The Analysis Of Highly Sensitive Areas To Extreme Precipitation Based On Probabilistic Risk

In this paper,the Generalized Extreme Value(GEV)is used to establish the statistical distribution relationship and theoretically explore the influence of the location parameter(climate mean state)and scale parameter(interannual variability)on the change of extreme precipitation probability ratio based on the measured daily precipitation data from 1961 to 2005;for the BCC-CSM1.1(m),MPI-ESM-MR,IPSL-CM5A-MR model data,the effect of various bias correction methods on the simulation of extreme precipitation in China is systematically examined;further,we discuss the effects of changes in climate mean state and interannual variability under global warming of 1.5and 2°C on the future risk changes of extreme precipitation in Chinese and their highly sensitive response areas with the revised model data.The following conclusions are drawn:(1)Small changes in climate mean state and interannual variability will lead to changes in the probability ratio of extreme precipitation events.The probability ratio change rate is always positive for different recurrence periods,and shows a parabolic variation with increasing climate state and interannual variability,followed by decreasing variability;The influence of both on the probability distribution is investigated with the help of numerical experiments to demonstrate the accuracy of the theoretical results;Further,through the calculation results of climate mean state,interannual variability and the corresponding probability ratio change rate of several representative stations and observations,the probability ratio change rate of both is the highest in the northwest region,indicating that the northwest region is the most sensitive region in response to extreme precipitation.(2)The model data of BCC-CSM1.1(m),MPI-ESM-MR,and IPSL-CM5A-MR have systematic bias and the simulation of extreme precipitation has a general bias;the model simulation is improved significantly after correction by quantile delta mapping(QDM)and two variants(MBCn and MBCp)of the multivariate bias correction method(MBC).However,there are differences between the three methods in different aspects of the revisions.After the MBC revision,the precipitation is closer to the observation in terms of distribution pattern and interval mean precipitation.MBCp has the most obvious improvement,and the revised precipitation intensity and 95% quantile precipitation are significantly lower than the other two methods in terms of percent deviation and root mean square error;meanwhile,MBC can significantly improve the spatial correlation coefficients with observations,and the correlation coefficients of all indices are over 0.9.(3)The increase in global temperature(relative to pre-industrial levels)will lead to a trend of increasing extreme precipitation probability ratio,and although the spatial pattern of PR at specific warming levels is similar,a difference of 0.5°C will lead to more frequent extreme precipitation.In addition,the highly sensitive areas of extreme precipitation are mainly located in the northeastern region and the region south of the Yangtze River;the changes in the probability ratio of extreme precipitation can be explained by the climate mean state and interannual variability,but there are some differences in the contributions of both to the changes in the probability ratio of highly sensitive areas.The contribution of interannual variability is mainly responsible for the increased risk of extreme precipitation probability in most regions of the country.