diff --git a/aws_geo_datasets.json b/aws_geo_datasets.json index a125c20..e5c3358 100644 --- a/aws_geo_datasets.json +++ b/aws_geo_datasets.json @@ -11066,7 +11066,7 @@ { "Name": "NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed", "Description": "New data notifications for JPSS data, only Lambda and SQS protocols allowed", - "ARN": "arn:aws:sns:us-east-1:709902155096:NewNOAA21Object", + "ARN": "arn:aws:sns:us-east-1:709902155096:NewSNPPObject", "Region": "us-east-1", "Type": "SNS Topic", "Documentation": "https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS", @@ -11089,7 +11089,7 @@ { "Name": "NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed", "Description": "New data notifications for JPSS data, only Lambda and SQS protocols allowed", - "ARN": "arn:aws:sns:us-east-1:709902155096:NewSNPPObject", + "ARN": "arn:aws:sns:us-east-1:709902155096:NewNOAA20Object", "Region": "us-east-1", "Type": "SNS Topic", "Documentation": "https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS", @@ -11112,7 +11112,7 @@ { "Name": "NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed", "Description": "New data notifications for JPSS data, only Lambda and SQS protocols allowed", - "ARN": "arn:aws:sns:us-east-1:709902155096:NewNOAA20Object", + "ARN": "arn:aws:sns:us-east-1:709902155096:NewNOAA21Object", "Region": "us-east-1", "Type": "SNS Topic", "Documentation": "https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS", @@ -12444,7 +12444,7 @@ { "Name": "NOAA U.S. Climate Gridded Dataset (NClimGrid) - New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowed", "Description": "New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowed", - "ARN": "arn:aws:sns:us-east-1:123901341784:NewNClimGridMonthlyObject", + "ARN": "arn:aws:sns:us-east-1:123901341784:NewNClimGridDailyObject", "Region": "us-east-1", "Type": "SNS Topic", "Documentation": "https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00332", @@ -12467,7 +12467,7 @@ { "Name": "NOAA U.S. Climate Gridded Dataset (NClimGrid) - New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowed", "Description": "New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowed", - "ARN": "arn:aws:sns:us-east-1:123901341784:NewNClimGridDailyObject", + "ARN": "arn:aws:sns:us-east-1:123901341784:NewNClimGridMonthlyObject", "Region": "us-east-1", "Type": "SNS Topic", "Documentation": "https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00332", @@ -16619,6 +16619,37 @@ "Host": null, "AccountRequired": null }, + { + "Name": "SeeFar V0", + "Description": "Primary SeeFar dataset containing multi-resolution satellite imagery in cloud-optimized GeoTIFF format across four spectral bands", + "ARN": "arn:aws:s3:::seefar-dataset", + "Region": "us-east-1", + "Type": "S3 Bucket", + "Documentation": "https://coastalcarbon.ai/seefar", + "Contact": "James Lowman", + "ManagedBy": "Coastal Carbon", + "UpdateFrequency": "Yearly", + "License": "The SeeFar dataset includes multiple licensing terms, specific to each satellite data source: - **Satellogic (Earthview)**: \"Creative Commons Attribution 4.0 International (CC BY 4.0) \u2014 allows for free use, sharing, and adaptation with attribution and indication of changes.\" - **WorldStrat (Airbus)**: \"Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0) \u2014 permits non-commercial use with attribution and indication of changes.\" - **Sentinel**: \"Creative Commons Attribution-Share Alike 3.0 IGO (CC BY-SA 3.0 IGO) \u2014 requires attribution, share-alike terms, and indication of any changes.\" - **USGS Landsat**: \"USGS Landsat License \u2014 unrestricted use with requested data source acknowledgment.\"", + "Tags": [ + "geospatial", + "earth observation", + "satellite imagery", + "climate", + "biodiversity", + "coastal", + "machine learning", + "environmental", + "sustainability", + "natural resource", + "global", + "mapping", + "aws-pds" + ], + "RequesterPays": null, + "Explore": null, + "Host": null, + "AccountRequired": null + }, { "Name": "Sentinel Near Real-time Canada Mirror | Miroir Sentinel temps quasi r\u00e9el du Canada", "Description": "Sentinel data over Canada | Donn\u00e9es sentinelles au Canada", diff --git a/aws_geo_datasets.tsv b/aws_geo_datasets.tsv index b2c768b..59a200f 100644 --- a/aws_geo_datasets.tsv +++ b/aws_geo_datasets.tsv @@ -409,9 +409,9 @@ NOAA Joint Polar Satellite System (JPSS) - NOAA JPSS NOAA-20 Data NOAA JPSS NOAA NOAA Joint Polar Satellite System (JPSS) - NOAA JPSS NOAA-21 Data NOAA JPSS NOAA-21 Data arn:aws:s3:::noaa-nesdis-n21-pds us-east-1 S3 Bucket https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-nesdis-n21-pds.s3.amazonaws.com/index.html)'] NOAA Joint Polar Satellite System (JPSS) - NOAA JPSS SNPP (Suomi NPP) Data NOAA JPSS SNPP (Suomi NPP) Data arn:aws:s3:::noaa-nesdis-snpp-pds us-east-1 S3 Bucket https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-nesdis-snpp-pds.s3.amazonaws.com/index.html)'] NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed New data notifications for JPSS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:709902155096:NewJPSSObject us-east-1 SNS Topic https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather -NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed New data notifications for JPSS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:709902155096:NewNOAA21Object us-east-1 SNS Topic https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed New data notifications for JPSS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:709902155096:NewSNPPObject us-east-1 SNS Topic https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed New data notifications for JPSS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:709902155096:NewNOAA20Object us-east-1 SNS Topic https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather +NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed New data notifications for JPSS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:709902155096:NewNOAA21Object us-east-1 SNS Topic https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA Multi-Radar/Multi-Sensor System (MRMS) - NOAA Multi-Radar/Multi-Sensor System (MRMS) NOAA Multi-Radar/Multi-Sensor System (MRMS) arn:aws:s3:::noaa-mrms-pds us-east-1 S3 Bucket https://www.nssl.noaa.gov/projects/mrms/ For specific MRMS data questions, please reach out to the MRMS Team at mrms@noaa [NOAA](http://www.noaa.gov/) Data is delivered in real-time with a 2-minute update cycle. Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-mrms-pds.s3.amazonaws.com/index.html)'] NOAA Multi-Radar/Multi-Sensor System (MRMS) - New data notifications for MRMS data, only Lambda and SQS protocols allowed New data notifications for MRMS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:123901341784:NewMRMSObject us-east-1 SNS Topic https://www.nssl.noaa.gov/projects/mrms/ For specific MRMS data questions, please reach out to the MRMS Team at mrms@noaa [NOAA](http://www.noaa.gov/) Data is delivered in real-time with a 2-minute update cycle. Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA Multi-Year Reanalysis of Remotely Sensed Storms (MYRORSS) Multi-Year Reanalysis of Remotely Sensed Storms arn:aws:s3:::noaa-oar-myrorss-pds us-east-1 S3 Bucket https://osf.io/9gzp2/ For any data delivery issues or any questions in general, please contact the NOA [NOAA](http://www.noaa.gov/) No updates Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, earth observation, meteorological, natural resource, sustainability, weather ['[Browse Bucket](https://noaa-oar-myrorss-pds.s3.amazonaws.com/index.html)'] @@ -463,8 +463,8 @@ NOAA Terrestrial Climate Data Records - NDVI NDVI arn:aws:s3:::noaa-cdr-ndvi-pds NOAA Terrestrial Climate Data Records - Snow Cover Extent Snow Cover Extent arn:aws:s3:::noaa-cdr-snow-cover-ext-north-pds us-east-1 S3 Bucket https://www.ncdc.noaa.gov/cdr For questions regarding the specific CDR data holdings, please contact NCEI.SAT. [NOAA](http://www.noaa.gov/) Climate Data Records are updated independently. For update frequency for a speci Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, sustainability, weather ['[Browse Bucket](https://noaa-cdr-snow-cover-ext-north-pds.s3.amazonaws.com/index.html)'] NOAA U.S. Climate Gridded Dataset (NClimGrid) - Daily NClimGrid Data Daily NClimGrid Data arn:aws:s3:::noaa-nclimgrid-daily-pds us-east-1 S3 Bucket https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc: For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Monthly Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-nclimgrid-daily-pds.s3.amazonaws.com/index.html)'] NOAA U.S. Climate Gridded Dataset (NClimGrid) - Monthly NClimGrid Data Monthly NClimGrid Data arn:aws:s3:::noaa-nclimgrid-monthly-pds us-east-1 S3 Bucket https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc: For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Monthly Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-nclimgrid-monthly-pds.s3.amazonaws.com/index.html)'] -NOAA U.S. Climate Gridded Dataset (NClimGrid) - New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe arn:aws:sns:us-east-1:123901341784:NewNClimGridMonthlyObject us-east-1 SNS Topic https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc: For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Monthly Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA U.S. Climate Gridded Dataset (NClimGrid) - New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe arn:aws:sns:us-east-1:123901341784:NewNClimGridDailyObject us-east-1 SNS Topic https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc: For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Monthly Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather +NOAA U.S. Climate Gridded Dataset (NClimGrid) - New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe arn:aws:sns:us-east-1:123901341784:NewNClimGridMonthlyObject us-east-1 SNS Topic https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc: For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Monthly Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA U.S. Climate Normals US Climate Normals Data arn:aws:s3:::noaa-normals-pds us-east-1 S3 Bucket [https://www.ncei.noaa.gov/products/us-climate-normals](https://www.ncei.noaa.go For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Data is updated on 10 year cycles or when corrections are implemented. Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, sustainability, weather ['[Browse Bucket](https://noaa-normals-pds.s3.amazonaws.com/index.html)'] NOAA Unified Forecast System (UFS) Global Ensemble Forecast System (GEFS) Version 13 Replay - New data notifications for UFS / GEFS Replay Data, only Lambda and SQS protocols New data notifications for UFS / GEFS Replay Data, only Lambda and SQS protocols arn:aws:sns:us-east-1:123901341784:NewUFS-GEFSObject us-east-1 SNS Topic https://psl.noaa.gov/data/ufs_replay/ For questions regarding data content or quality, visit [the NOAA GEFS Replay sit [NOAA](http://www.noaa.gov/) Static Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA Unified Forecast System (UFS) Global Ensemble Forecast System (GEFS) Version 13 Replay - UFS / GEFS Replay Data UFS / GEFS Replay Data arn:aws:s3:::-noaa-ufs-gefsv13replay-pds us-east-1 S3 Bucket https://psl.noaa.gov/data/ufs_replay/ For questions regarding data content or quality, visit [the NOAA GEFS Replay sit [NOAA](http://www.noaa.gov/) Static Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-ufs-gefsv13replay-pds.s3.amazonaws.com/index.html)'] @@ -626,6 +626,7 @@ SatPM2.5 Satellite-Derived Fine Particulate Matter (PM25) concentrations from th Satellite - Sea surface temperature - Level 3 - Single sensor - 1 day - Day and night time Cloud Optimised AODN dataset of IMOS - SRS - SST - L3S - Single Sensor - 1 day - arn:aws:s3:::aodn-cloud-optimised/satellite_ghrsst_l3s_1day_daynighttime_single_sensor_australia.zarr ap-southeast-2 S3 Bucket https://catalogue-imos.aodn.org.au/geonetwork/srv/eng/catalog.search#/metadata/a info@aodn.org.au AODN As Needed http://creativecommons.org/licenses/by/4.0/ oceans, satellite imagery Scottish Public Sector LiDAR Dataset LiDAR data (DSM, DTM and Laz) arn:aws:s3:::srsp-open-data eu-west-2 S3 Bucket https://remotesensingdata.gov.scot/data#/list https://remotesensingdata.gov.scot/feedback or email Scottish Government on gi-s [Joint Nature Conservation Committee](https://jncc.gov.uk/) New datasets have historically been added every 2-3 years but there is no guaran All data is made available under the [Open Government Licence v3](http://www.nat lidar, cities, coastal, environmental, urban, elevation, cog, aws-pds Sea Surface Temperature Daily Analysis: European Space Agency Climate Change Initiative product version 2.1 Global daily-mean sea surface temperatures from 1981 onwards, in Zarr format Th arn:aws:s3:::surftemp-sst us-west-2 S3 Bucket https://surftemp.github.io/sst-data-tutorials/ https://www.reading.ac.uk/met/ [University of Reading, Department of Meteorology](https://www.reading.ac.uk/met yearly Creative Commons Licence by attribution (https://creativecommons.org/licenses/by aws-pds, earth observation, oceans, climate, environmental, global, geospatial +SeeFar V0 Primary SeeFar dataset containing multi-resolution satellite imagery in cloud-op arn:aws:s3:::seefar-dataset us-east-1 S3 Bucket https://coastalcarbon.ai/seefar James Lowman Coastal Carbon Yearly The SeeFar dataset includes multiple licensing terms, specific to each satellite geospatial, earth observation, satellite imagery, climate, biodiversity, coastal, machine learning, environmental, sustainability, natural resource, global, mapping, aws-pds Sentinel Near Real-time Canada Mirror | Miroir Sentinel temps quasi réel du Canada Sentinel data over Canada | Données sentinelles au Canada arn:aws:s3:::sentinel-products-ca-mirror ca-central-1 S3 Bucket https://sentinel.esa.int/web/sentinel/home eodms-sgdot@nrcan-rncan.gc.ca [Natural Resources Canada](https://www.nrcan.gc.ca/) Sentinel-1 is an NRT dataset retrieved from ESA within 90 minutes of satellite d The access and use of Copernicus Sentinel data is available on a free, full and aws-pds, agriculture, earth observation, satellite imagery, geospatial, sustainability, disaster response, synthetic aperture radar, stac ['[EODMS STAC for Sentinel products](https://www.eodms-sgdot.nrcan-rncan.gc.ca/stac/)'] Sentinel-1 - GRD in a Requester Pays S3 bucket GRD in a Requester Pays S3 bucket arn:aws:s3:::sentinel-s1-l1c eu-central-1 S3 Bucket https://roda.sentinel-hub.com/sentinel-s1-l1c/GRD/readme.html https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, disaster response, cog, synthetic aperture radar True ['[STAC V1.0.0 endpoint](https://sentinel-s1-l1c-stac.s3.amazonaws.com/)'] Sentinel-1 - S3 Inventory files for L1C and CSV S3 Inventory files for L1C and CSV arn:aws:s3:::sentinel-inventory/ eu-central-1 S3 Bucket https://roda.sentinel-hub.com/sentinel-s1-l1c/GRD/readme.html https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, disaster response, cog, synthetic aperture radar diff --git a/aws_open_datasets.json b/aws_open_datasets.json index 40e8b5f..ca530b8 100644 --- a/aws_open_datasets.json +++ b/aws_open_datasets.json @@ -22195,8 +22195,8 @@ }, { "Name": "NREL Wind Integration National Dataset", - "Description": "Southeast Asia wind resource data (2017-2021) in HDF5 format", - "ARN": "arn:aws:s3:::nrel-pds-wtk/seasiawind/", + "Description": "Southeast Asia wind resource data v2 (2007-2021) in HDF5 format", + "ARN": "arn:aws:s3:::nrel-pds-wtk/seasiawind_v2/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://www.nrel.gov/grid/wind-toolkit.html", @@ -22211,7 +22211,7 @@ "meteorological" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=seasiawind%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=seasiawind_v2%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -22220,8 +22220,8 @@ }, { "Name": "NREL Wind Integration National Dataset", - "Description": "Puerto Rico wind resource data (2001-2020) in HDF5 format", - "ARN": "arn:aws:s3:::nrel-pds-wtk/pr100/", + "Description": "Southeast Asia wind resource data (2017-2021) in HDF5 format", + "ARN": "arn:aws:s3:::nrel-pds-wtk/seasiawind/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://www.nrel.gov/grid/wind-toolkit.html", @@ -22236,7 +22236,7 @@ "meteorological" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=pr100%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=seasiawind%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -22245,8 +22245,8 @@ }, { "Name": "NREL Wind Integration National Dataset", - "Description": "Southeast Asia wind resource data v2 (2007-2021) in HDF5 format", - "ARN": "arn:aws:s3:::nrel-pds-wtk/seasiawind_v2/", + "Description": "Puerto Rico wind resource data (2001-2020) in HDF5 format", + "ARN": "arn:aws:s3:::nrel-pds-wtk/pr100/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://www.nrel.gov/grid/wind-toolkit.html", @@ -22261,7 +22261,7 @@ "meteorological" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=seasiawind_v2%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=pr100%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -22522,8 +22522,8 @@ }, { "Name": "National Cancer Institute Imaging Data Commons (IDC) Collections", - "Description": "De-identified imaging data files in DICOM format distributed under CC-NC license Files in this bucket are covered by This bucket is updated with each new IDC release, while maintaining the versioning of the previous releases, as described in the IDC Data versioning documentation The content of the buckets is organized", - "ARN": "arn:aws:s3:::idc-open-data-cr", + "Description": "Second bucket containing de-identified imaging data files in DICOM format distributed under CC-BY license This bucket is updated with each new IDC release, while maintaining the versioning of the previous releases, as described in the IDC Data versioning documentation The content of the buckets is organized", + "ARN": "arn:aws:s3:::idc-open-data-two", "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "https://learn.canceridc.dev/", @@ -22550,8 +22550,8 @@ }, { "Name": "National Cancer Institute Imaging Data Commons (IDC) Collections", - "Description": "Second bucket containing de-identified imaging data files in DICOM format distributed under CC-BY license This bucket is updated with each new IDC release, while maintaining the versioning of the previous releases, as described in the IDC Data versioning documentation The content of the buckets is organized", - "ARN": "arn:aws:s3:::idc-open-data-two", + "Description": "De-identified imaging data files in DICOM format distributed under CC-BY license This bucket is updated with each new IDC release, while maintaining the versioning of the previous releases, as described in the IDC Data versioning documentation The content of the buckets is organized", + "ARN": "arn:aws:s3:::idc-open-data", "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "https://learn.canceridc.dev/", @@ -22578,8 +22578,8 @@ }, { "Name": "National Cancer Institute Imaging Data Commons (IDC) Collections", - "Description": "De-identified imaging data files in DICOM format distributed under CC-BY license This bucket is updated with each new IDC release, while maintaining the versioning of the previous releases, as described in the IDC Data versioning documentation The content of the buckets is organized", - "ARN": "arn:aws:s3:::idc-open-data", + "Description": "De-identified imaging data files in DICOM format distributed under CC-NC license Files in this bucket are covered by This bucket is updated with each new IDC release, while maintaining the versioning of the previous releases, as described in the IDC Data versioning documentation The content of the buckets is organized", + "ARN": "arn:aws:s3:::idc-open-data-cr", "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "https://learn.canceridc.dev/", @@ -23451,7 +23451,7 @@ }, { "Name": "ONS Open Data Portal", - "Description": "Daily stored energy per subsystem (PT-BR Energia Armazenada (EAR) di\u00e1rio por subsistema)", + "Description": "Daily stored energy per reservoir (PT-BR Energia Armazenada (EAR) di\u00e1rio por reservat\u00f3rio)", "ARN": "arn:aws:s3:::ons-aws-prod-opendata", "Region": "sa-east-1", "Type": "S3 Bucket", @@ -23467,7 +23467,7 @@ "energy" ], "Explore": [ - "[Browse Dataset](https://dados.ons.org.br/dataset/ear-diario-por-subsistema)" + "[Browse Dataset](https://dados.ons.org.br/dataset/ear-diario-por-reservatorio)" ], "RequesterPays": null, "ControlledAccess": null, @@ -24176,7 +24176,7 @@ }, { "Name": "ONS Open Data Portal", - "Description": "Daily stored energy per reservoir (PT-BR Energia Armazenada (EAR) di\u00e1rio por reservat\u00f3rio)", + "Description": "Daily stored energy per subsystem (PT-BR Energia Armazenada (EAR) di\u00e1rio por subsistema)", "ARN": "arn:aws:s3:::ons-aws-prod-opendata", "Region": "sa-east-1", "Type": "S3 Bucket", @@ -24192,7 +24192,7 @@ "energy" ], "Explore": [ - "[Browse Dataset](https://dados.ons.org.br/dataset/ear-diario-por-reservatorio)" + "[Browse Dataset](https://dados.ons.org.br/dataset/ear-diario-por-subsistema)" ], "RequesterPays": null, "ControlledAccess": null, @@ -24619,9 +24619,9 @@ }, { "Name": "Open Observatory of Network Interference (OONI)", - "Description": "Old S3 bucket with cans for older measurements", - "ARN": "arn:aws:s3:::ooni-data", - "Region": "us-east-1", + "Description": "New S3 bucket with JSONL files", + "ARN": "arn:aws:s3:::ooni-data-eu-fra", + "Region": "eu-central-1", "Type": "S3 Bucket", "Documentation": "https://ooni.org/data/", "Contact": "https://ooni.org/get-involved/", @@ -24640,9 +24640,9 @@ }, { "Name": "Open Observatory of Network Interference (OONI)", - "Description": "New S3 bucket with JSONL files", - "ARN": "arn:aws:s3:::ooni-data-eu-fra", - "Region": "eu-central-1", + "Description": "Old S3 bucket with cans for older measurements", + "ARN": "arn:aws:s3:::ooni-data", + "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "https://ooni.org/data/", "Contact": "https://ooni.org/get-involved/", @@ -24714,10 +24714,10 @@ }, { "Name": "OpenAQ", - "Description": "OpenAQ API", - "ARN": null, + "Description": "Daily gzipped CSVs of global air quality measurements fetched from sources all over the world", + "ARN": "arn:aws:s3:::openaq-data-archive", "Region": "us-east-1", - "Type": "CloudFront Distribution", + "Type": "S3 Bucket", "Documentation": "https://openaq.org", "Contact": "info@openaq.org", "ManagedBy": "[OpenAQ](https://openaq.org)", @@ -24734,14 +24734,14 @@ "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, - "Host": "api.openaq.org" + "Host": null }, { "Name": "OpenAQ", - "Description": "Daily gzipped CSVs of global air quality measurements fetched from sources all over the world", - "ARN": "arn:aws:s3:::openaq-data-archive", + "Description": "OpenAQ API", + "ARN": null, "Region": "us-east-1", - "Type": "S3 Bucket", + "Type": "CloudFront Distribution", "Documentation": "https://openaq.org", "Contact": "info@openaq.org", "ManagedBy": "[OpenAQ](https://openaq.org)", @@ -24758,7 +24758,7 @@ "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, - "Host": null + "Host": "api.openaq.org" }, { "Name": "OpenAQ", @@ -24812,8 +24812,8 @@ }, { "Name": "OpenAlex dataset", - "Description": "Openalex Entities decomposed to tab-separated columnar files for backward compatibility with Microsoft Academic Graph", - "ARN": "arn:aws:s3:::openalex-mag-format", + "Description": "OpenAlex Entities in JSON Lines format", + "ARN": "arn:aws:s3:::openalex", "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "https://docs.openalex.org", @@ -24829,7 +24829,7 @@ "aws-pds" ], "Explore": [ - "[Browse Bucket](https://openalex-mag-format.s3.amazonaws.com/browse.html)" + "[Browse Bucket](https://openalex.s3.amazonaws.com/browse.html)" ], "RequesterPays": null, "ControlledAccess": null, @@ -24838,8 +24838,8 @@ }, { "Name": "OpenAlex dataset", - "Description": "OpenAlex Entities in JSON Lines format", - "ARN": "arn:aws:s3:::openalex", + "Description": "Openalex Entities decomposed to tab-separated columnar files for backward compatibility with Microsoft Academic Graph", + "ARN": "arn:aws:s3:::openalex-mag-format", "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "https://docs.openalex.org", @@ -24855,7 +24855,7 @@ "aws-pds" ], "Explore": [ - "[Browse Bucket](https://openalex.s3.amazonaws.com/browse.html)" + "[Browse Bucket](https://openalex-mag-format.s3.amazonaws.com/browse.html)" ], "RequesterPays": null, "ControlledAccess": null, @@ -25023,10 +25023,10 @@ }, { "Name": "OpenStreetMap on AWS", - "Description": "Imagery and metadata", - "ARN": "arn:aws:s3:::osm-pds", + "Description": "New data notifications", + "ARN": "arn:aws:sns:us-east-1:800218804198:New_File", "Region": "us-east-1", - "Type": "S3 Bucket", + "Type": "SNS Topic", "Documentation": "https://github.com/awslabs/open-data-docs/tree/main/docs/osm-pds", "Contact": "https://github.com/mojodna/osm-pds-pipelines/issues", "ManagedBy": "Pacific Atlas", @@ -25047,10 +25047,10 @@ }, { "Name": "OpenStreetMap on AWS", - "Description": "New data notifications", - "ARN": "arn:aws:sns:us-east-1:800218804198:New_File", + "Description": "Imagery and metadata", + "ARN": "arn:aws:s3:::osm-pds", "Region": "us-east-1", - "Type": "SNS Topic", + "Type": "S3 Bucket", "Documentation": "https://github.com/awslabs/open-data-docs/tree/main/docs/osm-pds", "Contact": "https://github.com/mojodna/osm-pds-pipelines/issues", "ManagedBy": "Pacific Atlas", @@ -25172,8 +25172,8 @@ }, { "Name": "Orcasound - bioacoustic data for marine conservation", - "Description": "Live-streamed orca audio data (HLS)", - "ARN": "arn:aws:s3:::streaming-orcasound-net", + "Description": "Labeled audio data for ML model development", + "ARN": "arn:aws:s3:::acoustic-sandbox", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/orcasound/orcadata/wiki", @@ -25206,8 +25206,8 @@ }, { "Name": "Orcasound - bioacoustic data for marine conservation", - "Description": "Archived lossless orca audio data (FLAC)", - "ARN": "arn:aws:s3:::archive-orcasound-net", + "Description": "Live-streamed orca audio data (HLS)", + "ARN": "arn:aws:s3:::streaming-orcasound-net", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/orcasound/orcadata/wiki", @@ -25240,8 +25240,8 @@ }, { "Name": "Orcasound - bioacoustic data for marine conservation", - "Description": "Labeled audio data for ML model development", - "ARN": "arn:aws:s3:::acoustic-sandbox", + "Description": "Archived lossless orca audio data (FLAC)", + "ARN": "arn:aws:s3:::archive-orcasound-net", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/orcasound/orcadata/wiki", @@ -25297,10 +25297,10 @@ }, { "Name": "Overture Maps Foundation Open Map Data", - "Description": "Overture Maps Foundation Data (GeoParquet)", - "ARN": "arn:aws:s3:::overturemaps-us-west-2/release/", + "Description": "New File Notification", + "ARN": "arn:aws:sns:us-west-2:913550007193:overturemaps-us-west-2", "Region": "us-west-2", - "Type": "S3 Bucket", + "Type": "SNS Topic", "Documentation": "Documentation is available at [docs.overturemaps.org](https://docs.overturemaps.org/)", "Contact": "info@overturemaps.org", "ManagedBy": "[Overture Maps Foundation](https://overturemaps.org)", @@ -25323,10 +25323,10 @@ }, { "Name": "Overture Maps Foundation Open Map Data", - "Description": "New File Notification", - "ARN": "arn:aws:sns:us-west-2:913550007193:overturemaps-us-west-2", + "Description": "Overture Maps Foundation Data (GeoParquet)", + "ARN": "arn:aws:s3:::overturemaps-us-west-2/release/", "Region": "us-west-2", - "Type": "SNS Topic", + "Type": "S3 Bucket", "Documentation": "Documentation is available at [docs.overturemaps.org](https://docs.overturemaps.org/)", "Contact": "info@overturemaps.org", "ManagedBy": "[Overture Maps Foundation](https://overturemaps.org)", @@ -25349,8 +25349,8 @@ }, { "Name": "Oxford Nanopore Technologies Benchmark Datasets", - "Description": "Nanopore sequencing data of the Genome in a Bottle samples NA24385, NA24149, and NA24143 (HG002-HG004) using the LSK114 sequencing chemistry The direct sequencer output is included, raw signal data stored in fast5 files and basecalled data in fastq file Additional secondary analyses are included, notably alignments of sequence data to the reference genome and variant calls are provided along with statistics derived from theseThe following cell lines/DNA samples were obtained from the NIGMS Human Genetic Cell Repository at the Coriell Institute for Medical Research: NA24385, NA24149, and NA24143", - "ARN": "arn:aws:s3:::ont-open-data/giab_lsk114_2022.12", + "Description": "Oxford Nanopore Open Datasets", + "ARN": "arn:aws:s3:::ont-open-data", "Region": "eu-west-1", "Type": "S3 Bucket", "Documentation": "https://labs.epi2me.io/dataindex/", @@ -25377,8 +25377,8 @@ }, { "Name": "Oxford Nanopore Technologies Benchmark Datasets", - "Description": "Oxford Nanopore Open Datasets", - "ARN": "arn:aws:s3:::ont-open-data", + "Description": "Nanopore sequencing data of the Genome in a Bottle samples NA24385, NA24149, and NA24143 (HG002-HG004) using the LSK114 sequencing chemistry The direct sequencer output is included, raw signal data stored in fast5 files and basecalled data in fastq file Additional secondary analyses are included, notably alignments of sequence data to the reference genome and variant calls are provided along with statistics derived from theseThe following cell lines/DNA samples were obtained from the NIGMS Human Genetic Cell Repository at the Coriell Institute for Medical Research: NA24385, NA24149, and NA24143", + "ARN": "arn:aws:s3:::ont-open-data/giab_lsk114_2022.12", "Region": "eu-west-1", "Type": "S3 Bucket", "Documentation": "https://labs.epi2me.io/dataindex/", @@ -25681,8 +25681,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "original 256 kHz audio recordings year 2021", - "ARN": "arn:aws:s3:::pacific-sound-256khz-2021", + "Description": "original 256 kHz audio recordings year 2023", + "ARN": "arn:aws:s3:::pacific-sound-256khz-2023", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -25713,8 +25713,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "original 256 kHz audio recordings year 2020", - "ARN": "arn:aws:s3:::pacific-sound-256khz-2020", + "Description": "original 256 kHz audio recordings year 2015", + "ARN": "arn:aws:s3:::pacific-sound-256khz-2015", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -25745,8 +25745,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "original 256 kHz audio recordings year 2019", - "ARN": "arn:aws:s3:::pacific-sound-256khz-2019", + "Description": "original 256 kHz audio recordings year 2016", + "ARN": "arn:aws:s3:::pacific-sound-256khz-2016", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -25777,8 +25777,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "original 256 kHz audio recordings year 2018", - "ARN": "arn:aws:s3:::pacific-sound-256khz-2018", + "Description": "original 256 kHz audio recordings year 2017", + "ARN": "arn:aws:s3:::pacific-sound-256khz-2017", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -25809,8 +25809,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "original 256 kHz audio recordings year 2017", - "ARN": "arn:aws:s3:::pacific-sound-256khz-2017", + "Description": "original 256 kHz audio recordings year 2018", + "ARN": "arn:aws:s3:::pacific-sound-256khz-2018", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -25841,8 +25841,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "original 256 kHz audio recordings year 2016", - "ARN": "arn:aws:s3:::pacific-sound-256khz-2016", + "Description": "original 256 kHz audio recordings year 2019", + "ARN": "arn:aws:s3:::pacific-sound-256khz-2019", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -25873,8 +25873,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "original 256 kHz audio recordings year 2015", - "ARN": "arn:aws:s3:::pacific-sound-256khz-2015", + "Description": "original 256 kHz audio recordings year 2020", + "ARN": "arn:aws:s3:::pacific-sound-256khz-2020", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -25905,8 +25905,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "original 256 kHz audio recordings year 2024", - "ARN": "arn:aws:s3:::pacific-sound-256khz-2024", + "Description": "original 256 kHz audio recordings year 2021", + "ARN": "arn:aws:s3:::pacific-sound-256khz-2021", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -25937,8 +25937,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "original 256 kHz audio recordings year 2025", - "ARN": "arn:aws:s3:::pacific-sound-256khz-2025", + "Description": "original 256 kHz audio recordings year 2022", + "ARN": "arn:aws:s3:::pacific-sound-256khz-2022", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -25969,8 +25969,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "decimated 2 kHz audio recordings", - "ARN": "arn:aws:s3:::pacific-sound-2khz", + "Description": "decimated 16 kHz audio recordings", + "ARN": "arn:aws:s3:::pacific-sound-16khz", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -26001,8 +26001,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "decimated 16 kHz audio recordings", - "ARN": "arn:aws:s3:::pacific-sound-16khz", + "Description": "original 256 kHz audio recordings year 2024", + "ARN": "arn:aws:s3:::pacific-sound-256khz-2024", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -26033,8 +26033,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "original 256 kHz audio recordings year 2022", - "ARN": "arn:aws:s3:::pacific-sound-256khz-2022", + "Description": "original 256 kHz audio recordings year 2025", + "ARN": "arn:aws:s3:::pacific-sound-256khz-2025", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -26065,8 +26065,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "machine learning models", - "ARN": "arn:aws:s3:::pacific-sound-models", + "Description": "decimated 2 kHz audio recordings", + "ARN": "arn:aws:s3:::pacific-sound-2khz", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -26097,8 +26097,8 @@ }, { "Name": "Pacific Ocean Sound Recordings", - "Description": "original 256 kHz audio recordings year 2023", - "ARN": "arn:aws:s3:::pacific-sound-256khz-2023", + "Description": "machine learning models", + "ARN": "arn:aws:s3:::pacific-sound-models", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://docs.mbari.org/pacific-sound/", @@ -26150,8 +26150,8 @@ }, { "Name": "Pancreatic Cancer Organoid Profiling", - "Description": "WGS/WXS/RNA-Seq Aligned Reads, WXS Annotated Somatic Mutation, WXS Raw Somatic Mutation,RNA-Seq Splice Junction Quantification", - "ARN": "arn:aws:s3:::gdc-organoid-pancreatic-phs001611-2-controlled", + "Description": "RNA-Seq Gene Expression Quantification", + "ARN": "arn:aws:s3:::gdc-organoid-pancreatic-phs001611-2-open", "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001611.v1.p1", @@ -26170,14 +26170,14 @@ ], "Explore": null, "RequesterPays": null, - "ControlledAccess": "https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001611.v1.p1", + "ControlledAccess": null, "AccountRequired": null, "Host": null }, { "Name": "Pancreatic Cancer Organoid Profiling", - "Description": "RNA-Seq Gene Expression Quantification", - "ARN": "arn:aws:s3:::gdc-organoid-pancreatic-phs001611-2-open", + "Description": "WGS/WXS/RNA-Seq Aligned Reads, WXS Annotated Somatic Mutation, WXS Raw Somatic Mutation,RNA-Seq Splice Junction Quantification", + "ARN": "arn:aws:s3:::gdc-organoid-pancreatic-phs001611-2-controlled", "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001611.v1.p1", @@ -26196,7 +26196,7 @@ ], "Explore": null, "RequesterPays": null, - "ControlledAccess": null, + "ControlledAccess": "https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001611.v1.p1", "AccountRequired": null, "Host": null }, @@ -26320,8 +26320,8 @@ }, { "Name": "PoroTomo", - "Description": "PoroTomo Nodal Seismometer Field Notes and Metadata", - "ARN": "arn:aws:s3:::nrel-pds-porotomo/Nodal/nodal_metadata/", + "Description": "PoroTomo Horizontal Distributed Acoustic Sensing (DASH) Data Resampled in Time MATLAB Files", + "ARN": "arn:aws:s3:::nrel-pds-porotomo/DAS/SEG-Y/DASH/Resampled/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md", @@ -26337,7 +26337,7 @@ "geospatial" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=Nodal%2Fnodal_metadata%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FSEG-Y%2FDASH%2FResampled%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26346,8 +26346,8 @@ }, { "Name": "PoroTomo", - "Description": "PoroTomo Nodal Seismometer Continuous Data", - "ARN": "arn:aws:s3:::nrel-pds-porotomo/Nodal/nodal_sac/", + "Description": "PoroTomo Horizontal Distributed Acoustic Sensing (DASH) Data in SEG-Y format", + "ARN": "arn:aws:s3:::nrel-pds-porotomo/DAS/SEG-Y/DASH/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md", @@ -26363,7 +26363,7 @@ "geospatial" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=Nodal%2Fnodal_sac%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FSEG-Y%2FDASH%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26372,8 +26372,8 @@ }, { "Name": "PoroTomo", - "Description": "PoroTomo Vertical Distributed Acoustic Sensing (DASV) Data in HDF5 format", - "ARN": "arn:aws:s3:::nrel-pds-porotomo/DAS/H5/DASV/", + "Description": "PoroTomo Vertical Distributed Acoustic Sensing (DASV) Data in SEG-Y format", + "ARN": "arn:aws:s3:::nrel-pds-porotomo/DAS/SEG-Y/DASV/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md", @@ -26389,7 +26389,7 @@ "geospatial" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FH5%2FDASV%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FSEG-Y%2FDASV%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26424,8 +26424,8 @@ }, { "Name": "PoroTomo", - "Description": "PoroTomo Vertical Distributed Acoustic Sensing (DASV) Data in SEG-Y format", - "ARN": "arn:aws:s3:::nrel-pds-porotomo/DAS/SEG-Y/DASV/", + "Description": "PoroTomo Vertical Distributed Acoustic Sensing (DASV) Data in HDF5 format", + "ARN": "arn:aws:s3:::nrel-pds-porotomo/DAS/H5/DASV/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md", @@ -26441,7 +26441,7 @@ "geospatial" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FSEG-Y%2FDASV%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FH5%2FDASV%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26450,8 +26450,8 @@ }, { "Name": "PoroTomo", - "Description": "PoroTomo Horizontal Distributed Acoustic Sensing (DASH) Data Resampled in Time MATLAB Files", - "ARN": "arn:aws:s3:::nrel-pds-porotomo/DAS/SEG-Y/DASH/Resampled/", + "Description": "HSDS PoroTomo domains", + "ARN": "arn:aws:s3:::nrel-pds-hsds/nrel/porotomo/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md", @@ -26467,7 +26467,7 @@ "geospatial" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FSEG-Y%2FDASH%2FResampled%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-hsds&prefix=nrel%2Fporotomo%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26476,8 +26476,8 @@ }, { "Name": "PoroTomo", - "Description": "PoroTomo Horizontal Distributed Acoustic Sensing (DASH) Data in SEG-Y format", - "ARN": "arn:aws:s3:::nrel-pds-porotomo/DAS/SEG-Y/DASH/", + "Description": "PoroTomo Nodal Seismometer Continuous Data", + "ARN": "arn:aws:s3:::nrel-pds-porotomo/Nodal/nodal_sac/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md", @@ -26493,7 +26493,7 @@ "geospatial" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FSEG-Y%2FDASH%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=Nodal%2Fnodal_sac%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26502,8 +26502,8 @@ }, { "Name": "PoroTomo", - "Description": "PoroTomo Datasets", - "ARN": "arn:aws:s3:::nrel-pds-porotomo/", + "Description": "PoroTomo Nodal Seismometer Field Notes and Metadata", + "ARN": "arn:aws:s3:::nrel-pds-porotomo/Nodal/nodal_metadata/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md", @@ -26519,7 +26519,7 @@ "geospatial" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=Nodal%2Fnodal_metadata%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26554,8 +26554,8 @@ }, { "Name": "PoroTomo", - "Description": "HSDS PoroTomo domains", - "ARN": "arn:aws:s3:::nrel-pds-hsds/nrel/porotomo/", + "Description": "PoroTomo Datasets", + "ARN": "arn:aws:s3:::nrel-pds-porotomo/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md", @@ -26571,7 +26571,7 @@ "geospatial" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-hsds&prefix=nrel%2Fporotomo%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26708,10 +26708,10 @@ }, { "Name": "Protein Data Bank 3D Structural Biology Data", - "Description": "Globally cached distribution of the dataset Web frontend also available to browse the dataset and file directory", - "ARN": null, + "Description": "Historical snapshots of archival datasets from 2005 onwards Snapshots are generated annually and at major milestone", + "ARN": "arn:aws:s3:::pdbsnapshots", "Region": "us-west-2", - "Type": "CloudFront Distribution", + "Type": "S3 Bucket", "Documentation": "https://www.wwpdb.org/documentation/file-format", "Contact": "https://www.wwpdb.org/about/contact", "ManagedBy": "[Worldwide Protein Data Bank Partnership](wwpdb.org)", @@ -26740,7 +26740,7 @@ "x-ray crystallography" ], "Explore": [ - "[Browse Dataset](https://s3.rcsb.org)" + "[Browse Bucket](https://pdbsnapshots.s3.us-west-2.amazonaws.com/index.html)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26749,10 +26749,10 @@ }, { "Name": "Protein Data Bank 3D Structural Biology Data", - "Description": "Historical snapshots of archival datasets from 2005 onwards Snapshots are generated annually and at major milestone", - "ARN": "arn:aws:s3:::pdbsnapshots", + "Description": "Globally cached distribution of the dataset Web frontend also available to browse the dataset and file directory", + "ARN": null, "Region": "us-west-2", - "Type": "S3 Bucket", + "Type": "CloudFront Distribution", "Documentation": "https://www.wwpdb.org/documentation/file-format", "Contact": "https://www.wwpdb.org/about/contact", "ManagedBy": "[Worldwide Protein Data Bank Partnership](wwpdb.org)", @@ -26781,7 +26781,7 @@ "x-ray crystallography" ], "Explore": [ - "[Browse Bucket](https://pdbsnapshots.s3.us-west-2.amazonaws.com/index.html)" + "[Browse Dataset](https://s3.rcsb.org)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26812,8 +26812,8 @@ }, { "Name": "PubSeq - Public Sequence Resource", - "Description": "Pubseq output data (Arvados Keep)", - "ARN": "arn:aws:s3:::pubseq-output-data", + "Description": "PubSeq submitted datasets (FASTA and JSON metadata)", + "ARN": "arn:aws:s3:::pubseq-datasets", "Region": "us-east-2", "Type": "S3 Bucket", "Documentation": "https://covid19.genenetwork.org/about", @@ -26847,7 +26847,7 @@ "SPARQL" ], "Explore": [ - "[Arvados download](https://covid19.genenetwork.org/download)" + "[Browse Bucket](https://pubseq-datasets.s3.amazonaws.com/)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26856,8 +26856,8 @@ }, { "Name": "PubSeq - Public Sequence Resource", - "Description": "PubSeq submitted datasets (FASTA and JSON metadata)", - "ARN": "arn:aws:s3:::pubseq-datasets", + "Description": "Pubseq output data (Arvados Keep)", + "ARN": "arn:aws:s3:::pubseq-output-data", "Region": "us-east-2", "Type": "S3 Bucket", "Documentation": "https://covid19.genenetwork.org/about", @@ -26891,7 +26891,7 @@ "SPARQL" ], "Explore": [ - "[Browse Bucket](https://pubseq-datasets.s3.amazonaws.com/)" + "[Arvados download](https://covid19.genenetwork.org/download)" ], "RequesterPays": null, "ControlledAccess": null, @@ -26930,8 +26930,8 @@ }, { "Name": "PyEnvs and CallArgs", - "Description": "PyEnvs", - "ARN": "arn:aws:s3:::pyenvs-and-callargs/pyenvs/", + "Description": "CallArgs", + "ARN": "arn:aws:s3:::pyenvs-and-callargs/callargs/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/amazon-research/function-call-argument-completion", @@ -26951,8 +26951,8 @@ }, { "Name": "PyEnvs and CallArgs", - "Description": "CallArgs", - "ARN": "arn:aws:s3:::pyenvs-and-callargs/callargs/", + "Description": "PyEnvs", + "ARN": "arn:aws:s3:::pyenvs-and-callargs/pyenvs/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/amazon-research/function-call-argument-completion", @@ -27142,8 +27142,8 @@ }, { "Name": "REDASA COVID-19 Open Data", - "Description": "This is the raw data repository containing a common crawl of CORD-19 papers and other sources identified by the REDASA Project", - "ARN": "arn:aws:s3:::pansurg-curation-raw-open-data", + "Description": "An S3 bucket that contains the final curation data in GroundTruth format", + "ARN": "arn:aws:s3:::pansurg-curation-final-curations-open-data", "Region": "eu-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/PanSurg/redasa-sample-data/blob/master/open-data.md", @@ -27168,8 +27168,8 @@ }, { "Name": "REDASA COVID-19 Open Data", - "Description": "An S3 bucket that contains the final curation data in GroundTruth format", - "ARN": "arn:aws:s3:::pansurg-curation-final-curations-open-data", + "Description": "For all the questions curated during the REDASA project, we created a Kendra index The documents available in this S3 bucket were surfaced by the Kendra index as being relevant to the research medical question", + "ARN": "arn:aws:s3:::pansurg-curation-workflo-kendraqueryresults50d0eb-open-data", "Region": "eu-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/PanSurg/redasa-sample-data/blob/master/open-data.md", @@ -27194,8 +27194,8 @@ }, { "Name": "REDASA COVID-19 Open Data", - "Description": "For all the questions curated during the REDASA project, we created a Kendra index The documents available in this S3 bucket were surfaced by the Kendra index as being relevant to the research medical question", - "ARN": "arn:aws:s3:::pansurg-curation-workflo-kendraqueryresults50d0eb-open-data", + "Description": "This is the raw data repository containing a common crawl of CORD-19 papers and other sources identified by the REDASA Project", + "ARN": "arn:aws:s3:::pansurg-curation-raw-open-data", "Region": "eu-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/PanSurg/redasa-sample-data/blob/master/open-data.md", @@ -27444,8 +27444,8 @@ }, { "Name": "Reference Elevation Model of Antarctica (REMA)", - "Description": "REMA DEM Mosaics", - "ARN": "arn:aws:s3:::pgc-opendata-dems/rema/mosaics/", + "Description": "REMA DEM Strips", + "ARN": "arn:aws:s3:::pgc-opendata-dems/rema/strips/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://www.pgc.umn.edu/data/rema/", @@ -27465,7 +27465,7 @@ "stac" ], "Explore": [ - "[Browse STAC Catalog](https://polargeospatialcenter.github.io/stac-browser/#/external/pgc-opendata-dems.s3.us-west-2.amazonaws.com/rema/mosaics.json)" + "[Browse STAC Catalog](https://polargeospatialcenter.github.io/stac-browser/#/external/pgc-opendata-dems.s3.us-west-2.amazonaws.com/rema/strips.json)" ], "RequesterPays": null, "ControlledAccess": null, @@ -27474,8 +27474,8 @@ }, { "Name": "Reference Elevation Model of Antarctica (REMA)", - "Description": "REMA DEM Strips", - "ARN": "arn:aws:s3:::pgc-opendata-dems/rema/strips/", + "Description": "REMA DEM Mosaics", + "ARN": "arn:aws:s3:::pgc-opendata-dems/rema/mosaics/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://www.pgc.umn.edu/data/rema/", @@ -27495,7 +27495,7 @@ "stac" ], "Explore": [ - "[Browse STAC Catalog](https://polargeospatialcenter.github.io/stac-browser/#/external/pgc-opendata-dems.s3.us-west-2.amazonaws.com/rema/strips.json)" + "[Browse STAC Catalog](https://polargeospatialcenter.github.io/stac-browser/#/external/pgc-opendata-dems.s3.us-west-2.amazonaws.com/rema/mosaics.json)" ], "RequesterPays": null, "ControlledAccess": null, @@ -27633,8 +27633,8 @@ }, { "Name": "SILAM Air Quality", - "Description": "Notifications for new netcdf surface data", - "ARN": "arn:aws:sns:eu-west-1:916174725480:new-fmi-opendata-silam-surface-netcdf", + "Description": "Notifications for new zarr surface data", + "ARN": "arn:aws:sns:eu-west-1:916174725480:new-fmi-opendata-silam-surface-zarr", "Region": "eu-west-1", "Type": "SNS Topic", "Documentation": "http://en.ilmatieteenlaitos.fi/open-data-on-aws-s3", @@ -27658,8 +27658,8 @@ }, { "Name": "SILAM Air Quality", - "Description": "Notifications for new zarr surface data", - "ARN": "arn:aws:sns:eu-west-1:916174725480:new-fmi-opendata-silam-surface-zarr", + "Description": "Notifications for new netcdf surface data", + "ARN": "arn:aws:sns:eu-west-1:916174725480:new-fmi-opendata-silam-surface-netcdf", "Region": "eu-west-1", "Type": "SNS Topic", "Documentation": "http://en.ilmatieteenlaitos.fi/open-data-on-aws-s3", @@ -28061,8 +28061,8 @@ }, { "Name": "Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD)", - "Description": "Spatial transcriptomics data files in a public bucket", - "ARN": "arn:aws:s3:::sea-ad-spatial-transcriptomics", + "Description": "Single cell profiling (transcriptomics and epigenomics) data files in a public bucket", + "ARN": "arn:aws:s3:::sea-ad-single-cell-profiling", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://portal.brain-map.org/explore/seattle-alzheimers-disease/seattle-alzheimers-disease-brain-cell-atlas-download?edit&language=en", @@ -28088,7 +28088,7 @@ "transcriptomics" ], "Explore": [ - "[Browse Bucket](https://sea-ad-spatial-transcriptomics.s3.amazonaws.com/index.html)" + "[Browse Bucket](https://sea-ad-single-cell-profiling.s3.amazonaws.com/index.html)" ], "RequesterPays": null, "ControlledAccess": null, @@ -28097,8 +28097,8 @@ }, { "Name": "Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD)", - "Description": "Quantitative neuropathology (full resolution images, processed images, and quantifications) in a public bucket", - "ARN": "arn:aws:s3:::sea-ad-quantitative-neuropathology", + "Description": "Spatial transcriptomics data files in a public bucket", + "ARN": "arn:aws:s3:::sea-ad-spatial-transcriptomics", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://portal.brain-map.org/explore/seattle-alzheimers-disease/seattle-alzheimers-disease-brain-cell-atlas-download?edit&language=en", @@ -28124,7 +28124,7 @@ "transcriptomics" ], "Explore": [ - "[Browse Bucket](https://sea-ad-quantitative-neuropathology.s3.amazonaws.com/index.html)" + "[Browse Bucket](https://sea-ad-spatial-transcriptomics.s3.amazonaws.com/index.html)" ], "RequesterPays": null, "ControlledAccess": null, @@ -28133,8 +28133,8 @@ }, { "Name": "Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD)", - "Description": "Single cell profiling (transcriptomics and epigenomics) data files in a public bucket", - "ARN": "arn:aws:s3:::sea-ad-single-cell-profiling", + "Description": "Quantitative neuropathology (full resolution images, processed images, and quantifications) in a public bucket", + "ARN": "arn:aws:s3:::sea-ad-quantitative-neuropathology", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://portal.brain-map.org/explore/seattle-alzheimers-disease/seattle-alzheimers-disease-brain-cell-atlas-download?edit&language=en", @@ -28160,13 +28160,45 @@ "transcriptomics" ], "Explore": [ - "[Browse Bucket](https://sea-ad-single-cell-profiling.s3.amazonaws.com/index.html)" + "[Browse Bucket](https://sea-ad-quantitative-neuropathology.s3.amazonaws.com/index.html)" ], "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, "Host": null }, + { + "Name": "SeeFar V0", + "Description": "Primary SeeFar dataset containing multi-resolution satellite imagery in cloud-optimized GeoTIFF format across four spectral bands", + "ARN": "arn:aws:s3:::seefar-dataset", + "Region": "us-east-1", + "Type": "S3 Bucket", + "Documentation": "https://coastalcarbon.ai/seefar", + "Contact": "James Lowman", + "ManagedBy": "Coastal Carbon", + "UpdateFrequency": "Yearly", + "License": "The SeeFar dataset includes multiple licensing terms, specific to each satellite data source: - **Satellogic (Earthview)**: \"Creative Commons Attribution 4.0 International (CC BY 4.0) \u2014 allows for free use, sharing, and adaptation with attribution and indication of changes.\" - **WorldStrat (Airbus)**: \"Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0) \u2014 permits non-commercial use with attribution and indication of changes.\" - **Sentinel**: \"Creative Commons Attribution-Share Alike 3.0 IGO (CC BY-SA 3.0 IGO) \u2014 requires attribution, share-alike terms, and indication of any changes.\" - **USGS Landsat**: \"USGS Landsat License \u2014 unrestricted use with requested data source acknowledgment.\"", + "Tags": [ + "geospatial", + "earth observation", + "satellite imagery", + "climate", + "biodiversity", + "coastal", + "machine learning", + "environmental", + "sustainability", + "natural resource", + "global", + "mapping", + "aws-pds" + ], + "Explore": null, + "RequesterPays": null, + "ControlledAccess": null, + "AccountRequired": null, + "Host": null + }, { "Name": "Sentinel Near Real-time Canada Mirror | Miroir Sentinel temps quasi r\u00e9el du Canada", "Description": "Sentinel data over Canada | Donn\u00e9es sentinelles au Canada", @@ -28199,10 +28231,10 @@ }, { "Name": "Sentinel-1", - "Description": "SNS topic for notification of new scenes, can subscribe with Lambda", - "ARN": "arn:aws:sns:eu-central-1:214830741341:SentinelS1L1C", + "Description": "GRD in a Requester Pays S3 bucket", + "ARN": "arn:aws:s3:::sentinel-s1-l1c", "Region": "eu-central-1", - "Type": "SNS Topic", + "Type": "S3 Bucket", "Documentation": "https://roda.sentinel-hub.com/sentinel-s1-l1c/GRD/readme.html", "Contact": "https://forum.sentinel-hub.com/c/aws-sentinel", "ManagedBy": "[Sinergise](https://www.sinergise.com/)", @@ -28218,8 +28250,10 @@ "cog", "synthetic aperture radar" ], - "Explore": null, - "RequesterPays": null, + "Explore": [ + "[STAC V1.0.0 endpoint](https://sentinel-s1-l1c-stac.s3.amazonaws.com/)" + ], + "RequesterPays": true, "ControlledAccess": null, "AccountRequired": null, "Host": null @@ -28253,10 +28287,10 @@ }, { "Name": "Sentinel-1", - "Description": "GRD in a Requester Pays S3 bucket", - "ARN": "arn:aws:s3:::sentinel-s1-l1c", + "Description": "SNS topic for notification of new scenes, can subscribe with Lambda", + "ARN": "arn:aws:sns:eu-central-1:214830741341:SentinelS1L1C", "Region": "eu-central-1", - "Type": "S3 Bucket", + "Type": "SNS Topic", "Documentation": "https://roda.sentinel-hub.com/sentinel-s1-l1c/GRD/readme.html", "Contact": "https://forum.sentinel-hub.com/c/aws-sentinel", "ManagedBy": "[Sinergise](https://www.sinergise.com/)", @@ -28272,20 +28306,18 @@ "cog", "synthetic aperture radar" ], - "Explore": [ - "[STAC V1.0.0 endpoint](https://sentinel-s1-l1c-stac.s3.amazonaws.com/)" - ], - "RequesterPays": true, + "Explore": null, + "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, "Host": null }, { "Name": "Sentinel-1 Precise Orbit Determination (POD) Products", - "Description": "Sentinel-1 Orbits bucket", - "ARN": "arn:aws:s3:::s1-orbits", + "Description": "Notifications for new data", + "ARN": "arn:aws:sns:us-west-2:211125554030:s1-orbits-object_created", "Region": "us-west-2", - "Type": "S3 Bucket", + "Type": "SNS Topic", "Documentation": "https://s1-orbits.s3.us-west-2.amazonaws.com/README.html", "Contact": "https://asf.alaska.edu/asf/contact-us/", "ManagedBy": "[The Alaska Satellite Facility (ASF)](https://asf.alaska.edu/)", @@ -28301,9 +28333,7 @@ "sentinel-1", "synthetic aperture radar" ], - "Explore": [ - "[AWS S3 Explorer](https://s1-orbits.s3.amazonaws.com/index.html)" - ], + "Explore": null, "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, @@ -28311,10 +28341,10 @@ }, { "Name": "Sentinel-1 Precise Orbit Determination (POD) Products", - "Description": "Notifications for new data", - "ARN": "arn:aws:sns:us-west-2:211125554030:s1-orbits-object_created", + "Description": "Sentinel-1 Orbits bucket", + "ARN": "arn:aws:s3:::s1-orbits", "Region": "us-west-2", - "Type": "SNS Topic", + "Type": "S3 Bucket", "Documentation": "https://s1-orbits.s3.us-west-2.amazonaws.com/README.html", "Contact": "https://asf.alaska.edu/asf/contact-us/", "ManagedBy": "[The Alaska Satellite Facility (ASF)](https://asf.alaska.edu/)", @@ -28330,7 +28360,9 @@ "sentinel-1", "synthetic aperture radar" ], - "Explore": null, + "Explore": [ + "[AWS S3 Explorer](https://s1-orbits.s3.amazonaws.com/index.html)" + ], "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, @@ -28391,10 +28423,10 @@ }, { "Name": "Sentinel-2", - "Description": "S3 Inventory files for L2A and CSV", - "ARN": "arn:aws:s3:::sentinel-inventory/sentinel-s2-l2a", - "Region": "eu-central-1", - "Type": "S3 Bucket", + "Description": "New scene notifications for L1C, can subscribe with Lambda", + "ARN": "arn:aws:sns:eu-west-1:214830741341:NewSentinel2Product", + "Region": "eu-west-1", + "Type": "SNS Topic", "Documentation": "Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/sentinel-s2-l1c/readme.html) and [Sentinel-2 L2A](https://roda.sentinel-hub.com/sentinel-s2-l2a/readme.html).", "Contact": "https://forum.sentinel-hub.com/c/aws-sentinel", "ManagedBy": "[Sinergise](https://www.sinergise.com/)", @@ -28418,10 +28450,10 @@ }, { "Name": "Sentinel-2", - "Description": "New scene notifications for L2A, can subscribe with Lambda", - "ARN": "arn:aws:sns:eu-central-1:214830741341:SentinelS2L2A", + "Description": "Zipped archives for each L2A product with 3 day retention period, in Requester Pays bucket", + "ARN": "arn:aws:s3:::sentinel-s2-l2a-zips", "Region": "eu-central-1", - "Type": "SNS Topic", + "Type": "S3 Bucket", "Documentation": "Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/sentinel-s2-l1c/readme.html) and [Sentinel-2 L2A](https://roda.sentinel-hub.com/sentinel-s2-l2a/readme.html).", "Contact": "https://forum.sentinel-hub.com/c/aws-sentinel", "ManagedBy": "[Sinergise](https://www.sinergise.com/)", @@ -28438,17 +28470,17 @@ "stac" ], "Explore": null, - "RequesterPays": null, + "RequesterPays": true, "ControlledAccess": null, "AccountRequired": null, "Host": null }, { "Name": "Sentinel-2", - "Description": "New scene notifications for L1C, can subscribe with Lambda", - "ARN": "arn:aws:sns:eu-west-1:214830741341:NewSentinel2Product", - "Region": "eu-west-1", - "Type": "SNS Topic", + "Description": "Zipped archives for each L1C product with 3 day retention period, in Requester Pays bucket", + "ARN": "arn:aws:s3:::sentinel-s2-l1c-zips", + "Region": "eu-central-1", + "Type": "S3 Bucket", "Documentation": "Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/sentinel-s2-l1c/readme.html) and [Sentinel-2 L2A](https://roda.sentinel-hub.com/sentinel-s2-l2a/readme.html).", "Contact": "https://forum.sentinel-hub.com/c/aws-sentinel", "ManagedBy": "[Sinergise](https://www.sinergise.com/)", @@ -28465,15 +28497,15 @@ "stac" ], "Explore": null, - "RequesterPays": null, + "RequesterPays": true, "ControlledAccess": null, "AccountRequired": null, "Host": null }, { "Name": "Sentinel-2", - "Description": "Level 1C scenes and metadata, in Requester Pays S3 bucket", - "ARN": "arn:aws:s3:::sentinel-s2-l1c", + "Description": "S3 Inventory files for L2A and CSV", + "ARN": "arn:aws:s3:::sentinel-inventory/sentinel-s2-l2a", "Region": "eu-central-1", "Type": "S3 Bucket", "Documentation": "Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/sentinel-s2-l1c/readme.html) and [Sentinel-2 L2A](https://roda.sentinel-hub.com/sentinel-s2-l2a/readme.html).", @@ -28491,21 +28523,16 @@ "disaster response", "stac" ], - "Explore": [ - "[Earth Search STAC L1C Collection](https://earth-search.aws.element84.com/v1/collections/sentinel-2-l1c)", - "[Earth Search STAC Browser L1C Collection](https://radiantearth.github.io/stac-browser/#/external/earth-search.aws.element84.com/v1/collections/sentinel-2-l1c)", - "[STAC V1.0.0 endpoint](https://sentinel-s2-l1c-stac.s3.amazonaws.com/)", - "[Earth Viewer by Element 84](https://viewer.aws.element84.com/)" - ], - "RequesterPays": true, + "Explore": null, + "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, "Host": null }, { "Name": "Sentinel-2", - "Description": "S3 Inventory files for L1C and CSV", - "ARN": "arn:aws:s3:::sentinel-inventory/sentinel-s2-l1c", + "Description": "Level 2A scenes and metadata, in Requester Pays S3 bucket", + "ARN": "arn:aws:s3:::sentinel-s2-l2a", "Region": "eu-central-1", "Type": "S3 Bucket", "Documentation": "Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/sentinel-s2-l1c/readme.html) and [Sentinel-2 L2A](https://roda.sentinel-hub.com/sentinel-s2-l2a/readme.html).", @@ -28523,16 +28550,18 @@ "disaster response", "stac" ], - "Explore": null, - "RequesterPays": null, + "Explore": [ + "[STAC V1.0.0 endpoint](https://sentinel-s2-l2a-stac.s3.amazonaws.com/)" + ], + "RequesterPays": true, "ControlledAccess": null, "AccountRequired": null, "Host": null }, { "Name": "Sentinel-2", - "Description": "Level 2A scenes and metadata, in Requester Pays S3 bucket", - "ARN": "arn:aws:s3:::sentinel-s2-l2a", + "Description": "S3 Inventory files for L1C and CSV", + "ARN": "arn:aws:s3:::sentinel-inventory/sentinel-s2-l1c", "Region": "eu-central-1", "Type": "S3 Bucket", "Documentation": "Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/sentinel-s2-l1c/readme.html) and [Sentinel-2 L2A](https://roda.sentinel-hub.com/sentinel-s2-l2a/readme.html).", @@ -28550,18 +28579,16 @@ "disaster response", "stac" ], - "Explore": [ - "[STAC V1.0.0 endpoint](https://sentinel-s2-l2a-stac.s3.amazonaws.com/)" - ], - "RequesterPays": true, + "Explore": null, + "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, "Host": null }, { "Name": "Sentinel-2", - "Description": "Zipped archives for each L2A product with 3 day retention period, in Requester Pays bucket", - "ARN": "arn:aws:s3:::sentinel-s2-l2a-zips", + "Description": "Level 1C scenes and metadata, in Requester Pays S3 bucket", + "ARN": "arn:aws:s3:::sentinel-s2-l1c", "Region": "eu-central-1", "Type": "S3 Bucket", "Documentation": "Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/sentinel-s2-l1c/readme.html) and [Sentinel-2 L2A](https://roda.sentinel-hub.com/sentinel-s2-l2a/readme.html).", @@ -28579,7 +28606,12 @@ "disaster response", "stac" ], - "Explore": null, + "Explore": [ + "[Earth Search STAC L1C Collection](https://earth-search.aws.element84.com/v1/collections/sentinel-2-l1c)", + "[Earth Search STAC Browser L1C Collection](https://radiantearth.github.io/stac-browser/#/external/earth-search.aws.element84.com/v1/collections/sentinel-2-l1c)", + "[STAC V1.0.0 endpoint](https://sentinel-s2-l1c-stac.s3.amazonaws.com/)", + "[Earth Viewer by Element 84](https://viewer.aws.element84.com/)" + ], "RequesterPays": true, "ControlledAccess": null, "AccountRequired": null, @@ -28587,10 +28619,10 @@ }, { "Name": "Sentinel-2", - "Description": "Zipped archives for each L1C product with 3 day retention period, in Requester Pays bucket", - "ARN": "arn:aws:s3:::sentinel-s2-l1c-zips", + "Description": "New scene notifications for L2A, can subscribe with Lambda", + "ARN": "arn:aws:sns:eu-central-1:214830741341:SentinelS2L2A", "Region": "eu-central-1", - "Type": "S3 Bucket", + "Type": "SNS Topic", "Documentation": "Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/sentinel-s2-l1c/readme.html) and [Sentinel-2 L2A](https://roda.sentinel-hub.com/sentinel-s2-l2a/readme.html).", "Contact": "https://forum.sentinel-hub.com/c/aws-sentinel", "ManagedBy": "[Sinergise](https://www.sinergise.com/)", @@ -28607,15 +28639,15 @@ "stac" ], "Explore": null, - "RequesterPays": true, + "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, "Host": null }, { "Name": "Sentinel-2 Cloud-Optimized GeoTIFFs", - "Description": "Level 2A scenes and metadata", - "ARN": "arn:aws:s3:::sentinel-cogs", + "Description": "S3 Inventory files for L1C and CSV", + "ARN": "arn:aws:s3:::sentinel-cogs-inventory", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/cirrus-geo/cirrus-earth-search", @@ -28634,21 +28666,18 @@ "cog", "stac" ], - "Explore": [ - "[Earth Search STAC L2A Collection](https://earth-search.aws.element84.com/v1/collections/sentinel-2-l2a)", - "[STAC Browser L2A Collection](https://radiantearth.github.io/stac-browser/#/external/earth-search.aws.element84.com/v1/collections/sentinel-2-l2a)" - ], - "RequesterPays": false, + "Explore": null, + "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, "Host": null }, { "Name": "Sentinel-2 Cloud-Optimized GeoTIFFs", - "Description": "S3 Inventory files for L1C and CSV", - "ARN": "arn:aws:s3:::sentinel-cogs-inventory", + "Description": "New scene notifications, can subscribe with Lambda", + "ARN": "arn:aws:sns:us-west-2:608149789419:cirrus-v0-publish", "Region": "us-west-2", - "Type": "S3 Bucket", + "Type": "SNS Topic", "Documentation": "https://github.com/cirrus-geo/cirrus-earth-search", "Contact": "opendata@element84.com", "ManagedBy": "[Element 84](https://www.element84.com/)", @@ -28673,10 +28702,10 @@ }, { "Name": "Sentinel-2 Cloud-Optimized GeoTIFFs", - "Description": "New scene notifications, can subscribe with Lambda", - "ARN": "arn:aws:sns:us-west-2:608149789419:cirrus-v0-publish", + "Description": "Level 2A scenes and metadata", + "ARN": "arn:aws:s3:::sentinel-cogs", "Region": "us-west-2", - "Type": "SNS Topic", + "Type": "S3 Bucket", "Documentation": "https://github.com/cirrus-geo/cirrus-earth-search", "Contact": "opendata@element84.com", "ManagedBy": "[Element 84](https://www.element84.com/)", @@ -28693,8 +28722,11 @@ "cog", "stac" ], - "Explore": null, - "RequesterPays": null, + "Explore": [ + "[Earth Search STAC L2A Collection](https://earth-search.aws.element84.com/v1/collections/sentinel-2-l2a)", + "[STAC Browser L2A Collection](https://radiantearth.github.io/stac-browser/#/external/earth-search.aws.element84.com/v1/collections/sentinel-2-l2a)" + ], + "RequesterPays": false, "ControlledAccess": null, "AccountRequired": null, "Host": null @@ -28786,8 +28818,8 @@ }, { "Name": "Sentinel-3", - "Description": "Sentinel-3 Near Real Time Data (NRT) format", - "ARN": "arn:aws:s3:::meeo-s3/NRT/", + "Description": "Sentinel-3 Not Time Critical (NTC) format", + "ARN": "arn:aws:s3:::meeo-s3/NTC/", "Region": "eu-central-1", "Type": "S3 Bucket", "Documentation": "https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel3Description.md", @@ -28814,8 +28846,8 @@ }, { "Name": "Sentinel-3", - "Description": "Sentinel-3 Not Time Critical (NTC) format", - "ARN": "arn:aws:s3:::meeo-s3/NTC/", + "Description": "Sentinel-3 Near Real Time Data (NRT) format", + "ARN": "arn:aws:s3:::meeo-s3/NRT/", "Region": "eu-central-1", "Type": "S3 Bucket", "Documentation": "https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel3Description.md", @@ -28842,8 +28874,8 @@ }, { "Name": "Sentinel-5P Level 2", - "Description": "Sentinel-5p Cloud Optimised GeoTIFF (COGT) TIFF format", - "ARN": "arn:aws:s3:::meeo-s5p/COGT/", + "Description": "Sentinel-5p Reprocessed Data (RPRO) NetCDF format", + "ARN": "arn:aws:s3:::meeo-s5p/RPRO/", "Region": "eu-central-1", "Type": "S3 Bucket", "Documentation": "https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel5P_Description.md", @@ -28862,9 +28894,7 @@ "cog", "stac" ], - "Explore": [ - "[STAC V1.0.0 endpoint](https://meeo-s5p.s3.amazonaws.com/index.html?t=catalogs)" - ], + "Explore": null, "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, @@ -28872,8 +28902,8 @@ }, { "Name": "Sentinel-5P Level 2", - "Description": "Sentinel-5p Near Real Time Data (NRTI) NetCDF format", - "ARN": "arn:aws:s3:::meeo-s5p/NRTI/", + "Description": "Sentinel-5p Cloud Optimised GeoTIFF (COGT) TIFF format", + "ARN": "arn:aws:s3:::meeo-s5p/COGT/", "Region": "eu-central-1", "Type": "S3 Bucket", "Documentation": "https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel5P_Description.md", @@ -28892,7 +28922,9 @@ "cog", "stac" ], - "Explore": null, + "Explore": [ + "[STAC V1.0.0 endpoint](https://meeo-s5p.s3.amazonaws.com/index.html?t=catalogs)" + ], "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, @@ -28928,8 +28960,8 @@ }, { "Name": "Sentinel-5P Level 2", - "Description": "Sentinel-5p Reprocessed Data (RPRO) NetCDF format", - "ARN": "arn:aws:s3:::meeo-s5p/RPRO/", + "Description": "Sentinel-5p Near Real Time Data (NRTI) NetCDF format", + "ARN": "arn:aws:s3:::meeo-s5p/NRTI/", "Region": "eu-central-1", "Type": "S3 Bucket", "Documentation": "https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel5P_Description.md", @@ -29578,10 +29610,10 @@ }, { "Name": "Sudachi Language Resources", - "Description": "SudachiDict: Binary format of the mophological analysis dictionarieschiVe: Pretrained word embedding in various formats", - "ARN": "arn:aws:s3:::sudachi", + "Description": "Cloudfront CDN mirror", + "ARN": null, "Region": "ap-northeast-1", - "Type": "S3 Bucket", + "Type": "CloudFront Distribution", "Documentation": "https://worksapplications.github.io/Sudachi/", "Contact": "sudachi@worksap.co.jp", "ManagedBy": "[Works Applications](https://www.worksap.co.jp/about/csr/nlp/)", @@ -29595,14 +29627,14 @@ "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, - "Host": null + "Host": "d2ej7fkh96fzlu.cloudfront.net" }, { "Name": "Sudachi Language Resources", - "Description": "Cloudfront CDN mirror", - "ARN": null, + "Description": "SudachiDict: Binary format of the mophological analysis dictionarieschiVe: Pretrained word embedding in various formats", + "ARN": "arn:aws:s3:::sudachi", "Region": "ap-northeast-1", - "Type": "CloudFront Distribution", + "Type": "S3 Bucket", "Documentation": "https://worksapplications.github.io/Sudachi/", "Contact": "sudachi@worksap.co.jp", "ManagedBy": "[Works Applications](https://www.worksap.co.jp/about/csr/nlp/)", @@ -29616,12 +29648,12 @@ "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, - "Host": "d2ej7fkh96fzlu.cloudfront.net" + "Host": null }, { "Name": "Sup3rCC", - "Description": "Sup3rCC Generative Models", - "ARN": "arn:aws:s3:::nrel-pds-sup3rcc/models/", + "Description": "Sup3rCC", + "ARN": "arn:aws:s3:::nrel-pds-sup3rcc/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/NREL/sup3r", @@ -29637,7 +29669,7 @@ "climate model" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-sup3rcc&prefix=models%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-sup3rcc)" ], "RequesterPays": null, "ControlledAccess": null, @@ -29646,8 +29678,8 @@ }, { "Name": "Sup3rCC", - "Description": "Sup3rCC", - "ARN": "arn:aws:s3:::nrel-pds-sup3rcc/", + "Description": "Sup3rCC Generative Models", + "ARN": "arn:aws:s3:::nrel-pds-sup3rcc/models/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/NREL/sup3r", @@ -29663,7 +29695,7 @@ "climate model" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-sup3rcc)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-sup3rcc&prefix=models%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -29933,9 +29965,9 @@ }, { "Name": "Terrain Tiles", - "Description": "Gridded elevation tiles - replication in EU region", - "ARN": "arn:aws:s3:::elevation-tiles-prod-eu", - "Region": "eu-central-1", + "Description": "Gridded elevation tiles", + "ARN": "arn:aws:s3:::elevation-tiles-prod", + "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "https://github.com/tilezen/joerd/tree/master/docs", "Contact": "https://github.com/tilezen/joerd/issues", @@ -29950,7 +29982,9 @@ "geospatial", "disaster response" ], - "Explore": null, + "Explore": [ + "[Browse Map](https://elevation-tiles-prod.s3.amazonaws.com/index.html)" + ], "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, @@ -29958,9 +29992,9 @@ }, { "Name": "Terrain Tiles", - "Description": "Gridded elevation tiles", - "ARN": "arn:aws:s3:::elevation-tiles-prod", - "Region": "us-east-1", + "Description": "Gridded elevation tiles - replication in EU region", + "ARN": "arn:aws:s3:::elevation-tiles-prod-eu", + "Region": "eu-central-1", "Type": "S3 Bucket", "Documentation": "https://github.com/tilezen/joerd/tree/master/docs", "Contact": "https://github.com/tilezen/joerd/issues", @@ -29975,9 +30009,7 @@ "geospatial", "disaster response" ], - "Explore": [ - "[Browse Map](https://elevation-tiles-prod.s3.amazonaws.com/index.html)" - ], + "Explore": null, "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, @@ -30381,10 +30413,10 @@ }, { "Name": "Transiting Exoplanet Survey Satellite (TESS)", - "Description": "Notifications for new data", - "ARN": "arn:aws:sns:us-east-1:879230861493:stpubdata", + "Description": "TESS Mission data files", + "ARN": "arn:aws:s3:::stpubdata/tess", "Region": "us-east-1", - "Type": "SNS Topic", + "Type": "S3 Bucket", "Documentation": "https://archive.stsci.edu/missions-and-data/tess", "Contact": "archive@stsci.edu", "ManagedBy": "[Space Telescope Science Institute](http://www.stsci.edu/)", @@ -30395,17 +30427,17 @@ "aws-pds" ], "Explore": null, - "RequesterPays": null, + "RequesterPays": false, "ControlledAccess": null, "AccountRequired": null, "Host": null }, { "Name": "Transiting Exoplanet Survey Satellite (TESS)", - "Description": "TESS Mission data files", - "ARN": "arn:aws:s3:::stpubdata/tess", + "Description": "Notifications for new data", + "ARN": "arn:aws:sns:us-east-1:879230861493:stpubdata", "Region": "us-east-1", - "Type": "S3 Bucket", + "Type": "SNS Topic", "Documentation": "https://archive.stsci.edu/missions-and-data/tess", "Contact": "archive@stsci.edu", "ManagedBy": "[Space Telescope Science Institute](http://www.stsci.edu/)", @@ -30416,7 +30448,7 @@ "aws-pds" ], "Explore": null, - "RequesterPays": false, + "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, "Host": null @@ -30680,8 +30712,8 @@ }, { "Name": "USGS Landsat", - "Description": "New scene notifications, Level 3 Science Products", - "ARN": "arn:aws:sns:us-west-2:673253540267:public-c2-level-3-tile-notify-v2", + "Description": "New scene notifications, Level-1 and Level-2 Scenes", + "ARN": "arn:aws:sns:us-west-2:673253540267:public-c2-notify-v2", "Region": "us-west-2", "Type": "SNS Topic", "Documentation": "https://www.usgs.gov/core-science-systems/nli/landsat/landsat-commercial-cloud-data-access", @@ -30708,10 +30740,10 @@ }, { "Name": "USGS Landsat", - "Description": "New scene notifications, Level-1 and Level-2 Scenes", - "ARN": "arn:aws:sns:us-west-2:673253540267:public-c2-notify-v2", + "Description": "Scenes and metadata", + "ARN": "arn:aws:s3:::usgs-landsat/collection02/", "Region": "us-west-2", - "Type": "SNS Topic", + "Type": "S3 Bucket", "Documentation": "https://www.usgs.gov/core-science-systems/nli/landsat/landsat-commercial-cloud-data-access", "Contact": "https://answers.usgs.gov/", "ManagedBy": "[United States Geological Survey](https://www.usgs.gov)", @@ -30728,18 +30760,20 @@ "stac", "cog" ], - "Explore": null, - "RequesterPays": null, + "Explore": [ + "[STAC Catalog](https://landsatlook.usgs.gov/stac-server/collections)" + ], + "RequesterPays": true, "ControlledAccess": null, "AccountRequired": null, "Host": null }, { "Name": "USGS Landsat", - "Description": "Scenes and metadata", - "ARN": "arn:aws:s3:::usgs-landsat/collection02/", + "Description": "New scene notifications, Level 3 Science Products", + "ARN": "arn:aws:sns:us-west-2:673253540267:public-c2-level-3-tile-notify-v2", "Region": "us-west-2", - "Type": "S3 Bucket", + "Type": "SNS Topic", "Documentation": "https://www.usgs.gov/core-science-systems/nli/landsat/landsat-commercial-cloud-data-access", "Contact": "https://answers.usgs.gov/", "ManagedBy": "[United States Geological Survey](https://www.usgs.gov)", @@ -30756,10 +30790,8 @@ "stac", "cog" ], - "Explore": [ - "[STAC Catalog](https://landsatlook.usgs.gov/stac-server/collections)" - ], - "RequesterPays": true, + "Explore": null, + "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, "Host": null @@ -30843,8 +30875,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2021_02", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2021-02/", + "Description": "UniProt 2022_03", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2022-03/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -30873,8 +30905,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2021_03", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2021-03/", + "Description": "UniProt 2022_02", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2022-02/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -30903,8 +30935,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2021_04", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2021-04/", + "Description": "UniProt 2022_01", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2022-01/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -30933,8 +30965,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2022_01", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2022-01/", + "Description": "UniProt 2021_01", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2021-01/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -30963,8 +30995,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2022_02", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2022-02/", + "Description": "UniProt 2021_02", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2021-02/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -30993,8 +31025,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2022_03", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2022-03/", + "Description": "UniProt 2022_04", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2022-04/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31023,8 +31055,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2022_05", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2022-05/", + "Description": "UniProt 2021_04", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2021-04/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31053,8 +31085,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2022_04", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2022-04/", + "Description": "UniProt 2022_05", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2022-05/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31083,8 +31115,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2023_02", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2023-02/", + "Description": "UniProt 2021_03", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2021-03/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31113,8 +31145,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2021_01", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2021-01/", + "Description": "UniProt 2023_02", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2023-02/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31143,8 +31175,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2023_04", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2023-04/", + "Description": "UniProt 2023_03", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2023-03/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31173,8 +31205,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2023_05", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2023-05/", + "Description": "UniProt 2023_04", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2023-04/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31203,8 +31235,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2024_01", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2024-01/", + "Description": "UniProt 2023_05", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2023-05/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31233,8 +31265,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2024_02", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2024-02/", + "Description": "UniProt 2024_01", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2024-01/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31263,8 +31295,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2024_03", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2024-03/", + "Description": "UniProt 2024_02", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2024-02/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31293,8 +31325,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2024_05", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2024-05/", + "Description": "UniProt 2024_03", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2024-03/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31323,8 +31355,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2023_01", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2023-01/", + "Description": "UniProt 2024_05", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2024-05/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31353,8 +31385,8 @@ }, { "Name": "UniProt", - "Description": "UniProt 2023_03", - "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2023-03/", + "Description": "UniProt 2023_01", + "ARN": "arn:aws:s3:::aws-open-data-uniprot-rdf/2023-01/", "Region": "eu-west-3", "Type": "S3 Bucket", "Documentation": "https://www.uniprot.org/help/about", @@ -31503,8 +31535,8 @@ }, { "Name": "Vermont Open Geospatial on AWS", - "Description": "Imagery datsets are organized in this bucket as statewide file mosaics and by acquisition year (often a portion of the state in any given year) These data are available in Cloud Optimized GeoTIFF (COG) format and use the following naming convention; 1) Statewide - STATEWIDE__cm__<#BANDS>Band, 2) By Acquisition Year - _cm__<#BANDS>Band Individual tiles are also available as lossless COGs under the /_Tiles subfolder", - "ARN": "arn:aws:s3:::vtopendata-prd/Imagery", + "Description": "Elevation datsets (primarily lidar based) are organized in this bucket as statewide file mosaics and by acquisition year (often a portion of the state in any given year) These data are available in Cloud Optimized GeoTIFF (COG) format and use the following naming convention; 1) Statewide COGs - STATEWIDE__cm_, 2) By Acquisition Year - _cm_ Individual tiles are also available as lossless COGs under the /_Tiles subfolder", + "ARN": "arn:aws:s3:::vtopendata-prd/Elevation", "Region": "us-east-2", "Type": "S3 Bucket", "Documentation": "https://vcgi.vermont.gov/data-and-programs/", @@ -31553,8 +31585,8 @@ }, { "Name": "Vermont Open Geospatial on AWS", - "Description": "Elevation datsets (primarily lidar based) are organized in this bucket as statewide file mosaics and by acquisition year (often a portion of the state in any given year) These data are available in Cloud Optimized GeoTIFF (COG) format and use the following naming convention; 1) Statewide COGs - STATEWIDE__cm_, 2) By Acquisition Year - _cm_ Individual tiles are also available as lossless COGs under the /_Tiles subfolder", - "ARN": "arn:aws:s3:::vtopendata-prd/Elevation", + "Description": "Imagery datsets are organized in this bucket as statewide file mosaics and by acquisition year (often a portion of the state in any given year) These data are available in Cloud Optimized GeoTIFF (COG) format and use the following naming convention; 1) Statewide - STATEWIDE__cm__<#BANDS>Band, 2) By Acquisition Year - _cm__<#BANDS>Band Individual tiles are also available as lossless COGs under the /_Tiles subfolder", + "ARN": "arn:aws:s3:::vtopendata-prd/Imagery", "Region": "us-east-2", "Type": "S3 Bucket", "Documentation": "https://vcgi.vermont.gov/data-and-programs/", @@ -31866,8 +31898,8 @@ }, { "Name": "Wind AI Bench", - "Description": "Wind AI Bench Airfoil Computational Fluid Dynamics (CFD) - 2k Shapes Data Sets", - "ARN": "arn:aws:s3:::nrel-pds-windai/aerodynamic_shapes/2D/2K_airfoils/", + "Description": "Wind AI Bench Airfoil Computational Fluid Dynamics (CFD) - 9k Shapes Data Sets", + "ARN": "arn:aws:s3:::nrel-pds-windai/aerodynamic_shapes/2D/9K_airfoils/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/NREL/windAI_bench", @@ -31882,7 +31914,7 @@ "machine learning" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-windai&prefix=aerodynamic_shapes%2F2D%2F2k_airfoils%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-windai&prefix=aerodynamic_shapes%2F2D%2F9k_airfoils%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -31916,8 +31948,8 @@ }, { "Name": "Wind AI Bench", - "Description": "Wind AI Bench Airfoil Computational Fluid Dynamics (CFD) - 9k Shapes Data Sets", - "ARN": "arn:aws:s3:::nrel-pds-windai/aerodynamic_shapes/2D/9K_airfoils/", + "Description": "Wind AI Bench Airfoil Computational Fluid Dynamics (CFD) - 2k Shapes Data Sets", + "ARN": "arn:aws:s3:::nrel-pds-windai/aerodynamic_shapes/2D/2K_airfoils/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/NREL/windAI_bench", @@ -31932,7 +31964,7 @@ "machine learning" ], "Explore": [ - "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-windai&prefix=aerodynamic_shapes%2F2D%2F9k_airfoils%2F)" + "[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-windai&prefix=aerodynamic_shapes%2F2D%2F2k_airfoils%2F)" ], "RequesterPays": null, "ControlledAccess": null, @@ -32071,9 +32103,9 @@ }, { "Name": "YouTube 8 Million - Data Lakehouse Ready", - "Description": "Replica of the two locations above in us-east-1", - "ARN": "arn:aws:s3:::aws-roda-ml-datalake-us-east-1/", - "Region": "us-east-1", + "Description": "Lakehouse ready YT8M as Glue Parquet files Install instructions here", + "ARN": "arn:aws:s3:::aws-roda-ml-datalake/yt8m_ods/", + "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/docs/roda_install.md", "Contact": "https://github.com/aws-samples/data-lake-as-code/issues", @@ -32096,8 +32128,8 @@ }, { "Name": "YouTube 8 Million - Data Lakehouse Ready", - "Description": "Lakehouse ready YT8M as Glue Parquet files Install instructions here", - "ARN": "arn:aws:s3:::aws-roda-ml-datalake/yt8m_ods/", + "Description": "Original YT8M *tfrecords File structure info can be found here", + "ARN": "arn:aws:s3:::aws-roda-ml-datalake/yt8m/", "Region": "us-west-2", "Type": "S3 Bucket", "Documentation": "https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/docs/roda_install.md", @@ -32121,9 +32153,9 @@ }, { "Name": "YouTube 8 Million - Data Lakehouse Ready", - "Description": "Original YT8M *tfrecords File structure info can be found here", - "ARN": "arn:aws:s3:::aws-roda-ml-datalake/yt8m/", - "Region": "us-west-2", + "Description": "Replica of the two locations above in us-east-1", + "ARN": "arn:aws:s3:::aws-roda-ml-datalake-us-east-1/", + "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/docs/roda_install.md", "Contact": "https://github.com/aws-samples/data-lake-as-code/issues", @@ -32194,8 +32226,8 @@ }, { "Name": "iHART Whole Genome Sequencing Data Set", - "Description": "BAM, gVCF, and VCF files from The iHART whole genome sequencing study, Phase I", - "ARN": "arn:aws:s3:::ihart-release", + "Description": "gVCF and VCF files from The iHART whole genome sequencing study, control data sets", + "ARN": "arn:aws:s3:::ihart-brain", "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "http://www.ihart.org/data", @@ -32221,8 +32253,8 @@ }, { "Name": "iHART Whole Genome Sequencing Data Set", - "Description": "BAM, gVCF, and VCF files from The iHART whole genome sequencing study, Phase II", - "ARN": "arn:aws:s3:::ihart-main", + "Description": "Cram, gVCF, and VCF files from The iHART whole genome sequencing study, Phase I+II, GRCh38", + "ARN": "arn:aws:s3:::ihart-hg38", "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "http://www.ihart.org/data", @@ -32248,8 +32280,8 @@ }, { "Name": "iHART Whole Genome Sequencing Data Set", - "Description": "Cram, gVCF, and VCF files from The iHART whole genome sequencing study, Phase I+II, GRCh38", - "ARN": "arn:aws:s3:::ihart-hg38", + "Description": "BAM, gVCF, and VCF files from The iHART whole genome sequencing study, Phase II", + "ARN": "arn:aws:s3:::ihart-main", "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "http://www.ihart.org/data", @@ -32275,8 +32307,8 @@ }, { "Name": "iHART Whole Genome Sequencing Data Set", - "Description": "gVCF and VCF files from The iHART whole genome sequencing study, control data sets", - "ARN": "arn:aws:s3:::ihart-brain", + "Description": "BAM, gVCF, and VCF files from The iHART whole genome sequencing study, Phase I", + "ARN": "arn:aws:s3:::ihart-release", "Region": "us-east-1", "Type": "S3 Bucket", "Documentation": "http://www.ihart.org/data", @@ -32405,10 +32437,10 @@ }, { "Name": "nuPlan", - "Description": "Globally cached distribution of the nuPlan Dataset Web frontend is available to browse the dataset", - "ARN": null, + "Description": "nuPlan Dataset", + "ARN": "arn:aws:s3:::motional-nuplan", "Region": "ap-northeast-1", - "Type": "CloudFront Distribution", + "Type": "S3 Bucket", "Documentation": "https://nuplan.org", "Contact": "https://nuplan.org", "ManagedBy": "[Motional, Inc.](https://motional.com)", @@ -32422,18 +32454,20 @@ "transportation", "urban" ], - "Explore": null, + "Explore": [ + "[Browse Bucket](https://motional-nuplan.s3.ap-northeast-1.amazonaws.com/index.html)" + ], "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, - "Host": "https://d1qinkmu0ju04f.cloudfront.net" + "Host": null }, { "Name": "nuPlan", - "Description": "nuPlan Dataset", - "ARN": "arn:aws:s3:::motional-nuplan", + "Description": "Globally cached distribution of the nuPlan Dataset Web frontend is available to browse the dataset", + "ARN": null, "Region": "ap-northeast-1", - "Type": "S3 Bucket", + "Type": "CloudFront Distribution", "Documentation": "https://nuplan.org", "Contact": "https://nuplan.org", "ManagedBy": "[Motional, Inc.](https://motional.com)", @@ -32447,13 +32481,11 @@ "transportation", "urban" ], - "Explore": [ - "[Browse Bucket](https://motional-nuplan.s3.ap-northeast-1.amazonaws.com/index.html)" - ], + "Explore": null, "RequesterPays": null, "ControlledAccess": null, "AccountRequired": null, - "Host": null + "Host": "https://d1qinkmu0ju04f.cloudfront.net" }, { "Name": "nuScenes", @@ -32511,10 +32543,10 @@ }, { "Name": "real-changesets", - "Description": "New File Notification", - "ARN": "arn:aws:sns:us-west-2:877446169145:real-changesets-object_created", + "Description": "real-changesets", + "ARN": "arn:aws:s3:::real-changesets", "Region": "us-west-2", - "Type": "SNS Topic", + "Type": "S3 Bucket", "Documentation": "https://github.com/osmus/osmcha-charter-project/blob/main/real-changesets-docs.md", "Contact": "team@openstreetmap.us", "ManagedBy": "OpenStreetMap US", @@ -32535,10 +32567,10 @@ }, { "Name": "real-changesets", - "Description": "real-changesets", - "ARN": "arn:aws:s3:::real-changesets", + "Description": "New File Notification", + "ARN": "arn:aws:sns:us-west-2:877446169145:real-changesets-object_created", "Region": "us-west-2", - "Type": "S3 Bucket", + "Type": "SNS Topic", "Documentation": "https://github.com/osmus/osmcha-charter-project/blob/main/real-changesets-docs.md", "Contact": "team@openstreetmap.us", "ManagedBy": "OpenStreetMap US", diff --git a/aws_open_datasets.tsv b/aws_open_datasets.tsv index ad8ddea..b5ac1e9 100644 --- a/aws_open_datasets.tsv +++ b/aws_open_datasets.tsv @@ -809,9 +809,9 @@ NREL Wind Integration National Dataset California offshore wind resource data (2 NREL Wind Integration National Dataset Mid Atlantic wind resource data with modeled wakes in HDF5 format arn:aws:s3:::nrel-pds-wtk/NOW-WAKES_Mid_Atlantic/ us-west-2 S3 Bucket https://www.nrel.gov/grid/wind-toolkit.html wind-toolkit@nrel.gov [National Renewable Energy Laboratory](https://www.nrel.gov/) As Needed Creative Commons Attribution 3.0 United States License aws-pds, environmental, geospatial, meteorological ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=NOW-WAKES_Mid_Atlantic%2F)'] NREL Wind Integration National Dataset Southeast Asia wind resource data v3 (2007-2021) in HDF5 format arn:aws:s3:::nrel-pds-wtk/seasiawind_v3/ us-west-2 S3 Bucket https://www.nrel.gov/grid/wind-toolkit.html wind-toolkit@nrel.gov [National Renewable Energy Laboratory](https://www.nrel.gov/) As Needed Creative Commons Attribution 3.0 United States License aws-pds, environmental, geospatial, meteorological ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=seasiawind_v3%2F)'] NREL Wind Integration National Dataset Mid Atlantic three-dimensional planetary boundary layer (3D PBL) scheme wind res arn:aws:s3:::nrel-pds-wtk/mid_atlantic_3d_pbl/ us-west-2 S3 Bucket https://www.nrel.gov/grid/wind-toolkit.html wind-toolkit@nrel.gov [National Renewable Energy Laboratory](https://www.nrel.gov/) As Needed Creative Commons Attribution 3.0 United States License aws-pds, environmental, geospatial, meteorological ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=mid_atlantic_3d_pbl%2F)'] +NREL Wind Integration National Dataset Southeast Asia wind resource data v2 (2007-2021) in HDF5 format arn:aws:s3:::nrel-pds-wtk/seasiawind_v2/ us-west-2 S3 Bucket https://www.nrel.gov/grid/wind-toolkit.html wind-toolkit@nrel.gov [National Renewable Energy Laboratory](https://www.nrel.gov/) As Needed Creative Commons Attribution 3.0 United States License aws-pds, environmental, geospatial, meteorological ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=seasiawind_v2%2F)'] NREL Wind Integration National Dataset Southeast Asia wind resource data (2017-2021) in HDF5 format arn:aws:s3:::nrel-pds-wtk/seasiawind/ us-west-2 S3 Bucket https://www.nrel.gov/grid/wind-toolkit.html wind-toolkit@nrel.gov [National Renewable Energy Laboratory](https://www.nrel.gov/) As Needed Creative Commons Attribution 3.0 United States License aws-pds, environmental, geospatial, meteorological ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=seasiawind%2F)'] NREL Wind Integration National Dataset Puerto Rico wind resource data (2001-2020) in HDF5 format arn:aws:s3:::nrel-pds-wtk/pr100/ us-west-2 S3 Bucket https://www.nrel.gov/grid/wind-toolkit.html wind-toolkit@nrel.gov [National Renewable Energy Laboratory](https://www.nrel.gov/) As Needed Creative Commons Attribution 3.0 United States License aws-pds, environmental, geospatial, meteorological ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=pr100%2F)'] -NREL Wind Integration National Dataset Southeast Asia wind resource data v2 (2007-2021) in HDF5 format arn:aws:s3:::nrel-pds-wtk/seasiawind_v2/ us-west-2 S3 Bucket https://www.nrel.gov/grid/wind-toolkit.html wind-toolkit@nrel.gov [National Renewable Energy Laboratory](https://www.nrel.gov/) As Needed Creative Commons Attribution 3.0 United States License aws-pds, environmental, geospatial, meteorological ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=seasiawind_v2%2F)'] NREL Wind Integration National Dataset Maine wind resource data (2000-2020) in HDF5 format arn:aws:s3:::nrel-pds-wtk/maine/ us-west-2 S3 Bucket https://www.nrel.gov/grid/wind-toolkit.html wind-toolkit@nrel.gov [National Renewable Energy Laboratory](https://www.nrel.gov/) As Needed Creative Commons Attribution 3.0 United States License aws-pds, environmental, geospatial, meteorological ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-wtk&prefix=maine%2F)'] NSF NCAR Curated ECMWF Reanalysis 5 (ERA5) ERA5 NetCDF4 Data Files arn:aws:s3:::nsf-ncar-era5 us-west-2 S3 Bucket https://doi.org/10.5065/BH6N-5N20 rdahelp@ucar.edu [NSF National Center for Atmospheric Research](https://ncar.ucar.edu/) Monthly, with a 3-4 month lag from realtime https://www.ucar.edu/terms-of-use/data climate, model, atmosphere, land, data assimilation, forecast, meteorological, weather, geoscience, geospatial, aws-pds, netcdf ['[Browse Bucket](https://nsf-ncar-era5.s3.amazonaws.com/index.html)'] NSF NCAR Curated ECMWF Reanalysis 5 (ERA5) Notifications for the NSF NCAR ERA5 bucket arn:aws:sns:us-west-2:891377163634:nsf-ncar-era5-object_created us-west-2 SNS Topic https://doi.org/10.5065/BH6N-5N20 rdahelp@ucar.edu [NSF National Center for Atmospheric Research](https://ncar.ucar.edu/) Monthly, with a 3-4 month lag from realtime https://www.ucar.edu/terms-of-use/data climate, model, atmosphere, land, data assimilation, forecast, meteorological, weather, geoscience, geospatial, aws-pds, netcdf @@ -821,9 +821,9 @@ Nanopore Reference Human Genome Nanopore Reference Human Genome arn:aws:s3:::nan NapierOne Mixed File Dataset NapierOne Mixed File Dataset arn:aws:s3:::napierone.com eu-north-1 S3 Bucket https://github.com/simonrdavies/NapierOne Simon Davies s.davies@napier.ac.uk Richard Macfarlane R.Macfarlane@napier.ac.u [School of Computing at Edinburgh Napier University](https://www.napier.ac.uk/ab Data will be added as methodology improves or new common or required file types NapierOne is released under the Edinburgh Napier University License Agreement an computer forensics, computer security, cyber security, digital forensics, ransomware, malware, mixed file dataset, aws-pds ['[Browse Bucket](http://napierone.com.s3-website.eu-north-1.amazonaws.com)'] National Archives Catalog National Archives Catalog arn:aws:s3:::nara-national-archives-catalog us-east-2 S3 Bucket https://www.archives.gov/developer/national-archives-catalog-dataset public.dataset.program@nara.gov National Archives and Records Administration (NARA) Biannual US Government work nara, national archives catalog, archives, government records, aws-pds National Cancer Institute Center for Cancer Research - Diffuse Large B Cell Lymphoma (DLBCL) Genomics and Expression RNA-Seq Gene Expression Quantification arn:aws:s3:::gdc-nciccr-phs001444-2-open us-east-1 S3 Bucket https://gdc.cancer.gov/about-data/publications/DLBCL-2018 dcf-support@datacommons.io [Center for Translational Data Science at The University of Chicago](https://ctd Genomic Data Commons (GDC) is source of truth for this dataset; GDC offers month NIH Genomic Data Sharing Policy: https://gdc.cancer.gov/access-data/data-access- aws-pds, cancer, genomic -National Cancer Institute Imaging Data Commons (IDC) Collections De-identified imaging data files in DICOM format distributed under CC-NC license arn:aws:s3:::idc-open-data-cr us-east-1 S3 Bucket https://learn.canceridc.dev/ https://discourse.canceridc.dev/ Imaging Data Commons (IDC)(https://imaging.datacommons.cancer.gov) team Every 1-3 months https://fairsharing.org/FAIRsharing.0b5a1d aws-pds, cancer, imaging, digital pathology, radiology, microscopy, fluorescence imaging, image processing, machine learning National Cancer Institute Imaging Data Commons (IDC) Collections Second bucket containing de-identified imaging data files in DICOM format distri arn:aws:s3:::idc-open-data-two us-east-1 S3 Bucket https://learn.canceridc.dev/ https://discourse.canceridc.dev/ Imaging Data Commons (IDC)(https://imaging.datacommons.cancer.gov) team Every 1-3 months https://fairsharing.org/FAIRsharing.0b5a1d aws-pds, cancer, imaging, digital pathology, radiology, microscopy, fluorescence imaging, image processing, machine learning National Cancer Institute Imaging Data Commons (IDC) Collections De-identified imaging data files in DICOM format distributed under CC-BY license arn:aws:s3:::idc-open-data us-east-1 S3 Bucket https://learn.canceridc.dev/ https://discourse.canceridc.dev/ Imaging Data Commons (IDC)(https://imaging.datacommons.cancer.gov) team Every 1-3 months https://fairsharing.org/FAIRsharing.0b5a1d aws-pds, cancer, imaging, digital pathology, radiology, microscopy, fluorescence imaging, image processing, machine learning +National Cancer Institute Imaging Data Commons (IDC) Collections De-identified imaging data files in DICOM format distributed under CC-NC license arn:aws:s3:::idc-open-data-cr us-east-1 S3 Bucket https://learn.canceridc.dev/ https://discourse.canceridc.dev/ Imaging Data Commons (IDC)(https://imaging.datacommons.cancer.gov) team Every 1-3 months https://fairsharing.org/FAIRsharing.0b5a1d aws-pds, cancer, imaging, digital pathology, radiology, microscopy, fluorescence imaging, image processing, machine learning National Climate Database (NCDB) NCDB CONUS 4km Hourly CONUS (2006-2100) in HDF5 format arn:aws:s3:::nrel-pds-ncdb/4km-Hourly-CONUS/ us-west-2 S3 Bucket https://nsrdb.nrel.gov/ Manajit.Sengupta@nrel.gov [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, earth observation, energy, geospatial, meteorological, solar, climate projections, CMIP5, CMIP6 ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-ncdb&prefix=v3%2F4km-Hourly-CONUS%2F)'] National Climate Database (NCDB) National Climate Database (NCDB) arn:aws:s3:::nrel-pds-ncdb/ us-west-2 S3 Bucket https://nsrdb.nrel.gov/ Manajit.Sengupta@nrel.gov [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, earth observation, energy, geospatial, meteorological, solar, climate projections, CMIP5, CMIP6 ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-ncdb)'] National Climate Database (NCDB) HSDS NCDB Domains arn:aws:s3:::nrel-pds-hsds/nrel/ncdb/ us-west-2 S3 Bucket https://nsrdb.nrel.gov/ Manajit.Sengupta@nrel.gov [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, earth observation, energy, geospatial, meteorological, solar, climate projections, CMIP5, CMIP6 ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-hsds&prefix=nrel%2Fncdb%2F)'] @@ -857,7 +857,7 @@ ONS Open Data Portal Data of the relationship between power plant and group (PT- ONS Open Data Portal Data of the relationship between power plant and groups of small power plants (P arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/usina_pqu)'] ONS Open Data Portal Daily stored energy per basin (PT-BR Energia Armazenada (EAR) diário por bacia) arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/ear-diario-por-bacia)'] ONS Open Data Portal Daily stored energy per equivalent energy reservoir (PT-BR Energia Armazenada (E arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/ear-diario-por-ree-reservatorio-equivalente-de-energia)'] -ONS Open Data Portal Daily stored energy per subsystem (PT-BR Energia Armazenada (EAR) diário por sub arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/ear-diario-por-subsistema)'] +ONS Open Data Portal Daily stored energy per reservoir (PT-BR Energia Armazenada (EAR) diário por res arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/ear-diario-por-reservatorio)'] ONS Open Data Portal Daily affluent natural energy per basin (PT-BR Energia Natural Afluente (ENA) di arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/ena-diario-por-bacia)'] ONS Open Data Portal Daily affluent natural energy per equivalent energy reservoir (PT-BR Energia Nat arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/ena-diario-por-ree-reservatorio-equivalente-de-energia)'] ONS Open Data Portal Contour of watersheds (PT-BR Contorno das Bacias Hidrográficas) arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/bacia_contorno)'] @@ -886,7 +886,7 @@ ONS Open Data Portal Fluviometric data (PT-BR Grandezas fluviométricas) arn:aws ONS Open Data Portal Generation per power plant on an hourly basis (PT-BR Geração por usina em base h arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/geracao-usina-2)'] ONS Open Data Portal Performance indicator of generation functions per generating unit on an yearly b arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/ind_disponibilidade_fgeracao_uge_anual)'] ONS Open Data Portal Weekly marginal cost of operation (PT-BR Custo Marginal de Operação (CMO) semana arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/cmo-semanal)'] -ONS Open Data Portal Daily stored energy per reservoir (PT-BR Energia Armazenada (EAR) diário por res arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/ear-diario-por-reservatorio)'] +ONS Open Data Portal Daily stored energy per subsystem (PT-BR Energia Armazenada (EAR) diário por sub arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/ear-diario-por-subsistema)'] ONS Open Data Portal Scheduled energy charge (PT-BR Carga de energia programda) arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/carga-energia-programada)'] ONS Open Data Portal Monthly energy charge (PT-BR Carga de energia mensal) arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/carga-mensal)'] ONS Open Data Portal Daily energy charge (PT-BR Carga de Energia Diária) arn:aws:s3:::ons-aws-prod-opendata sa-east-1 S3 Bucket https://dados.ons.org.br/dataset/ dadosabertos@ons.org.br [ONS - National Electric System Operator](https://www.ons.org.br/) diary CC-BY 4.0 aws-pds, electricity, hydrography, energy ['[Browse Dataset](https://dados.ons.org.br/dataset/carga-energia)'] @@ -904,36 +904,36 @@ Open Bioinformatics Reference Data for Galaxy The data is organized as versioned Open City Model (OCM) Project data files arn:aws:s3:::opencitymodel us-east-1 S3 Bucket https://github.com/opencitymodel/opencitymodel https://github.com/opencitymodel/opencitymodel#contact BuildZero Quarterly https://github.com/opencitymodel/opencitymodel#license aws-pds, events, cities, geospatial Open Food Facts Images Open Food Facts image dataset arn:aws:s3:::openfoodfacts-images eu-west-3 S3 Bucket https://openfoodfacts.github.io/openfoodfacts-server/api/aws-images-dataset contact@openfoodfacts.org [Open Food Facts](https://world.openfoodfacts.org) Monthly All data contained in this dataset is licenced under the [Creative Commons Attri aws-pds, machine learning, image processing Open NeuroData Neuroglancer precomputed volumes in a public bucket arn:aws:s3:::open-neurodata us-east-1 S3 Bucket https://neurodata.io/help/download/ support@neurodata.io [NeuroData](https://neurodata.io/ocp) The dataset may be updated with additional or corrected data on a need-to-update ODC-By v1.0 unless otherwise specified aws-pds, biology, image processing, neuroimaging, neuroscience, electron microscopy, life sciences, light-sheet microscopy, magnetic resonance imaging, array tomography -Open Observatory of Network Interference (OONI) Old S3 bucket with cans for older measurements arn:aws:s3:::ooni-data us-east-1 S3 Bucket https://ooni.org/data/ https://ooni.org/get-involved/ Open Observatory of Network Interference Hourly Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International https:// aws-pds, internet Open Observatory of Network Interference (OONI) New S3 bucket with JSONL files arn:aws:s3:::ooni-data-eu-fra eu-central-1 S3 Bucket https://ooni.org/data/ https://ooni.org/get-involved/ Open Observatory of Network Interference Hourly Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International https:// aws-pds, internet +Open Observatory of Network Interference (OONI) Old S3 bucket with cans for older measurements arn:aws:s3:::ooni-data us-east-1 S3 Bucket https://ooni.org/data/ https://ooni.org/get-involved/ Open Observatory of Network Interference Hourly Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International https:// aws-pds, internet Open VLF: Scientific Open Data Initiative for CRAAM's SAVNET and AWESOME VLF Data. The Open VLF Files Total size of 736 GB arn:aws:s3:::craam-files-bucket sa-east-1 S3 Bucket [Open VLF](https://open-vlf.web.app) [Open VLF Feedback](https://open-vlf.web.app/markdown/the-project) [CRAAM Mackenzie](https://www.mackenzie.br/centro-de-radio-astronomia-e-astrofis Various. Data since 2006, and still updated. Follow the announcements and what i There are no restrictions on the use of this data. archives, astronomy, atmosphere, aws-pds, global, open source software, signal processing Open-Meteo Weather API Database Open-Meteo Weather API Database arn:aws:s3:::openmeteo us-west-2 S3 Bucket https://github.com/open-meteo/open-data info@open-meteo.com [Open-Meteo](https://www.open-meteo.com/) Hourly CC-BY 4.0 aws-pds, agriculture, climate, earth observation, meteorological, weather ['[Browse Bucket](https://openmeteo.s3.amazonaws.com/index.html#data/)'] -OpenAQ OpenAQ API us-east-1 CloudFront Distribution https://openaq.org info@openaq.org [OpenAQ](https://openaq.org) Hourly Varies, depends on data provider aws-pds, air quality, cities, environmental, geospatial api.openaq.org OpenAQ Daily gzipped CSVs of global air quality measurements fetched from sources all o arn:aws:s3:::openaq-data-archive us-east-1 S3 Bucket https://openaq.org info@openaq.org [OpenAQ](https://openaq.org) Hourly Varies, depends on data provider aws-pds, air quality, cities, environmental, geospatial +OpenAQ OpenAQ API us-east-1 CloudFront Distribution https://openaq.org info@openaq.org [OpenAQ](https://openaq.org) Hourly Varies, depends on data provider aws-pds, air quality, cities, environmental, geospatial api.openaq.org OpenAQ SNS topic for new objects in the openaq-data-archive bucket arn:aws:sns:us-east-1:817926761842:openaq-data-archive-object_created us-east-1 SNS Topic https://openaq.org info@openaq.org [OpenAQ](https://openaq.org) Hourly Varies, depends on data provider aws-pds, air quality, cities, environmental, geospatial OpenAerialMap on AWS OpenAerialMap files and metadata arn:aws:s3:::oin-hotosm us-east-1 S3 Bucket https://docs.openaerialmap.org/ info@openaerialmap.org [Humanitarian OpenStreetMap Team](https://www.hotosm.org/) New imagery is added as soon as it is uploaded by community contributors. All imagery is publicly licensed CC-BY 4.0, with attribution as contributors of satellite imagery, aerial imagery, earth observation, disaster response, cog ['[Browse Bucket](https://oin-hotosm.s3.amazonaws.com/)'] -OpenAlex dataset Openalex Entities decomposed to tab-separated columnar files for backward compat arn:aws:s3:::openalex-mag-format us-east-1 S3 Bucket https://docs.openalex.org team@ourresearch.org [OurResearch](https://ourresearch.org/) Approximately monthly [CC0](https://creativecommons.org/publicdomain/zero/1.0/) graph, json, metadata, scholarly communication, aws-pds ['[Browse Bucket](https://openalex-mag-format.s3.amazonaws.com/browse.html)'] OpenAlex dataset OpenAlex Entities in JSON Lines format arn:aws:s3:::openalex us-east-1 S3 Bucket https://docs.openalex.org team@ourresearch.org [OurResearch](https://ourresearch.org/) Approximately monthly [CC0](https://creativecommons.org/publicdomain/zero/1.0/) graph, json, metadata, scholarly communication, aws-pds ['[Browse Bucket](https://openalex.s3.amazonaws.com/browse.html)'] +OpenAlex dataset Openalex Entities decomposed to tab-separated columnar files for backward compat arn:aws:s3:::openalex-mag-format us-east-1 S3 Bucket https://docs.openalex.org team@ourresearch.org [OurResearch](https://ourresearch.org/) Approximately monthly [CC0](https://creativecommons.org/publicdomain/zero/1.0/) graph, json, metadata, scholarly communication, aws-pds ['[Browse Bucket](https://openalex-mag-format.s3.amazonaws.com/browse.html)'] OpenCRAVAT OpenCRAVAT Store US arn:aws:s3:::opencravat-store-aws us-east-1 S3 Bucket https://open-cravat.readthedocs.io support@opencravat.org KarchinLab, Potomac IT Group Data is mirrored daily. Update frequencies of individual annotators depend on th "License varies per-annotator. Commercial users must check the ""commercial_warnin" aws-pds, genetic, genomic, life sciences, variant annotation, sqlite, tertiary analysis OpenCRAVAT OpenCRAVAT Store EU arn:aws:s3:::opencravat-store-eu-west-2 eu-west-2 S3 Bucket https://open-cravat.readthedocs.io support@opencravat.org KarchinLab, Potomac IT Group Data is mirrored daily. Update frequencies of individual annotators depend on th "License varies per-annotator. Commercial users must check the ""commercial_warnin" aws-pds, genetic, genomic, life sciences, variant annotation, sqlite, tertiary analysis OpenCell on AWS Live-cell confocal fluorescence microscopy images of the OpenCell library of flu arn:aws:s3:::czb-opencell us-west-2 S3 Bucket https://opencell.czbiohub.org/download opencell@czbiohub.org [Chan Zuckerberg Biohub](https://www.czbiohub.org/) This is the final version of the dataset. https://github.com/czbiohub/opencell/blob/master/LICENSE aws-pds, biology, cell biology, life sciences, imaging, cell imaging, fluorescence imaging, microscopy, computer vision, machine learning OpenEEW OpenEEW arn:aws:s3:::grillo-openeew us-east-1 S3 Bucket https://github.com/openeew/openeew hello@openeew.com [Grillo](https://grillo.io/) Approximately every 5 minutes https://github.com/openeew/openeew#license disaster response, earth observation, earthquakes, aws-pds ['[Browse Bucket](https://grillo-openeew.s3.amazonaws.com/index.html)'] OpenNeuro MRI, MEG, EEG, iEEG, and ECoG datasets from OpenNeuro arn:aws:s3:::openneuro.org us-east-1 S3 Bucket http://openneuro.org Support form at https://openneuro.org [Stanford University Center for Reproducible Neuroscience](https://reproducibili New datasets deposited every 4-6 days CC0 aws-pds, biology, imaging, life sciences, neurobiology, neuroimaging OpenProteinSet A repository of MSAs and template hits arn:aws:s3:::openfold us-east-1 S3 Bucket https://docs.google.com/document/d/1R90-VJSLQEbot7tgXF3zb068Y1ZJAmsckQ_t2sJTv2c/ https://github.com/aqlaboratory/openfold/issues OpenFold Never [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) openfold, msa, protein, protein template, protein folding, alphafold, open source software, life sciences, aws-pds -OpenStreetMap on AWS Imagery and metadata arn:aws:s3:::osm-pds us-east-1 S3 Bucket https://github.com/awslabs/open-data-docs/tree/main/docs/osm-pds https://github.com/mojodna/osm-pds-pipelines/issues Pacific Atlas Data is updated weekly https://www.openstreetmap.org/copyright aws-pds, geospatial, mapping, osm, disaster response OpenStreetMap on AWS New data notifications arn:aws:sns:us-east-1:800218804198:New_File us-east-1 SNS Topic https://github.com/awslabs/open-data-docs/tree/main/docs/osm-pds https://github.com/mojodna/osm-pds-pipelines/issues Pacific Atlas Data is updated weekly https://www.openstreetmap.org/copyright aws-pds, geospatial, mapping, osm, disaster response +OpenStreetMap on AWS Imagery and metadata arn:aws:s3:::osm-pds us-east-1 S3 Bucket https://github.com/awslabs/open-data-docs/tree/main/docs/osm-pds https://github.com/mojodna/osm-pds-pipelines/issues Pacific Atlas Data is updated weekly https://www.openstreetmap.org/copyright aws-pds, geospatial, mapping, osm, disaster response OpenSurfaces OpenSurfaces data arn:aws:s3:::labelmaterial us-east-1 S3 Bucket http://opensurfaces.cs.cornell.edu/publications/opensurfaces/ snavely@cs.cornell.edu Cornell University Static dataset (not updated) The annotations are licensed under a Creative Commons Attribution 4.0 Internatio computer vision, aws-pds ['[Browse data on project webpage](http://opensurfaces.cs.cornell.edu/)'] OpenUniverse 2024 Matched Rubin and Roman Simulations: Preview The simulated Roman data products include truth files listing the basic physical arn:aws:s3:::nasa-irsa-simulations/openuniverse2024/roman/ us-east-1 S3 Bucket https://irsa.ipac.caltech.edu/data/theory/openuniverse2024 https://irsa.ipac.caltech.edu/docs/help_desk.html NASA/IPAC Infrared Science Archive ([IRSA](https://irsa.ipac.caltech.edu)) at Ca The OpenUniverse 2024 Data Preview has been finalized and will not be updated. https://irsa.ipac.caltech.edu/data_use_terms.html aws-pds, astronomy, imaging, object detection, parquet, satellite imagery, simulations, survey False False OpenUniverse 2024 Matched Rubin and Roman Simulations: Preview The simulated Rubin data products include raw pixel data, calibrated exposures, arn:aws:s3:::nasa-irsa-simulations/openuniverse2024/rubin/ us-east-1 S3 Bucket https://irsa.ipac.caltech.edu/data/theory/openuniverse2024 https://irsa.ipac.caltech.edu/docs/help_desk.html NASA/IPAC Infrared Science Archive ([IRSA](https://irsa.ipac.caltech.edu)) at Ca The OpenUniverse 2024 Data Preview has been finalized and will not be updated. https://irsa.ipac.caltech.edu/data_use_terms.html aws-pds, astronomy, imaging, object detection, parquet, satellite imagery, simulations, survey False False Opioid Industry Documents Archive (OIDA) Data on AWS Raw data from the Opioid Industry Documents Archive (OIDA), including documents arn:aws:s3:::opioid-industry-documents-archive-dataset-bucket us-east-1 S3 Bucket https://opioid-industry-documents-archive-dataset-bucket.s3.amazonaws.com/index. opioidarchive@jh.edu Johns Hopkins University monthly https://www.industrydocuments.ucsf.edu/opioids/help/copyright/ aws-pds, archives, text analysis, txt, pharmaceutical +Orcasound - bioacoustic data for marine conservation Labeled audio data for ML model development arn:aws:s3:::acoustic-sandbox us-west-2 S3 Bucket https://github.com/orcasound/orcadata/wiki info@orcasound.net Orcasound Typical latency is 10-120 seconds https://creativecommons.org/licenses/by-nc-sa/4.0/ aws-pds, biodiversity, biology, coastal, conservation, deep learning, ecosystems, environmental, geospatial, labeled, machine learning, mapping, oceans, open source software, signal processing Orcasound - bioacoustic data for marine conservation Live-streamed orca audio data (HLS) arn:aws:s3:::streaming-orcasound-net us-west-2 S3 Bucket https://github.com/orcasound/orcadata/wiki info@orcasound.net Orcasound Typical latency is 10-120 seconds https://creativecommons.org/licenses/by-nc-sa/4.0/ aws-pds, biodiversity, biology, coastal, conservation, deep learning, ecosystems, environmental, geospatial, labeled, machine learning, mapping, oceans, open source software, signal processing Orcasound - bioacoustic data for marine conservation Archived lossless orca audio data (FLAC) arn:aws:s3:::archive-orcasound-net us-west-2 S3 Bucket https://github.com/orcasound/orcadata/wiki info@orcasound.net Orcasound Typical latency is 10-120 seconds https://creativecommons.org/licenses/by-nc-sa/4.0/ aws-pds, biodiversity, biology, coastal, conservation, deep learning, ecosystems, environmental, geospatial, labeled, machine learning, mapping, oceans, open source software, signal processing -Orcasound - bioacoustic data for marine conservation Labeled audio data for ML model development arn:aws:s3:::acoustic-sandbox us-west-2 S3 Bucket https://github.com/orcasound/orcadata/wiki info@orcasound.net Orcasound Typical latency is 10-120 seconds https://creativecommons.org/licenses/by-nc-sa/4.0/ aws-pds, biodiversity, biology, coastal, conservation, deep learning, ecosystems, environmental, geospatial, labeled, machine learning, mapping, oceans, open source software, signal processing Oregon Health & Science University Chronic Neutrophilic Leukemia Dataset RNA-Seq Gene Expression Quantification arn:aws:s3:::gdc-ohsu-cnl-phs001799-2-open us-east-1 S3 Bucket https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001799.v dcf-support@datacommons.io [Center for Translational Data Science at The University of Chicago](https://ctd Genomic Data Commons (GDC) is source of truth for this dataset; GDC offers month NIH Genomic Data Sharing Policy: https://gdc.cancer.gov/access-data/data-access- aws-pds, cancer, genomic, life sciences -Overture Maps Foundation Open Map Data Overture Maps Foundation Data (GeoParquet) arn:aws:s3:::overturemaps-us-west-2/release/ us-west-2 S3 Bucket Documentation is available at [docs.overturemaps.org](https://docs.overturemaps. info@overturemaps.org [Overture Maps Foundation](https://overturemaps.org) Monthly Overture data is licensed under the Community Database License Agreement Permiss aws-pds, geospatial, global, mapping, osm, parquet, transportation Overture Maps Foundation Open Map Data New File Notification arn:aws:sns:us-west-2:913550007193:overturemaps-us-west-2 us-west-2 SNS Topic Documentation is available at [docs.overturemaps.org](https://docs.overturemaps. info@overturemaps.org [Overture Maps Foundation](https://overturemaps.org) Monthly Overture data is licensed under the Community Database License Agreement Permiss aws-pds, geospatial, global, mapping, osm, parquet, transportation -Oxford Nanopore Technologies Benchmark Datasets Nanopore sequencing data of the Genome in a Bottle samples NA24385, NA24149, and arn:aws:s3:::ont-open-data/giab_lsk114_2022.12 eu-west-1 S3 Bucket https://labs.epi2me.io/dataindex/ support@nanoporetech.com Oxford Nanopore Technologies Additional datasets will be added periodically. Updates and amendents will be ma Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) https://creativecommo aws-pds, bioinformatics, biology, fastq, fast5, genomic, life sciences, Homo sapiens, whole genome sequencing False +Overture Maps Foundation Open Map Data Overture Maps Foundation Data (GeoParquet) arn:aws:s3:::overturemaps-us-west-2/release/ us-west-2 S3 Bucket Documentation is available at [docs.overturemaps.org](https://docs.overturemaps. info@overturemaps.org [Overture Maps Foundation](https://overturemaps.org) Monthly Overture data is licensed under the Community Database License Agreement Permiss aws-pds, geospatial, global, mapping, osm, parquet, transportation Oxford Nanopore Technologies Benchmark Datasets Oxford Nanopore Open Datasets arn:aws:s3:::ont-open-data eu-west-1 S3 Bucket https://labs.epi2me.io/dataindex/ support@nanoporetech.com Oxford Nanopore Technologies Additional datasets will be added periodically. Updates and amendents will be ma Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) https://creativecommo aws-pds, bioinformatics, biology, fastq, fast5, genomic, life sciences, Homo sapiens, whole genome sequencing False +Oxford Nanopore Technologies Benchmark Datasets Nanopore sequencing data of the Genome in a Bottle samples NA24385, NA24149, and arn:aws:s3:::ont-open-data/giab_lsk114_2022.12 eu-west-1 S3 Bucket https://labs.epi2me.io/dataindex/ support@nanoporetech.com Oxford Nanopore Technologies Additional datasets will be added periodically. Updates and amendents will be ma Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) https://creativecommo aws-pds, bioinformatics, biology, fastq, fast5, genomic, life sciences, Homo sapiens, whole genome sequencing False Oxford Nanopore Technologies Benchmark Datasets Using nanopore sequencing, researchers have directly identified DNA and RNA base arn:aws:s3:::ont-open-data/gm24385_mod_2021.09/extra_analysis/bonito_remora eu-west-1 S3 Bucket https://labs.epi2me.io/dataindex/ support@nanoporetech.com Oxford Nanopore Technologies Additional datasets will be added periodically. Updates and amendents will be ma Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) https://creativecommo aws-pds, bioinformatics, biology, fastq, fast5, genomic, life sciences, Homo sapiens, whole genome sequencing False Oxford Nanopore Technologies Benchmark Datasets CpG dinucleotides frequently occur in high-density clusters called CpG islands ( arn:aws:s3:::ont-open-data/rrms_2022.07 eu-west-1 S3 Bucket https://labs.epi2me.io/dataindex/ support@nanoporetech.com Oxford Nanopore Technologies Additional datasets will be added periodically. Updates and amendents will be ma Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) https://creativecommo aws-pds, bioinformatics, biology, fastq, fast5, genomic, life sciences, Homo sapiens, whole genome sequencing False Ozone Monitoring Instrument (OMI) / Aura NO2 Tropospheric Column Density S3 Bucket for OMI NO2 in Cloud-Optimized GeoTiff format arn:aws:s3:::omi-no2-nasa us-west-2 S3 Bucket https://disc.gsfc.nasa.gov/datasets/OMNO2d_003/summary binita.kc@nasa.gov NASA None There are no restrictions on the use of these data. aws-pds, earth observation, geospatial, satellite imagery, air quality, atmosphere, environmental @@ -944,60 +944,60 @@ PALSAR-2 ScanSAR Turkey & Syria Earthquake (L2.1 & L1.1) PALSAR-2 ScanSAR L11 & PASS: Perturb-and-Select Summarizer for Product Reviews A collection of summaries generated by PASS for the FewSum Product Reviews datas arn:aws:s3:::pass-summary-fewsum us-east-1 S3 Bucket https://pass-summary-fewsum.s3.amazonaws.com/README.md noved@amazon.com [Amazon](https://www.amazon.com/) Not updated This data is available for anyone to use under the terms of the CDLA-Sharing lic amazon.science, natural language processing, text analysis ['[pass_generated_summaries.jsonl](https://pass-summary-fewsum.s3.amazonaws.com/pass_gen_summaries_fewsum_amazon_val_test.jsonl)'] PD12M Image files arn:aws:s3:::pd12m us-west-2 S3 Bucket https://huggingface.co/datasets/Spawning/PD12M info@spawning.ai Spawning Data will be adjusted as infringing works are discovered, improved provenance is https://cdla.dev/permissive-2-0/ image processing, machine learning, media, art, deep learning, labeled PROJ datum grids Horizontal and vertical adjustment datasets us-east-1 CloudFront Distribution https://github.com/OSGeo/proj-datumgrid-geotiff proj@lists.osgeo.org [PROJ](https://proj.org) New grids are added when made available Per file. Under an Open Source Definition compliant license. Consult the READMEs aws-pds, geospatial, mapping cdn.proj.org -Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2021 arn:aws:s3:::pacific-sound-256khz-2021 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software -Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2020 arn:aws:s3:::pacific-sound-256khz-2020 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software -Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2019 arn:aws:s3:::pacific-sound-256khz-2019 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software -Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2018 arn:aws:s3:::pacific-sound-256khz-2018 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software -Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2017 arn:aws:s3:::pacific-sound-256khz-2017 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software -Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2016 arn:aws:s3:::pacific-sound-256khz-2016 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software +Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2023 arn:aws:s3:::pacific-sound-256khz-2023 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2015 arn:aws:s3:::pacific-sound-256khz-2015 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software +Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2016 arn:aws:s3:::pacific-sound-256khz-2016 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software +Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2017 arn:aws:s3:::pacific-sound-256khz-2017 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software +Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2018 arn:aws:s3:::pacific-sound-256khz-2018 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software +Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2019 arn:aws:s3:::pacific-sound-256khz-2019 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software +Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2020 arn:aws:s3:::pacific-sound-256khz-2020 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software +Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2021 arn:aws:s3:::pacific-sound-256khz-2021 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software +Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2022 arn:aws:s3:::pacific-sound-256khz-2022 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software +Pacific Ocean Sound Recordings decimated 16 kHz audio recordings arn:aws:s3:::pacific-sound-16khz us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2024 arn:aws:s3:::pacific-sound-256khz-2024 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2025 arn:aws:s3:::pacific-sound-256khz-2025 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software Pacific Ocean Sound Recordings decimated 2 kHz audio recordings arn:aws:s3:::pacific-sound-2khz us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software -Pacific Ocean Sound Recordings decimated 16 kHz audio recordings arn:aws:s3:::pacific-sound-16khz us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software -Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2022 arn:aws:s3:::pacific-sound-256khz-2022 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software Pacific Ocean Sound Recordings machine learning models arn:aws:s3:::pacific-sound-models us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software -Pacific Ocean Sound Recordings original 256 kHz audio recordings year 2023 arn:aws:s3:::pacific-sound-256khz-2023 us-west-2 S3 Bucket https://docs.mbari.org/pacific-sound/ dcline@mbari.org [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) daily CC-BY 4.0 aws-pds, acoustics, biodiversity, ecosystems, biology, marine mammals, oceans, climate, coastal, deep learning, machine learning, environmental, open source software Pan-STARRS PS1 Survey PS1 DR1 and DR2 image files arn:aws:s3:::stpubdata/ps1 us-east-1 S3 Bucket https://outerspace.stsci.edu/display/PANSTARRS/ archive@stsci.edu [Space Telescope Science Institute](http://www.stsci.edu/) Never STScI hereby grants the non-exclusive, royalty-free, non-transferable, worldwide aws-pds, astronomy False -Pancreatic Cancer Organoid Profiling WGS/WXS/RNA-Seq Aligned Reads, WXS Annotated Somatic Mutation, WXS Raw Somatic M arn:aws:s3:::gdc-organoid-pancreatic-phs001611-2-controlled us-east-1 S3 Bucket https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001611.v dcf-support@datacommons.io [Center for Translational Data Science at The University of Chicago](https://ctd Genomic Data Commons (GDC) is source of truth for this dataset; GDC offers month NIH Genomic Data Sharing Policy: https://gdc.cancer.gov/access-data/data-access- aws-pds, cancer, genetic, genomic, transcriptomics, whole genome sequencing, STRIDES https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001611.v1.p1 Pancreatic Cancer Organoid Profiling RNA-Seq Gene Expression Quantification arn:aws:s3:::gdc-organoid-pancreatic-phs001611-2-open us-east-1 S3 Bucket https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001611.v dcf-support@datacommons.io [Center for Translational Data Science at The University of Chicago](https://ctd Genomic Data Commons (GDC) is source of truth for this dataset; GDC offers month NIH Genomic Data Sharing Policy: https://gdc.cancer.gov/access-data/data-access- aws-pds, cancer, genetic, genomic, transcriptomics, whole genome sequencing, STRIDES +Pancreatic Cancer Organoid Profiling WGS/WXS/RNA-Seq Aligned Reads, WXS Annotated Somatic Mutation, WXS Raw Somatic M arn:aws:s3:::gdc-organoid-pancreatic-phs001611-2-controlled us-east-1 S3 Bucket https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001611.v dcf-support@datacommons.io [Center for Translational Data Science at The University of Chicago](https://ctd Genomic Data Commons (GDC) is source of truth for this dataset; GDC offers month NIH Genomic Data Sharing Policy: https://gdc.cancer.gov/access-data/data-access- aws-pds, cancer, genetic, genomic, transcriptomics, whole genome sequencing, STRIDES https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001611.v1.p1 PersonPath22 Source data arn:aws:s3:::tracking-dataset-eccv-2022 us-east-2 S3 Bucket https://amazon-science.github.io/tracking-dataset/personpath22.html Post any questions to [re:Post](https://repost.aws/tags/questions/TApd0Wl5P8S9O6 [Amazon Web Services](https://aws.amazon.com/) Periodically Creative Commons Attribution-NonCommercial 4.0 International Public License (CC amazon.science, computer vision Phrase Clustering Dataset (PCD) Phsrase Clustering Dataset (PCD) arn:aws:s3:::amazon-phrase-clustering us-west-2 S3 Bucket https://amazon-phrase-clustering.s3.amazonaws.com/readme.md Post any questions to [re:Post](https://repost.aws/tags/questions/TApd0Wl5P8S9O6 [Amazon](https://www.amazon.com/) Not updated This data is available for anyone to use under the terms of the CDLA-permissive amazon.science, natural language processing, json ['[phrase-clustering-dataset.json](https://amazon-phrase-clustering.s3.amazonaws.com/phrase-clustering-dataset.json)'] Physionet https://s3amazonawscom/physionet-pds/indexhtml arn:aws:s3:::physionet-pds us-east-1 S3 Bucket https://physionet.org/ contact@physionet.org [MIT Laboratory for Computational Physiology](https://lcp.mit.edu/) Not updated PhysioBank databases are made available under the ODC Public Domain Dedication a aws-pds, biology, life sciences Platinum Pedigree https://githubcom/Platinum-Pedigree-Consortium/Platinum-Pedigree-Datasets arn:aws:s3:::platinum-pedigree-data us-west-1 S3 Bucket https://github.com/Platinum-Pedigree-Consortium https://github.com/Platinum-Pedigree-Consortium/Platinum-Pedigree-Datasets/issue Platinum Pedigree Consortium As needed [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) genomic, genotyping, long read sequencing, bioinformatics, Homo sapiens, life sciences, whole genome sequencing Pohang Canal Dataset: A Multimodal Maritime Dataset for Autonomous Navigation in Restricted Waters Pohang Canal dataset arn:aws:s3:::pohang-canal-dataset us-west-2 S3 Bucket https://sites.google.com/view/pohang-canal-dataset/home morin-lab@kaist.ac.kr [MORIN](http://morin.kaist.ac.kr) Not updated [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) aws-pds, autonomous vehicles, marine navigation, robotics, computer vision, lidar -PoroTomo PoroTomo Nodal Seismometer Field Notes and Metadata arn:aws:s3:::nrel-pds-porotomo/Nodal/nodal_metadata/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=Nodal%2Fnodal_metadata%2F)'] -PoroTomo PoroTomo Nodal Seismometer Continuous Data arn:aws:s3:::nrel-pds-porotomo/Nodal/nodal_sac/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=Nodal%2Fnodal_sac%2F)'] -PoroTomo PoroTomo Vertical Distributed Acoustic Sensing (DASV) Data in HDF5 format arn:aws:s3:::nrel-pds-porotomo/DAS/H5/DASV/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FH5%2FDASV%2F)'] -PoroTomo PoroTomo Horizontal Distributed Acoustic Sensing (DASH) Data in HDF5 format arn:aws:s3:::nrel-pds-porotomo/DAS/H5/DASH/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FH5%2FDASH%2F)'] -PoroTomo PoroTomo Vertical Distributed Acoustic Sensing (DASV) Data in SEG-Y format arn:aws:s3:::nrel-pds-porotomo/DAS/SEG-Y/DASV/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FSEG-Y%2FDASV%2F)'] PoroTomo PoroTomo Horizontal Distributed Acoustic Sensing (DASH) Data Resampled in Time M arn:aws:s3:::nrel-pds-porotomo/DAS/SEG-Y/DASH/Resampled/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FSEG-Y%2FDASH%2FResampled%2F)'] PoroTomo PoroTomo Horizontal Distributed Acoustic Sensing (DASH) Data in SEG-Y format arn:aws:s3:::nrel-pds-porotomo/DAS/SEG-Y/DASH/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FSEG-Y%2FDASH%2F)'] -PoroTomo PoroTomo Datasets arn:aws:s3:::nrel-pds-porotomo/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo)'] -PoroTomo PoroTomo Nodal Seismometer Sweep Data arn:aws:s3:::nrel-pds-porotomo/Nodal/nodal_sac_sweep/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=Nodal%2Fnodal_sac_sweep%2F)'] +PoroTomo PoroTomo Vertical Distributed Acoustic Sensing (DASV) Data in SEG-Y format arn:aws:s3:::nrel-pds-porotomo/DAS/SEG-Y/DASV/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FSEG-Y%2FDASV%2F)'] +PoroTomo PoroTomo Horizontal Distributed Acoustic Sensing (DASH) Data in HDF5 format arn:aws:s3:::nrel-pds-porotomo/DAS/H5/DASH/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FH5%2FDASH%2F)'] +PoroTomo PoroTomo Vertical Distributed Acoustic Sensing (DASV) Data in HDF5 format arn:aws:s3:::nrel-pds-porotomo/DAS/H5/DASV/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=DAS%2FH5%2FDASV%2F)'] PoroTomo HSDS PoroTomo domains arn:aws:s3:::nrel-pds-hsds/nrel/porotomo/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-hsds&prefix=nrel%2Fporotomo%2F)'] +PoroTomo PoroTomo Nodal Seismometer Continuous Data arn:aws:s3:::nrel-pds-porotomo/Nodal/nodal_sac/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=Nodal%2Fnodal_sac%2F)'] +PoroTomo PoroTomo Nodal Seismometer Field Notes and Metadata arn:aws:s3:::nrel-pds-porotomo/Nodal/nodal_metadata/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=Nodal%2Fnodal_metadata%2F)'] +PoroTomo PoroTomo Nodal Seismometer Sweep Data arn:aws:s3:::nrel-pds-porotomo/Nodal/nodal_sac_sweep/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo&prefix=Nodal%2Fnodal_sac_sweep%2F)'] +PoroTomo PoroTomo Datasets arn:aws:s3:::nrel-pds-porotomo/ us-west-2 S3 Bucket https://github.com/openEDI/documentation/blob/master/PoroTomo/PoroTomo.md Thomas Coleman (thomas.coleman@silixa.com) [National Renewable Energy Laboratory](https://www.nrel.gov/) As needed Creative Commons Attribution 3.0 United States License aws-pds, geothermal, seismology, image processing, geospatial ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-porotomo)'] Poseidon 3D Seismic, Australia Poseidon 3D Seismic MDIO volumes and Reports arn:aws:s3:::tgs-opendata-poseidon us-west-2 S3 Bucket TBD For any questions regarding the datasets and MDIO, email the TGS Open Data Team [TGS](https://www.tgs.com) Dataset is static. CC BY 4.0 seismology, geophysics, exploration ['[Browse Bucket](https://tgs-opendata-poseidon.s3.amazonaws.com/index.html)'] Pre- and post-purchase product questions S3 bucket with dataset arn:aws:s3:::pre-post-purchase-questions us-east-1 S3 Bucket https://pre-post-purchase-questions.s3.amazonaws.com/README.txt litalku@amazon.com [Amazon](https://www.amazon.com/) Not currently being updated [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0) amazon.science, natural language processing, machine learning ['[PrePostQuestions.csv](https://pre-post-purchase-questions.s3.amazonaws.com/PrePostQuestions.csv)'] Prefeitura Municipal de São Paulo (PMSP) LiDAR Point Cloud São Paulo city's 3D LiDAR - LAZ Files arn:aws:s3:::laz-m3dc-pmsp sa-east-1 S3 Bucket https://github.com/geoinfo-smdu/M3DC geosampa@prefeitura.sp.gov.br [GeoSampa - o mapa digital da cidade de São Paulo](http://geosampa.prefeitura.sp Local survey executed by demand generates new data as local point clouds. [GNU General Public License v3.0](https://www.gnu.org/licenses/gpl-3.0.html) cities, land, lidar, urban, geospatial, elevation, mapping, aws-pds Prefeitura Municipal de São Paulo (PMSP) LiDAR Point Cloud São Paulo city's 3D LiDAR - Entwine Point Tiles arn:aws:s3:::ept-m3dc-pmsp sa-east-1 S3 Bucket https://github.com/geoinfo-smdu/M3DC geosampa@prefeitura.sp.gov.br [GeoSampa - o mapa digital da cidade de São Paulo](http://geosampa.prefeitura.sp Local survey executed by demand generates new data as local point clouds. [GNU General Public License v3.0](https://www.gnu.org/licenses/gpl-3.0.html) cities, land, lidar, urban, geospatial, elevation, mapping, aws-pds Product Comparison Dataset for Online Shopping Product Comparison Dataset for Online Shopping arn:aws:s3:::prod-comp-shopping-dataset us-west-2 S3 Bucket https://prod-comp-shopping-dataset.s3.us-west-2.amazonaws.com/README.md Post any questions to [re:Post](https://repost.aws/tags/questions/TApd0Wl5P8S9O6 [Amazon](https://www.amazon.com/) None [CC-BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) product comparison, online shopping, amazon.science, natural language processing, machine learning ['[final_prodcomp_dataset_cleaned.tsv](https://prod-comp-shopping-dataset.s3.us-west-2.amazonaws.com/final_prodcomp_dataset_cleaned.tsv)'] -Protein Data Bank 3D Structural Biology Data Globally cached distribution of the dataset Web frontend also available to brow us-west-2 CloudFront Distribution https://www.wwpdb.org/documentation/file-format https://www.wwpdb.org/about/contact [Worldwide Protein Data Bank Partnership](wwpdb.org) New and updated data files are published weekly and released on Wednesdays 0:00 https://creativecommons.org/publicdomain/zero/1.0/ aws-pds, amino acid, archives, bioinformatics, biomolecular modeling, cell biology, chemical biology, COVID-19, electron microscopy, electron tomography, enzyme, life sciences, molecule, nuclear magnetic resonance, pharmaceutical, protein, protein template, SARS-CoV-2, structural biology, x-ray crystallography ['[Browse Dataset](https://s3.rcsb.org)'] Protein Data Bank 3D Structural Biology Data Historical snapshots of archival datasets from 2005 onwards Snapshots are gener arn:aws:s3:::pdbsnapshots us-west-2 S3 Bucket https://www.wwpdb.org/documentation/file-format https://www.wwpdb.org/about/contact [Worldwide Protein Data Bank Partnership](wwpdb.org) New and updated data files are published weekly and released on Wednesdays 0:00 https://creativecommons.org/publicdomain/zero/1.0/ aws-pds, amino acid, archives, bioinformatics, biomolecular modeling, cell biology, chemical biology, COVID-19, electron microscopy, electron tomography, enzyme, life sciences, molecule, nuclear magnetic resonance, pharmaceutical, protein, protein template, SARS-CoV-2, structural biology, x-ray crystallography ['[Browse Bucket](https://pdbsnapshots.s3.us-west-2.amazonaws.com/index.html)'] +Protein Data Bank 3D Structural Biology Data Globally cached distribution of the dataset Web frontend also available to brow us-west-2 CloudFront Distribution https://www.wwpdb.org/documentation/file-format https://www.wwpdb.org/about/contact [Worldwide Protein Data Bank Partnership](wwpdb.org) New and updated data files are published weekly and released on Wednesdays 0:00 https://creativecommons.org/publicdomain/zero/1.0/ aws-pds, amino acid, archives, bioinformatics, biomolecular modeling, cell biology, chemical biology, COVID-19, electron microscopy, electron tomography, enzyme, life sciences, molecule, nuclear magnetic resonance, pharmaceutical, protein, protein template, SARS-CoV-2, structural biology, x-ray crystallography ['[Browse Dataset](https://s3.rcsb.org)'] Provision of Web-Scale Parallel Corpora for Official European Languages (ParaCrawl) Parallel Corpora to/from English for all official EU languages arn:aws:s3:::web-language-models us-east-1 S3 Bucket https://paracrawl.eu/releases.html For questions regarding the datasets contact Kenneth Heafield, email kheafiel@in [ParaCrawl](https://paracrawl.eu) New data is added according to ParaCrawl release schedule. "Creative Commons CC0 license (""no rights reserved"")." aws-pds, machine translation, natural language processing -PubSeq - Public Sequence Resource Pubseq output data (Arvados Keep) arn:aws:s3:::pubseq-output-data us-east-2 S3 Bucket https://covid19.genenetwork.org/about https://covid19.genenetwork.org/contact [UTHSC GeneNetwork](https://covid19.genenetwork.org/) Rolling dataset. Creative Commons Attribution 4.0 International (CC BY 4.0) unless otherwise spec aws-pds, bam, bioinformatics, biology, coronavirus, COVID-19, fasta, fastq, fast5, genetic, genomic, health, json, life sciences, long read sequencing, open source software, MERS, metadata, medicine, RDF, SARS, SARS-CoV-2, SPARQL ['[Arvados download](https://covid19.genenetwork.org/download)'] PubSeq - Public Sequence Resource PubSeq submitted datasets (FASTA and JSON metadata) arn:aws:s3:::pubseq-datasets us-east-2 S3 Bucket https://covid19.genenetwork.org/about https://covid19.genenetwork.org/contact [UTHSC GeneNetwork](https://covid19.genenetwork.org/) Rolling dataset. Creative Commons Attribution 4.0 International (CC BY 4.0) unless otherwise spec aws-pds, bam, bioinformatics, biology, coronavirus, COVID-19, fasta, fastq, fast5, genetic, genomic, health, json, life sciences, long read sequencing, open source software, MERS, metadata, medicine, RDF, SARS, SARS-CoV-2, SPARQL ['[Browse Bucket](https://pubseq-datasets.s3.amazonaws.com/)'] +PubSeq - Public Sequence Resource Pubseq output data (Arvados Keep) arn:aws:s3:::pubseq-output-data us-east-2 S3 Bucket https://covid19.genenetwork.org/about https://covid19.genenetwork.org/contact [UTHSC GeneNetwork](https://covid19.genenetwork.org/) Rolling dataset. Creative Commons Attribution 4.0 International (CC BY 4.0) unless otherwise spec aws-pds, bam, bioinformatics, biology, coronavirus, COVID-19, fasta, fastq, fast5, genetic, genomic, health, json, life sciences, long read sequencing, open source software, MERS, metadata, medicine, RDF, SARS, SARS-CoV-2, SPARQL ['[Arvados download](https://covid19.genenetwork.org/download)'] Public Utility Data Liberation Project All PUDL data outputs arn:aws:s3:::pudl.catalyst.coop us-west-2 S3 Bucket You can download the [data directly](https://catalystcoop-pudl.readthedocs.io/en For general questions or feedback about the data, create an GitHub issue or disc [Catalyst Cooperative](https://catalyst.coop/) The federal agencies that publish the raw data PUDL processes release new data, The PUDL data and documentation are published under the [Creative Commons Attrib aws-pds, climate, climate model, energy, environmental, government records, infrastructure, open source software, electricity, energy modeling, utilities -PyEnvs and CallArgs PyEnvs arn:aws:s3:::pyenvs-and-callargs/pyenvs/ us-west-2 S3 Bucket https://github.com/amazon-research/function-call-argument-completion Post any questions to [re:Post](https://repost.aws/tags/questions/TApd0Wl5P8S9O6 Amazon None Planned Please note that while we are providing this aggregation of code snippets unlice machine learning, code completion PyEnvs and CallArgs CallArgs arn:aws:s3:::pyenvs-and-callargs/callargs/ us-west-2 S3 Bucket https://github.com/amazon-research/function-call-argument-completion Post any questions to [re:Post](https://repost.aws/tags/questions/TApd0Wl5P8S9O6 Amazon None Planned Please note that while we are providing this aggregation of code snippets unlice machine learning, code completion +PyEnvs and CallArgs PyEnvs arn:aws:s3:::pyenvs-and-callargs/pyenvs/ us-west-2 S3 Bucket https://github.com/amazon-research/function-call-argument-completion Post any questions to [re:Post](https://repost.aws/tags/questions/TApd0Wl5P8S9O6 Amazon None Planned Please note that while we are providing this aggregation of code snippets unlice machine learning, code completion QIIME 2 Tutorial Data Source for rendered documentation and tutorial datasets for the QIIME 2 project arn:aws:s3:::qiime2-data us-west-2 S3 Bucket https://use.qiime2.org https://forum.qiime2.org Caporaso Lab Twice per year BSD 3-Clause License aws-pds, bioinformatics, biology, ecosystems, environmental, genetic, genomic, health, microbiome, metagenomics, life sciences Quoref Project data files in a public bucket arn:aws:s3:::ai2-public-datasets us-west-2 S3 Bucket https://allenai.org/data/quoref info@allenai.org [Allen Institute for AI](https://allenai.org) Not updated [CC BY](https://creativecommons.org/licenses/by/4.0) aws-pds, machine learning, natural language processing RACECAR Dataset The RACECAR dataset is the first open dataset for full-scale and high-speed auto arn:aws:s3:::racecar-dataset us-west-2 S3 Bucket https://github.com/linklab-uva/RACECAR_DATA Prof. Madhur Behl (madhur.behl@viginia.edu) Amar Kulkarni (ark8su@virginia.edu) This dataset was constructed during a single racing season (2021-22). Future sea Creative Commons Attribution-NonCommercial 4.0 International Public License [(CC aws-pds, autonomous vehicles, autonomous racing, robotics, computer vision, perception, lidar, radar, GNSS, image processing, localization, object detection, object tracking RADARSAT-1 Cloud Optimized GeoTIFF (COG) images arn:aws:s3:::radarsat-r1-l1-cog ca-central-1 S3 Bucket https://www.asc-csa.gc.ca/eng/satellites/radarsat1/what-is-radarsat1.asp https://www.eodms-sgdot.nrcan-rncan.gc.ca [Natural Resources Canada](https://nrcan.gc.ca/) Products are added on an adhoc basis driven by prioritized foreign repatriation [Open Government License (OGL)](https://open.canada.ca/en/open-government-licenc earth observation, global, aws-pds, ice, agriculture, disaster response, satellite imagery, geospatial, cog, synthetic aperture radar RAPID NRT Flood Maps RAPID archive flood maps arn:aws:s3:::rapid-nrt-flood-maps us-west-2 S3 Bucket https://github.com/QingYang6/RAPID-NRT-flood-maps-on-AWS/blob/master/README.md xinyi.shen@uconn.edu; qing.yang6@hotmail.com University of Connecticut; Guangxi University NRT data will be update as soon as SAR images available and done processed. Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International aws-pds, agriculture, earth observation, water, environmental, disaster response ['[Browse Bucket](https://rapid-nrt-flood-maps.s3.amazonaws.com/index.html)'] RCM CEOS Analysis Ready Data | Données prêtes à l'analyse du CEOS pour le MCR RCM CEOS Analysis Ready Data Données prêtes à l'analyse (DPA) du CEOS pour le M arn:aws:s3:::rcm-ceos-ard ca-central-1 S3 Bucket https://www.asc-csa.gc.ca/eng/satellites/radarsat/ eodms-sgdot@nrcan-rncan.gc.ca [Natural Resources Canada](https://www.nrcan.gc.ca/) The initial dataset will be Canada-wide, 30M Compact-Polarization standard cover RCM image products are available free of charge, to the broadest extent possible aws-pds, agriculture, earth observation, satellite imagery, geospatial, sustainability, disaster response, synthetic aperture radar, stac ['[EODMS STAC for RCM CEOS ARD](https://www.eodms-sgdot.nrcan-rncan.gc.ca/stac/collections/rcm-ard/items/)'] -REDASA COVID-19 Open Data This is the raw data repository containing a common crawl of CORD-19 papers and arn:aws:s3:::pansurg-curation-raw-open-data eu-west-2 S3 Bucket https://github.com/PanSurg/redasa-sample-data/blob/master/open-data.md redasa-open-data@imperial.ac.uk REDASA Consortium, Imperial College London, UK Yearly updates CC-BY-4.0 aws-pds, COVID-19, coronavirus, life sciences, information retrieval, natural language processing, text analysis REDASA COVID-19 Open Data An S3 bucket that contains the final curation data in GroundTruth format arn:aws:s3:::pansurg-curation-final-curations-open-data eu-west-2 S3 Bucket https://github.com/PanSurg/redasa-sample-data/blob/master/open-data.md redasa-open-data@imperial.ac.uk REDASA Consortium, Imperial College London, UK Yearly updates CC-BY-4.0 aws-pds, COVID-19, coronavirus, life sciences, information retrieval, natural language processing, text analysis REDASA COVID-19 Open Data For all the questions curated during the REDASA project, we created a Kendra ind arn:aws:s3:::pansurg-curation-workflo-kendraqueryresults50d0eb-open-data eu-west-2 S3 Bucket https://github.com/PanSurg/redasa-sample-data/blob/master/open-data.md redasa-open-data@imperial.ac.uk REDASA Consortium, Imperial College London, UK Yearly updates CC-BY-4.0 aws-pds, COVID-19, coronavirus, life sciences, information retrieval, natural language processing, text analysis +REDASA COVID-19 Open Data This is the raw data repository containing a common crawl of CORD-19 papers and arn:aws:s3:::pansurg-curation-raw-open-data eu-west-2 S3 Bucket https://github.com/PanSurg/redasa-sample-data/blob/master/open-data.md redasa-open-data@imperial.ac.uk REDASA Consortium, Imperial College London, UK Yearly updates CC-BY-4.0 aws-pds, COVID-19, coronavirus, life sciences, information retrieval, natural language processing, text analysis RSNA Abdominal Trauma Detection (RSNA-ABT) Zip archive containing DCM and CSV files arn:aws:s3:::abdominal-trauma-detection us-west-2 S3 Bucket https://github.com/RSNA/AI-Challenge-Data/wiki/RSNA-Abdominal-Trauma-Detection informatics@rsna.org Radiological Society of North America (https://www.rsna.org/) The dataset may be updated with additional or corrected data on a need-to-update You may access and use these de-identified imaging datasets and annotations (“th aws-pds, radiology, medical imaging, medical image computing, machine learning, computer vision, csv, labeled, computed tomography, x-ray tomography https://mira.rsna.org/dataset/5 RSNA Cervical Spine Fracture Detection (RSNA-CSF) Dataset Zip archive containing DCM and CSV files arn:aws:s3:::cervical-spine-fracture us-west-2 S3 Bucket https://github.com/RSNA/AI-Challenge-Data/wiki/RSNA-Cervical-Spine-Fracture-Dete informatics@rsna.org [Radiological Society of North America](https://www.rsna.org/) The dataset may be updated with additional or corrected data on a need-to-update You may access and use these de-identified imaging datasets and annotations (“th aws-pds, radiology, medical imaging, medical image computing, machine learning, computer vision, csv, labeled, computed tomography, x-ray tomography https://mira.rsna.org/dataset/4 RSNA Intracranial Hemorrhage Detection Zip archive containing DCM and CSV files arn:aws:s3:::intracranial-hemorrhage us-west-2 S3 Bucket https://github.com/RSNA/AI-Challenge-Data informatics@rsna.org Radiological Society of North America (https://www.rsna.org/) The dataset may be updated with additional or corrected data on a need-to-update You may access and use these de-identified imaging datasets and annotations (“th aws-pds, radiology, medical imaging, medical image computing, machine learning, computer vision, csv, labeled, computed tomography, x-ray tomography https://mira.rsna.org/dataset/2 @@ -1006,15 +1006,15 @@ RSNA Screening Mammography Breast Cancer Detection (RSNA-SMBC) Dataset Zip archi Radiant MLHub Radiant MLHub Training Data arn:aws:s3:::radiant-mlhub us-west-2 S3 Bucket http://docs.mlhub.earth/ support@radiant.earth [Radiant Earth Foundation](https://www.radiant.earth/) New training data catalogs are added on a rolling basis Access to Radiant MLHub data is free for everyone. Each dataset has its own lice aws-pds, labeled, machine learning, geospatial, earth observation, satellite imagery, environmental, cog, stac RarePlanes Real and synthetic satellite imagery, annotations, and metadata arn:aws:s3:::rareplanes-public us-west-2 S3 Bucket www.cosmiqworks.org/RarePlanes jss5102@gmail.com and avanetten@iqt.org In-Q-Tel - CosmiQ Works None Planned [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) computer vision, deep learning, earth observation, geospatial, machine learning, satellite imagery, aws-pds, labeled Reasoning Over Paragraph Effects in Situations (ROPES) Project data files in a public bucket arn:aws:s3:::ai2-public-datasets us-west-2 S3 Bucket https://allenai.org/data/ropes info@allenai.org [Allen Institute for AI](https://allenai.org) Not updated [CC BY](https://creativecommons.org/licenses/by/4.0) aws-pds, machine learning, natural language processing, json -Reference Elevation Model of Antarctica (REMA) REMA DEM Mosaics arn:aws:s3:::pgc-opendata-dems/rema/mosaics/ us-west-2 S3 Bucket https://www.pgc.umn.edu/data/rema/ pgc-support@umn.edu [Polar Geospatial Center](https://www.pgc.umn.edu/) New DEM strips are added twice yearly. Mosaic products are added as soon as the [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecom aws-pds, elevation, earth observation, geospatial, mapping, open source software, satellite imagery, cog, stac ['[Browse STAC Catalog](https://polargeospatialcenter.github.io/stac-browser/#/external/pgc-opendata-dems.s3.us-west-2.amazonaws.com/rema/mosaics.json)'] Reference Elevation Model of Antarctica (REMA) REMA DEM Strips arn:aws:s3:::pgc-opendata-dems/rema/strips/ us-west-2 S3 Bucket https://www.pgc.umn.edu/data/rema/ pgc-support@umn.edu [Polar Geospatial Center](https://www.pgc.umn.edu/) New DEM strips are added twice yearly. Mosaic products are added as soon as the [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecom aws-pds, elevation, earth observation, geospatial, mapping, open source software, satellite imagery, cog, stac ['[Browse STAC Catalog](https://polargeospatialcenter.github.io/stac-browser/#/external/pgc-opendata-dems.s3.us-west-2.amazonaws.com/rema/strips.json)'] +Reference Elevation Model of Antarctica (REMA) REMA DEM Mosaics arn:aws:s3:::pgc-opendata-dems/rema/mosaics/ us-west-2 S3 Bucket https://www.pgc.umn.edu/data/rema/ pgc-support@umn.edu [Polar Geospatial Center](https://www.pgc.umn.edu/) New DEM strips are added twice yearly. Mosaic products are added as soon as the [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecom aws-pds, elevation, earth observation, geospatial, mapping, open source software, satellite imagery, cog, stac ['[Browse STAC Catalog](https://polargeospatialcenter.github.io/stac-browser/#/external/pgc-opendata-dems.s3.us-west-2.amazonaws.com/rema/mosaics.json)'] Reference data for HiFi human WGS HiFi Human WGS Reference data arn:aws:s3:::pacbio-hifi-human-wgs-reference us-west-2 S3 Bucket https://zenodo.org/records/8415406 dl_it-awsopendata@pacificbiosciences.com [Pacific Biosciences of California, Inc](https://www.pacb.com/) Files are updated to reflect the support for the lastest version of[PacBio WGS V [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) aws-pds, health, life sciences, Homo sapiens, long read sequencing, genetic, mapping, whole genome sequencing, vcf, variant annotation Refgenie reference genome assets Refgenie S3 Bucket arn:aws:s3:::awspds.refgenie.databio.org us-east-1 S3 Bucket http://refgenie.databio.org https://github.com/databio/refgenie/issues Sheffield lab at the University of Virginia As new data becomes available (roughly quarterly) Public domain aws-pds, biology, bioinformatics, genetic, genomic, infrastructure, life sciences, single-cell transcriptomics, transcriptomics, whole genome sequencing Registry of Open Data on AWS SNS topic for object create events arn:aws:sns:us-east-1:652627389412:roda-object_created us-east-1 SNS Topic https://github.com/awslabs/open-data-registry#how-are-datasets-added-to-the-regi opendata@amazon.com [Amazon Web Services](https://aws.amazon.com/) Automatically when new datasets are added [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0) amazon.science, json, metadata Registry of Open Data on AWS Registry of Open Data on AWS arn:aws:s3:::registry.opendata.aws/roda/ndjson/ us-east-1 S3 Bucket https://github.com/awslabs/open-data-registry#how-are-datasets-added-to-the-regi opendata@amazon.com [Amazon Web Services](https://aws.amazon.com/) Automatically when new datasets are added [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0) amazon.science, json, metadata SILAM Air Quality Surface Zarr files arn:aws:s3:::fmi-opendata-silam-surface-zarr eu-west-1 S3 Bucket http://en.ilmatieteenlaitos.fi/open-data-on-aws-s3 avoin-data@fmi.fi [Finnish Meteorological Institute](https://www.ilmatieteenlaitos.fi/) 1 time a day Creative Commons Attribution 4.0 International (CC BY 4.0) aws-pds, earth observation, climate, weather, air quality, meteorological ['[Browse Bucket](https://fmi-opendata-silam-surface-zarr.s3.amazonaws.com/index.html)'] -SILAM Air Quality Notifications for new netcdf surface data arn:aws:sns:eu-west-1:916174725480:new-fmi-opendata-silam-surface-netcdf eu-west-1 SNS Topic http://en.ilmatieteenlaitos.fi/open-data-on-aws-s3 avoin-data@fmi.fi [Finnish Meteorological Institute](https://www.ilmatieteenlaitos.fi/) 1 time a day Creative Commons Attribution 4.0 International (CC BY 4.0) aws-pds, earth observation, climate, weather, air quality, meteorological SILAM Air Quality Notifications for new zarr surface data arn:aws:sns:eu-west-1:916174725480:new-fmi-opendata-silam-surface-zarr eu-west-1 SNS Topic http://en.ilmatieteenlaitos.fi/open-data-on-aws-s3 avoin-data@fmi.fi [Finnish Meteorological Institute](https://www.ilmatieteenlaitos.fi/) 1 time a day Creative Commons Attribution 4.0 International (CC BY 4.0) aws-pds, earth observation, climate, weather, air quality, meteorological +SILAM Air Quality Notifications for new netcdf surface data arn:aws:sns:eu-west-1:916174725480:new-fmi-opendata-silam-surface-netcdf eu-west-1 SNS Topic http://en.ilmatieteenlaitos.fi/open-data-on-aws-s3 avoin-data@fmi.fi [Finnish Meteorological Institute](https://www.ilmatieteenlaitos.fi/) 1 time a day Creative Commons Attribution 4.0 International (CC BY 4.0) aws-pds, earth observation, climate, weather, air quality, meteorological SILAM Air Quality Surface NetCDF files arn:aws:s3:::fmi-opendata-silam-surface-netcdf eu-west-1 S3 Bucket http://en.ilmatieteenlaitos.fi/open-data-on-aws-s3 avoin-data@fmi.fi [Finnish Meteorological Institute](https://www.ilmatieteenlaitos.fi/) 1 time a day Creative Commons Attribution 4.0 International (CC BY 4.0) aws-pds, earth observation, climate, weather, air quality, meteorological ['[Browse Bucket](https://fmi-opendata-silam-surface-netcdf.s3.amazonaws.com/index.html)'] SILO climate data on AWS SILO open data arn:aws:s3:::silo-open-data ap-southeast-2 S3 Bucket https://www.longpaddock.qld.gov.au/silo/gridded-data https://www.longpaddock.qld.gov.au/silo/contact-us Queensland Government Daily SILO datasets are constructed by the [Queensland Government](http://www.qld.gov. aws-pds, agriculture, climate, earth observation, environmental, meteorological, model, sustainability, water, weather SMN Hi-Res Weather Forecast over Argentina WRF SMN data arn:aws:s3:::smn-ar-wrf us-west-2 S3 Bucket General information, tutorials and examples:[https://odp-aws-smn.github.io/docum For any questions regarding the data set or any general questions, you can conta [SMN](http://www.smn.gov.ar/) New data is added as soon as it's available. Two forecast cycles a day initializ [Creative Commons Attribution 2.5 Argentina License](https://creativecommons.org aws-pds, earth observation, natural resource, weather, meteorological ['[Browse Bucket](https://smn-ar-wrf.s3.amazonaws.com/index.html)'] @@ -1030,37 +1030,38 @@ Satellite - Sea surface temperature - Level 3 - Single sensor - 1 day - Day and Scottish Public Sector LiDAR Dataset LiDAR data (DSM, DTM and Laz) arn:aws:s3:::srsp-open-data eu-west-2 S3 Bucket https://remotesensingdata.gov.scot/data#/list https://remotesensingdata.gov.scot/feedback or email Scottish Government on gi-s [Joint Nature Conservation Committee](https://jncc.gov.uk/) New datasets have historically been added every 2-3 years but there is no guaran All data is made available under the [Open Government Licence v3](http://www.nat lidar, cities, coastal, environmental, urban, elevation, cog, aws-pds Sea Around Us Global Fisheries Catch Data Global Fisheries Catch Data arn:aws:s3:::fisheries-catch-data us-west-2 S3 Bucket https://www.seaaroundus.org/ubc-cic-sea-around-us-project-collaboration/ https://www.seaaroundus.org/feedback/ [Sea Around Us](https://www.seaaroundus.org/) The full dataset is computed only once or twice a year or when there is a signif This data is available for anyone to use under the [Sea Around Us Terms of Use]( aws-pds, fisheries, ecosystems, biodiversity, marine Sea Surface Temperature Daily Analysis: European Space Agency Climate Change Initiative product version 2.1 Global daily-mean sea surface temperatures from 1981 onwards, in Zarr format Th arn:aws:s3:::surftemp-sst us-west-2 S3 Bucket https://surftemp.github.io/sst-data-tutorials/ https://www.reading.ac.uk/met/ [University of Reading, Department of Meteorology](https://www.reading.ac.uk/met yearly Creative Commons Licence by attribution (https://creativecommons.org/licenses/by aws-pds, earth observation, oceans, climate, environmental, global, geospatial +Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) Single cell profiling (transcriptomics and epigenomics) data files in a public b arn:aws:s3:::sea-ad-single-cell-profiling us-west-2 S3 Bucket https://portal.brain-map.org/explore/seattle-alzheimers-disease/seattle-alzheime awspublicdataset@alleninstitute.org [Allen Institute](http://www.alleninstitute.org/) Annually https://alleninstitute.org/legal/terms-use/ aws-pds, biology, cell biology, cell imaging, epigenomics, gene expression, histopathology, Homo sapiens, imaging, medicine, microscopy, neurobiology, neuroscience, single-cell transcriptomics, transcriptomics ['[Browse Bucket](https://sea-ad-single-cell-profiling.s3.amazonaws.com/index.html)'] Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) Spatial transcriptomics data files in a public bucket arn:aws:s3:::sea-ad-spatial-transcriptomics us-west-2 S3 Bucket https://portal.brain-map.org/explore/seattle-alzheimers-disease/seattle-alzheime awspublicdataset@alleninstitute.org [Allen Institute](http://www.alleninstitute.org/) Annually https://alleninstitute.org/legal/terms-use/ aws-pds, biology, cell biology, cell imaging, epigenomics, gene expression, histopathology, Homo sapiens, imaging, medicine, microscopy, neurobiology, neuroscience, single-cell transcriptomics, transcriptomics ['[Browse Bucket](https://sea-ad-spatial-transcriptomics.s3.amazonaws.com/index.html)'] Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) Quantitative neuropathology (full resolution images, processed images, and quant arn:aws:s3:::sea-ad-quantitative-neuropathology us-west-2 S3 Bucket https://portal.brain-map.org/explore/seattle-alzheimers-disease/seattle-alzheime awspublicdataset@alleninstitute.org [Allen Institute](http://www.alleninstitute.org/) Annually https://alleninstitute.org/legal/terms-use/ aws-pds, biology, cell biology, cell imaging, epigenomics, gene expression, histopathology, Homo sapiens, imaging, medicine, microscopy, neurobiology, neuroscience, single-cell transcriptomics, transcriptomics ['[Browse Bucket](https://sea-ad-quantitative-neuropathology.s3.amazonaws.com/index.html)'] -Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) Single cell profiling (transcriptomics and epigenomics) data files in a public b arn:aws:s3:::sea-ad-single-cell-profiling us-west-2 S3 Bucket https://portal.brain-map.org/explore/seattle-alzheimers-disease/seattle-alzheime awspublicdataset@alleninstitute.org [Allen Institute](http://www.alleninstitute.org/) Annually https://alleninstitute.org/legal/terms-use/ aws-pds, biology, cell biology, cell imaging, epigenomics, gene expression, histopathology, Homo sapiens, imaging, medicine, microscopy, neurobiology, neuroscience, single-cell transcriptomics, transcriptomics ['[Browse Bucket](https://sea-ad-single-cell-profiling.s3.amazonaws.com/index.html)'] +SeeFar V0 Primary SeeFar dataset containing multi-resolution satellite imagery in cloud-op arn:aws:s3:::seefar-dataset us-east-1 S3 Bucket https://coastalcarbon.ai/seefar James Lowman Coastal Carbon Yearly The SeeFar dataset includes multiple licensing terms, specific to each satellite geospatial, earth observation, satellite imagery, climate, biodiversity, coastal, machine learning, environmental, sustainability, natural resource, global, mapping, aws-pds Sentinel Near Real-time Canada Mirror | Miroir Sentinel temps quasi réel du Canada Sentinel data over Canada | Données sentinelles au Canada arn:aws:s3:::sentinel-products-ca-mirror ca-central-1 S3 Bucket https://sentinel.esa.int/web/sentinel/home eodms-sgdot@nrcan-rncan.gc.ca [Natural Resources Canada](https://www.nrcan.gc.ca/) Sentinel-1 is an NRT dataset retrieved from ESA within 90 minutes of satellite d The access and use of Copernicus Sentinel data is available on a free, full and aws-pds, agriculture, earth observation, satellite imagery, geospatial, sustainability, disaster response, synthetic aperture radar, stac ['[EODMS STAC for Sentinel products](https://www.eodms-sgdot.nrcan-rncan.gc.ca/stac/)'] -Sentinel-1 SNS topic for notification of new scenes, can subscribe with Lambda arn:aws:sns:eu-central-1:214830741341:SentinelS1L1C eu-central-1 SNS Topic https://roda.sentinel-hub.com/sentinel-s1-l1c/GRD/readme.html https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, disaster response, cog, synthetic aperture radar -Sentinel-1 S3 Inventory files for L1C and CSV arn:aws:s3:::sentinel-inventory/ eu-central-1 S3 Bucket https://roda.sentinel-hub.com/sentinel-s1-l1c/GRD/readme.html https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, disaster response, cog, synthetic aperture radar Sentinel-1 GRD in a Requester Pays S3 bucket arn:aws:s3:::sentinel-s1-l1c eu-central-1 S3 Bucket https://roda.sentinel-hub.com/sentinel-s1-l1c/GRD/readme.html https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, disaster response, cog, synthetic aperture radar ['[STAC V1.0.0 endpoint](https://sentinel-s1-l1c-stac.s3.amazonaws.com/)'] True -Sentinel-1 Precise Orbit Determination (POD) Products Sentinel-1 Orbits bucket arn:aws:s3:::s1-orbits us-west-2 S3 Bucket https://s1-orbits.s3.us-west-2.amazonaws.com/README.html https://asf.alaska.edu/asf/contact-us/ [The Alaska Satellite Facility (ASF)](https://asf.alaska.edu/) Updated as new data becomes available on the [Copernicus Data Space Ecosystem](h Access to Sentinel data is free, full and open for the broad Regional, National, auxiliary data, disaster response, earth observation, earthquakes, floods, geophysics, sentinel-1, synthetic aperture radar ['[AWS S3 Explorer](https://s1-orbits.s3.amazonaws.com/index.html)'] +Sentinel-1 S3 Inventory files for L1C and CSV arn:aws:s3:::sentinel-inventory/ eu-central-1 S3 Bucket https://roda.sentinel-hub.com/sentinel-s1-l1c/GRD/readme.html https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, disaster response, cog, synthetic aperture radar +Sentinel-1 SNS topic for notification of new scenes, can subscribe with Lambda arn:aws:sns:eu-central-1:214830741341:SentinelS1L1C eu-central-1 SNS Topic https://roda.sentinel-hub.com/sentinel-s1-l1c/GRD/readme.html https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, disaster response, cog, synthetic aperture radar Sentinel-1 Precise Orbit Determination (POD) Products Notifications for new data arn:aws:sns:us-west-2:211125554030:s1-orbits-object_created us-west-2 SNS Topic https://s1-orbits.s3.us-west-2.amazonaws.com/README.html https://asf.alaska.edu/asf/contact-us/ [The Alaska Satellite Facility (ASF)](https://asf.alaska.edu/) Updated as new data becomes available on the [Copernicus Data Space Ecosystem](h Access to Sentinel data is free, full and open for the broad Regional, National, auxiliary data, disaster response, earth observation, earthquakes, floods, geophysics, sentinel-1, synthetic aperture radar +Sentinel-1 Precise Orbit Determination (POD) Products Sentinel-1 Orbits bucket arn:aws:s3:::s1-orbits us-west-2 S3 Bucket https://s1-orbits.s3.us-west-2.amazonaws.com/README.html https://asf.alaska.edu/asf/contact-us/ [The Alaska Satellite Facility (ASF)](https://asf.alaska.edu/) Updated as new data becomes available on the [Copernicus Data Space Ecosystem](h Access to Sentinel data is free, full and open for the broad Regional, National, auxiliary data, disaster response, earth observation, earthquakes, floods, geophysics, sentinel-1, synthetic aperture radar ['[AWS S3 Explorer](https://s1-orbits.s3.amazonaws.com/index.html)'] Sentinel-1 SLC dataset for Germany Public access to Sentinel-1 SLC IW scenes over Germany arn:aws:s3:::sentinel1-slc eu-west-1 S3 Bucket https://github.com/live-eo/sentinel1-slc/ For any enquires regarding the dataset, please email OpenData at Live-EO opendat [LiveEO](https://live-eo.com/) New Sentinel1-SLC IW data are updated regularly in an interval of 6 days, after The data usage will inherit and fully comply with the free and open data policy aws-pds, disaster response, satellite imagery, geospatial, sustainability, earth observation, environmental, synthetic aperture radar Sentinel-1 SLC dataset for South and Southeast Asia, Taiwan, Korea and Japan Public access to Sentinel-1 SLC IW scenes over South and Southeast Asia, Taiwan arn:aws:s3:::sentinel1-slc-seasia-pds ap-southeast-1 S3 Bucket https://github.com/earthobservatory/sentinel1-opds/ For any enquires regarding data delivery, please email ehill@ntu.edu.sg and stch [Earth Observatory of Singapore, Nanyang Technological University](https://earth S1 SLC data for the region of interest will be updated regularly, as it becomes The data usage will inherit and fully comply with the free and open data policy aws-pds, disaster response, satellite imagery, geospatial, earth observation, environmental, synthetic aperture radar -Sentinel-2 S3 Inventory files for L2A and CSV arn:aws:s3:::sentinel-inventory/sentinel-s2-l2a eu-central-1 S3 Bucket Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac -Sentinel-2 New scene notifications for L2A, can subscribe with Lambda arn:aws:sns:eu-central-1:214830741341:SentinelS2L2A eu-central-1 SNS Topic Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac Sentinel-2 New scene notifications for L1C, can subscribe with Lambda arn:aws:sns:eu-west-1:214830741341:NewSentinel2Product eu-west-1 SNS Topic Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac -Sentinel-2 Level 1C scenes and metadata, in Requester Pays S3 bucket arn:aws:s3:::sentinel-s2-l1c eu-central-1 S3 Bucket Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac ['[Earth Search STAC L1C Collection](https://earth-search.aws.element84.com/v1/collections/sentinel-2-l1c)', '[Earth Search STAC Browser L1C Collection](https://radiantearth.github.io/stac-browser/#/external/earth-search.aws.element84.com/v1/collections/sentinel-2-l1c)', '[STAC V1.0.0 endpoint](https://sentinel-s2-l1c-stac.s3.amazonaws.com/)', '[Earth Viewer by Element 84](https://viewer.aws.element84.com/)'] True -Sentinel-2 S3 Inventory files for L1C and CSV arn:aws:s3:::sentinel-inventory/sentinel-s2-l1c eu-central-1 S3 Bucket Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac -Sentinel-2 Level 2A scenes and metadata, in Requester Pays S3 bucket arn:aws:s3:::sentinel-s2-l2a eu-central-1 S3 Bucket Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac ['[STAC V1.0.0 endpoint](https://sentinel-s2-l2a-stac.s3.amazonaws.com/)'] True Sentinel-2 Zipped archives for each L2A product with 3 day retention period, in Requester P arn:aws:s3:::sentinel-s2-l2a-zips eu-central-1 S3 Bucket Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac True Sentinel-2 Zipped archives for each L1C product with 3 day retention period, in Requester P arn:aws:s3:::sentinel-s2-l1c-zips eu-central-1 S3 Bucket Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac True -Sentinel-2 Cloud-Optimized GeoTIFFs Level 2A scenes and metadata arn:aws:s3:::sentinel-cogs us-west-2 S3 Bucket https://github.com/cirrus-geo/cirrus-earth-search opendata@element84.com [Element 84](https://www.element84.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, cog, stac ['[Earth Search STAC L2A Collection](https://earth-search.aws.element84.com/v1/collections/sentinel-2-l2a)', '[STAC Browser L2A Collection](https://radiantearth.github.io/stac-browser/#/external/earth-search.aws.element84.com/v1/collections/sentinel-2-l2a)'] False +Sentinel-2 S3 Inventory files for L2A and CSV arn:aws:s3:::sentinel-inventory/sentinel-s2-l2a eu-central-1 S3 Bucket Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac +Sentinel-2 Level 2A scenes and metadata, in Requester Pays S3 bucket arn:aws:s3:::sentinel-s2-l2a eu-central-1 S3 Bucket Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac ['[STAC V1.0.0 endpoint](https://sentinel-s2-l2a-stac.s3.amazonaws.com/)'] True +Sentinel-2 S3 Inventory files for L1C and CSV arn:aws:s3:::sentinel-inventory/sentinel-s2-l1c eu-central-1 S3 Bucket Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac +Sentinel-2 Level 1C scenes and metadata, in Requester Pays S3 bucket arn:aws:s3:::sentinel-s2-l1c eu-central-1 S3 Bucket Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac ['[Earth Search STAC L1C Collection](https://earth-search.aws.element84.com/v1/collections/sentinel-2-l1c)', '[Earth Search STAC Browser L1C Collection](https://radiantearth.github.io/stac-browser/#/external/earth-search.aws.element84.com/v1/collections/sentinel-2-l1c)', '[STAC V1.0.0 endpoint](https://sentinel-s2-l1c-stac.s3.amazonaws.com/)', '[Earth Viewer by Element 84](https://viewer.aws.element84.com/)'] True +Sentinel-2 New scene notifications for L2A, can subscribe with Lambda arn:aws:sns:eu-central-1:214830741341:SentinelS2L2A eu-central-1 SNS Topic Documentation is available for [Sentinel-2 L1C](https://roda.sentinel-hub.com/se https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac Sentinel-2 Cloud-Optimized GeoTIFFs S3 Inventory files for L1C and CSV arn:aws:s3:::sentinel-cogs-inventory us-west-2 S3 Bucket https://github.com/cirrus-geo/cirrus-earth-search opendata@element84.com [Element 84](https://www.element84.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, cog, stac Sentinel-2 Cloud-Optimized GeoTIFFs New scene notifications, can subscribe with Lambda arn:aws:sns:us-west-2:608149789419:cirrus-v0-publish us-west-2 SNS Topic https://github.com/cirrus-geo/cirrus-earth-search opendata@element84.com [Element 84](https://www.element84.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, cog, stac +Sentinel-2 Cloud-Optimized GeoTIFFs Level 2A scenes and metadata arn:aws:s3:::sentinel-cogs us-west-2 S3 Bucket https://github.com/cirrus-geo/cirrus-earth-search opendata@element84.com [Element 84](https://www.element84.com/) New Sentinel data are added regularly, usually within few hours after they are a Access to Sentinel data is free, full and open for the broad Regional, National, aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, cog, stac ['[Earth Search STAC L2A Collection](https://earth-search.aws.element84.com/v1/collections/sentinel-2-l2a)', '[STAC Browser L2A Collection](https://radiantearth.github.io/stac-browser/#/external/earth-search.aws.element84.com/v1/collections/sentinel-2-l2a)'] False Sentinel-2 L2A 120m Mosaic Sentinel-2 L2A 120m mosaics data in a S3 bucket arn:aws:s3:::sentinel-s2-l2a-mosaic-120 eu-central-1 S3 Bucket Documentation is available [here](https://sentinel-s2-l2a-mosaic-120.s3.amazonaw https://forum.sentinel-hub.com/c/aws-sentinel [Sinergise](https://www.sinergise.com/) New data will be added annually. CC-BY 4.0, Credit: Contains modified Copernicus data [year] processed by Sentine aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, machine learning, cog False Sentinel-3 Sentinel-3 Cloud Optimized GeoTIFF (COG) format arn:aws:s3:::meeo-s3-cog/ eu-central-1 S3 Bucket https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel3Descri sentinel3@meeo.it [Meteorological Environmental Earth Observation](http://www.meeo.it/) Daily https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice aws-pds, oceans, earth observation, environmental, geospatial, land, satellite imagery, cog, stac ['[STAC V1.0.0 endpoint](https://meeo-s3.s3.amazonaws.com/)'] Sentinel-3 Sentinel-3 Short Time Critical (STC) format arn:aws:s3:::meeo-s3/STC/ eu-central-1 S3 Bucket https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel3Descri sentinel3@meeo.it [Meteorological Environmental Earth Observation](http://www.meeo.it/) Daily https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice aws-pds, oceans, earth observation, environmental, geospatial, land, satellite imagery, cog, stac -Sentinel-3 Sentinel-3 Near Real Time Data (NRT) format arn:aws:s3:::meeo-s3/NRT/ eu-central-1 S3 Bucket https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel3Descri sentinel3@meeo.it [Meteorological Environmental Earth Observation](http://www.meeo.it/) Daily https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice aws-pds, oceans, earth observation, environmental, geospatial, land, satellite imagery, cog, stac Sentinel-3 Sentinel-3 Not Time Critical (NTC) format arn:aws:s3:::meeo-s3/NTC/ eu-central-1 S3 Bucket https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel3Descri sentinel3@meeo.it [Meteorological Environmental Earth Observation](http://www.meeo.it/) Daily https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice aws-pds, oceans, earth observation, environmental, geospatial, land, satellite imagery, cog, stac +Sentinel-3 Sentinel-3 Near Real Time Data (NRT) format arn:aws:s3:::meeo-s3/NRT/ eu-central-1 S3 Bucket https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel3Descri sentinel3@meeo.it [Meteorological Environmental Earth Observation](http://www.meeo.it/) Daily https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice aws-pds, oceans, earth observation, environmental, geospatial, land, satellite imagery, cog, stac +Sentinel-5P Level 2 Sentinel-5p Reprocessed Data (RPRO) NetCDF format arn:aws:s3:::meeo-s5p/RPRO/ eu-central-1 S3 Bucket https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel5P_Desc sentinel5p@meeo.it [Meteorological Environmental Earth Observation](http://www.meeo.it/) Daily https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice aws-pds, air quality, atmosphere, earth observation, environmental, geospatial, satellite imagery, cog, stac Sentinel-5P Level 2 Sentinel-5p Cloud Optimised GeoTIFF (COGT) TIFF format arn:aws:s3:::meeo-s5p/COGT/ eu-central-1 S3 Bucket https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel5P_Desc sentinel5p@meeo.it [Meteorological Environmental Earth Observation](http://www.meeo.it/) Daily https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice aws-pds, air quality, atmosphere, earth observation, environmental, geospatial, satellite imagery, cog, stac ['[STAC V1.0.0 endpoint](https://meeo-s5p.s3.amazonaws.com/index.html?t=catalogs)'] -Sentinel-5P Level 2 Sentinel-5p Near Real Time Data (NRTI) NetCDF format arn:aws:s3:::meeo-s5p/NRTI/ eu-central-1 S3 Bucket https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel5P_Desc sentinel5p@meeo.it [Meteorological Environmental Earth Observation](http://www.meeo.it/) Daily https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice aws-pds, air quality, atmosphere, earth observation, environmental, geospatial, satellite imagery, cog, stac Sentinel-5P Level 2 Sentinel-5p Off Line Data (OFFL) NetCDF format arn:aws:s3:::meeo-s5p/OFFL/ eu-central-1 S3 Bucket https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel5P_Desc sentinel5p@meeo.it [Meteorological Environmental Earth Observation](http://www.meeo.it/) Daily https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice aws-pds, air quality, atmosphere, earth observation, environmental, geospatial, satellite imagery, cog, stac -Sentinel-5P Level 2 Sentinel-5p Reprocessed Data (RPRO) NetCDF format arn:aws:s3:::meeo-s5p/RPRO/ eu-central-1 S3 Bucket https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel5P_Desc sentinel5p@meeo.it [Meteorological Environmental Earth Observation](http://www.meeo.it/) Daily https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice aws-pds, air quality, atmosphere, earth observation, environmental, geospatial, satellite imagery, cog, stac +Sentinel-5P Level 2 Sentinel-5p Near Real Time Data (NRTI) NetCDF format arn:aws:s3:::meeo-s5p/NRTI/ eu-central-1 S3 Bucket https://github.com/Sentinel-5P/data-on-s3/blob/master/DocsForAws/Sentinel5P_Desc sentinel5p@meeo.it [Meteorological Environmental Earth Observation](http://www.meeo.it/) Daily https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice aws-pds, air quality, atmosphere, earth observation, environmental, geospatial, satellite imagery, cog, stac Serratus: Ultra-deep Search for Novel Viruses - Versioned Data Release Versioned and structured data releases from the Serratus project Current versio arn:aws:s3:::lovelywater2 us-east-1 S3 Bucket https://github.com/ababaian/serratus/wiki/Access-Data-Release https://github.com/ababaian/serratus/issues Serratus / UBC Cloud Innovation Centre Quarterly [CC-0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) aws-pds, life sciences, genetic, genomic, bam, virus, COVID-19, SARS, SARS-CoV-2, MERS Ships of Opportunity - Biogeochemical sensors - Delayed mode Cloud Optimised AODN dataset of IMOS - SOOP Underway CO2 Measurements Research G arn:aws:s3:::aodn-cloud-optimised/vessel_co2_delayed_qc.parquet ap-southeast-2 S3 Bucket https://catalogue-imos.aodn.org.au/geonetwork/srv/eng/catalog.search#/metadata/6 info@aodn.org.au AODN As Needed http://creativecommons.org/licenses/by/4.0/ oceans, chemistry Ships of Opportunity - Expendable bathythermographs - Real time Cloud Optimised AODN dataset of IMOS - SOOP Expendable Bathythermographs (XBT) R arn:aws:s3:::aodn-cloud-optimised/vessel_xbt_realtime_nonqc.parquet ap-southeast-2 S3 Bucket https://catalogue-imos.aodn.org.au/geonetwork/srv/eng/catalog.search#/metadata/3 info@aodn.org.au AODN As Needed http://creativecommons.org/licenses/by/4.0/ oceans @@ -1086,10 +1087,10 @@ Speedtest by Ookla Global Fixed and Mobile Network Performance Maps Parquet and Spitzer Enhanced Imaging Products (SEIP) Super Mosaics SEIP Super Mosaics: 36, 45, 58, 8, and 24 micron mean and median mosaics with arn:aws:s3:::nasa-irsa-spitzer/spitzer/seip us-west-2 S3 Bucket https://irsa.ipac.caltech.edu/data/SPITZER/Enhanced/SEIP/overview.html https://irsa.ipac.caltech.edu/docs/help_desk.html NASA/IPAC Infrared Science Archive ([IRSA](https://irsa.ipac.caltech.edu)) at Ca This data set may be updated once or twice in the future. https://irsa.ipac.caltech.edu/data_use_terms.html aws-pds, astronomy, imaging, satellite imagery, survey False False Storm EVent ImageRy (SEVIR) Dataset of storm imagery arn:aws:s3:::sevir us-west-2 S3 Bucket https://nbviewer.jupyter.org/github/MIT-AI-Accelerator/eie-sevir/blob/master/exa mark.veillette@mit.edu Mark S. Veillette New events will be added to SEVIR yearly There are no restrictions on the use of this data. satellite imagery, weather, meteorological, aws-pds Sub-Meter Canopy Tree Height of California in 2020 by CTrees.org Cloud-optimized GeoTIFF files with names corresponding to image of California fo arn:aws:s3:::ctrees-tree-height-ca-2020/ us-west-2 S3 Bucket [Project overview](https://ctrees.org/products/tree-level) info@ctrees.org [CTrees](https://ctrees.org/) TBD https://creativecommons.org/licenses/by/4.0/ aws-pds, cog, earth observation, land cover, deep learning, aerial imagery, image processing, environmental, conservation, geospatial -Sudachi Language Resources SudachiDict: Binary format of the mophological analysis dictionarieschiVe: Pret arn:aws:s3:::sudachi ap-northeast-1 S3 Bucket https://worksapplications.github.io/Sudachi/ sudachi@worksap.co.jp [Works Applications](https://www.worksap.co.jp/about/csr/nlp/) The dictionaries are updated every few months to include neologism and fixes for Apache-2.0 aws-pds, natural language processing Sudachi Language Resources Cloudfront CDN mirror ap-northeast-1 CloudFront Distribution https://worksapplications.github.io/Sudachi/ sudachi@worksap.co.jp [Works Applications](https://www.worksap.co.jp/about/csr/nlp/) The dictionaries are updated every few months to include neologism and fixes for Apache-2.0 aws-pds, natural language processing d2ej7fkh96fzlu.cloudfront.net -Sup3rCC Sup3rCC Generative Models arn:aws:s3:::nrel-pds-sup3rcc/models/ us-west-2 S3 Bucket https://github.com/NREL/sup3r Grant Buster (grant.buster@nrel.gov) [National Renewable Energy Laboratory](https://www.nrel.gov/) Annual Creative Commons Attribution 4.0 United States License aws-pds, energy, solar, air temperature, climate model ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-sup3rcc&prefix=models%2F)'] +Sudachi Language Resources SudachiDict: Binary format of the mophological analysis dictionarieschiVe: Pret arn:aws:s3:::sudachi ap-northeast-1 S3 Bucket https://worksapplications.github.io/Sudachi/ sudachi@worksap.co.jp [Works Applications](https://www.worksap.co.jp/about/csr/nlp/) The dictionaries are updated every few months to include neologism and fixes for Apache-2.0 aws-pds, natural language processing Sup3rCC Sup3rCC arn:aws:s3:::nrel-pds-sup3rcc/ us-west-2 S3 Bucket https://github.com/NREL/sup3r Grant Buster (grant.buster@nrel.gov) [National Renewable Energy Laboratory](https://www.nrel.gov/) Annual Creative Commons Attribution 4.0 United States License aws-pds, energy, solar, air temperature, climate model ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-sup3rcc)'] +Sup3rCC Sup3rCC Generative Models arn:aws:s3:::nrel-pds-sup3rcc/models/ us-west-2 S3 Bucket https://github.com/NREL/sup3r Grant Buster (grant.buster@nrel.gov) [National Renewable Energy Laboratory](https://www.nrel.gov/) Annual Creative Commons Attribution 4.0 United States License aws-pds, energy, solar, air temperature, climate model ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-sup3rcc&prefix=models%2F)'] Sup3rCC Sup3rCC - CONUS - MRI ESM 20 - SSP585 - r1i1p1f1 arn:aws:s3:::nrel-pds-sup3rcc/conus_mriesm20_ssp585_r1i1p1f1/ us-west-2 S3 Bucket https://github.com/NREL/sup3r Grant Buster (grant.buster@nrel.gov) [National Renewable Energy Laboratory](https://www.nrel.gov/) Annual Creative Commons Attribution 4.0 United States License aws-pds, energy, solar, air temperature, climate model ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-sup3rcc&prefix=conus_mriesm20_ssp585_r1i1p1f1%2F)'] Swiss Public Transport Stops data files ESRI FGDB, CSV , MapInfo, Interlis arn:aws:s3:::data.geo.admin.ch/ch.bav.haltestellen-oev/data.zip eu-west-1 S3 Bucket https://www.bav.admin.ch/bav/de/home/allgemeine-themen/fachthemen/geoinformation fredi.daellenbach@bav.admin.ch Swiss Geoportal annually You may use this dataset for non-commercial purposes. You may use this dataset f aws-pds, cities, geospatial, infrastructure, mapping, traffic, transportation ['[Browse Bucket](https://data.geo.admin.ch/index.html)'] Synthea Coherent Data Set Synthetic data set that includes FHIR resources, DICOM images, genomic data, phy arn:aws:s3:::synthea-open-data/coherent/ us-east-1 S3 Bucket https://doi.org/10.3390/electronics11081199 synthea-list@groups.mitre.org [The MITRE Corporation](https://www.mitre.org) Rarely [Creative Commons Attribution 4.0 International License](https://creativecommons aws-pds, health, bioinformatics, life sciences, medicine, csv, dicom, genomic, imaging @@ -1100,8 +1101,8 @@ Tabula Muris https://githubcom/czbiohub/tabula-muris arn:aws:s3:::czb-tabula-mur Tabula Muris Senis https://githubcom/czbiohub/tabula-muris-senis arn:aws:s3:::czb-tabula-muris-senis us-west-2 S3 Bucket https://github.com/czbiohub/tabula-muris-senis/blob/master/tabula-muris-senis-on If you have questions about the data, you can create an Issue at https://github. [Chan Zuckerberg Biohub](https://www.czbiohub.org/) This is the first version of the dataset and it will be updated after the manusc https://github.com/czbiohub/tabula-muris-senis/blob/master/LICENSE aws-pds, biology, encyclopedic, genomic, health, life sciences, medicine, single-cell transcriptomics Tabula Sapiens http://tabula-sapiens-portaldsczbiohuborg arn:aws:s3:::czb-tabula-sapiens us-west-2 S3 Bucket http://tabula-sapiens-portal.ds.czbiohub.org/ https://github.com/czbiohub/tabula-muris-senis/issues [Chan Zuckerberg Biohub](https://www.czbiohub.org/) This is the first version of the dataset and it will be updated once per month u http://tabula-sapiens-portal.ds.czbiohub.org/whereisthedata aws-pds, biology, encyclopedic, genetic, genomic, health, life sciences, medicine, single-cell transcriptomics https://docs.google.com/forms/d/e/1FAIpQLSeeB0N7TrklXbCbpc6nDi5e77uad3uZDZ4WCMV77jwhVzxUtQ/viewform Terra Fusion Data Sampler AWS S3 Public Bucket Containing Terra Basic Fusion Hierarchical Data Format 5 (H arn:aws:s3:::terrafusiondatasampler us-west-2 S3 Bucket https://go.illinois.edu/terra-fusion-doc gdi@illinois.edu University of Illinois Static, with a planned update for years 2016-2020 in the future. Creative Commons Level 0 aws-pds, geospatial, satellite imagery -Terrain Tiles Gridded elevation tiles - replication in EU region arn:aws:s3:::elevation-tiles-prod-eu eu-central-1 S3 Bucket https://github.com/tilezen/joerd/tree/master/docs https://github.com/tilezen/joerd/issues Mapzen, a Linux Foundation project New data is added based on community feedback https://github.com/tilezen/joerd/blob/master/docs/attribution.md aws-pds, agriculture, elevation, earth observation, geospatial, disaster response Terrain Tiles Gridded elevation tiles arn:aws:s3:::elevation-tiles-prod us-east-1 S3 Bucket https://github.com/tilezen/joerd/tree/master/docs https://github.com/tilezen/joerd/issues Mapzen, a Linux Foundation project New data is added based on community feedback https://github.com/tilezen/joerd/blob/master/docs/attribution.md aws-pds, agriculture, elevation, earth observation, geospatial, disaster response ['[Browse Map](https://elevation-tiles-prod.s3.amazonaws.com/index.html)'] +Terrain Tiles Gridded elevation tiles - replication in EU region arn:aws:s3:::elevation-tiles-prod-eu eu-central-1 S3 Bucket https://github.com/tilezen/joerd/tree/master/docs https://github.com/tilezen/joerd/issues Mapzen, a Linux Foundation project New data is added based on community feedback https://github.com/tilezen/joerd/blob/master/docs/attribution.md aws-pds, agriculture, elevation, earth observation, geospatial, disaster response Textbook Question Answering (TQA) Project data files in a public bucket arn:aws:s3:::ai2-public-datasets us-west-2 S3 Bucket https://allenai.org/data/tqa info@allenai.org [Allen Institute for AI](https://allenai.org) Not updated [CC BY-SA](https://creativecommons.org/licenses/by-sa/4.0/) aws-pds, machine learning The Cancer Genome Atlas WXS/RNA-Seq/miRNA-Seq/ATAC-Seq Aligned Reads, WXS Annotated Somatic Mutation, WX arn:aws:s3:::tcga-2-controlled us-east-1 S3 Bucket https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/t dcf-support@datacommons.io [Center for Translational Data Science at The University of Chicago](https://ctd Genomic Data Commons (GDC) is source of truth for this dataset; GDC offers month NIH Genomic Data Sharing Policy: https://gdc.cancer.gov/access-data/data-access- aws-pds, life sciences, cancer, genomic, whole genome sequencing, STRIDES https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000178.v1.p1 The Cancer Genome Atlas Clinical Supplement, Biospecimen Supplement, RNA-Seq Gene Expression Quantificat arn:aws:s3:::tcga-2-open us-east-1 S3 Bucket https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/t dcf-support@datacommons.io [Center for Translational Data Science at The University of Chicago](https://ctd Genomic Data Commons (GDC) is source of truth for this dataset; GDC offers month NIH Genomic Data Sharing Policy: https://gdc.cancer.gov/access-data/data-access- aws-pds, life sciences, cancer, genomic, whole genome sequencing, STRIDES @@ -1117,8 +1118,8 @@ The Singapore Nanopore Expression Data Set Nanopore long read RNA Seq data and m The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset Zip archive containing NifTI files arn:aws:s3:::ucsf-dmi/UCSF_BrainMetastases_v1.zip us-west-1 S3 Bucket https://imagingdatasets.ucsf.edu/dataset/1 dmi-support@ucsf.edu [UCSF Center for Intelligent Imaging](https://intelligentimaging.ucsf.edu/) ad hoc Custom, non-commerical, attribution, no redistribution, no re-identification. F aws-pds, cancer, life sciences, magnetic resonance imaging, medicine, medical imaging, radiology https://imagingdatasets.ucsf.edu/dataset/1 Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Clinical Supplement, Biospecimen Supplement, RNA-Seq Gene Expression Quantificat arn:aws:s3:::gdc-target-phs000218-2-open us-east-1 S3 Bucket https://ocg.cancer.gov/programs/target/ dcf-support@datacommons.io [Center for Translational Data Science at The University of Chicago](https://ctd Genomic Data Commons (GDC) is source of truth for this dataset; GDC offers month NIH Genomic Data Sharing Policy: https://gdc.cancer.gov/access-data/data-access- aws-pds, cancer, genomic, life sciences, whole genome sequencing, STRIDES Toxicant Exposures and Responses by Genomic and Epigenomic Regulators of Transcription (TaRGET) Released and archived TaRGET II data arn:aws:s3:::targetepigenomics us-west-2 S3 Bucket https://data.targetepigenomics.org/ targetdcc16@gmail.com TaRGET II Data Coordination Center (TaRGET-DCC) TaRGET-DCC offers monthly data releases, although this dataset may not be update External data users may freely download, analyze, and publish results based on a biology, bioinformatics, genetic, genomic, life sciences, environmental, epigenomics, aws-pds -Transiting Exoplanet Survey Satellite (TESS) Notifications for new data arn:aws:sns:us-east-1:879230861493:stpubdata us-east-1 SNS Topic https://archive.stsci.edu/missions-and-data/tess archive@stsci.edu [Space Telescope Science Institute](http://www.stsci.edu/) Monthly STScI hereby grants the non-exclusive, royalty free, non-transferable, worldwide astronomy, aws-pds Transiting Exoplanet Survey Satellite (TESS) TESS Mission data files arn:aws:s3:::stpubdata/tess us-east-1 S3 Bucket https://archive.stsci.edu/missions-and-data/tess archive@stsci.edu [Space Telescope Science Institute](http://www.stsci.edu/) Monthly STScI hereby grants the non-exclusive, royalty free, non-transferable, worldwide astronomy, aws-pds False +Transiting Exoplanet Survey Satellite (TESS) Notifications for new data arn:aws:sns:us-east-1:879230861493:stpubdata us-east-1 SNS Topic https://archive.stsci.edu/missions-and-data/tess archive@stsci.edu [Space Telescope Science Institute](http://www.stsci.edu/) Monthly STScI hereby grants the non-exclusive, royalty free, non-transferable, worldwide astronomy, aws-pds Tropical Cyclone Precipitation, Infrared, Microwave, and Environmental Dataset (TC PRIMED) The Tropical Cyclone Precipitation, Infrared, Microwave and Environmental Datase arn:aws:s3:::noaa-nesdis-tcprimed-pds us-east-1 S3 Bucket https://rammb-data.cira.colostate.edu/tcprimed/TCPRIMED_v01r00_documentation.pdf CIRA_tcprimed [at] colostate [dot] edu [CIRA](https://www.cira.colostate.edu/) Annually, several months after the conclusion of the Northern Hemisphere tropica No constraints on data access or use atmosphere, aws-pds, earth observation, environmental, geophysics, geoscience, global, meteorological, model, netcdf, precipitation, satellite imagery, weather ['[Browse Bucket](https://noaa-nesdis-tcprimed-pds.s3.amazonaws.com/index.html)'] U.S. Census ACS PUMS PUMS data in Turtle - Terse RDF Triple Language (ttl) format along with ontolog arn:aws:s3:::dataworld-linked-acs us-east-1 S3 Bucket https://docs.data.world/uscensus/#american-community-survey-linked-open-data https://docs.data.world/uscensus/#60---contact Data.world Yearly, after ACS 1-year PUMS raw data are released [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecom aws-pds, statistics, census, survey UCSC Genome Browser Sequence and Annotations https://genomeucscedu/FAQ/FAQformathtml arn:aws:s3:::genome-browser us-east-1 S3 Bucket https://hgdownload.soe.ucsc.edu/downloads.html https://genome.ucsc.edu/contacts.html University of California Santa Cruz Genome Institute Monthly [Public domain, some tracks require attribution](https://genome.ucsc.edu/license aws-pds, genetic, genomic, life sciences, bioinformatics, biology @@ -1129,22 +1130,23 @@ USGS 3DEP LiDAR Point Clouds Public access Entwine Point Tiles of most resources USGS 3DEP LiDAR Point Clouds A Requester Pays Bucket of Raw LAZ 14 3DEP data Data in this bucket is more co arn:aws:s3:::usgs-lidar us-west-2 S3 Bucket https://github.com/hobu/usgs-lidar/ https://github.com/hobu/usgs-lidar [Hobu, Inc.](https://hobu.co) Periodically US Government Public Domain https://www.usgs.gov/faqs/what-are-terms-uselicensin aws-pds, agriculture, elevation, disaster response, geospatial, lidar, stac True USGS COAWST (Coupled Ocean Atmosphere Wave and Sediment Transport) Forecast Model Archive, US East and Gulf Coasts A collection of NetCDF4 files, kerchunk generated JSON files, and an Intake cata arn:aws:s3:::usgs-coawst us-west-2 S3 Bucket https://www.sciencebase.gov/catalog/item/610acd4fd34ef8d7056893da jbzambon@fathomscience.com Fathom Science None CC0 aws-pds, oceans USGS Landsat New scene notifications, US ARD Tiles arn:aws:sns:us-west-2:673253540267:public-c2-ard-tile-notify-v2 us-west-2 SNS Topic https://www.usgs.gov/core-science-systems/nli/landsat/landsat-commercial-cloud-d https://answers.usgs.gov/ [United States Geological Survey](https://www.usgs.gov) New scenes are added daily. There are no restrictions on Landsat data downloaded from the USGS; it can be us aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac, cog -USGS Landsat New scene notifications, Level 3 Science Products arn:aws:sns:us-west-2:673253540267:public-c2-level-3-tile-notify-v2 us-west-2 SNS Topic https://www.usgs.gov/core-science-systems/nli/landsat/landsat-commercial-cloud-d https://answers.usgs.gov/ [United States Geological Survey](https://www.usgs.gov) New scenes are added daily. There are no restrictions on Landsat data downloaded from the USGS; it can be us aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac, cog USGS Landsat New scene notifications, Level-1 and Level-2 Scenes arn:aws:sns:us-west-2:673253540267:public-c2-notify-v2 us-west-2 SNS Topic https://www.usgs.gov/core-science-systems/nli/landsat/landsat-commercial-cloud-d https://answers.usgs.gov/ [United States Geological Survey](https://www.usgs.gov) New scenes are added daily. There are no restrictions on Landsat data downloaded from the USGS; it can be us aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac, cog USGS Landsat Scenes and metadata arn:aws:s3:::usgs-landsat/collection02/ us-west-2 S3 Bucket https://www.usgs.gov/core-science-systems/nli/landsat/landsat-commercial-cloud-d https://answers.usgs.gov/ [United States Geological Survey](https://www.usgs.gov) New scenes are added daily. There are no restrictions on Landsat data downloaded from the USGS; it can be us aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac, cog ['[STAC Catalog](https://landsatlook.usgs.gov/stac-server/collections)'] True +USGS Landsat New scene notifications, Level 3 Science Products arn:aws:sns:us-west-2:673253540267:public-c2-level-3-tile-notify-v2 us-west-2 SNS Topic https://www.usgs.gov/core-science-systems/nli/landsat/landsat-commercial-cloud-d https://answers.usgs.gov/ [United States Geological Survey](https://www.usgs.gov) New scenes are added daily. There are no restrictions on Landsat data downloaded from the USGS; it can be us aws-pds, agriculture, earth observation, satellite imagery, geospatial, natural resource, disaster response, stac, cog USearch Molecules Project data files in a public bucket arn:aws:s3:::usearch-molecules us-west-2 S3 Bucket https://github.com/ashvardanian/usearch-molecules ash.vardanian@unum.cloud [Ash Vardanian](https://ashvardanian.com) Not updated [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0) aws-pds, life sciences, biology, chemical biology, pharmaceutical Umbra Synthetic Aperture Radar (SAR) Open Data Umbra Spotlight collects including GEC, SICD, SIDD, CPHD data and metadata arn:aws:s3:::umbra-open-data-catalog us-west-2 S3 Bucket https://help.umbra.space/product-guide help@umbra.space [Umbra](http://umbra.space/) New data is added frequently. The frequent updates enable users to analyze the t All data is provided with a Creative Commons License ([CC by 4.0](https://umbra. aws-pds, synthetic aperture radar, stac, satellite imagery, earth observation, image processing, geospatial ['[Browse Bucket](http://umbra-open-data-catalog.s3-website.us-west-2.amazonaws.com/)', '[STAC Browser](https://radiantearth.github.io/stac-browser/#/external/s3.us-west-2.amazonaws.com/umbra-open-data-catalog/stac/catalog.json)'] False Unblurred Coadds of the Wide-field Infrared Survey Explorer (unWISE) The unWISE Time-Domain Catalog is based on 'time-resolved' coadds, each of which arn:aws:s3:::nasa-irsa-wise/unwise/ us-west-2 S3 Bucket https://irsa.ipac.caltech.edu/data/WISE/unWISE/overview.html https://irsa.ipac.caltech.edu/docs/help_desk.html NASA/IPAC Infrared Science Archive ([IRSA](https://irsa.ipac.caltech.edu)) at Ca The unWISE dataset is updated periodically to include new data released by NEOWI https://irsa.ipac.caltech.edu/data_use_terms.html aws-pds, astronomy, object detection, parquet, survey False False +UniProt UniProt 2022_03 arn:aws:s3:::aws-open-data-uniprot-rdf/2022-03/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL +UniProt UniProt 2022_02 arn:aws:s3:::aws-open-data-uniprot-rdf/2022-02/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL +UniProt UniProt 2022_01 arn:aws:s3:::aws-open-data-uniprot-rdf/2022-01/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL +UniProt UniProt 2021_01 arn:aws:s3:::aws-open-data-uniprot-rdf/2021-01/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL UniProt UniProt 2021_02 arn:aws:s3:::aws-open-data-uniprot-rdf/2021-02/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL -UniProt UniProt 2021_03 arn:aws:s3:::aws-open-data-uniprot-rdf/2021-03/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL +UniProt UniProt 2022_04 arn:aws:s3:::aws-open-data-uniprot-rdf/2022-04/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL UniProt UniProt 2021_04 arn:aws:s3:::aws-open-data-uniprot-rdf/2021-04/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL -UniProt UniProt 2022_01 arn:aws:s3:::aws-open-data-uniprot-rdf/2022-01/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL -UniProt UniProt 2022_02 arn:aws:s3:::aws-open-data-uniprot-rdf/2022-02/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL -UniProt UniProt 2022_03 arn:aws:s3:::aws-open-data-uniprot-rdf/2022-03/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL UniProt UniProt 2022_05 arn:aws:s3:::aws-open-data-uniprot-rdf/2022-05/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL -UniProt UniProt 2022_04 arn:aws:s3:::aws-open-data-uniprot-rdf/2022-04/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL +UniProt UniProt 2021_03 arn:aws:s3:::aws-open-data-uniprot-rdf/2021-03/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL UniProt UniProt 2023_02 arn:aws:s3:::aws-open-data-uniprot-rdf/2023-02/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL -UniProt UniProt 2021_01 arn:aws:s3:::aws-open-data-uniprot-rdf/2021-01/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL +UniProt UniProt 2023_03 arn:aws:s3:::aws-open-data-uniprot-rdf/2023-03/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL UniProt UniProt 2023_04 arn:aws:s3:::aws-open-data-uniprot-rdf/2023-04/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL UniProt UniProt 2023_05 arn:aws:s3:::aws-open-data-uniprot-rdf/2023-05/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL UniProt UniProt 2024_01 arn:aws:s3:::aws-open-data-uniprot-rdf/2024-01/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL @@ -1152,14 +1154,13 @@ UniProt UniProt 2024_02 arn:aws:s3:::aws-open-data-uniprot-rdf/2024-02/ eu-west- UniProt UniProt 2024_03 arn:aws:s3:::aws-open-data-uniprot-rdf/2024-03/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL UniProt UniProt 2024_05 arn:aws:s3:::aws-open-data-uniprot-rdf/2024-05/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL UniProt UniProt 2023_01 arn:aws:s3:::aws-open-data-uniprot-rdf/2023-01/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL -UniProt UniProt 2023_03 arn:aws:s3:::aws-open-data-uniprot-rdf/2023-03/ eu-west-3 S3 Bucket https://www.uniprot.org/help/about https://www.uniprot.org/contact [SIB Swiss Institute of Bioinformatics](https://sp.sib.swiss/) on behalf of the Under 1 months after a new UniProt release. http://creativecommons.org/licenses/by/4.0/ aws-pds, chemistry, protein, enzyme, molecule, life sciences, bioinformatics, biology, RDF, graph, SPARQL University of British Columbia Sunflower Genome Dataset UBC Sunflower Genome Data 1 arn:aws:s3:::ubc-sunflower-genome us-west-2 S3 Bucket https://rieseberglab.github.io/ubc-sunflower-genome/ UBC Botany Sunflower The Rieseberg Lab at the University of British Columbia Twice per year. Public Domain aws-pds, agriculture, biodiversity, bioinformatics, biology, food security, genetic, genomic, life sciences, whole genome sequencing VENUS L2A Cloud-Optimized GeoTIFFs New Venus L2A dataset notifications, can subscribe with Lambda arn:aws:sns:us-east-1:794383284256:venus-l2a-cogs-object_created us-east-1 SNS Topic https://github.com/earthdaily/venus-on-aws/ Klaus Bachhuber - klaus.bachhuber@earthdaily.com [EarthDaily Analytics](https://earthdaily.com/) New Venus data are added regularly https://creativecommons.org/licenses/by-nc/4.0/ aws-pds, agriculture, earth observation, satellite imagery, geospatial, image processing, natural resource, disaster response, cog, stac, activity detection, environmental, land cover VENUS L2A Cloud-Optimized GeoTIFFs Venus L2A dataset (COG) and metadata (STAC) arn:aws:s3:::venus-l2a-cogs us-east-1 S3 Bucket https://github.com/earthdaily/venus-on-aws/ Klaus Bachhuber - klaus.bachhuber@earthdaily.com [EarthDaily Analytics](https://earthdaily.com/) New Venus data are added regularly https://creativecommons.org/licenses/by-nc/4.0/ aws-pds, agriculture, earth observation, satellite imagery, geospatial, image processing, natural resource, disaster response, cog, stac, activity detection, environmental, land cover ['[STAC Browser Venus L2A (COG) Catalog](https://radiantearth.github.io/stac-browser/#/external/venus-l2a-cogs.s3.us-east-1.amazonaws.com/catalog.json)'] False Variant Effect Predictor (VEP) and the Loss-Of-Function Transcript Effect Estimator (LOFTEE) Plugin VEP and LOFTEE data arn:aws:s3:::hail-vep-pipeline us-east-1 S3 Bucket https://hail-vep-pipeline.public.tennex.io/ https://www.tennex.io/contact [Tennex](https://www.tennex.io/) New packages are added as soon as they are available and confirmed to work with [VEP](https://uswest.ensembl.org/info/about/publications.html) use is governed b aws-pds, genome wide association study, genomic, life sciences, vep, loftee -Vermont Open Geospatial on AWS Imagery datsets are organized in this bucket as statewide file mosaics and by ac arn:aws:s3:::vtopendata-prd/Imagery us-east-2 S3 Bucket https://vcgi.vermont.gov/data-and-programs/ If you have specific questions please contact - vcgi@vermont.gov [Vermont Center for Geographic Information](https://vcgi.vermont.gov) Vermont acquires statewide imagery approximately once every other year. Lidar is Public Domain with Attribution earth observation, aerial imagery, geospatial, lidar, elevation, land cover False -Vermont Open Geospatial on AWS Landcover datsets are organized in this bucket as statewide file mosaics These arn:aws:s3:::vtopendata-prd/Landcover us-east-2 S3 Bucket https://vcgi.vermont.gov/data-and-programs/ If you have specific questions please contact - vcgi@vermont.gov [Vermont Center for Geographic Information](https://vcgi.vermont.gov) Vermont acquires statewide imagery approximately once every other year. Lidar is Public Domain with Attribution earth observation, aerial imagery, geospatial, lidar, elevation, land cover False Vermont Open Geospatial on AWS Elevation datsets (primarily lidar based) are organized in this bucket as statew arn:aws:s3:::vtopendata-prd/Elevation us-east-2 S3 Bucket https://vcgi.vermont.gov/data-and-programs/ If you have specific questions please contact - vcgi@vermont.gov [Vermont Center for Geographic Information](https://vcgi.vermont.gov) Vermont acquires statewide imagery approximately once every other year. Lidar is Public Domain with Attribution earth observation, aerial imagery, geospatial, lidar, elevation, land cover False +Vermont Open Geospatial on AWS Landcover datsets are organized in this bucket as statewide file mosaics These arn:aws:s3:::vtopendata-prd/Landcover us-east-2 S3 Bucket https://vcgi.vermont.gov/data-and-programs/ If you have specific questions please contact - vcgi@vermont.gov [Vermont Center for Geographic Information](https://vcgi.vermont.gov) Vermont acquires statewide imagery approximately once every other year. Lidar is Public Domain with Attribution earth observation, aerial imagery, geospatial, lidar, elevation, land cover False +Vermont Open Geospatial on AWS Imagery datsets are organized in this bucket as statewide file mosaics and by ac arn:aws:s3:::vtopendata-prd/Imagery us-east-2 S3 Bucket https://vcgi.vermont.gov/data-and-programs/ If you have specific questions please contact - vcgi@vermont.gov [Vermont Center for Geographic Information](https://vcgi.vermont.gov) Vermont acquires statewide imagery approximately once every other year. Lidar is Public Domain with Attribution earth observation, aerial imagery, geospatial, lidar, elevation, land cover False Virginia Coastal Resilience Master Plan, Phase 1 - December 2021 Data Product List See readmetxt file for more information on the folder struc arn:aws:s3:::vadcr-frp us-east-1 S3 Bucket https://www.dcr.virginia.gov/crmp/ flood.resilience@dcr.virginia.gov [Virginia Department of Conservation and Recreation](https://www.dcr.virginia.go Every 5 years or as data becomes available Conditions of Release - Data is available by permission of the Virginia Departme aws-pds, coastal, floods ['[Browse Data](https://vadcr-frp.s3.us-east-1.amazonaws.com/index.html)'] Virtual Shizuoka, 3D Point Cloud Data Point Cloud Data of Shizuoka Prefecture, Japan arn:aws:s3:::virtual-shizuoka ap-northeast-1 S3 Bucket https://github.com/aigidjp/opendata_virtualshizuoka/README.md virtualshizuoka@aigid.jp [AIGID](https://aigid.jp/) Currently not scheduled Creative Commons Attribution 4.0 International (CC-BY 4.0) and Open Data Commons aws-pds, bathymetry, disaster response, elevation, geospatial, japanese, land, lidar, mapping VirtualFlow Ligand Libraries VirtualFlow Version of the Enamine REAL Space Molecule Library (version 2022q12) arn:aws:s3:::vf-libraries us-east-2 S3 Bucket https://virtual-flow.org/real-space-2022q12 c.gorgulla@gmail.com [VirtualFlow Project](https://virtual-flow.org/) Every ~3 years There are no restrictions on the use of this data. Redistribution is not allowed aws-pds, structural biology, pharmaceutical, medicine, bioinformatics, life sciences ['[Browse Bucket](https://vf-libraries.s3.amazonaws.com/index.html)'] @@ -1171,32 +1172,32 @@ WIS2 Global Cache on AWS Core data as defined in the WMO Unified Data Policy (Re Whiffle WINS50 Open Data on AWS Whiffle WINS50 LES Data arn:aws:s3:::whiffle-wins50-data eu-central-1 S3 Bucket https://gitlab.com/whiffle-public/whiffle-open-data support@whiffle.nl [Whiffle](http://www.whiffle.nl/) No updates planned. CC BY-SA 4.0 aws-pds, weather, sustainability, atmosphere, electricity, meteorological, model, zarr, turbulence ['[Browse Bucket](https://whiffle-wins50-data.s3.amazonaws.com/index.html)'] WikiSum: Coherent Summarization Dataset for Efficient Human-Evaluation WikiSum Dataset arn:aws:s3:::wikisum us-east-1 S3 Bucket https://wikisum.s3.amazonaws.com/README.txt nachshon@amazon.com, orenk@amazon.com [Amazon](https://www.amazon.com/) Not currently being updated Dataset is published under [CC-NC-SA-3.0](https://creativecommons.org/licenses/b amazon.science, natural language processing, machine learning ['[wikisum.zip](https://wikisum.s3.amazonaws.com/WikiSumDataset.zip)', '[wikisum-human-eval.zip](https://wikisum.s3.amazonaws.com/HumanEvaluation.zip)'] Will Two Do? Varying Dimensions in Electrocardiography: The PhysioNet/Computing in Cardiology Challenge 2021 https://doiorg/1013026/34va-7q14 arn:aws:s3:::physionet-open/challenge-2021/ us-east-1 S3 Bucket https://doi.org/10.13026/34va-7q14 https://physionet.org/about/#contact_us [PhysioNet](https://physionet.org/) Not updated Creative Commons Attribution 4.0 International Public License aws-pds -Wind AI Bench Wind AI Bench Airfoil Computational Fluid Dynamics (CFD) - 2k Shapes Data Sets arn:aws:s3:::nrel-pds-windai/aerodynamic_shapes/2D/2K_airfoils/ us-west-2 S3 Bucket https://github.com/NREL/windAI_bench Ryan King (ryan.king@nrel.gov) [National Renewable Energy Laboratory](https://www.nrel.gov/) Annually Creative Commons Attribution 4.0 United States License aws-pds, energy, benchmark, machine learning ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-windai&prefix=aerodynamic_shapes%2F2D%2F2k_airfoils%2F)'] -Wind AI Bench Wind AI Bench Flow Redirection and Induction in Steady State (FLORIS) Wind Plant arn:aws:s3:::nrel-pds-windai/wind_plant_power/floris/ us-west-2 S3 Bucket https://github.com/NREL/windAI_bench Ryan King (ryan.king@nrel.gov) [National Renewable Energy Laboratory](https://www.nrel.gov/) Annually Creative Commons Attribution 4.0 United States License aws-pds, energy, benchmark, machine learning ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-windai&prefix=wind_plant_power%2Ffloris%2F)'] Wind AI Bench Wind AI Bench Airfoil Computational Fluid Dynamics (CFD) - 9k Shapes Data Sets arn:aws:s3:::nrel-pds-windai/aerodynamic_shapes/2D/9K_airfoils/ us-west-2 S3 Bucket https://github.com/NREL/windAI_bench Ryan King (ryan.king@nrel.gov) [National Renewable Energy Laboratory](https://www.nrel.gov/) Annually Creative Commons Attribution 4.0 United States License aws-pds, energy, benchmark, machine learning ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-windai&prefix=aerodynamic_shapes%2F2D%2F9k_airfoils%2F)'] +Wind AI Bench Wind AI Bench Flow Redirection and Induction in Steady State (FLORIS) Wind Plant arn:aws:s3:::nrel-pds-windai/wind_plant_power/floris/ us-west-2 S3 Bucket https://github.com/NREL/windAI_bench Ryan King (ryan.king@nrel.gov) [National Renewable Energy Laboratory](https://www.nrel.gov/) Annually Creative Commons Attribution 4.0 United States License aws-pds, energy, benchmark, machine learning ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-windai&prefix=wind_plant_power%2Ffloris%2F)'] +Wind AI Bench Wind AI Bench Airfoil Computational Fluid Dynamics (CFD) - 2k Shapes Data Sets arn:aws:s3:::nrel-pds-windai/aerodynamic_shapes/2D/2K_airfoils/ us-west-2 S3 Bucket https://github.com/NREL/windAI_bench Ryan King (ryan.king@nrel.gov) [National Renewable Energy Laboratory](https://www.nrel.gov/) Annually Creative Commons Attribution 4.0 United States License aws-pds, energy, benchmark, machine learning ['[Browse Dataset](https://data.openei.org/s3_viewer?bucket=nrel-pds-windai&prefix=aerodynamic_shapes%2F2D%2F2k_airfoils%2F)'] Wizard of Tasks Wizard of Tasks Dataset arn:aws:s3:::wizard-of-tasks us-west-2 S3 Bucket https://wizard-of-tasks.s3.us-west-2.amazonaws.com/README.md giusecas@amazon.com [Amazon](https://www.amazon.com/) Not currently being updated [cc-by-sa 4.0](https://creativecommons.org/licenses/by-sa/4.0/) conversation data, dialog, amazon.science, natural language processing, machine learning ['[wizard_of_tasks_cooking_v1.0.json](https://wizard-of-tasks.s3.us-west-2.amazonaws.com/wizard_of_tasks_cooking_v1.0.json)', '[wizard_of_tasks_diy_v1.0.json](https://wizard-of-tasks.s3.us-west-2.amazonaws.com/wizard_of_tasks_diy_v1.0.json)'] World Bank - Light Every Night Light Every Night dataset of all VIIRS DNB and DMSP-OLS nighttime satellite data arn:aws:s3:::globalnightlight us-east-1 S3 Bucket https://worldbank.github.io/OpenNightLights/wb-light-every-night-readme.html Trevor Monroe tmonroe@worldbank.org; Benjamin P. Stewart bstewart@worldbankgroup [World Bank Group](https://www.worldbank.org/en/home) Quarterly [World Bank Open Database License (ODbL)](https://creativecommons.org/licenses/b disaster response, earth observation, satellite imagery, aws-pds, stac, cog ['[STAC 1.0.0-beta.2 endpoint](https://stacindex.org/catalogs/world-bank-light-every-night#/)'] World Bank Climate Change Knowledge Portal (CCKP) World Bank Climate Change Knowledge Portal observed and projected climate datase arn:aws:s3:::wbg-cckp us-west-2 S3 Bucket https://worldbank.github.io/climateknowledgeportal C. MacKenzie Dove cdove@worldbank.org; askclimate@worldbank.org [World Bank Group](https://www.worldbank.org/en/home) Semi-annually [World Bank Open Database License (ODbL)](https://creativecommons.org/licenses/b aws-pds, climate, climate model, earth observation, climate projections, CMIP6, netcdf Xiph.Org Test Media Video and imagery data arn:aws:s3:::xiph-media us-east-1 S3 Bucket https://media.xiph.org/aws.html Thomas Daede tdaede@xiph.org [Xiph.org](https://xiph.org/) New videos are added when contributors submit them. Various. Most are under the CC-BY license. License text accompanies each sequenc aws-pds, computer vision, image processing, imaging, media, movies, multimedia, video Yale-CMU-Berkeley (YCB) Object and Model Set Project data files arn:aws:s3:::ycb-benchmarks us-east-1 S3 Bucket http://www.ycbbenchmarks.com/ bcalli@wpi.edu Yale University and Berkeley Yearly Creative Commons Attribution 4.0 International (CC BY 4.0) aws-pds, robotics ['[Browse Bucket](https://ycb-benchmarks.s3.amazonaws.com/index.html)'] -YouTube 8 Million - Data Lakehouse Ready Replica of the two locations above in us-east-1 arn:aws:s3:::aws-roda-ml-datalake-us-east-1/ us-east-1 S3 Bucket https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/docs/roda_install. https://github.com/aws-samples/data-lake-as-code/issues [Amazon Web Services](https://aws.amazon.com/) Google Research has not updated the dataset since 2019. https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/docs/roda_attribut amazon.science, computer vision, machine learning, labeled, parquet, video YouTube 8 Million - Data Lakehouse Ready Lakehouse ready YT8M as Glue Parquet files Install instructions here arn:aws:s3:::aws-roda-ml-datalake/yt8m_ods/ us-west-2 S3 Bucket https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/docs/roda_install. https://github.com/aws-samples/data-lake-as-code/issues [Amazon Web Services](https://aws.amazon.com/) Google Research has not updated the dataset since 2019. https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/docs/roda_attribut amazon.science, computer vision, machine learning, labeled, parquet, video YouTube 8 Million - Data Lakehouse Ready Original YT8M *tfrecords File structure info can be found here arn:aws:s3:::aws-roda-ml-datalake/yt8m/ us-west-2 S3 Bucket https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/docs/roda_install. https://github.com/aws-samples/data-lake-as-code/issues [Amazon Web Services](https://aws.amazon.com/) Google Research has not updated the dataset since 2019. https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/docs/roda_attribut amazon.science, computer vision, machine learning, labeled, parquet, video +YouTube 8 Million - Data Lakehouse Ready Replica of the two locations above in us-east-1 arn:aws:s3:::aws-roda-ml-datalake-us-east-1/ us-east-1 S3 Bucket https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/docs/roda_install. https://github.com/aws-samples/data-lake-as-code/issues [Amazon Web Services](https://aws.amazon.com/) Google Research has not updated the dataset since 2019. https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/docs/roda_attribut amazon.science, computer vision, machine learning, labeled, parquet, video ZEST: ZEroShot learning from Task descriptions Project data files in a public bucket arn:aws:s3:::ai2-public-datasets/zest/ us-west-2 S3 Bucket https://allenai.org/data/zest info@allenai.org [Allen Institute for AI](https://allenai.org) Not updated [CC BY](https://creativecommons.org/licenses/by/4.0) aws-pds, machine learning, natural language processing ZINC Database 3D molecular docking structure files in db2gz, sdf and mol2 formats arn:aws:s3:::zinc3d us-east-1 S3 Bucket http://wiki.docking.org/index.php/ZINC15:Resources [John Irwin](chemistry4biology@gmail.com) [John Irwin](chemistry4biology@gmail.com) Monthly ZINC is free as in beer. You may not redistribute without the written permission aws-pds, life sciences, biology, chemical biology, pharmaceutical, molecular docking, protein -iHART Whole Genome Sequencing Data Set BAM, gVCF, and VCF files from The iHART whole genome sequencing study, Phase I arn:aws:s3:::ihart-release us-east-1 S3 Bucket http://www.ihart.org/data ihart2-org@stanford.edu [Stanford University](https://wall-lab.stanford.edu/projects/ihart/) The dataset may be updated with additional or corrected data on a need-to-update Data use is subject to the access and publication polices of the iHART. More inf aws-pds, autism spectrum disorder, genetic, genomic, life sciences, whole genome sequencing, bam, vcf http://www.ihart.org/access -iHART Whole Genome Sequencing Data Set BAM, gVCF, and VCF files from The iHART whole genome sequencing study, Phase II arn:aws:s3:::ihart-main us-east-1 S3 Bucket http://www.ihart.org/data ihart2-org@stanford.edu [Stanford University](https://wall-lab.stanford.edu/projects/ihart/) The dataset may be updated with additional or corrected data on a need-to-update Data use is subject to the access and publication polices of the iHART. More inf aws-pds, autism spectrum disorder, genetic, genomic, life sciences, whole genome sequencing, bam, vcf http://www.ihart.org/access -iHART Whole Genome Sequencing Data Set Cram, gVCF, and VCF files from The iHART whole genome sequencing study, Phase I+ arn:aws:s3:::ihart-hg38 us-east-1 S3 Bucket http://www.ihart.org/data ihart2-org@stanford.edu [Stanford University](https://wall-lab.stanford.edu/projects/ihart/) The dataset may be updated with additional or corrected data on a need-to-update Data use is subject to the access and publication polices of the iHART. More inf aws-pds, autism spectrum disorder, genetic, genomic, life sciences, whole genome sequencing, bam, vcf http://www.ihart.org/access iHART Whole Genome Sequencing Data Set gVCF and VCF files from The iHART whole genome sequencing study, control data se arn:aws:s3:::ihart-brain us-east-1 S3 Bucket http://www.ihart.org/data ihart2-org@stanford.edu [Stanford University](https://wall-lab.stanford.edu/projects/ihart/) The dataset may be updated with additional or corrected data on a need-to-update Data use is subject to the access and publication polices of the iHART. More inf aws-pds, autism spectrum disorder, genetic, genomic, life sciences, whole genome sequencing, bam, vcf http://www.ihart.org/access +iHART Whole Genome Sequencing Data Set Cram, gVCF, and VCF files from The iHART whole genome sequencing study, Phase I+ arn:aws:s3:::ihart-hg38 us-east-1 S3 Bucket http://www.ihart.org/data ihart2-org@stanford.edu [Stanford University](https://wall-lab.stanford.edu/projects/ihart/) The dataset may be updated with additional or corrected data on a need-to-update Data use is subject to the access and publication polices of the iHART. More inf aws-pds, autism spectrum disorder, genetic, genomic, life sciences, whole genome sequencing, bam, vcf http://www.ihart.org/access +iHART Whole Genome Sequencing Data Set BAM, gVCF, and VCF files from The iHART whole genome sequencing study, Phase II arn:aws:s3:::ihart-main us-east-1 S3 Bucket http://www.ihart.org/data ihart2-org@stanford.edu [Stanford University](https://wall-lab.stanford.edu/projects/ihart/) The dataset may be updated with additional or corrected data on a need-to-update Data use is subject to the access and publication polices of the iHART. More inf aws-pds, autism spectrum disorder, genetic, genomic, life sciences, whole genome sequencing, bam, vcf http://www.ihart.org/access +iHART Whole Genome Sequencing Data Set BAM, gVCF, and VCF files from The iHART whole genome sequencing study, Phase I arn:aws:s3:::ihart-release us-east-1 S3 Bucket http://www.ihart.org/data ihart2-org@stanford.edu [Stanford University](https://wall-lab.stanford.edu/projects/ihart/) The dataset may be updated with additional or corrected data on a need-to-update Data use is subject to the access and publication polices of the iHART. More inf aws-pds, autism spectrum disorder, genetic, genomic, life sciences, whole genome sequencing, bam, vcf http://www.ihart.org/access iHART Whole Genome Sequencing Data Set gVCF and VCF files from The iHART whole genome sequencing study, control data se arn:aws:s3:::ihart-psp us-east-1 S3 Bucket http://www.ihart.org/data ihart2-org@stanford.edu [Stanford University](https://wall-lab.stanford.edu/projects/ihart/) The dataset may be updated with additional or corrected data on a need-to-update Data use is subject to the access and publication polices of the iHART. More inf aws-pds, autism spectrum disorder, genetic, genomic, life sciences, whole genome sequencing, bam, vcf http://www.ihart.org/access iNaturalist Licensed Observation Images Image files (eg JPEG) associated with metadata describing the observation asso arn:aws:s3:::inaturalist-open-data us-east-1 S3 Bucket "Documentation can be found
This data set includes satellite-based observations of calibrated, geo-located antenna temperature and brightness temperatures, along with the sensor telemetry used to derive those values. Brightness temperatures are derived from the microwave band frequencies 18.7 GHz, 23.8 GHz, and 34.5 GHz. This product is best suited for a cal/val user or sensor expert. These level 1c measurements make up the temperature sensor data record (TSDR) from the COWVR (Compact Ocean Wind Vector Radiometer) sensor aboard the international space station (ISS), starting in January 2022 forward-streaming to PO.DAAC till the planned mission end in December 2024. Its swath width is 1012 km and spatial resolution is <35 km. Data files in HDF5 format are available at roughly hourly frequency (the ISS orbit period is ~90 minutes), although note that the coverage shown in the thumbnail is for a full day. Files include calibration and flag data in addition to brightness temperatures. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbers of the project team prior to release

