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agricultureair qualityanalyticsarchivesatmosphereclimateclimate modeldata assimilationdeep learningearth observationenergyenvironmentalforecastgeosciencegeospatialglobalhistoryimagingindustrymachine learningmachine translationmetadatameteorologicalmodelnetcdfopendapradiationsatellite imagerysolarstatisticssustainabilitytime series forecastingwaterweatherzarr
NASA's goal in Earth science is to observe, understand, and model the Earth system to discover how it is changing, to better predict change, and to understand the consequences for life on Earth. The Applied Sciences Program serves NASA and Society by expanding and accelerating the realization of societal and economic benefits from Earth science, information, and technology research and development.
The NASA Prediction Of Worldwide Energy Resources (POWER) Project, a NASA Applied Sciences program, improves the accessibility and usage NASA Earth Observations (EO) supporting community research in three focus areas: 1) renewable energy development, 2) building energy efficiency, and 3) agroclimatology applications. POWER can help communities be resilient amid observed climate variability through the easy access of solar and meteorological data via a variety of access methods.
The latest POWER version includes hourly-based source Analysis Ready Data (ARD), in addition to enhanced daily, monthly, annual, and climatology ARD. The daily time-series spans 40 years for meteorology available from 1981 and solar-based parameters start in 1984. The hourly source data are from Clouds and the Earth's Radiant Energy System (CERES) and Global Modeling and Assimilation Office (GMAO), spanning 20 years from 2001. The hourly data will provide users the ARD needed to model the energy performance of building systems, providing information directly amenable to decision support tools introducing the industry standard EPW (EnergyPlus Weather file).
POWER also provides parameters at daily, monthly, annual, and user-defined time periods, spanning from 1984 through to within a week of real time. Additionally, POWER provides are user-defined analytic capabilities, including custom climatologies and climatological-based reports for parameter anomalies, ASHRAE® compatible climate design condition statistics, and building climate zones.
The ARD and climate analytics will be readily accessible through POWER's integrated services suite, including the Data Access Viewer (DAV). The DAV has recently been improved to incorporate updated parameter groupings, new analytical capabilities, and the new data formats. POWER also provides a complete API (Application Programming Interface) that allows uses...
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...
agricultureclimatecogdeafricaearth observationfood securitygeospatialmeteorologicalsatellite imagerystacsustainability
Digital Earth Africa (DE Africa) provides free and open access to a copy of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) monthly and daily products over Africa. The CHIRPS rainfall maps are produced and provided by the Climate Hazards Center in collaboration with the US Geological Survey, and use both rain gauge and satellite observations. The CHIRPS-2.0 Africa Monthly dataset is regularly indexed to DE Africa from the CHIRPS monthly data. The CHIRPS-2.0 Africa Daily dataset is likewise indexed from the CHIRPS daily data. Both products have been converted to clou...
climatecoastaldeafricaearth observationgeospatialsatellite imagerysustainability
Africa's long and dynamic coastline is subject to a wide range of pressures, including extreme weather and climate, sea level rise and human development. Understanding how the coastline responds to these pressures is crucial to managing this region, from social, environmental and economic perspectives. The Digital Earth Africa Coastlines (provisional) is a continental dataset that includes annual shorelines and rates of coastal change along the entire African coastline from 2000 to the present. The product combines satellite data from the Digital Earth Africa program with tidal modelling t...
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 significant.
The National Ocean Service (NOS) has the mission and mandate to provide guidance and information to support navigation and coastal needs. To support this mission, NOS has been developing and implementing hydrodynamic model-based Operational Forecast Systems.
This forecast guidance provides oceanographic information that helps mariners safely navigate their local waters. This national network of hydrodynamic models provides users with operational nowcast and forecast guidance (out to 48 – 120 hours) on parameters such as water levels, water temperature, salinity, and currents. These forecast systems are implemented in critical ports, harbors, estuaries, Great Lakes and coastal waters of the United States, and form a national backbone of real-time data, tidal predictions, data management and operational modeling.
Nowcasts and forecasts are scientific predictions about the present and future states of water levels (and possibly currents and other relevant oceanographic variables, such as salinity and temperature) in a coastal area. These predictions rely on either observed data or forecasts from a numerical model. A nowcast incorporates recent (and often near real-time) observed meteorological, oceanographic, and/or river flow rate data. A nowcast covers the period from the recent past (e.g., the past few days) to the present, and it can make predictions for locations where observational data are not available. A forecast incorporates meteorological, oceanographic, and/or river flow rate forecasts and makes predictions for times where observational data will not be available. A forecast is usually initiated by the results of a nowcast.
OFS generally runs four times per day (every 6 hours) on NOAA's Weather and Climate Operational Supercomputing Systems (WCOSS) in a standard Coastal Ocean Modeling Framework (COMF) developed by the Center for Operational Oceanographic Products and Services (CO-OPS). COMF is a set...
climateearth observationenvironmentalnatural resourceoceanssatellite imagerywaterweather
A global, gap-free, gridded, daily 1 km Sea Surface Temperature (SST) dataset created by merging multiple Level-2 satellite SST datasets. Those input datasets include the NASA Advanced Microwave Scanning Radiometer-EOS (AMSR-E), the JAXA Advanced Microwave Scanning Radiometer 2 (AMSR-2) on GCOM-W1, the Moderate Resolution Imaging Spectroradiometers (MODIS) on the NASA Aqua and Terra platforms, the US Navy microwave WindSat radiometer, the Advanced Very High Resolution Radiometer (AVHRR) on several NOAA satellites, and in situ SST observations from the NOAA iQuam project. Data are available fro...
agricultureatmosphereclimateearth observationenvironmentalmodeloceanssimulationsweather
High-resolution historical and future climate simulations from 1980-2100
climateCMIP5natural resourcesustainability
A collection of downscaled climate change projections, derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) [Taylor et al. 2012] and across the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs) [Meinshausen et al. 2011]. The NASA Earth Exchange group maintains the NEX-DCP30 (CMIP5), NEX-GDDP (CMIP5), and LOCA (CMIP5).
agricultureatmosphereclimateearth observationenvironmentalmodeloceanssimulationsweather
The sixth phase of global coupled ocean-atmosphere general circulation model ensemble.
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 temporal analyses with hourly streamflow output and 3-hourly land surface output. This dataset can also be used in the development of end user applications which require a long baseline of data for system training or verification purposes.
...
air qualityatmospherechemistryclimateenvironmentalmeteorologicalmodelweather
Input data for the GEOS-Chem Chemical Transport Model, includes NASA/GMAO MERRA-2 and GEOS-FP meteorological products, chemistry input data, emissions input data, and other smaller datasets such as model initial conditions.
air qualityatmospherechemistryclimateenvironmentalmeteorologicalmodelweather
Input data for nested-grid simulations using the GEOS-Chem Chemical Transport Model. This includes the NASA/GMAO MERRA-2 and GEOS-FP meteorological products, the HEMCO emission inventories, and other small data such as model initial conditions.
