Amazon Sustainability Data Initiative (ASDI) Cloud Grants

Amazon Sustainability Data Initiative (ASDI) Cloud Grants is sponsored by Amazon Web Services (AWS). This opportunity supports mission-aligned projects and measurable outcomes.

Registry of Open Data on AWS Amazon Sustainability Data Initiative The Amazon Sustainability Data Initiative (ASDI) seeks to accelerate sustainability research and innovation by minimizing the cost and time required to acquire and analyze large sustainability datasets. These datasets are publicly available to anyone.

In addition, ASDI provides cloud grants to those interested in exploring the use of AWS’ technology and scalable infrastructure to solve big, long-term sustainability challenges with this data. The dual-pronged approach allows sustainability researchers to analyze massive amounts of data in mere minutes, regardless of where they are in the world or how much local storage space or computing capacity they can access.

Learn more about ASDI here.

Categories: weather , climate , water , agriculture , satellite imagery , elevation , air quality , energy , disaster response , oceans , socioeconomic , infrastructure , ecosystems , biodiversity , sustainability Search datasets (currently 13 matching datasets ) 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 . (EXPERIMENTAL) NOAA FourCastNet Global Forecast System (FourCastNetGFS) (EXPERIMENTAL) The FourCastNet Global Forecast System (FourCastNetGFS) is an experimental system set up by the National Centers for Environmental Prediction (NCEP) to produce medium range global forecasts.

The model runs on a 0. 25 degree latitude-longitude grid (about 28 km) and 13 pressure levels. The model produces forecasts 4 times a day at 00Z, 06Z, 12Z and 18Z cycles.

Major atmospheric and surface fields including temperature, wind components, geopotential height, relative humidity and 2 meter temperature and 10 meter winds are available. The products are 6 hourly forecasts up to 10 days. The data format is ...

AI Weather Prediction (AIWP) Model Reforecasts Managed by Dr. Jacob Radford ( jacob. radford@noaa. gov ) This is an archive of pure AI-based weather prediction reforecasts produced collaboratively between the Cooperative Institute for Research in the Atmosphere (CIRA) and the NOAA Global Systems Laboratory (NOAA-GSL) .

Currently, FourCastNetv2-small , Pangu-Weather , and GraphCast are included, with more models to come. Each of these models has been initialized with both NOAA GFS (directories with no extension) and ECMWF IFS initial conditions (directories ending in "_IFS"). The datasets are updated with near-real-time data twice per day (00Z and 12Z initializations).

FourCastNetv2-small and Pangu-Weather are available from 10/2020 to present ... Atmospheric Models from Météo-France Global and high-resolution regional atmospheric models from Météo-France. ARPEGE World covers the entire world at a base horizontal resolution of 0.

5° (~55km) between grid points, it predicts weather out up to 114 hours in the future. ARPEGE Europe covers Europe and North-Africa at a base horizontal resolution of 0. 1° (~11km) between grid points, it predicts weather out up to 114 hours in the future.

AROME France covers France at a base horizontal resolution of 0. 025° (~2. 5km) between grid points, it predicts weather out up to 42 hours in the future.

AROME France HD covers France and neighborhood a CRC-SAS/SISSA historical seasonal and subseasonal forecast database En el marco del Sistema de Información de Sequías del Sur de Sudamérica (SISSA) se ha desarrollado una base de predicciones en escala subestacional y estacional con datos corregidos y sin corregir, con el propósito que permita estudiar predictibilidad en distintas escalas y también que sirva para alimentar modelos de sectores como agricultura e hidrología.

La base contiene datos en escala diaria entre 2000-2019 (sin corregir) y 2010-2019 (corregidos) para diversas variables incluyendo: temperatura media, máxima y mínima, así como también lluvia, viento medio y otras variables pensadas para alimentar modelos hidrológicos y de cultivo.