The COWVR sensor is a fully polarimetric, conically imaging microwave radiometer for measuring ocean surface wind vectors. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. It was deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission. A successful COWVR mission will demonstrate a lower-cost sensor architecture (e.g. in comparison to WindSat) for providing imaging passive microwave data, including ocean surface vector wind products for the Department of Defense (DoD). COWVR was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping.", + "description": "This data set includes satellite-based observations of calibrated, geo-located antenna temperature and brightness temperatures, along with the sensor telemetry used to derive those values. Brightness temperatures are derived from the microwave band frequencies 18.7 GHz, 23.8 GHz, and 34.5 GHz. This product is best suited for a cal/val user or sensor expert. These level 1c measurements make up the temperature sensor data record (TSDR) from the COWVR (Compact Ocean Wind Vector Radiometer) sensor aboard the international space station (ISS), starting in January 2022 forward-streaming to PO.DAAC till the planned mission end in December 2024. Its swath width is 1012 km and spatial resolution is <35 km. Data files in HDF5 format are available at roughly hourly frequency (the ISS orbit period is ~90 minutes), although note that the coverage shown in the thumbnail is for a full day. Files include calibration and flag data in addition to brightness temperatures. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbers of the project team prior to release

The COWVR sensor is a fully polarimetric, conically imaging microwave radiometer for measuring ocean surface wind vectors. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. It was deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission. A successful COWVR mission will demonstrate a lower-cost sensor architecture (e.g. in comparison to WindSat) for providing imaging passive microwave data, including ocean surface vector wind products for the Department of Defense (DoD). COWVR was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping.", "license": "proprietary" }, { @@ -56416,7 +56416,7 @@ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3237678855-POCLOUD.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3237678855-POCLOUD.html", "href": "https://cmr.earthdata.nasa.gov/stac/POCLOUD/collections/COWVR_STPH8_L2_EDR_V10.0_10.0", - "description": "!!!Temporary notice posted Sept. 27th, 2024!!! These data are in the process of being ingested and not all files are available yet. The data were made public early to allow assessment by early science users. Accordingly, not all data set resources may be available yet. Please check over the next 2-3 weeks for finalization of this data set and PO.DAAC's release announcement.