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 2024. 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.
The RRFS is underpinned by the Unified Forecast System (UFS), a community-based Earth modeling initiative, and benefits from collaborative development efforts across NOAA, academia, and research institutions.
This bucket provides access to real time, experimental RRFS prototype output.
rrfs_a/rrfs_a.20230428/12/control contains the deterministic forecast initialized at 12 UTC on 28 April 2023. Users will find two types of output in GRIB2 format. The first is:rrfs.t00z.natlev.f018.conus_3km.grib2 rrfs.t00z.prslev.f018.conus_3km.grib2 rrfs.t00z.prslev.f002.grib2
Alaska: rrfs.t00z.prslev.f002.ak.grib2
Hawaii: rrfs.t00z.prslev.f002.hi.grib2
Puerto Rico: rrfs.t00z.prslev.f002.pr.grib2rrfs_a/rrfs_a.20231214/00/mem0001 contains the forecast from member 1, and rrfs_a/rrfs_a.20231214/00/enspost_timelag co...
acousticsbiodiversitybiologyclimatecoastaldeep learningecosystemsenvironmentalmachine learningmarine mammalsoceansopen source software
This project offers passive acoustic data (sound recordings) from a deep-ocean environment off central California. Recording began in July 2015, has been nearly continuous, and is ongoing. These resources are intended for applications in ocean soundscape research, education, and the arts.
chemical biologychemistryclimatedatacenterdigital assetsgeochemistrygeophysicsgeosciencemarinenetcdfoceans
Argo is an international program to observe the interior of the ocean with a fleet of profiling floats drifting in the deep ocean currents (https://argo.ucsd.edu). Argo GDAC is a dataset of 5 billion in situ ocean observations from 18.000 profiling floats (4.000 active) which started 20 years ago. Argo GDAC dataset is a collection of 18.000 NetCDF files. It is a major asset for ocean and climate science, a contributor to IOCCP reports.
atmosphereclimateclimate modeldata assimilationforecastgeosciencegeospatiallandmeteorologicalweatherzarr
This is a cloud-hosted subset of the CAM6+DART (Community Atmosphere Model version 6 Data Assimilation Research Testbed) Reanalysis dataset. These data products are designed to facilitate a broad variety of research using the NCAR CESM 2.1 (National Center for Atmospheric Research's Community Earth System Model version 2.1), including model evaluation, ensemble hindcasting, data assimilation experiments, and sensitivity studies. They come from an 80 member ensemble reanalysis of the global troposphere and stratosphere using DART and CAM6. The data products represent states of the atmospher...
climateclimate modelclimate projectionsCMIP6ocean circulationocean currentsocean sea surface heightocean simulationocean velocity
This dataset provides several global fields describing the state of atmosphere, ocean, land and ice from a high-resolution (0.1o for the ocean/ice models 0.25o for the land/atmosphere models) numerical earth system model, the Community Earth System Model (CESM, https://www.cesm.ucar.edu/). Texas A&M University (TAMU) and National Center for Atmospheric Research together with international partners collaboratively carried out a large set of high-resolution climate simulations, including a 500-year long preindustrial control simulation (PI-CTRL) described here. The CESM uses dynamic equation...
air qualityclimateenvironmentalgeospatialmeteorological
CMAS Data Warehouse on AWS collects and disseminates meteorology, emissions and air quality model input and output for Community Multiscale Air Quality (CMAQ) Model Applications. This dataset is available as part of the AWS Open Data Program, therefore egress fees are not charged to either the host or the person downloading the data. This S3 bucket is maintained as a public service by the University of North Carolina's CMAS Center, the US EPA’s Office of Research and Development, and the US EPA’s Office of Air and Radiation. Metadata and DOIs for datasets included in the CMAS Data Wareho...
atmosphereclimateclimate modelgeospatialicelandmodeloceanssustainabilityzarr
The Community Earth System Model (CESM) Large Ensemble Numerical Simulation (LENS) dataset includes a 40-member ensemble of climate simulations for the period 1920-2100 using historical data (1920-2005) or assuming the RCP8.5 greenhouse gas concentration scenario (2006-2100), as well as longer control runs based on pre-industrial conditions. The data comprise both surface (2D) and volumetric (3D) variables in the atmosphere, ocean, land, and ice domains. The total data volume of the original dataset is ~500TB, which has traditionally been stored as ~150,000 individual CF/NetCDF files on disk o...
citiesclimateenergyenergy modelinggeospatialmetadatamodelopen source softwaresustainabilityutilities
The U.S. Department of Energy (DOE) funded a three-year project, End-Use Load Profiles for the U.S. Building Stock, that culminated in this publicly available dataset of calibrated and validated 15-minute resolution load profiles for all major residential and commercial building types and end uses, across all climate regions in the United States. These EULPs were created by calibrating the ResStock and ComStock physics-based building stock models using many different measured datasets, as described here. This dataset includes load profiles for both the baseline building stock and the building ...
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 with diameter equal to or less than 2.5 micrometers (PM2.5) using meteorological forecasts based on NCEP’s operational weather forecast models such as North American Mesoscale Models (NAM) and Global Forecast System (GFS), and atmospheric chemistry based on the EPA’s Community Multiscale Air Quality (CMAQ) model. In addition, the modeling system incorporates information related to chemical emissions, including anthropogenic emissions provided by the EPA and fire emissions from NOAA/NESDIS. The NCEP NAQFC AQM output fields in this archive include 72-hr forecast products of model raw and bias-correction predictions, extending back to 1 January 2020. All of the output was generated by the contemporaneous operational AQM, beginning with AQMv5 in 2020, with upgrades to AQMv6 on 20 July 2021, and AQMv7 on 14 May 2024. The history of AQM upgrades is documented here
The second prediction is known as the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT). It is a widely used atmospheric transport and dispersion model containing an internal dust-generation module. It provides forecast guidance for atmospheric dust concentration and, prior to 28 June 2022, it also provided the NAQFC forecast guidance for smoke. Since that date, the third prediction system, a regional numerical weather prediction (NWP) model known as the Rapid Refresh (RAP) model, has subsumed HYSPLIT for operational smoke guidance, simulating the emission, transport, and deposition of smoke particles that originate from biomass burning (fires) and anthropogenic sources.
The output from each of these modeling systems is generated over three separate domains, one covering CONUS, one Alaska, and the other Hawaii. Currently, for this archive, the ozone, (PM2.5), and smoke output is available over all three domains, while dust products are available only over the CONUS domain. The predicted concentrations of all species in the lowest model layer (i.e., the layer in contact with the surface) are available, as are vertically integrated values of smoke and dust. The data is gridded horizontally within each domain, with a grid spacing of approximately 5 km over CONUS, 6 km over Alaska, and 2.5 km over Hawaii. Ozone concentrations are provided in parts per billion (PPB), while the concentrations of all other species are quantified in units of micrograms per cubic meter (ug/m3), except for the column-integrated smoke values which are expressed in units of mg/m2.
