NOAA Open Data Dissemination Program
Amazon Web Services has entered into a research agreement with the US National Oceanic and Atmospheric Administration (NOAA) to explore sustainable models to increase the output of open NOAA data. Publicly available NOAA data drives multi-billion dollar industries and critical research efforts. Under this agreement, AWS and its collaborators will look at ways to push more NOAA data to the cloud and build an ecosystem of innovation around it.
Search datasets (currently 13 matching datasets)
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NOAA Geostationary Operational Environmental Satellites (GOES) 16, 17, 18 & 19
agriculturedisaster responseearth observationgeospatialmeteorologicalsatellite imageryweather
NEW GOES-19 Data!! On April 4, 2025 at 1500 UTC, the GOES-19 satellite will be declared the Operational GOES-East satellite. All products and services, including NODD, for GOES-East will transition to GOES-19 data at that time. GOES-19 will operate out of the GOES-East location of 75.2°W starting on April 1, 2025 and through the operational transition. Until the transition time and during the final stretch of Post Launch Product Testing (PLPT), GOES-19 products are considered non-operational regardless of their validation maturity level. Shortly following the transition of GOES-19 to GOES-East, all data distri...
Usage examples
- GOES-2-go is a python package for downloading and plotting plotting GOES data. by Brian K. Blaylock
- SunCast: Solar Irradiance Nowcasting from Geosynchronous Satellite Data by Dhileeban Kumaresan, Richard Wang, Ernesto Martinez, Richard Cziva, Alberto Todeschini, Colorado J Reed, Hossein Vahabi
- Solar irradiance forecasting for the solar powered future by Solcast
- GOES Quick Guides (Spanish) by Anthony Segura García
- Imaging Considerations From a Geostationary Orbit Using the Short Wavelength Side of the Mid-Infrared Water Vapor Absorption Band by N.B. Miller, M.M. Gunshor, A.J. Merrelli, T.S. L'Ecuyer, T.J. Schmit, J.J. Gerth, N.J. Gordillo
NEXRAD on AWS
agricultureearth observationmeteorologicalnatural resourceweather
Real-time and archival data from the Next Generation Weather Radar (NEXRAD) network....
Usage examples
- Into the eye of the storm: NEXRAD Level II open data by Jonni Walker
- Mapping Noaa Nexrad Radar Data With CARTO by Stuart Lynn
- nexradaws on pypi.python.org - python module to query and download Nexrad data from Amazon S3 by Aaron Anderson
- Explore NEXRAD in a Browser-Based Notebook with Scigantic by Scigantic
- Get NEXRAD data from AWS, get severe reports from SPC archive, and plot a loop of them by Russ Schumacher
NOAA Joint Polar Satellite System (JPSS)
agricultureclimatemeteorologicalweather
Near Real Time JPSS data is now flowing! See bucket information on the right side of this page to access products!
Satellites in the JPSS constellation gather global measurements of atmospheric, terrestrial and oceanic conditions, including sea and land surface temperatures, vegetation, clouds, rainfall, snow and ice cover, fire locations and smoke plumes, atmospheric temperature, water vapor and ozone. JPSS delivers key observations for the Nation's essential products and services, including forecasting severe weather like hurricanes, tornadoes and blizzards days in advance, and assessin...
Usage examples
- Python scripts to download and display JPSS NODD datasets by Amy Huff and Rebekah Esmaili
- VIIRS Active Fire Quick Guide by NOAA
- JPSS Science Seminar Annual Digest 2021 by NOAA
- JPSS Science Seminar Annual Digest 2020 by NOAA
- JPSS Proving Ground by NOAA
NOAA Operational Forecast System (OFS)
climatecoastaldisaster responseenvironmentalmeteorologicaloceanswaterweather
ANNOUNCEMENTS: [NOS OFS Version Updates and Implementation of Upgraded Oceanographic Forecast Modeling Systems for Lakes Superior and Ontario; Effective October 25, 2022}(https://www.weather.gov/media/notification/pdf2/scn22-91_nos_loofs_lsofs_v3.pdf)
For decades, mariners in the United States have depended on NOAA's Tide Tables for the best estimate of expected water levels. These tables provide accurate predictions of the astronomical tide (i.e., the change in water level due to the gravitational effects of the moon and sun and the rotation of the Earth); however, they cannot predict water-level changes due to wind, atmospheric pressure, and river flow, which are often significan...
Usage examples
- Skill Assessment of the Delaware River and Bay OFS (DBOFS) by NOAA
- Technical Implementation Notice for Delaware River and Bay OFS by NOAA
- Chesapeake Bay OFS Flyer by NOAA
- Three-Dimensional Hydrodynamic Model Developments for a Delaware River and Bay Nowcast/Forecast System by NOAA
- Tampa Bay OFS: Model Development and Skill Assessment by NOAA
NOAA Water-Column Sonar Data Archive
biodiversityearth observationecosystemsenvironmentalgeospatialmappingoceans
Water-column sonar data archived at the NOAA National Centers for Environmental Information.
Usage examples
- Building an Accessible Archive for Water Column Sonar Data by Carrie Wall
- Reading and Plotting Processed CSV Data by Carrie Wall
- Plotting Raw EK60 Data by Carrie Wall
- pyEcholab - an open-source, python-based toolkit for reading, processing, plotting, and exporting fisheries acoustic echosounder data by Rick Towler, Chuck Anderson, Veronica Martinez, Pamme Crandell
- Water Column Sonar Data Explorer - Map viewer for exploring sonar water column data by NCEI, NOAA
NOAA National Water Model CONUS Retrospective Dataset
agricultureagricultureclimatedisaster responseenvironmentaltransportationweather
The NOAA National Water Model Retrospective dataset contains input and output from multi-decade CONUS retrospective simulations. These simulations used meteorological input fields from meteorological retrospective datasets. The output frequency and fields available in this historical NWM dataset differ from those contained in the real-time operational NWM forecast model. Additionally, note that no streamflow or other data assimilation is performed within any of the NWM retrospective simulations
One application of this dataset is to provide historical context to current near real-time streamflow, soil moisture and snowpack conditions. The retrospective data can be used to infer flow frequencies and perform tempor...