La base de datos abarca toda el área del Centro Regional del Clima para el sur de sudamérica (CRC-SAS), abarcando desde Bolivia y centro-sur de Brasil hasta la Patagonia incluyendo los países miembros como Chile, Argentina, Brasil, Paraguay, Uruguay y Bolivia. La base fue generada a p... Central Weather Bureau OpenData Managed by Central Weather Bureau Various kinds of weather raw data and charts from Central Weather Bureau.

Danish Meteorological Institute (DMI) Reanalysis dataset v0.

5 Managed by Danish Meteorological Institute DANRA is a high-resolution meteorological reanalysis dataset for Denmark and Northwestern Europe covering the period September 1990 to December 2023 East Coast Community Ocean Forecast System (ECCOFS) The East Coast Community Ocean Forecast System (ECCOFS) is a data assimilating ocean analysis and forecast system being developed by Rutgers University, the University of California Santa Cruz, Fathom Science Inc., and the National Ocean Service (NOS) of NOAA for transition to operations at NCEP in 2028.

The ECCOFS domain spans the eastern seaboard of North America and Intra-Americas Seas from the Grand Banks of Newfoundland in the north to the mouth of the Orinoco River, Venezuela, in the south. ECCOFS will complement the existing WCOFS (West Coast Operational Forecast System) to achieve complete forecast coverage of U.S. territori...

Finnish Meteorological Institute Weather Radar Data Managed by Finnish Meteorological Institute The up-to-date weather radar from the FMI radar network is available as Open Data. The data contain both single radar data along with composites over Finland in GeoTIFF and HDF5-formats. Available composite parameters consist of radar reflectivity (DBZ), rainfall intensity (RR), and precipitation accumulation of 1, 12, and 24 hours.

Single radar parameters consist of radar reflectivity (DBZ), radial velocity (VRAD), rain classification (HCLASS), and Cloud top height (ETOP 20). Raw volume data from singe radars are also provided in HDF5 format with ODIM 2. 3 conventions.

Radar data becomes avail... Managed by The Weather Company A zarr-formatted dataset of 1836 reforecast cases (approx. 5 years) from The Weather Company GRAF (Global high-Resolution Atmospheric Forecasting) model, a version of the National Center for Atmospheric Research (NCAR) Model for Predictions Across Scales (MPAS).

GRAF is global, but the configuration for this reforecast had a mesh refinement to approx. 4 km over the US, Caribbean Basin, and Europe, and 15 km elsewhere. This model was designed to run much of its computation on graphical processing units, with this development assisted by NVIDIA.

The 1836 cases (approx. 5 years) were generated fr... Managed by Finnish Meteorological Institute HIRLAM (High Resolution Limited Area Model) is an operational synoptic and mesoscale weather prediction model managed by the Finnish Meteorological Institute.

IDEAM - Colombian Radar Network Historical and one-day delay data from the IDEAM radar network. Met Office Blended Probabilistic Forecast – Global gridded percentiles This product provides percentile weather forecasts. The grid resolution is approximately 20km and covers the whole globe.

It is produced by the Met Office IMPROVER Blended Probabilistic Forecast system. It is available in NetCDF format. Blended Probabilistic Forecast data is derived from the Met Office's operational NWP (Numerical Weather Prediction) ensembles and nowcasts.

To give more reliable predictions, these are then blended and calibrated using the IMPROVER pipeline, and verified using spread–skill and reliability checks. This is 1 of 8 Blended Probabilistic Forecast products publishe... Met Office Blended Probabilistic Forecast – Global gridded probabilities This product provides gridded probabilistic weather forecasts.

The grid resolution is approximately 20km and covers the whole globe. It is produced by the Met Office IMPROVER Blended Probabilistic Forecast system. It is available in NetCDF format.

Blended Probabilistic Forecast data is derived from the Met Office's operational NWP (Numerical Weather Prediction) ensembles and nowcasts. To give more reliable predictions, these are then blended and calibrated using the IMPROVER pipeline, and verified using spread–skill and reliability checks. This is 1 of 8 Blended Probabilistic Forecast produc...

