The NCEP operational Global Forecast System analysis and forecast grids are on a 0.25 by 0.25 global latitude longitude grid. Grids include analysis and forecast time steps at a 3 hourly interval from 0 to 240, and a 12 hourly interval from 240 to 384. Model forecast runs occur at 00, 06, 12, and 18 UTC daily. For real-time data access please use the NCEP data server [http://www.nco.ncep.noaa.gov/pmb/products/gfs/]. NOTE: This dataset now has a direct, continuously updating copy located on AWS (https://noaa-gfs-bdp-pds.s3.amazonaws.com/index.html [https://noaa-gfs-bdp-pds.s3.amazonaws.com/index.html]). Therefore, the RDA will stop updating this dataset in early 2025

The Global Forecast System (GFS) is a weather forecast model produced by the National Centers for Environmental Prediction (NCEP). Dozens of atmospheric and land-soil variables are available through this dataset, from temperatures, winds, and precipitation to soil moisture and atmospheric ozone concentration. The GFS data files stored here can be immediately used for OAR/ARL’s NOAA-EPA Atmosphere-Chemistry Coupler Cloud (NACC-Cloud) tool, and are in a Network Common Data Form (netCDF), which is a very common format used across the scientific community. These particular GFS files contain a comprehensive number of global atmosphere/land variables at a relatively high spatiotemporal resolution (approximately 13x13 km horizontal, vertical resolution of 127 levels, and hourly), are not only necessary for the NACC-Cloud tool to adequately drive community air quality applications (e.g., U.S. EPA’s Community Multiscale Air Quality model; https://www.epa.gov/cmaq), but can be very useful for a myriad of other applications in the Earth system modeling communities (e.g., atmosphere, hydrosphere, pedosphere, etc.). While many other data file and record formats are indeed available for Earth system and climate research (e.g., GRIB, HDF, GeoTIFF), the netCDF files here are advantageous to the larger community because of the comprehensive, high spatiotemporal information they contain, and because they are more scalable, appendable, shareable, self-describing, and community-friendly (i.e., many tools available to the community of users). Out of the four operational GFS forecast cycles per day (at 00Z, 06Z, 12Z and 18Z) this particular netCDF dataset is updated daily (/inputs/yyyymmdd/) for the 12Z cycle and includes 24-hr output for both 2D (gfs.t12z.sfcf$0hh.nc) and 3D variables (gfs.t12z.atmf$0hh.nc).

Also available are netCDF formatted Global Land Surface Datasets (GLSDs) developed by Hung et al. (2024). The GLSDs are based on numerous satellite products, and have been gridded to match the GFS spatial resolution (~13x13 km). These GLSDs contain vegetation canopy data (e.g., land surface type, vegetation clumping index, leaf area index, vegetative canopy height, and green vegetation fraction) that are supplemental to and can be combined with the GFS meteorological netCDF data for various applications, including NOAA-ARL's canopy-app. The canopy data variables are climatological, based on satellite data from the year 2020, combined with GFS meteorology for the year 2022, and are created at a daily temporal resolution (/inputs/geo-files/gfs.canopy.t12z.2022mmdd.sfcf000.global.nc)

