Examples of Python-based Ensemble Displays for Decision Support

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Monday, 5 January 2015
Richard Grumm, NOAA/NWSFO, State College, PA; and S. J. Greybush

Examples on the use of Python to make effective displays of ensemble forecast data is presented. These displays were developed in an effort to teach undergraduate students (in the classroom and NWS volunteers) how to program in Python, how to make effective use of ensemble forecast data, and learn about predictability horizons.

The examples show how standard probability of exceedance, ensemble mean / spread, spaghetti, and plume diagrams can aide in forecasting winter storms, heavy rain, and when to use sunscreen on vacation. These data also help students visualize the evolution of uncertainty in forecasts, how the area to be affected by a weather system can change as forecast length decreases, and the concept of predictability horizons.

This poster will show the various examples and how programing in Python can aid in forecasting, teaching students the value of ensemble forecasts systems in the forecast process and how a probabilistic framework can aid in making better decisions.