Met Office Blended Probabilistic Forecast – Global spot percentiles This product provides percentile weather forecasts for 5,956 sites (or spots) across the globe. It is produced by the Met Office IMPROVER Blended Probabilistic Forecast system. It is available in NetCDF format.

Blended Probabilistic Forecast data is derived from the Met Office's operational NWP (Numerical Weather Prediction) ensembles and nowcasts. To give more reliable predictions, these are then blended and calibrated using the IMPROVER pipeline, and verified using spread–skill and reliability checks. This is 1 of 8 Blended Probabilistic Forecast products published by the Met Office on the Registry of Open Data on AWS.

Data is available for the Global and UK domains, as gridded and spot (site-specific), and represented as percentiles and probabilities. Met Office Blended Probabilistic Forecast – Global spot probabilities This product provides probabilistic weather forecasts for 5,956 sites (or spots) across the globe. It is produced by the Met Office IMPROVER Blended Probabilistic Forecast system.

It is available in NetCDF format. Blended Probabilistic Forecast data is derived from the Met Office's operational NWP (Numerical Weather Prediction) ensembles and nowcasts. To give more reliable predictions, these are then blended and calibrated using the IMPROVER pipeline, and verified using spread–skill and reliability checks.

This is 1 of 8 Blended Probabilistic Forecast products published by the Met Office on the Registry of Open Data on AWS. Data is available for the Global and UK domains, as gridded and spot (site-specific), and represented as per... Met Office Blended Probabilistic Forecast – UK Spot Percentiles This product provides percentile weather forecasts for 7,213 sites (or spots) across the United Kingdom, Ireland and parts of Western Europe.

It is produced by the Met Office IMPROVER Blended Probabilistic Forecast system. It is available in NetCDF format. Blended Probabilistic Forecast data is derived from the Met Office's operational NWP (Numerical Weather Prediction) ensembles and nowcasts.

To give more reliable predictions, these are then blended and calibrated using the IMPROVER pipeline, and verified using spread–skill and reliability checks. This is 1 of 8 Blended Probabilistic Forecast products published by the Met Office on the Registry of Open Data on AWS. Data is available for the Global and UK domains, as gridded and spot (site-specific), and represented as percentiles ...

Met Office Blended Probabilistic Forecast – UK Spot Probabilities This product provides probabilistic weather forecasts for 7,213 sites (or spots) across the United Kingdom, Ireland and parts of Western Europe. It is produced by the Met Office IMPROVER Blended Probabilistic Forecast system. It is available in NetCDF format.

Blended Probabilistic Forecast data is derived from the Met Office's operational NWP (Numerical Weather Prediction) ensembles and nowcasts. To give more reliable predictions, these are then blended and calibrated using the IMPROVER pipeline, and verified using spread–skill and reliability checks. This is 1 of 8 Blended Probabilistic Forecast products published by the Met Office on the Registry of Open Data on AWS.

Data is available for the Global and UK domains, as gridded and spot (site-specific)... Met Office Blended Probabilistic Forecast – UK gridded percentiles This product provides gridded percentile weather forecasts. The grid resolution is approximately 2km and covers the UK and parts of Western Europe.

It is produced by the Met Office IMPROVER Blended Probabilistic Forecast system. It is available in NetCDF format. Blended Probabilistic Forecast data is derived from the Met Office's operational NWP (Numerical Weather Prediction) ensembles and nowcasts.

To give more reliable predictions, these are then blended and calibrated using the IMPROVER pipeline, and verified using spread–skill and reliability checks. This is 1 of 8 Blended Probabilistic ... Met Office Blended Probabilistic Forecast – UK gridded probabilities This product provides gridded probabilistic weather forecasts.

The grid resolution is approximately 2km and covers the UK and parts of Western Europe. It is produced by the Met Office IMPROVER Blended Probabilistic Forecast system. It is available in NetCDF format.

Blended Probabilistic Forecast data is derived from the Met Office's operational NWP (Numerical Weather Prediction) ensembles and nowcasts. To give more reliable predictions, these are then blended and calibrated using the IMPROVER pipeline, and verified using spread–skill and reliability checks. This is 1 of 8 Blended Probabilist...

