From GEMPAK to Python: Evolution of the Storm Prediction Center's Graphics In the Social Media Era

The NOAA/NWS Storm Prediction Center (SPC) is tasked with producing forecasts of severe thunderstorms and their associated hazards (tornadoes, large hail, and damaging thunderstorm winds). Historically, this guidance was consumed primarily by local National Weather Service forecast offices. However, with the advent of the Internet, social media, and the always-connected society, SPC forecasts and graphics are being consumed increasingly by the public-at-large. This new audience, with less technical knowledge, resulted in discussions about how to present SPC forecasts in the best graphical format.

The result was a transition toward more public friendly, social-media-ready graphics generated in Python. Many challenges were faced in the creation of these numerous, high quality, localized graphics in an operational setting, including conversion of open line segments into closed polygons, rapid transformation of geographic polygons between different geographic projections, and minimizing creation time of similar graphics. This presentation will discuss these issues as well as discuss SPC's solutions to these challenges, which include the creation of a custom mapping engine.