Temporally, O3 and PM2.5 are available as maximum and/or averaged values over various time periods. Specifically, O3 is available in both 1-hour and 8-hour (backward calculated) averages, as well as preceding 1-hour and 8-hour maximum values. Similarly, PM2.5 is available in 1-hour and 24-hour average values and 24-hour maximum values. In addition, all O3 and PM2.5 fields are available with bias-corrected magnitudes, based on derived model biases relative to observations.
The AQM produces hourly forecast guidance for O3 and PM2.5 out to 72 hours twice per day, starting at 0600 and 1...
agricultureclimateearth observationmeteorologicalweather
Open-Meteo integrates weather models from reputable national weather services, offering a swift and efficient weather API. Real-time weather forecasts are unified into a time-series database that provides historical and future weather data for any location worldwide.Through Open-Meteo on AWS Open Data, you can download the Open-Meteo weather database and analysis weather data locally. Docker images are provided to download data and to expose an HTTP API endpoint. Using Open-Meteo SDKs, you can seamlessly integrate weather data into your Python, Typescript, Swift, Kotlin, or Java applications.T...
climateenvironmentalmeteorologicaloceansoceanssustainabilityweather
This dataset includes archival hourly data from the [Sofar Spotter buoy global network] (https://weather.sofarocean.com/) from 2019 to March 2022.
climateenvironmentalGPSweather
SondeHub Radiosonde telemetry contains global radiosonde (weather balloon) data captured by SondeHub from our participating radiosonde_auto_rx receiving stations. radiosonde_auto_rx is a open source project aimed at receiving and decoding telemetry from airborne radiosondes using software-defined-radio techniques, enabling study of the telemetry and sometimes recovery of the radiosonde itself. Currently 313 receiver stations are providing data for an average of 384 radiosondes a day. The data within this repository contains received telemetry frames, including radiosonde type, gps position, a...
atmosphereclimatedeep learningenvironmentalexplorationgeophysicsgeosciencegeospatialglobaliceplanetarysatellite imageryzarr
The Chalmers Cloud Ice Climatology (CCIC) is a novel, deep-learning-based climate record of ice-particle concentrations in the atmosphere. CCIC results are available at high spatial and temporal resolution (0.07° / 3 h from 1983, 0.036° / 30 min from 2000) and thus ideally suited for evaluating high-resolution weather and climate models or studying individual weather systems.
atmosphereclimateclimate modelgeospatialicelandmodeloceanssustainabilityzarr
The US National Center for Atmospheric Research partnered with the IBS Center for Climate Physics in South Korea to generate the CESM2 Large Ensemble which consists of 100 ensemble members at 1 degree spatial resolution covering the period 1850-2100 under CMIP6 historical and SSP370 future radiative forcing scenarios. Data sets from this ensemble were made downloadable via the Climate Data Gateway on June 14th, 2021. NCAR has copied a subset (currently ~500 TB) of CESM2 LENS data to Amazon S3 as part of the AWS Public Datasets Program. To optimize for large-scale analytics we have represented ...
atmosphereclimateearth observationglobalsignal processingweather
This is an updating archive of radio occultation (RO) data using the transmitters of the Global Navigation Satellite Systems (GNSS) as generated and processed by the COSMIC DAAC (ucar), the Jet Propulsion Laboratory (jpl) of the California Institute of Technology, and the Radio Occultation Meteorology Satellite Application Facility (romsaf). The contributions for ucar and romsaf are currently active.
This dataset is funded by the NASA Earth Science Data Systems and the Advancing Collaborative Connections for Earth System Science (ACCESS) 2019 program.
aerial imageryagricultureclimatecogearth observationgeospatialimage processingland covermachine learningsatellite imagery
Global and regional Canopy Height Maps (CHM). Created using machine learning models on high-resolution worldwide Maxar satellite imagery.
atmosphereclimateclimate modelgeospatiallandmodelsustainabilityzarr
The NA-CORDEX dataset contains regional climate change scenario data and guidance for North America, for use in impacts, decision-making, and climate science. The NA-CORDEX data archive contains output from regional climate models (RCMs) run over a domain covering most of North America using boundary conditions from global climate model (GCM) simulations in the CMIP5 archive. These simulations run from 1950–2100 with a spatial resolution of 0.22°/25km or 0.44°/50km. This AWS S3 version of the data includes selected variables converted to Zarr format from the original NetCDF. Only daily data a...
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 ...
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.
agricultureclimateearth observationenvironmentalmeteorologicalmodelsustainabilitywaterweather
SILO is a database of Australian climate data from 1889 to the present. It provides continuous, daily time-step data products in ready-to-use formats for research and operational applications. SIL...
climateearth observationenvironmentalgeospatialglobaloceans
Global daily-mean sea surface temperatures, presented on a 0.05° latitude-longitude grid, with gaps between available daily observations filled by statistical means, spanning late 1981 to recent time. Suitable for large-scale oceanographic meteorological and climatological applications, such as evaluating or constraining environmental models or case-studies of marine heat wave events. Includes temperature uncertainty information and auxiliary information about land-sea fraction and sea-ice coverage. For reference and citation see: www.nature.com/articles/s41597-019-0236-x.
climateenvironmentalsatellite imagery
A dataset of satellite retrievals of atmospheric methane that extends from 30 April 2018 to present.
atmosphereclimateclimate modelgeospatialmodelzarr
The EURO-CORDEX dataset contains regional climate model data for Europe, for use in impacts, decision-making, and climate science. Currently, the bucket contains monthly datasets of 2m air temperature downscaled from CMIP5 global model datasets using different regional climate models.
air temperatureclimateclimate modelclimate projectionsCMIP6cogearth observationenvironmentalglobalmodelNASA Center for Climate Simulation (NCCS)near-surface relative humiditynear-surface specific humiditynetcdfprecipitation
The NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four "Tier 1" greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The CMIP6 GCM runs were developed in support of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). This dataset includes downscaled projections from ScenarioMIP model runs for which daily scenarios were produced and distributed...
climateenvironmentalmeteorologicaloceanssustainabilityweather
This dataset includes hourly sea surface temperature and current data collected by satellite-tracked surface drifting buoys ("drifters") of the NOAA Global Drifter Program. The Drifter Data Assembly Center (DAC) at NOAA’s Atlantic Oceanographic and Meteorological Laboratory (AOML) has applied quality control procedures and processing to edit these observational data and obtain estimates at regular hourly intervals. The data include positions (latitude and longitude), sea surface temperatures (total, diurnal, and non-diurnal components) and velocities (eastward, northward) with accompanying uncertainty estimates. Metadata include identification numbers, experiment number, start location and time, end location and time, drogue loss date, death code, manufacturer, and drifter type.