U.S. National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) numerical weather prediction model 8-day, 3-hourly forecast for the Pacific region at approximately 25-km or 0.25-deg resolution. _CoordSysBuilder=ucar.nc2.dataset.conv.CF1Convention acknowledgement=The Pacific Islands Ocean Observing System (PacIOOS) is funded through the National Oceanic and Atmospheric Administration (NOAA) as a Regional Association within the U.S. Integrated Ocean Observing System (IOOS). PacIOOS is coordinated by the University of Hawaii School of Ocean and Earth Science and Technology (SOEST). cdm_data_type=Grid Conventions=CF-1.6, ACDD-1.3 dataType=Grid date_metadata_modified=2023-01-24 drawLandMask=under Easternmost_Easting=179.75 geospatial_bounds=POLYGON ((-40.0 120.0, 40.0 120.0, 40.0 180.0, -40.0 180.0, -40.0 120.0), (-40.0 -180.0, 40.0 -180.0, 40.0 -80.0, -40.0 -80.0, -40.0 -180.0)) geospatial_bounds_crs=EPSG:4326 geospatial_lat_max=40.0 geospatial_lat_min=-40.0 geospatial_lat_resolution=0.25 geospatial_lat_units=degrees_north geospatial_lon_max=179.75 geospatial_lon_min=-180.0 geospatial_lon_resolution=0.25 geospatial_lon_units=degrees_east history=2017-02-03T00:00:00Z Subset 0.25-deg NCEP GFS daily from nomads server via OPeNDAP and Python. 2023-01-24T21:20:00Z Removed erroneous inclusion of "net" in the long_name and standard_name of the variables dlwrfsfc (surface_downwelling_longwave_flux) and dswrfsfc (surface_downwelling_shortwave_flux). Added variables ulwrfsfc (surface_upwelling_longwave_flux) and uswrfsfc (surface_upwelling_shortwave_flux) for users wishing to compute net downward fluxes (e.g., dlwrfsfc minus ulwrfsfc and dswrfsfc minus uswrfsfc). ; FMRC Best Dataset id=ncep_pac infoUrl=https://www.nco.ncep.noaa.gov/pmb/products/gfs/ institution=National Oceanic and Atmospheric Administration (NOAA) instrument=Not Applicable > Not Applicable instrument_vocabulary=GCMD Instrument Keywords ISO_Topic_Categories=climatologyMeteorologyAtmosphere keywords_vocabulary=GCMD Science Keywords location=Proto fmrc:NCEP_Pacific_Atmospheric_Model locations=Geographic Region > Oceania, Ocean > Pacific Ocean locations_vocabulary=GCMD Location Keywords metadata_link=https://www.pacioos.hawaii.edu/metadata/ncep_pac.html naming_authority=org.pacioos Northernmost_Northing=40.0 platform=Models/Analyses > > NCEP-GFS > NCEP Global Forecast System, Models/Analyses > > Operational Models platform_vocabulary=GCMD Platform Keywords program=Pacific Islands Ocean Observing System (PacIOOS) project=Pacific Islands Ocean Observing System (PacIOOS) references=https://www.nco.ncep.noaa.gov/pmb/products/gfs/ source=NOAA/NCEP Global Forecast System (GFS) numerical weather prediction model sourceUrl=https://pae-paha.pacioos.hawaii.edu/thredds/dodsC/ncep_pac/NCEP_Pacific_Atmospheric_Model_best.ncd Southernmost_Northing=-40.0 standard_name_vocabulary=CF Standard Name Table v39 testOutOfDate=now+136hours time_coverage_end=2025-07-21T12:00:00Z time_coverage_resolution=PT3H time_coverage_start=2022-12-01T12:00:00Z Westernmost_Easting=-180.0

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.

1. The 37 vertical levels model is removed due to the storage restriction and limited accuracy.
   
2. The 13 levels graphcast ML model was fine-tuned with NCEP’s GDAS data as inputs and ECMWF ERA5 data as ground truth from 20210323 to 20220901, validated from 20220901 to 20230101. Evaluation is done with forecasts from 20230101-20240101. The new weights created from the training are used to create global forecasts. It is important to note that the GraphCastGFS v1 model weights obtained from Google’s DeepMInd were provided based on 12 timesteps training with ERA5 data, while the GraphCastGFS v2 model weights resulted from training with 14 timesteps with GDAS and ERA5 data that significantly increased the accuracy of the forecasts compared with GraphCastGFS V1.
   
   The input data generated from the GDAS data as GraphCast input is provided under input/ directory. An example of file names is shown below
   
   source-gdas_date-2024022000_res-0.25_levels-13_steps-2.nc
   
   The files are under forecasts_13_levels/. There are 40 files under each directory covering a 10 day forecast. An example of file name is listed below
   
   graphcastgfs.t00z.pgrb2.0p25.f006
   
   

1. Starting from 06 cycle on 20240710, the forecast length is increased from 10 days to 16 days.
   
   Please note that this NOAA GraphCastGFS Model was produced using a code package released by Google DeepMind. For information on Google DeepMind, please visit their github page listed in the documentation and license sections of this page.

