Spatial and Temporal Variations of the Precipitation Structure in Jiangsu Province from 1960 to 2020 and Its Potential Climate-Driving Factors

Abstract

This study investigated the temporal and spatial variations of precipitation duration and intensity in Jiangsu Province from 1960 to 2020 using the IDW spatial interpolation method and Kendall’s tau trend test, based on daily precipitation data collected from 22 meteorological stations. Additionally, a Pearson correlation analysis was conducted to examine the correlations between the occurrence rate and contribution rate of precipitation with different durations and grades, as well as five large-scale climate indices. The results indicated the following trends: (1) An increase in the precipitation duration corresponded to a decrease in the occurrence rates, while the contribution rates initially increased and then decreased. The province was predominantly characterized by 1–3 days of light rainfall, with a higher probability of short-duration heavy rainfall in northern Jiangsu. (2) From 1960 to 2020, most stations experienced decreasing trends in the precipitation duration occurrence and contribution rates, but heavy rainfall increased, suggesting a shift to short-duration heavy precipitation. (3) The Arctic Oscillation (AO) notably negatively correlates with the 9-day occurrence rate of precipitation (9dOR), while it positively correlates significantly with the occurrence rate of moderate rainfall (MROR). The North Atlantic Oscillation (NAO) exhibits a significant positive correlation with the 2-day occurrence rate of precipitation (2dOR) and a notable negative correlation with the 9-day occurrence rate of precipitation (9dOR). The PDO (Pacific Decadal Oscillation) has shown significant positive correlations with the 2-day precipitation occurrence rate (2dOR) and contribution rate (2dCR), a negative correlation with the light rainfall occurrence rate (LROR), and significant positive correlations with both the moderate and heavy rainfall occurrence rates (MROR and HROR, respectively). The AO, NAO, and PDO are potential climate factors that influence changes in the precipitation structure in Jiangsu Province. These research findings offer valuable insights for regional water resource management, flood risk assessment, and predicting future precipitation trends under climate change scenarios.