The Registry of Open Data on AWS is now available on AWS Data Exchange
All datasets on the Registry of Open Data are now discoverable on AWS Data Exchange alongside 3,000+ existing data products from category-leading data providers across industries. Explore the catalog to find open, free, and commercial data sets. Learn more about AWS Data Exchange

About

This registry exists to help people discover and share datasets that are available via AWS resources. See recent additions and learn more about sharing data on AWS.

See all usage examples for datasets listed in this registry tagged with sustainability.


Search datasets (currently 13 matching datasets)

You are currently viewing a subset of data tagged with sustainability.


Add to this registry

If you want to add a dataset or example of how to use a dataset to this registry, please follow the instructions on the Registry of Open Data on AWS GitHub repository.

Unless specifically stated in the applicable dataset documentation, datasets available through the Registry of Open Data on AWS are not provided and maintained by AWS. Datasets are provided and maintained by a variety of third parties under a variety of licenses. Please check dataset licenses and related documentation to determine if a dataset may be used for your application.


Tell us about your project

If you have a project using a listed dataset, please tell us about it. We may work with you to feature your project in a blog post.

NASA Prediction of Worldwide Energy Resources (POWER)

agricultureair qualityanalyticsarchivesatmosphereclimateclimate modeldata assimilationdeep learningearth observationenergyenvironmentalforecastgeosciencegeospatialglobalhistoryimagingindustrymachine learningmachine translationmetadatameteorologicalmodelnetcdfopendapradiationsatellite imagerysolarstatisticssustainabilitytime series forecastingwaterweatherzarr

NASA's goal in Earth science is to observe, understand, and model the Earth system to discover how it is changing, to better predict change, and to understand the consequences for life on Earth. The Applied Sciences Program serves NASA and Society by expanding and accelerating the realization of societal and economic benefits from Earth science, information, and technology research and development.

The NASA Prediction Of Worldwide Energy Resources (POWER) Project, a NASA Applied Sciences program, improves the accessibility and usage NASA Earth Observations (EO) supporting community research in three focus areas: 1) renewable energy development, 2) building energy efficiency, and 3) agroclimatology applications. POWER can help communities be resilient amid observed climate variability through the easy access of solar and meteorological data via a variety of access methods.

The latest POWER version includes hourly-based source Analysis Ready Data (ARD), in addition to enhanced daily, monthly, annual, and climatology ARD. The daily time-series spans 40 years for meteorology available from 1981 and solar-based parameters start in 1984. The hourly source data are from Clouds and the Earth's Radiant Energy System (CERES) and Global Modeling and Assimilation Office (GMAO), spanning 20 years from 2001. The hourly data will provide users the ARD needed to model the energy performance of building systems, providing information directly amenable to decision support tools introducing the industry standard EPW (EnergyPlus Weather file).

POWER also provides parameters at daily, monthly, annual, and user-defined time periods, spanning from 1984 through to within a week of real time. Additionally, POWER provides are user-defined analytic capabilities, including custom climatologies and climatological-based reports for parameter anomalies, ASHRAE® compatible climate design condition statistics, and building climate zones.

The ARD and climate analytics will be readily accessible through POWER's integrated services suite, including the Data Access Viewer (DAV). The DAV has recently been improved to incorporate updated parameter groupings, new analytical capabilities, and the new data formats. POWER also provides a complete API (Application Programming Interface) that allows uses...

Details →

Usage examples

See 18 usage examples →

ESA WorldCover

agriculturecogdisaster responseearth observationgeospatialland coverland usemachine learningmappingnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

The European Space Agency (ESA) WorldCover product provides global land cover maps for 2020 & 2021 at 10 m resolution based on Copernicus Sentinel-1 and Sentinel-2 data. The WorldCover product comes with 11 land cover classes and has been generated in the framework of the ESA WorldCover project, part of the 5th Earth Observation Envelope Programme (EOEP-5) of the European Space Agency. A first version of the product (v100), containing the 2020 map was released in October 2021. The 2021 map was released in October 2022 using an improved algorithm (v200). The WorldCover 2020 and 2021 maps we...

