气候变化背景下海河流域极端降水特征及不同重现期降水量估计  

Extreme precipitation characteristics and return period estimation in the Haihe River basin under climate change

作　　者：庄园煌 陈宏 孙密娜[2] 梁健 ZHUANG Yuanhuang;CHEN Hong;SUN Mina;LIANG Jian(Tianjin Key Laboratory of Marine Meteorology,Tianjin 300074,China;Tianjin Meteorological Observatory,Tianjin 300074,China;China Meteorological Administration Hyolro-Meteorology Key Laboratory,Beijing 100081,China;Tianjin Weather Modification Office,Tianjin 300074,China;Tianjin Meteorological Information Center,Tianjin 300074,China)

机构地区：[1]天津市海洋气象重点实验室,天津300074 [2]天津市气象台,天津300074 [3]中国气象局水文气象重点开放实验室,北京100081 [4]天津市人工影响天气办公室,天津300074 [5]天津市气象信息中心,天津300074

出　　处：《大气科学学报》2025年第2期278-288,共11页Transactions of Atmospheric Sciences

基　　金：国家重点研发计划项目(2022YFC3090600);湖北省自然科学基金联合基金项目(2023AFD106);中国气象科学研究院基本科研业务费专项资金项目(2023Z016)。

摘　　要：天津市气象局科研项目(202544ybxm29);中国气象局水文气象重点开放实验室开放研究课题项目(24SWQXZ014);国家自然科学基金项目(42192561)摘要基于1961-2022年逐日站点降水观测资料,选取年最大降水量序列(annual maximum,AM)和超门限峰值序列(peak over threshold,POT),对气候变化背景下海河流域极端降水的时空变化及其统计特征进行研究。结果表明,过去62 a,海河流域有54个站的年最大日降水量呈增加趋势,有79个站点表现出减少的趋势。从单个气象站点来看,年最大降水量的最大值发生的时间大多集中于20世纪60-70年代,且以汛期(7、8月)居多。进一步利用多种极值分布方法、L-矩法和K-S检验等方法,发现广义极值(generalized extreme value,GEV)、广义帕累托(generalized Pareto,GP)极值分布函数分别能够较好拟合AM和POT序列。比较不同重现期水平下的降水量,发现AM序列及其对应的GEV分布能够更好地模拟海河流域极端降水。With the ongoing intensification of global warming,extreme precipitation events have become more frequent,exerting dramatic impact on socio-economic development and poses a severe risks to lives and property in the Haihe River basin.This study analyzes the spatiotemporal variability and statistical characteristics of extreme precipitation in the basin under climate change,utilizing daily precipitation observation from 1961 to 2022.Extreme precipitation events are defined using the annual maximum precipitation(AM)series and peak-over-threshold(POT)series.The results show that the spatial distribution patterns of the multi-year average AM and POT series are similar,with maximum daily precipitation primarily concentrated west of the Taihang Mountains and south of the Yanshan Mountains.Variability analysis reveals that annual maximum daily precipitation at most meteorological stations ranged between 0 and 50 mm,with the highest variability along the Taihang and Yanshan Mountains ranges,where the standard deviation reaches approximately 40 to 50 mm.Furthermore,trends in the annual maximum precipitation show spatial heterogeneity:among the 133 meteorological stations analyzed,54 exhibit increasing trend,whereas 79 stations showed a decreasing trend over the study periods(1961-2022).On a station-specific scale,the majority of extreme daily precipitation events occurred during the flood season(July to August)in the 1960s and 1970s.To model extreme precipitation,various extreme value distribution function,including the Generalized Extreme Value(GEV),Generalized Pareto(GP),and Gamma distributions,were evaluated using the L-moment method and the Kolmogorov-Smirnov(K-S)test.The findings demonstrated that the GEV distribution effectively models the AM series,while the GP distributions provides an optimal fit for POT series.Furthermore,comparative analysis of precipitation estimates across different return periods suggests that the AM series,in conjunction with the GEV distribution provide a better representation of extreme pr

关 键 词：海河流域 极端降水 L-矩法 K-S检验 

分 类 号：P426.6[天文地球—大气科学及气象学]