Timeline / Data.gov — Climate Datasets
changed Source changed
A new raw object was archived. Both versions are preserved. 164 line(s) added, 169 line(s) removed.
Evidence
| Source | Data.gov — Climate Datasets |
|---|---|
| Agency | Data.gov |
| URL | https://api.gsa.gov/technology/datagov/v4/search?q=climate&sort=last_harvested_date&per_page=100&api_key=${DATAGOV_API_KEY} |
| Observed by | Civic Memory, directly, on 2026-09-13T06:19:12+00:00 |
| Content type | application/json |
| Current object |
81aae92eada7de3cd64fa6220e7b2ed51c3dd3062a091407c34b5253fd3919df
download raw
metadata
|
| Previous object |
5ef125e2897f3e645c4577f1e5e4db81d047ba30ba9040dd3c4d22f8f3a66a6a
download raw
metadata
|
What changed derived
This diff is not evidence. It was produced by
civic-memory.diff_engine 1.1.0 at
2026-09-13T06:19:12+00:00 by normalizing the two archived objects above. The
objects are authoritative; this reading of them can be regenerated or deleted
without loss. 164 line(s) added, 169 line(s) removed.
--- previous +++ current @@ -1,6 +1,150 @@ { - "after": "WzE3ODkwODA1MTY2OTksOS4zNjg1OTEsMiwiMGE0NGZlNDAtMGNkZi00MGJmLTg0MjEtZmQ3N2Q4NGIxMDQzIl0=", + "after": "WzE3ODkwODA1MTcxMzYsMTEuNTE1MzA3LDIsImEwZWJjODdjLWI4YmItNGIzZi04OGZjLTQ1OWFmYTllOTc3NCJd", "results": [ + { + "_score": 47.684364, + "_sort": [ + 1789259307799, + 47.684364, + 0, + "03de313e-c0b4-4534-8bae-474841acd228" + ], + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Anne Nolin", + "hasEmail": "mailto:nolina@geo.oregonstate.edu" + }, + "description": "We used the observed historical meteorology and mean modeled snow-water-equivalent for the reference period (1989-2009) and mean modeled snow-water-equivalent under two climate change scenarios, T2 and T2P10.\nIn the T2 scenario the observed historical (reference period) meteorology is perturbed by adding +2oC to each daily temperature record in the reference period meteorology, and this data is then used as input to the model. In the T2P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +2oC to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model. T2P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +2°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://doi.org/10.5066/P19SX4T8", + "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.6a0e8faf-6aa4-4e1b-b4c7-e9044a10ac3f.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6a0e8faf-6aa4-4e1b-b4c7-e9044a10ac3f", + "keyword": [ + "McKenzie River Basin", + "Oregon", + "SWE", + "USGS:6a0e8faf-6aa4-4e1b-b4c7-e9044a10ac3f", + "climate change", + "climatologyMeteorologyAtmosphere", + "effects of climate change", + "environment", + "external research support", + "geospatial datasets", + "modeling", + "precipitation (atmospheric)", + "snow water equivalent" + ], + "modified": "2026-09-10T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-123.1290, 43.8333, -121.7185, 44.5237", + "theme": [ + "geospatial" + ], + "title": "Historical and Climate‑Scenario Snow‑Water Equivalent Conditions and Change Metrics under T2 and T2p10 Scenarios for the McKenzie River Basin, Oregon" + }, + "description": "We used the observed historical meteorology and mean modeled snow-water-equivalent for the reference period (1989-2009) and mean modeled snow-water-equivalent under two climate change scenarios, T2 and T2P10.\nIn the T2 scenario the observed historical (reference period) meteorology is perturbed by adding +2oC to each daily temperature record in the reference period meteorology, and this data is then used as input to the model. In the T2P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +2oC to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model. T2P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +2°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model.", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/4e838c0a-2422-4d25-b80b-9da27064c317", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/4e838c0a-2422-4d25-b80b-9da27064c317/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6a0e8faf-6aa4-4e1b-b4c7-e9044a10ac3f", + "keyword": [ + "McKenzie River Basin", + "Oregon", + "SWE", + "USGS:6a0e8faf-6aa4-4e1b-b4c7-e9044a10ac3f", + "climate change", + "climatologyMeteorologyAtmosphere", + "effects of climate change", + "environment", + "external research support", + "geospatial datasets", + "modeling", + "precipitation (atmospheric)", + "snow water equivalent" + ], + "last_harvested_date": "2026-09-13T00:28:27.799211", + "organization": { + "aliases": [ + "dept" + ], + "code_repo_exempt": false, + "code_repo_url": null, + "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" + }, + "parent_identifier": null, + "popularity": 0, + "publisher": "U.S. Geological Survey", + "slug": "historical-and-climatescenario-snowwater-equivalent-conditions-and-change-metrics-under-t2", + "spatial_centroid": { + "lat": 44.10946, + "lon": -122.56480000000002 