Usage examples
- NOAA's National Water Model: Advancing Operational Hydrology Through Continental-scale Modeling. by Brian Cosgrove, David Gochis, Trey Flowers, Aubrey Dugger, Fred Ogden, Tom Graziano, Ed Clark, et al; 2024
- On Strictly Enforced Mass Conservation Constraints for Modeling the Rainfall-Runoff Process by Jonathan M. Frame, Frederik Kratzert, Hoshin V. Gupta, Paul Ullrich and Grey S. Nearing
- Explore the National Water Model V2.1 Retrospective Dataset in Zarr by James McCreight, Ishita Srivastava, Rich Signell
- Explore the National Water Model V2.0 Retrospective in Zarr by Rich Signell
- Processing the 250 TB NWM dataset with Coiled, Dask, and Xarray by Sarah Johnson (Coiled)
NOAA Rapid Refresh Forecast System (RRFS) [Prototype]
agricultureclimatemeteorologicalweather
The Rapid Refresh Forecast System (RRFS) is the National Oceanic and Atmospheric Administration’s (NOAA) next generation convection-allowing, rapidly-updated ensemble prediction system, currently scheduled for operational implementation in 2026. The operational configuration will feature a 3 km grid covering North America and include deterministic forecasts every hour out to 18 hours, with deterministic and ensemble forecasts to 60 hours four times per day at 00, 06, 12, and 18 UTC.The RRFS will provide guidance to support forecast interests including, but not limited to, aviation, severe convective weather, renewable energy, heavy precipitation, and winter weather on timescales where rapidly-updated guidance is particularly useful....
Usage examples
- Assessment of the data assimilation framework for the Rapid Refresh Forecast System v0.1 and impacts on forecasts of a convective storm case study by Banos, I. H., W. D. Mayfield, G. Ge, L. F. Sapucci, J. R. Carley, and L. Nance
- Community modeling framework underpinning the RRFS - The UFS Short Range Weather Application by UFS Community
- Status and Opportunities with the Rapid Refresh Forecast System by Carley J. R. and C. R. Alexander
- Prototype UFS-Based Rapid Refresh Forecast System (RRFS) on the Cloud by Holt, C., D. Abdi, J. A. Abeles, J. R. Carley, C. W. Harrop, R. Panda, S. Trahan, and C. R. Alexander
- A Limited Area Modeling Capability for the Finite-Volume Cubed-Sphere (FV3) Dynamical Core and Comparison With a Global Two-Way Nest by Black, T. L., J. A. Abeles, B. T. Blake, D. Jovic, E. Rogers, X. Zhang, E. A. Aligo, L. C. Dawson, Y. Lin, E. Strobach, P. C. Shafran, and J. R. Carley
JMA Himawari-8/9
agriculturedisaster responseearth observationgeospatialmeteorologicalsatellite imageryweather
Himawari-9, stationed at 140.7E, owned and operated by the Japan Meteorological Agency (JMA), is a geostationary meteorological satellite, with Himawari-8 as on-orbit back-up, that provides constant and uniform coverage of east Asia, and the west and central Pacific regions from around 35,800 km above the equator with an orbit corresponding to the period of the earth’s rotation. This allows JMA weather offices to perform uninterrupted observation of environmental phenomena such as typhoons, volcanoes, and general weather systems. Archive data back to July 2015 is available for Full Disk (AHI-L...
Usage examples
- Introduction of Himawari-8/9 (pdf file) by JMA
- Himawari-8: Enabling access to key weather data by Manan Dalal, Jena Kent
- Identifying the Causes of Pyrocumulonimbus (PyroCb) by Emiliano Díaz Salas-Porras, Kenza Tazi, Ashwin Braude, Daniel Okoh, Kara D. Lamb, Duncan Watson-Parris, Paula Harder, and Nis Meinert
- Himawari-8 on AWS (pdf file) by ASDI
- Himawari-8 Advanced Himawari Imager Data on AWS (pdf file) by NOAA NESDIS
NOAA National Air Quality Forecast Capability (NAQFC) Regional Model Guidance
agricultureclimatedisaster responseenvironmentalmeteorologicalweather
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, ...
Usage examples
- Development of the next-generation air quality prediction system in the UFS framework: Enhancing predictability of wildfire air quality impacts (2024)(Bull. Amer. Meteor. Soc. In review) by Huang, J.P., I. Stajner, R. Montuoro, F. Yang, K. Wang, H.-C. Huang, C.-H. Jeon, B. Curtis, J. McQueen, H. Liu, B. Baker, D. Tong , Y. Tang, P. Campbell, G. Grell, G. Frost, R. Schwantes, S. Wang, S. Kondragunta, F. Li, and Y. Jung
- Using VIIRS fire radiative power data to simulate biomass burning emissions, plume rise and smoke transport in a real-time air quality modeling system (Proc. 2017 IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS0),Fort Worth, TX, IEEE, 2806–2808) by Ahmadov, R., and Coauthors
- An empirically derived emission algorithm for wind-blown dust (J.Geophys. Res., 115, D16212) by Draxler, R. R., P. Ginoux, and A. F. Stein
- Improving NOAA NAQFC PM2.5 predictions with a bias correction approach (2017, Wea. and Forecasting, 32(2), 407–421) by Huang, J., McQueen, J., Wilczak, J., Djalalova, I., Stajner, I., Shafran, P., Allured, D., Lee, P., Pan, L., Tong, D., Huang, H.-C., DiMego, G., Upadhayay, S., & Delle Monache, L
- Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16 (2022, Geosci. Model Dev., 15, 3281–3313) by Campbell, P.C., and Coauthors
NOAA Global Forecast System (GFS)
agricultureclimatedisaster responseenvironmentalmeteorologicalweather
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
out to 16...