The Global Ensemble Forecast System (GEFS) has been operational at NCEP since December 1992, with the initial version using the NCEP Global Spectral Model (GSM) at T62L18 resolution (about 200km in horizontal and 18 vertical sigma levels) and the initial condition perturbations (2 pairs perturbed and 1 control members) were generated by breeding vector (BV) method (Toth and Kalnay 1993; Toth and Kalnay 1997; Toth et al. 1997; Toth et al. 2001; Zhu et al. 2002; Buizza et al. 2005; Zhu 2005). The GEFS ran once per day, out to 12 days in the early 90s. During the early 2000s, the 1st generation of GEFS reforecast (1979 - 2006) was produced off-line from using NCEP GFS/GEFS 1998 model version by NOAA PSL (Hamill et al. 2006) to demonstrate the improved ensemble reliability through bias correction and calibration. Over the years, the GEFS has been upgraded. In early 2010, the GEFS was upgraded with enhanced representation of model uncertainty using the Stochastic Total Tendency Perturbation (STTP) algorithm (Hou et al., 2008). The stochastic tendency perturbations were updated every 6 hours. Meanwhile, the 2nd generation of NOAA GEFS reforecasts were produced off-line for 29 years (1985 - 2013) by NOAA PSL (Hamill et al. 2013; NOAA/PSL reforecast website) using GEFS v10 configurations and CFS reanalysis. Through another major upgrade in December 2015, the GEFS initial perturbations were chosen from the operational hybrid Global Data Assimilation System (GDAS) 80-member Ensemble Kalman Filter (EnKF; Whitaker et al., 2008) 6-h forecasts along with tropical storm relocation and centralization of the initial perturbations (Zhou et al. 2016; 2017).More information on GEFS can be found at [a link ]. GEFS data can be found in the GEFS bucket: gs://gfs-ensemble-forecast-system Pub/Sub topics you can subscribe to for updates: projects/gcp-public-data-weather/topics/gfs-ensemble-forecast-system

This data set contains NOAA/NCEP GFS forecast model imagery over the Western Pacific Ocean. Products include 200mb heights/winds, 200mb height anomaly, 500mb heights and PMSL, tropopause 2PVU height, 200/500/850925mb streamlines, 200-300mb and 700-850mb PV, 850-200mb shear, 850 and 200mb divergence, 200/500/850/925mb RH, and 850mb vorticity. Products are available every 6 hours to 36 hours and every 12 hours from 36-144 hours. These images were developed by NRL and are in gif format.

The Global Forecast System (GFS) forecast precipitation data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near real-time usage by the national and international relief agencies and the general public. The users of this data include the U.S. Geological Survey (USGS), the U.S. Agency for International Development (USAID), the Joint Agricultural Weather Facility (JAWF) and the national Meteorological Centers in Africa, Asia and South America. The data is disseminated in the binary format as well as in the form of shape and tiff files for use by the GIS community. This data has seven individual 24-hour accumulated precipitation amounts (in millimeters) corresponding to the seven forecast days and one for the grand total of accumulated 7day total precipitation (in millimeters). Thus, the represented forecast fields have 8 Geotiff files and 8 shape files. All these files are zipped into a single file (per day).

The Global Forecast System (GFS) forecast 0-10cm soil-moisture data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near real-time usage by the national and international relief agencies and the general public. The users of this data include the U.S. Geological Survey (USGS), the U.S. Agency for International Development (USAID), the Joint Agricultural Weather Facility (JAWF) and the national Meteorological Centers in Africa, Asia and South America. The data is disseminated in the binary format as well as in the form of shape and tiff files for use by the GIS community. The soil moisture data in the GIS format can be accessed at the online linkage provided above.

This dataset contains Mid level clouds NCEP GFS forecast imagery taken during the HIPPO project. The data is in PNG format. The data covers the time span from 2009-01-09 12:00:00 to 2009-01-09 12:00:00.

7 day accumulated precipitation anomaly from the Global Forecast SystemLink to graphical web page: https://www.cpc.ncep.noaa.gov/products/Global_Monsoons/American_Monsoons/gfs_model.shtmlLink to data download (geo-tiffs): https://ftp.cpc.ncep.noaa.gov/GIS/GRADS_GIS/GeoTIFF/PREC_FORECASTLink to metadataQuestions/Concerns about the service, please contact the DISS GIS teamTime Information:This service is not time enabled

The NCEP Climate Forecast System Reanalysis (CFSR) was initially completed for the 31-year period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high resolution, coupled atmosphere-ocean-land surface-sea ice system to provide the best estimate of the state of these coupled domains over this 31-year period. The CFSR has also been extended as an operational, real time product into the future. New features of the CFSR include: (1) coupling of atmosphere and ocean during the generation of the 6 hour guess field; (2) an interactive sea-ice model; and (3) assimilation of satellite radiances by the Grid-point Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is approximately 38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25 deg at the equator, extending to a global 0.5 deg beyond the tropics, with 40 levels to a depth of 4737m. The global land surface model has four4 soil levels and the global sea ice model has 3 layers. The CFSR atmospheric model has observed variations in carbon dioxide (CO2) over the 1979-2009 period, together with changes in aerosols and other trace gases and solar variations. Most available in-situ and satellite observation data were included in the CFSR. Satellite-based radiance observations were bias corrected with spin-up runs at full resolution, taking into account variable CO2 concentrations. This procedure enabled smooth transitions of the observation record due to evolutionary changes in satellite observing systems. The CFSR atmospheric, oceanic and land surface output products are available at an hourly time resolution and at a 0.5 deg x 0.5 deg latitude and longitude resolution. In total, there are 10 data products available from the National Climatic Data Center that make up the CFS Reanalysis collection: MON - Monthly Means; TIME - Parameter Timeseries; PGB - 3-D Pressure Level Data; FLX - Surface and Radiative Fluxes; OCN - 3-D Ocean Data; IPV - 3-D Isentropic Level Data; DIAB - 3-D Diabatic Heating Data; GRBLOW - Low-Resolution Data; HIC - High-Res Initial Conditions; LIC - Low-Res Initial Conditions. All data are in GRIB-2 format, except for the initial condition data which are in native binary formats. Total CFSR data volume is approximately 200 TB.

