Projections of Autumn Precipitation Extremes in Southwest China Based on a Statistically Downscaled CMIP6 Dataset

This study evaluates the performance of 15 Coupled Model Intercomparison Project Phase 6 (CMIP6) models (before and after downscaling) in simulating autumn precipitation extremes in Southwest China based on a high-resolution, statistically downscaled CMIP6 dataset, using the CN05.1 dataset as a reference. The Bias Correction Constructed Analogues with Quantile mapping reordering (BCCAQ) method used in deriving the downscaled CMIP6 dataset significantly enhances the models’ abilities to reproduce the spatial patterns of the extreme precipitation indices, particularly for total precipitation, number of moderate rain days (R10), and number of heavy rain days (R20). Notable improvements are also observed for maximum 1-day precipitation (RX1), maximum 5-day precipitation (RX5), and simple daily intensity index (SDII), alongside reduced inter-model spread and systematic biases. Bias correction also improves the simulation of interannual variability, substantially reducing the root mean square error (RMSE) for total precipitation, R10, and R20. Increased interannual variability in the future is expected for certain indices, spatially concentrated for RX1 and RX5 in the south and R20 in the east. Projections using the bias-corrected multi-model ensemble under the SSP2-4.5 and SSP5-8.5 scenarios indicate a significant intensification of autumn extreme precipitation in both intensity- and frequency-related indices by the 2080s, especially in southern Southwest China, with precipitation becoming more concentrated in heavier events. Consecutive dry days (CDDs) exhibit spatial variability with an observed increase in the southeast, while consecutive wet days (CWDs) shows no significant change. These findings highlight an increased risk of intensified autumn rainfall and altered precipitation patterns in the region under future climate change.