Please note that data from the Global Drifter Program are also available at 6-hourly intervals but derived via alternative methods. The 6-hourly dataset goes back further in time (1979) and may be more appropriate for studies of long-term, low frequency patterns of the oceanic circulation. Yet, the 6-hourly dataset does not resolve fully high-frequency processes such as tides and inertial oscillations as well as sea surface temperature diurnal variability.
[CITING NOAA - hourly position, current, and sea surface temperature from drifters data. Citation for this dataset should include the following information below.]
Elipot, Shane; Sykulski, Adam; Lumpkin, Rick; ...
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...
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...
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 days in the future. Horizontal resolution drops to 44 miles
(70 kilometers) between grid point for forecasts between one week and two
weeks.
The NOAA Global Forecast Systems (GFS) Warm Start Initial Conditions are
produced by the National Centers for Environmental Prediction Center (NCEP)
to run operational deterministic medium-range numerical weather predictions.
The GFS is built with the GFDL Finite-Volume Cubed-Sphere Dynamical Core (FV3)
and the Grid-Point Statistical Interpolation (GSI) data assimilation system.
Please visit the links below in the Documentation section to find more details
about the model and the data...
agriculturebiodiversitybiologyclimatedigital preservationecosystemsenvironmental
The National Herbarium of New South Wales is one of the most significant scientific, cultural and historical botanical resources in the Southern hemisphere. The 1.43 million preserved plant specimens have been captured as high-resolution images and the biodiversity metadata associated with each of the images captured in digital form. Botanical specimens date from year 1770 to today, and form voucher collections that document the distribution and diversity of the world's flora through time, particularly that of NSW, Austalia and the Pacific.The data is used in biodiversity assessment, syste...
atmosphereclimateearth observationforecastgeosciencehydrologymeteorologicalmodeloceansweather
Global real-time Earth system data deemed by the World Meteorological Organisation (WMO) as essential for provision of services for the protection of life and property and for the well-being of all nations. Data is sourced from all WMO Member countries / territories and retained for 24-hours. Met Office and NOAA operate this Global Cache service curating and publishing the dataset on behalf of WMO.
agricultureclimatedisaster responseearth observationenvironmentalmeteorologicalmodelweather
Global and high-resolution regional atmospheric models from Météo-France.
agricultureclimatecoastalearth observationenvironmentalsustainabilityweather
This dataset contains historical and projected dynamically downscaled climate data for the State of Alaska and surrounding regions at 20km spatial resolution and hourly temporal resolution. Select variables are also summarized into daily resolutions. This data was produced using the Weather Research and Forecasting (WRF) model (Version 3.5). We downscaled both ERA-Interim historical reanalysis data (1979-2015) and both historical and projected runs from 2 GCM’s from the Coupled Model Inter-comparison Project 5 (CMIP5): GFDL-CM3 and NCAR-CCSM4 (historical run: 1970-2005 and RCP 8.5: 2006-2100)....
agricultureagricultureclimatedisaster responseenvironmentaltransportationweather
The Analysis Of Record for Calibration (AORC) is a gridded record of near-surface weather conditions covering the continental United States and Alaska and their hydrologically contributing areas. It is defined on a latitude/longitude spatial grid with a mesh length of 30 arc seconds (~800 m), and a temporal resolution of one hour. Elements include hourly total precipitation, temperature, specific humidity, terrain-level pressure, downward longwave and shortwave radiation, and west-east and south-north wind components. It spans the period from 1979 across the Continental U.S. (CONUS) and from 1981 across Alaska, to the near-present (at all locations). This suite of eight variables is sufficient to drive most land-surface and hydrologic models and is used as input to the National Water Model (NWM) retrospective simulation. While the native AORC process generates netCDF output, the data is post-processed to create a cloud optimized Zarr formatted equivalent for dissemination using cloud technology and infrastructure.
AORC Version 1.1 dataset creation
The AORC dataset was created after reviewing, identifying, and processing multiple large-scale, observation, and analysis datasets. There are two versions of The Analysis Of Record for Calibration (AORC) data.
The initial AORC Version 1.0 dataset was completed in November 2019 and consisted of a grid with 8 elements at a resolution of 30 arc seconds. The AORC version 1.1 dataset was created to address issues "see Table 1 in Fall et al., 2023" in the version 1.0 CONUS dataset. Full documentation on version 1.1 of the AORC data and the related journal publication are provided below.
The native AORC version 1.1 process creates a dataset that consists of netCDF files with the following dimensions: 1 hour, 4201 latitude values (ranging from 25.0 to 53.0), and 8401 longitude values (ranging from -125.0 to -67).
The data creation runs with a 10-day lag to ensure the inclusion of any corrections to the input Stage IV and NLDAS data.
Note - The full extent of the AORC grid as defined in its data files exceed those cited above; those outermost rows and columns of data grids are filled with missing values and are the remnant of an early set of required AORC extents that have since been adjusted inward.
AORC Version 1.1 Zarr Conversion
The goal for converting the AORC data from netCDF to Zarr was to allow users to quickly and efficiently load/use the data. For example, one year of data takes 28 mins to load via NetCDF while only taking 3.2 seconds to load via Zarr (resulting in a substantial increase in speed). For longer periods of time, the percentage increase in speed using Zarr (vs NetCDF) is even higher. Using Zarr also leads to less memory and CPU utilization.
It was determined that the optimal conversion for the data was 1 year worth of Zarr files with a chunk size of 18MB. The chunking was completed across all 8 variables. The chunks consist of the following dimensions: 144 time, 128 latitude, and 256 longitude. To create the files in the Zarr format, the NetCDF files were rechunked using chunk() and "Xarray". After chunking the files, they were converted to a monthly Zarr file. Then, each monthly Zarr file was combined using "to_zarr" to create a Zarr file that represents a full year
Users wanting more than 1 year of data will be able to utilize Zarr utilities/libraries to combine multiple years up to the span of the full data set.
There are eight variables representing the meteorological conditions
Total Precipitaion (APCP_surface)
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...
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, convection, icing, and turbulence diagnosis.
MRMS is being used to develop and test new Federal Aviation Administration (FAA) NextGen products in addition to advancing techniques in quality control, icing detection, and turbulence in collaboration with the National Center for Atmospheric Research, the University Corporation for Atmospheric Research, and Lincoln Laboratories.
MRMS was deployed operationally in 2014 at the National Center for Environmental Prediction (NCEP). All of the 100+ products it produces are available via NCEP to all of the WFOs, RFCs, CWSUs and NCEP service centers. In addition, the MRMS product suite is publicly available to any other entity who wishes to access and use the data. Other federal agencies that use MRMS include FEMA, DOD, FAA, and USDA.
MRMS is the proposed operational version of the WDSS-II and NMQ research systems.
...
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...
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
climateclimate modelelectricityenergyenergy modelingenvironmentalgovernment recordsinfrastructureopen source softwareutilities
The Public Utility Data Liberation Project (PUDL) provides analysis-ready energy system data to climate advocates,
researchers, policymakers, and journalists.