This dataset contains Imagery Products generated by the NCEP GFS Small Domain Forecast Model for the area and time of interest for the VOCALS project. The image files are in GIF format.

This dataset contains Imagery Products generated by the NCEP GFS Cross Section Forecast Model for the area and time of interest for the VOCALS project. The image files are in GIF format.

This dataset contains GFS forecast product model imagery collected during the MILAGRO field project.

This dataset contains gif images from the National Weather Service - National Centers for Environmental Prediction (NCEP) Atlantic area forecasts during the Ice in Clouds Experiment - Tropical (ICE-T) project.

The Global Forecast System (GFS) is a weather forecast model produced by the National Centers for Environmental Prediction (NCEP). The GFS dataset consists of selected model outputs (described below) as gridded forecast variables. The 384-hour forecasts, with 3-hour forecast interval, are made at 6-hour temporal resolution (i.e. updated four times daily). Use the 'creation_time' and 'forecast_time' properties to select data of interest. The GFS is a coupled model, composed of an atmosphere model, an ocean model, a land/soil model, and a sea ice model which work together to provide an accurate picture of weather conditions. See history of recent modifications to the global forecast/analysis system , the model performance statistical web page , and the documentation homepage for more information.Más información

This dataset contains 350mb winds NCEP GFS forecast imagery taken during the HIPPO project. The data is in PNG format. The data covers the time span from 2008-12-31 12:00:00 to 2009-01-09 12:00:00.

This dataset includes NCEP Global Forecast System (GFS) Forecast Products from the PREDICT field catalog. The files are gif images and were taken during the Pre-Depression Investigation of Cloud-systems in the Tropics (PREDICT) project. The PREDICT project took place during the summer and fall of 2010 in the Atlantic basin.

Map Information

This nowCOAST time-enabled map service provides maps depicting the latest global forecast guidance of water currents, water temperature, and salinity at forecast projections: 0, 12, 24, 36, 48, 60, 72, 84, and 96-hours from the NWS/NCEP Global Real-Time Ocean Forecast System (GRTOFS). The surface water currents velocity maps displays the direction using white or black streaklets. The magnitude of the current is indicated by the length and width of the streaklet. The maps of the GRTOFS surface forecast guidance are updated on the nowCOAST map service once per day. For more detailed information about the update schedule, see: http://new.nowcoast.noaa.gov/help/#section=updateschedule

Background Information

GRTOFS is based on the Hybrid Coordinates Ocean Model (HYCOM), an eddy resolving, hybrid coordinate numerical ocean prediction model. GRTOFS has global coverge and a horizontal resolution of 1/12 degree and 32 hybrid vertical layers. It has one forecast cycle per day (i.e. 0000 UTC) which generates forecast guidance out to 144 hours (6 days). However, nowCOAST only provides guidance out to 96 hours (4 days). The forecast cycle uses 3-hourly momentum and radiation fluxes along with precipitation predictions from the NCEP Global Forecast System (GFS). Each forecast cycle is preceded with a 48-hr long nowcast cycle.
The nowcast cycle uses daily initial 3-D fields from the NAVOCEANO operational HYCOM-based forecast system which assimilates situ profiles of temperature and salinity from a variety of sources and remotely sensed SST, SSH and sea-ice concentrations. GRTOFS was developed by NCEP/EMC/Marine Modeling and Analysis Programs. GRTOFS is run once per day (0000 UTC forecast cycle) on the NOAA Weather and Climate Operational Supercomputer System (WCOSS) operated by NWS/NCEP Central Operations.

The maps are generated using a visualization technique was developed by the Data Visualization Research Lab at The University of New Hampshire Center for Coastal and Ocean Mapping (http://www.ccom.unh.edu/vislab/). The method combines two techniques. First, equally spaced streamlines are computed in the flow field using Jobard and Lefer's (1977) algorithm. Second, a series of "streaklets" are rendered head to tail along each streamline to show the direction of flow. Each of these varies along its length in size, color and transparency using a method developed by Fowler and Ware (1989), and later refined by Mr. Pete Mitchell and Dr. Colin Ware (Mitchell, 2007).