Usage examples
- GFS Warm Restart Files Additional Information by Fanglin Yang
- NOAA Global Forecast System (GFS) quickstart notebook on AWS by Benoit de Chateauvieux
- Validation and Application of the Accu-Waves Operational Platform for Wave Forecasts at Ports by Christos Makris et al.
- Toward the Next Generation of Microwave Sounders: Benefits of a Low-Earth Orbit Hyperspectral Microwave Instrument in All- Weather Conditions using AI by Eric S. Maddy
NOAA Global Historical Climatology Network Daily (GHCN-D)
agricultureclimatemeteorologicalweather
UPDATE TO GHCN PREFIXES - The NODD team is working on improving performance and access to the GHCNd data and will be implementing an updated prefix structure. For more information on the prefix changes, please see the "READ ME on the NODD Github". If you have questions, comments, or feedback, please reach out to nodd@noaa.gov with GHCN in the subject line.
Global Historical Climatology Network - Daily is a dataset from NOAA that contains daily observations over global land areas. It contains station-based measurements f...
Usage examples
- Calculating growing degree days using AWS Registry of Open Data by Karen Hildebrand and Zac Flamig
- Explore & Visualize 200+ Years of Global Temperature by Kapil Sreedharan
- Visualize over 200 years of global climate data using Amazon Athena and Amazon QuickSight by Conor Delaney
- Natural and Socioeconomic Conditions Influence Tick-Borne Encephalitis Cases in Russia by Lantian Zhang, Linsheng Yang, Li Wang, Lijuan Gu, Hairong Li, Svetlana Malkhazova
NOAA High-Resolution Rapid Refresh (HRRR) Model
agricultureclimatedisaster responseenvironmentalweather
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...
Usage examples
- HRRR-B Python package: download and read HRRR grib2 files by Brian Blaylock
- Using the U.S. Climate Reference Network to Identify Biases in Near- and Sub-Surface Meteorological Fields in the High-Resolution Rapid Refresh (HRRR) Weather Prediction Model by Temple R. Lee, Ronald D. Leeper, Tim Wilson, Howard Diamond, Tilden P. Meyers, and David D. Turner
- The HRRR Zarr Archive Managed by MesoWest by Taylor Gowan
- Using Cloud Computing to Analyze Model Output Archived in Zarr Format by Taylor A. Gowan, John D. Horel, Alexander A. Jacques, and Adair Kovac
NOAA's Coastal Ocean Reanalysis (CORA) Dataset: 1979-2022
agricultureagricultureclimatedisaster responseenvironmentaloceanstransportationweather
NOAA's Coastal Ocean Reanalysis (CORA) for the Gulf, East Coast/Atlantic, and Caribbean (GEC) is produced using verified hourly water levels from the National Ocean Service’s Center of Operational Oceanographic Products & Services (CO-OPS). ADvanced CIRCulation Model (ADCIRC) and Simulating WAves Nearshore (SWAN) models are coupled to model coastal water levels and nearshore waves. Hourly water level observations are used for data assimilation and validation to improve the accuracy of modeled water levels and wave datasets.
Additional Details:
Metadata associated with model domain and time span:
- Timeseries - 1979 to 2022
- Size - Approx. 44.6 TB
- Domain - Lat 5.8 to 45.8 ; Long -98.0 to -53.
Usage examples
- NOAA Technical Report NOS CO-OPS 108: NOAA’s Coastal Ocean Reanalysis: Gulf of Mexico, Atlantic, and Caribbean (January 2025) by Keeney, Analise; Dusek, Gregory; Callahan, John; Ratcliff, John; Jima, Tigist; Brooks, William; Marcy, Doug; Blanton, Brian; Tilson, Jeffrey; Asher, Taylor G.; Leuttich, Richard A.; Widlansky, Matthew J.; Rose, Linta; Morse, Cheryl; Haddad, Jana; & Waring, Blake
- Using Python to Access Coastal Ocean Reanalysis (CORA) Data by NOAA's Center for Operational Oceanographic Products and Services
- Coastal Ocean Reanalysis Use cases by NOAA's Center for Operational Oceanographic Products and Services
- Assessment of water levels from 43 years of NOAA’s Coastal Ocean Reanalysis (CORA) for the Gulf of Mexico and East Coasts by Rose, Linta; Widlansky, Matthew J.; Feng, Xue; Thompson, Thompson; Asher, Taylor G.; Dusek, Gregory; Blanton, Blanton; Luettich, Richard A. Jr.; Callahan, John; Brooks, William; Keeney, Analise; Haddad, Jana; Sweet, William; Genz, Ayesha; Hovenga, Paige; Marra, John & Tilson, Jeffrey
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 numbe...
Usage examples
- A global surface drifter dataset at hourly resolution (2016) by Elipot, S., R. Lumpkin, R. C. Perez, J. M. Lilly, J. J. Early, and A. M. Sykulski
- Working with GDP hourly data using python and xarray, a CloudDrift notebook by Shane Elipot
- A Dataset of Hourly Sea Surface Temperature From Drifting Buoys (2022) by Elipot, S., A. Sykulski, R. Lumpkin, L. Centurioni, and M. Pazos
NOAA Emergency Response Imagery
aerial imageryclimatecogdisaster responseweather
In order to support NOAA's homeland security and emergency response requirements, the National Geodetic Survey Remote Sensing Division (NGS/RSD) has the capability to acquire and rapidly disseminate a variety of spatially-referenced datasets to federal, state, and local government agencies, as well as the general public. Remote sensing technologies used for these projects have included lidar, high-resolution digital cameras, a film-based RC-30 aerial camera system, and hyperspectral imagers. Examples of rapid response initiatives include acquiring high resolution images with the Emerge/App...