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -123.129, + 43.8333 + ], + [ + -123.129, + 44.5237 + ], + [ + -121.7185, + 44.5237 + ], + [ + -121.7185, + 43.8333 + ], + [ + -123.129, + 43.8333 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Historical and Climate‑Scenario Snow‑Water Equivalent Conditions and Change Metrics under T2 and T2p10 Scenarios for the McKenzie River Basin, Oregon", + "type": "dataset" + }, { "_score": 64.95431, "_sort": [ @@ -180,10 +324,10 @@ "type": "dataset" }, { - "_score": 15.00548, + "_score": 15.003489, "_sort": [ 1789259059539, - 15.00548, + 15.003489, 0, "6b00d1de-e182-4b6c-b359-0d4545b84e5d" ], @@ -1006,10 +1150,10 @@ "type": "dataset" }, { - "_score": 24.699986, + "_score": 24.69719, "_sort": [ 1789257735718, - 24.699986, + 24.69719, 0, "229cb5a7-d202-450f-9838-bff57bc5dc36" ], @@ -2436,10 +2580,10 @@ "type": "dataset" }, { - "_score": 12.228698, + "_score": 12.227076, "_sort": [ 1789253963336, - 12.228698, + 12.227076, 0, "c5400f56-caaf-4565-9bd3-34f9441dad4c" ], @@ -2572,10 +2716,10 @@ "type": "dataset" }, { - "_score": 62.26512, + "_score": 62.249428, "_sort": [ 1789172782067, - 62.26512, + 62.249428, 4, "da2aaec4-62bc-4c37-8d6c-4b518821d658" ], @@ -3542,10 +3686,10 @@ "type": "dataset" }, { - "_score": 32.12073, + "_score": 32.117058, "_sort": [ 1789172550470, - 32.12073, + 32.117058, 11, "45da5901-9cf1-45be-95c2-78d11ddb5efe" ], @@ -4106,10 +4250,10 @@ "type": "dataset" }, { - "_score": 55.7542, + "_score": 55.740917, "_sort": [ 1789171969712, - 55.7542, + 55.740917, 0, "1a436420-1fb6-4b26-a110-fc352d2284e6" ], @@ -4520,10 +4664,10 @@ "type": "dataset" }, { - "_score": 61.12919, + "_score": 61.113945, "_sort": [ 1789170635329, - 61.12919, + 61.113945, 1, "b4028bd6-f9f9-4552-b7cd-c5543206d498" ], @@ -4944,10 +5088,10 @@ "type": "dataset" }, { - "_score": 54.712738, + "_score": 54.698975, "_sort": [ 1789169736530, - 54.712738, + 54.698975, 2, "f7e4ba50-e169-4a89-a188-c32997ff4466" ], @@ -5218,10 +5362,10 @@ "type": "dataset" }, { - "_score": 62.365944, + "_score": 62.350243, "_sort": [ 1789169467470, - 62.365944, + 62.350243, 2, "b3fd7921-fc72-4b26-ad97-463b4fcc88b8" ], @@ -5652,153 +5796,4 @@ "fn": "Sarah L. Shafer", "hasEmail": "mailto:sshafer@usgs.gov" }, - "description": "Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions.We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "http://doi.org/10.5066/F73X84PH", - "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.283f3ce9-6b5d-46db-8057-1c74b96e58ee.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_283f3ce9-6b5d-46db-8057-1c74b96e58ee", - "keyword": [ - "British Columbia", - "Climate change", - "Ecosystems", - "Forests", - "Grasses", - "Grasslands", - "Idaho", - "Montana", - "Paleoclimatology", - "Shrubs", - "Simulation and modeling", - "USGS:283f3ce9-6b5d-46db-8057-1c74b96e58ee", - "Washington", - "climate change", - "geospatial datasets", - "modeling", - "vegetation" - ], - "modified": "2026-09-09T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-125.5042, 46.4958, -113.9958, 53.0042", - "theme": [ - "geospatial" - ], - "title": "Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model" - }, - "description": "Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions.We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/e07647b3-83a4-40f1-b4bb-3ab85358f744", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/e07647b3-83a4-40f1-b4bb-3ab85358f744/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_283f3ce9-6b5d-46db-8057-1c74b96e58ee", - "keyword": [ - "British Columbia", - "Climate change", - "Ecosystems", - "Forests", - "Grasses", - "Grasslands", - "Idaho", - "Montana", - "Paleoclimatology", - "Shrubs", - "Simulation and modeling", - "USGS:283f3ce9-6b5d-46db-8057-1c74b96e58ee", - "Washington", - "climate change", - "geospatial datasets", - "modeling", - "vegetation" - ], - "last_harvested_date": "2026-09-11T23:24:35.257831", - "organization": { - "aliases": [ - "dept" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "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" - }, - "parent_identifier": null, - "popularity": 0, - "publisher": "U.S. Geological Survey", - "slug": "projected-future-vegetation-changes-for-the-northwest-united-states-and-southwest-canada-a", - "spatial_centroid": { - "lat": 49.09916, - "lon": -120.90083999999999 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -125.5042, - 46.4958 - ], - [ - -125.5042, - 53.0042 - ], - [ - -113.9958, - 53.0042 - ], - [ - -113.9958, - 46.4958 - ], - [ - -125.5042, - 46.4958 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model", - "type": "dataset" - }, - { - "_score": 62.365944, - "_sort": [ - 1789168956296, - 62.365944, - 1, - "5f067244-90e6-4d9d-b903-343030acfcb3" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Center for Large Lands + "description": "Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions.We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation chang