Time Information

This map is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.

This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.

In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.

Due to software limitations, the time extent of the service and map layers displayed below does not provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time information about the service:

Issue a returnUpdates=true request for an individual layer or for
the service itself, which will return the current start and end times of
available data, in epoch time format (milliseconds since 00:00 January 1,
1970). To see an example, click on the "Return Updates" link at the bottom of
this page under "Supported Operations". Refer to the
ArcGIS REST API Map Service Documentation
for more information.


  Issue an Identify (ArcGIS REST) or GetFeatureInfo (WMS) request against
  the proper layer corresponding with the target dataset. For raster
  data, this would be the "Image Footprints with Time Attributes" layer
  in the same group as the target "Image" layer being displayed. For
  vector (point, line, or polygon) data, the target layer can be queried
  directly. In either case, the attributes returned for the matching
  raster(s) or vector feature(s) will include the following:


      validtime: Valid timestamp.


      starttime: Display start time.


      endtime: Display end time.


      reftime: Reference time (sometimes reffered to as
      issuance time, cycle time, or initialization time).


      projmins: Number of minutes from reference time to valid
      time.


      desigreftime: Designated reference time; used as a
      common reference time for all items when individual reference
      times do not match.


      desigprojmins: Number of minutes from designated
      reference time to valid time.




  Query the nowCOAST LayerInfo web service, which has been created to
  provide additional information about each data layer in a service,
  including a list of all available "time stops" (i.e. "valid times"),
  individual timestamps, or the valid time of a layer's latest available
  data (i.e. "Product Time"). For more information about the LayerInfo
  web service, including examples of various types of requests, refer to
  the nowCOAST help documentation at:
  http://new.nowcoast.noaa.gov/help/#section=layerinfo

References

Fowler, D. and C. Ware, 1989: Strokes for Representing Vector Field Maps. Proceedings: Graphics Interface '98 249-253. Jobard, B and W. Lefer,1977: Creating evenly spaced streamlines of arbitrary density. Proceedings: Eurographics workshop on Visualization in Scientific Computing. 43-55. Mitchell, P.W., 2007: The Perceptual optimization of 2D Flow Visualizations Using Human in the Loop Local Hill Climbing. University of New Hampshire Masters Thesis. Department of Computer Science. NWS, 2013: About Global RTOFS, NCEP/EMC/MMAB, College Park, MD (Available at http://polar.ncep.noaa.gov/global/about/). Chassignet, E.P., H.E. Hurlburt, E.J. Metzger, O.M. Smedstad, J. Cummings, G.R. Halliwell, R. Bleck, R. Baraille, A.J. Wallcraft, C. Lozano, H.L. Tolman, A. Srinivasan, S. Hankin, P. Cornillon, R. Weisberg, A. Barth, R. He, F. Werner, and J. Wilkin, 2009: U.S. GODAE: Global Ocean Prediction with the HYbrid Coordinate Ocean Model (HYCOM). Oceanography, 22(2), 64-75. Mehra, A, I. Rivin, H. Tolman, T. Spindler, and B. Balasubramaniyan, 2011: A Real-Time Operational Global Ocean Forecast System, Poster, GODAE OceanView –GSOP-CLIVAR Workshop in Observing System Evaluation and Intercomparisons, Santa Cruz, CA.

The NBSv2.0 dataset synthesizes observations from multiple satellites (up to 16 satellites since 1987) to create globally gridded, high-resolution 10 m neutral ocean wind speeds and wind stress components. The wind directions come from two sources depending on the products: for the research delayed mode product, the source is the European Centre for Medium-Range Weather Forecasts ERA5 and for the near-real-time products, the source is the National Centers for Environmental Prediction (NCEP) GFS. This is an updated version of the existing NOAA NBS v1.0, which is a global gridded 0.25 degree and 6-hourly/daily/monthly sea surface winds product that has wide applications in marine transportation, marine ecosystem and fisheries, offshore winds, weather and ocean forecasts, and other areas. A Climatological mean or WMO 30-year Normals are also generated for this product. This newly developed version 2 shows improvement (over its predecessor version 1.0) in following aspects: Resolving very high winds associated with Cyclones/Hurricanes, A gap-free global spatial coverage, Better improved algorithm and coded with open source Python reducing the computational clock time by 10x, and A near-real time production. The data are available in netCDF format for the period of record, July 1987 to present, with six-hourly, daily, and monthly time resolutions for both the blended Sea Surface Wind (SSW) as well as SSW stress data.