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NOAA Open Data Dissemination Program

Amazon Web Services has entered into a research agreement with the US National Oceanic and Atmospheric Administration (NOAA) to explore sustainable models to increase the output of open NOAA data. Publicly available NOAA data drives multi-billion dollar industries and critical research efforts. Under this agreement, AWS and its collaborators will look at ways to push more NOAA data to the cloud and build an ecosystem of innovation around it.


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NOAA Geostationary Operational Environmental Satellites (GOES) 16, 17 & 18

agriculturedisaster responseearth observationgeospatialmeteorologicalsatellite imageryweather



NOTICE: As of January 10th 2023, GOES-18 assumed the GOES-West position and all data files are deemed both operational and provisional, so no ‘preliminary, non-operational’ caveat is needed. GOES-17 is now offline, shifted approximately 105 degree West, where it will be in on-orbit storage. GOES-17 data will no longer flow into the GOES-17 bucket. Operational GOES-West products can be found in the GOES-18 bucket.

NEW GOES-18 Data!!! GOES-18 is now provisional and data has began streaming. Data files will be available between Provisional and the Operational Declaration of the satellite, however, data will have the caveat GOES-18 Preliminary, Non-Operational Data. The exception is during the interleave period when ABI Radiances and Cloud and Moisture Imagery data will be shared operationally via the NOAA Open Data Dissemination Program.

GOES satellites (GOES-16, GOES-17, & GOES-18) provide continuous weather imagery and monitoring of meteorological and space environment data across North America. GOES satelli
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NEXRAD on AWS

agricultureearth observationmeteorologicalnatural resourceweather

Real-time and archival data from the Next Generation Weather Radar (NEXRAD) network.

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NOAA Joint Polar Satellite System (JPSS)

agricultureclimatemeteorologicalweather

Near Real Time JPSS data is now flowing! See bucket information on the right side of this page to access products!
Satellites in the JPSS constellation gather global measurements of atmospheric, terrestrial and oceanic conditions, including sea and land surface temperatures, vegetation, clouds, rainfall, snow and ice cover, fire locations and smoke plumes, atmospheric temperature, water vapor and ozone. JPSS delivers key observations for the Nation's essential products and services, including forecasting severe weather like hurricanes, tornadoes and blizzards days in advance, and assessin...

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NOAA Operational Forecast System (OFS)

climatecoastaldisaster responseenvironmentalmeteorologicaloceanswaterweather

ANNOUNCEMENTS: [NOS OFS Version Updates and Implementation of Upgraded Oceanographic Forecast Modeling Systems for Lakes Superior and Ontario; Effective October 25, 2022}(https://www.weather.gov/media/notification/pdf2/scn22-91_nos_loofs_lsofs_v3.pdf)

For decades, mariners in the United States have depended on NOAA's Tide Tables for the best estimate of expected water levels. These tables provide accurate predictions of the astronomical tide (i.e., the change in water level due to the gravitational effects of the moon and sun and the rotation of the Earth); however, they cannot predict water-level changes due to wind, atmospheric pressure, and river flow, which are often 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...

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NOAA Rapid Refresh Forecast System (RRFS) [Prototype]

agricultureclimatemeteorologicalweather

NOTE** 3DRTMA data is being populated in the RRFS bucket under the prefix 3DRTMA and diag. The content provided supports model development. These are not yet operational NWS products and should not to be relied upon for operational purposes. This web site is not subject to 24/7 support, and thus may be unavailable during system outages.

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.


The real-time RRFS prototype is experimental and evolving. It is not under 24x7 monitoring and is not operational. Output may be delayed or missing. Outputs will change. When significant changes to output take place, this description will be updated.

We currently provide hourly deterministic forecasts at 3 km grid spacing out to 60 hours at 00, 06, 12, and 18 UTC, and out to 18 hours for other cycles. Output is organized by cycle date and cycle hour.For example, 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

Meaning that this is the RRFS_A initialized at 00 UTC, covers the CONUS domain, and is the native level post-processed gridded data at hour 18. This output is on a Lambert Conic Conformal gird at 3 km grid spacing.

