| A Newly-Discovered GPD-GEV Relationship Together with Comparing Their Models of Extreme Precipitation in Summer |
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| 作者姓名： | 丁裕国 程炳岩 江志红 |
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| 作者单位： | National Key Laboratory of Meteorological Diseases of Jiangsu Nanjing University of Information Science and Technology，Nanjing 210044，Climate Center of Chongqing City Meteorological Bureau，Chongqing 401147，National Key Laboratory of Meteorological Diseases of Jiangsu，Nanjing University of Information Science and Technology，Nanjing 210044 |
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| 基金项目： | 国家自然科学基金，Program of the Jiangsu Key Laboratory of Meteorological Disaster |
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| 摘 要： | It has been theoretically proven that at a high threshold an approximate expression for a quantile of GEV （Generalized Extreme Values） distribution can be derived from GPD （Generalized Pareto Distribution）. Afterwards, a quantile of extreme rainfall events in a certain return period is found using L-moment estimation and extreme rainfall events simulated by GPD and GEV, with all aspects of their results compared. Numerical simulations show that POT （Peaks Over Threshold）-based GPD is advantageous in its simple operation and subjected to practically no effect of the sample size of the primitive series, producing steady high-precision fittings in the whole field of values （including the high-end heavy tailed）. In comparison, BM （Block Maximum）-based GEV is limited, to some extent, to the probability and quantile simulation, thereby showing that GPD is an extension of GEV, the former being of greater utility and higher significance to climate research compared to the latter.
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| 关 键 词： | 暴风雨 降雨量 测试方法 沉淀系数 |
A newly-discovered GPD-GEV relationship together with comparing their models of extreme precipitation in summer |
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| Yuguo Ding,Bingyan Cheng,Zhihong Jiang.A Newly-Discovered GPD-GEV Relationship Together with Comparing Their Models of Extreme Precipitation in Summer[J].Advances in Atmospheric Sciences,2008,25(3):507-516. |
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| Authors: | Yuguo Ding Bingyan Cheng Zhihong Jiang |
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| Abstract: | It has been theoretically proven that at a high threshold an approximate expression for a quantile of GEV (Generalized Extreme Values) distribution can be derived from GPD (Generalized Pareto Distribu-tion). Afterwards, a quantile of extreme rainfall events in a certain return period is found using L-moment estimation and extreme rainfall events simulated by GPD and GEV, with all aspects of their results com-pared. Numerical simulations show that POT (Peaks Over Threshold)-based GPD is advantageous in its simple operation and subjected to practically no effect of the sample size of the primitive series, producing steady high-precision fittings in the whole field of values (including the high-end heavy tailed). In compari-son, BM (Block Maximum)-based GEV is limited, to some extent, to the probability and quantile simulation, thereby showing that GPD is an extension of GEV, the former being of greater utility and higher significance to climate research compared to the latter. |
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| Keywords: | Generalized Pareto Distribution Generalized Extreme Value daily rainfall extreme precipitation rainstorm |
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