This dataset includes satellite-based observations of geolocated surface wind vectors, precipitable water vapor, and integrated cloud liquid water, as well as the microwave brightness temperatures used to derive them. Theses measurements make up the environmental data record (EDR) from the COWVR (Compact Ocean Wind Vector Radiometer) sensor aboard the international space station (ISS), beginning in January 2022 with forward-streaming to PO.DAAC. Data over the satellite swath are available in HDF5 format with roughly one file per hour (the ISS orbit period is ~90 minutes), and coverage shown in the thumbnail is for a full day. The file metadata formats may be different than what an average user is familiar with \u2013 please see the User Guide to learn more. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbering of the project team prior to release.

The COWVR sensor is a fully polarimetric, conically imaging microwave radiometer for measuring ocean surface wind vectors. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. It was deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission. A successful COWVR mission will demonstrate a lower-cost sensor architecture (e.g. in comparison to WindSat) for providing imaging passive microwave data, including ocean surface vector wind products for the Department of Defense (DoD). COWVR was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping.", + "description": "This dataset includes satellite-based observations of geolocated surface wind vectors, precipitable water vapor, and integrated cloud liquid water, as well as the microwave brightness temperatures used to derive them. Theses measurements make up the environmental data record (EDR) from the COWVR (Compact Ocean Wind Vector Radiometer) sensor aboard the international space station (ISS), beginning in January 2022 with forward-streaming to PO.DAAC. Data over the satellite swath are available in HDF5 format with roughly one file per hour (the ISS orbit period is ~90 minutes), and coverage shown in the thumbnail is for a full day. Spatial resolution is roughly 35 km. The file metadata formats may be different than what an average user is familiar with \u2013 please see the User Guide to learn more. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbering of the project team prior to release.

