The Utility of ProbSevere v2.0 for Predicting Pulse Severe Thunderstorms

Abstract

Abstract Pulse severe storms are single-cell thunderstorms that produce severe wind and/or severe hail for a brief period of time. These storms pose a major warm season forecasting problem since forecasters presently do not have sufficient guidance to know which, if any, of the cells that are observed will become severe. The empirical Probability of Severe (ProbSevere) model, developed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS), fuses real-time data to produce short-term (0–60 min), statistically derived probabilistic forecasts of thunderstorm intensity. This study evaluates the ability of ProbSevere to predict pulse severe storms in the southeast United States. ProbSevere objects fitting the usual definition of a pulse severe environment were matched with severe events from Storm Data to create a dataset of ProbSevere objects that corresponded to pulse severe thunderstorms. A null dataset consisted of objects in pulse severe environments that did not match with a severe event. Results reveal that ProbSevere’s probabilities are small to moderate at the times corresponding to pulse severe events. While probabilities of nonsevere storms are generally smaller, there are a large number of outliers. Lightning flash rate is the only predictor relevant to this study that correlates strongly with increasingly favorable pulse storm probabilities. We conclude that ProbSevere provides forecasters only limited guidance as to whether a pulse severe event will soon occur. Developing a version of ProbSevere specifically for pulse severe storms would likely lead to better predictability for this mode of convection.