资源环境科技发展态势分析平台

Prediction of Meiyu withdrawal date (MWD) over the Yangtze-Huaihe River basin (YHRB) around mid-July has aroused extensive concern recently because of the profound socioeconomic and academic importance. However, relatively few researches have been carried out to identify the potential predictability source that can physically contribute to the Meiyu retreat over the YHRB, which exhibits profound year-to-year variations. This study identifies that the later-than-normal Meiyu withdrawal is preceded by the significant tropical June Arabian Sea (AS) surface sea surface (SST) warming on the interannual timescale. Analyses of possible mechanisms suggest that a striking quasi-barotropic “north-low–south-high” meridional seesaw pattern (i.e. PJ-like pattern) over the Northeast Asian–western North Pacific sector in July favors the transport and convergence of warm-moist water vapor and cold-dry air mass over the YHRB, inducing abundant in situ precipitation and thereby maintaining the Meiyu rainband. Under such a background, the Meiyu termination over the YHRB is delayed. Moreover, dynamical diagnoses and numerical model simulations indicate that the warmer-than-normal AS, which persists from June to the following July, can induce a notable localized low-level cyclonic anomaly via a Rossby-wave-like Matsuno–Gill-type atmospheric response. This cyclonic anomaly can further stimulate a large-scale atmosphere bridge stretching across South Asia and propagating poleward into Northeast Asia, which modulates the aforementioned downstream MWD-related atmospheric conditions continuously. Therefore, AS SST warming can remotely regulate and maintain the July Meiyu rainband through inducing a major direct forcing for the later Meiyu withdrawal over the YHRB, namely the East Asian coastal “north-low-south-high” meridional teleconnection. These results indicate and demonstrate the possible source of predictability for Meiyu withdrawal. This work may help improve forecasting of the withdrawal timing of Meiyu over the YHRB through more accurate predictions of SST over the AS region.