Studies On The Variation Characteristics And Experimentation With Simulation Of China's Extreme Temperatures

Based on the part of 203 stations data from 1957-2001 which are of more extreme sense, the variation characteristics of extreme temperature are studied. At first, analysis of extreme temperature's spatial distribution of variety trend shows that the minimum temperature in the North are going up while the maximal temperature in East China declining widely, which is a numerical characteristics of prevailing warmer-winter in recent years. So the change of minimum and maximal temperature are dissymmetrical. The frequency of minimum-value fluctuates faintly while the maximal-value's fluctuating is more complex and fiercer. Contrasted with average temperature, the change of extreme temperature is more unsteadily.Chinese minimum and maximum temperature fields are divided respectively by the Rotted Empirical Orthogonal Function Eleven,twelve sub regions can be taken for minimum and maximum temperatures respectively. The change of maximum temperature is very different in diverse sub regions, and the characteristics of each phase are different also. All subregions'minimum temperatures are going up, but the changing ranges are different in different sub regions. The relations between extreme temperature and average temperature are diverse in different sub regions, whbreas extreme temperature is more consistent in winter than in summer.With the data of China's yearly extreme-values, the asymptotic distribution is fitted using the Gumbel Distributions. Probability Weighted Moments is an effective method to parameter estimation, with which calculation is simplified and the fitting precision areimproved. Based on the region dividing, region extreme-value is defined and the regulation of its occurring is researched. It is of imported instructional significance for the region layout. Monte Carlo Method does stochastic stimulants experiments about the characteristics of extreme temperature in the future on the background of global warmer. It is feasible to forecast extreme-value of future by the mean value change; but it is difficult to forecast with the changing of variance which rule of variety is difficult to know. So it is the next work to search the variances periodicity and its response to global climate change in order to forecast future.