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| WRF Model | |
|---|---|
| Name | WRF Model |
| Developer | National Center for Atmospheric Research; National Oceanic and Atmospheric Administration |
| Released | 2000s |
| Latest release | ongoing |
| Programming language | Fortran, C, MPI |
| Operating system | Linux, Unix, macOS |
| Genre | Numerical weather prediction, mesoscale modeling |
| License | Varied academic/research licenses |
WRF Model
The WRF Model is a flexible, mesoscale numerical weather prediction system designed for research and operational forecasting. It supports regional and convection-permitting simulations across multiple scales and integrates with observational networks, data assimilation frameworks, and high-performance computing centers. Its development involves collaborations among major institutions and serves communities in atmospheric science, emergency management, and renewable energy.
The WRF Model provides an advanced platform for simulating atmospheric processes from synoptic to storm-scale, combining dynamical cores, physics packages, and data assimilation utilities. Users include researchers at National Center for Atmospheric Research, forecasters at National Weather Service, engineers at NASA, and academics at institutions such as Massachusetts Institute of Technology, University of Oklahoma, University Corporation for Atmospheric Research, Princeton University, and University of Washington. Operational deployments run on supercomputers at Oak Ridge National Laboratory, Argonne National Laboratory, and regional computing centers supporting programs like Department of Energy campaigns and European Centre for Medium-Range Weather Forecasts collaborations.
Development began through partnerships among National Center for Atmospheric Research, National Oceanic and Atmospheric Administration, Air Force Weather Agency, and university groups including Colorado State University and Pennsylvania State University. Early milestones parallel advances in numerical weather prediction exemplified by models such as Global Forecast System, European Centre for Medium-Range Weather Forecasts, and innovations tied to projects like Global Energy and Water Exchanges. Funding and programmatic support came from agencies including National Science Foundation and Department of Defense, while scientific contributions referenced foundational work by researchers associated with American Meteorological Society symposia and conferences at AGU Fall Meeting.
The system couples dynamical cores—such as the Advanced Research WRF dynamical core—with physics suites, pre- and post-processing tools, and coupled components for land, ocean, and chemistry. Key components interface with external systems like Weather Research and Forecasting Data Assimilation modules, the NOAA Hydrometeorological Prediction Center workflows, and community tools used by European Centre for Medium-Range Weather Forecasts and UK Met Office researchers. Software engineering leverages libraries and standards from MPI, netCDF, and high-performance Fortran coding practices developed at centers like Los Alamos National Laboratory.
The model implements multiple boundary layer schemes, microphysics, cumulus parameterizations, and radiation models developed through research at Texas A&M University, Iowa State University, University of California, Los Angeles, and national labs. Parameterizations draw on seminal approaches from scientists affiliated with American Geophysical Union and are applied in studies spanning Hurricane Sandy, Hurricane Katrina, and severe convective outbreaks evaluated by teams from NOAA Storm Prediction Center and National Severe Storms Laboratory. Schemes often reference observational programs such as Tropical Rainfall Measuring Mission and field campaigns like VORTEX and PRE-STORM.
Data assimilation integrations utilize methods like 3DVAR, 4DVAR, and ensemble Kalman filters developed in collaboration with groups at National Oceanic and Atmospheric Administration, European Centre for Medium-Range Weather Forecasts, Naval Research Laboratory, and universities including University of Maryland and Penn State. The system ingests observations from networks such as Global Telecommunications System, Doppler radar arrays, GOES satellites, Aerosonde platforms, and in situ radiosonde launches coordinated by World Meteorological Organization. Initialization strategies support reanalysis products and coupling with ocean models used in projects by NOAA Geophysical Fluid Dynamics Laboratory.
Users apply the model for operational forecasting at agencies like National Weather Service and Air Force Weather Agency, research into mesoscale convective systems at National Severe Storms Laboratory, renewable energy forecasting for companies working with Department of Energy programs, air quality modeling tied to Environmental Protection Agency studies, and climate downscaling in collaborations with Intergovernmental Panel on Climate Change researchers. Case studies include simulations of Super Typhoon Haiyan, Mount Pinatubo aerosol impacts, urban heat island analyses in cities like New York City and Los Angeles, and wind resource assessments for offshore projects near Gulf of Mexico.
Verification frameworks are informed by best practices advocated by World Meteorological Organization and testing protocols used by European Centre for Medium-Range Weather Forecasts and National Aeronautics and Space Administration. Validation relies on observational datasets from Surface Weather Observing Systems, Aircraft Meteorological Data Relay, and research campaigns such as COASTAL and Hurricane Field Program. Performance tuning and scalability studies are reported from deployments on supercomputers at Oak Ridge National Laboratory, National Energy Research Scientific Computing Center, and cloud platforms used by commercial partners.
The WRF Model is supported by a broad community including National Center for Atmospheric Research, National Oceanic and Atmospheric Administration, university consortia, and international partners like UK Met Office contributors. Distribution channels include community repositories and institutional mirrors with licensing terms that permit academic and governmental use, often accompanied by user support via workshops at venues such as American Meteorological Society conferences and training at NCAR and NOAA centers. Collaborative development practices mirror those in projects supported by National Science Foundation grants and interagency memoranda.