Details →

Usage examples

See 15 usage examples →

Digital Earth Africa Global Mangrove Watch

coastalcogdeafricaearth observationgeospatialland covernatural resourcesatellite imagerystacsustainability

The Global Mangrove Watch (GMW) dataset is a result of the collaboration between Aberystwyth University (U.K.), solo Earth Observation (soloEO; Japan), Wetlands International the World Conservation Monitoring Centre (UNEP-WCMC) and the Japan Aerospace Exploration Agency (JAXA). The primary objective of producing this dataset is to provide countries lacking a national mangrove monitoring system with first cut mangrove extent and change maps, to help safeguard against further mangrove forest loss and degradation. The Global Mangrove Watch dataset (version 2) consists of a global baseline map of ...

Details →

Usage examples

See 13 usage examples →

Digital Earth Africa CHIRPS Rainfall

agricultureclimatecogdeafricaearth observationfood securitygeospatialmeteorologicalsatellite imagerystacsustainability

Digital Earth Africa (DE Africa) provides free and open access to a copy of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) monthly and daily products over Africa. The CHIRPS rainfall maps are produced and provided by the Climate Hazards Center in collaboration with the US Geological Survey, and use both rain gauge and satellite observations. The CHIRPS-2.0 Africa Monthly dataset is regularly indexed to DE Africa from the CHIRPS monthly data. The CHIRPS-2.0 Africa Daily dataset is likewise indexed from the CHIRPS daily data. Both products have been converted to clou...

Details →

Usage examples

See 11 usage examples →

Digital Earth Africa Coastlines

climatecoastaldeafricaearth observationgeospatialsatellite imagerysustainability

Africa's long and dynamic coastline is subject to a wide range of pressures, including extreme weather and climate, sea level rise and human development. Understanding how the coastline responds to these pressures is crucial to managing this region, from social, environmental and economic perspectives. The Digital Earth Africa Coastlines (provisional) is a continental dataset that includes annual shorelines and rates of coastal change along the entire African coastline from 2000 to the present. The product combines satellite data from the Digital Earth Africa program with tidal modelling t...

Details →

Usage examples

See 11 usage examples →

Digital Earth Africa Cropland Extent Map (2019)

agriculturecogdeafricaearth observationfood securitygeospatialsatellite imagerystacsustainability

Digital Earth Africa's cropland extent map (2019) shows the estimated location of croplands in Africa for the period January to December 2019. Cropland is defined as: "a piece of land of minimum 0.01 ha (a single 10m x 10m pixel) that is sowed/planted and harvest-able at least once within the 12 months after the sowing/planting date." This definition will exclude non-planted grazing lands and perennial crops which can be difficult for satellite imagery to differentiate from natural vegetation. This provisional cropland extent map has a resolution of 10m, and was built using Cope...

Details →

Usage examples

See 9 usage examples →

Digital Earth Africa Fractional Cover

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsustainability

Fractional cover (FC) describes the landscape in terms of coverage by green vegetation, non-green vegetation (including deciduous trees during autumn, dry grass, etc.) and bare soil. It provides insight into how areas of dry vegetation and/or bare soil and green vegetation are changing over time. The product is derived from Landsat satellite data, using an algorithm developed by the Joint Remote Sensing Research Program. Digital Earth Africa's FC service has two components. Fractional Cover is estimated from each Landsat scene, providing measurements from individual days. Fractional Cover...

Details →

Usage examples

See 9 usage examples →

NASA Earth Exchange (NEX) Data Collection

climateCMIP5natural resourcesustainability

A collection of downscaled climate change projections, derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) [Taylor et al. 2012] and across the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs) [Meinshausen et al. 2011]. The NASA Earth Exchange group maintains the NEX-DCP30 (CMIP5), NEX-GDDP (CMIP5), and LOCA (CMIP5).

Details →

Usage examples

See 8 usage examples →

ASTER L1T Cloud-Optimized GeoTIFFs

cogearth observationgeospatialminingnatural resourcesatellite imagerysustainability

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), 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) product.The precision terrain correction process incorporates GLS2000 digital elevation data with derived ground control points (GCPs) to achieve topographic accuracy for all daytim...

Details →

Usage examples

See 7 usage examples →

10m Annual Land Use Land Cover (9-class)

cogearth observationenvironmentalgeospatialland coverland usemachine learningmappingplanetarysatellite imagerystacsustainability

This dataset, produced by Impact Observatory, Microsoft, and Esri, displays a global map of land use and land cover (LULC) derived from ESA Sentinel-2 imagery at 10 meter resolution for the years 2017 - 2023. Each map is a composite of LULC predictions for 9 classes throughout the year in order to generate a representative snapshot of each year. This dataset was generated by Impact Observatory, which used billions of human-labeled pixels (curated by the National Geographic Society) to train a deep learning model for land classification. Each global map was produced by applying this model to ...