The second output file in grib2 format is:

rrfs.t00z.prslev.f018.conus_3km.grib2

The “prslev” descriptor indicates that this post-processed gridded data is output on pressure levels.For users interested in other domains, output is provided on the full 3-km North American grid and also subset over Alaska, Hawaii, and Puerto Rico. The files are identified as follows:

North America: 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.grib2

Beginning on December 8th, 2023 we now provide prototype RRFSv1 ensemble output and products. Output is available for 00, 06, 12, and 18 UTC cycles, and is organized by cycle date and cycle hour. For example, rrfs_a/rrfs_a.20231214/00/mem0001 contains the forecast from member 1, and rrfs_a/rrfs_a.20231214/00/enspost_timelag co...

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JMA Himawari-8/9

agriculturedisaster responseearth observationgeospatialmeteorologicalsatellite imageryweather

Himawari-9, stationed at 140.7E, owned and operated by the Japan Meteorological Agency (JMA), is a geostationary meteorological satellite, with Himawari-8 as on-orbit back-up, that provides constant and uniform coverage of east Asia, and the west and central Pacific regions from around 35,800 km above the equator with an orbit corresponding to the period of the earth’s rotation. This allows JMA weather offices to perform uninterrupted observation of environmental phenomena such as typhoons, volcanoes, and general weather systems. Archive data back to July 2015 is available for Full Disk (AHI-L...

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NOAA Global Historical Climatology Network Daily (GHCN-D)

agricultureclimatemeteorologicalweather


UPDATE TO GHCN PREFIXES - The NODD team is working on improving performance and access to the GHCNd data and will be implementing an updated prefix structure. For more information on the prefix changes, please see the "READ ME on the NODD Github". If you have questions, comments, or feedback, please reach out to nodd@noaa.gov with GHCN in the subject line.

Global Historical Climatology Network - Daily is a dataset from NOAA that contains daily observations over global land areas. It contains station-based measurements...

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NOAA High-Resolution Rapid Refresh (HRRR) Model

agricultureclimatedisaster responseenvironmentalweather

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

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

climateenvironmentalmeteorologicaloceanssustainabilityweather

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

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

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

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NOAA Global Ensemble Forecast System (GEFS) Re-forecast

agricultureclimatemeteorologicalweather

NOAA has generated a multi-decadal reanalysis and reforecast data set to accompany the next-generation version of its ensemble prediction system, the Global Ensemble Forecast System, version 12 (GEFSv12). Accompanying the real-time forecasts are “reforecasts” of the weather, that is, retrospective forecasts spanning the period 2000-2019. These reforecasts are not as numerous as the real-time data; they were generated only once per day, from 00 UTC initial conditions, and only 5 members were provided, with the following exception. Once weekly, an 11-member reforecast was generated, and these ex...

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NOAA Climate Forecast System (CFS)

agricultureclimatemeteorologicalweather

The Climate Forecast System (CFS) is a model representing the global interaction between Earth's oceans, land, and atmosphere. Produced by several dozen scientists under guidance from the National Centers for Environmental Prediction (NCEP), this model offers hourly data with a horizontal resolution down to one-half of a degree (approximately 56 km) around Earth for many variables. CFS uses the latest scientific approaches for taking in, or assimilating, observations from data sources including surface observations, upper air balloon observations, aircraft observations, and satellite obser...

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NOAA Emergency Response Imagery

aerial imageryclimatecogdisaster responseweather

In order to support NOAA's homeland security and emergency response requirements, the National Geodetic Survey Remote Sensing Division (NGS/RSD) has the capability to acquire and rapidly disseminate a variety of spatially-referenced datasets to federal, state, and local government agencies, as well as the general public. Remote sensing technologies used for these projects have included lidar, high-resolution digital cameras, a film-based RC-30 aerial camera system, and hyperspectral imagers. Examples of rapid response initiatives include acquiring high resolution images with the Emerge/App...

