Abstract
Abstract The time of rainy season onset is crucial information for policymakers, especially in densely populated regions such as the Yangtze River basin (YRB) in China. In this study, we proposed a new grid-based index to objectively detect mei-yu onset timing using reanalysis data and model predictions, and then we identified the key processes via which intraseasonal oscillation (ISO) affects the YRB mei-yu onset and its subseasonal predictability based on scale-decomposed moisture analysis. Climatologically, propagation of an ISO anticyclonic anomaly toward East China supports the moisture convergence required for rainy season onset over the YRB via interaction with the seasonal-mean moisture component. In the years of early mei-yu onset, the ISO was enhanced earlier in May and favored the moisture convergence anomaly in late May–early June, when the mei-yu started. In contrast, the enhanced ISO and associated moistening processes were observed later in June–early July in the years with delayed onset. The European Centre for Medium-Range Weather Forecasts and National Centers for Environmental Prediction models show skillful prediction of mei-yu onset at forecast lead times of 5–6 pentads, whereas the China Meteorological Administration model has limited skill of 3 pentads. The differences in model prediction skill are related to the accuracy of predicted moisture convergence anomalies induced by the ISO. The prediction bias in mei-yu onset timing (early or delayed) is also connected to bias in the occurrence timing of enhanced intraseasonal perturbations, suggesting the vital role of ISO in YRB mei-yu onset on the subseasonal time scale.
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