Detection and attribution of extreme precipitation events over the Asian monsoon region

Abstract

Extreme precipitation events have enormous impacts on the natural and human aspects of most regions. This study presents a detection and attribution analysis of extreme precipitation in the Asian monsoon region (AM) from 1950 to 2014 using the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The observed positive PI (probability-based index) trends for annual maxima of 5-day (Rx5day) and 1-day (Rx1day) precipitation accumulations are 6.04%/100yr and 10.96%/100yr. The simulated PI trends for Rx5day and Rx1day under greenhouse-gas (GHG) forcing are 9.70%/100yr and 10.86%/100yr, respectively, while the trends are −8.99%/100yr and −7.01%/100yr under the aerosol (AER) forcing. Greenhouse-gas concentrations alone cause extreme precipitation increases, while the offsetting effects of anthropogenic aerosols may result in weaker increasing trends in ALL forcing simulations. The anthropogenic (ANT) signals are detectable, while the natural (NAT) signals could not be distinguished from the noise (internal climate variability) based on the optimal fingerprinting method. GHG forcing is detected for AM's extreme precipitation when GHG, AER, and NAT forcing are all considered. A three-signal analysis confirms that CO2 forcing had a detectable influence on observations, whereas the influence of volcanic and solar-irradiance forcings could not be distinguished. Our results provide evidence that anthropogenic greenhouse gases (mainly CO2) are the prime external factor influencing the increase of AM's extreme precipitation.