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NOAA Unified Forecast System Subseasonal to Seasonal Prototypes

agricultureclimatedisaster responseenvironmentalmeteorologicaloceansweather

The Unified Forecast System Subseasonal to Seasonal prototypes consist of reforecast data from the UFS atmosphere-ocean coupled model experimental prototype version 5, 6, 7, and 8 produced by the Medium Range and Subseasonal to Seasonal Application team of the UFS-R2O project. The UFS prototypes are the first dataset released to the broader weather community for analysis and feedback as part of the development of the next generation operational numerical weather prediction system from NWS. The datasets includes all the major weather variables for atmosphere, land, ocean, sea ice, and ocean wav...

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NOAA World Ocean Database (WOD)

climateoceans

The World Ocean Database (WOD) is the largest uniformly formatted, quality-controlled, publicly available historical subsurface ocean profile database. From Captain Cook's second voyage in 1772 to today's automated Argo floats, global aggregation of ocean variable information including temperature, salinity, oxygen, nutrients, and others vs. depth allow for study and understanding of the changing physical, chemical, and to some extent biological state of the World's Oceans. Browse the bucket via the AWS S3 explorer: https://noaa-wod-pds.s3.amazonaws.com/index.html

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  • The World Ocean Database User's Manual by Hernan E. Garcia, Tim P. Boyer, Ricardo A. Locarnini, Olga K. Baranova, Melissa M. Zweng
  • The World Ocean Database Introduction by Tim P. Boyer, Olga K. Baranova, Carla Coleman, Hernan E. Garcia, Alexandra Grodsky, Ricardo A. Locarnini, Alexey V. Mishonov, Christopher R. Paver, James R. Reagan, Dan Seidov, Igor V. Smolyar, Katharine W. Weathers, Melissa M. Zweng

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

climatecoastaldisaster responseenvironmentalmeteorologicaloceanssustainabilitywaterweather

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

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

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NOAA Coastal Lidar Data

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...

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NOAA Global Forecast System (GFS)

agricultureclimatedisaster responseenvironmentalmeteorologicalweather

NOTE - Upgrade NCEP Global Forecast System to v16.3.0 - Effective November 29, 2022 See notification HERE

The Global Forecast System (GFS) is a weather forecast model produced by the National Centers for Environmental Prediction (NCEP). Dozens of atmospheric and land-soil variables are available through this dataset, from temperatures, winds, and precipitation to soil moisture and atmospheric ozone concentration. The entire globe is covered by the GFS at a base horizontal resolution of 18 miles (28 kilometers) between grid points, which is used by the operational forecasters who predict weather out to 16 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...

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NOAA Global Surface Summary of Day

agricultureclimateenvironmentalnatural resourceregulatoryweather

Global Surface Summary of the Day is derived from The Integrated Surface Hourly (ISH) dataset. The ISH dataset includes global data obtained from the USAF Climatology Center, located in the Federal Climate Complex with NCDC. The latest daily summary data are normally available 1-2 days after the date-time of the observations used in the daily summaries. The online data files begin with 1929 and are at the time of this writing at the Version 8 software level. Over 9000 stations' data are typically available. The daily elements included in the dataset (as available from each station) are:
Mean 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
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NOAA Integrated Surface Database (ISD)

agricultureclimatemeteorologicalweather

The Integrated Surface Database (ISD) consists of global hourly and synoptic observations compiled from numerous sources into a gzipped fixed width format. ISD was developed as a joint activity within Asheville's Federal Climate Complex. The database includes over 35,000 stations worldwide, with some having data as far back as 1901, though the data show a substantial increase in volume in the 1940s and again in the early 1970s. Currently, there are over 14,000 "active" stations updated daily in the database. The total uncompressed data volume is around 600 gigabytes; however, it ...

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NOAA National Digital Forecast Database (NDFD)

agricultureclimatemeteorologicalweather

Please note NWS is Soliciting Comments until April 30, 2024 on Availability of Probabilistic Snow Grids for Select Weather Forecast Offices (WFOs) as an Experimental Element in the National Digital Forecast Database (NDFD) for the Contiguous United States (CONUS). A PDF version of the Public Notice can be found "HERE"

The National Digital Forecast Database (NDFD) is a suite of gridded forecasts of sensible weather elements (e.g., cloud cover, maximum temperature). Forecasts prepared by NWS field offices working in collaboration with the National Centers for Environmental Predictio...

