The Experimental Research About Extreme Precipitation Used Statistical Simulating Model At Present-day Climate Scenarios

In this paper, the sensitivity, of the extreme events responded to the mean value is discussed in both theory, and practical spheres. The summertime mean daily temperatures in Shenyang are modified using normal distribution, and it is found that the extreme values show a non-linear trend by compare the ratios of extreme values before and after the transition of linear trend of mean temperatures. Based on the simulation of JJA precipitation in Nanjing using Gamma distribution, the scale parameter along with the position parameter increased accompanied by the growth of precipitation. In addition, extreme values indicate irregular variations.The daily extreme precipitations from May to September in eastern part of China are simulated by GPD model. The result shows that GPD is superior to GEV and other distributions in simulating the distribution of extreme precipitations. Threshold of the extreme events occurred every, 50 years and 100 years are calculated respectively and its spatial distributions are analyzed. The two results are similar which display decreasing trend from south-east to north-west and are different between northern and southern part. The extreme precipitation in southern part of China is probably as twice as that in northern part and the longer the data are the better the result is. And it is verified that the scale parameter has a reciprocal correlation with standard deviation. The position parameter is affected by the standard deviation as well as the mean value which is more important.The daily precipitation are derived at the 6 representative stations in eastern part of China and 78 representative stations based on the multi-state one-order Markov chain model. The simulated results are compared with the observations such as the square deviation of monthly precipitation, the maximum daily precipitation, month-averaged rainy days, the square deviation of daily precipitation, daily mean rainfall, indicating that the model is able to simulate characteristics of the precipitation. The characteristics of precipitation can be stimulated and since the representative stations located in different climate regions, this model is of universal significance. Markov chain model used to simulate extreme precipitation is also of universal significance. The simulated extreme precipitation is belong to Pareto distribution and is good at simulation. The simulated results are similar to the conversational data in analyzing threshold value and reoccur in the period 50 years and 100 years. Additionally, the less the error between the simulated results and the conversational ones. the less the contrast of the extreme values in reoccur period is.