PUDL is an open source data processing pipeline
that makes US energy data easier to access and use programmatically. Hundreds of gigabytes of valuable data
are published by US government agencies, but it's often difficult to work with.
PUDL takes the original spreadsheets, CSV files, and databases and turns them into a unified resource. This allows users to
spend more time on novel analysis and less time on data preparation.
This...
biodiversityclimatecoastalearth observationenvironmentalgeospatialglobalmachine learningmappingnatural resourcesatellite imagerysustainability
A collection of multi-resolution satellite images from both public and commercial satellites. The dataset is specifically curated for training geospatial foundation models.
atmosphereclimateclimate modelearth observationgeosciencegeospatialmeteorologicalsimulationsweatherzarr
Downscaled future and historical climate projections for California and her environs in support of California's Fifth Climate Assessment
atmosphereclimateclimate modelgeospatialicelandmodeloceanssustainability
Data from ARISE-SAI Experiments with CESM2
climatecoastaldisaster responseenvironmentalmeteorologicaloceanssustainabilitywaterweather
The University of Wisconsin Probabilistic Downscaling (UWPD) is a statistically downscaled dataset based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. UWPD consists of three variables, daily precipitation and maximum and minimum temperature. The spatial resolution is 0.1°x0.1° degree resolution for the United States and southern Canada east of the Rocky Mountains.
The downscaling methodology is not deterministic. Instead, to properly capture unexplained variability and extreme events, the methodology predicts a spatially and temporally varying Probability Density Function (PDF) for each variable. Statistics such as the mean, mean PDF and annual maximum statistics can be calculated directly from the daily PDF and these statistics are included in the dataset. In addition, “standard”, “raw” data is created by randomly sampling from the PDFs to create a “realization” of the local scale given the large-scale from the climate model. There are 3 realizations for temperature and 14 realizations for precipitation.
...
analyticsblockchainclimatecommercecopyright monitoringcsvfinancial marketsgovernancegovernment spendingjsonmarket datasocioeconomicstatisticstransparencyxml
The Legal Entity Identifier (LEI) is a 20-character, alpha-numeric code based on the ISO 17442 standard developed by the International Organization for Standardization (ISO). It connects to key reference information that enables clear and unique identification of legal entities participating in financial transactions. Each LEI contains information about an entity’s ownership structure and thus answers the questions of 'who is who’ and ‘who owns whom’. Simply put, the publicly available LEI data pool can be regarded as a global directory, which greatly enhances transparency in the global ma...
atmosphereclimateclimate modelCMIP6geospatialicelandmodeloceanssustainability
Data from the UK Earth System Model (UKESM1) ARISE-SAI experiment. The UKESM1 ARISE-SAI experiment explores the impacts of geoengineering via the injection of sulphur dioxide (SO2) into the stratosphere in order to keep global mean surface air temperature near 1.5 C above the pre-industrial climate. Data includes a five member ensemble of simulations with SO2 injection plus a five member ensemble of SSP2-4.5 simulations from CMIP6 to serve as a reference data set
climatedisaster responseelevationgeospatiallidar
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...
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 temperature (.1 Fahrenheit)
Mean dew point (.1 Fahrenheit)
Mean sea level pressure (.1 mb)
Mean station pressure (.1 mb)
Mean visibility (.1 miles)
Mean wind speed (.1 knots)
Maximum sustained wind speed (.1 knots)
Maximum wind gust (.1 knots)
Maximum temperature (.1 Fahrenheit)
Minimum temperature (.1 Fahrenheit)
Precipitation amount (.01 inches)
Snow depth (.1 inches)
Indicator for occurrence of: Fog, Rain or Drizzle, Snow or Ice Pellets, Hail, Thunder, Tornado/Funnel Cloud.
G...
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 ...
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...
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...
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...
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 (https://github.com/NOAA-EMC/WW3/tree/develop/regtests/ww3_ufs1.3). ...
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...
atmosphereclimatedata assimilationforecastgeosciencegeospatiallandmeteorologicalmodelnetcdfweather
NSF NCAR is providing a NetCDF-4 structured version of the 0.25 degree atmospheric ECMWF Reanalysis 5 (ERA5) to the AWS ODSP. ERA5 is produced using high-resolution forecasts (HRES) at 31 kilometer resolution (one fourth the spatial resolution of the operational model) and a 62 kilometer resolution ten member 4D-Var ensemble of data assimilation (EDA) in CY41r2 of ECMWF's Integrated Forecast System (IFS) with 137 hybrid sigma-pressure (model) levels in the vertical, up to a top level of 0.01 hPa. Atmospheric data on these levels are interpolated to 37 pressure levels (the same levels as in...
air qualityclimateearth observationmeteorologicalweather
Air Quality is a global SILAM atmospheric composition and air quality forecast performed on a daily basis for > 100 species and covering the troposphere and the stratosphere. The output produces 3D concentration fields and aerosol optical thickness. The data are unique: 20km resolution for global AQ models is unseen worldwide.
air qualityclimateenvironmentalgeospatialradiation
An ongoing collection of radiation and air quality measurements taken by devices involved in the Safecast project.
climateclimate modelclimate projectionsCMIP6earth observationnetcdf
CCKP provides open access to a comprehensive suite of climate and climate change resources derived from the latest generation of climate data archives. Products are based on a consistent and transparent approach with a systematic way of pre-processing the raw observed and model-based projection data to enable inter-comparable use across a broad range of applications. Climate products consist of basic climate variables as well as a large collection (70+) of more specialized, application-orientated variables and indices across different scenarios. Precomputed data can be extracted per specified ...
agricultureclimatedisaster responseenvironmentalmeteorologicalweather
The GraphCast Global Forecast System (GraphCastGFS) is an experimental system set up by the National Centers for Environmental Prediction (NCEP) to produce medium range global forecasts. The horizontal resolution is a 0.25 degree latitude-longitude grid (about 28 km). The model runs 4 times a day at 00Z, 06Z, 12Z and 18Z cycles. Major atmospheric and surface fields including temperature, wind components, geopotential height, specific humidity, and vertical velocity, are available. The products are 6 hourly forecasts up to 10 days. The data format is GRIB2.
The GraphCastGFS system is an experimental weather forecast model built upon the pre-trained Google DeepMind’s GraphCast Machine Learning Weather Prediction (MLWP) model. The GraphCast model is implemented as a message-passing graph neural network (GNN) architecture with “encoder-processor-decoder” configuration. It uses an icosahedron grid with multiscale edges and has around 37 million parameters. This model is pre-trained with ECMWF’s ERA5 reanalysis data. The GraphCastGFSl takes two model states as initial conditions (current and 6-hr previous states) from NCEP 0.25 degree GDAS analysis data and runs GraphCast (37 levels) and GraphCast_operational (13 levels) with a pre-trained model provided by GraphCast. Unit conversion to the GDAS data is conducted to match the input data required by GraphCast and to generate forecast products consistent with GFS from GraphCastGFS’ native forecast data.
