An Evaluation of the Effectiveness of Known Large-scale Modes for Predicting Extreme Mei-yu Precipitation over China using Causality Driven Approach

Record-breaking amount of Mei-yu rainfall around the Yangtze River has been observed in the 2020 Mei-yu season. This shows the necessity and urgency of accurate prediction of extreme Mei-yu precipitation over China for the current and future climate. Such information could further improve the decision and policy making in the region. 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. One might be possible to construct a causally guided statistical model based on those known large-scale modes to predict extreme Mei-yu precipitation.

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. The relationships between large-scale modes and extreme Mei-yu precipitation on different time scale are explored. Implication of relationships in constructing statistical predictive model is also discussed.