-science-precipitation-atmosphere-precipitation-amount","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-oceans-liquid-precipitation","earth-science-weather-events-atmosphere-stability-severe-weather-indices"],"last_harvested_date":"2026-08-04T23:13:21.400754","organization":{"aliases":[""],"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"},"popularity":6,"publisher":"NASA/MSFC/GHRC","slug":"high-impact-weather-assessment-toolkit-hiwat","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"High-Impact Weather Assessment Toolkit (HIWAT)"},{"_score":10.853249,"_sort":[1785885187000,10.853249,1,"58d7a9bf-6190-4118-8d9c-9f74d6cb85ad"],"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 monthly-averaged ocean density, stratification, and hydrostatic pressure interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","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/C2076114664-LPCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://appeears.earthdatacloud.nasa.gov/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/ECOSTRESS/ECO_L2_LSTE.002","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ecostress.jpl.nasa.gov/science","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/nasa/ECOSTRESS-Data-Resources","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/documents/1573/Quick_Guide_for_Accessing_ECOSTRESS_Swath_Data_in_NASA_Earthdata_Search.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/documents/1574/ECOL2_User_Guide_V2.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/documents/2235/ECO2_LSTE_ATBD_V1.1.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/documents/2249/obst_all_sort.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/documents/2253/qa_20250423-present.txt","format":"TXT","mediaType":"text/plain"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/documents/299/ECO2_ASD_V1.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/documents/380/ECO2_PSD_V1.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2076114664-LPCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/centers/lp-daac","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/ECG5M-ODE44","keyword":["earth-science-ocean-pressure-oceans","earth-science-ocean-pressure-oceans-water-pressure","earth-science-salinity-density-oceans","earth-science-salinity-density-oceans-density","earth-science-services-earth-science-reanalyses-assimilation-models-models"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"EastBoundingCoordinate\": 180.0, \"NorthBoundingCoordinate\": 90.0, \"SouthBoundingCoordinate\": -90.0, \"WestBoundingCoordinate\": -180.0}]]","temporal":"1992-01-01/2018-01-01","theme":["Earth Science"],"title":"ECCO Ocean Density, Stratification, and Hydrostatic Pressure - Monthly Mean 0.5 Degree (Version 4 Release 4)"},"description":"This dataset contains monthly-averaged ocean density, stratification, and hydrostatic pressure interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/8c794caf-7938-49f4-875e-4d968ee6f187","harvest_record_raw":"https://catalog.data.gov/harvest_record/8c794caf-7938-49f4-875e-4d968ee6f187/raw","has_spatial":true,"identifier":"10.5067/ECG5M-ODE44","keyword":["earth-science-ocean-pressure-oceans","earth-science-ocean-pressure-oceans-water-pressure","earth-science-salinity-density-oceans","earth-science-salinity-density-oceans-density","earth-science-services-earth-science-reanalyses-assimilation-models-models"],"last_harvested_date":"2026-08-04T23:13:07.000461","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"NASA/JPL/PODAAC","slug":"ecco-ocean-density-stratification-and-hydrostatic-pressure-monthly-mean-0-5-degree-version","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ECCO Ocean Density, Stratification, and Hydrostatic Pressure - Monthly Mean 0.5 Degree (Version 4 Release 4)"},{"_score":10.288322,"_sort":[1785885185761,10.288322,1,"771019f3-1fd4-4408-88c3-9426ee7fcbcb"],"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 daily-averaged ocean three-dimensional potential temperature fluxes on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height and model sea level anomaly (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","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/C1990404798-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_overview_plots.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_reproduction_howto.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_synopsis.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_user_guide.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C1990404798-POCLOUD/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/ECG5M-ODE44","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://dspace.mit.edu/handle/1721.1/110380","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ecco-v4-python-tutorial.readthedocs.io/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/ECCO-GROUP/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/ECCO-GROUP/ECCO-v4-Configurations/tree/master/ECCOv4%20Release%204","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/Podaac/thumbnails/ECCO_L4_DENS_STRAT_PRESS_05DEG_MONTHLY_V4R4.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/ecco","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1990404798-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.ecco-group.org","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/ECL5D-3TF44","keyword":["earth-science-ocean-heat-budget-oceans-heat-flux","earth-science-services-earth-science-reanalyses-assimilation-models-models"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90.0, \"WestBoundingCoordinate\": -180.