The GraphCastGFS version 2 made the following changes from the GraphcastCastGFS version 1.
climatesustainability
The CSIRO Climate retrospective Analysis and Forecast Ensemble system: version 1 (CAFE60v1) provides a large ensemble retrospective analysis of the global climate system from 1960 to present with sufficiently many realizations and at spatio-temporal resolutions suitable to enable probabilistic climate studies. Using a variant of the ensemble Kalman filter, 96 climate state estimates are generated over the most recent six decades. These state estimates are constrained by monthly mean ocean, atmosphere and sea ice observations such that their trajectories track the observed state while enabling ...
agricultureclimatefood securitysustainability
High resolution climate data to help assess the impacts of climate change primarily on agriculture. These open access datasets of climate projections will help researchers make climate change impact assessments.
climateearth observationearthquakessatellite imageryweather
Various kinds of weather raw data and charts from Central Weather Administration.
climateearth observationearthquakessatellite imageryweather
Various kinds of weather raw data and charts from Central Weather Bureau.
agricultureair qualityair temperatureatmosphereclimateclimate modelclimate projectionsCMIP5CMIP6ecosystemselevationenvironmentalEulerianeventsfloodsfluid dynamicsgeosciencegeospatialhdf5healthHPChydrologyinfrastructureland coverland usemeteorologicalmodelnear-surface air temperaturenear-surface relative humiditynear-surface specific humiditynetcdfopen source softwarephysicspost-processingprecipitationradiationsimulationsuswaterweather
The data are a subset of the EPA Dynamically Downscaled Ensemble (EDDE), Version 1. EDDE is a collection of physics-based modeled data that represent 3D atmospheric conditions for historical and future periods under different scenarios. The EDDE Version 1 datasets cover the contiguous United States at a horizontal grid spacing of 36 kilometers at hourly increments. EDDE Version 1 includes simulations that have been dynamically downscaled from multiple global climate models (GCMs) under both mid- and high-emission scenarios from the Fifth Coupled Model Intercomparison Project (CMIP5) using the...
agricultureclimateearth observationmeteorologicalweather
HIRLAM (High Resolution Limited Area Model) is an operational synoptic and mesoscale weather prediction model managed by the Finnish Meteorological Institute.
agricultureclimatecoastalearth observationenvironmentalsustainabilityweather
This dataset contains historical and projected dynamically downscaled climate data for the Southeast region of the State of Alaska at 1 and 4km spatial resolution and hourly temporal resolution. Select variables are also summarized into daily resolutions. This data was produced using the Weather Research and Forecasting (WRF) model (Version 4.0). We downscaled both Climate Forecast System Reanalysis (CFSR) historical reanalysis data (1980-2019) and both historical and projected runs from two GCM’s from the Coupled Model Inter-comparison Project 5 (CMIP5): GFDL-CM3 and NCAR-CCSM4 (historical ru...
climatenetcdfprecipitation
GCMs under CMIP6 have been widely used to investigate climate change impacts and put forward associated adaptation and mitigation strategies. However, the relatively coarse spatial resolutions (usually 100~300km) preclude their direct applications at regional scales, which are exactly where the analysis (e.g., hydrological model simulation) is performed. To bridge this gap, a typical approach is to ‘refine’ the information from GCMs through regional climate downscaling experiments, which can be conducted statistically, dynamically, or a combination thereof. Statistical downscaling establishes ...
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’s (NASA) Ice, Cloud and land Elevation SATellite-2 (ICESat-2), an Earth observing, space-based light detection and ranging (LiDAR)
capability, as a useful bathymetry tool for nearshore bathymetry information in differing environmental conditions. Upon validating the ICESat-2 bathymetry retrievals relative to sea floor
type, water clarity, and water surface dynamics, the next objective is to use ICESat-2 as a calibration tool to improve existing Satellite Derived Bathymetry (SDB) coastal bathymetry products
with poor coastal depth information but superior spatial coverage. Current resources that monitor coastal bathymetry can have large vertical depth errors (up to 50 percent) in the nearshore
region; however, derived results from ICESat-2 shows promising results for improving the accuracy of the bathymetry information in the nearshore region.
Project Overview
One of NGA’s and NOAA’s primary missions is to provide safety of navigation information. However, coastal depth information is still lacking in some regions—specifically, remote regions. In fact, it has been reported that 80 percent of the entire seafloor has not been mapped. Traditionally, airborne LiDARs and survey boats are used to map the seafloor, but in remote areas, we have to rely on satellite capabilities, which currently lack the vertical accuracy desired to support safety of navigation in shallow water. In 2018, NASA launched a space-based LiDAR system called ICESat-2 that has global coverage and a polar orbit originally designed to monitor the ice elevation in polar regions. Remarkably, because it has a green laser beam, ICESat-2 also happens to collect bathymetry information ICESat-2. With algorithm development provided by University of Texas (UT) Austin, NGA Research and Development (R&D) leveraged the ICESat-2 platform to generate SCuBA, an automated depth retrieval algorithm for accurate, global, refraction-corrected underwater depths from 0 m to 30 m, detailed in Figure 1 of the documentation. The key benefit of this product is the vertical depth accuracy of depth retrievals, which is ideal for a calibration tool. NGA and NOAA National Geodetic Survey (NGS), partnered to make this product available to the public for all US territories.
...
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-dimensional fields of water temperature, salinity, and currents. The water level outputs represent the combined tidal and subtidal water surface elevations and are referenced to xGEOID20B
STOFS-3D-Atlantic has been developed to serve the marine navigation, weather forecasting, and disaster mitigation user communities. It is developed in a collaborative effort between the NOAA/National Ocean Service (NOS)/Office of Coast Survey, the NOAA/National Weather Service (NWS)/National Centers for Environmental Prediction (NCEP) Central Operations (NCO), and the Virginia Institute of Marine Science.
STOFS-3D-Atlantic employs the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM) as the hydrodynamic model core. Its unstructured grid consists of 2,926,236 nodes and 5,654,157 triangular or quadrilateral elements. Grid resolution is 1.5-2 km near the shoreline, ~600 m for the floodplain, down to 8 m for watershed rivers (at least 3 nodes across each river cross-section), and around 2-10 m for levees. Along the U.S. coastline, the land boundary of the domain aligns with the 10-m contour above xGEOID20B, encompassing the coastal transitional zone most vulnerable to coastal and inland flooding.
STOFS-3D-Atlantic makes uses of outputs from the National Water Model (NWM) to include inland hydrology and extreme precipitation effects on coastal flooding; forecast guidance from the NCEP Global Forecast System (GFS) and High-Resolution Rapid Refresh (HRRR) model as the surface meteorological forci...
agricultureclimatemeteorologicalsustainabilityweather
NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).
Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.
