基于高密度气象站的订正与日极端降水量精细化研究  

Adjusting and refinement of daily extreme precipitation based on high-density weather stations

作　　者：司丽丽 邵琪[4,5,6] 赵亮 魏铁鑫 侯佳[4,5,6] 黄敬峰 SI Lili;SHAO Qi;ZHAO Liang;WEI Tiexin;HOU Jia;HUANG Jingfeng(Key Laboratory of Meteorology and Ecological Environment of Hebei Province,Shijiazhuang 050021,China;China Meteorological Administration Xiong’an Atmospheric Boundary Layer Key Laboratory,Baoding 071800,China;Meteorological Disaster Prevention and Environment Meteorology Center of Hebei Province,Shijiazhuang 050021;Key Laboratory of Environment Remediation and Ecological Health,Ministry of Education,College of Environmental Resource Sciences,Zhejiang University,Hangzhou 310058,China;Institute of Agricultural Remote Sensing and Information Technology Application,Zhejiang University,Hangzhou 310058,China;Key Laboratory of Agricultural Remote Sensing and Information System,Zhejiang University,Hangzhou 310058,China)

机构地区：[1]河北省气象与生态环境重点实验室,河北石家庄050021 [2]中国气象局雄安大气边界层重点开放实验室,河北保定071800 [3]河北省气象灾害防御和环境气象中心,河北石家庄050021 [4]污染环境修复与生态健康教育部重点实验室,浙江大学环境与资源学院,浙江杭州310058 [5]浙江大学农业遥感与信息技术应用研究所,浙江杭州310058 [6]浙江省农业遥感与信息技术重点研究实验室,浙江杭州310058

出　　处：《自然灾害学报》2023年第3期145-159,共15页Journal of Natural Disasters

基　　金：河北省“十三五”重点工程项目;中央高校基本科研业务费专项资金项目(2020FZZX001-06)。

摘　　要：随着全球气候变暖,近年来极端降水事件及其引发的洪涝灾害频发,极端降水事件的模拟与精细化研究显得尤为重要。随着区域气象站网的加密建设,为极端降水事件的精细化研究提供可能。为了将区域站短序列数据应用到日极端降水量的研究中,本研究首先基于年最大值法(annual maximum,AM)和超阈值峰值法(peak over threshold,POT)抽样方法与44种概率分布模型,选择最优抽样方法与概率分布模型,并在此基础上提出对于短序列数据计算日极端降水量的订正方案,通过国家站分析论证,优选出最佳订正方案,将该订正方法应用到只有短序列实测数据的区域站中,优选插值参数并比较不同空间插值方法对插值精度的影响,选择最优的插值方法实现日极端降水量的精细化研究。结果表明,POT1抽样方法与广义帕累托模型是最适用于计算河北省日极端降水量的抽样方法与模型;本研究提出的区域站订正与计算日极端降水量方法可行,将区域站考虑进来后与国家站联合插值使得在空间上更加精细。With global warming,extreme precipitation events and flood disasters have become frequent in recent years,so fine research of extreme precipitation events are particularly important.With the construction of regional weather station,it is possible to study extreme precipitation events in detail.In order to apply short series data to the study of daily extreme precipitation,this study firstly select the optimal sampling method and probability distribution model based on AM(annual maximum)and POT1(peak over threshold)sampling methods and 44 probability distribution models.On this basis,an adjusting method for calculating daily extreme precipitation with short series data is proposed.The best adjusting method is chosen through the analysis and demonstration of national stations,and the best adjusting method is applied to regional stations with only short series measured data.The interpolation parameters are optimized and the effects of different spatial interpolation methods on interpolation accuracy are compared.The best interpolation method is selected to realize the fine study of daily extreme precipitation.The results show that POT1 sampling method is the most suitable sampling method and Gen.Pareto model are the most suitable model for calculating daily extreme precipitation in Hebei Province.The regional stations adjust method and daily extreme precipitation calculation method proposed in this study is feasible,and the regional stations are taken into account and combined with national interpolation to make the spatial distribution more precise.

关 键 词：日极端降水量 概率分布模型 区域站 重现期 订正延长 精细化研究 

分 类 号：P426.6[天文地球—大气科学及气象学]