Dataset Search

This dataset is a collection of various NCEP GFS data used by NCAR's researchers. It consists of periods of GFS spectral coefficients (in binary format) and flux terms (in GRIB format), as well as their transformed, gridded NetCDF files of various spatial resolutions, T382, T254, T170 and T62. All data files are stored on HPSS. There is no attempt to recover, reconstruct missing data. All products are provided as is.

These NCEP FNL (Final) Operational Global Analysis data are on 1-degree by 1-degree grids prepared operationally every six hours. This product is from the Global Data Assimilation System (GDAS), which continuously collects observational data from the Global Telecommunications System (GTS), and other sources, for many analyses. The FNLs are made with the same model which NCEP uses in the Global Forecast System (GFS), but the FNLs are prepared about an hour or so after the GFS is initialized. The FNLs are delayed so that more observational data can be used. The GFS is run earlier in support of time critical forecast needs, and uses the FNL from the previous 6 hour cycle as part of its initialization.

The analyses are available on the surface, at 26 mandatory (and other pressure) levels from 1000 millibars to 10 millibars, in the surface boundary layer and at some sigma layers, the tropopause and a few others. Parameters include surface pressure, sea level pressure, geopotential height, temperature, sea surface temperature, soil values, ice cover, relative humidity, u- and v- winds, vertical motion, vorticity and ozone.

The archive time series is continuously extended to a near-current date. It is not maintained in real-time.

These NCEP FNL (Final) operational global analysis and forecast data are on 0.25-degree by 0.25-degree grids prepared operationally every six hours. This product is from the Global Data Assimilation System (GDAS), which continuously collects observational data from the Global Telecommunications System (GTS), and other sources, for many analyses. The FNLs are made with the same model which NCEP uses in the Global Forecast System (GFS), but the FNLs are prepared about an hour or so after the GFS is initialized. The FNLs are delayed so that more observational data can be used. The GFS is run earlier in support of time critical forecast needs, and uses the FNL from the previous 6 hour cycle as part of its initialization.

The analyses are available on the surface, at 26 mandatory (and other pressure) levels from 1000 millibars to 10 millibars, in the surface boundary layer and at some sigma layers, the tropopause and a few others. Parameters include surface pressure, sea level pressure, geopotential height, temperature, sea surface temperature, soil values, ice cover, relative humidity, u- and v- winds, vertical motion, vorticity and ozone.

The archive time series is continuously extended to a near-current date. It is not maintained in real-time.

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.

NOTE: This dataset now has a direct, continuously updating copy located on AWS (https://noaa-gfs-bdp-pds.s3.amazonaws.com/index.html). Therefore, the RDA will stop updating this dataset in early 2025

The NCEP operational Global Forecast System auxiliary 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.

NCEP ADP Global Upper Air and Surface Weather Observations (PREPBUFR format) are composed of a global set of surface and upper air reports operationally collected by the National Centers for Environmental Prediction (NCEP). These include land surface, marine surface, radiosonde, pibal and aircraft reports from the Global Telecommunications System (GTS), profiler and US radar derived winds, SSM/I oceanic winds and TCW retrievals, and satellite wind data from the National Environmental Satellite Data and Information Service (NESDIS). The reports can include pressure, geopotential height, temperature, dew point temperature, wind direction and speed. Report time intervals range from hourly to 12 hourly.

These data are the output from the PREPBUFR processing performed at NCEP, which is the final step in preparing the majority of conventional observational data for assimilation into the various NCEP analyses including the North American Model (NAM) and NAM Data Assimilation System (NDAS) unified grid-point statistical interpolation (GSI) analysis (the "NAM" and "NDAS" networks), the Global Forecast System (GFS) and Global Data Assimilation System (GDAS) unified grid-point statistical interpolation (GSI) analysis (the "GFS" and "GDAS" networks), the Rapid Refresh (RAP) unified grid-point statistical interpolation (GSI) analysis (the "RAP" network), the Real Time Mesoscale Analysis (RTMA) unified grid-point statistical interpolation (GSI) analysis (the "RTMA" network), and the Climate Data Assimilation System (CDAS) spectral statistical interpolation (SSI) analysis (the "CDAS" network).

This step involves the execution of series of programs designed to assemble observations dumped from a number of on-line decoder databases, encode information about the observational error for each data type as well the background (first guess) interpolated to each data location, perform both rudimentary multi-platform quality control and more complex platform-specific quality control, and store the output in a monolithic BUFR file, known as PREPBUFR. The background guess information is used by certain quality control programs while the observation error is used by the analysis to weigh the observations. The structure of the BUFR file is such that each PREPBUFR processing step which changes a datum (either the observation itself, or its quality marker) records the change as an "event" with a program code and a reason code. Each time an event is stored, the previous events for the datum are "pushed down" in the stack. In this way, the PREPBUFR file contains a complete history of changes to the data throughout all of the PREPBUFR processing. The most recent changes are always at the top of the stack and are thus read first by any subsequent data decoder routine. It is expected that the data at the top of the stack are of the highest quality.