Usage examples
- ERI notebook using SageMaker Studio Lab (SMSL) by Mya Sears
- Using Emergency and Pre-Event Imagery by Jon Sellars
- Open data helps recovery in the aftermath of devastating weather events by Jena Kent
NOAA Global Ensemble Forecast System (GEFS) Re-forecast
agricultureclimatemeteorologicalweather
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...
Usage examples
NOAA Multi-Radar/Multi-Sensor System (MRMS)
agricultureclimatemeteorologicalweather
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, c...
Usage examples
- Collection of Jupyter Notebooks using Python for working with MRMS Data by Project Pythia Community
- Multi-Radar Multi-Sensor (MRMS) Quantitative Precipitation Estimation: Initial Operating Capabilities by Jian Zhang, Kenneth Howard, Carrie Langston, Brian Kaney, Youcun Qi, Lin Tang, Heather Grams, Yadong Wang, Stephen Cocks, Steven Martinaitis, Ami Arthur, Karen Cooper, Jeff Brogden, David Kitzmiller
- Multi-Radar Multi-Sensor (MRMS) Severe Weather and Aviation Products: Initial Operating Capabilities by Travis M. Smith, Valliappa Lakshmanan, Gregory J. Stumpf, Kiel L. Ortega, Kurt Hondl, Karen Cooper, Kristin M. Calhoun, Darrel M. Kingfield, Kevin L. Manross, Robert Toomey, Jeff Brogden
NOAA Analysis of Record for Calibration (AORC) Dataset
agricultureagricultureclimatedisaster responseenvironmentaltransportationweather
...
Usage examples
- Explore the AORC 1.1 dataset in Zarr by Michael AuCoin
- The Office of Water Prediction's Analysis of Record for Calibration, version 1.1: Dataset description and precipitation evaluation (09 July 2023). J. Am. Water Resour. Assoc., 59 (6). 1246-1272. by Greg Fall, David Kitzmiller, Sandra Pavlovic, Ziya Zhang, Nathan Patrick, Michael St. Laurent, Carl Trypaluk, Wanru Wu, and Dennis Miller
NOAA Climate Forecast System (CFS)
agricultureclimatemeteorologicalweather
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...
Usage examples
- The NCEP Climate Forecast System Reanalysis by Saha, Suranjana, and Coauthors
- The NCEP Climate Forecast System Version 2 by Saha, Suranjana, and Coauthors
NOAA Global Forecast System (GFS) netCDF Formatted Data
agricultureclimatedisaster responseenvironmentalmeteorologicalweather
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...
Usage examples
- U.S. EPA’s application of NOAA’s GFS netCDF data on AWS and NACC-Cloud: 'Expedited modeling of burn events results (EMBER): A screening-level dataset of 2023 ozone fire impacts in the US.' by Simon et al.
- NOAA’s Global Forecast System Data in the Cloud for Community Air Quality Modeling. Atmosphere 2023, 14, 1110. by Campbell, P.C.; Jiang, W.; Moon, Z.; Zinn, S.; Tang, Y.
NOAA Unified Forecast System Subseasonal to Seasonal Prototypes
agricultureclimatedisaster responseenvironmentalmeteorologicaloceansweather
The Unified Forecast System Subseasonal to Seasonal prototypes consist of reforecast data from the UFS atmosphere-ocean coupled model experimental prototype version 5, 6, 7, and 8 produced by the Medium Range and Subseasonal to Seasonal Application team of the UFS-R2O project. The UFS prototypes are the first dataset released to the broader weather community for analysis and feedback as part of the development of the next generation operational numerical weather prediction system from NWS. The datasets includes all the major weather variables for atmosphere, land, ocean, sea ice, and ocean wav...
Usage examples
- The impact of tropical SST biases on the S2S precipitation forecast skill over the Contiguous United States in the UFS global coupled model by Hedanqiu Bai, Bin Li, Avichal Mehra, Jessica Meixner, Shrinivas Moorthi, Sulagna Ray, Lydia Stefanova, Jiande Wang, Jun Wang, Denise Worthen, Fanglin Yang, and Cristiana Stan
- Advances in Seasonal Predictions of Arctic Sea Ice With NOAA UFS by Jieshun Zhu, Wanqiu Wang, Yanyun Liu, Arun Kumar, and David DeWitt
NOAA World Ocean Database (WOD)
climateoceans
The World Ocean Database (WOD) is the largest uniformly formatted, quality-controlled, publicly available historical subsurface ocean profile database. From Captain Cook's second voyage in 1772 to today's automated Argo floats, global aggregation of ocean variable information including temperature, salinity, oxygen, nutrients, and others vs. depth allow for study and understanding of the changing physical, chemical, and to some extent biological state of the World's Oceans. Browse the bucket via the AWS S3 explorer: https://noaa-wod-pds.s3.amazonaws.com/index.html
Usage examples
- The World Ocean Database Introduction by Tim P. Boyer, Olga K. Baranova, Carla Coleman, Hernan E. Garcia, Alexandra Grodsky, Ricardo A. Locarnini, Alexey V. Mishonov, Christopher R. Paver, James R. Reagan, Dan Seidov, Igor V. Smolyar, Katharine W. Weathers, Melissa M. Zweng
- The World Ocean Database User's Manual by Hernan E. Garcia, Tim P. Boyer, Ricardo A. Locarnini, Olga K. Baranova, Melissa M. Zweng
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, me...
Usage examples
Crowdsourced Bathymetry
earth observationoceans
Community provided bathymetry data collected in collaboration with the International Hydrographic Organization.
Usage examples
- Crowdsourced Bathymetry Data (CSB) Visualization by David Neufeld
Korea Meteorological Administration (KMA) GK-2A Satellite Data
agriculturedisaster responseearth observationgeospatialmeteorologicalsatellite imageryweather
The Geo-KOMPSAT-2A (GK2A) is the new generation geostationary meteorological satellite (located in 128.2°E) of the Korea Meteorological Administration (KMA). The main mission of the GK2A is to observe the atmospheric phenomena over the Asia-Pacific region. The Advance Meteorological Imager (AMI) on GK2A scan the Earth full disk every 10 minutes and the Korean Peninsula area every 2 minutes with a high spatial resolution of 4 visible channels and 12 infrared channels. In addition, the AMI has an ability of flexible target area scanning useful for monitoring severe weather events such as typhoon...