Details →

Usage examples

See 6 usage examples →

Amazonia EO satellite on AWS

agriculturecogdisaster responseearth observationgeospatialimagingsatellite imagerystacsustainability

Imagery acquired by Amazonia-1 satellite. The image files are recorded and processed by Instituto Nacional de Pesquisas Espaciais (INPE) and are converted to Cloud Optimized Geotiff format in order to optimize its use for cloud based applications. WFI Level 4 (Orthorectified) scenes are being ingested daily starting from 08-29-2022, the complete Level 4 archive will be ingested by the end of October 2022.

Details →

Usage examples

See 5 usage examples →

Community Earth System Model Large Ensemble (CESM LENS)

atmosphereclimateclimate modelgeospatialicelandmodeloceanssustainabilityzarr

The Community Earth System Model (CESM) Large Ensemble Numerical Simulation (LENS) dataset includes a 40-member ensemble of climate simulations for the period 1920-2100 using historical data (1920-2005) or assuming the RCP8.5 greenhouse gas concentration scenario (2006-2100), as well as longer control runs based on pre-industrial conditions. The data comprise both surface (2D) and volumetric (3D) variables in the atmosphere, ocean, land, and ice domains. The total data volume of the original dataset is ~500TB, which has traditionally been stored as ~150,000 individual CF/NetCDF files on disk o...

Details →

Usage examples

See 5 usage examples →

ESA WorldCover Sentinel-1 and Sentinel-2 10m Annual Composites

agriculturecogdisaster responseearth observationgeospatialland coverland usemachine learningmappingnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

The WorldCover 10m Annual Composites were produced, as part of the European Space Agency (ESA) WorldCover project, from the yearly Copernicus Sentinel-1 and Sentinel-2 archives for both years 2020 and 2021. These global mosaics consists of four products composites. A Sentinel-2 RGBNIR yearly median composite for bands B02, B03, B04, B08. A Sentinel-2 SWIR yearly median composite for bands B11 and B12. A Sentinel-2 NDVI yearly percentiles composite (NDVI 90th, NDVI 50th NDVI 10th percentiles). A Sentinel-1 GAMMA0 yearly median composite for bands VV, VH and VH/VV (power scaled). Each product is...

Details →

Usage examples

See 5 usage examples →

End-Use Load Profiles for the U.S. Building Stock

citiesclimateenergyenergy modelinggeospatialmetadatamodelopen source softwaresustainabilityutilities

The U.S. Department of Energy (DOE) funded a three-year project, End-Use Load Profiles for the U.S. Building Stock, that culminated in this publicly available dataset of calibrated and validated 15-minute resolution load profiles for all major residential and commercial building types and end uses, across all climate regions in the United States. These EULPs were created by calibrating the ResStock and ComStock physics-based building stock models using many different measured datasets, as described here. This dataset includes load profiles for both the baseline building stock and the building ...

Details →

Usage examples

See 5 usage examples →

Sofar Spotter Archive

climateenvironmentalmeteorologicaloceansoceanssustainabilityweather

This dataset includes archival hourly data from the [Sofar Spotter buoy global network] (https://weather.sofarocean.com/) from 2019 to March 2022.

Details →

Usage examples

See 5 usage examples →

Community Earth System Model v2 Large Ensemble (CESM2 LENS)

atmosphereclimateclimate modelgeospatialicelandmodeloceanssustainabilityzarr

The US National Center for Atmospheric Research partnered with the IBS Center for Climate Physics in South Korea to generate the CESM2 Large Ensemble which consists of 100 ensemble members at 1 degree spatial resolution covering the period 1850-2100 under CMIP6 historical and SSP370 future radiative forcing scenarios. Data sets from this ensemble were made downloadable via the Climate Data Gateway on June 14th, 2021. NCAR has copied a subset (currently ~500 TB) of CESM2 LENS data to Amazon S3 as part of the AWS Public Datasets Program. To optimize for large-scale analytics we have represented ...

