Detectable Human Influence on Changes in Precipitation Extremes Across China

This study explored the human influence on the observed changes in precipitation extremes across China for the period of 1961-2014 by the latest simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Changes in observations and CMIP6 simulations under different external forcings for annual total wet-day precipitation (PRCPTOT), the number of heavy precipitation days (R10 mm), very wet days (R95p), extremely wet days (R99p), the maximum 1-day precipitation amount (RX1day), and the maximum 5-day precipitation amount (RX5day) are compared using a regularized optimal fingerprinting method. The results show that both anthropogenic (ANT) and greenhouse gas (GHG) experiments generally exhibit increasing trends in precipitation extremes over China, agreeing with the overall observed increases. The ANT influence is robustly detected for R95p, R99p, RX1day, and RX5day over China, with clear separation from the natural forcing. Additionally, the GHG signal is also detectable for R95p, R99p, and RX1day but separated from the natural and other ANT forcings for only R99p and RX1day and from the natural and ANT aerosol forcings for only RX5day. Thus, the intensified precipitation extremes can be attributed to human influence dominated by the GHG effect. However, detections fail for PRCPTOT and R10 mm. The ANT aerosol forcing may partly offset the role of the GHG responses to observed increases despite being undetectable. Based on the detection and attribution results, the observation-constrained projections indicate that precipitation extremes are projected to significantly increase under the SSP2-4.5 and SSP5-8.5 scenarios but with a smaller magnitude compared to the raw CMIP6 outputs.

Automated summary

This study used CMIP6 simulations to explore the human influence on precipitation extremes in China. The results showed that both anthropogenic and greenhouse gas experiments exhibited increasing trends in precipitation extremes, and the intensified extremes could be attributed to human influence dominated by the greenhouse gas effect.