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]","temporal":"1992-01-01/2018-01-01","theme":["Earth Science"],"title":"ECCO Ocean Three-Dimensional Potential Temperature Fluxes - Daily Mean llc90 Grid (Version 4 Release 4)"},"description":"This dataset provides daily-averaged ocean three-dimensional potential temperature fluxes on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height and model sea level anomaly (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/078a8e96-dd0e-4e71-b7ba-cc5343be4380","harvest_record_raw":"https://catalog.data.gov/harvest_record/078a8e96-dd0e-4e71-b7ba-cc5343be4380/raw","has_spatial":true,"identifier":"10.5067/ECL5D-3TF44","keyword":["earth-science-ocean-heat-budget-oceans-heat-flux","earth-science-services-earth-science-reanalyses-assimilation-models-models"],"last_harvested_date":"2026-08-04T23:13:05.761119","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"NASA/JPL/PODAAC","slug":"ecco-ocean-three-dimensional-potential-temperature-fluxes-daily-mean-llc90-grid-version-4-","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ECCO Ocean Three-Dimensional Potential Temperature Fluxes - Daily Mean llc90 Grid (Version 4 Release 4)"},{"_score":10.882347,"_sort":[1785885184580,10.882347,1,"608a1898-ea15-4f3a-b69a-24bac978f8d2"],"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 daily-averaged ocean velocity on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","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/C1991543808-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_overview_plots.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_reproduction_howto.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_synopsis.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_user_guide.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C1991543808-POCLOUD/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/ECL5D-OVE44","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://dspace.mit.edu/handle/1721.1/110380","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ecco-v4-python-tutorial.readthedocs.io/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/ECCO-GROUP/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/ECCO-GROUP/ECCO-v4-Configurations/tree/master/ECCOv4%20Release%204","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/Podaac/thumbnails/ECCO_L4_OCEAN_VEL_LLC0090GRID_DAILY_V4R4.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/ecco","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1991543808-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.ecco-group.org","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/ECL5D-OVE44","keyword":["earth-science-ocean-circulation-oceans","earth-science-ocean-circulation-oceans-ocean-currents","earth-science-services-earth-science-reanalyses-assimilation-models-models"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90.0, \"WestBoundingCoordinate\": -180.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]","temporal":"1992-01-01/2018-01-01","theme":["Earth Science"],"title":"ECCO Ocean Velocity - Daily Mean llc90 Grid (Version 4 Release 4)"},"description":"This dataset provides daily-averaged ocean velocity on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/04b3f8f4-d5c9-4b8f-8113-9fa355a11cee","harvest_record_raw":"https://catalog.data.gov/harvest_record/04b3f8f4-d5c9-4b8f-8113-9fa355a11cee/raw","has_spatial":true,"identifier":"10.5067/ECL5D-OVE44","keyword":["earth-science-ocean-circulation-oceans","earth-science-ocean-circulation-oceans-ocean-currents","earth-science-services-earth-science-reanalyses-assimilation-models-models"],"last_harvested_date":"2026-08-04T23:13:04.580883","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"NASA/JPL/PODAAC","slug":"ecco-ocean-velocity-daily-mean-llc90-grid-version-4-release-4","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ECCO Ocean Velocity - Daily Mean llc90 Grid (Version 4 Release 4)"},{"_score":10.879223,"_sort":[1785885184022,10.879223,3,"9f30ac7d-1b16-4b23-a331-e793d67e9983"],"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 daily-averaged dynamic sea surface height interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","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/C1991543812-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_overview_plots.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_reproduction_howto.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_synopsis.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_user_guide.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C1991543812-POCLOUD/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/ECL5D-3TF44","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://dspace.mit.edu/handle/1721.1/110380","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ecco-v4-python-tutorial.readthedocs.io/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/ECCO-GROUP/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/ECCO-GROUP/ECCO-v4-Configurations/tree/master/ECCOv4%20Release%204","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/Podaac/thumbnails/ECCO_L4_OCEAN_3D_TEMPERATURE_FLUX_LLC0090GRID_DAILY_V4R4.