Details →

Usage examples

See 4 usage examples →

Indiana Statewide Digital Aerial Imagery Catalog

aerial imageryagriculturecogearth observationgeospatialimagingmappingnatural resourcesustainability

The State of Indiana Geographic Information Office and IOT Office of Technology manage a series of digital orthophotography dating back to 2005. Every year's worth of imagery is available as Cloud Optimized GeoTIFF (COG) files, original GeoTIFF, and other compressed deliverables such as ECW and MrSID. Additionally, each imagery year is organized into a tile grid scheme covering the entire geography of Indiana. All years of imagery are tiled from a 5,000 ft grid or sub tiles depending upon the resolution of the imagery. The naming of the tiles reflects the lower left coordinate from the...

Details →

Usage examples

See 4 usage examples →

NA-CORDEX - North American component of the Coordinated Regional Downscaling Experiment

atmosphereclimateclimate modelgeospatiallandmodelsustainabilityzarr

The NA-CORDEX dataset contains regional climate change scenario data and guidance for North America, for use in impacts, decision-making, and climate science. The NA-CORDEX data archive contains output from regional climate models (RCMs) run over a domain covering most of North America using boundary conditions from global climate model (GCM) simulations in the CMIP5 archive. These simulations run from 1950–2100 with a spatial resolution of 0.22°/25km or 0.44°/50km. This AWS S3 version of the data includes selected variables converted to Zarr format from the original NetCDF. Only daily data a...

Details →

Usage examples

See 4 usage examples →

SILO climate data on AWS

agricultureclimateearth observationenvironmentalmeteorologicalmodelsustainabilitywaterweather

SILO is a database of Australian climate data from 1889 to the present. It provides continuous, daily time-step data products in ready-to-use formats for research and operational applications. SIL...

Details →

Usage examples

See 4 usage examples →

NOAA - hourly position, current, and sea surface temperature from drifters

climateenvironmentalmeteorologicaloceanssustainabilityweather

This dataset includes hourly sea surface temperature and current data collected by satellite-tracked surface drifting buoys ("drifters") of the NOAA Global Drifter Program. The Drifter Data Assembly Center (DAC) at NOAA’s Atlantic Oceanographic and Meteorological Laboratory (AOML) has applied quality control procedures and processing to edit these observational data and obtain estimates at regular hourly intervals. The data include positions (latitude and longitude), sea surface temperatures (total, diurnal, and non-diurnal components) and velocities (eastward, northward) with accompanying uncertainty estimates. Metadata include identification numbers, experiment number, start location and time, end location and time, drogue loss date, death code, manufacturer, and drifter type.

Please note that data from the Global Drifter Program are also available at 6-hourly intervals but derived via alternative methods. The 6-hourly dataset goes back further in time (1979) and may be more appropriate for studies of long-term, low frequency patterns of the oceanic circulation. Yet, the 6-hourly dataset does not resolve fully high-frequency processes such as tides and inertial oscillations as well as sea surface temperature diurnal variability.

[CITING NOAA - hourly position, current, and sea surface temperature from drifters data. Citation for this dataset should include the following information below.]
Elipot, Shane; Sykulski, Adam; Lumpkin, Rick; ...

Details →

Usage examples

See 3 usage examples →

Downscaled Climate Data for Alaska (v1.1, August 2023)

agricultureclimatecoastalearth observationenvironmentalsustainabilityweather

This dataset contains historical and projected dynamically downscaled climate data for the State of Alaska and surrounding regions at 20km spatial resolution and hourly temporal resolution. Select variables are also summarized into daily resolutions. This data was produced using the Weather Research and Forecasting (WRF) model (Version 3.5). We downscaled both ERA-Interim historical reanalysis data (1979-2015) and both historical and projected runs from 2 GCM’s from the Coupled Model Inter-comparison Project 5 (CMIP5): GFDL-CM3 and NCAR-CCSM4 (historical run: 1970-2005 and RCP 8.5: 2006-2100)....

Details →

Usage examples

See 2 usage examples →

PALSAR-2 ScanSAR Turkey & Syria Earthquake (L2.1 & L1.1)

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

JAXA has responded to the Earthquake events in Turkey and Syria by conducting emergency disaster observations and providing data as requested by the Disaster and Emergency Management Authority (AFAD), Ministry of Interior in Turkey, through Sentinel Asia and the International Disaster Charter. Additional information on the event and dataset can be found here. The 25 m PALSAR-2 ScanSAR is normalized backscatter data of PALSAR-2 broad area observation mode with observation width of 350 km. Polarization data are stored as 16-bit digital numbers (DN). The DN values can be converted to gamma naught...