Atmospheric Climate Data Records are measurements of several global variables to help characterize the atmosphere...
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:
NOAA Operational Forecast System (OFS)
NOAA Global Real-Time Ocean Forecast System (Global RTOFS)
NOAA National Water Model Short-Range Forecast
Filenames follow the source dataset’s conventions. For example, if the source file is
nos.dbofs.fields.f024.20240527.t00z.nc
Then the cloud-optimized filename is the same, with “.zarr” appended
nos.dbofs.fields.f024.20240527.t00z.nc.zarr
Data Aggregations
We also produce virtual aggregations to group an entire forecast model run, and the “best” available forecast.
Best Forecast (continuously updated) - nos.dbofs.fields.best.nc.zarr
Full Model Run - nos.dbofs.fields.forecast.[YYYYMMDD].t[CC]z.nc.zarr
agricultureclimatemeteorologicalsustainabilityweather
NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).
Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.
Fundamental CDRs are composed of sensor data (e.g. calibrated radiances, brightness temperatures) that have been ...
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...
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...
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 ...
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 Coordinates Ocean Model) (https://www.hycom.org/), which is coupled to the Community Ice CodE (CICE) Version 4 (https://www.arcus.org/witness-the-arctic/2018/5/highlight/1). The RTOFS grid has a 1/12 degree horizontal resolution and 41 hybrid vertical levels on a global tripolar grid.
Since 2020, the RTOFS system implements a multivariate, multi-scale 3DVar data assimilation algorithm (Cummings and Smedstad, 2014) using a 24-hour update cycle. The data types presently assimilated include
(1) satellite Sea Surface Temperature (SST) from METOP-B, JPSS-VIIRS, and in-Situ SST, from ships, fixed and drifting buoys
(2) Sea Surface Salinity (SSS) from SMAP, SMOS, and buoys
(3) profiles of Temperature and Salinity from Animal-borne, Alamo floats, Argo floats, CTD, fixed buoys, gliders, TESAC, and XBT
(4) Absolute Dynamic Topography (ADT) from Altika, Cryosat, Jason-3, Sentinel 3a, 3b, 6a
(5) sea ice concentration from SSMI/S, AMSR2
The system is designed to incorporate new observing systems as the data becomes available.
Once the observations go through a fully automated quality control and thinning process, the increments, or corrections, are obtained by executing the 3D variational algorithm. The increments are then added to the 24-hours forecast fields using a 6-hourly incremental analysis update. An earlier version of the system is described in Garraffo et al (2020).
Garraffo, Z.D., J.A. Cummings, S. Paturi, Y. Hao, D. Iredell, T. Spindler, B. Balasubramanian, I. Rivin, H-C. Kim, A. Mehra, 2020. Real Time Ocean-Sea Ice Coupled Three Dimensional Variational Global Data Assimilative Ocean Forecast System. In Research Activities in Earth System Modeling, edited by E. Astakhova, WMO, World Climate Research Program Report No.6, July 2020.
Cummings, J. A. and O. M. Smedstad. 2013. Variational Data Assimilation for the Global Ocean.
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol II)
S. Park and L. Xu (eds), Springer, Chapter 13, 303-343.
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, and disaster mitigation user communities. STOFS-2D-Global was developed in a collaborative effort between the NOAA/National Ocean Service (NOS)/Office of Coast Survey, the NOAA/National Weather Service (NWS)/National Centers for Environmental Prediction (NCEP) Central Operations (NCO), the University of Notre Dame, the University of North Carolina, and The Water Institute of the Gulf. The model generates forecasts out to 180 hours four times per day; forecast output includes water levels caused by the combined effects of storm surge and tides, by astronomical tides alone, and by sub-tidal water levels (isolated storm surge).
The hydrodynamic model employed by STOFS-2D-Global is the ADvanced CIRCulation (ADCIRC) finite element model. The model is forced by GFS winds, mean sea level pressure, and sea ice. The unstructured grid used by STOFS-2D-Global consists of 12,785,004 nodes and 24,875,336 triangular elements. Coastal res...
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:
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...
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.
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...
agricultureclimatemeteorologicaloceanssustainabilityweather
NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).
Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.
Oceanic Climate Data Records are measurements of oceans and seas both surface and subsurface as well as frozen st...
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...
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 ...
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...
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...
agricultureclimatemeteorologicalsustainabilityweather
NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).
Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.
Terrestrial CDRs are composed of sensor data that have been improved and quality controlled over time, together w...
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 research.
EpiNOAA is an analysis ready dataset that consists of a daily time-series of nClimGrid measures (maximum temperature, minimum temperature, average temperature, and precipitation) at the county scale. Each file provides daily values for the Continental United States. Data are available from 1951 to the present. Daily data are updated every 3 days with a preliminary data file and replaced with the scaled (i.e., quality controlled) data file every three months. This derivative data product is an enhancement from the original daily nClimGrid dataset in that all four weather parameters are now p...
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 was initialized from these reanalyses, which were pre-processed for the UFS model components, including the GFDL Finite-Volume Cubed-Sphere Dynamical Core (FV3; 25 km, 127 vertical levels) and the Modular Ocean Model (MOM6; ¼ degree tri-polar grid, 72 vertical levels). This replay methodology enforces a predetermined model state while allowing cross-component fluxes and unconstrained processes to be computed.
For the land surface, NOAA’s JEDI-based land data assimilation system incorporated snow depth observations from the NCEI Global Historical Climatology Network (GHCN) and satellite-derived snow cover from the U.S. National Ice Center. The JEDI Sea-ice Ocean and Coupled Analysis system (SOCA) adjusted sea-ice thickness and concentration for consistency with ORAS5.
The original dataset spanned January 1994 to October 2023, with plans for ongoing updates and a 1-degree version covering 1958 to 2023. The dataset is hosted on AWS and GCP clou...
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 enhances code management practices, fosters user accessibility, and promotes adherence to established testing protocols. It enables developers to conduct testing efficiently and consistently, ensuring code integrity and reliability through the use of established technologies such as CMake and CTest. When integrated with containerization techniques, the HTF facilitates portability of test cases and promotes reproducibility across different computing environments. This approach reduces the computational overhead and enhances collaboration within the UFS community by providing a unified testing framework.
Acknowledgment - The Unified Forecast System (UFS) atmosphere-ocean coupled model...
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 simulations. In this traditional uncoupled mode, near-surface atmospheric forcing data is required as input. Sample forcing and restart data are provided in this data bucket.
The Noah-MP LSM has evolved through community efforts to pursue and refine a modern-era LSM suitable for use in the National Centers for Environmental Prediction (NCEP) operational weather and climate prediction models. This collaborative effort continues with participation from entities such as NCAR, NCEP, NASA, and university groups.
For details regarding the physical parameterizations used in Noah-MP, see "[Niu, et al. (2011)] (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2010JD015139)". The "[Land DA User’s Guide] (https://land-da.readthedocs.io/en/latest/)" provides information on building and running the Land DA System in offline mode. Users can access additional technical support via the "[UFS GitHub Discussions] (https://github.com/NOAA-EPIC/land-offline_workflow/discussions)" for the L...