Met Office Global Deterministic 10km on a 2-year rolling archive A numerical weather prediction forecast for the whole globe, with a resolution of approximately 0. 09 degrees i.e. 10km (2,560 x 1,920 grid points). The data is available as NetCDF files.

It's offered on a free, unsupported basis, so we don't recommend using it for any critical business purposes. The global deterministic model is a global configuration of the Unified Model, which is the Met Office’s flagship Numerical Weather Prediction model. The model’s initial state is kept close to the real atmosphere using hybrid 4D-Var data assimilation.

The archive contains data from the past two years. The data is typ... Met Office Global Ensemble Prediction System (MOGREPS-G) on a 30-day rolling archive A numerical weather prediction model that produces forecasts for the whole globe up to a week ahead.

The projection used is the Equirectangular Latitude-Longitude and the grid resolution is 20km. The data is available as NetCDF files. It's offered on a free, unsupported basis, so we don’t recommend using it for any critical business purposes.

Met Office Global Ensemble Prediction System (MOGREPS-G) is a global configuration of the Unified Model, which is the Met Office's flagship Numerical Weather Prediction model. The archive contains 30 days of data. The data is typically available approximately 10-11...

Met Office Global Ocean model on a 2-year rolling archive The Global Ocean component of the Met Office Global Coupled Atmosphere-Land-Ocean-Ice system which has been running in operations since May 2022.

The system provides a global physical analysis and coupled forecast products providing 3D daily mean fields of temperature and salinity, zonal and meridional velocities; 2D daily mean fields of sea surface height, bottom temperature, mixed layer depth, sea ice fraction, sea ice thickness and sea ice zonal and meridional velocities; and instantaneous hourly fields for sea surface height, sea surface temperature and surface currents.

The Met Office Glo... Met Office Global Wave model on a 2-year rolling archive The Met Office runs global wave forecast models to support marine safety and operational decision making. Met Office configurations are developed to be run using the community wave model WAVEWATCH IIITM.

The global wave configuration is designed to generate accurate forecasts for open waters of the world’s oceans and larger seas. The Met Office wave models are forced using wind data from the Met Office Global Atmospheric Hi-Res Model. The global wave model is run to provide a five day outlook for wave characteristics defining height, period and direction of waves within a given sea-state.

The ... Met Office Global and Regional Ensemble Prediction System - UK (MOGREPS-UK) on a 30-day rolling archive A numerical weather prediction model that produces forecasts for the UK for the next 5 days. Parameters including temperature, pressure, wind, humidity, etc. are forecast at grid points separated by about 2.

2 km, and the model has multiple vertical levels. The data is available as NetCDF files. It's offered on a free, unsupported basis, so we don’t recommend using it for any critical business purposes.

Met Office Global and Regional Ensemble Prediction System - UK (MOGREPS-UK) is a UK configuration of the Unified Model, which is the Met Office's flagship Numerical Weather Prediction model. Met Office NWS Ocean model on a 2-year rolling archive The Northwest European continental shelf physical ocean model predicts temperature, salinity and circulation for waters surrounding the UK.

Ocean physics analysis provides a 6-day forecast for the North-West European Atlantic shelf at 1. 5km resolution: Met Office NWS Wave model on a 2-year rolling archive Northwest European continental shelf regional wave model predicting sea-state and various sea and swell wave characteristics for waters surrounding the UK.

The Met Office runs global and regional wave forecast models to support marine safety and operational decision making. Met Office configurations are developed to be run using the community wave model WAVEWATCH IIITM. The global wave configuration is designed to generate accurate forecasts for open waters of the world's oceans and larger seas, whilst regional configurations are run in order to improve accuracy closer to the coast.

Met Office UK Deterministic (UKV)2km on a 2-year rolling archive A high-resolution gridded weather forecast for the UK, with a resolution of 0. 018 degrees, projected on to a 2km horizontal grid. The data is available as NetCDF files.