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/ecco","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C1991543812-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.ecco-group.org","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/ECG5D-SSH44","keyword":["earth-science-sea-surface-topography-oceans-sea-surface-height","earth-science-services-earth-science-reanalyses-assimilation-models-models"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"EastBoundingCoordinate\": 180.0, \"NorthBoundingCoordinate\": 90.0, \"SouthBoundingCoordinate\": -90.0, \"WestBoundingCoordinate\": -180.0}]]","temporal":"1992-01-01/2018-01-01","theme":["Earth Science"],"title":"ECCO Sea Surface Height - Daily Mean 0.5 Degree (Version 4 Release 4)"},"description":"This dataset contains daily-averaged dynamic sea surface height interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/50c06126-1c8f-4934-92fa-7999a8a0c997","harvest_record_raw":"https://catalog.data.gov/harvest_record/50c06126-1c8f-4934-92fa-7999a8a0c997/raw","has_spatial":true,"identifier":"10.5067/ECG5D-SSH44","keyword":["earth-science-sea-surface-topography-oceans-sea-surface-height","earth-science-services-earth-science-reanalyses-assimilation-models-models"],"last_harvested_date":"2026-08-04T23:13:04.022762","organization":{"aliases":[""],"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"},"popularity":3,"publisher":"NASA/JPL/PODAAC","slug":"ecco-sea-surface-height-daily-mean-0-5-degree-version-4-release-4","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ECCO Sea Surface Height - Daily Mean 0.5 Degree (Version 4 Release 4)"},{"_score":10.7742405,"_sort":[1785885182028,10.7742405,1,"1daed54e-bcb2-4f94-bf03-5ba6c8517296"],"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 monthly-averaged sea-ice velocity interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","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/C2872578364-LPCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/EMIT/EMITL2BCO2ENH.001","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://earth.jpl.nasa.gov/emit/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/emit-sds/emit-ghg","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/nasa/EMIT-Data-Resources","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/documents/1695/EMIT_L2B_GHG_User_Guide_V1.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/documents/1696/EMIT_GHG_ATBD_V1.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://lpdaac.usgs.gov/search/?query=EMIT&content_types=E-Learning&view=cards&sort=relevance","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.earthdata.nasa.gov/centers/lp-daac","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/ECG5M-SIV44","keyword":["earth-science-sea-ice-cryosphere-sea-ice-motion","earth-science-services-earth-science-reanalyses-assimilation-models-models"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"EastBoundingCoordinate\": 180.0, \"NorthBoundingCoordinate\": 90.0, \"SouthBoundingCoordinate\": -90.0, \"WestBoundingCoordinate\": -180.0}]]","temporal":"1992-01-01/2018-01-01","theme":["Earth Science"],"title":"ECCO Sea-Ice Velocity - Monthly Mean 0.5 Degree (Version 4 Release 4)"},"description":"This dataset contains monthly-averaged sea-ice velocity interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/689090aa-fadc-4b48-84cc-0441777f09b7","harvest_record_raw":"https://catalog.data.gov/harvest_record/689090aa-fadc-4b48-84cc-0441777f09b7/raw","has_spatial":true,"identifier":"10.5067/ECG5M-SIV44","keyword":["earth-science-sea-ice-cryosphere-sea-ice-motion","earth-science-services-earth-science-reanalyses-assimilation-models-models"],"last_harvested_date":"2026-08-04T23:13:02.028366","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"NASA/JPL/PODAAC","slug":"ecco-sea-ice-velocity-monthly-mean-0-5-degree-version-4-release-4","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ECCO Sea-Ice Velocity - Monthly Mean 0.5 Degree (Version 4 Release 4)"},{"_score":8.877277,"_sort":[1785885180302,8.877277,0,"0489965b-ef43-4e0a-a6dc-ad157ac5dd39"],"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 geometric parameters for the regular 0.5-degree lat-lon grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Parameters include areas and lengths of grid cell sides and the horizontal and vertical coordinates of grid cell centers and corners. Additional information related to the global domain geometry (e.g., bathymetry and land/ocean masks) are also included. However, users should note these domain geometry fields are approximations because they have been interpolated from the ECCO lat-lon-cap 90 (llc90) native model grid. Users interested in exact budget closure calculations for volume, heat, salt, or momentum should use ECCO fields provided on the llc90 grid. Estimating the Circulation and Climate of the Ocean (ECCO) state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of a global, nominally 1-degree configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","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/C2389022016-ORNL_CLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://daac.ornl.gov/CMS/guides/EF_Data_Mexico_Fig1.png","format":"PNG","mediaType":"image/png"},{"@type":"dcat:Distribution","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/protected/bundle/EF_Data_Mexico_1693.zip","format":"ZIP","mediaType":"application/zip"},{"@type":"dcat:Distribution","downloadURL":"https://data.ornldaac.earthdata.nasa.gov/public/cms/EF_Data_Mexico/comp/EF_Data_Mexico.