Diverse Synoptic Weather Patterns of Warm-Season Heavy Rainfall Events in South Korea

This study identifies diverse synoptic weather patterns of warm-season heavy rainfall events (HREs) in South Korea. The HREs not directly connected to tropical cyclones (TCs) (81.1%) are typically associated with a mid-latitude cyclone from eastern China, the expanded North Pacific high, and strong southwesterly moisture transport in between. They are frequent both in the first (early summer) and second rainy periods (late summer) with impacts on the south coast and west of the mountainous region. In contrast, the HREs resulting from TCs (18.9%) are caused by the synergetic interaction between the TC and meandering midlatitude flow, especially in the second rainy period. The strong south-southeasterly moisture transport makes the southern and eastern coastal regions prone to the TC-driven HREs. By applying a self-organizing map algorithm to the non-TC HREs, their surface weather patterns are further classified into six clusters. Clusters 1 and 3 exhibit a frontal boundary between the low and high with differing relative strengths. Clusters 2 and 5 feature an extratropical cyclone migrating from eastern China under different background sea level pressure patterns. Cluster 4 is characterized by the expanded North Pacific high with no organized negative sea level pressure anomaly, and cluster 6 displays a development of a moisture pathway between the continental and oceanic highs. Each cluster exhibits a distinct spatiotemporal occurrence distribution. The result provides useful guidance for HRE prediction by depicting important factors to be differently considered depending on their synoptic categorization.

Automated summary

This study identifies diverse synoptic weather patterns of warm-season heavy rainfall events in South Korea, with two main causes: those not directly connected to tropical cyclones and those resulting from tropical cyclones. These different weather patterns exhibit distinct spatiotemporal distributions, providing important guidance for HRE prediction.