The relationship between the land features and thermodynamic parameters and the thunderstorm hours over central and eastern China

Abstract The thunderstorm hour (TH) is a valuable indicator for assessing the impact of climate change on thunderstorm frequency. Using the cloud-to-ground (CG) lightning stroke data detected by the lightning location network (LLN) from 2013 to 2021, the annual spatial distribution of stroke density (SD) and THs in China is analyzed. The monthly and diurnal variations of THs on different landforms were examined over central and eastern China as the region of interest. Considering differences in geomorphic types, we also explored the relationship between THs and land features and monthly average convective parameters. In space, the overall pattern of THs is similar to that of SD; however, there are differences in local regions. In time, the maximum value of THs occurs in July for annual variation and around 16:00 Beijing time for daily variation. The average thunderstorm hours in mountainous areas are higher than in flat areas. In addition, thunderstorm hour index (THI) on mountainous landforms is usually greater than 1, meaning these landform types have a "preference" for thunderstorm occurrence. Due to the higher coverage area of flat terrain compared to other terrains, THs tend to accumulate in low-elevation areas. In mountainous areas, the sloping terrain is a factor in the increase in thunderstorm hours in all seasons. The THs generally increase with increasing spring, summer, and autumn vegetation cover. However, in summer, there is an opposite trend when the vegetation index exceeds 0.8. Instability, humidity, and composite parameters can be used as proxies to predict the monthly thunderstorm number. Furthermore, the correlation relationship between thunderstorm hours and land features and thermodynamic parameters varies with geomorphic types. Our research provides a theoretical foundation for constructing a long-term historical dataset of thunderstorm hours in the future.