The skill of convective parameters and indices to predict isolated and severe thunderstorms

Abstract

The preconvective environment on days with ordinary, widespread, and severe thunderstorms in Southwest Germany was investigated. Various thermodynamic and kinetic parameters calculated from radiosoundings at 12:00 UTC were verified against subsequent thunderstorm observations derived from SYNOP station data, radar data, and damage reports of a building insurance company. The skill of the convective parameters and indices to predict thunderstorms was evaluated by means of probability distribution functions, probabilities of thunderstorms according to an index threshold, and skill scores like the Heidke Skill Score (HSS) that are based on categorical verification. For the ordinary decision as to whether a thunderstorm day was expected or not, the best results were obtained with the original Lifted Index (80% prediction probability for LI≤−1.73; HSS=0.57 for LI≤1.76), the Showalter Index, and the modified K-Index. Considering days with isolated compared to widespread thunderstorms, the best performance is reached by the Deep Convective Index. For days with severe thunderstorms that caused damage due to hail, local storms or floods, the best prediction skill is found again for the Lifted Index and the Deep Convective Index, but also for the Potential Instability Index, the Delta-θe Index, and a version of the CAPE, where the lifting profile is determined by averaging over the lowest 100 hPa.