The COWVR sensor is a fully polarimetric, conically imaging microwave radiometer for measuring ocean surface wind vectors. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. It was deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission. A successful COWVR mission will demonstrate a lower-cost sensor architecture (e.g. in comparison to WindSat) for providing imaging passive microwave data, including ocean surface vector wind products for the Department of Defense (DoD). COWVR was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping.", "license": "proprietary" }, { @@ -79978,52 +79978,52 @@ { "id": "GLAH01_033", "title": "GLAS/ICESat L1A Global Altimetry Data (HDF5) V033", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000400-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000400-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH01_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547306-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547306-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH01_033", "description": "Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter. 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Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH02_033", "title": "GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH02_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH02_033", "description": "GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH02_033", "title": "GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH02_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH02_033", "description": "GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). 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Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH09_033", "title": "GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH09_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991869-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991869-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH09_033", "description": "GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH09_033", "title": "GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991869-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991869-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH09_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH09_033", "description": "GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH10_033", "title": "GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-09-25", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH10_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH10_033", "description": "GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH10_033", "title": "GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-09-25", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH10_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH10_033", "description": "GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product.", "license": "proprietary" }, @@ -80287,19 +80287,6 @@ "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", "license": "proprietary" }, - { - "id": "GLAH13_034", - "title": "GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034", - "catalog": "NSIDC_CPRD STAC Catalog", - "state_date": "2003-02-20", - "end_date": "2009-10-11", - "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH13_034", - "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", - "license": "proprietary" - }, { "id": "GLAH13_034", "title": "GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034", @@ -80314,15 +80301,15 @@ "license": "proprietary" }, { - "id": "GLAH14_034", - "title": "GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034", + "id": "GLAH13_034", + "title": "GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034", "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH14_034", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH13_034", "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", "license": "proprietary" }, @@ -80340,15 +80327,15 @@ "license": "proprietary" }, { - "id": "GLAH15_034", - "title": "GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034", - "catalog": "NSIDC_ECS STAC Catalog", + "id": "GLAH14_034", + "title": "GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH15_034", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH14_034", "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", "license": "proprietary" }, @@ -80365,6 +80352,19 @@ "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", "license": "proprietary" }, + { + "id": "GLAH15_034", + "title": "GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034", + "catalog": "NSIDC_ECS STAC Catalog", + "state_date": "2003-02-20", + "end_date": "2009-10-11", + "bbox": "-180, -86, 180, 86", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH15_034", + "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", + "license": "proprietary" + }, { "id": "GLCHMK_001", "title": "G-LiHT Canopy Height Model KML V001", @@ -85539,6 +85539,32 @@ "description": "These data are the Goddard Satellite-based Surface Turbulent Fluxes Version 3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. This HDF-EOS5 dataset is part of the MEaSUREs project. This is a Daily product; data are projected to equidistant Grid that covers the globe at 0.25x0.25 degree cell size, resulting in data arrays of 1440x720 size. Data gap: Daily GSSTF_NCEP files are missing for October 21-22,26-28, in 1990. The input data sets used for this recent GSSTF production include the upgraded and improved datasets such as the Special Sensor Microwave Imager (SSM/I) Version-6 (V6) product of brightness temperature [Tb], total precipitable water [W], and wind speed [U] produced by the Wentz of Remote Sensing Systems (RSS), as well as the NCEP/DOE Reanalysis-2 (R2) product of sea skin temperature [SKT], 2-meter air temperature [Tair], and sea level pressure [SLP]. The short name for this product is GSSTF_NCEP. ", "license": "proprietary" }, + { + "id": "GVHRRATS6IMIR_001", + "title": "GVHRR/ATS-6 Black and White Infrared Images on Film V001 (GVHRRATS6IMIR) at GES DISC", + "catalog": "GES_DISC STAC Catalog", + "state_date": "1974-06-07", + "end_date": "1974-08-15", + "bbox": "175, -90, -5, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3275628922-GES_DISC.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3275628922-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/GVHRRATS6IMIR_001", + "description": "GVHRRATS6IMIR is the Geosynchronous Very High Resolution Radiometer (GVHRR) Black and White Infrared Images on 70mm Film data product from the sixth Applications Technology Satellite (ATS-6). This set of IR imagery (10.5 to 12.5 micrometer, with an 11 km footprint at the sub-satellite point) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title at the bottom of the image and a gray scale on the right boundary that represents brightness temperatures. The title contains the satellite identification, receiving station, spectral band, picture number, picture type, pixel scale, sector number, and date. The ATS-6 satellite was in a geosynchronous orbit parked at 95W viewing the hemisphere below the satellite. The GVHRR experiment returned data from launch until August 15, 1974 when it became inoperable, The PI was William E. Shenk from NASA Goddard Space Flight Center. This product was previously available from the NSSDC with the identifier ESAD-00092 (old ID 74-039A-08B).", + "license": "proprietary" + }, + { + "id": "GVHRRATS6IMVIS_001", + "title": "GVHRR/ATS-6 Black and White Visible Images on Film V001 (GVHRRATS6IMVIS) at GES DISC", + "catalog": "GES_DISC STAC Catalog", + "state_date": "1974-06-07", + "end_date": "1974-08-15", + "bbox": "175, -90, -5, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3275628923-GES_DISC.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3275628923-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/GVHRRATS6IMVIS_001", + "description": "GVHRRATS6IMVIS is the Geosynchronous Very High Resolution Radiometer (GVHRR) Black and White Visible Images on Film data product from the sixth Applications Technology Satellite (ATS-6). This set of visible imagery (0.55 to 0.75 micrometer, with a 5.5 km footprint at the sub-satellite point) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title at the bottom of the image and a gray scale on the right boundary that represents brightness temperatures. The title contains the satellite identification, receiving station, spectral band, picture number, picture type, pixel scale, sector number, and date. The ATS-6 satellite was in a geosynchronous orbit parked at 95W viewing the hemisphere below the satellite. The GVHRR experiment returned data from launch until August 15, 1974 when it became inoperable, The PI was William E. Shenk from NASA Goddard Space Flight Center. This product was previously available from the NSSDC with the identifier ESAD-00047 (old ID 74-039A-08A).", + "license": "proprietary" + }, { "id": "GVdem_2008_3", "title": "A bathymetric Digital Elevation Model (DEM) of the George V and Terre Adelie continental shelf and margin", @@ -119404,6 +119430,71 @@ "description": "The Landsat-Derived Global Rainfed and Irrigated-Cropland Product (LGRIP) provides high resolution, global cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data (GFSAD) project, LGRIP maps the world\u2019s agricultural lands by dividing them into irrigated and rainfed croplands, and calculates irrigated and rainfed areas for every country in the world. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2014-2017 time period to create a nominal 2015 product. Each LGRIP 30 meter resolution GeoTIFF file contains a contains a layer that identifies areas of rainfed cropland (cropland areas that are purely dependent on direct precipitation), irrigated cropland (cropland that had at least one irrigation during the crop growing period), non-cropland, and water bodies over a 10\u00b0 by 10\u00b0 area, as well as an accuracy assessment of the product. A low-resolution browse image is also available. ", "license": "proprietary" }, + { + "id": "LGRIP30_L1_IRRI_002", + "title": "Landsat-Derived Global Irrigated-Cropland Product L1 2020 30 m V002", + "catalog": "LPCLOUD STAC Catalog", + "state_date": "2019-01-01", + "end_date": "2022-01-01", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3262829042-LPCLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3262829042-LPCLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPCLOUD/collections/LGRIP30_L1_IRRI_002", + "description": "The Landsat-Derived Global Irrigated-Cropland Product Level 1 2020 (LGRIP30_L1_IRRI) Version 2 data provides high-resolution, 30 meter (m) cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data ([GFSAD](https://www.usgs.gov/centers/western-geographic-science-center/science/global-food-security-support-analysis-data-30-m)) project, LGRIP_L1_IRRI V2 maps agricultural lands by dividing them into 32 irrigated cropland types and calculates applicable cropland areas across the globe. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2019 through 2021 time period to create a nominal 2020 product. Each LGRIP30 L1 V2 Irrigated 30 m resolution GeoTIFF file contains a layer that identifies areas of irrigated cropland (cropland that had at least one irrigation during the crop growing period) divided into 32 types, non-irrigated land (rainfed cropland and areas not classified as cropland), and water bodies over a 10\u00b0 by 10\u00b0 area, as well as an accuracy assessment of the product. A low-resolution browse image is also included. Currently, LGRIP30 V2 products contain data only for the conterminous United States (CONUS). LGRIP30 V2 data covering the rest of the globe will be added at a later date.", + "license": "proprietary" + }, + { + "id": "LGRIP30_L1_RAIN_002", + "title": "Landsat-Derived Global Rainfed-Cropland Product L1 2020 30 m V002", + "catalog": "LPCLOUD STAC Catalog", + "state_date": "2019-01-01", + "end_date": "2022-01-01", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3263421104-LPCLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3263421104-LPCLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPCLOUD/collections/LGRIP30_L1_RAIN_002", + "description": "The Landsat-Derived Global Rainfed-Cropland Product Level 1 2020 (LGRIP30_L1_RAIN) Version 2 data provides high-resolution, 30 meter (m) cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data ([GFSAD](https://www.usgs.gov/centers/western-geographic-science-center/science/global-food-security-support-analysis-data-30-m)) project, LGRIP30_L1_RAIN V2 maps agricultural lands by dividing them into 24 types of rainfed croplands and calculates applicable cropland areas across the globe. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2019 through 2021 time period to create a nominal 2020 product. Each LGRIP L1 Rainfed 30 m resolution GeoTIFF file contains a layer that identifies areas of rainfed cropland (cropland areas that are purely dependent on direct precipitation without any artificial watering) divided into 24 types, non-rainfed land (irrigated croplands and areas not classified as cropland), and water bodies over a 10\u00b0 by 10\u00b0 area, as well as an accuracy assessment of the product. A low-resolution browse image is also included. Currently, LGRIP30 V2 products only contain data for the conterminous United States (CONUS). LGRIP30 V2 data covering the rest of the globe will be added at a later date.", + "license": "proprietary" + }, + { + "id": "LGRIP30_L2_IRRI_002", + "title": "Landsat-Derived Global Irrigated-Cropland Product L2 2020 30 m V002", + "catalog": "LPCLOUD STAC Catalog", + "state_date": "2019-01-01", + "end_date": "2022-01-01", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3263429968-LPCLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3263429968-LPCLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPCLOUD/collections/LGRIP30_L2_IRRI_002", + "description": "The Landsat-Derived Global Irrigated-Cropland Product Level 2 2020 (LGRIP30_L2_IRRI) Version 2 data provides high-resolution, 30 meter (m) cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data ([GFSAD](https://www.usgs.gov/centers/western-geographic-science-center/science/global-food-security-support-analysis-data-30-m)) project, LGRIP_L2_IRRI V2 maps agricultural lands by dividing them into irrigated single crop, double crop, and continuous croplands, and calculates applicable cropland areas across the globe. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2019 through 2021 time period to create a nominal 2020 product. Each LGRIP L2 Irrigated 30 m resolution GeoTIFF file contains a layer that identifies areas of irrigated cropland (cropland that had at least one irrigation during the crop growing period) divided into single, double, and continuous crop classifications, non-irrigated land (rainfed cropland and areas not classified as cropland), and water bodies over a 10\u00b0 by 10\u00b0 area, as well as an accuracy assessment of the product. A low-resolution browse image is also included. Currently, LGRIP30 V2 products only contain data for the conterminous United States (CONUS). LGRIP30 V2 data covering the rest of the globe will be added at a later date.", + "license": "proprietary" + }, + { + "id": "LGRIP30_L2_RAIN_002", + "title": "Landsat-Derived Global Rainfed-Cropland Product L2 2020 30 m V002", + "catalog": "LPCLOUD STAC Catalog", + "state_date": "2019-01-01", + "end_date": "2022-01-01", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3263433662-LPCLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3263433662-LPCLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPCLOUD/collections/LGRIP30_L2_RAIN_002", + "description": "The Landsat-Derived Global Rainfed-Cropland Product Level 2 2020 (LGRIP30_L2_RAIN) Version 2 data provides high-resolution, 30 meter (m) cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data ([GFSAD](https://www.usgs.gov/centers/western-geographic-science-center/science/global-food-security-support-analysis-data-30-m)) project, LGRIP_L2_RAIN V2 maps agricultural lands by dividing them into rainfed single croplands and rainfed single croplands mixed with natural vegetation, and calculates applicable cropland areas across the globe. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2019 through 2021 time period to create a nominal 2020 product. Each LGRIP L2 Rainfed 30 m resolution GeoTIFF file contains a layer that identifies areas of rainfed cropland (cropland areas that are purely dependent on direct precipitation without any artificial watering) divided into single crop and single crop that is mixed with natural vegetation, non-rainfed land (irrigated croplands and areas not classified as cropland), and water bodies over a 10\u00b0 by 10\u00b0 area, as well as an accuracy assessment of the product. A low-resolution browse image is also included. Currently, LGRIP30 V2 products only contain data for the conterminous United States (CONUS). LGRIP30 V2 data covering the rest of the globe will be added at a later date.", + "license": "proprietary" + }, + { + "id": "LGRIP30_L3_002", + "title": "Landsat-derived Global Rainfed and Irrigated-Cropland Product L3 2020 30 m V002", + "catalog": "LPCLOUD STAC Catalog", + "state_date": "2019-01-01", + "end_date": "2022-01-01", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3262817664-LPCLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3262817664-LPCLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPCLOUD/collections/LGRIP30_L3_002", + "description": "The Landsat-derived Global Rainfed and Irrigated-Cropland Product Level 3 2020 (LGRIP30_L3) Version 2 data provides high-resolution, 30 meter (m) cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data ([GFSAD](https://www.usgs.gov/centers/western-geographic-science-center/science/global-food-security-support-analysis-data-30-m)) project, LGRIP L3 V2 maps agricultural croplands by dividing them into irrigated and rainfed croplands, and calculates irrigated and rainfed areas across the globe. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2019 through 2021 time period to create a nominal 2020 product. Each LGRIP30 L3 V2 30 m resolution GeoTIFF file contains a layer that identifies areas of rainfed cropland (cropland areas that are purely dependent on direct precipitation without any artificial watering), irrigated cropland (cropland that had at least one irrigation during the crop growing period), non-cropland, and water bodies over a 10\u00b0 by 10\u00b0 area, as well as an accuracy assessment of the product. A low-resolution browse image is also included. Currently, LGRIP30 V2 products only contain data for the conterminous United States (CONUS). LGRIP30 V2 data covering the rest of the globe will be added at a later date.", + "license": "proprietary" + }, { "id": "LIDA", "title": "Lidar Data from Brazil", @@ -147094,6 +147185,19 @@ "description": "This data set provides spatial distributions of fast ice and glacial ice in eight fjords spanning the Southeast Greenland coast: Nansen, Kangerlusruaq, Ikertivaq, Skjoldungen, Tingmiarmiut, Napasorsvaq, Anoritup, and Kangerlluluk. Temporal coverage is discontinuous, depending on the availability and quality of images. Fjord data were sourced from USGS EarthExplorer, Copernicus Open Access Hub, and the NSIDC. Landsat-8 and MODIS imagery for ice identification were collected from NASA Worldview and USGS EarthExplorer. Fjord, fast ice, and glacial ice boundaries were manually delineated using ArcGIS. Glacial ice was further categorized as dense glacial melange (Type 3), substantial glacial ice with large icebergs (Type 2), low-density glacial ice with large icebergs (Type 1), consistent small ice surface without large icebergs (Type 0), or glacier surface (Type 99).", "license": "proprietary" }, + { + "id": "NSIDC-0797_1", + "title": "SMAP/CYGNSS EASE-Grid Soil Moisture V001", + "catalog": "NSIDC_ECS STAC Catalog", + "state_date": "2017-04-01", + "end_date": "2023-12-31", + "bbox": "-180, -40, 180, 40", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3286281558-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3286281558-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/NSIDC-0797_1", + "description": "This data set is derived by downscaling Soil Moisture Active Passive (SMAP) enhanced Level-3 9 km brightness temperatures (TB) using Cyclone Global Navigation Satellite System (CYGNSS) reflectivity data and employing a slightly modified version of the baseline SMAP active-passive TB algorithm, the Single Channel Algorithm \u2013 Vertical polarization (SCA-V). The main parameter of this data set is surface soil moisture presented on the Global EASE-Grid 2.0 projection, with each data point representing the top 5 cm of the soil column. For SMAP-derived data, see SMAP Enhanced L3 Radiometer Global and Polar Grid Daily 9 km EASE-Grid Soil Moisture, Version 5; for CYGNSS-derived data, see CYGNSS Level 1, Version 2.1.", + "license": "proprietary" + }, { "id": "NURE_SEDIMENT_CHEM", "title": "National Uranium Resource Evaluation Program: Sediment Chemistry of the Conterminous United States", @@ -151475,6 +151579,19 @@ "description": "The OMPS-N21 L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit product contains the calibrated earth-viewing radiances measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the NOAA 21 (JPSS-2) satellite. The LP L1G product measures radiances in the wavelength region from 280 nm to 1000 nm. Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1-2 km. The data are written using the Hierarchical Data Format Version 5 or HDF5.", "license": "proprietary" }, + { + "id": "OMPS_N21_LP_L2_AER_DAILY_1.0", + "title": "OMPS-N21 L2 LP Aerosol Extinction Vertical Profile swath daily 3slit V2 (OMPS_N21_LP_L2_AER_DAILY) at GES DISC", + "catalog": "GES_DISC STAC Catalog", + "state_date": "2022-11-10", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3262950749-GES_DISC.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3262950749-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/OMPS_N21_LP_L2_AER_DAILY_1.0", + "description": "The OMPS-N21 L2 LP Aerosol Extinction Vertical Profile swath daily 3slit (AER) product contains the retrieved aerosol extinction coefficients measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the NOAA-21 satellite. The AER product measures stratospheric aerosol abundance and evolution at 6 wavelengths (510, 600, 675, 745, 869 and 997 nm) to complement the OMPS LP measurements of stratospheric and mesospheric profile ozone. This product replaces the previous single wavelength 675 nm (AER675) product. Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1.8 km. The files are written using the Hierarchical Data Format Version 5 or HDF5.", + "license": "proprietary" + }, { "id": "OMPS_N21_LP_L2_O3_DAILY_1.0", "title": "OMPS-N21 L2 LP Ozone (O3) Vertical Profile swath daily 3slit V1.0 (OMPS_N21_LP_L2_O3_DAILY) at GES DISC", @@ -151904,19 +152021,6 @@ "description": "The OMI science team produces this Level-3 daily global TOMS-Like Total Column Ozone gridded product OMTO3d (1 deg Lat/Lon grids). The OMTO3d product is produced by gridding and averaging only good quality level-2 total column ozone orbital swath data (OMTO3, based on the enhanced TOMS version-8 algorithm) on the 1x1 degree global grids. The OMTO3d files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3d data product is about 0.65 Mbytes.", "license": "proprietary" }, - { - "id": "OMTO3e_003", - "title": "OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT", - "catalog": "OMINRT STAC Catalog", - "state_date": "2004-07-15", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OMINRT/collections/OMTO3e_003", - "description": "The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. OMTO3e files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. (The shortname for this Level-3 TOMS-Like Total Column Ozone gridded product is OMTO3e) .", - "license": "proprietary" - }, { "id": "OMTO3e_003", "title": "OMI/Aura TOMS-Like Ozone and Radiative Cloud Fraction L3 1 day 0.25 degree x 0.25 degree V3 (OMTO3e) at GES DISC", @@ -151930,6 +152034,19 @@ "description": "The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. The OMTO3e files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes.", "license": "proprietary" }, + { + "id": "OMTO3e_003", + "title": "OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT", + "catalog": "OMINRT STAC Catalog", + "state_date": "2004-07-15", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OMINRT/collections/OMTO3e_003", + "description": "The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. OMTO3e files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. (The shortname for this Level-3 TOMS-Like Total Column Ozone gridded product is OMTO3e) .", + "license": "proprietary" + }, { "id": "OMUANC_004", "title": "Primary Ancillary Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km V4 (OMUANC) at GES DISC", @@ -173377,7 +173494,7 @@ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3237795822-POCLOUD.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3237795822-POCLOUD.html", "href": "https://cmr.earthdata.nasa.gov/stac/POCLOUD/collections/TEMPEST_STPH8_L1_TSDR_V10.0_10.0", - "description": "!!!Temporary notice posted Sept. 27th, 2024!!! These data are in the process of being ingested and not all files are available yet. The data were made public early to allow assessment by early science users. Accordingly, not all data set resources may be available yet. Please check over the next 2-3 weeks for finalization of this data set and PO.DAAC's release announcement.

This dataset includes satellite-based observations of calibrated, geo-located antenna temperature and brightness temperatures, along with the sensor telemetry used to derive those values. Brightness temperatures are derived from the microwave band frequencies 87, 164, 174, 178 and 181 GHz. This product is best suited for a cal/val user or sensor expert. These level 1c measurements make up the temperature sensor data record (TSDR) from the TEMPEST (Temporal Experiment for Storms and Tropical Systems) sensor aboard the international space station (ISS), starting in January 2022 forward-streaming to PO.DAAC till the planned mission end in December 2024. TEMPEST swath width is 1400 kilometers and resolution at nadir is 25 km for the 87 GHz channel and 13 km for the 180 GHz channels. Data files in HDF5 format are available at roughly hourly frequency (the ISS orbit period is ~90 minutes), although note that the coverage shown in the thumbnail is for a full day. Files include calibration and flag data in addition to brightness temperatures. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbering of the project team prior to release.

The TEMPEST instrument is a microwave radiometer deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission, with the primary objective of tropical cyclone intensity tracking. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. A successful mission will demonstrate a lower-cost, lighter-weight sensor architecture for providing microwave data. TEMPEST was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping.", + "description": "This dataset includes satellite-based observations of calibrated, geo-located antenna temperature and brightness temperatures, along with the sensor telemetry used to derive those values. Brightness temperatures are derived from the microwave band frequencies 87, 164, 174, 178 and 181 GHz. This product is best suited for a cal/val user or sensor expert. These level 1c measurements make up the temperature sensor data record (TSDR) from the TEMPEST (Temporal Experiment for Storms and Tropical Systems) sensor aboard the international space station (ISS), starting in January 2022 forward-streaming to PO.DAAC till the planned mission end in December 2024. TEMPEST swath width is 1400 kilometers and resolution at nadir is 25 km for the 87 GHz channel and 13 km for the 180 GHz channels. Data files in HDF5 format are available at roughly hourly frequency (the ISS orbit period is ~90 minutes), although note that the coverage shown in the thumbnail is for a full day. Files include calibration and flag data in addition to brightness temperatures. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbering of the project team prior to release.

The TEMPEST instrument is a microwave radiometer deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission, with the primary objective of tropical cyclone intensity tracking. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. A successful mission will demonstrate a lower-cost, lighter-weight sensor architecture for providing microwave data. TEMPEST was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping.", "license": "proprietary" }, { @@ -178646,16 +178763,16 @@ "license": "proprietary" }, { - "id": "TROPICS03MIRSL2B_0.2", - "title": "TROPICS03\u00a0L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V0.2", + "id": "TROPICS03MIRSL2B_1.0", + "title": "TROPICS03\u00a0L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V1.0", "catalog": "GES_DISC STAC Catalog", "state_date": "2021-07-19", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2857802936-GES_DISC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2857802936-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/TROPICS03MIRSL2B_0.2", - "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles.\u00a0See README for this and other calibration observations and the Data Product Users Guide for orbit details.", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3255751009-GES_DISC.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3255751009-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/TROPICS03MIRSL2B_1.0", + "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Validated Stage-1 release of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. ", "license": "proprietary" }, { @@ -178776,16 +178893,16 @@ "license": "proprietary" }, { - "id": "TROPICS06MIRSL2B_0.2", - "title": "TROPICS06\u00a0L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V0.2", + "id": "TROPICS06MIRSL2B_1.0", + "title": "TROPICS06\u00a0L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V1.0", "catalog": "GES_DISC STAC Catalog", "state_date": "2021-07-19", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2857801590-GES_DISC.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2857801590-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/TROPICS06MIRSL2B_0.2", - "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS06 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details.", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3255752538-GES_DISC.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3255752538-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/TROPICS06MIRSL2B_1.0", + "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS06 satellite, as the Validated Stage-1 release of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. ", "license": "proprietary" }, { diff --git a/nasa_cmr_catalog.tsv b/nasa_cmr_catalog.tsv index 8767d27..ab0f921 100644 --- a/nasa_cmr_catalog.tsv +++ b/nasa_cmr_catalog.tsv @@ -2421,13 +2421,13 @@ AST_L1B_003 ASTER L1B Registered Radiance at the Sensor V003 LPDAAC_ECS STAC Cat AST_L1T_003 ASTER Level 1 precision terrain corrected registered at-sensor radiance V003 LPDAAC_ECS STAC Catalog 2000-03-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000320-LPDAAC_ECS.umm_json The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level 1 Precision Terrain Corrected Registered At-Sensor Radiance (AST_L1T) data contains calibrated at-sensor radiance, which corresponds with the ASTER Level 1B (AST_L1B) (https://doi.org/10.5067/ASTER/AST_L1B.003), that has been geometrically corrected, and rotated to a north-up UTM projection. The AST_L1T is created from a single resampling of the corresponding ASTER L1A (AST_L1A) (https://doi.org/10.5067/ASTER/AST_L1A.003) product. The bands available in the AST_L1T depend on the bands in the AST_L1A and can include up to three Visible and Near Infrared (VNIR) bands, six Shortwave Infrared (SWIR) bands, and five Thermal Infrared (TIR) bands. The AST_L1T dataset does not include the aft-looking VNIR band 3. The precision terrain correction process incorporates GLS2000 digital elevation data with derived ground control points (GCPs) to achieve topographic accuracy for all daytime scenes where correlation statistics reach a minimum threshold. Alternate levels of correction are possible (systematic terrain, systematic, or precision) for scenes acquired at night or that otherwise represent a reduced quality ground image (e.g., cloud cover). For daytime images, if the VNIR or SWIR telescope collected data and precision correction was attempted, each precision terrain corrected image will have an accompanying independent quality assessment. It will include the geometric correction available for distribution in both as a text file and a single band browse images with the valid GCPs overlaid. This multi-file product also includes georeferenced full resolution browse images. The number of browse images and the band combinations of the images depends on the bands available in the corresponding (AST_L1A) (https://doi.org/10.5067/ASTER/AST_L1A.003) dataset. proprietary AST_L1T_031 ASTER Level 1 Precision Terrain Corrected Registered At-Sensor Radiance V031 LPDAAC_ECS STAC Catalog 2000-03-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2052604735-LPDAAC_ECS.umm_json The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level 1 Precision Terrain Corrected Registered At-Sensor Radiance (AST_L1T) Version 3.1 data contains calibrated at-sensor radiance, which corresponds with the ASTER Level 1B AST_L1B (https://doi.org/10.5067/ASTER/AST_L1B.003), that has been geometrically corrected and rotated to a north-up UTM projection. The AST_L1T V3.1 is created from a single resampling of the corresponding ASTER L1A AST_L1A (https://doi.org/10.5067/ASTER/AST_L1A.003) product. Radiometric calibration coefficients Version 5 (RCC V5) are applied to this product to improve the degradation curve derived from vicarious and lunar calibrations. The bands available in the AST_L1T V3.1 depend on the bands in the AST_L1A and can include up to three Visible and Near Infrared (VNIR) bands, six Shortwave Infrared (SWIR) bands, and five Thermal Infrared (TIR) bands. The AST_L1T V3.1 dataset does not include the aft-looking VNIR band 3. The 3.1 version uses a precision terrain correction process that incorporates GLS2000 digital elevation data with derived ground control points (GCPs) to achieve topographic accuracy for all daytime scenes where correlation statistics reach a minimum threshold. Alternate levels of correction are possible (systematic terrain, systematic, or precision) for scenes acquired at night or that otherwise represent a reduced quality ground image (e.g., cloud cover). For daytime images, if the VNIR or SWIR telescope collected data and precision correction was attempted, each precision terrain corrected image will have an accompanying independent quality assessment. It will include the geometric correction available for distribution in both a text file and a single band browse image with the valid GCPs overlaid. This multi-file product also includes georeferenced full resolution browse images. The number of browse images and the band combinations of the images depend on the bands available in the corresponding AST_L1A dataset. The AST_L1T V3.1 data product is only available through NASA’s Earthdata Search. The ASTER L1T V3.1 Order Instructions provide step-by-step directions for ordering this product. proprietary ATCS_0 The A-Train Cloud Segmentation Dataset OB_DAAC STAC Catalog 2007-11-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2172083412-OB_DAAC.umm_json ATCS is a dataset designed to train deep learning models to volumetrically segment clouds from multi-angle satellite imagery. The dataset consists of spatiotemporally aligned patches of multi-angle polarimetry from the POLDER sensor aboard the PARASOL mission and vertical cloud profiles from the 2B-CLDCLASS product using the cloud profiling radar (CPR) aboard CloudSat. proprietary -ATL02_006 ATLAS/ICESat-2 L1B Converted Telemetry Data V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.umm_json This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations. proprietary ATL02_006 ATLAS/ICESat-2 L1B Converted Telemetry Data V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2541211133-NSIDC_ECS.umm_json This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations. proprietary +ATL02_006 ATLAS/ICESat-2 L1B Converted Telemetry Data V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.umm_json This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations. proprietary ATL03_006 ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.umm_json This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03. proprietary ATL03_006 ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2559919423-NSIDC_ECS.umm_json This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03. proprietary ATL03_ANC_MASKS_1 ATLAS/ICESat-2 ATL03 Ancillary Masks, Version 1 NSIDCV0 STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2278879612-NSIDCV0.umm_json This ancillary ICESat-2 data set contains four static surface masks (land ice, sea ice, land, and ocean) provided by ATL03 to reduce the volume of data that each surface-specific along-track data product is required to process. For example, the land ice surface mask directs the ATL06 land ice algorithm to consider data from only those areas of interest to the land ice community. Similarly, the sea ice, land, and ocean masks direct ATL07, ATL08, and ATL12 algorithms, respectively. A detailed description of all four masks can be found in section 4 of the Algorithm Theoretical Basis Document (ATBD) for ATL03 linked under technical references. proprietary -ATL04_006 ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.umm_json ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL04_006 ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.umm_json ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary +ATL04_006 ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.umm_json ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL06_006 ATLAS/ICESat-2 L3A Land Ice Height V006 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2564427300-NSIDC_ECS.umm_json This data set (ATL06) provides geolocated, land-ice surface heights (above the WGS 84 ellipsoid, ITRF2014 reference frame), plus ancillary parameters that can be used to interpret and assess the quality of the height estimates. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL06_006 ATLAS/ICESat-2 L3A Land Ice Height V006 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2670138092-NSIDC_CPRD.umm_json This data set (ATL06) provides geolocated, land-ice surface heights (above the WGS 84 ellipsoid, ITRF2014 reference frame), plus ancillary parameters that can be used to interpret and assess the quality of the height estimates. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL07QL_006 ATLAS/ICESat-2 L3A Sea Ice Height Quick Look V006 NSIDC_ECS STAC Catalog 2024-08-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2548344839-NSIDC_ECS.umm_json ATL07QL is the quick look version of ATL07. Once final ATL07 files are available, the corresponding ATL07QL files will be removed. ATL07 contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary @@ -2442,17 +2442,17 @@ ATL09_006 ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Lay ATL10QL_006 ATLAS/ICESat-2 L3A Sea Ice Freeboard Quick Look V006 NSIDC_ECS STAC Catalog 2024-08-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2551529078-NSIDC_ECS.umm_json ATL10QL is the quick look version of ATL10. Once final ATL10 files are available the corresponding ATL10QL files will be removed. ATL10 contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL10_006 ATLAS/ICESat-2 L3A Sea Ice Freeboard V006 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2567856357-NSIDC_ECS.umm_json This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL10_006 ATLAS/ICESat-2 L3A Sea Ice Freeboard V006 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553243-NSIDC_CPRD.umm_json This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary -ATL11_006 ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series V006 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2750966856-NSIDC_ECS.umm_json This data set provides time series of land-ice surface heights derived from the ICESat-2 ATL06 Land Ice Height product. It is intended primarily as an input for higher level gridded products but can also be used on its own as a spatially organized product that allows easy access to height-change information derived from ICESat-2 observations. proprietary ATL11_006 ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series V006 NSIDC_CPRD STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2752556504-NSIDC_CPRD.umm_json This data set provides time series of land-ice surface heights derived from the ICESat-2 ATL06 Land Ice Height product. It is intended primarily as an input for higher level gridded products but can also be used on its own as a spatially organized product that allows easy access to height-change information derived from ICESat-2 observations. proprietary +ATL11_006 ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series V006 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2750966856-NSIDC_ECS.umm_json This data set provides time series of land-ice surface heights derived from the ICESat-2 ATL06 Land Ice Height product. It is intended primarily as an input for higher level gridded products but can also be used on its own as a spatially organized product that allows easy access to height-change information derived from ICESat-2 observations. proprietary ATL12_006 ATLAS/ICESat-2 L3A Ocean Surface Height V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553216-NSIDC_CPRD.umm_json This data set (ATL12) contains along-track sea surface height of the global open ocean, including the ice-free seasonal ice zone and near-coast regions. Estimates of height distributions, significant wave height, sea state bias, and 10 m heights are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL12_006 ATLAS/ICESat-2 L3A Ocean Surface Height V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2560378689-NSIDC_ECS.umm_json This data set (ATL12) contains along-track sea surface height of the global open ocean, including the ice-free seasonal ice zone and near-coast regions. Estimates of height distributions, significant wave height, sea state bias, and 10 m heights are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL13QL_006 ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data Quick Look V006 NSIDC_ECS STAC Catalog 2024-08-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2650092501-NSIDC_ECS.umm_json ATL13QL is the quick look version of ATL13. Once final ATL13 files are available the corresponding ATL13QL files will be removed. ATL13 contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7 km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit). proprietary -ATL13_006 ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2650116584-NSIDC_ECS.umm_json This data set (ATL13) contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit). proprietary ATL13_006 ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2684928243-NSIDC_CPRD.umm_json This data set (ATL13) contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit). proprietary -ATL14_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003 NSIDC_CPRD STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary +ATL13_006 ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2650116584-NSIDC_ECS.umm_json This data set (ATL13) contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit). proprietary ATL14_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary -ATL14_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004 NSIDC_CPRD STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.umm_json This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary +ATL14_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003 NSIDC_CPRD STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary ATL14_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004 NSIDC_ECS STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3159684163-NSIDC_ECS.umm_json This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary +ATL14_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004 NSIDC_CPRD STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.umm_json This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary ATL15_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776464171-NSIDC_ECS.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary ATL15_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003 NSIDC_CPRD STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776895930-NSIDC_CPRD.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary ATL15_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V004 NSIDC_CPRD STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3162334027-NSIDC_CPRD.umm_json This data set contains land ice height changes and change rates for the Antarctic ice sheet and regions around the Arctic gridded at four spatial resolutions (1 km, 10 km, 20 km, and 40 km). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary @@ -2465,12 +2465,12 @@ ATL19_003 ATLAS/ICESat-2 L3B Monthly Gridded Dynamic Ocean Topography V003 NSIDC ATL19_003 ATLAS/ICESat-2 L3B Monthly Gridded Dynamic Ocean Topography V003 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2754956786-NSIDC_CPRD.umm_json This data set contains monthly gridded dynamic ocean topography (DOT), derived from along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided in this data set. Both single beam and all-beam gridded averages are available in this data set. Single beam averages are useful to identify biases among the beams and the all-beam averages are advised to use for physical oceanography. proprietary ATL20_004 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Sea Ice Freeboard V004 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2666857908-NSIDC_ECS.umm_json ATL20 contains daily and monthly gridded estimates of sea ice freeboard, derived from along-track freeboard estimates in the ATLAS/ICESat-2 L3A Sea Ice Freeboard product (ATL10). Data are gridded at 25 km using the SSM/I Polar Stereographic Projection. proprietary ATL20_004 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Sea Ice Freeboard V004 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2753295020-NSIDC_CPRD.umm_json ATL20 contains daily and monthly gridded estimates of sea ice freeboard, derived from along-track freeboard estimates in the ATLAS/ICESat-2 L3A Sea Ice Freeboard product (ATL10). Data are gridded at 25 km using the SSM/I Polar Stereographic Projection. proprietary -ATL21_003 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.umm_json ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids. proprietary ATL21_003 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.umm_json ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids. proprietary +ATL21_003 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.umm_json ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids. proprietary ATL22_003 ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.umm_json ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers. proprietary ATL22_003 ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003 NSIDC_ECS STAC Catalog 2018-10-14 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.umm_json ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers. proprietary -ATL23_001 ATLAS/ICESat-2 L3B Monthly 3-Month Gridded Dynamic Ocean Topography V001 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2765424272-NSIDC_CPRD.umm_json This data set contains 3-month gridded averages of dynamic ocean topography (DOT) over midlatitude, north-polar, and south-polar grids derived from the along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided. Both single beam and all-beam gridded averages are available. Simple averages, degree-of-freedom averages, and averages interpolated to the center of grid cells are included, as well as uncertainty estimates. proprietary ATL23_001 ATLAS/ICESat-2 L3B Monthly 3-Month Gridded Dynamic Ocean Topography V001 NSIDC_ECS STAC Catalog 2018-10-13 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2692731693-NSIDC_ECS.umm_json This data set contains 3-month gridded averages of dynamic ocean topography (DOT) over midlatitude, north-polar, and south-polar grids derived from the along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided. Both single beam and all-beam gridded averages are available. Simple averages, degree-of-freedom averages, and averages interpolated to the center of grid cells are included, as well as uncertainty estimates. proprietary +ATL23_001 ATLAS/ICESat-2 L3B Monthly 3-Month Gridded Dynamic Ocean Topography V001 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2765424272-NSIDC_CPRD.umm_json This data set contains 3-month gridded averages of dynamic ocean topography (DOT) over midlatitude, north-polar, and south-polar grids derived from the along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided. Both single beam and all-beam gridded averages are available. Simple averages, degree-of-freedom averages, and averages interpolated to the center of grid cells are included, as well as uncertainty estimates. proprietary ATLAS_DEALIASED_SASS_L2_1 SEASAT SCATTEROMETER DEALIASED OCEAN WIND VECTORS (Atlas) POCLOUD STAC Catalog 1978-07-07 1978-10-10 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2617197627-POCLOUD.umm_json Contains wind speeds and directions derived from the Seasat-A Scatterometer (SASS), presented chronologically by swath for the period between 7 July 1978 and 10 October 1978. Robert Atlas et al. (1987) produced this product using an objective ambiguity removal scheme to dealias the wind vector data binned at 100 km cells, which were calculated by Frank Wentz. proprietary ATLAS_Veg_Plots_1541_1 Arctic Vegetation Plots ATLAS Project North Slope and Seward Peninsula, AK, 1998-2000 ORNL_CLOUD STAC Catalog 1998-07-01 2000-07-29 -165.07, 64.73, -153.74, 71.32 https://cmr.earthdata.nasa.gov/search/concepts/C2162120307-ORNL_CLOUD.umm_json This data set provides environmental, soil, and vegetation data collected from study sites on the North Slope and Seward Peninsula of Alaska during the Arctic Transition in Land-Atmosphere System (ATLAS) project. ATLAS-1 sites on the North Slope, located in Barrow, Atqasuk, Oumalik, and Ivotuk, were sampled in 1998-1999. ATLAS-2 sites located at Council and Quartz Creek on the Seward Peninsula were sampled in 2000. Specific attributes include dominant vegetation species and cover, biomass, soil chemistry and moisture, leaf area index (LAI), normalized difference vegetation index (NDVI), topography and elevation, and plant cover abundance. proprietary ATMOSL1_3 ATMOS L1 Spectra and Runlogs V3 (ATMOSL1) at GES DISC GES_DISC STAC Catalog 1985-04-30 1994-11-12 -180, -73, 180, 75 https://cmr.earthdata.nasa.gov/search/concepts/C2234896943-GES_DISC.umm_json This is the version 3 Atmospheric Trace Molecule Spectroscopy (ATMOS) Level 1 product containing spectra and runlog (i.e. ) information in a netCDF format. ATMOS is an infrared spectrometer (a Fourier transform interferometer) designed to derive vertical concentrations of various trace gases in the atmosphere, particularly the ozone depleting chlorine and fluorine based molecules. The transmission spectra are ratioed from ATMOS high sun observations, on a scale of 0 to 1. Data files also include time, geolocation and other information. The data were collected during four space shuttle missions: STS-51B/Spacelab 3 (April 30 to May 1, 1985), STS-45/ATLAS-1 (March 25 to April 2, 1992), STS-55/ATLAS-2 (April 8 to 16, 1993), and STS-66/ATLAS-3 (November 3 to 12, 1994). Data are written to separate files grouped by mission (sl3, at1, at2 or at3), and occultation type (sunrise or sunset) and number. proprietary @@ -4340,8 +4340,8 @@ CORAL_0 CORAL Experiment OB_DAAC STAC Catalog 2014-07-21 -180, -90, 180, 90 htt COROAS-AVHRR AVHRR Sea Surface Temperature for Southwestern Atlantic CEOS_EXTRA STAC Catalog 1992-09-01 -60, -38, -38, -20 https://cmr.earthdata.nasa.gov/search/concepts/C2227456149-CEOS_EXTRA.umm_json Data consisting of AVHRR five channels from satellites NOAA-11 and NOAA-12 and Sea Surface Temperature derived from brightness temperature files through NOAA algorithms. Exchange of data after January 1995. Due to system limitation, files are 512 lines x 512 pixels per line, 8 bits resolution. proprietary CORONA_SATELLITE_PHOTOS CORONA Satellite Photographs from the U.S. Geological Survey USGS_LTA STAC Catalog 1960-08-01 1972-05-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566377-USGS_LTA.umm_json The first generation of U.S. photo intelligence satellites collected more than 860,000 images of the Earth’s surface between 1960 and 1972. The classified military satellite systems code-named CORONA, ARGON, and LANYARD acquired photographic images from space and returned the film to Earth for processing and analysis. The images were originally used for reconnaissance and to produce maps for U.S. intelligence agencies. In 1992, an Environmental Task Force evaluated the application of early satellite data for environmental studies. Since the CORONA, ARGON, and LANYARD data were no longer critical to national security and could be of historical value for global change research, the images were declassified by Executive Order 12951 in 1995. The first successful CORONA mission was launched from Vandenberg Air Force Base in 1960. The satellite acquired photographs with a telescopic camera system and loaded the exposed film into recovery capsules. The capsules or buckets were de-orbited and retrieved by aircraft while the capsules parachuted to earth. The exposed film was developed and the images were analyzed for a range of military applications. The intelligence community used Keyhole (KH) designators to describe system characteristics and accomplishments. The CORONA systems were designated KH-1, KH-2, KH-3, KH-4, KH-4A, and KH-4B. The ARGON systems used the designator KH-5 and the LANYARD systems used KH-6. Mission numbers were a means for indexing the imagery and associated collateral data. A variety of camera systems were used with the satellites. Early systems (KH-1, KH-2, KH-3, and KH-6) carried a single panoramic camera or a single frame camera (KH-5). The later systems (KH-4, KH-4A, and KH-4B) carried two panoramic cameras with a separation angle of 30° with one camera looking forward and the other looking aft. The original film and technical mission-related documents are maintained by the National Archives and Records Administration (NARA). Duplicate film sources held in the USGS EROS Center archive are used to produce digital copies of the imagery. Mathematical calculations based on camera operation and satellite path were used to approximate image coordinates. Since the accuracy of the coordinates varies according to the precision of information used for the derivation, users should inspect the preview image to verify that the area of interest is contained in the selected frame. Users should also note that the images have not been georeferenced. proprietary COSMO-SkyMed.full.archive.and.tasking_NA COSMO-SkyMed full archive and tasking ESA STAC Catalog 2008-09-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336822-ESA.umm_json "The archive and new tasking X-band SAR products are available from COSMO-Skymed (CSK) and COSMO-SkyMed Second Generation (CSG) missions in ScanSAR and Stripmap modes, right and left looking acquisition (20 to 60° incidence angle). COSMO-SkyMed modes: Acquisition Mode / Single look Resolution [Az. X. Rg, SCS] (m) / Scene size [Az. X. Rg] (km) / Polarisation / Scene duration (seconds) / Number of looks / Multilook resolution (m) / Geolocation accuracy ±3 s (m) // / / / / / [DGM, GEC, GTC] // Stripmap Himage / 2.6 x 3 / 40 x 40 / Single: HH, HV, VH, VV / 7 / 3 / 5 / 25 // Stripmap PingPong / 9.7 x 11 / 30 x 30 / Alternate: HH/VV, HH/HV, VV/VH / 6 / 3 / 20 / 25 // ScanSAR Wide / 23 x 13.5 / 100 x 100 / Single: HH, HV, VH, VV / 15 / 4 - 9 / 30 / 30 // ScanSAR Huge / 38 x 13.5 / 200 x 200 / Single: HH, HV, VH, VV / 30 / 25 - 66 / 100 / 100 // COSMO-Skymed Second Generation Modes: Acquisition Mode / Single look Resolution [Az. X. Rg, SCS] (m) / Scene size [Az. X. Rg] (km) / Polarisation / Scene duration (seconds) / Number of looks / Multilook resolution (m)10/05/2021 10:28 / Geolocation accuracy ±3 s (m) // / / / / / [DGM, GEC, GTC] // Stripmap / 3 x 3 / 40 x 40 / Single (HH, VV, HV, VH) or Dual (HH+HV, VV+VH) / 7 / 2 x 2; 4 x 4 / 5 x 5; 11 x 11 / 3.75 // Stripmap PingPong / 12 x 5 / 30 x 30 / Alternate (HH/VV, HH/VH-HV/VV) / 6 / 1 x 2; 2 x 5 / 12 x 10; 22 x 25/ 12 // ScanSAR 1 / 20 x 4 / 100 x 100 / Single (HH, VV, HV, VH) or Dual (HH+HV, VV+VH) / 15 / 1 x 3; 1 x 5 / 20 x 13; 23 x 27; 35 x 40 / 12 // ScanSAR 2 / 40 x 6 / 200 x 200 / Single (HH, VV, HV, VH) or Dual (HH+HV, VV+VH) / 30 / 1 x 4; 1 x 7; 3 x 16 / 40 x 27; 47 x 54; 115 x 135 / 12 // Following Processing Levels are available, for both CSK and CSG: - SCS (Level 1A, Single-look Complex Slant): data in complex format, in slant range projection (the sensor's natural acquisition projection) and zero doppler projection, weighted and radiometrically equalised; the coverage corresponds to the full resolution area illuminated by the SAR instrument - DGM (Level 1B, Detected Ground Multi-look): product obtained detecting, multi-looking and projecting the Single-look Complex Slant data onto a grid regular in ground: it contains focused data, amplitude detected, optionally despeckled by multi-looking approach, radiometrically equalised and represented in ground/azimuth projection - GEC (Level 1C, Geocoded Ellipsoid Corrected): focused data, amplitude detected, optionally despeckled by multi-looking approach, geolocated on the reference ellipsoid and represented in a uniform preselected cartographic presentation. Any geometric correction derived by usage of terrain model isn't applied to this product by default - GTC (Level 1D, Geocoded Terrain Corrected): focused data, fully calibrated with the usage of terrain model, amplitude detected, optionally despeckled by multi-looking approach, geolocated on a DEM and represented in a uniform preselected cartographic presentation. The image scene is located and accurately rectified onto a map projection, through the use of Ground Control Points (GCPs) and Digital Elevation Model (DEM); it differs from GEC for the use of the DEM (instead of reference ellipsoid) for the accurate conversion from slant to ground range and to approximate the real earth surface The list of available data can be retrieved using the _$$CLEOS COSMO-SkyMed products catalogue$$ https://www.cleos.earth/ . User registration is requested to navigate the catalogue." proprietary -COWVR_STPH8_L1_TSDR_V10.0_10.0 COWVR STP-H8 Antenna and Microwave Brightness Temperatures Version 10.0 POCLOUD STAC Catalog 2022-01-08 -180, -61, 180, 61 https://cmr.earthdata.nasa.gov/search/concepts/C3237785963-POCLOUD.umm_json !!!Temporary notice posted Sept. 27th, 2024!!! These data are in the process of being ingested and not all files are available yet. The data were made public early to allow assessment by early science users. Accordingly, not all data set resources may be available yet. Please check over the next 2-3 weeks for finalization of this data set and PO.DAAC's release announcement.

