Impact of Eurasian Spring Snowmelt on July Extreme Precipitation over Southeast China

Southeast China, a densely populated and economically developed region, has experienced an increase in extreme precipitation in recent years. However, the current understanding of the influencing factors and related mechanisms of extreme precipitation remains incomplete. This study investigates the possible impact of spring Eurasian snowmelt on July extreme precipitation in Southeast China, using observational and reanalysis datasets. Singular Value Decomposition (SVD) analysis was used to explore the relationship between spring snowmelt and July extreme precipitation. The dominant SVD mode reveals that significantly increased snowmelt over the high latitudes of Eurasia and decreased snowmelt over the western and eastern sides of the mid-latitudes of Eurasia tend to be accompanied by a meridional dipole pattern of extreme precipitation anomalies over Southeast China, with a positive center over the Yangtze River Basin (YRB) and a negative center over South China (SC), and vice versa. Further analysis indicates that the soil moisture anomaly induced by the spring snowmelt anomaly can persist until July, modulating the land surface energy budget and atmospheric circulation conditions. When a snowmelt anomaly occurs, a distinct wave train type anomalous circulation develops over Eurasia, propagating southeastward from mid–high latitudes to South China, resulting in an anomalous cyclonic circulation around the Sea of Japan and North China, and an intensified western North Pacific subtropical high (WNPSH). The anomalous sinking motion related to the strengthened WNPSH inhibits water vapor convergence and results in reduced extreme precipitation over SC. In contrast, the anomalous southwesterly winds on the western flank of the WNPSH transport warm and moist air northward and converge with the anomalous northerly flow over the YRB, contributing to intense moisture convergence, which increases precipitation potential and the likelihood of extreme rainfall. Our findings provide valuable insights for improving the understanding and prediction of July extreme precipitation in Southeast China.