Details →

Usage examples

See 2 usage examples →

Whiffle WINS50 Open Data on AWS

atmosphereelectricitymeteorologicalmodelsustainabilityturbulenceweatherzarr

Large Eddy Simulation (LES) data of the Winds of the North Sea in 2050 (WINS50) project.

Details →

Usage examples

See 2 usage examples →

Community Earth System Model v2 ARISE (CESM2 ARISE)

atmosphereclimateclimate modelgeospatialicelandmodeloceanssustainability

Data from ARISE-SAI Experiments with CESM2

Details →

Usage examples

See 1 usage example →

Coupled Model Intercomparison Project Phase 5 (CMIP5) University of Wisconsin-Madison Probabilistic Downscaling Dataset

climatecoastaldisaster responseenvironmentalmeteorologicaloceanssustainabilitywaterweather

The University of Wisconsin Probabilistic Downscaling (UWPD) is a statistically downscaled dataset based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. UWPD consists of three variables, daily precipitation and maximum and minimum temperature. The spatial resolution is 0.1°x0.1° degree resolution for the United States and southern Canada east of the Rocky Mountains.

The downscaling methodology is not deterministic. Instead, to properly capture unexplained variability and extreme events, the methodology predicts a spatially and temporally varying Probability Density Function (PDF) for each variable. Statistics such as the mean, mean PDF and annual maximum statistics can be calculated directly from the daily PDF and these statistics are included in the dataset. In addition, “standard”, “raw” data is created by randomly sampling from the PDFs to create a “realization” of the local scale given the large-scale from the climate model. There are 3 realizations for temperature and 14 realizations for precipitation. ...

Details →

Usage examples

See 1 usage example →

NOAA Multi-Year Reanalysis of Remotely Sensed Storms (MYRORSS)

agricultureearth observationmeteorologicalnatural resourcesustainabilityweather

The Multi-Year Reanalysis of Remotely Sensed Storms (MYRORSS) consists of radar reflectivity data run through the Multi-Radar, Multi-Sensor (MRMS) framework to create a three-dimensional radar volume on a quasi-Cartesian latitude-longitude grid across the entire contiguous United States. The radar reflectivity grid is also combined with hourly forecast model analyses to produce derived products such as echo top heights and hail size estimates. Radar Doppler velocity data was also processed into two azimuthal shear layer products. The source radar data was from the NEXRAD Level-II archive and the model analyses came from NOAA's Rapid Update Cycle model. Radar reflectivity was quality controlled to remove non-weather echoes and the data set was manually quality contolled to remove errors as revealed through inspection of daily accumulations of the hail size product and the azimuthal shear products. MYRORSS contains data from April 1998 through December 2011. The horizontal resolution is 0.01° by 0.01° and t...

Details →

Usage examples

See 1 usage example →

NOAA U.S. Climate Normals

agricultureclimatemeteorologicalsustainabilityweather

The U.S. Climate Normals are a large suite of data products that provide information about typical climate conditions for thousands of locations across the United States. Normals act both as a ruler to compare today’s weather and tomorrow’s forecast, and as a predictor of conditions in the near future. The official normals are calculated for a uniform 30 year period, and consist of annual/seasonal, monthly, daily, and hourly averages and statistics of temperature, precipitation, and other climatological variables from almost 15,000 U.S. weather stations.

NCEI generates the official U.S. norma
...

Details →

Usage examples

See 1 usage example →

PALSAR-2 ScanSAR CARD4L (L2.2)

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

The 25 m PALSAR-2 ScanSAR is normalized backscatter data of PALSAR-2 broad area observation mode with observation width of 350 km. The SAR imagery was ortho-rectificatied and slope corrected using the ALOS World 3D - 30 m (AW3D30) Digital Surface Model. Polarization data are stored as 16-bit digital numbers (DN). The DN values can be converted to gamma naught values in decibel unit (dB) using the following equation: γ0 = 10*log10(DN2) - 83.0 dB CARD4L stands for CEOS Analysis Ready Data for Land (Level 2.2) data are ortho-rectified and radiometrically terrain-corrected. This datase...