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 (DATM-MOM6-CICE6) model was applied with two atmospheric forcing data sets: CFSR from 1979 to 1999 and GEFS from 2000 to 2019. Assimilated observation data sets include extensive space-based marine observations and conventional direct measurements of in situ profile data sets.
This first UFS-marine interim reanalysis product is released to the broader weather and earth system modeling and analysis communities to obtain scientific feedback and applications for the development of the next generation operational numerical weather prediction system at the National Weather Service(NWS). The released file sets include two parts 1.) 1979 - 2019 UFS-DATM-MOM6-CICE6 model free runs and 2) 1979-2019 reanalysis cycle outputs (see descriptions embedded in each file set). Analyzed sea ice and ocean variables are ocean temperature, salinity, sea surface height, and sea ice conce...
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" includes information on these components and provides detailed instructions on how to build and run the SRW Application. Users can access additional technical support via the "UFS GitHub Discussions"
This data registry contains the data required to run the “out-of-the-box” SRW Application case. The SRW App requires numerous input files to run, including static datasets (fix files containing climatological information, terrain and land use data), initial condition data files, lateral boundary condition data files, and model configuration files (such as namelists). The SRW App experiment generation system also contains a set of workflow end-to-end (WE2E) tests that exercise various configurations of the system (e.g., different grids, physics suites). Data for running a subset of these WE2E tests are also included within this registry.
Users can generate forecasts for dates not included in this data registry by downloading and manually adding raw model files for the desired dates. Many of these model files are publicly available and can be accessed via links on the "Developmental Testbed Center" webs...
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 in log files and these files will be committed to the UFS-WM repository along with the code changes. Currently, the UFS-WM RTs have been developed to support several applications targeted for operational implementations including the global weather forecast, subseasonal to seasonal forecasts, hurricane forecast, regional rapid refresh forecast, and ocean analysis.
At this time, there are 123 regression tests to support the UFS applications. The tests are evolving along with the development merged to the UFS-WM code repository. The regression test framework has been developed in the UFS-WM to run these tests on tier-1 supported systems. Each of the regression tests require a set of input data files and configuration files. The configuration files include namelist and model configuration files residing within the UFS-WM code repository. The input data includes initial conditions, climatology data, and fixed data sets such as orographic data and grid sp...
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 hence the utility in forecasting space weather disturbances) of model results, the domain of the MHD model (Enlil) is limited from 21.5 Solar Radii (R_s) to just beyond the orbit of Earth, while the inner portion, spanning from the solar photosphere to 21.5R_s, is characterized by the WSA model. This coupled modeling system is driven by solar synoptic maps composed of numerous magnetogram observations from the National Solar Observatory’s (NSO) Global Oscillation Network Group (GONG). Such maps provide a full surface description of solar photospheric magnetic flux density, while not accounting for the evolution of surface features for regions outside the view of the observatories.
In its current configuration (NOAA WSA-Enlil V3.0), the modeling system consists of WSA V5.4 and Enlil V2.9e. The system relies upon the zero point corrected GONG synoptic maps (mrzqs) to define the inner photospheric boundary.
The operational data files provided in this bucket include NetCDF files containing 3-dimensional gridded neutral density from 100 to 1000 km, Total Electron Content (TEC), and Maximum Usable Frequency (MUF).
The full 3D datasets from the operational model are provided here as compressed tar files with naming convention wsa_enlil.mrid########.full3d.tgz. These files consist of the full set of 3D datacubes (tim..nc), all time series results stored at predefined observation points (evo..nc), and supplemented by the operational CME fits (conefiles) and the operationally...
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 top of approximately 3 x 10-7 Pa (typically 400-600km depending on levels of solar activity). Additional upper atmospheric physics and chemistry, including electrodynamics and plasma processes, are included. The IPE model provides the plasma component of the atmosphere. It is a time-dependent, global 3D model of the ionosphere and plasmasphere from 90 km to approximately 10,000 km. WAM fields of winds, temperature, and molecular and atomic atmospheric composition are coupled to IPE to enable the plasma to respond to changes driven by the neutral atmosphere.
The operational WAM-IPE is currently running in two different Concepts of Operation (CONOPS) to produce results of Nowcast and Forecast. The WAM-IPE real-time nowcast system (WRS) ingests real-time solar wind parameters every 5 minutes from NOAA’s spacecrafts located at Lagrange point 1 (L1) between the Sun and Earth in order to capture rapid changes in the ionosphere and thermosphere due to the sudden onset of geomagnetic storms. The nowcast is reinitialized every six hours to include the latest forcing from the lower atmosphere. The forecast system (WFS) runs four times daily (0, 6, 12, 18 UT), providing two-day forecasts. Observed solar wind parameters are used whenever observational values are available, for the forecast portion, the forecasted 3-hour Kp and daily F10.7 issued by SWFO are ingested into the model to estimate solar wind parameters. Lower atmospheric data assimilation only carries out twice daily at 0 and 12 UT cycles to maintain the stability of the coupled model. Model version v1.2 became available in July 2023, featuring the implementation of the WRS into operations, as well as improvements to the Kp-derived solar wind parameters utilized by WFS forecasts.
The data files within this bucket are provided strictly on a non-operational basis, with no guarantee of timely delivery or availability. There may exist temporal gaps in coverage.
The top-level versioned directories (v1.x) include NetCDF files from operational runs providing 3-dimensional gridded neutral density every 10 minutes with an altitude range from 100 to 1000 km. wfs.YYYYMMDD subdirectories contain two-day forecasts, updated four times daily (cycle initialization 00, 06, 12, 18 UT). wrs.YYYYMMDD subdirectories contain real-time nowcast neutral density outputs, reinitialized ever...
agricultureagricultureclimatedisaster responseenvironmentaloceanstransportationweather
NOAA's Coastal Ocean Reanalysis (CORA) for the Gulf of Mexico and East Coast (GEC) is produced using verified hourly water levels from the Center of Operational Oceanographic Products & Services (CO-OPS), through hydrodynamic modeling from Advanced Circulation "ADCIRC" and Simulating WAves Nearshore "SWAN" models. Data are assimilated, processed, corrected, and processed again before quality assurance and skill assessment with additional verified tide station-based observations.
Details for CORA Dataset
Timeseries - 1979 to 2022
Size - Approx. 20.5TB
Domain - Lat 5.8 to 45.8 ; Long -98.0 to -53.8
Nodes - 1813443 centroids, 3564104 elements
Grid cells - Currently apporximately 505
Spatial Resolution ...
climatelandoceans
The Global Carbon Budget (GCB) is recognised globally as the most comprehensive report on global carbon emissions and sinks. This dataset, updated every year, includes estimates of land and ocean carbon fluxes from the suite of models used in the report.