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NOAA National Water Model Short-Range Forecast

agricultureagricultureclimatedisaster responseenvironmentaltransportationweather

The National Water Model (NWM) is a water resources model that simulates and forecasts water budget variables, including snowpack, evapotranspiration, soil moisture and streamflow, over the entire continental United States (CONUS). The model, launched in August 2016, is designed to improve the ability of NOAA to meet the needs of its stakeholders (forecasters, emergency managers, reservoir operators, first responders, recreationists, farmers, barge operators, and ecosystem and floodplain managers) by providing expanded accuracy, detail, and frequency of water information. It is operated by NOA...

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NOAA S-111 Surface Water Currents Data

oceanswater

S-111 is a data and metadata encoding specification that is part of the S-100 Universal Hydrographic Data Model, an international standard for hydrographic data. This collection of data contains surface water currents forecast guidance from NOAA/NOS Operational Forecast Systems, a set of operational hydrodynamic nowcast and forecast modeling systems, for various U.S. coastal waters and the great lakes. The collection also contains surface current forecast guidance output from the NCEP Global Real-Time Ocean Forecast System (GRTOFS) for some offshore areas. These datasets are encoded as HDF-5 f...

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NOAA U.S. Climate Normals

agricultureclimatemeteorologicalsustainabilityweather

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

NCEI generates the official U.S. norma
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NOAA Wave Ensemble Reforecast

agricultureclimatemeteorologicalweather

This is a 20-year global wave reforecast generated by WAVEWATCH III model (https://github.com/NOAA-EMC/WW3) forced by GEFSv12 winds (https://noaa-gefs-retrospective.s3.amazonaws.com/index.html). The wave ensemble was run with one cycle per day (at 03Z), spatial resolution of 0.25°X0.25° and temporal resolution of 3 hours. There are five ensemble members (control plus four perturbed members) and, once a week (Wednesdays), the ensemble is expanded to eleven members. The forecast range is 16 days and, once a week (Wednesdays), it extends to 35 days. More information about the wave modeling, wave grids and calibration can be found in the WAVEWATCH III regtest ww3_ufs1.3 (https://github.com/NOAA-EMC/WW3/tree/develop/regtests/ww3_ufs1.3). ...

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NOAA/PMEL Ocean Climate Stations Moorings

climateenvironmentaloceansweather

The mission of the Ocean Climate Stations (OCS) Project is to make meteorological and oceanic measurements from autonomous platforms. Calibrated, quality-controlled, and well-documented climatological measurements are available on the OCS webpage and the OceanSITES Global Data Assembly Centers (GDACs), with near-realtime data available prior to release of the complete, downloaded datasets.

OCS measurements served through the Big Data Program come from OCS high-latitude moored buoys located in the Kuroshio Extension (32°N 145°E) and the Gulf of Alaska (50°N 145°W). Initiated in 2004 and 20
...

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

climatecoastaldisaster responseenvironmentalglobalmarine navigationmeteorologicaloceanssustainabilitywaterweather

NOTICE - The Coast Survey Development Laboratory (CSDL) in NOAA/National Ocean Service (NOS)/Office of Coast Survey is upgrading the Surge and Tide Operational Forecast System (STOFS, formerly ESTOFS) to Version 2.1.4. A Service Change Notice (SCN) has been issued and can be found "HERE"

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

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

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

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

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NOAA Atmospheric Climate Data Records

agricultureclimatemeteorologicalsustainabilityweather

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

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

Atmospheric Climate Data Records are measurements of several global variables to help characterize the atmosphere
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NOAA Continuously Operating Reference Stations (CORS) Network (NCN)

broadcast ephemerisContinuously Operating Reference Station (CORS)earth observationgeospatialGNSSGPSmappingNOAA CORS Network (NCN)post-processingRINEXsurvey

The NOAA Continuously Operating Reference Stations (CORS) Network (NCN), managed by NOAA/National Geodetic Survey (NGS), provide Global Navigation Satellite System (GNSS) data, supporting three dimensional positioning, meteorology, space weather, and geophysical applications throughout the United States. The NCN is a multi-purpose, multi-agency cooperative endeavor, combining the efforts of hundreds of government, academic, and private organizations. The stations are independently owned and operated. Each agency shares their GNSS/GPS carrier phase and code range measurements and station metadata with NGS, which are analyzed and distributed free of charge. ...

