WRF Ensemble Management can help you create WRF ensembles from GEFS reanalysis data via submodule lazyWRF. It can also post-process the data (such as computing ensemble means, creating postage-stamp plots of all members, etc) via submodule postWRF.
As a sidenote, I encourage all users of Python to cite packages and acknowledge fellow users in publications and presentations. There is often little incentive for researchers to open source their efforts, yet it is a process that needs to be encouraged.
Documentation is here (incomplete): http://johnrobertlawson.github.io/WEM/
./lazyWRF/ contains scripts that form the basis of automating your WRF
ensemble runs. ./postWRF/bin/ contains examples of post-processing that
you may like to perform with the module. The other essential file you will need
to personalise for post-processing is /bin/settings.py. The class therein contains
all the settings for loading data, saving output, etc. Almost all settings can be
left as default (by not specifying a setting), other than essentials like
the path to your WRF data, the path to output figures, etc.
To run lazyWRF, the top-level script must be in your WPS folder to allow WPS
executables to see the namelist.wps. So you might need to soft-link from your WPS
directory to where you keep your top-level lazyWRF/WEM controlling scripts (e.g.,
ln -sf /path/to/WEM/scripts/ in your WPS folder). At least,
I can't find a way around this.
Some files or methods contain attributions to other programmers whose code has been refactored to fit this project (or is/will become a prerequisite). In summary, thanks to:
- Patrick Marsh
- John Hart
URL: http://www.atmos.washington.edu/~lmadaus/pyscripts.html
- David-John Gagne
- Tim Supinie
- Luke Madaus
URL: http://code.google.com/p/pywrf/
URL: https://github.com/scaine1/pyWRF/
URL: https://code.google.com/p/pywrfplot/
- Geir Arne Waagbø