Attribution And Future Projections Of Summer Extreme Precipitation Events In The Middle And Lower Reaches Of The Yangtze Rive

With the recurrence of extreme precipitation events and the growing demands by the public to know the causes after the events,extreme event attribution has emerged as a frontier of climate change research.It explores the impact of anthropogenic influence on the probability or intensity of one certain extreme event.Many authors have attempted to investigate human influence on extreme precipitation in China but their findings are not always consistent.Moreover,an event attribution study focuses on one individual extreme event that has just occurred.Studies rarely examine human influence on multiple extreme events in different times of the past.Therefore,exploring the impact of different external forcings on extreme precipitation events under global warming can help to deeply understand the causes and projections of extreme precipitation events.This study analyzes the long-term change of mean precipitation（Pmean）,maximum 1-day precipitation（Rx1day）and maximum 5-day precipitation（Rx5day）over the MLYRV in rainy season（June to July）based on homogenized daily precipitation observations of 2419 stations from the China Meteorological Administration.The roles of internal variability and external forcings such as greenhouse gases（GHGs）and aerosols（AAs）on historical extreme precipitation events,especially the four heaviest events（1931,1954,1998 and 2020）in past100 years are further investigated.Moreover,given that models are difficult to capture extreme precipitation events,a comprehensive attribution analysis for all possible regions of similar size to the MLYRV in a larger domain in eastern China is proposed according to the performance of CMIP6 models.The temporal change of external forcings since 1850 on the pre-defined events is explored based on this method.Finally,the research establishes the relationship between the intensity（frequency）change of extreme precipitation events described by different return periods with global mean surface temperature（GMST）change and focuses on the changes under some keyΔGMST thresholds.The main conclusions are as follows:（1）Pmean and Rx1day over MLYRV show large interannual to interdecadal variations since early 20^th century with no clear long-term trend until the 1960s with slope 0.35%/yr and0.25%/yr respectively while Rx5day shows insignificant trend with 0.18%/yr（probability=0.83）.Four heaviest events are identified based on Pmean in 1954,2020,1998 and 1931,which all are typical El Nino-decaying year summers.The combined effects by three oceans enhance the western North Pacific anticyclone（WNPAC）,leading to the intensified moisture transport to south-eastern China.（2）CMIP6 models can reasonably reproduce the climatology,interannual variability and linear trend of Pmean,Rx1day and Rx5day over the MLYRV.CMIP6 has wet bias in simulating the climatology of precipitation.The relative error（RE）of Pmean is the smallest among three indices while that of Rx1day is the largest.CMIP6 has high skill in the interannual variability of precipitation,especially of Rx5day.Moreover,compared with the climatology and variability,CMIP6 is weak in the long-term trend of precipitation with large uncertainty in models but still can simulate the trends of precipitation in most cells over the MLYRV and reproduce the significant regional change.（3）This study conducts a comprehensive attribution analysis on extreme precipitation events,which allows the precise location of the area to change in different years.The traditional and new methods both find the different anthropogenic influence on 1931,1954,1998 and 2020events.The impacts are negligible in the early period and the RRs in 1931 are around the unity.As emissions increase,the effects of greenhouse gases（GHGs）in increasing extreme precipitation and aerosols（AAs）in suppressing extreme precipitation gradually emerge and strengthen.Their competing effects lead to the transition of anthropogenic effects from reducing occurrence probability（1954 and 1998 events）to increasing probability（2020 event）.The more extreme the precipitation event,the clearer the anthropogenic influence.However,GHGs have exerted a larger influence on short-duration precipitation events while AAs have had a larger influence on monthly mean precipitation,leading the positive contribution from anthropogenic influence to Rx1day(late in 20^th)and Rx5day to emerge earlier than Pmean(early in 21^st).（4）Based on CMIP6 models,Pmean,Rx1day and Rx5day over the MLYRV are increasing with time under all scenarios.The higher the emission scenario,the more intense the precipitation enhancement,and the more significant the external forcing effect.The sensitivities of 1-in-20-yr Pmean,Rx1day and Rx5day toΔGMST are respectively 4.4%/K,7.3%/K and6.4%/K.At 2℃warming relative to 2000,1-in-20-yr Pmean,Rx1day and Rx5day events are respectively expected to occur about every 11,9 and 10 years.The sensitivity of Pmean magnitude toΔGMST is independent of the extremity and transient climate response（TCR）of models while dependent on emission scenarios,and that of Rx1day only depends on extremity and that of Rx5day depends both on extremity and emission scenarios.In terms of frequency sensitivity,the impact factors of Rx1day and Rx5day are consistent with those of magnitude sensitivity while Pmean is only independent of TCR.