An evaluation of the effectiveness of known large-scale modes for predicting extreme Mei-yu precipitation over China using causality driven approach

Abstract

<p>Record-breaking amount of Mei-yu rainfall around the Yangtze River has been observed in the 2020 Mei-yu season.&#160; This shows the necessity and urgency of accurate prediction of extreme Mei-yu precipitation over China for the current and future climate.&#160; Such information could further improve the decision and policy making in the region.&#160; Many studies in the past have shown that large-scale modes, e.g. western north Pacific subtropical high and the south Asia high, play a role in controlling extreme Mei-yu precipitation over China. Although the spatial resolution of typical climate models might be too coarse to simulate extreme precipitation accurately, they are likely to simulate large-scale modes reasonably well.&#160; One might be possible to construct a causally guided statistical model based on those known large-scale modes to predict extreme Mei-yu precipitation.&#160;</p><p>In this presentation, we show preliminary results of the relationship between known large-scale atmospheric and oceanic modes and extreme Mei-yu precipitation in the two regions of China, i.e. Yangtze River Valley and Southern China, using the causal network discovery approach.&#160; The relationships between large-scale modes and extreme Mei-yu precipitation on different time scale are explored.&#160; Implication of relationships in constructing statistical predictive model is also discussed.</p>