An Introduction to WRF-Python

The Weather Research and Forecasting (WRF) model is not well supported in Python based meteorological tools due to its lack of CF compliance, the complexity of dealing with its Arakawa C staggered grid and terrain-following hydrostatic pressure coordinates, and lack of commonly used meteorological variables contained in the WRF output NetCDF files.  For this reason, meteorologists working with WRF data commonly use the National Center for Atmospheric Research (NCAR) Command Language (NCL) for post-processing, analysis, and plotting.  Python programmers wishing to work with WRF data often use NCL to compute diagnostic variables from the WRF output, then pass the computed variables back to Python using intermediate NetCDF files.  In this presentation, we introduce the NCAR wrf-python package, which eliminates the need to work across multiple software platforms.  The wrf-python package contains all of the computational routines found in NCL-WRF.  These computational routines include variable extraction and calculation routines for over thirty diagnostics, along with routines for horizontal interpolation and vertical cross-section interpolation.  The wrf-python package is compatible with the various NetCDF readers (PyNIO, netcdf4-python) and mapping packages (PyNGL, basemap, cartopy) currently used in the Python community.  Metadata is an optional feature in wrf-python and is handled by the xarray package.