It's offered on a free, unsupported basis, so we don’t recommend using it for any critical business purposes. Based on the Met Office UKV model, which is a deterministic, numerical weather prediction model for the UK and Ireland. It is a UK configuration of the Unified Model, which is the Met Office’s flagship Numerical Weather Prediction model.

The archive contains data from the past two years. The data is typically available approximately 3 to 6 hours after... Met Office UK Land Surface Observations Land surface weather observations for 31 parameters from over 250 locations across the Met Office UK land observation network.

The data is available as CSV files. You can use it to monitor the latest weather affecting a specific location so you can plan for your business or operations. The observations are produced every minute and transmitted to the Amazon Registry of Open Data every hour.

They’re available for a rolling 7-day period (168 hours). All locations in the observation network are within the bounding box: On average they are about 40km apart, Met Office UK Marine Observations Marine surface weather observations for 32 parameters from 69 locations across the Met Office marine observation network. Observations are available for a rolling 7-day period (168 hours).

The data is available as CSV files. The data comes from moored buoys, light vessels and ships with automatic weather stations onboard. Buoys and light vessels are static and you can view their locations on the Met Office Marine Observations page .

You can use the data to monitor the latest weather affecting a specific marine location so you can plan for your business or operations. Join the Met Office researc ... Met Office UK Radar Observations on a 2-year rolling archive The United Kingdom Composite, Surface Rain Rate Estimate is an international radar composite produced by Met Office (UK).

This is a composite, radar reflectivity derived, surface rain rate estimate product in HDF5 code from stations covering the United Kingdom. Real-time and archival data from the Next Generation Weather Radar (NEXRAD) network....

NOAA - hourly position, current, and sea surface temperature from drifters 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 numbe ... NOAA Climate Forecast System (CFS) The Climate Forecast System (CFS) is a model representing the global interaction between Earth's oceans, land, and atmosphere.

Produced by several dozen scientists under guidance from the National Centers for Environmental Prediction (NCEP), this model offers hourly data with a horizontal resolution down to one-half of a degree (approximately 56 km) around Earth for many variables.

CFS uses the latest scientific approaches for taking in, or assimilating, observations from data sources including surface observations, upper air balloon observations, aircraft observations, and satellite obser...

NOAA EAGLE (Experimental AI Global and Limited-Area Ensemble) Global Deterministic and Ensemble Forecasts NOAA Global Data Assimilation (DA) Test Data The Unified Forecast System (UFS) is a community-based, coupled, comprehensive Earth Modeling System. It supports multiple applications with different forecast durations and spatial domains.

The Global Data Assimilation System (GDAS) Application (App) is being used as the basis for uniting the Global Workflow and Global Forecast System (GFS) model with Joint Effort for Data assimilation Integration (JEDI) capabilities. The National Centers for Environmental Prediction (NCEP) use GDAS to interpolate data from various observing systems and instruments onto a three-dimensional grid. GDAS obtain ...

NOAA Global Ensemble Forecast System (GEFS) The Global Ensemble Forecast System (GEFS), previously known as the GFS Global ENSemble (GENS), is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental Prediction (NCEP) started the GEFS to address the nature of uncertainty in weather observations, which is used to initialize weather forecast models.

The GEFS attempts to quantify the amount of uncertainty in a forecast by generating an ensemble of multiple forecasts, each minutely different, or perturbed, from the original observations. With global coverage, GEFS is produced fo...

NOAA Global Ensemble Forecast System (GEFS) Re-forecast NOAA has generated a multi-decadal reanalysis and reforecast data set to accompany the next-generation version of its ensemble prediction system, the Global Ensemble Forecast System, version 12 (GEFSv12). Accompanying the real-time forecasts are “reforecasts” of the weather, that is, retrospective forecasts spanning the period 2000-2019.

These reforecasts are not as numerous as the real-time data; they were generated only once per day, from 00 UTC initial conditions, and only 5 members were provided, with the following exception. Once weekly, an 11-member reforecast was generated, and these ex... NOAA Global Forecast System (GFS) NOTE - Upgrade NCEP Global Forecast System to v16.

