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| WRF (Weather Research and Forecasting Model) | |
|---|---|
| Name | WRF (Weather Research and Forecasting Model) |
| Developer | National Center for Atmospheric Research; National Oceanic and Atmospheric Administration; University Corporation for Atmospheric Research |
| Released | 2000s |
| Programming language | Fortran; C |
| Operating system | UNIX; Linux; macOS |
| Genre | Numerical weather prediction; atmospheric modeling |
WRF (Weather Research and Forecasting Model) The WRF (Weather Research and Forecasting Model) is a mesoscale numerical weather prediction system used for research and operational forecasting. Developed through a collaboration among National Center for Atmospheric Research, National Oceanic and Atmospheric Administration, and University Corporation for Atmospheric Research, WRF supports a wide range of scales and applications from convection-resolving simulations to climate downscaling.
WRF provides a modular, portable framework for simulating atmospheric phenomena across nested domains and variable-resolution grids, enabling coupling with models and systems such as European Centre for Medium-Range Weather Forecasts, NASA, Jet Propulsion Laboratory, NOAA National Weather Service, and Los Alamos National Laboratory. It implements multiple dynamical cores and physics suites used by institutions like Massachusetts Institute of Technology, Princeton University, University of Washington, Colorado State University, and University of Oklahoma. WRF supports interfaces to data sources including Global Forecast System, ERA5, Modern-Era Retrospective analysis for Research and Applications, and observational networks maintained by National Aeronautics and Space Administration programs and field campaigns such as VORTEX, Hurricane Field Program, and GPM.
The WRF project emerged from collaborative efforts during workshops held by organizations including National Science Foundation, National Oceanic and Atmospheric Administration, and academic partners such as Pennsylvania State University and Oregon State University. Early development drew on heritage from models like MM5, GFS, and research at centers including European Centre for Medium-Range Weather Forecasts and Meteorological Office (United Kingdom). Funding and governance have involved agencies such as Department of Energy, U.S. Air Force, and international partners like Environment and Climate Change Canada and Met Office. Over successive releases, contributions from research groups at University of California, Berkeley, University of Colorado Boulder, Texas A&M University, and University of Maryland expanded capabilities for physics, coupling, and data assimilation used in initiatives such as Coupled Model Intercomparison Project workflows.
WRF is built around interchangeable components: dynamical cores (e.g., ARW), physics packages, and utilities for preprocessing and postprocessing developed by teams at National Center for Atmospheric Research, NOAA Earth System Research Laboratory, and university collaborators. Core modules include the Advanced Research WRF dynamical core, nesting and grid-stretching utilities, and the WRF Preprocessing System used with datasets from NCEP and ECMWF. WRF couples to community tools like WRF-Chem for chemistry, WRF-Hydro for hydrology, and external systems such as Community Earth System Model, Model for Prediction Across Scales, and assimilation systems used at European Centre for Medium-Range Weather Forecasts and NASA Goddard Space Flight Center. Software engineering practices adopted by the WRF community draw from projects at Lawrence Berkeley National Laboratory and Argonne National Laboratory to support parallelization on platforms from Cray to clusters at Oak Ridge National Laboratory.
WRF implements suites of parameterizations for microphysics, planetary boundary layer, cumulus convection, radiation, and land-surface processes, developed by groups at University of Illinois Urbana-Champaign, University of Arizona, University of Colorado, Scripps Institution of Oceanography, and Rutgers University. Options include schemes traced to work at Lin, Kessler, and formulations used in operational centers like National Weather Service and international centers such as Japan Meteorological Agency and Deutscher Wetterdienst. Land-surface models integrated into WRF reflect developments from Noah Land Surface Model teams, while aerosol and chemical modules connect to research from Pacific Northwest National Laboratory and National Center for Atmospheric Research laboratories involved in Aerosol Robotic Network studies.
WRF interoperates with data assimilation systems including WRFDA, 3DVAR, 4DVAR, and ensemble-based methods developed in collaborations involving University of Maryland, McGill University, University of Miami, and National Oceanic and Atmospheric Administration laboratories. Initialization workflows use observations from networks such as Global Precipitation Measurement, Doppler radar arrays operated by Federal Aviation Administration and National Weather Service, radiosonde launches coordinated by World Meteorological Organization, and satellite retrievals from NOAA satellites, GOES, Aqua (satellite), and missions by European Space Agency. Coupling to ocean analyses from National Centers for Environmental Prediction and sea-ice products developed by National Snow and Ice Data Center supports coastal and marine initialization.
WRF is used in operational forecasting at agencies like National Weather Service, climate downscaling projects coordinated by Intergovernmental Panel on Climate Change participants, and research studies at institutions such as Columbia University, Harvard University, Yale University, and University of California, Los Angeles. Applications include severe-weather simulations for Tropical Cyclone studies, air-quality modeling in concert with Environmental Protection Agency initiatives, wind-farm planning informed by projects with National Renewable Energy Laboratory, and urban meteorology applied in collaborations with municipalities and research centers affiliated with MIT Senseable City Lab and Lawrence Livermore National Laboratory.
Performance tuning and validation efforts involve benchmarking on supercomputers at Oak Ridge National Laboratory, National Energy Research Scientific Computing Center, and national facilities supported by Department of Energy. Validation campaigns compare WRF output against observations from projects like Hydrometeorological Testbed, STEP, and instrument arrays operated by Scripps Institution of Oceanography. Limitations include sensitivity to parameterization choices and boundary conditions noted by researchers at University of Reading, University of Exeter, and University of Leeds, and challenges in coupling for fully coupled Earth-system experiments pursued by groups at NCAR and NOAA.
Category:Numerical weather prediction models