Details →

Usage examples

See 1 usage example →

PALSAR-2 ScanSAR Flooding in Rwanda (L2.1)

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

Torrential rainfall triggered flooding and landslides in many parts of Rwanda. The hardest-hit districts were Ngororero, Rubavu, Nyabihu, Rutsiro and Karongi. According to reports, 14 people have died in Karongi, 26 in Rutsiro, 18 in Rubavu, 19 in Nyabihu and 18 in Ngororero.Rwanda National Police reported that the Mukamira-Ngororero and Rubavu-Rutsiro roads are impassable due to flooding and landslide debris. UNITAR on behalf of United Nations Office for the Coordination of Humanitarian Affairs (OCHA) / Regional Office for Southern & Eastern Africa in cooperation with Rwanda Space Agency ...

Details →

Usage examples

See 1 usage example →

PALSAR-2 ScanSAR Tropical Cycolne Mocha (L2.1)

agriculturecogdisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

Tropical Cyclone Mocha began to form in the Bay of Bengal on 11 May 2023 and continues to intensify as it moves towards Myanmar and Bangladesh.Cyclone Mocha is the first storm to form in the Bay of Bengal this year and is expected to hit several coastal areas in Bangladesh on 14 May with wind speeds of up to 175 km/h.After made its landfall in the coast between Cox’s Bazar (Bangladesh) and Kyaukphyu (Myanmar) near Sittwe (Myanmar). At most, Catastrophic Damage-causing winds was possible especially in the areas of Rakhine State and Chin State, and Severe Damage-causing winds is possible in the ...

Details →

Usage examples

See 1 usage example →

Sentinel-1 SLC dataset for Germany

disaster responseearth observationenvironmentalgeospatialsatellite imagerysustainabilitysynthetic aperture radar

The Sentinel1 Single Look Complex (SLC) unzipped dataset contains Synthetic Aperture Radar (SAR) data from the European Space Agency’s Sentinel-1 mission. Different from the zipped data provided by ESA, this dataset allows direct access to individual swaths required for a given study area, thus drastically minimizing the storage and downloading time requirements of a project. Since the data is stored on S3, users can utilize the boto3 library and s3 get_object method to read the entire content of the object into the memory for processing, without actually having to download it. The Sentinel-1 ...

Details →

Usage examples

See 1 usage example →

UK Earth System Model (UKESM1) ARISE-SAI geoengineering experiment data

atmosphereclimateclimate modelCMIP6geospatialicelandmodeloceanssustainability

Data from the UK Earth System Model (UKESM1) ARISE-SAI experiment. The UKESM1 ARISE-SAI experiment explores the impacts of geoengineering via the injection of sulphur dioxide (SO2) into the stratosphere in order to keep global mean surface air temperature near 1.5 C above the pre-industrial climate. Data includes a five member ensemble of simulations with SO2 injection plus a five member ensemble of SSP2-4.5 simulations from CMIP6 to serve as a reference data set

Details →

Usage examples

See 1 usage example →

CAFE60 reanalysis

climatesustainability

The CSIRO Climate retrospective Analysis and Forecast Ensemble system: version 1 (CAFE60v1) provides a large ensemble retrospective analysis of the global climate system from 1960 to present with sufficiently many realizations and at spatio-temporal resolutions suitable to enable probabilistic climate studies. Using a variant of the ensemble Kalman filter, 96 climate state estimates are generated over the most recent six decades. These state estimates are constrained by monthly mean ocean, atmosphere and sea ice observations such that their trajectories track the observed state while enabling ...

Details →

CCAFS-Climate Data

agricultureclimatefood securitysustainability

High resolution climate data to help assess the impacts of climate change primarily on agriculture. These open access datasets of climate projections will help researchers make climate change impact assessments.

Details →

Grid Algorithms and Data Analytics Library (GADAL)

energyenvironmentalmodelsustainability

The aim of this project is to create an easy-to-use platform where various types of analytics can be performed on a wide range of electrical grid datasets. The aim is to establish an open-source library of algorithms that universities, national labs and other developers can contribute to which can be used on both open-source and proprietary grid data to improve the analysis of electrical distribution systems for the grid modeling community. OEDI Systems Integration (SI) is a grid algorithms and data analytics API created to standardize how data is sent between different modules that are run as...

