Ensemble Model Visualization and Decision Support Tools with Python

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Monday, 5 January 2015
Steven J. Greybush, Penn State Univ., University Park, PA; and R. H. Grumm

Python is an effective means for visualizing output from ensemble prediction systems, both for operational meteorologists and students in the classroom. Upper level undergraduate students in Computer Applications to Meteorology at Penn State learn Python and its visualization capabilities including the Matplotlib Basemap toolkit for displaying in-house Weather Research and Forecasting (WRF) and operational ensemble model output.

Several types of plots encourage probabilistic rather than deterministic thinking: probability of exceedance, ensemble mean / spread, spaghetti, and plume diagrams. Visualizations are demonstrated in the context of understanding the predictability of winter storms for the Northeastern US. A collaboration between Penn State and National Weather Service State College has made real-time plots available for forecasting applications via a web portal. Finally, the students develop decision support tools enabling a user to make an actionable decision based on a probabilistic forecast in a variety of applications, including assessing weather hazards and planning outdoor activities.