Spatial patterns of torrential rain in the Haihe River Basin and the corresponding large‐scale circulation

Abstract

AbstractThe classification of torrential rain is crucial to the flood mitigation and water resources, but the relevant research in the Haihe River Basin (HRB) is lacking. In this study, 156 regional torrential rain events from 1972 to 2022 were classified into two types using cluster analysis: eastern type and southern type. The eastern type is the typical torrential rain in the HRB, accounting for 61.5% of the total days, whereas the southern type mainly occurs in the piedmont plain with larger intensity and scope, which would pose more severe hazards. Corresponding large‐scale circulation patterns of the two types reveal a clear relationship between the HRB torrential rain and ascending motion, associated with the anomalies of low‐level moisture convergence and upper‐level wind divergence. The anomalous upper‐level divergence is accompanied by the northward expansion of South Asian High and intensified westerly jets. In the eastern type, strong low‐pressure anomalies north of Lake Baikal at mid‐level produce anomalous northwesterlies. The cold air from mid–high latitudes encounters enhanced southwesterly moist air accompanied by the northward expansion of Western Pacific Subtropical High (WPSH), resulting in the low‐level moisture convergence. In the southern type, the low‐level anomalous convergence is caused by a relatively weak cyclonic anomaly and significantly strengthened southeasterly moisture from the Pacific. The enhancement of southwesterlies results from the cooperative effect of the remarkably northwesterly WPSH and low‐pressure anomalies in South China Sea. As a whole, the eastern type is the result of convergence of cold air and southwesterly moisture driven by a dipole pattern at mid–high latitudes, whereas the southern type is mainly attributed to the accumulation of abundant southeasterly water vapour. This classification can identify high‐risk areas for torrential rain in the HRB and contribute to the forecast skills of extreme precipitation.