3. 0 - Effective November 29, 2022 See notification HERE The Global Forecast System (GFS) is a weather forecast model produced by the National Centers for Environmental Prediction (NCEP). Dozens of atmospheric and land-soil variables are available through this dataset, from temperatures, winds, and precipitation to soil moisture and atmospheric ozone concentration.

The entire globe is covered by the GFS at a base horizontal resolution of 18 miles (28 kilometers) between grid points, which is used by the operational forecasters who predict weather NOAA Global Forecast System (GFS) netCDF Formatted Data The Global Forecast System (GFS) is a weather forecast model produced by the National Centers for Environmental Prediction (NCEP).

Dozens of atmospheric and land-soil variables are available through this dataset, from temperatures, winds, and precipitation to soil moisture and atmospheric ozone concentration. The GFS data files stored here can be immediately used for OAR/ARL’s NOAA-EPA Atmosphere-Chemistry Coupler Cloud (NACC-Cloud) tool , and are in a Network Common Data Form (netCDF), which is a very common format used across the scientific community.

These particular GFS files contain a comprehensive number of global atmosphere/land variables at a relatively high spati ... NOAA Global Surface Summary of Day Global Surface Summary of the Day is derived from The Integrated Surface Hourly (ISH) dataset. The ISH dataset includes global data obtained from the USAF Climatology Center, located in the Federal Climate Complex with NCDC.

The latest daily summary data are normally available 1-2 days after the date-time of the observations used in the daily summaries. The online data files begin with 1929 and are at the time of this writing at the Version 8 software level. Over 9000 stations' data are typically available.

The daily elements included in the dataset (as available from each station) are: NOAA HYSPLIT-compatible meteorological data archives The HYSPLIT model is a complete system for computing simple air parcel trajectories, as well as complex transport, dispersion, chemical transformation, and deposition simulations.

HYSPLIT continues to be one of the most extensively used atmospheric transport and dispersion models in the atmospheric sciences community. A common application is a back trajectory analysis to determine the origin of air masses and establish source-receptor relationships. HYSPLIT has also been used in a variety of simulations describing the atmospheric transport, dispersion, and deposition of pollutants and hazardou...

NOAA High-Resolution Rapid Refresh (HRRR) Model The HRRR is a NOAA real-time 3-km resolution, hourly updated, cloud-resolving, convection-allowing atmospheric model, initialized by 3km grids with 3km radar assimilation. Radar data is assimilated in the HRRR every 15 min over a 1-h period adding further detail to that provided by the hourly data assimilation from the 13km radar-enhanced Rapid Refresh.

The HRRR ZARR formatted data was originally generated by the University of Utah under a grant provided by NOAA. They are are continuing to publish ZARR versions of HRRR data. For information about data in the s3://hrrrzarr/ please contact &#x ...

NOAA Hurricane Analysis and Forecast System (HAFS) The last several hurricane seasons have been active with records being set for the number of tropical storms and hurricanes in the Atlantic basin. These record-breaking seasons underscore the importance of accurate hurricane forecasting. Imperative to increased forecasting skill for hurricanes is the development of the Hurricane Forecast Analysis System or HAFS.

To accelerate improvements in hurricane forecasting, this project has the following goals: To improve the HAFS.

The HAFS is NOAA’s next-generation multi-scale numerical model, with data assimilation package and ocean coupling, which will provide an op NOAA Integrated Surface Database (ISD) The Integrated Surface Database (ISD) consists of global hourly and synoptic observations compiled from numerous sources into a gzipped fixed width format. ISD was developed as a joint activity within Asheville's Federal Climate Complex.

The database includes over 35,000 stations worldwide, with some having data as far back as 1901, though the data show a substantial increase in volume in the 1940s and again in the early 1970s. Currently, there are over 14,000 "active" stations updated daily in the database. The total uncompressed data volume is around 600 gigabytes; however, it ...