Usage examples
- GK2A Full Fact Sheet by KMA
NOAA Coastal Lidar Data
climatedisaster responseelevationgeospatiallidarstac
Lidar (light detection and ranging) is a technology that can measure the 3-dimentional location of objects, including the solid earth surface. The data consists of a point cloud of the positions of solid objects that reflected a laser pulse, typically from an airborne platform. In addition to the position, each point may also be attributed by the type of object it reflected from, the intensity of the reflection, and other system dependent metadata. The NOAA Coastal Lidar Data is a collection of lidar projects from many different sources and agencies, geographically focused on the coastal areas of the ...
Usage examples
NOAA Global Surface Summary of Day
agricultureclimateenvironmentalnatural resourceregulatoryweather
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:
Mean t...
Usage examples
NOAA HYSPLIT-compatible meteorological data archives
agricultureclimatedisaster responseenvironmentalmeteorologicalweather
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...
Usage examples
- HYSPLIT Basic Tutorial by NOAA ARL HYSPLIT
NOAA Integrated Surface Database (ISD)
agricultureclimatemeteorologicalweather
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 ...
Usage examples
- NOAA Integrated Surface Database (ISD) Example Notebook by Zac Flamig
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 t...
Usage examples
- Comprehensive radar data for the contiguous United States: Multi-year reanalysis of remotely sensed storms. by Williams, S. S., K. L. Ortega, T. M. Smith, and A. E. Reinhart
NOAA National Digital Forecast Database (NDFD)
agricultureclimatemeteorologicalweather
Please note NWS is Soliciting Comments until April 30, 2024 on Availability of Probabilistic Snow Grids for Select Weather Forecast Offices (WFOs) as an Experimental Element in the National Digital Forecast Database (NDFD) for the Contiguous United States (CONUS). A PDF version of the Public Notice can be found "HERE"
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 Predictio...
Usage examples
- NDFD Product Spreadsheet (excel file) by NOAA MDL
NOAA National Water Model Short-Range Forecast
agricultureagricultureclimatedisaster responseenvironmentaltransportationweather
The National Water Model (NWM) is a water resources model that simulates and forecasts water budget variables, including snowpack, evapotranspiration, soil moisture and streamflow, over the entire continental United States (CONUS). The model, launched in August 2016, is designed to improve the ability of NOAA to meet the needs of its stakeholders (forecasters, emergency managers, reservoir operators, first responders, recreationists, farmers, barge operators, and ecosystem and floodplain managers) by providing expanded accuracy, detail, and frequency of water information. It is operated by NOA...
Usage examples
NOAA S-111 Surface Water Currents Data
oceanswater
S-111 is a data and metadata encoding specification that is part of the S-100 Universal Hydrographic Data Model, an international standard for hydrographic data. This collection of data contains surface water currents forecast guidance from NOAA/NOS Operational Forecast Systems, a set of operational hydrodynamic nowcast and forecast modeling systems, for various U.S. coastal waters and the great lakes. The collection also contains surface current forecast guidance output from the NCEP Global Real-Time Ocean Forecast System (GRTOFS) for some offshore areas. These datasets are encoded as HDF-5 f...
Usage examples
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...
Usage examples
NOAA Wave Ensemble Reforecast
agricultureclimatemeteorologicalweather
This is a 20-year global wave reforecast generated by WAVEWATCH III model (https://github.com/NOAA-EMC/WW3) forced by GEFSv12 winds (https://noaa-gefs-retrospective.s3.amazonaws.com/index.html). The wave ensemble was run with one cycle per day (at 03Z), spatial resolution of 0.25°X0.25° and temporal resolution of 3 hours. There are five ensemble members (control plus four perturbed members) and, once a week (Wednesdays), the ensemble is expanded to eleven members. The forecast range is 16 days and, once a week (Wednesdays), it extends to 35 days. More information about the wave modeling, wave grids and calibration can be found in the WAVEWATCH III regtest ww3_ufs1.3 (Details →
Usage examples
NOAA nClimGrid and Livneh Gridded Historical Climate Observation Thresholds
agricultureclimateenvironmentalmeteorologicalweather
Livneh and nClimGrid are gridded observed historical climatology data that were used in the LOCA2 and STAR-ESDM downscaling process of global climate models as part of the 5th National Climate Assessment. The original Livneh and nClimGrid daily temperature and precipitation observations have been converted to a series of decision-relevant thresholds as part of the (U.S. Climate Resilience Information System (CRIS)). These thresholds, such as days with extreme heat or precipitation, have been calculated to match the future projections from LOCA2 and STAR, also available in CRIS.
Usage examples
- U.S. CRIS Resources by U.S. CRIS
NOAA/PMEL Ocean Climate Stations Moorings
climateenvironmentaloceansweather
The mission of the Ocean Climate Stations (OCS) Project is to make meteorological and
oceanic measurements from autonomous platforms. Calibrated, quality-controlled, and well-documented
climatological measurements are available on the OCS webpage and the OceanSITES Global Data
Assembly Centers (GDACs), with near-realtime data available prior to release of the complete,
downloaded datasets.
OCS measurements served through the Big Data Program come from OCS high-latitude moored buoys located in the Kuroshio
Extension (32°N 145°E) and the Gulf of Alaska (50°N 145°W). Initiated in 2004 and 20...
Usage examples
(EXPERIMENTAL) NOAA FourCastNet Global Forecast System (FourCastNetGFS) (EXPERIMENTAL)
agricultureclimatedisaster responseenvironmentalmeteorologicalweather
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 ...
