非正态分布的天气气候序列极值特征诊断方法研究

A Diagnosis Method of the Extreme Features of Weather and Climate in Time Series Based on Non-Normal Distribution

推广了非正态假设下的交叉理论 ,且将其用于极值特征的诊断 ,并从理论上导出了适用性更广的基于Gamma分布和负指数分布的极值特征量诊断公式及其样本估计式。以有关降水要素的时间序列为例 ,说明了这种方法在天气气候诊断与气候影响研究中的应用前景。

According to the theory presented by Desmond and Guy (1991), the diagnostic formulae for the extreme features are generalized by using the cross theory under the hypothesis of non normal distribution The theoretic formulae and sampling estimator for diagnosis extreme features are derived from the hypothesis of Gamma or exponential distribution in weather or climate series The cases studies of rainfall time series show that the sampling estimator formulae are very effective to observational data series The calculation results show consistence in theory and observation, which show that the method can be applied to the diagnosis of the extreme event of weather or climate, and particularly to the research of the problem for future climatic influence