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NOAA Fundamental Climate Data Records (FCDR)

agricultureclimatemeteorologicalsustainabilityweather

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

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

Fundamental CDRs are composed of sensor data (e.g. calibrated radiances, brightness temperatures) that have been
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NOAA Global Ensemble Forecast System (GEFS)

agricultureclimatemeteorologicalweather

The Global Ensemble Forecast System (GEFS), previously known as the GFS Global ENSemble (GENS), is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental Prediction (NCEP) started the GEFS to address the nature of uncertainty in weather observations, which is used to initialize weather forecast models. The GEFS attempts to quantify the amount of uncertainty in a forecast by generating an ensemble of multiple forecasts, each minutely different, or perturbed, from the original observations. With global coverage, GEFS is produced fo...

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NOAA Global Hydro Estimator (GHE)

agriculturemeteorologicalwaterweather

Global Hydro-Estimator provides a global mosaic imagery of rainfall estimates from multi-geostationary satellites, which currently includes GOES-16, GOES-15, Meteosat-8, Meteosat-11 and Himawari-8. The GHE products include: Instantaneous rain rate, 1 hour, 3 hour, 6 hour, 24 hour and also multi-day rainfall accumulation.

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NOAA Global Mosaic of Geostationary Satellite Imagery (GMGSI)

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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 ...

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NOAA Global Real-Time Ocean Forecast System (Global RTOFS)

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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 Real ...

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NOAA Global Surge and Tide Operational Forecast System 2-D (STOFS-2D-Global)

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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 2.1.4. 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 12,784,991 nodes and 24,875,313 triangular elements. Coastal r...

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NOAA National Bathymetric Source Data

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The National Bathymetric Source (NBS) project creates and maintains high-resolution bathymetry composed of the best available data. This project enables the creation of next-generation nautical charts while also providing support for modeling, industry, science, regulation, and public curiosity. Primary sources of bathymetry include NOAA and U.S. Army Corps of Engineers hydrographic surveys and topographic bathymetric (topo-bathy) lidar (light detection and ranging) data. Data submitted through the NOAA Office of Coast Survey’s external source data process are also included, with gaps...

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NOAA National Blend of Models (NBM)

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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.

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NOAA North American Mesoscale Forecast System (NAM)

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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...

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NOAA Oceanic Climate Data Records

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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
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NOAA Rapid Refresh (RAP)

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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...

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NOAA Real-Time Mesoscale Analysis (RTMA) / Unrestricted Mesoscale Analysis (URMA)

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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
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NOAA S-102 Bathymetric Surface Data

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S-102 is a data and metadata encoding specification that is part of the S-100 Universal Hydrographic Data Model, an international standard for hydrographic data exchange. This collection of data contains bathymetric surfaces from NOAA/NOS/OCS National Bathymetric Source, for various U.S. coastal and offshore waters and the great lakes. These datasets are encoded as HDF5 files conforming to the S-102 specification.

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NOAA Severe Weather Data Inventory (SWDI)

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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...

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NOAA Space Weather Forecast and Observation Data

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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...

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NOAA Terrestrial Climate Data Records

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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
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NOAA U.S. Climate Gridded Dataset (NClimGrid)

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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
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NOAA Unified Forecast System (UFS) Marine Reanalysis: 1979-2019

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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
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NOAA Unified Forecast System Short-Range Weather (UFS SRW) Application

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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...

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NOAA Unified Forecast System Weather Model (UFS-WM) Regression Tests

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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
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