Details →

High Resolution Downscaled Climate Data for Southeast Alaska

agricultureclimatecoastalearth observationenvironmentalsustainabilityweather

This dataset contains historical and projected dynamically downscaled climate data for the Southeast region of the State of Alaska at 1 and 4km spatial resolution and hourly temporal resolution. Select variables are also summarized into daily resolutions. This data was produced using the Weather Research and Forecasting (WRF) model (Version 4.0). We downscaled both Climate Forecast System Reanalysis (CFSR) historical reanalysis data (1980-2019) and both historical and projected runs from two GCM’s from the Coupled Model Inter-comparison Project 5 (CMIP5): GFDL-CM3 and NCAR-CCSM4 (historical ru...

Details →

NOAA 3-D Surge and Tide Operational Forecast System for the Atlantic Basin (STOFS-3D-Atlantic)

climatecoastaldisaster responseenvironmentalglobalmarine navigationmeteorologicaloceanssustainabilitywaterweather

NOTICE - The Coast Survey Development Laboratory (CSDL) in NOAA/National Ocean Service (NOS)/Office of Coast Survey is upgrading the Surge and Tide Operational Forecast System (STOFS, formerly ESTOFS) to Version 2.1.7. A Service Change Notice (SCN) has been issued and can be found "HERE"

NOAA's Surge and Tide Operational Forecast System: Three-Dimensional Component for the Atlantic Basin (STOFS-3D-Atlantic). STOFS-3D-Atlantic runs daily (at 12 UTC) to provide users with 24-hour nowcasts (analyses of near present conditions) and up to 48-hour forecast guidance of water level conditions, and 2- and 3-dimensional fields of water temperature, salinity, and currents. The water level outputs represent the combined tidal and subtidal water surface elevations and are referenced to NAVD88 in general or geoid referenced where there is no NAVD88 coverage, e.g., Puerto Rico.

STOFS-3D-Atlantic has been developed to serve the marine navigation, weather forecasting, and disaster mitigation user communities. It is developed in a collaborative effort between the NOAA/National Ocean Service (NOS)/Office of Coast Survey, the NOAA/National Weather Service (NWS)/National Centers for Environmental Prediction (NCEP) Central Operations (NCO), and the Virginia Institute of Marine Science.

STOFS-3D-Atlantic employs the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM) as the hydrodynamic model core. Its unstructured grid consists of 2,654,153 nodes and 5,137,229 triangular or quadrilateral elements. Grid resolution is 1.5-2 km near the shoreline, 200-550 m for the floodplain, and up to 10 m for both levees and some small rivers. Along the U.S. coastline, the land boundary of the domain aligns with the 10-m contour above NAVD88, encompassing the coastal transitional zone most vulnerable to coastal and inland flooding.

STOFS-3D-Atlantic makes uses of outputs from the National Water Model (NWM) to include inland hydrology and extreme precipitation effects on coastal flooding; forecast guidance from the NCEP Global Forecast System (GFS) and High-Resolution Rapid Refresh (HRRR) model as the surface meteorological for...

Details →

NOAA Atmospheric Climate Data Records

agricultureclimatemeteorologicalsustainabilityweather

NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).

Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.

Atmospheric Climate Data Records are measurements of several global variables to help characterize the atmosphere
...

Details →

NOAA Fundamental Climate Data Records (FCDR)

agricultureclimatemeteorologicalsustainabilityweather

NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).

Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.

Fundamental CDRs are composed of sensor data (e.g. calibrated radiances, brightness temperatures) that have been
...

Details →

NOAA Oceanic Climate Data Records

agricultureclimatemeteorologicaloceanssustainabilityweather

NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).

Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.

Oceanic Climate Data Records are measurements of oceans and seas both surface and subsurface as well as frozen st
...

Details →

NOAA Terrestrial Climate Data Records

agricultureclimatemeteorologicalsustainabilityweather

NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).

Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.

Terrestrial CDRs are composed of sensor data that have been improved and quality controlled over time, together w
...

Details →

Sentinel Near Real-time Canada Mirror

agriculturedisaster responseearth observationgeospatialsatellite imagerystacsustainabilitysynthetic aperture radar

The official Government of Canada (GC) 🍁 Near Real-time (NRT) Sentinel Mirror connected to the EU Copernicus programme, focused on Canadian coverage. In 2015, Canada joined the Sentinel collaborative ground segment which introduced an NRT Sentinel mirror site for users and programs inside the Government of Canada (GC). In 2022, the Commission signed a Copernicus Arrangement with the Canadian Space Agency with the aim to share each other’s satellite Earth Observation data on the basis of reciprocity. Further to this arrangement as well as ongoing Open Government efforts, the private mirror was...

Details →