NOAA / NGA Satellite Computed Bathymetry Assessment-SCuBA
agricultureagriculturebathymetryclimatedisaster responseenvironmentaloceanstransportationweather
One of the National Geospatial-Intelligence Agency’s (NGA) and the National Oceanic and Atmospheric Administration’s (NOAA) missions is to ensure the safety of navigation on the seas by maintaining the most current information and the highest quality services for U.S. and global transport networks. To achieve this mission, we need accurate coastal bathymetry over diverse environmental conditions. The SCuBA program focused on providing critical information to improve existing bathymetry resources and techniques with two specific objectives. The first objective was to validate National Aeronautics and Space Administration’...
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. 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 96-hour forecast guidance of water level conditions, and 2- and 3...
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. NOA...
NOAA Cloud Optimized Zarr Reference Files (Kerchunk)
climatecoastaldisaster responseenvironmentalmeteorologicaloceanswaterweather
This repository contains references to datasets published to the NOAA Open Data Dissemination Program. These reference datasets serve as index files to the original data by mapping to the Zarr V2 specification. When multidimensional model output is read through zarr, data can be lazily loaded (i.e. retrieving only the data chunks needed for processing) and data reads can be scaled horizontally to optimize object storage read performance.
The process used to optimize the data is called kerchunk. RPS runs the workflow in their AWS cloud environment every time a new data notification is received from a relevant source data bucket.
These are the current datasets being cloud-optimized. Refer to those pages for file naming conventions and other information regarding the specific model implementations:
Details →
NOAA Continuously Operating Reference Stations (CORS) Network (NCN)
broadcast ephemerisContinuously Operating Reference Station (CORS)earth observationgeospatialGNSSGPSmappingNOAA CORS Network (NCN)post-processingRINEXsurvey
The NOAA Continuously Operating Reference Stations (CORS) Network (NCN), managed by NOAA/National Geodetic Survey (NGS), provide Global Navigation Satellite System (GNSS) data, supporting three dimensional positioning, meteorology, space weather, and geophysical applications throughout the United States. The NCN is a multi-purpose, multi-agency cooperative endeavor, combining the efforts of hundreds of government, academic, and private organizations. The stations are independently owned and operated. Each agency shares their GNSS/GPS carrier phase and code range measurements and station metada...
NOAA EAGLE (Experimental AI Global and Limited-Area Ensemble) Global Deterministic and Ensemble Forecasts
agricultureclimatedisaster responseenvironmentalmeteorologicalweather
...
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. NOA...
NOAA Global Data Assimilation (DA) Test Data
agricultureclimatedisaster responseenvironmentalmeteorologicalweather
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)
agricultureclimatemeteorologicalweather
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 Hydro Estimator (GHE) / Enterprise Rain Rate
agriculturemeteorologicalwaterweather
NOTE - The legacy on-premises version of the Global Hydroestimator (GHE) is being retired. It is being replaced by the global Enterprise Rain Rate algorithm. You can find Enterprise Rain Rate products in the new bucket listed under the Resources section.
Global Hydro-Estimator provides a global mosaic imagery of rainfall estimates from multi-geostationary satellites, which currently includes GOES-16, GOES-15, Meteosat-8, Meteosat-11 and Himawari-8. The GHE products include: Instantaneous rain rate, 1 hour, 3 hour, 6 hour, 24 hour and also multi-day rainfall accumulation.
NOAA Global Mosaic of Geostationary Satellite Imagery (GMGSI)
agricultureclimatemeteorologicalweather
NOAA/NESDIS Global Mosaic of Geostationary Satellite Imagery (GMGSI) visible (VIS), shortwave infrared (SIR), longwave infrared (LIR) imagery, and water vapor imagery (WV) are composited from data from several geostationary satellites orbiting the globe, including the GOES-East and GOES-West Satellites operated by U.S. NOAA/NESDIS, the Meteosat-10 and Meteosat-9 satellites from theMeteosat Second Generation (MSG) series of satellites operated by European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), and the Himawari-9 satellite operated by the Japan Meteorological ...
NOAA Global Real-Time Ocean Forecast System (Global RTOFS)
climatecoastaldisaster responseenvironmentalglobalmeteorologicaloceanswaterweather
NOAA is soliciting public comment on petential changes to the Real Time Ocean Forecast System (RTOFS) through March 27, 2024. Please see Public Notice at (https://www.weather.gov/media/notification/pdf_2023_24/pns24-12_rtofs_v2.4.0.pdf)
NOAA's Global Real-Time Ocean Forecast System (Global RTOFS) provides users with nowcasts (analyses of near present conditions) and forecast guidance up to eight days of ocean temperature and salinity, water velocity, sea surface elevation, sea ice coverage and sea ice thickness.
The Global Operational Real-Time Ocean Forecast System (Global RTOFS) is based on an eddy resolving 1/12° global HYCOM (HYbrid Coor...
NOAA Global Surge and Tide Operational Forecast System 2-D (STOFS-2D-Global)
climatecoastaldisaster responseenvironmentalglobalmeteorologicaloceanswaterweather
NOTICE - The Coast Survey Development Laboratory (CSDL) in NOAA/National Ocean Service (NOS)/Office of Coast Survey has upgraded the Surge and Tide Operational Forecast System (STOFS, formerly ESTOFS) to Version 2.1. A Service Change Notice (SCN) has been issued and can be found "HERE"
NOAA's Global Surge and Tide Operational Forecast System 2-D (STOFS-2D-Global) provides users with nowcasts (analyses of near present conditions) and forecast guidance of water level conditions for the entire globe. STOFS-2D-Global has been developed to serve the marine navigation, weather forecasting, an...
NOAA Historical Maps and Charts
coastalgeospatialhistorymappingsurvey
Historical Charts are not for Navigation. The collection primarily consists of historic charts and maps produced by NOAA's Coast Survey and its predecessors, especially the U.S. Coast and Geodetic Survey and the U.S. Lake Survey (previously under the Department of War). The collection also includes bathymetric maps, land sketches, Civil War battle maps, aeronautical charting from the 1930s to the 1950s, and other drawings and photographs.
