Abstract

The development of the Weather Research and Forecasting (WRF) modeling system is a multiagency effort to provide a next-generation mesoscale forecast model system that aims at advancing both the understanding and prediction of mesoscale weather and accelerating the transfer of research advances i... Show moreThe development of the Weather Research and Forecasting (WRF) modeling system is a multiagency effort to provide a next-generation mesoscale forecast model system that aims at advancing both the understanding and prediction of mesoscale weather and accelerating the transfer of research advances into operations. The model is being developed as a collaborative effort among the National Centers for Environmental Prediction (NOAA/NCEP), the NOAA Earth Systems Research Laboratory Global Systems Division (NOAA/ESRL/GSD), the National Center for Atmospheric Research (NCAR) Mesoscale Microscale Meteorology Division (MMM), the Department of Defense's Air Force Weather Agency (AFWA), and the Federal Aviation Administration (FAA), along with the participation of a number of university scientists and international collaborators. The WRF model is designed to be a flexible, state-of-the-art, portable code that is efficient in a massively parallel computing environment. A modular single-source code is maintained that can be configured for both research and operations. The WRF system offers two separate dynamical cores, the Non-hydrostatic Mesoscale Model (NMM) and the Advanced Research WRF (ARW), numerous physics options, pre and post processors, advanced data assimilation systems including WRF VAR (WRF Variational Data Assimilation system), Newtonian relaxation FDDA, and the Grid-point Statistical Interpolator (GSI), as well as a verification toolkit known as the Model Evaluation Toolkit (MET). It is suitable for use in a broad spectrum of applications across scales ranging from meters to thousands of kilometers. Such applications include research and operational numerical weather prediction (NWP), data assimilation and parameterized physics research, downscaling climate simulations, driving air quality models, atmospheric-ocean coupling, and idealized simulations (e.g. boundary layer eddies, convection, baroclinic waves). With WRF as a common tool in the university and operational centers, closer ties are promoted between these communities, and research advances will have a direct path to operations. These hallmarks make the WRF modeling system unique in the history of NWP in the United States. The principle components of the WRF system are depicted in Fig. 1.1. The WRF Software Framework (WSF) provides the infrastructure that accommodates multiple dynamics solvers, physics packages that plug into the solvers through standard physics interfaces, programs for initialization, and data assimilation systems. As noted above, there are currently two dynamic solvers available in the WRF system; the NMM and the ARW. The ARW was developed primarily at NCAR and the NMM was developed at NCEP. This manual describes the NMM dynamic solver or "core". Separate documents describe the ARW core, the various physics options, and the data assimilation systems. It is a goal of the WRF program that any component of the WRF system will work interchangeably with all other components. Thus, each WRF component should be able to work with different dynamical cores, physics options, data assimilation systems, verification tools and pre and post processors. At this writing not all physics components are yet interchangeable, and not all of the options are fully operational, but we expect most to be in the near future. The Developmental Testbed Center (DTC) supported the preparation of this Technical Note. Dr. Robert Gall was the National Director of the DTC and the Director of the Joint Numerical Testbed in NCAR's Research Applications Laboratory at the time preparations for this document were undertaken. Dr. Gall's current affiliation is the Development Manager, Hurricane Forecast Improvement Program, NOAA/OST, Silver Spring, MD. Zavisa Janjic and Matthew E. Pyle are affiliated with the Environmental Modeling Center, National Centers for Environmental Prediction, Camp Springs, MD. Show less