This data set includes satellite-based observations of calibrated, geo-located antenna temperature and brightness temperatures, along with the sensor telemetry used to derive those values. Brightness temperatures are derived from the microwave band frequencies 18.7 GHz, 23.8 GHz, and 34.5 GHz. This product is best suited for a cal/val user or sensor expert. These level 1c measurements make up the temperature sensor data record (TSDR) from the COWVR (Compact Ocean Wind Vector Radiometer) sensor aboard the international space station (ISS), starting in January 2022 forward-streaming to PO.DAAC till the planned mission end in December 2024. Its swath width is 1012 km and spatial resolution is <35 km. Data files in HDF5 format are available at roughly hourly frequency (the ISS orbit period is ~90 minutes), although note that the coverage shown in the thumbnail is for a full day. Files include calibration and flag data in addition to brightness temperatures. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbers of the project team prior to release

The COWVR sensor is a fully polarimetric, conically imaging microwave radiometer for measuring ocean surface wind vectors. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. It was deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission. A successful COWVR mission will demonstrate a lower-cost sensor architecture (e.g. in comparison to WindSat) for providing imaging passive microwave data, including ocean surface vector wind products for the Department of Defense (DoD). COWVR was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping. proprietary -COWVR_STPH8_L2_EDR_V10.0_10.0 COWVR STP-H8 Surface Wind Vector and Column-Integrated Atmospheric Water Measurements Version 10.0 POCLOUD STAC Catalog 2022-01-08 -180, -61, 180, 61 https://cmr.earthdata.nasa.gov/search/concepts/C3237678855-POCLOUD.umm_json !!!Temporary notice posted Sept. 27th, 2024!!! These data are in the process of being ingested and not all files are available yet. The data were made public early to allow assessment by early science users. Accordingly, not all data set resources may be available yet. Please check over the next 2-3 weeks for finalization of this data set and PO.DAAC's release announcement.

This dataset includes satellite-based observations of geolocated surface wind vectors, precipitable water vapor, and integrated cloud liquid water, as well as the microwave brightness temperatures used to derive them. Theses measurements make up the environmental data record (EDR) from the COWVR (Compact Ocean Wind Vector Radiometer) sensor aboard the international space station (ISS), beginning in January 2022 with forward-streaming to PO.DAAC. Data over the satellite swath are available in HDF5 format with roughly one file per hour (the ISS orbit period is ~90 minutes), and coverage shown in the thumbnail is for a full day. The file metadata formats may be different than what an average user is familiar with – please see the User Guide to learn more. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbering of the project team prior to release.

The COWVR sensor is a fully polarimetric, conically imaging microwave radiometer for measuring ocean surface wind vectors. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. It was deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission. A successful COWVR mission will demonstrate a lower-cost sensor architecture (e.g. in comparison to WindSat) for providing imaging passive microwave data, including ocean surface vector wind products for the Department of Defense (DoD). COWVR was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping. proprietary +COWVR_STPH8_L1_TSDR_V10.0_10.0 COWVR STP-H8 Antenna and Microwave Brightness Temperatures Version 10.0 POCLOUD STAC Catalog 2022-01-08 -180, -61, 180, 61 https://cmr.earthdata.nasa.gov/search/concepts/C3237785963-POCLOUD.umm_json This data set includes satellite-based observations of calibrated, geo-located antenna temperature and brightness temperatures, along with the sensor telemetry used to derive those values. Brightness temperatures are derived from the microwave band frequencies 18.7 GHz, 23.8 GHz, and 34.5 GHz. This product is best suited for a cal/val user or sensor expert. These level 1c measurements make up the temperature sensor data record (TSDR) from the COWVR (Compact Ocean Wind Vector Radiometer) sensor aboard the international space station (ISS), starting in January 2022 forward-streaming to PO.DAAC till the planned mission end in December 2024. Its swath width is 1012 km and spatial resolution is <35 km. Data files in HDF5 format are available at roughly hourly frequency (the ISS orbit period is ~90 minutes), although note that the coverage shown in the thumbnail is for a full day. Files include calibration and flag data in addition to brightness temperatures. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbers of the project team prior to release

The COWVR sensor is a fully polarimetric, conically imaging microwave radiometer for measuring ocean surface wind vectors. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. It was deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission. A successful COWVR mission will demonstrate a lower-cost sensor architecture (e.g. in comparison to WindSat) for providing imaging passive microwave data, including ocean surface vector wind products for the Department of Defense (DoD). COWVR was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping. proprietary +COWVR_STPH8_L2_EDR_V10.0_10.0 COWVR STP-H8 Surface Wind Vector and Column-Integrated Atmospheric Water Measurements Version 10.0 POCLOUD STAC Catalog 2022-01-08 -180, -61, 180, 61 https://cmr.earthdata.nasa.gov/search/concepts/C3237678855-POCLOUD.umm_json This dataset includes satellite-based observations of geolocated surface wind vectors, precipitable water vapor, and integrated cloud liquid water, as well as the microwave brightness temperatures used to derive them. Theses measurements make up the environmental data record (EDR) from the COWVR (Compact Ocean Wind Vector Radiometer) sensor aboard the international space station (ISS), beginning in January 2022 with forward-streaming to PO.DAAC. Data over the satellite swath are available in HDF5 format with roughly one file per hour (the ISS orbit period is ~90 minutes), and coverage shown in the thumbnail is for a full day. Spatial resolution is roughly 35 km. The file metadata formats may be different than what an average user is familiar with – please see the User Guide to learn more. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbering of the project team prior to release.