NOAA Hurricane Analysis and Forecast System (HAFS)
agricultureclimatemeteorologicalweather
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 NASA Joint Archive (NNJA) of Observations for Earth System Reanalysis
agricultureclimatemeteorologicalweather
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 Bathymetric Source Data
bathymetryearth observationmarine navigationmodeloceansoceans
The National Bathymetric Source (NBS) project creates and maintains high-resolution bathymetry composed of the best available data. This project enables the creation of next-generation nautical charts while also providing support for modeling, industry, science, regulation, and public curiosity. Primary sources of bathymetry include NOAA and U.S. Army Corps of Engineers hydrographic surveys and topographic bathymetric (topo-bathy) lidar (light detection and ranging) data. Data submitted through the NOAA Office of Coast Survey’s external source data process are also included, with gaps...
NOAA National Blend of Models (NBM)
agricultureclimatecogmeteorologicalweather
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
agricultureclimatedisaster responseenvironmentalmeteorologicalweather
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 North American Mesoscale Forecast System (NAM)
agricultureclimatemeteorologicalweather
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 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. NOA...
NOAA Office of Coast Survey - Hydrographic Survey Data
bathymetryearth observationmarine navigationmodeloceansoceans
Founded in 1807, NOAA’s Office of Coast Survey is the nation’s first scientific agency and today is responsible for supporting nearly $5.4 trillion in economic activity through providing advanced marine navigation services. The Office of Coast Survey collects and qualifies hydrographic, bathymetric, and topographic data, from NOAA platforms and many other data providers. These data and associated deliverables are posted here for various users to access, including but not limited to the "National Bathymetric Source Program" for incorporation into compilations of the best available bat...
NOAA Rapid Refresh (RAP)
agricultureclimatemeteorologicalweather
The Rapid Refresh (RAP) is a NOAA/NCEP operational weather prediction system comprised primarily of a numerical forecast model and analysis/assimilation system to initialize that model. It covers North America and is run with a horizontal resolution of 13 km and 50 vertical layers. The RAP was developed to serve users needing frequently updated short-range weather forecasts, including those in the US aviation community and US severe weather forecasting community. The model is run for every hour of the day; it is integrated to 51 hours for the 03/09/15/21 UTC cycles and to 21 hours for every ot...
NOAA Real-Time Mesoscale Analysis (RTMA) / Unrestricted Mesoscale Analysis (URMA)
agricultureclimatemeteorologicalweather
The Real-Time Mesoscale Analysis (RTMA) is a NOAA National Centers For Environmental Prediction (NCEP) high-spatial and temporal resolution analysis/assimilation system for near-surf ace weather conditions. Its main component is the NCEP/EMC Gridpoint Statistical Interpolation (GSI) system applied in two-dimensional variational mode to assimilate conventional and satellite-derived observations.
The RTMA was developed to support NDFD operations and provide field forecasters with high quality analyses for nowcasting, situational awareness, and forecast verification purposes. The system produces ...
NOAA S-102 Bathymetric Surface Data
bathymetryhydrographymarine navigationoceansseafloorwater
S-102 is a data and metadata encoding specification that is part of the S-100 Universal Hydrographic Data Model, an international standard for hydrographic data exchange. This collection of data contains bathymetric surfaces from NOAA/NOS/OCS National Bathymetric Source, for various U.S. coastal and offshore waters and the great lakes. These datasets are encoded as HDF5 files conforming to the S-102 specification.
NOAA Severe Weather Data Inventory (SWDI)
agricultureclimatemeteorologicalweather
The Storm Events Database is an integrated database of severe weather events across the United States from 1950 to this year, with information about a storm event's location, azimuth, distance, impact, and severity, including the cost of damages to property and crops. It contains data documenting: The occurrence of storms and other significant weather phenomena having sufficient intensity to cause loss of life, injuries, significant property damage, and/or disruption to commerce. Rare, unusual, weather phenomena that generate media attention, such as snow flurries in South Florida or the S...
NOAA Space Weather Follow-On Mission Geostationary Operational Environmental Satellite (GOES) 19
satellite imageryspace weather
The National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellite 19 (GOES-19) is the fourth and final satellite in the
Geostationary Operational Environmental Satellites (GOES) – R Series, the Western Hemisphere’s most sophisticated weather-observing and environmental monitoring
system.
The GOES-R Series provides advanced imagery and atmospheric measurements, real-time mapping of lightning activity, and space weather observations. As a part of the
Space Weather Follow On (SWFO) Mission, the GOES-19 spacecraft contains a Compact Coronagraph-1 (...
NOAA Space Weather Forecast and Observation Data
climatemeteorologicalsolarweather
Space weather forecast and observation data is collected and disseminated by NOAA’s Space Weather Prediction Center (SWPC) in Boulder, CO. SWPC produces forecasts for multiple space weather phenomenon types and the resulting impacts to Earth and human activities. A variety of products are available that provide these forecast expectations, and their respective measurements, in formats that range from detailed technical forecast discussions to NOAA Scale values to simple bulletins that give information in laymen's terms. Forecasting is the prediction of future events, based on analysis and...
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. NOA...
NOAA U.S. Climate Gridded Dataset (NClimGrid)
agricultureclimatemeteorologicalweather
The NOAA Monthly U.S. Climate Gridded Dataset (NClimGrid) consists of four climate variables derived from the GHCN-D dataset: maximum temperature, minimum temperature, average temperature and precipitation. Each file provides monthly values in a 5x5 lat/lon grid for the Continental United States. Data is available from 1895 to the present. On an annual basis, approximately one year of "final" nClimGrid will be submitted to replace the initially supplied "preliminary" data for the same time period. Users should be sure to ascertain which level of data is required for their resear...
