Changes in precipitation extremes and associated risks under the 1.5 and 2.0℃ global warming targets in the Yangtze River basin(YRB)were assessed.The projections from 10 global climate models(GCMs)of the Coupled Mode...Changes in precipitation extremes and associated risks under the 1.5 and 2.0℃ global warming targets in the Yangtze River basin(YRB)were assessed.The projections from 10 global climate models(GCMs)of the Coupled Model Intercomparison Project phase 6(CMIP6)were bias-corrected and averaged with Bayesian and arithmetic mean methods,respectively.The results show that the Bayesian weights can reflect the performance of each GCM in capturing seasonal precipitation extremes.Thus,its multimodel ensemble projections noticeably improve the performance of the mean,interannual variability,and trends of precipitation extremes.The areal-mean risks of Rx5day(maximum consecutive 5-day precipitation)are projected to increase by ratios of 3.3 in summer,2.9 in autumn,2.2 in spring,and 1.9 in winter under the 1.5℃ target.Spatially,the northwestern part of the YRB may experience the highest risk of increments in Rx5day extreme in summer and autumn.In response to an additional 0.5℃ warming from 1.5 to 2.0℃,the risks of seasonal Rx5day extreme for all 20-,50-,and 100-yr return periods are projected to increase respectively.The higher probabilities of extreme precipitation events under the warming targets may cause more hazardous flooding;therefore,new strategies and infrastructures for climate change and hydrological risk mitigation are imperative in the YRB.展开更多
基金Supported by the National Key Research and Development Program of China(2022YFF0801804 and 2017YFA0603702).
文摘Changes in precipitation extremes and associated risks under the 1.5 and 2.0℃ global warming targets in the Yangtze River basin(YRB)were assessed.The projections from 10 global climate models(GCMs)of the Coupled Model Intercomparison Project phase 6(CMIP6)were bias-corrected and averaged with Bayesian and arithmetic mean methods,respectively.The results show that the Bayesian weights can reflect the performance of each GCM in capturing seasonal precipitation extremes.Thus,its multimodel ensemble projections noticeably improve the performance of the mean,interannual variability,and trends of precipitation extremes.The areal-mean risks of Rx5day(maximum consecutive 5-day precipitation)are projected to increase by ratios of 3.3 in summer,2.9 in autumn,2.2 in spring,and 1.9 in winter under the 1.5℃ target.Spatially,the northwestern part of the YRB may experience the highest risk of increments in Rx5day extreme in summer and autumn.In response to an additional 0.5℃ warming from 1.5 to 2.0℃,the risks of seasonal Rx5day extreme for all 20-,50-,and 100-yr return periods are projected to increase respectively.The higher probabilities of extreme precipitation events under the warming targets may cause more hazardous flooding;therefore,new strategies and infrastructures for climate change and hydrological risk mitigation are imperative in the YRB.