The COWVR sensor is a fully polarimetric, conically imaging microwave radiometer for measuring ocean surface wind vectors. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. It was deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission. A successful COWVR mission will demonstrate a lower-cost sensor architecture (e.g. in comparison to WindSat) for providing imaging passive microwave data, including ocean surface vector wind products for the Department of Defense (DoD). COWVR was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping. proprietary CPEXAW-ADM-Aeolus_1 CPEX-AW ADM-Aeolus Datasets LARC_ASDC STAC Catalog 2021-08-06 2021-09-17 -125, 11, -45, 35 https://cmr.earthdata.nasa.gov/search/concepts/C2404262719-LARC_ASDC.umm_json CPEXAW-ADM-Aeolus_1 is the ESA ADM-Aeolus Datasets for the Convective Processes Experiment - Aerosols & Winds (CPEX-AW) sub-orbital campaign. Data collection for this product is complete. The Convective Processes Experiment – Aerosols & Winds (CPEX-AW) campaign was a joint effort between the US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) with the primary goal of conducting a post-launch calibration and validation activities of the Atmospheric Dynamics Mission-Aeolus (ADM-AEOLUS) Earth observation wind Lidar satellite in St. Croix. CPEX-AW is a follow-on to the Convective Processes Experiment (CPEX) field campaign which took place in the summer of 2017. In addition to joint calibration/validation of ADM-AEOLUS, CPEX-AW studied the dynamics related to the Saharan Air Layer, African Easterly Waves and Jets, Tropical Easterly Jet, and deep convection in the InterTropical Convergence Zone (ITCZ). CPEX-AW science goals include: • Better understanding interactions of convective cloud systems and tropospheric winds as part of the joint NASA-ESA Aeolus Cal/Val effort over the tropical Atlantic; • Observing the vertical structure and variability of the marine boundary layer in relation to initiation and lifecycle of the convective cloud systems, convective processes (e.g., cold pools), and environmental conditions within and across the ITCZ; • Investigating how the African easterly waves and dry air and dust associated with Sahara Air Layer control the convectively suppressed and active periods of the ITCZ; • Investigating interactions of wind, aerosol, clouds, and precipitation and effects on long range dust transport and air quality over the western Atlantic. In order to successfully achieve the objectives of the campaign, NASA deployed its DC-8 aircraft equipped with an Airborne Third Generation Precipitation Radar (APR-3), Doppler Aerosol WiNd Lidar (DAWN), High Altitude Lidar Observatory (HALO), High Altitude Monolithic Microwave Integrated Circuit (MMIC) Sounding Radiometer (HAMSR), and dropsondes. This campaign aims to provide useful material to atmospheric scientists, meteorologists, lidar experts, air quality experts, professors, and students. The Atmospheric Science Data Center (ASDC) archives the dropsonde, HALO, and DAWN data products for CPEX-AW. For additional datasets please visit the Global Hydrometeorology Resource Center (GHRC). proprietary CPEXAW-DAWN_DC8_1 CPEX-AW DAWN Doppler Aerosol WiNd Lidar LARC_ASDC STAC Catalog 2020-08-20 2021-09-04 -81, 11, -45, 35 https://cmr.earthdata.nasa.gov/search/concepts/C2260262728-LARC_ASDC.umm_json CPEXAW-DAWN_DC8_1 are the Doppler Aerosol WiNd lidar (DAWN) image and NetCDF data files collected during the Convective Processes Experiment - Aerosols & Winds (CPEX-AW) onboard the DC-8 aircraft. Data collection for this product is complete. The Convective Processes Experiment – Aerosols & Winds (CPEX-AW) campaign was a joint effort between the US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) with the primary goal of conducting a post-launch calibration and validation activities of the Atmospheric Dynamics Mission-Aeolus (ADM-AEOLUS) Earth observation wind Lidar satellite in St. Croix. CPEX-AW is a follow-on to the Convective Processes Experiment (CPEX) field campaign which took place in the summer of 2017. In addition to joint calibration/validation of ADM-AEOLUS, CPEX-AW studied the dynamics related to the Saharan Air Layer, African Easterly Waves and Jets, Tropical Easterly Jet, and deep convection in the InterTropical Convergence Zone (ITCZ). CPEX-AW science goals include: • Better understanding interactions of convective cloud systems and tropospheric winds as part of the joint NASA-ESA Aeolus Cal/Val effort over the tropical Atlantic; • Observing the vertical structure and variability of the marine boundary layer in relation to initiation and lifecycle of the convective cloud systems, convective processes (e.g., cold pools), and environmental conditions within and across the ITCZ; • Investigating how the African easterly waves and dry air and dust associated with Sahara Air Layer control the convectively suppressed and active periods of the ITCZ; • Investigating interactions of wind, aerosol, clouds, and precipitation and effects on long range dust transport and air quality over the western Atlantic. In order to successfully achieve the objectives of the campaign, NASA deployed its DC-8 aircraft equipped with an Airborne Third Generation Precipitation Radar (APR-3), Doppler Aerosol WiNd Lidar (DAWN), High Altitude Lidar Observatory (HALO), High Altitude Monolithic Microwave Integrated Circuit (MMIC) Sounding Radiometer (HAMSR), and dropsondes. This campaign aims to provide useful material to atmospheric scientists, meteorologists, lidar experts, air quality experts, professors, and students. The Atmospheric Science Data Center (ASDC) archives the dropsonde, HALO, and DAWN data products for CPEX-AW. For additional datasets please visit the Global Hydrometeorology Resource Center (GHRC). proprietary CPEXAW-Dropsondes_1 CPEX-AW Dropsonde Data LARC_ASDC STAC Catalog 2021-08-05 2021-09-17 -127, 9, -35, 37 https://cmr.earthdata.nasa.gov/search/concepts/C2299858387-LARC_ASDC.umm_json CPEXAW-Dropsondes_1 is the dropsonde data files collected during the Convective Processes Experiment - Aerosols & Winds (CPEX-AW). Data collection for this product is complete. The Convective Processes Experiment – Aerosols & Winds (CPEX-AW) campaign was a joint effort between the US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) with the primary goal of conducting a post-launch calibration and validation activities of the Atmospheric Dynamics Mission-Aeolus (ADM-AEOLUS) Earth observation wind Lidar satellite in St. Croix. CPEX-AW is a follow-on to the Convective Processes Experiment (CPEX) field campaign which took place in the summer of 2017. In addition to joint calibration/validation of ADM-AEOLUS, CPEX-AW studied the dynamics related to the Saharan Air Layer, African Easterly Waves and Jets, Tropical Easterly Jet, and deep convection in the InterTropical Convergence Zone (ITCZ). CPEX-AW science goals include: • Better understanding interactions of convective cloud systems and tropospheric winds as part of the joint NASA-ESA Aeolus Cal/Val effort over the tropical Atlantic; • Observing the vertical structure and variability of the marine boundary layer in relation to initiation and lifecycle of the convective cloud systems, convective processes (e.g., cold pools), and environmental conditions within and across the ITCZ; • Investigating how the African easterly waves and dry air and dust associated with Sahara Air Layer control the convectively suppressed and active periods of the ITCZ; • Investigating interactions of wind, aerosol, clouds, and precipitation and effects on long range dust transport and air quality over the western Atlantic. In order to successfully achieve the objectives of the campaign, NASA deployed its DC-8 aircraft equipped with an Airborne Third Generation Precipitation Radar (APR-3), Doppler Aerosol WiNd Lidar (DAWN), High Altitude Lidar Observatory (HALO), High Altitude Monolithic Microwave Integrated Circuit (MMIC) Sounding Radiometer (HAMSR), and dropsondes. This campaign aims to provide useful material to atmospheric scientists, meteorologists, lidar experts, air quality experts, professors, and students. The Atmospheric Science Data Center (ASDC) archives the dropsonde, HALO, and DAWN data products for CPEX-AW. For additional datasets please visit the Global Hydrometeorology Resource Center (GHRC). proprietary @@ -6154,10 +6154,10 @@ GHISACONUS_001 Global Hyperspectral Imaging Spectral-library of Agricultural cro GIMMS3g_NDVI_Trends_1275_1 Long-Term Arctic Growing Season NDVI Trends from GIMMS 3g, 1982-2012 ORNL_CLOUD STAC Catalog 1982-06-01 2012-08-31 -180, 20, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2784897341-ORNL_CLOUD.umm_json This data set provides normalized difference vegetation index (NDVI) data for the arctic growing season derived primarily with data from Advanced Very High Resolution Radiometer (AVHRR) sensors onboard several NOAA satellites over the years 1982 through 2012. The NDVI data, which show vegetation activity, were averaged annually for the arctic growing season (GS; June, July and August). The products include the annual GS-NDVI values and the results of a cumulative GS-NDVI time series trends analysis. The data are circumpolar in coverage at 8-km resolution and limited to greater than 20 degrees N.These normalized difference vegetation index (NDVI) trends were calculated using the third generation data set from the Global Inventory Modeling and Mapping Studies (GIMMS 3g). GIMMS 3g improves on its predecessor (GIMMS g) in three important ways. First, GIMMS 3g integrates data from NOAA-17 and 18 satellites to lengthen its record. Second, it addresses the spatial discontinuity north of 72 degrees N, by using SeaWiFS, in addition to SPOT VGT, to calibrate between the second and third versions of the AVHRR sensor (AVHRR/2 and AVHRR/3). Finally, the GIMMS 3g algorithm incorporates improved snowmelt detection and is calibrated based on data from the shorter, arctic growing season (May-September) rather than the entire year (January-December). proprietary GISS-CMIP5_1 GISS ModelE2 contributions to the CMIP5 archive NCCS STAC Catalog 0850-01-01 2100-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1542315069-NCCS.umm_json We present a description of the ModelE2 version of the Goddard Institute for Space Studies (GISS) General Circulation Model (GCM) and the configurations used in the simulations performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). We use six variations related to the treatment of the atmospheric composition, the calculation of aerosol indirect effects, and ocean model component. Specifically, we test the difference between atmospheric models that have noninteractive composition, where radiatively important aerosols and ozone are prescribed from precomputed decadal averages, and interactive versions where atmospheric chemistry and aerosols are calculated given decadally varying emissions. The impact of the first aerosol indirect effect on clouds is either specified using a simple tuning, or parameterized using a cloud microphysics scheme. We also use two dynamic ocean components: the Russell and HYbrid Coordinate Ocean Model (HYCOM) which differ significantly in their basic formulations and grid. Results are presented for the climatological means over the satellite era (1980-2004) taken from transient simulations starting from the preindustrial (1850) driven by estimates of appropriate forcings over the 20th Century. Differences in base climate and variability related to the choice of ocean model are large, indicating an important structural uncertainty. The impact of interactive atmospheric composition on the climatology is relatively small except in regions such as the lower stratosphere, where ozone plays an important role, and the tropics, where aerosol changes affect the hydrological cycle and cloud cover. While key improvements over previous versions of the model are evident, these are not uniform across all metrics. proprietary GIS_EastAngliaClimateMonthly_551_1 Global Monthly Climatology for the Twentieth Century (New et al.) ORNL_CLOUD STAC Catalog 1900-01-01 1998-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2780535151-ORNL_CLOUD.umm_json A 0.5 degree lat/lon data set of monthly surface climate over global land areas, excluding Antarctica. Primary variables are interpolated directly from station time-series: precipitation, mean temperature and diurnal temperature range. proprietary -GLAH01_033 GLAS/ICESat L1A Global Altimetry Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000400-NSIDC_ECS.umm_json Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter. Each data granule has an associated browse product. proprietary GLAH01_033 GLAS/ICESat L1A Global Altimetry Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547306-NSIDC_CPRD.umm_json Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter. Each data granule has an associated browse product. proprietary -GLAH02_033 GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product. proprietary +GLAH01_033 GLAS/ICESat L1A Global Altimetry Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000400-NSIDC_ECS.umm_json Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter. Each data granule has an associated browse product. proprietary GLAH02_033 GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.umm_json GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product. proprietary +GLAH02_033 GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product. proprietary GLAH03_033 GLAS/ICESat L1A Global Engineering Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547514-NSIDC_CPRD.umm_json Level-1A global engineering data (GLAH03) include satellite housekeeping data used to calibrate data values for GLA01 and GLA02. proprietary GLAH03_033 GLAS/ICESat L1A Global Engineering Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991863-NSIDC_ECS.umm_json Level-1A global engineering data (GLAH03) include satellite housekeeping data used to calibrate data values for GLA01 and GLA02. proprietary GLAH04_033 GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.umm_json Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing. proprietary @@ -6168,22 +6168,22 @@ GLAH06_034 GLAS/ICESat L1B Global Elevation Data (HDF5) V034 NSIDC_CPRD STAC Cat GLAH06_034 GLAS/ICESat L1B Global Elevation Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000445-NSIDC_ECS.umm_json GLAH06 Level-1B Global Elevation is a product that is analogous to the geodetic data records distributed for radar altimetry missions. It contains elevations previously corrected for tides, atmospheric delays, and surface characteristics within the footprint. Elevation is calculated using the ice sheet parameterization. Additional information allows the user to calculate an elevation based on land, sea ice, or ocean algorithms. Each data granule has an associated browse product. proprietary GLAH07_033 GLAS/ICESat L1B Global Backscatter Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.umm_json GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product. proprietary GLAH07_033 GLAS/ICESat L1B Global Backscatter Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.umm_json GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product. proprietary -GLAH08_033 GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol Layer Heights (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1631093696-NSIDC_ECS.umm_json GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate). Each data granule has an associated browse product. proprietary GLAH08_033 GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol Layer Heights (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549511-NSIDC_CPRD.umm_json GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate). Each data granule has an associated browse product. proprietary -GLAH09_033 GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.umm_json GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product. proprietary +GLAH08_033 GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol Layer Heights (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1631093696-NSIDC_ECS.umm_json GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate). Each data granule has an associated browse product. proprietary GLAH09_033 GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991869-NSIDC_ECS.umm_json GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product. proprietary -GLAH10_033 GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-09-25 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.umm_json GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product. proprietary +GLAH09_033 GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.umm_json GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product. proprietary GLAH10_033 GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-09-25 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product. proprietary +GLAH10_033 GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-09-25 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.umm_json GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product. proprietary GLAH11_033 GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991871-NSIDC_ECS.umm_json GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product. proprietary GLAH11_033 GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.umm_json GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product. proprietary GLAH12_034 GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH12_034 GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000461-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary -GLAH13_034 GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH13_034 GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000464-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary -GLAH14_034 GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary +GLAH13_034 GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH14_034 GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000443-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary -GLAH15_034 GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary +GLAH14_034 GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH15_034 GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153552369-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary +GLAH15_034 GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLCHMK_001 G-LiHT Canopy Height Model KML V001 LPCLOUD STAC Catalog 2011-06-30 -170, 10, -50, 73 https://cmr.earthdata.nasa.gov/search/concepts/C2763264695-LPCLOUD.umm_json Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT(https://gliht.gsfc.nasa.gov/)) mission utilizes a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico. The purpose of G-LiHT’s Canopy Height Model Keyhole Markup Language (KML) data product (GLCHMK) is to provide LiDAR-derived maximum canopy height and canopy variability information to aid in the study and analysis of biodiversity and climate change. Scientists at NASA’s Goddard Space Flight Center began collecting data over locally-defined areas in 2011 and that the collection will continue to grow as aerial campaigns are flown and processed. GLCHMK data are processed as a Google Earth overlay KML file at a nominal 1 meter spatial resolution over locally-defined areas. A low resolution browse is also provided showing the canopy height with a color map applied in JPEG format. proprietary GLCHMT_001 G-LiHT Canopy Height Model V001 LPCLOUD STAC Catalog 2011-06-30 -170, 10, -50, 73 https://cmr.earthdata.nasa.gov/search/concepts/C2763264702-LPCLOUD.umm_json Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT(https://gliht.gsfc.nasa.gov/)) mission utilizes a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico. The purpose of G-LiHT’s Canopy Height Model data product (GLCHMT) is to provide LiDAR-derived maximum canopy height and canopy variability information to aid in the study and analysis of biodiversity and climate change. Scientists at NASA’s Goddard Space Flight Center began collecting data over locally-defined areas in 2011 and that the collection will continue to grow as aerial campaigns are flown and processed. GLCHMT data are processed as a raster data product (GeoTIFF) at a nominal 1 meter spatial resolution over locally-defined areas. A low resolution browse is also provided showing the canopy height with a color map applied in JPEG format. proprietary GLDAS_CLM10SUBP_3H_001 GLDAS CLM Land Surface Model L4 3 hourly 1.0 x 1.0 degree Subsetted V001 (GLDAS_CLM10SUBP_3H) at GES DISC GES_DISC STAC Catalog 1979-01-02 2020-03-31 -180, -60, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1279404074-GES_DISC.umm_json With the upgraded Land Surface Models (LSMs) and updated forcing data sets, the GLDAS version 2.1 (GLDAS-2.1) production stream serves as a replacement for GLDAS-001. The entire GLDAS-001 collection from January 1979 through March 2020 was decommissioned on June 30, 2020 and removed from the GES DISC system. However, the replacement for GLDAS-001 monthly and 3-hourly 1.0 x 1.0 degree products from CLM Land Surface Model currently are not available yet. Once their replacement data products become available, the DOIs of GLDAS-001 CLM data products will direct to the GLDAS-2.1 CLM data products. This data set contains a series of land surface parameters simulated from the Common Land Model (CLM) V2.0 model in the Global Land Data Assimilation System (GLDAS). The data are in 1.0 degree resolution and range from January 1979 to present. The temporal resolution is 3-hourly. This simulation was forced by a combination of NOAA/GDAS atmospheric analysis fields, spatially and temporally disaggregated NOAA Climate Prediction Center Merged Analysis of Precipitation (CMAP) fields, and observation based downward shortwave and longwave radiation fields derived using the method of the Air Force Weather Agency's AGRicultural METeorological modeling system (AGRMET). The simulation was initialized on 1 January 1979 using soil moisture and other state fields from a GLDAS/CLM model climatology for that day of the year. WGRIB or another GRIB reader is required to read the files. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units. For more information, please see the README document. proprietary @@ -6582,6 +6582,8 @@ GSSTF_F15_2c Goddard Satellite-Based Surface Turbulent Fluxes, 1x1 deg Daily Gri GSSTF_F15_3 Goddard Satellite-Based Surface Turbulent Fluxes, 0.25 x 0.25 deg, Daily Grid F15 V3 (GSSTF_F15) at GES DISC GES_DISC STAC Catalog 2000-01-01 2009-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1237113424-GES_DISC.umm_json These data are part of the Goddard Satellite-based Surface Turbulent Fluxes Version 3 (GSSTF3) Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project. This is a Daily (24-hour) product; data are projected to equidistant Grid that covers the globe at 0.25x0.25 degree cell size, resulting in data arrays of 1440x720 size. The daily fluxes are produced for each individual available SSM/I satellite tapes (e.g., F11, F13, F14 and F15), and then serve as input to the Combined daily fluxes (GSSTF_3). The short name of this data set is GSSTF_F15. proprietary GSSTF_NCEP_2c NCEP/DOE Reanalysis II in HDF-EOS5, for GSSTF2c, 1x1 deg Daily grid V2c (GSSTF_NCEP) at GES DISC GES_DISC STAC Catalog 1987-07-01 2009-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1237113451-GES_DISC.umm_json These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-2c (GSSTF2c) Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project. This is a Daily (24-hour) product; data are projected to equidistant Grid that covers the globe at 1x1 degree cell size, resulting in data arrays of 360x180 size. A finer resolution, 0.25 deg, of this product has been released as Version 3. The input data sets used for this recent GSSTF production include the upgraded and improved datasets such as the Special Sensor Microwave Imager (SSM/I) Version-6 (V6) product of brightness temperature [Tb], total precipitable water [W], and wind speed [U] produced by the Wentz of Remote Sensing Systems (RSS), as well as the NCEP/DOE Reanalysis-2 (R2) product of sea skin temperature [SKT], 2-meter air temperature [Tair], and sea level pressure [SLP]. The short name for this product is GSSTF_NCEP. proprietary GSSTF_NCEP_3 NCEP/DOE Reanalysis II, for GSSTF, 0.25 x 0.25 deg, Daily Grid V3 (GSSTF_NCEP) at GES DISC GES_DISC STAC Catalog 1987-07-01 2009-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1237113465-GES_DISC.umm_json These data are the Goddard Satellite-based Surface Turbulent Fluxes Version 3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. This HDF-EOS5 dataset is part of the MEaSUREs project. This is a Daily product; data are projected to equidistant Grid that covers the globe at 0.25x0.25 degree cell size, resulting in data arrays of 1440x720 size. Data gap: Daily GSSTF_NCEP files are missing for October 21-22,26-28, in 1990. The input data sets used for this recent GSSTF production include the upgraded and improved datasets such as the Special Sensor Microwave Imager (SSM/I) Version-6 (V6) product of brightness temperature [Tb], total precipitable water [W], and wind speed [U] produced by the Wentz of Remote Sensing Systems (RSS), as well as the NCEP/DOE Reanalysis-2 (R2) product of sea skin temperature [SKT], 2-meter air temperature [Tair], and sea level pressure [SLP]. The short name for this product is GSSTF_NCEP. proprietary +GVHRRATS6IMIR_001 GVHRR/ATS-6 Black and White Infrared Images on Film V001 (GVHRRATS6IMIR) at GES DISC GES_DISC STAC Catalog 1974-06-07 1974-08-15 175, -90, -5, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3275628922-GES_DISC.umm_json GVHRRATS6IMIR is the Geosynchronous Very High Resolution Radiometer (GVHRR) Black and White Infrared Images on 70mm Film data product from the sixth Applications Technology Satellite (ATS-6). This set of IR imagery (10.5 to 12.5 micrometer, with an 11 km footprint at the sub-satellite point) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title at the bottom of the image and a gray scale on the right boundary that represents brightness temperatures. The title contains the satellite identification, receiving station, spectral band, picture number, picture type, pixel scale, sector number, and date. The ATS-6 satellite was in a geosynchronous orbit parked at 95W viewing the hemisphere below the satellite. The GVHRR experiment returned data from launch until August 15, 1974 when it became inoperable, The PI was William E. Shenk from NASA Goddard Space Flight Center. This product was previously available from the NSSDC with the identifier ESAD-00092 (old ID 74-039A-08B). proprietary +GVHRRATS6IMVIS_001 GVHRR/ATS-6 Black and White Visible Images on Film V001 (GVHRRATS6IMVIS) at GES DISC GES_DISC STAC Catalog 1974-06-07 1974-08-15 175, -90, -5, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3275628923-GES_DISC.umm_json GVHRRATS6IMVIS is the Geosynchronous Very High Resolution Radiometer (GVHRR) Black and White Visible Images on Film data product from the sixth Applications Technology Satellite (ATS-6). This set of visible imagery (0.55 to 0.75 micrometer, with a 5.5 km footprint at the sub-satellite point) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title at the bottom of the image and a gray scale on the right boundary that represents brightness temperatures. The title contains the satellite identification, receiving station, spectral band, picture number, picture type, pixel scale, sector number, and date. The ATS-6 satellite was in a geosynchronous orbit parked at 95W viewing the hemisphere below the satellite. The GVHRR experiment returned data from launch until August 15, 1974 when it became inoperable, The PI was William E. Shenk from NASA Goddard Space Flight Center. This product was previously available from the NSSDC with the identifier ESAD-00047 (old ID 74-039A-08A). proprietary GVdem_2008_3 A bathymetric Digital Elevation Model (DEM) of the George V and Terre Adelie continental shelf and margin AU_AADC STAC Catalog 2008-03-17 2010-07-16 138, -69, 148, -63 https://cmr.earthdata.nasa.gov/search/concepts/C1214313477-AU_AADC.umm_json This dataset comprises Digital Elevation Models (DEMs) of varying resolutions for the George V and Terre Adelie continental margin, derived by incorporating all available singlebeam and multibeam point depth data into ESRI ArcGIS grids. The purpose was to provide revised DEMs for Census of Antarctic Marine Life (CAML) researchers who required accurate, high-resolution depth models for correlating seabed biota data against the physical environment. The DEM processing method utilised all individual multibeam and singlebeam depth points converted to geographic xyz (long/lat/depth) ASCII files. In addition, an ArcGIS line shapefile of the East Antarctic coastline showing the grounding lines of coastal glaciers and floating ice shelves, was converted to a xyz ASCII file with 0 m as the depth value. Land elevation data utilised the Radarsat Antarctic Mapping Project (RAMP) 200 m DEM data converted to xyz ASCII data. All depth, land and coastline ASCII files were input to Fledermaus 3DEditor visualisation software for removal of noisy data. The cleaned point data were then binned into a gridded surface using Fledermaus DMagic software, resulting in a 0.001-arcdegree (~100 m) resolution DEM with holes where no input data exists. ArcGIS Topogrid software was used to interpolate across the holes to output a full-coverage DEM. ArcGIS was used to produce the additional 0.0025-arcdegree (~250 m) and 0.005-arcdegree (~500 m) resolution grids. Full processing details can be viewed in: Beaman, R.J., O'Brien, P.E., Post, A.L., De Santis, L., 2011. A new high-resolution bathymetry model for the Terre Adelie and George V continental margin, East Antarctica. Antarctic Science 23(1), 95-103. doi:10.1017/S095410201000074X proprietary GWELDMO_003 NASA Global Web-Enabled Landsat Data Monthly Global 30 m V003 LPCLOUD STAC Catalog 2008-12-01 2011-11-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2763266354-LPCLOUD.umm_json The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Web-Enabled Landsat Data Monthly (GWELDMO) Version 3 data product provides Landsat data at 30 meter (m) resolution for terrestrial non-Antarctica locations over monthly reporting periods for the 2010 epoch. GWELD data products are generated from all available Landsat 4 and 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data in the U.S. Geological Survey (USGS) Landsat archive. The GWELD suite of products provide consistent data to derive land cover as well as geophysical and biophysical information for regional assessment of land surface dynamics. The GWELD products include Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) for the reflective wavelength bands and to top of atmosphere (TOA) brightness temperature for the thermal bands. The products are defined in the Sinusoidal coordinate system to promote continuity of NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) land tile grid. Provided in the GWELDMO product are layers for surface reflectance bands 1 through 5 and 7, TOA brightness temperature for thermal bands, Normalized Difference Vegetation Index (NDVI), day of year, ancillary angle, and data quality information. A low-resolution red, green, blue (RGB) browse image of bands 5, 4, 3 is also available for each granule. proprietary GWELDMO_031 NASA Global Web-Enabled Landsat Data Monthly Global 30 m V031 LPCLOUD STAC Catalog 1984-03-01 2001-11-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2763268458-LPCLOUD.umm_json The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Web-Enabled Landsat Data Monthly (GWELDMO) Version 3.1 data product provides Landsat data at 30 meter (m) resolution for terrestrial non-Antarctica locations over monthly reporting periods for the 1985, 1990, and 2000 epochs. GWELD data products are generated from all available Landsat 4 and 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data in the U.S. Geological Survey (USGS) Landsat archive. The GWELD suite of products provide consistent data to derive land cover as well as geophysical and biophysical information for regional assessment of land surface dynamics. The GWELD products include Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) for the reflective wavelength bands and to top of atmosphere (TOA) brightness temperature for the thermal bands. The products are defined in the Sinusoidal coordinate system to promote continuity of NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) land tile grid. Provided in the GWELDMO product are layers for surface reflectance bands 1 through 5 and 7, TOA brightness temperature for thermal bands, Normalized Difference Vegetation Index (NDVI), day of year, ancillary angle, and data quality information. A low-resolution red, green, blue (RGB) browse image of bands 5, 4, 3 is also available for each granule. Version 3.1 products use Landsat Collection 1 products as input and have improved per-pixel cloud mask, new quality data, improved calibration information, and improved product metadata that enable view and solar geometry calculations. proprietary @@ -9187,6 +9189,11 @@ LGB_Ht_traverse_1 Ice sheet surface elevation data: LGB traverses 1989-95 AU_AAD LGB_Vel_traverse_1 Ice sheet surface velocity data: LGB traverses 1989-95 AU_AADC STAC Catalog 1989-11-01 1995-02-28 54, -77, 78, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214313578-AU_AADC.umm_json The ANARE Lambert Glacier Basin (LGB) series of oversnow traverses were conducted during the period 1989-95. Field operations were carried out along the proximity of the 2500 m elevation contour around the interior basin between Mawson and Davis stations. The main traverse route covered some 2014 km of track from LGB00 at 68.6543 S, 61.1201 E, and LGB72 at 69.9209 S, 76.4933 E. Ice sheet surface velocities were obtained for 73 sites known as Ice Movement Stations (IMS), spaced approximately 30 km apart between LGB00 and LGB72. Raw data were recorded in Wild-Leitz (WM102) or Leica-Wild (200-series) proprietary mode including data, observation, almanac and ephemeris files. Processed data were stored in proprietary software output modes and has been written to standard spreadsheet (MS Excel) files for sharing with downstream processing programs. The data available at the url below are stored in various formats. Summary data (2 km spatial average) can be obtained from CRC Research Note No. 23, 'Ice Sheet Surface Velocities along the Lambert Basin Traverse Route'. Documents providing archive details of the logbooks are available for download from the provided URL. This work was completed as part of ASAC projects 3 and 2216. proprietary LGP_2 Latitudinal Gradient Project - Australian contributions AU_AADC STAC Catalog 1989-01-01 2009-12-31 168, -86, 180, -72 https://cmr.earthdata.nasa.gov/search/concepts/C1214313600-AU_AADC.umm_json This record relates to the Australian component of the Latitudinal Gradient Project. The LGP is largely a New Zealand, US and Italian venture, but a small contribution has been made by Australian scientists. The Australian component of this work was completed as part of ASAC projects 2361 and 2682 (ASAC_2361, and ASAC_2682). Data from this project were entered into the herbarium access database, which has been linked to this record. The list below contains details of where and when samples were collected, and also the type of sample and the method of sampling. Cape Hallett and vicinity (2000, 2004): Biodiversity assessment of terrestrial plants (mosses, lichens); Invertebrate collections (mites, Collembola); plant ecology and community analysis; photosynthetic physiology of mosses and lichens; molecular genetics of mosses and lichens. Random sampling for biodiversity studies; point quadrats, releves for vegetation analysis, field laboratory experiments for physiological studies. Dry Valleys: Taylor Valley (1989, 1996), Garwood Valley (2001), Granite Harbour (1989; 1994, 1996) - plant ecology; plant physiology; biodiversity; invertebrate collections; molecular genetics of mosses. Random sampling for biodiversity studies; point quadrats, releves for vegetation analysis, field laboratory experiments for physiological studies. Beaufort Island (1996) - plant biodiversity; molecular genetics of mosses. Random sampling for biodiversity studies; point quadrats, releves for vegetation analysis, laboratory studies for molecular genetics. Darwin Glacier (1994): plant biodiversity; molecular genetics of invertebrates and mosses (random sampling for biodiversity; laboratory studies of invertebrate and moss molecular genetics). Project objectives: 1. Investigate the distribution of bryophytes and lichens in continental Antarctica 1a). to test the null hypothesis that species diversity does not change significantly with latitude; 1b). to explore the relationships between species and key environmental attributes including latitude, distance from the coast, temperature, substrate, snow cover, age of ice-free substrate. 2. To continue to participate in the Ross Sea Sector Latitudinal Gradient Project and develop an Australian corollary in the Prince Charles Mountains, involving international collaborators, incorporating the first two objectives of this project. 3. To develop an international collaborative biodiversity and ecophysiological program in the Prince Charles Mountains that will provide a parallel N-S latitude gradient study to mirror the LGP program in the Ross Sea region as part of the present RISCC cooperative program (to be superseded by the EBA (Evolution and Biodiversity of Antarctica) program) to address the above objectives. Taken from the 2008-2009 Progress Report: Progress against objectives: Continuing identification of moss and lichen samples previously collected from Cape Hallett, Granite Harbour and Darwin Glacier region. Lecidea s.l. lichens currently being studied in Austria by PhD student. Field work in Dry Valleys significantly curtailed by adverse weather. Field work planned for Darwin Glacier region and McMurdo Dry Valleys, particularly Taylor Valley and Granite Harbour region was severely curtailed due to adverse weather, helicopter diversions due to a Medical Evacuation, and other logistic constraints. 10 days of field time were lost. Limitations on field travel in Darwin Glacier region restricted the field work to a biologically depauperate region. The Prince Charles Mountains N-S transect, the only continental transect possibility for comparison with the Ross Sea area, unfortunately appears to have been abandoned through lack of logistic support. Taken from the 2009-2010 Progress Report: Identification of samples collected from AAT and Ross Sea Region continued during the year, interrupted significantly by the packing of the collection and transfer of specimens to the Tasmanian Herbarium. Work is now proceeding at the Herbarium with sorting, databasing and incorporation of packets into the Herbarium collection. The merging of the collection provides long-term security of curation and significantly boosts the cryptogam collections (35000 numbers) of the Tasmanian Herbarium. proprietary LGRIP30_001 Landsat-Derived Global Rainfed and Irrigated-Cropland Product 30 m V001 LPDAAC_ECS STAC Catalog 2014-01-01 2017-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3281868752-LPDAAC_ECS.umm_json The Landsat-Derived Global Rainfed and Irrigated-Cropland Product (LGRIP) provides high resolution, global cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data (GFSAD) project, LGRIP maps the world’s agricultural lands by dividing them into irrigated and rainfed croplands, and calculates irrigated and rainfed areas for every country in the world. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2014-2017 time period to create a nominal 2015 product. Each LGRIP 30 meter resolution GeoTIFF file contains a contains a layer that identifies areas of rainfed cropland (cropland areas that are purely dependent on direct precipitation), irrigated cropland (cropland that had at least one irrigation during the crop growing period), non-cropland, and water bodies over a 10° by 10° area, as well as an accuracy assessment of the product. A low-resolution browse image is also available. proprietary +LGRIP30_L1_IRRI_002 Landsat-Derived Global Irrigated-Cropland Product L1 2020 30 m V002 LPCLOUD STAC Catalog 2019-01-01 2022-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3262829042-LPCLOUD.umm_json The Landsat-Derived Global Irrigated-Cropland Product Level 1 2020 (LGRIP30_L1_IRRI) Version 2 data provides high-resolution, 30 meter (m) cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data ([GFSAD](https://www.usgs.gov/centers/western-geographic-science-center/science/global-food-security-support-analysis-data-30-m)) project, LGRIP_L1_IRRI V2 maps agricultural lands by dividing them into 32 irrigated cropland types and calculates applicable cropland areas across the globe. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2019 through 2021 time period to create a nominal 2020 product. Each LGRIP30 L1 V2 Irrigated 30 m resolution GeoTIFF file contains a layer that identifies areas of irrigated cropland (cropland that had at least one irrigation during the crop growing period) divided into 32 types, non-irrigated land (rainfed cropland and areas not classified as cropland), and water bodies over a 10° by 10° area, as well as an accuracy assessment of the product. A low-resolution browse image is also included. Currently, LGRIP30 V2 products contain data only for the conterminous United States (CONUS). LGRIP30 V2 data covering the rest of the globe will be added at a later date. proprietary +LGRIP30_L1_RAIN_002 Landsat-Derived Global Rainfed-Cropland Product L1 2020 30 m V002 LPCLOUD STAC Catalog 2019-01-01 2022-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3263421104-LPCLOUD.umm_json The Landsat-Derived Global Rainfed-Cropland Product Level 1 2020 (LGRIP30_L1_RAIN) Version 2 data provides high-resolution, 30 meter (m) cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data ([GFSAD](https://www.usgs.gov/centers/western-geographic-science-center/science/global-food-security-support-analysis-data-30-m)) project, LGRIP30_L1_RAIN V2 maps agricultural lands by dividing them into 24 types of rainfed croplands and calculates applicable cropland areas across the globe. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2019 through 2021 time period to create a nominal 2020 product. Each LGRIP L1 Rainfed 30 m resolution GeoTIFF file contains a layer that identifies areas of rainfed cropland (cropland areas that are purely dependent on direct precipitation without any artificial watering) divided into 24 types, non-rainfed land (irrigated croplands and areas not classified as cropland), and water bodies over a 10° by 10° area, as well as an accuracy assessment of the product. A low-resolution browse image is also included. Currently, LGRIP30 V2 products only contain data for the conterminous United States (CONUS). LGRIP30 V2 data covering the rest of the globe will be added at a later date. proprietary +LGRIP30_L2_IRRI_002 Landsat-Derived Global Irrigated-Cropland Product L2 2020 30 m V002 LPCLOUD STAC Catalog 2019-01-01 2022-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3263429968-LPCLOUD.umm_json The Landsat-Derived Global Irrigated-Cropland Product Level 2 2020 (LGRIP30_L2_IRRI) Version 2 data provides high-resolution, 30 meter (m) cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data ([GFSAD](https://www.usgs.gov/centers/western-geographic-science-center/science/global-food-security-support-analysis-data-30-m)) project, LGRIP_L2_IRRI V2 maps agricultural lands by dividing them into irrigated single crop, double crop, and continuous croplands, and calculates applicable cropland areas across the globe. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2019 through 2021 time period to create a nominal 2020 product. Each LGRIP L2 Irrigated 30 m resolution GeoTIFF file contains a layer that identifies areas of irrigated cropland (cropland that had at least one irrigation during the crop growing period) divided into single, double, and continuous crop classifications, non-irrigated land (rainfed cropland and areas not classified as cropland), and water bodies over a 10° by 10° area, as well as an accuracy assessment of the product. A low-resolution browse image is also included. Currently, LGRIP30 V2 products only contain data for the conterminous United States (CONUS). LGRIP30 V2 data covering the rest of the globe will be added at a later date. proprietary +LGRIP30_L2_RAIN_002 Landsat-Derived Global Rainfed-Cropland Product L2 2020 30 m V002 LPCLOUD STAC Catalog 2019-01-01 2022-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3263433662-LPCLOUD.umm_json The Landsat-Derived Global Rainfed-Cropland Product Level 2 2020 (LGRIP30_L2_RAIN) Version 2 data provides high-resolution, 30 meter (m) cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data ([GFSAD](https://www.usgs.gov/centers/western-geographic-science-center/science/global-food-security-support-analysis-data-30-m)) project, LGRIP_L2_RAIN V2 maps agricultural lands by dividing them into rainfed single croplands and rainfed single croplands mixed with natural vegetation, and calculates applicable cropland areas across the globe. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2019 through 2021 time period to create a nominal 2020 product. Each LGRIP L2 Rainfed 30 m resolution GeoTIFF file contains a layer that identifies areas of rainfed cropland (cropland areas that are purely dependent on direct precipitation without any artificial watering) divided into single crop and single crop that is mixed with natural vegetation, non-rainfed land (irrigated croplands and areas not classified as cropland), and water bodies over a 10° by 10° area, as well as an accuracy assessment of the product. A low-resolution browse image is also included. Currently, LGRIP30 V2 products only contain data for the conterminous United States (CONUS). LGRIP30 V2 data covering the rest of the globe will be added at a later date. proprietary +LGRIP30_L3_002 Landsat-derived Global Rainfed and Irrigated-Cropland Product L3 2020 30 m V002 LPCLOUD STAC Catalog 2019-01-01 2022-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3262817664-LPCLOUD.umm_json The Landsat-derived Global Rainfed and Irrigated-Cropland Product Level 3 2020 (LGRIP30_L3) Version 2 data provides high-resolution, 30 meter (m) cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data ([GFSAD](https://www.usgs.gov/centers/western-geographic-science-center/science/global-food-security-support-analysis-data-30-m)) project, LGRIP L3 V2 maps agricultural croplands by dividing them into irrigated and rainfed croplands, and calculates irrigated and rainfed areas across the globe. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2019 through 2021 time period to create a nominal 2020 product. Each LGRIP30 L3 V2 30 m resolution GeoTIFF file contains a layer that identifies areas of rainfed cropland (cropland areas that are purely dependent on direct precipitation without any artificial watering), irrigated cropland (cropland that had at least one irrigation during the crop growing period), non-cropland, and water bodies over a 10° by 10° area, as well as an accuracy assessment of the product. A low-resolution browse image is also included. Currently, LGRIP30 V2 products only contain data for the conterminous United States (CONUS). LGRIP30 V2 data covering the rest of the globe will be added at a later date. proprietary LIDA Lidar Data from Brazil CEOS_EXTRA STAC Catalog 1972-02-23 -45, -23, -45, -23 https://cmr.earthdata.nasa.gov/search/concepts/C2227456105-CEOS_EXTRA.umm_json The FISAT home page on the WWW is http://www.laser.inpe.br/fisat/ . This set contains data obtained at the location of Sao Jose dos Campos (23 degrees S, 45 degrees W), only. >From 1972 to 1981 only night-time data of the Lidar backscatter return at 589.0 nm are available. The periodicity of the data is irregular. Generally short-duration measurements (less than 2 hours) are available at about one measurerent per week. Long-duration data covering most of the night are available in a few campaigns. Data are also given, in processed form, providing aerosol backscatter ratio from 15 to 30 km altitude and sodium density from 75 to 105 km altitude. >From 1981 to 1993, campaigns of sodium measurements taken during the day, including several diurnal cycles are also available. >From 1983 to the present day a new powerful laser at 593.0 nm provides the Rayleigh scatter profiles giving the atmospheric density and temperatures from 35 to nearly 70 km altitude. Data are currently obtained, approximately, on a weekly basis. proprietary LIDAR_0 Pigment measurements from 1989 and 1990 in the Gulf of St Lawrence OB_DAAC STAC Catalog 1989-09-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360430-OB_DAAC.umm_json Pigment measurements from 1989 and 1990 in the Gulf of St Lawrence. proprietary LIDAR_FOREST_CANOPY_HEIGHTS_1271_1 CMS: GLAS LiDAR-derived Global Estimates of Forest Canopy Height, 2004-2008 ORNL_CLOUD STAC Catalog 2004-10-03 2004-11-08 -161.41, -55.45, 179.89, 69.29 https://cmr.earthdata.nasa.gov/search/concepts/C2343105406-ORNL_CLOUD.umm_json This data set provides estimates of forest canopy height derived from the Geoscience Laser Altimeter System (GLAS) LiDAR instrument that was aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite. A global GLAS waveform data set (n=12,336,553) from collection periods between October 2004 and March 2008 was processed to obtain canopy height estimates.Estimates of GLAS maximum canopy height and crown-area-weighted Lorey's height are provided for 18,578 statistically-selected globally distributed forested sites in a point shapefile. Country is included as a site attribute.Also provided is the average canopy height for the forested area of each country, plus the number of GLAS data footprints (shots), number of selected sample sites, and estimates of the variance for each country. proprietary @@ -11320,6 +11327,7 @@ NSIDC-0792_1 MEaSUREs ITS_LIVE Antarctic Quarterly 1920 m Ice Shelf Height Chang NSIDC-0793_1 MEaSUREs ITS_LIVE Greenland Monthly 120 m Ice Sheet Extent Masks, 1972-2022 V001 NSIDC_ECS STAC Catalog 1972-09-15 2022-02-15 -94.4, 58.33, 11.32, 81.51 https://cmr.earthdata.nasa.gov/search/concepts/C3177912929-NSIDC_ECS.umm_json This ITS_LIVE data set, part of the Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, contains monthly, 120 m resolution ice masks for the Greenland Ice Sheet from 1972 to 2022. The presence of ice was determined from 237,556 manually and AI-derived terminus positions acquired by satellite optical and radar observations. Months with no observations have been gap-filled using past and future observations of terminus positions and advance rates constrained by the average flow speed of the glacier. Animations are also available for 206 catchments that show how the ice front positions have changed over the course of the time series and can be used as a quality control check. proprietary NSIDC-0794_1 MEaSUREs ITS_LIVE Antarctic Annual 240 m Ice Sheet Extent Masks, 1997-2021 V001 NSIDC_ECS STAC Catalog 1997-10-01 2021-03-14 -180, -90, 180, -57.6 https://cmr.earthdata.nasa.gov/search/concepts/C3179071550-NSIDC_ECS.umm_json This ITS_LIVE data set, part of the Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, consists of 240 m Antarctic Ice Sheet extent masks at roughly annual resolution from 1997 through 2021. The ice masks were generated by combining data acquired by multiple satellite-borne optical, thermal, and radar sensors. The ice thickness and velocity data used to determine the presence of ice are also provided. proprietary NSIDC-0796_1 Glacial and Fast Ice Distributions in Southeast Greenland Fjords V001 NSIDC_ECS STAC Catalog 2015-01-01 2019-12-31 -44.199176, 60.286876, -22.410516, 70.009956 https://cmr.earthdata.nasa.gov/search/concepts/C3226155848-NSIDC_ECS.umm_json This data set provides spatial distributions of fast ice and glacial ice in eight fjords spanning the Southeast Greenland coast: Nansen, Kangerlusruaq, Ikertivaq, Skjoldungen, Tingmiarmiut, Napasorsvaq, Anoritup, and Kangerlluluk. Temporal coverage is discontinuous, depending on the availability and quality of images. Fjord data were sourced from USGS EarthExplorer, Copernicus Open Access Hub, and the NSIDC. Landsat-8 and MODIS imagery for ice identification were collected from NASA Worldview and USGS EarthExplorer. Fjord, fast ice, and glacial ice boundaries were manually delineated using ArcGIS. Glacial ice was further categorized as dense glacial melange (Type 3), substantial glacial ice with large icebergs (Type 2), low-density glacial ice with large icebergs (Type 1), consistent small ice surface without large icebergs (Type 0), or glacier surface (Type 99). proprietary +NSIDC-0797_1 SMAP/CYGNSS EASE-Grid Soil Moisture V001 NSIDC_ECS STAC Catalog 2017-04-01 2023-12-31 -180, -40, 180, 40 https://cmr.earthdata.nasa.gov/search/concepts/C3286281558-NSIDC_ECS.umm_json "This data set is derived by downscaling Soil Moisture Active Passive (SMAP) enhanced Level-3 9 km brightness temperatures (TB) using Cyclone Global Navigation Satellite System (CYGNSS) reflectivity data and employing a slightly modified version of the baseline SMAP active-passive TB algorithm, the Single Channel Algorithm – Vertical polarization (SCA-V). The main parameter of this data set is surface soil moisture presented on the Global EASE-Grid 2.0 projection, with each data point representing the top 5 cm of the soil column. For SMAP-derived data, see SMAP Enhanced L3 Radiometer Global and Polar Grid Daily 9 km EASE-Grid Soil Moisture, Version 5; for CYGNSS-derived data, see CYGNSS Level 1, Version 2.1." proprietary NURE_SEDIMENT_CHEM National Uranium Resource Evaluation Program: Sediment Chemistry of the Conterminous United States CEOS_EXTRA STAC Catalog 1964-01-01 1996-01-01 -179, 19, -68, 70 https://cmr.earthdata.nasa.gov/search/concepts/C2231552690-CEOS_EXTRA.umm_json From NURE Sediment Chemistry FAQ: These maps are derived from a subset of the National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR) data. Approximately 260,000 samples were analyzed in the continental U.S. and consisted of solid samples, including stream, lake, pond, spring, and playa sediments, and soils. Data for eleven elements: Na, Ti, Fe, Cu, Zn, As, Ce, Hf, Pb, Th, and U were analyzed and included on the National Geochemical Atlas CD and the digital release NURE Sediment Chemistry. These publications are intended to allow the rapid visualization of the geochemical landscape of the conterminous U.S. using NURE HSSR data. The raw data used in the production of these publications are available on the following CD-ROM: Hoffman, J.D., Kim P. Buttleman, Russell A. Ambroziak, and Christine A. Cook, 1996, National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR) data. available proprietary NVAP_CLIMATE_Layered-Precipitable-Water_1 NASA Water Vapor Project MEaSUREs (NVAP-M) CLIMATE Layered Precipitable Water LARC_ASDC STAC Catalog 1988-01-01 2009-12-01 180, -90, -179.9, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1595664379-LARC_ASDC.umm_json NVAP_CLIMATE_Layered-Precipitable-Water data set is designed to provide the most stable water vapor data set 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. proprietary NVAP_CLIMATE_Total-Precipitable-Water_1 NASA Water Vapor Project MEaSUREs (NVAP-M) CLIMATE Total Precipitable Water LARC_ASDC STAC Catalog 1988-01-01 2009-12-01 180, -90, -179.9, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1600001034-LARC_ASDC.umm_json 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. proprietary @@ -11657,6 +11665,7 @@ OMPS_N20_NMHCHO_L2_1 OMPS-N20 L2 NM Formaldehyde (HCHO) Total Column swath orbit OMPS_N20_NMSO2_PCA_L2_Step1_1 OMPS-N20 NM PCA SO2 Step 1 Total Column 1-Orbit L2 Swath 17x13km GES_DISC STAC Catalog 2018-01-16 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2808692512-GES_DISC.umm_json The OMPS-N20 NM PCA SO2 Step1 Total Column 1-Orbit L2 Swath 17x13km collection 1 product contains the retrieved sulfur dioxide (SO2) measured by the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor on the NOAA-20 (JPSS-1) satellite. The product is based on the NASA Goddard Space Flight Center principal component analysis (PCA) spectral fitting algorithm (Li et al., 2013, 2017) used to retrieve the SO2 total column amounts assuming different SO2 plume heights, including the boundary layer (lowest 1 km of the atmosphere), the lower (centered at 3 km), middle (centered at 8 km) and upper (centered at 13 km) troposphere, as well as the lower stratosphere (centered at 18 km). Each granule contains data from the daylight portion for a single orbit or about 50 minutes. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14 orbits per day each with a swath width of 2600 km. There are 104 pixels in the cross-track direction before February 13, 2019 with a pixel resolution of about 17 km x 17 km at nadir. Since then, the pixel resolution has been enhanced to 17 km x 13 km at nadir, with 140 pixels in the cross-track direction. The files are written using netCDF version 4. proprietary OMPS_N20_NMSO2_PCA_L2_Step1_NRT_1 OMPS-N20 NM PCA SO2 Step 1 Total Column 1-Orbit L2 Swath 17x13km NRT OMINRT STAC Catalog 2018-01-16 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3186057121-OMINRT.umm_json The OMPS-N20 NM PCA SO2 Step1 Total Column 1-Orbit L2 Swath 17x13km collection 1 product contains the retrieved sulfur dioxide (SO2) measured by the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor on the NOAA-20 (JPSS-1) satellite. The product is based on the NASA Goddard Space Flight Center principal component analysis (PCA) spectral fitting algorithm (Li et al., 2013, 2017) used to retrieve the SO2 total column amounts assuming different SO2 plume heights, including the boundary layer (lowest 1 km of the atmosphere), the lower (centered at 3 km), middle (centered at 8 km) and upper (centered at 13 km) troposphere, as well as the lower stratosphere (centered at 18 km). Each granule contains data from the daylight portion for a single orbit or about 50 minutes. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14 orbits per day each with a swath width of 2600 km. There are 104 pixels in the cross-track direction before February 13, 2019 with a pixel resolution of about 17 km x 17 km at nadir. Since then, the pixel resolution has been enhanced to 17 km x 13 km at nadir, with 140 pixels in the cross-track direction. The files are written using netCDF version 4. proprietary OMPS_N21_LP_L1G_EV_1.0 OMPS-N21 L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit V1.0 (OMPS_N21_LP_L1G_EV) at GES DISC GES_DISC STAC Catalog 2022-11-10 -180, -84, 180, 84 https://cmr.earthdata.nasa.gov/search/concepts/C3117300814-GES_DISC.umm_json The OMPS-N21 L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit product contains the calibrated earth-viewing radiances measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the NOAA 21 (JPSS-2) satellite. The LP L1G product measures radiances in the wavelength region from 280 nm to 1000 nm. Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1-2 km. The data are written using the Hierarchical Data Format Version 5 or HDF5. proprietary +OMPS_N21_LP_L2_AER_DAILY_1.0 OMPS-N21 L2 LP Aerosol Extinction Vertical Profile swath daily 3slit V2 (OMPS_N21_LP_L2_AER_DAILY) at GES DISC GES_DISC STAC Catalog 2022-11-10 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3262950749-GES_DISC.umm_json The OMPS-N21 L2 LP Aerosol Extinction Vertical Profile swath daily 3slit (AER) product contains the retrieved aerosol extinction coefficients measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the NOAA-21 satellite. The AER product measures stratospheric aerosol abundance and evolution at 6 wavelengths (510, 600, 675, 745, 869 and 997 nm) to complement the OMPS LP measurements of stratospheric and mesospheric profile ozone. This product replaces the previous single wavelength 675 nm (AER675) product. Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1.8 km. The files are written using the Hierarchical Data Format Version 5 or HDF5. proprietary OMPS_N21_LP_L2_O3_DAILY_1.0 OMPS-N21 L2 LP Ozone (O3) Vertical Profile swath daily 3slit V1.0 (OMPS_N21_LP_L2_O3_DAILY) at GES DISC GES_DISC STAC Catalog 2022-11-10 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3237592774-GES_DISC.umm_json The OMPS-N21 L2 LP Ozone (O3) Vertical Profile swath daily 3slit collection contains ozone measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the NOAA-21 satellite. The LP ozone product measures the vertical distribution of ozone in the stratosphere and lower mesosphere. The algorithm derives ozone profile values along with errors in the UV from 29.5 km and 52.5 km, and in the visible from cloud top to 37.5 km (when there are no clouds the lower limit is 12.5 km). Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day, the data from the center of the LP three slits are used to make a vertical profile. The profile is measured from the ground up to about 60 km with a vertical resolution of the retrieved profiles of approximately 1.8 km. The data are written using the Hierarchical Data Format Version 5 or HDF5. proprietary OMPS_NPP_LP_L1G_EV_2 OMPS-NPP L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit V2 (OMPS_NPP_LP_L1G_EV) at GES DISC GES_DISC STAC Catalog 2011-11-07 -180, -84, 180, 84 https://cmr.earthdata.nasa.gov/search/concepts/C1412974463-GES_DISC.umm_json The OMPS-NPP L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit product contains the calibrated earth-viewing radiances measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The LP L1G product measures radiances in the wavelength region from 280 nm to 1000 nm. Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1-2 km. The data are written using the Hierarchical Data Format Version 5 or HDF5. proprietary OMPS_NPP_LP_L1G_EV_2.6 OMPS-NPP L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit V2.6 (OMPS_NPP_LP_L1G_EV) at GES DISC GES_DISC STAC Catalog 2011-11-07 -180, -84, 180, 84 https://cmr.earthdata.nasa.gov/search/concepts/C2469227759-GES_DISC.umm_json The OMPS-NPP L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit product contains the calibrated earth-viewing radiances measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The LP L1G product measures radiances in the wavelength region from 280 nm to 1000 nm. Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1-2 km. The data are written using the Hierarchical Data Format Version 5 or HDF5. proprietary @@ -11690,8 +11699,8 @@ OMTO3_003 OMI/Aura Ozone(O3) Total Column 1-Orbit L2 Swath 13x24 km V003 (OMTO3) OMTO3_003 OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003 NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.umm_json The OMI/Aura Level-2 Total Column Ozone Data Product OMTO3 Near Real Time data is made available from the OMI SIPS NASA for the public access. The Ozone Monitoring Instrument (OMI)was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator's (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. This level-2 global total column ozone product (OMTO3)is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI additional hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrieval (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and extensive quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3 and the algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia ( Pawan.K.Bhartia@nasa.gov). OMTO3 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is about 35 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMTO3 data file contains one swath which consists of two groups: Data fields: OMI Total Ozone,Effective Reflectivity (331 - 360 nm), N-value, Cloud Fraction, Cloud Top Pressure, O3 below Cloud, UV Aerosol Index, SO2 index, Wavelength used in the algorithm, many Auxiliary Algorithm Parameter and Quality Flags Geolocation Fields: Latitude, Longitude, Time, Relative Azimuth, Solar Zenith and Azimuth, Viewing Zenith and Azimuth angles, Spacecraft Altitude, Latitude, Longitude, Terrain Height, Ground Pixel Quality Flags.For the full set of Aura data products available from the GES DISC, please see the link http://disc.sci.gsfc.nasa.gov/Aura/ . proprietary OMTO3_CPR_003 OMI/Aura Level 2 Ozone (O3) Total Column 1-Orbit Subset and Collocated Swath along CloudSat track 200-km wide at 13x24 km2 resolution GES_DISC STAC Catalog 2006-06-01 2018-03-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236350982-GES_DISC.umm_json This is a CloudSat-collocated subset of the original product OMTO3, for the purposes of the A-Train mission. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track of CloudSat. This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications. (The shortname for this CloudSat-collocated OMI Level 2 Total Ozone Column subset is OMTO3_CPR_V003) proprietary OMTO3d_003 OMI/Aura TOMS-Like Ozone, Aerosol Index, Cloud Radiance Fraction L3 1 day 1 degree x 1 degree V3 (OMTO3d) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136070-GES_DISC.umm_json The OMI science team produces this Level-3 daily global TOMS-Like Total Column Ozone gridded product OMTO3d (1 deg Lat/Lon grids). The OMTO3d product is produced by gridding and averaging only good quality level-2 total column ozone orbital swath data (OMTO3, based on the enhanced TOMS version-8 algorithm) on the 1x1 degree global grids. The OMTO3d files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3d data product is about 0.65 Mbytes. proprietary -OMTO3e_003 OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.umm_json The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. OMTO3e files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. (The shortname for this Level-3 TOMS-Like Total Column Ozone gridded product is OMTO3e) . proprietary OMTO3e_003 OMI/Aura TOMS-Like Ozone and Radiative Cloud Fraction L3 1 day 0.25 degree x 0.25 degree V3 (OMTO3e) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136071-GES_DISC.umm_json The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. The OMTO3e files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. proprietary +OMTO3e_003 OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.umm_json The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. OMTO3e files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. (The shortname for this Level-3 TOMS-Like Total Column Ozone gridded product is OMTO3e) . proprietary OMUANC_004 Primary Ancillary Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km V4 (OMUANC) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2556143653-GES_DISC.umm_json The Primary Ancillary Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km (OMUANC) provides selected parameters from GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath. The fields in this product include snow cover, sea ice cover, land cover, terrain height, row anomaly flag, and pixel area. The OMI team also provides a corresponding product for the OMI VIS swath, OMVANC. This product has been generated for convenient use by the OMI/Aura team in their L2 algorithms, and for research where those L2 products are used. The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir. The OMUANC files are in netCDF4 format which is compatible with most netCDF and HDF5 readers and tools. Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official. proprietary OMUFPITMET_003 GEOS-5 FP-IT Assimilation Geo-colocated to OMI/Aura UV-2 1-Orbit L2 Support Swath 13x24km V3 (OMUFPITMET) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1561222825-GES_DISC.umm_json The GEOS-5 FP-IT Assimilation Geo-colocated to OMI/Aura UV-2 1-Orbit L2 Support Swath 13x24km (OMUFPITMET) provides selected parameters from GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath. The fields in this product include surface pressure, vertical temperature profiles, surface and vertical wind profiles, tropopause pressure, boundary layer top pressure, and surface geopotenial. The OMI team also provides a corresponding product for the OMI VIS swath, OMVFPITMET. The product has been generated for convenient use by the OMI/Aura team in their L2 algorithms, and for research where those L2 products are used. The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir. To reduce the size of each orbital file, FP-IT data fields with a vertical dimension of 72 layers have been reduced to 47 layers in OMUFPITMET by combining layers above the troposphere. The OMUFPITMET files are in netCDF4 format which is compatible with most HDF5 readers and tools. Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official. proprietary OMUFPMET_004 GEOS-5 FP-IT 3D Time-Averaged Model-Layer Assimilated Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km V4 (OMUFPMET) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2556146042-GES_DISC.umm_json The GEOS-5 FP-IT 3D Time-Averaged Model-Layer Assimilated Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km (OMUFPMET) product provides selected meteorlogical fields from the GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath. The fields in this product include layer pressure thickness, surface pressure, vertical temperature profiles, surface potential, and mid-layer pressure along with geolocation info. The OMI team also provides a corresponding product for the OMI VIS swath, OMVFPMET. The OMI ancillary products were developed to provide supplementary information for use with the OMI collection 4 L1B data sets. The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir. The OMUFPMET files are in netCDF4 format which is compatible with most netCDF and HDF5 readers and tools. Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official. proprietary @@ -13341,7 +13350,7 @@ TELLUS_GRFO_L3_GFZ_RL06.3_LND_v04_RL06.3v04 GFZ TELLUS GRACE-FO Level-3 Monthly TELLUS_GRFO_L3_GFZ_RL06.3_OCN_v04_RL06.3v04 GFZ TELLUS GRACE-FO Level-3 Monthly Ocean Bottom Pressure Anomaly Release 6.3 version 04 POCLOUD STAC Catalog 2018-05-22 -180, -89.5, 180, 89.5 https://cmr.earthdata.nasa.gov/search/concepts/C3193298027-POCLOUD.umm_json This data set is produced by the German Research Centre for Geosciences (GFZ) as part of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the ocean bottom pressure (OBP) anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents sea floor pressure changes due to the integral effect of ocean and atmosphere processes, including global mean ocean bottom pressure changes (mean ocean mass and mean atmosphere mass over the global oceans). A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats.

GRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 – 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the ocean bottom pressure data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this release 06.3 is an updated version of the Level 3 products in coordination with the release of the analogous Level 2 products used to generate them. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data. proprietary TELLUS_GRFO_L3_JPL_RL06.3_LND_v04_RL06.3v04 JPL TELLUS GRACE-FO Level-3 Monthly Land Water-Equivalent-Thickness Surface Mass Anomaly Release 6.3 version 04 POCLOUD STAC Catalog 2018-05-22 -180, -89.5, 180, 89.5 https://cmr.earthdata.nasa.gov/search/concepts/C3193302127-POCLOUD.umm_json This data set is produced by the Jet Propulsion Laboratory (JPL) as part of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the terrestrial water storage anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents the total terrestrial water storage anomalies from soil moisture, snow, surface water (incl. rivers, lakes, reservoirs etc.), as well as groundwater and aquifers. A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats.

GRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 – 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the terrestrial water storage data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this RL06.3 is an updated release of the previous RL06.1. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data. proprietary TELLUS_GRFO_L3_JPL_RL06.3_OCN_v04_RL06.3v04 JPL TELLUS GRACE-FO Level-3 Monthly Ocean Bottom Pressure Anomaly Release 6.3 version 04 POCLOUD STAC Catalog 2018-05-22 -180, -89.5, 180, 89.5 https://cmr.earthdata.nasa.gov/search/concepts/C3193304376-POCLOUD.umm_json This data set is produced by the Jet Propulsion Laboratory (JPL) as part of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the ocean bottom pressure (OBP) anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents sea floor pressure changes due to the integral effect of ocean and atmosphere processes, including global mean ocean bottom pressure changes (mean ocean mass and mean atmosphere mass over the global oceans). A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats.

GRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 – 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the ocean bottom pressure data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this RL06.3 is an updated release of the previous RL06.1. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data. proprietary -TEMPEST_STPH8_L1_TSDR_V10.0_10.0 TEMPEST STP-H8 Antenna and Microwave Brightness Temperatures Version 10.0 POCLOUD STAC Catalog 2022-01-08 -180, -61, 180, 61 https://cmr.earthdata.nasa.gov/search/concepts/C3237795822-POCLOUD.umm_json !!!Temporary notice posted Sept. 27th, 2024!!! These data are in the process of being ingested and not all files are available yet. The data were made public early to allow assessment by early science users. Accordingly, not all data set resources may be available yet. Please check over the next 2-3 weeks for finalization of this data set and PO.DAAC's release announcement.

This dataset includes satellite-based observations of calibrated, geo-located antenna temperature and brightness temperatures, along with the sensor telemetry used to derive those values. Brightness temperatures are derived from the microwave band frequencies 87, 164, 174, 178 and 181 GHz. This product is best suited for a cal/val user or sensor expert. These level 1c measurements make up the temperature sensor data record (TSDR) from the TEMPEST (Temporal Experiment for Storms and Tropical Systems) sensor aboard the international space station (ISS), starting in January 2022 forward-streaming to PO.DAAC till the planned mission end in December 2024. TEMPEST swath width is 1400 kilometers and resolution at nadir is 25 km for the 87 GHz channel and 13 km for the 180 GHz channels. Data files in HDF5 format are available at roughly hourly frequency (the ISS orbit period is ~90 minutes), although note that the coverage shown in the thumbnail is for a full day. Files include calibration and flag data in addition to brightness temperatures. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbering of the project team prior to release.

The TEMPEST instrument is a microwave radiometer deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission, with the primary objective of tropical cyclone intensity tracking. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. A successful mission will demonstrate a lower-cost, lighter-weight sensor architecture for providing microwave data. TEMPEST was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping. proprietary +TEMPEST_STPH8_L1_TSDR_V10.0_10.0 TEMPEST STP-H8 Antenna and Microwave Brightness Temperatures Version 10.0 POCLOUD STAC Catalog 2022-01-08 -180, -61, 180, 61 https://cmr.earthdata.nasa.gov/search/concepts/C3237795822-POCLOUD.umm_json This dataset includes satellite-based observations of calibrated, geo-located antenna temperature and brightness temperatures, along with the sensor telemetry used to derive those values. Brightness temperatures are derived from the microwave band frequencies 87, 164, 174, 178 and 181 GHz. This product is best suited for a cal/val user or sensor expert. These level 1c measurements make up the temperature sensor data record (TSDR) from the TEMPEST (Temporal Experiment for Storms and Tropical Systems) sensor aboard the international space station (ISS), starting in January 2022 forward-streaming to PO.DAAC till the planned mission end in December 2024. TEMPEST swath width is 1400 kilometers and resolution at nadir is 25 km for the 87 GHz channel and 13 km for the 180 GHz channels. Data files in HDF5 format are available at roughly hourly frequency (the ISS orbit period is ~90 minutes), although note that the coverage shown in the thumbnail is for a full day. Files include calibration and flag data in addition to brightness temperatures. Version 10.0 is the first public release, and is named as such to be consistent with the internal version numbering of the project team prior to release.

The TEMPEST instrument is a microwave radiometer deployed as part of the Space Test Program - Houston 8 (STP-H8) technology demonstration mission, with the primary objective of tropical cyclone intensity tracking. It operates nominally on-orbit aboard the ISS and data are non-sun-synchronous. A successful mission will demonstrate a lower-cost, lighter-weight sensor architecture for providing microwave data. TEMPEST was provided by the Jet Propulsion Laboratory and flown by the United States Space Force, Space Systems Command, Development Corps for Innovation and Prototyping. proprietary TEMPO_CLDO4_L2_V03 TEMPO cloud pressure and fraction (O2-O2 dimer) V03 (BETA) LARC_CLOUD STAC Catalog 2023-08-01 -170, 10, -10, 80 https://cmr.earthdata.nasa.gov/search/concepts/C2930760329-LARC_CLOUD.umm_json O2-O2 cloud Level 2 files provide cloud information at TEMPO’s native spatial resolution, ~10 km^2 at the center of the Field of Regard (FOR), for individual granules. Each granule covers the entire North-South TEMPO FOR but only a portion of the East-West FOR. The files are provided in netCDF4 format, and contain information on effective cloud fraction (ECF), cloud optical centroid pressure (OCP), ancillary data, processing quality flags, etc. The ECF is derived from reflectance at 466 nm. The OCP is derived from O2-O2 slant column density. The cloud retrieval uses Look Up Tables (LUTs) of reflectance and air mass factors, GEOS-CF forecast meteorology, and GLER surface albedo. proprietary TEMPO_CLDO4_L3_V03 TEMPO gridded cloud fraction and pressure (O2-O2 dimer) V03 (BETA) LARC_CLOUD STAC Catalog 2023-08-01 -170, 10, -10, 80 https://cmr.earthdata.nasa.gov/search/concepts/C2930727817-LARC_CLOUD.umm_json O2-O2 cloud Level 3 files provide cloud information on a regular grid covering the TEMPO field of regard for nominal TEMPO observations. Level 3 files are derived by combining information from all Level 2 files constituting a TEMPO East-West scan cycle. The files are provided in netCDF4 format, and contain information on effective cloud fraction, cloud optical centroid pressure, and ancillary data. The re-gridding algorithm uses an area-weighted approach. proprietary TEMPO_DRK_L1_V02 TEMPO dark exposure V02 (BETA) LARC_CLOUD STAC Catalog 2023-06-06 -170, 10, -10, 80 https://cmr.earthdata.nasa.gov/search/concepts/C2842836142-LARC_CLOUD.umm_json Level 1 dark files provide the processed dark currents, corresponding to either solar irradiance measurements or radiance measurements. Each file includes the measured dark currents for all the North-South cross-track pixels. The files are provided in netCDF4 format, and contain information on dark current rates of all frames and their average for the UV and visible bands, pixel quality flags and other ancillary information. The product is produced using the image processing of L0-1b processor. Please refer to the ATBD for details. These data are beta. Beta maturity is defined as: the product is minimally validated but may still contain significant errors; it is based on product quick looks using the initial calibration parameters. Because the products at this stage have minimal validation, users should refrain from making conclusive public statements regarding science and applications of the data products until a product is designated at the provisional validation status. The TEMPO Level 1 ATBD is still being finalized. For access to Version 1.0 ATBD, please contact the ASDC at larc-dl-asdc-tempo@mail.nasa.gov. proprietary @@ -13747,7 +13756,7 @@ TROPICS01TCIEL2B_1.0 TROPICS01 Pathfinder L2B Tropical Cyclone Intensity Estim TROPICS01URADL2A_1.0 TROPICS01 Pathfinder L2A Unified Resolution Brightness Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859214263-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the Pathfinder satellite, as the provisional version of the Level 2A geolocated brightness temperature that are reported at native spatial resolutions. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS03ANTTL1A_1.0 TROPICS03 L1A Orbital Geolocated Native-Resolution Antenna Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3171499152-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS03BRTTL1B_1.0 TROPICS03 L1B Orbital Geolocated Native-Resolution Brightness Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3171499529-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary -TROPICS03MIRSL2B_0.2 TROPICS03 L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V0.2 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2857802936-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details." proprietary +TROPICS03MIRSL2B_1.0 TROPICS03 L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3255751009-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Validated Stage-1 release of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. " proprietary TROPICS03PRPSL2B_1.0 TROPICS03 Pathfinder L2B Instantaneous Surface Rain Rate (ISRR) V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3254839500-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details." proprietary TROPICS03TCIEL2B_1.0 TROPICS03 L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3279630448-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) and one channel from the moisture sounding channel (Ch. 1) along with ancillary information from the TC working best track file and the CIMSS ARCHER algorithm (eye size information) to estimate the TC intensity. This validated TCIE data release starts in June 2023 for the constellation CubeSats, and August 2021 for the TROPICS-01/Pathfinder." proprietary TROPICS03URADL2A_1.0 TROPICS03 L2A Unified Resolution Brightness Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3179859133-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Validated Stage-1 version of the Level 2A geolocated brightness temperature with the water vapor sounding channels (Ch. 9 to 12) converted from their native G-band resolution to the temperature sounding channel (F-band) native resolution (i.e., all measurements at the same unified larger resolution). This product is used in the Atmospheric Vertical Temperature Profile (AVTP) retrievals to gain the benefit of averaging the G-band channels (i.e., noise reduction) while maintain the F-band (AVTP) spatial resolution. The conversion uses the Backus-Gilbert technique. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary @@ -13757,7 +13766,7 @@ TROPICS05PRPSL2B_0.2 TROPICS05 Pathfinder L2B Instantaneous Surface Rain Rate TROPICS05URADL2A_0.2 TROPICS05 L2A Unified Resolution Brightness Temperatures V0.2 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2985145612-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS05 satellite, as the Provisional version of the Level 2A geolocated brightness temperature with the water vapor sounding channels (Ch. 9 to 12) converted from their native G-band resolution to the temperature sounding channel (F-band) native resolution (i.e., all measurements at the same unified larger resolution). This product is used in the Atmospheric Vertical Temperature Profile (AVTP) retrievals to gain the benefit of averaging the G-band channels (i.e., noise reduction) while maintain the F-band (AVTP) spatial resolution. The conversion uses the Backus-Gilbert technique. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS06ANTTL1A_1.0 TROPICS06 L1A Orbital Geolocated Native-Resolution Antenna Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3171499640-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS06BRTTL1B_1.0 TROPICS06 L1B Orbital Geolocated Native-Resolution Brightness Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3171499970-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary -TROPICS06MIRSL2B_0.2 TROPICS06 L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V0.2 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2857801590-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS06 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details." proprietary +TROPICS06MIRSL2B_1.0 TROPICS06 L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3255752538-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS06 satellite, as the Validated Stage-1 release of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. " proprietary TROPICS06PRPSL2B_1.0 TROPICS06 Pathfinder L2B Instantaneous Surface Rain Rate (ISRR) V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3254839721-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details." proprietary TROPICS06TCIEL2B_1.0 TROPICS06 L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3280808959-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) and one channel from the moisture sounding channel (Ch. 1) along with ancillary information from the TC working best track file and the CIMSS ARCHER algorithm (eye size information) to estimate the TC intensity. This validated TCIE data release starts in June 2023 for the constellation CubeSats, and August 2021 for the TROPICS-01/Pathfinder." proprietary TROPICS06URADL2A_1.0 TROPICS06 L2A Unified Resolution Brightness Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3179860505-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS06 satellite, as the Validated Stage-1 version of the Level 2A geolocated brightness temperature with the water vapor sounding channels (Ch. 9 to 12) converted from their native G-band resolution to the temperature sounding channel (F-band) native resolution (i.e., all measurements at the same unified larger resolution). This product is used in the Atmospheric Vertical Temperature Profile (AVTP) retrievals to gain the benefit of averaging the G-band channels (i.e., noise reduction) while maintain the F-band (AVTP) spatial resolution. The conversion uses the Backus-Gilbert technique. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary