气候变化研究进展2017，Vol.13Issue(4)：346-355,10.DOI:10.12006/j.issn.1673-1719.2016.186
中国格点化日降水极值统计模型及阈值的选取
Statistical Model and Threshold Value Selection of Gridded Daily Precipitation Extremes in China
摘要
Abstract
Based on the national daily precipitation 0.5°× 0.5°gridded dataset, annual maximum (AM) samples and peaks over threshold (POT) samples were selected. The generalized extreme value distribution (GEV) and the generalized Pareto distribution (GPD) were employed to establish statistical models of precipitation extremes respectively. The goodness of fit of each model was evaluated by Kolmogorov-Smirnov test. The statistical analysis was performed. Extreme value distribution model of precipitation and threshold value selection criteria applicable to different areas were proposed. The results show that: (1) The simulated results of POT samples are superior to those of AM samples; (2) The method of sample percentile for determining threshold value is better than the others; (3) The geographical distribution pattern of optimization results is similar to the distribution of dry and wet regions in China. The 90?94 percentile is the fittest to determine threshold value in humid regions. The 94?97 percentile is better in semi-arid and sub-humid regions. The 97?99 percentile is the most suitable in arid regions.关键词
极端降水事件/义极值分布/义帕累托分布/K-S检验/阈值Key words
extreme precipitation events/generalized extreme value/generalized Pareto distribution/Kolmogorov-Smirnov test/threshold引用本文复制引用
张昕怡,方国华,闻昕,叶健,郭玉雪..中国格点化日降水极值统计模型及阈值的选取[J].气候变化研究进展,2017,13(4):346-355,10.基金项目
国家自然科学基金资助项目(51609061) （51609061）
长江科学院开放研究基金资助项目(CKWV2016370/KY) （CKWV2016370/KY）
中央高校基本科研业务费专项资金(2015B28614) （2015B28614）
江苏高校优势学科建设工程资助项目 （）
