Region-dependent meteorological conditions of thunderstorm based on clustering analysis of stability and precipitable water indices

Thunderstorms contribute to a large number of destructive weather events. However, due to the availability of comprehensive thunderstorm datasets, current researches on thresholds of stability indices during thunderstorms have always been limited within a specific local area during a relatively short time span. This study uses observations of thunderstorms data and ERA5 reanalysis data in summer (June-August) at 0600 and 1200 UTC from 1995 to 2019 to investigate the region-dependent thresholds of four indices for indicating the occurrence of thunderstorm. The indices include the K index (K), the Showalter index (SI), convective available potential energy (CAPE), and precipitable water (PW). By applying the K-means clustering method on the composite mean fields of four indices on thunderstorm days, China is objectively divided into three regions based on three stability indices (K, SI, and CAPE) and two regions based on PW index. Region-dependent thresholds have been established for each index related to thunderstorms. When these thresholds are applied, accuracy rate of detecting thunderstorms exceeds 60% at 85% of the stations over China. The remarkable regional difference in the thresholds of the four indices are further attributed to the climatic backgrounds. Summer climatological means of surface potential temperature and surface relative humidity play a pivotal role in shaping the distinctive thresholds of K, CAPE, and PW across diverse regions, while surface potential temperature and topography are pivotal for the region-dependent thresholds of SI. Based on the terrain characteristics and relevant summer climatology in each region, the thunderstorm thresholds can be potentially applied to regions with limited thunderstorm records but exhibiting similar climatic features beyond China. These findings would provide a reliable reference for thunderstorm monitoring by meteorological departments and related decision-making services. By applying K-means clustering on four indices (K index, Showalter index, convective available potential energy, and precipitable water) during thunderstorm events in June-August from 1994 to 2019, China is divided into two or three regions (a). Using the thunderstorm thresholds of each index in the corresponding region (b), the probability of detecting the thunderstorm occurrence exceeds 60% at 85% of China stations. image