Using Python to pre- and post-process GEFS/WRF ensembles

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Tuesday, 4 February 2014: 8:30 AM
Room C302 (The Georgia World Congress Center )
John Lawson, University of Utah, Salt Lake City, UT; and J. D. Horel

The Weather Research and Forecast model (WRF) and its output are often pre- and post-processed with a multitude of different programming languages, methods, scripts, and programs. Python, however, has the capability to replace or enhance existing code infrastructure. Python is flexible enough to prepare WRF in its pre-processing stages as an intelligent shell-scripting replacement. This presentation focuses on its use in downloading and organising Global Ensemble Forecast System (GEFS) model-data files ready for use to drive WRF ensembles. Python is also powerful enough to manipulate model output and generate journal-ready and presentation-quality figures. An enhancement of the open-source PyWRF package is presented, along with examples of Python's use in plotting ensemble output.