【摘要】 提出了气候极值推断的不确定性问题。并以中国156个测站为例着重探讨了广义极值(GEV)分布模式的分位数估计的标准误差对气候极值不确定性的重要影响,评估了极值分位数的置信区间及其在地域上的分布特征。数值试验表明,样本容量(n)大小是影响广义极值的分位数标准误差的最主要因素,而随着重现期加长(概率愈小)其分位数的标准误差必然增大,因此,直接影响了置信区间——即估计的可信度。更多还原

【Abstract】 The quantile estimation values with the various fitted distributeion are generally undetermined because there are three main inference factors: (1) the indetermination of extreme values due to the statistics theory self;(2) the indetermination of the simulation result from globel climate model; and (3) the results from each donwscaling technology. Generally, bigger errors for the estimated quantile come from mixture influence from the above three factors. In this paper, the sampling errors of estimated quantile with the GEV distribution are researched by means of the statistics inference theory. The numerical test for sampling errors of estimated quantile with the GEV distribution in the 156 stations over East China is made. The results show that total number of observations n is the main affection factor and the sampling errors increase with the increasing return period, thus influencing directly the confidence degree of quantile estimation values.更多还原