NOAA Multi-Radar/Multi-Sensor System (MRMS) The MRMS system was developed to produce severe weather, transportation, and precipitation products for improved decision-making capability to improve hazardous weather forecasts and warnings, along with hydrology, aviation, and numerical weather prediction.

MRMS is a system with fully-automated algorithms that quickly and intelligently integrate data streams from multiple radars, surface and upper air observations, lightning detection systems, satellite observations, and forecast models. Numerous two-dimensional multiple-sensor products offer assistance for hail, wind, tornado, quantitative precipitation estimations, co...

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

NOAA NASA Joint Archive (NNJA) of Observations for Earth System Reanalysis The NOAA NASA Joint Archive (NNJA) of Observations for Earth System Reanalysis is a curated joint observation archive containing Earth system data from 1979 to present prepared by teams at NOAA's Physical Sciences Laboratory and NASA's Global Modeling and Assimilation Office.

The goal is to foster collaboration across organizations and develop the ability for direct comparison of Earth System reanalysis results. Providing a singular dataset for observation input use will allow reanalyses to be compared on their unique development qualities by removing the variation from using different...

NOAA National Air Quality Forecast Capability (NAQFC) Regional Model Guidance The National Air Quality Forecasting Capability (NAQFC) dataset contains model-generated air quality (AQ) forecast guidance from three different prediction systems. The first system is a coupled weather and atmospheric chemistry numerical forecast model, known as the Air Quality Model (AQM).

It is used to produce forecast guidance for ozone (O3) and particulate matter that is less than or equal to 2. 5 micrometers in diameter (PM2. 5).

Prior to May 14, 2024, AQM predictions were derived using the EPA’s Community Multiscale Air Quality (CMAQ) model, driven by meteorological fields from NCEP’s operational weather forecast models, ...

NOAA National Blend of Models (NBM) The National Blend of Models (NBM) is a nationally consistent and skillful suite of calibrated forecast guidance based on a blend of both NWS and non-NWS numerical weather prediction model data and post-processed model guidance. The goal of the NBM is to create a highly accurate, skillful and consistent starting point for the gridded forecast.

NOAA National Blend of Models (NBM) Parallel The National Blend of Models (NBM) is a nationally consistent and skillful suite of calibrated forecast guidance based on a blend of both NWS and non-NWS numerical weather prediction model data and post-processed model guidance. The goal of the NBM is to create a highly accurate, skillful and consistent starting point for the gridded forecast.

This dataset contains data from the current parallel version of the NBM which is a test version, featuring many changes, that is a candidate to be implemented into operations following a careful vetting process. NOAA National Digital Forecast Database (NDFD) The National Digital Forecast Database (NDFD) is a suite of gridded forecasts of sensible weather elements (e.g., cloud cover, maximum temperature).

Forecasts prepared by NWS field offices working in collaboration with the National Centers for Environmental Prediction (NCEP) are combined in the NDFD to create a seamless mosaic of digital forecasts from which operational NWS products are generated. The most recent data is under the opnl and expr prefixes. A copy is also placed under the wmo prefix.

The wmo prefix is structured like so: wmo/<parameter>/<year>/&... NOAA North American Mesoscale Forecast System (NAM) The North American Mesoscale Forecast System (NAM) is one of the National Centers For Environmental Prediction’s (NCEP) major models for producing weather forecasts. NAM generates multiple grids (or domains) of weather forecasts over the North American continent at various horizontal resolutions.

Each grid contains data for dozens of weather parameters, including temperature, precipitation, lightning, and turbulent kinetic energy. NAM uses additional numerical weather models to generate high-resolution forecasts over fixed regions, and occasionally to follow significant weather events like hur...

NOAA North American Multi-Model Ensemble (NMME) The North American Multi-Model Ensemble (NMME) is an experimental multi-model seasonal forecasting system consisting of coupled models from US modeling centers including NOAA/NCEP, NOAA/GFDL, NCAR, NASA, and Canada's ECCC.

The need for the development of NMME operational predictive capability was recommended in US National Academies report "Assessment of Intraseasonal to Interannual Climate Prediction and Predictability". Indeed, the national effort is