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.3334/ORNLDAAC/1693","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2389022016-ORNL_CLOUD","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/ECG5A-GRD44","keyword":["earth-science-sea-ice-oceans-sea-ice-concentration"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90.0, \"WestBoundingCoordinate\": 180.0, \"EastBoundingCoordinate\": -180.0, \"SouthBoundingCoordinate\": -90.0}]]","temporal":"1992-01-01/2018-01-01","theme":["Earth Science"],"title":"ECCO Geometry Parameters for the 0.5 degree Lat-Lon Model Grid (Version 4 Release 4)"},"description":"This dataset provides geometric parameters for the regular 0.5-degree lat-lon grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Parameters include areas and lengths of grid cell sides and the horizontal and vertical coordinates of grid cell centers and corners. Additional information related to the global domain geometry (e.g., bathymetry and land/ocean masks) are also included. However, users should note these domain geometry fields are approximations because they have been interpolated from the ECCO lat-lon-cap 90 (llc90) native model grid. Users interested in exact budget closure calculations for volume, heat, salt, or momentum should use ECCO fields provided on the llc90 grid. Estimating the Circulation and Climate of the Ocean (ECCO) state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of a global, nominally 1-degree configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/54c75f30-a154-4f0a-a2eb-64c59efcaa93","harvest_record_raw":"https://catalog.data.gov/harvest_record/54c75f30-a154-4f0a-a2eb-64c59efcaa93/raw","has_spatial":true,"identifier":"10.5067/ECG5A-GRD44","keyword":["earth-science-sea-ice-oceans-sea-ice-concentration"],"last_harvested_date":"2026-08-04T23:13:00.302528","organization":{"aliases":[""],"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"},"popularity":0,"publisher":"NASA/JPL/PODAAC","slug":"ecco-geometry-parameters-for-the-0-5-degree-lat-lon-model-grid-version-4-release-4","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ECCO Geometry Parameters for the 0.5 degree Lat-Lon Model Grid (Version 4 Release 4)"},{"_score":10.879223,"_sort":[1785885178777,10.879223,1,"904b34ad-1398-4cef-8152-7fd7a15d51d9"],"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 monthly-averaged ocean and sea-ice surface freshwater fluxes on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","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/C2013583732-POCLOUD.iso19115","format":"ISO","mediaType":"text/xml","title":"Original Metadata"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_overview_plots.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_reproduction_howto.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_synopsis.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/ecco/docs/v4r4_user_guide.pdf","format":"PDF","mediaType":"application/pdf"},{"@type":"dcat:Distribution","downloadURL":"https://cmr.earthdata.nasa.gov/virtual-directory/collections/C2013583732-POCLOUD/temporal","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://doi.org/10.5067/ECG5A-GRD44","format":"HTML","mediaType":"text/html"},{"@type":"dcat:Distribution","downloadURL":"https://dspace.mit.edu/handle/1721.1/110380","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://ecco-v4-python-tutorial.readthedocs.io/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/ECCO-GROUP/","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://github.com/ECCO-GROUP/ECCO-v4-Configurations/tree/master/ECCOv4%20Release%204","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/Podaac/thumbnails/ECCO_L4_GEOMETRY_05DEG_V4R4.jpg","format":"JPEG","mediaType":"image/jpeg"},{"@type":"dcat:Distribution","downloadURL":"https://podaac.jpl.nasa.gov/ecco","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://search.earthdata.nasa.gov/search/granules?p=C2013583732-POCLOUD","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.ecco-group.org","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.5067/ECL5M-FRE44","keyword":["earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-ocean-circulation-oceans-fresh-water-flux","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-services-earth-science-reanalyses-assimilation-models-models","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"license":"https://www.usa.gov/government-works","modified":"2026-06-22","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"NASA/JPL/PODAAC"},"spatial":"[\"CARTESIAN\", [{\"NorthBoundingCoordinate\": 90.0, \"WestBoundingCoordinate\": -180.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]","temporal":"1992-01-01/2018-01-01","theme":["Earth Science"],"title":"ECCO Ocean and Sea-Ice Surface Freshwater Fluxes - Monthly Mean llc90 Grid (Version 4 Release 4)"},"description":"This dataset provides monthly-averaged ocean and sea-ice surface freshwater fluxes on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/95ec45ff-6460-4092-88e3-a4ac260c48e0","harvest_record_raw":"https://catalog.data.gov/harvest_record/95ec45ff-6460-4092-88e3-a4ac260c48e0/raw","has_spatial":true,"identifier":"10.5067/ECL5M-FRE44","keyword":["earth-science-atmospheric-water-vapor-atmosphere-water-vapor-processes","earth-science-ocean-circulation-oceans-fresh-water-flux","earth-science-precipitation-atmosphere-precipitation-rate","earth-science-precipitation-atmosphere-solid-precipitation","earth-science-services-earth-science-reanalyses-assimilation-models-models","earth-science-surface-water-terrestrial-hydrosphere-surface-water-processes-measurements"],"last_harvested_date":"2026-08-04T23:12:58.777595","organization":{"aliases":[""],"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"},"popularity":1,"publisher":"NASA/JPL/PODAAC","slug":"ecco-ocean-and-sea-ice-surface-freshwater-fluxes-monthly-mean-llc90-grid-version-4-release","spatial_centroid":null,"spatial_shape":null,"theme":["Earth Science"],"title":"ECCO Ocean and Sea-Ice Surface Freshwater Fluxes - Monthly Mean llc90 Grid (Version 4 Release 4)"}],"sort":"last_harvested_date"}
