四川盆地短历时强降水极值分布的研究  

Research on extreme value distribution of short-duration heavy precipitation in the Sichuan Basin

作　　者：司波[1] 余锦华[1] 丁裕国[1] 

机构地区：[1]南京信息工程大学气象灾害省部共建教育部重点实验室,南京210044

出　　处：《气象科学》2012年第4期403-410,共8页Journal of the Meteorological Sciences

基　　金：国家重点基础研究发展计划(973计划)项目(2012CB955903);国家科技支撑计划项目(2007BAC29B0602)

摘　　要：运用广义帕雷托分布(GPD)和广义极值分布(GEV),借助于L-矩的参数估计方法,对四川盆地12站的小时极端降水量进行拟合,并对两种模型的拟合效果进行比较。运用Hill图,结合统计量D*来确定GPD的最佳门限值是合适的,选出的样本是独立的。各站的小时极端降水概率分布均符合GPD和GEV,但GPD模型的拟合精度要优于GEV模型。利用两种模型推算出各站给定重现期的最大小时降水量,其中泸州50 a一遇和100 a一遇的降水极值分位数都超过了100 mm,除了遂宁站外,两种模型估计出的极值分位数的相对误差基本都在10%以下。通过分析,GPD推算的结果更加可靠。The generalized extreme value distribution （GEV） and generalized Pareto distribution （GPD） are used to fit the hourly extreme-precipitation of twelve stations in the Sichuan Basin, based on parameter estimation method of L-moment. Then we compare the effects of the two models. It is appropri- ate to use Hill plot with D＊ to determine the optimal threshold of GPD, and the selected samples are in- dependent. The probability distribution of hourly extreme-precipitation of each station is all in line with GPD and GEV, but GPD model shows better fitting accuracy than GEV model. The maximum hourly pre- cipitation with a given return period was calculated by the two models for each station. The extreme quantiles for 50 a and 100 a return period in Luzhou exceeded 100 ram. In addition to Suining, the relative errors of the estimation of extreme quantiles are basically below 10% for each model. The estimated resuits based on GPD are more reliable by the analysis.

关 键 词：短历时强降水 广义帕雷托分布 广义极值分布 重现期 

分 类 号：P467[天文地球—大气科学及气象学]