Potential Seasonal Predictability of the Risk of Local Rainfall Extremes Estimated Using High‐Resolution Large Ensemble Simulations

Abstract Significant progress has been made in seasonal climate predictions based on general circulation models (GCMs). However, seasonal prediction of local heavy rain remains challenging due to limited resolution. A small signal‐to‐noise ratio also prevents meaningful predictions. In this study, 100‐member large‐ensemble sets of GCM simulations and high‐resolution downscaled products with a regional climate model were used to identify the unknown source of seasonal predictability for the risk of local heavy rainfall around Japan and Taiwan. The detected predictable signals depended on the location and the season. Highly predictable signals were found for events caused by typhoons and the stationary front. Further analyses of the large‐scale backgrounds simulated by the parent‐GCM revealed that each source of predictability comes from various flavors of El Niño/Southern Oscillation and anomalies in the Indian Ocean. The approach of this study potentially provides an opportunity to identify unknown predictable regional signals all over the world.