A synoptic clustering-based definition of South China Sea summer monsoon onset and application to seasonal prediction

Abstract. Accurately predicting the South China Sea summer monsoon (SCSSM) onset date is of crucial importance for effective water resource management, agricultural planning, and disaster prevention across East Asia and the Western North Pacific. However, reliable predictions at seasonal timescales remain challenging. To address this, we propose a synoptic circulation–based approach that defines monsoon onset through persistent large-scale circulation regimes identified by clustering low-level atmospheric fields. Using ECMWF SEAS5 seasonal forecasts, we evaluate onset predictions derived from the proposed regime-based definition against those based on a conventional zonal wind criterion. The regime-based definition yields systematic improvements in deterministic correlations, potential predictability, and categorical and probabilistic skill metrics. Skill gains are evident during both a dependent training period and an independent forecast period, with enhanced performance persisting at long lead times of up to five months. The improved predictability reflects the multi-timescale controls on monsoon onset, wherein slowly varying boundary forcing modulates large-scale circulation and subseasonal variability triggers the onset transition. By emphasizing regime persistence and structural evolution, the proposed framework better isolates the predictable component of onset variability and enhances forecast robustness. These findings demonstrate that circulation-regime–based definitions offer a physically grounded and effective alternative for seasonal prediction of monsoon onset.