The data provided here are also available in NetCDF and ASCII formats, which can be accessed by following the "Get a subset" link on the ds337.0 data access page. The NetCDF datafiles are converted from PREPBUFR format using the pb2nc utility in the Model Evaluation Tools (MET) software package.

Realtime micro-scale weather simulations were performed to support UAV (Uncrewed Aerial Vehicle) flights during the ISARRA Lower Atmospheric Process Studies at Elevation a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field deployment. These simulations were performed by driving a nested grid configuration of the Weather Research and Forecasting model with its innermost mesh being run at 111 m grid spacing. The innermost grid was nested within a grid with 1 km grid spacing. The outermost grid being driven using operational forecast models data as described below. While the MYNN2 PBL scheme is used to parameterize turbulence in the 1 km grid, the PBL scheme is turned off within the 111 m grid, thus, allowing large-scale turbulent eddies to be resolved by WRF primitive equations. Details of the model configuration and data formats are given in Pinto et al. (2021).

LAPSE-RATE took place in the San Luis Valley of Colorado during July of 2018. Goals of LAPSE-RATE were to sample the finescale evolution of the boundary layer and associated sub-mesoscale flows across a sub-alpine desert valley using a combination of surface-based instrumentation and in situ data collected using numerous, low-flying small UAVs. The realtime simulations were produced twice per day in order to support mission planning and UAVs flight operations. The simulation used for next-day planning was run using forcing data from NCEP's Global Forecast System (GFS) while the simulation available each morning of the experiment to support in flight operations was run using data from the NCEP High Resolution Rapid Refresh (HRRR), Version 3. Both simulations were valid between 04:00 and 16:00 MDT. The dataset consists of two sets of files: 3D grids and high temporal resolution time series and profiles for a select group of grid points. The 3D grids consist of all relevant basic state parameters (P, T, U, RH) and diagnostics (e.g., sub-grid scale TKE, ceiling height, visibility) that have been interpolated to flight levels AGL using the Unified Post-Processor (UPP). The UPP was used to de-stagger the mass and wind fields, interpolate forecast data to flight levels AGL and to compute diagnostics such as visibility, ceiling height, and radar reflectivity. Point data were stored for select grid points coincident with 3 fixed observation sites set up during LAPSE-RATE (i.e., Saguache, Moffat and Leach Airfield). The 3D grid files are stored every 10 minutes, while grid point data have a time resolution of 0.666 and 6 seconds for the 111 m grid spacing domain and 1 km grid spacing domain, respectively.

Please see the README files for more details describing the dataset.

The Final (FNL) global tropospheric analyses archived here were produced by NCEP's Global Forecast System (GFS), which was run operationally at 12-hour intervals to make multiple-day weather forecasts, from July 1976 through mid-April 1997. FNLs are analyses that are produced after the model has completed the forecast cycle, and they include the most complete set of observations available for a given cycle. The FNL from a given cycle, which is the best available analysis, is then used in the initialization of the next cycle.

FNL Data are available on pairs of 2.5-degree hemispheric grids (North and South) at the Earth's surface, twelve vertical levels from 1000 millibars up to 50 millibars, the tropopause, boundary and some sigma layers, and a few other levels. Parameters include surface pressure, sea level pressure, geopotential height, temperature, sea surface temperature, potential temperature, relative humidity, snow depth (weekly, Northern Hemisphere only) precipitable water, u- and v- winds, and vertical motion.

The Final (FNL) global tropospheric analyses archived here were produced by NCEP's Global Forecast System (GFS), which was run operationally at 12-hour intervals to make multiple-day weather forecasts, from April 1997 through June 2007. FNLs are analyses that are produced after the model has completed the forecast cycle, and they include the most complete set of observations available for a given cycle. The FNL from a given cycle, which is the best available analysis, is then used in the initialization of the next cycle.

FNL Data are available on pairs of 2.5-degree hemispheric grids (North and South) at the Earth's surface, sixteen vertical levels from 1000 millibars up to 10 millibars, the tropopause, boundary layer, two subsurface levels, and a few others. Parameters include surface pressure, sea level pressure, geopotential height, temperature, sea surface temperature, potential temperature, relative humidity, snow depth (weekly, Northern Hemisphere only) precipitable water, u- and v- winds, and vertical motion.

These NCEP FNL (Final) Operational Global Analysis data are on pairs of 2.5 by 2.5 degree hemispheric grids every twelve hours. This product was from the Global Forecast System (GFS) that was run operationally in near-real time at NCEP. DSS prepared this surface subset from ds082.0.

The analyses are available on the surface, at 1000mb and a boundary layer. Parameters include surface pressure, sea level pressure, geopotential height, temperature, sea surface temperature, soil temperature, water content of soil, ice cover, water equivalent of snow depth, relative humidity, specific humidity, u- and v-wind components, minimum temperature, maximum temperature and land-sea mask.

More information is available