Abstract:
Based primarily on a probability distribution model of daily rainfall fitted by using Weibull distribution together with Monte Carlo simulation and statistical downscaling methods, statistical simulation experiments are carried out for studying the responses of the regional extremes of daily station rainfall over eastern China to future climate warming. The results show that the change of mean temperature under the backgruond of global warming may lead to variations in the probability distribution features of extreme daily rainfall. For example, there is a positive response of precipitation amount to the average temperature change south of the lowermiddle reaches of the Yangtze River, because the simulated probability distribution curve of regional extreme rainfall events is obviously shifted rightward, which indicates the shortening of the return period for intense extreme rainfall, or the increase of the extremes' probability. But, in the Shandong and Bohai Bay area, there is a nagtive response of precipitation amount to the average temperature change, due to a significant reduction in the scale paremeter of the probability density function for regional extreme rainfall over there. The reduced scale parameter means larger variance, which is represented by enhanced probability density function in both right and left ends. This also leads to the increase of the probability of intense extreme rainfall. This paper only investigates the effect of the change of climatic mean temperature on regional extreme rainfall. The extreme rainfall may be more sensitive to the climatic temperature variance change, sensitivity which needs to be further investigated.