NOAA Unified Forecast System (UFS) Coastal Model
climatedisaster responseelevationgeospatiallidarstac
The Unified Forecast System (UFS) is a community-based, coupled, comprehensive Earth Modeling System. The UFS Coastal application is a project under development by NOAA and NCAR, which supports coastal forecasting requirements based on UFS standards. The coupling infrastructure for UFS Coastal App is currently being developed based on a fork of the ufs-weather-model (UFS-WM), with additional coastal model-components including SCHISM, ADCIRC, ROMS, and FVCOM, as well as additional infrastructure to support coastal coupling of WW3 and CICE. The model-level repository contains the model code and external submo...
NOAA Unified Forecast System (UFS) Global Ensemble Forecast System (GEFS) Version 13 Replay
agricultureclimatemeteorologicalweather
The NOAA Unified Forecast System (UFS) / Global Ensemble Forecast System version 13 (GEFSv13) Replay dataset supports the retrospective forecast archive in preparation for GEFSv13 / GFSv17. It includes a range of atmospheric and oceanic variables—such as temperature, humidity, winds, salinity, and currents—covering global conditions at a nominal horizontal resolution of ¼ degree, enabling detailed weather analysis.
The dataset was generated by replaying the coupled UFS model against pre-existing external reanalyses; ERA5 for atmospheric data and ORAS5 for ocean and ice dynamics. Each simulation stream...
NOAA Unified Forecast System (UFS) Hierarchical Testing Framework (HTF)
agricultureclimatedisaster responseenvironmentalmeteorologicaloceansweather
The "Unified Forecast System" (UFS) is a community-based, coupled, comprehensive Earth Modeling System. The Hierarchical Testing Framework (HTF) serves as a comprehensive toolkit designed to enhance the testing capabilities within UFS "repositories". It aims to standardize and simplify the testing process across various "UFS Weather Model" (WM) components and associated modules, aligning with the Hierarchical System Development (HSD) approach and NOAA baseline operational metrics.
The HTF provides a structured methodology for test case design and execution, which enh...
NOAA Unified Forecast System (UFS) Land Data Assimilation (DA) System
agricultureclimatemeteorologicalweather
The Unified Forecast System (UFS) is a community-based, coupled, comprehensive Earth modeling system. It supports "multiple applications" covering different forecast durations and spatial domains. The Land Data Assimilation (DA) System is an offline version of the Noah Multi-Physics (Noah-MP) land surface model (LSM) used in the UFS Weather Model (WM). Its data assimilation framework uses "[Joint Effort for Data assimilation Integration - JEDI] (https://www.jcsda.org/jcsda-project-jedi)" software. The offline Noah-MP LSM is a stand-alone, uncoupled model used to execute land surface simu...
NOAA Unified Forecast System (UFS) Marine Reanalysis: 1979-2019
agricultureclimatemeteorologicalweather
The NOAA UFS Marine Reanalysis is a global sea ice ocean coupled reanalysis product produced by the marine data assimilation team of the UFS Research-to-Operation (R2O) project. Underlying forecast and data assimilation systems are based on the UFS model prototype version-6 and the Next Generation Global Ocean Data Assimilation System (NG-GODAS) release of the Joint Effort for Data assimilation Integration (JEDI) Sea Ice Ocean Coupled Assimilation (SOCA). Covering the 40 year reanalysis time period from 1979 to 2019, the data atmosphere option of the UFS coupled global atmosphere ocean sea ice (DAT...
NOAA Unified Forecast System Short-Range Weather (UFS SRW) Application
agricultureclimatemeteorologicalweather
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 UFS Short-Range Weather (SRW) Application figures among these applications. It targets predictions of atmospheric behavior on a limited spatial domain and on time scales from minutes to several days. The SRW Application includes a prognostic atmospheric model, pre-processor, post-processor, and community workflow for running the system end-to-end. The "SRW Application Users's Guide...
NOAA Unified Forecast System Weather Model (UFS-WM) Regression Tests
agricultureclimatemeteorologicalweather
The Unified Forecast System (UFS) is a community-based, coupled, comprehensive Earth Modeling System. The ufs-weather-model (UFS-WM) is the model source of the UFS for NOAA’s operational numerical weather prediction applications. The UFS-WM Regression Test (RT) is the testing software to ensure that previously developed and tested capabilities in UFS-WM still work after code changes are integrated into the system. It is required that UFS-WM RTs are performed successfully on the required Tier-1 platforms whenever code changes are made to the UFS-WM. The results of the UFS-WM RTs are summarized i...
NOAA Wang Sheeley Arge (WSA) Enlil
climatemeteorologicalsolarweather
The WSA-Enlil heliospheric model provides critical information regarding the propagation of solar Coronal Mass Ejections (CMEs) and transient structures within the heliosphere. Two distinct models comprise the WSA-Enlil modeling system; 1) the Wang-Sheeley-Arge (WSA) semi-empirical solar coronal model, and 2) the Enlil magnetohydrodynamic (MHD) heliospheric model. MHD modeling of the full domain (solar photosphere to Earth) is extremely computationally demanding due to the large parameter space and resulting characteristic speeds within the system. To reduce the computational burden and improve the timeliness (and he...
NOAA Whole Atmosphere Model-Ionosphere Plasmasphere Electrodynamics (WAM-IPE) Forecast System (WFS)
climatemeteorologicalsolarweather
The coupled Whole Atmosphere Model-Ionosphere Plasmasphere Electrodynamics (WAM-IPE) Forecast System (WFS) is developed and maintained by the NOAA Space Weather Prediction Center (SWPC). The WAM-IPE model provides a specification of ionosphere and thermosphere conditions with real-time nowcasts and forecasts up to two days in advance in response to solar, geomagnetic, and lower atmospheric forcing. The WAM is an extension of the Global Forecast System (GFS) with a spectral hydrostatic dynamical core utilizing an enthalpy thermodynamic variable to 150 vertical levels on a hybrid pressure-sigma grid, with a model t...
AI Weather Prediction (AIWP) Model Reforecasts
environmentalmeteorologicalweather
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...