WRF (Weather Research and Forecasting) model is an open source meteorological model developed at NCAR (https://github.com/wrf-model/WRF; Skamarock, 2008). The model is flexible with respect to projection and resolution, and the model setup at NILU can provide meteorological data ranging from ~1 × 1 km2 to 1° × 1° globally. The model output can be generated on an even finer spatial scale when high resolution topography is available. The model is also flexible regarding vertical resolution and temporal output. Temporal resolutions of 1h, 3h or 6h are most frequently used.
The WRF and WRF Preprocessing System (WPS) can easily be run with input from NCEP GFS (Global Forecast System) or FNL (Final) Operational Global Analysis data, which are available on grids down to 0.25° x 0.25° resolution. The FNL data are computed with the same model as GFS, but FNL is prepared later than GFS to allow more observational data to be used. Parameters include surface pressure, sea level pressure, geopotential height, temperature, sea surface temperature, soil parameters, ice cover, relative humidity, horizontal winds, vertical motion, vorticity and ozone (see https://rda.ucar.edu/datasets/ds083.3/). The WRF model can also be forced with data from ECMWF, but NCEP data are currently used as the standard at NILU.
The WRF model serves a wide range of applications and are used in combinations with other models at NILU that require a meteorological driver. Examples are WRF-EMEP, WRF-EPISODE, WRF-Flexpart, and WRF-NORTRIP.
Autowrf is a python package under development aimed to run WRF in an automatized way, without in-depth knowledge about the WRF model itself. By providing the domain size (coordinates) and year/period, autowrf will automatically generate the desired meteorological data. Alternatively, the WRF model can be run on the NILU cluster njord (/xnilu_wrk/projects/WRF-EMEP/WRF).
Contact WRF: Tove Svendby (email@example.com), Sverre Solberg (firstname.lastname@example.org)
Contact autowrf: Islen Vallejo (email@example.com)
Skamarock, W. C., and Klemp, J. B. (2008) A time-split nonhydrostatic atmospheric model for weather research and forecasting applications, J. Comput. Phys., 227 (7), 3465-3485, 10.1016/j.jcp.2007.01.037