Abstract
Hailstorms are one of the most dangerous atmospheric phenomena for people and can cause significant damage to agriculture, buildings and cars. Therefore, the investigation of the entire hailstorms’ life cycle is crucial to understand in which conditions these phenomena are generated. Many studies demonstrated that an increase in lightning activity is generally associated with severe atmospheric conditions (large hail, tornadoes, flash floods, strong wind gusts etc.). Starting from the total number of lightning strikes, which is the most common variable related to lightning activity, in this work we describe some additional features emerging between very large hail occurrence and flashes in the Italian territory, by analyzing the lightning jump indicator. To meet the goals of this study, a small dataset including hail reports and lightning data from LAMPINET network for 10 hailstorms occurred in the Italian Peninsula between 2015 and 2022 has been analyzed. The main results show that the total lightning intensification and reduction may occur in different stages that characterize the evolution of the hailstorms, showing different types of behaviour from the initial stage to the dissipative one. In the first evolutionary steps, an abrupt increase in the number of strokes (i.e. the lightning jump) is usually observed, leading to a lightning rate that, in some hailstorms, may grow with a linear or exponential trend. The new mathematical approach proposed allows us to analyze the hailstorms using different temporal series (at 20, 30 and 40-minute intervals) leading to a comparison between hail reports and lightning jump values every 10 min. As a general result, the strongest lightning jump value doesn’t show a clear relationship with the maximum hail diameter detected. In 5/10 case studies analyzed, the highest lightning jump value anticipates the occurrence of hail on the ground by 10 to 60 min, while it is coincident with the first hail reports (using a tolerance of ± 10 min) in 2/10 hail events. In the remaining 3 case studies, it is observed at least 10 min after the first hailstones have reached the ground. Such preliminary results encourage to experiment a proper combination of total lightning and lightning jump to improve retrieval algorithms currently working to identify and track the hailstorms.