Spatial Distribution of High-temperature Risk with a Return Period of Different Years in the Yangtze River Delta Urban Agglomeration

作     者：ZHANG Guixin WANG Shisheng ZHU Shanyou XU Yongming ZHANG Guixin;WANG Shisheng;ZHU Shanyou;XU Yongming

作者机构：School of Geographical SciencesNanjing University of Information Science&TechnologyNanjing 210044China Academy of Environmental Planning&Design CO.LTD.Nanjing UniversityNanjing 210093China School of Remote Sensing and Geomatics EngineeringNanjing University of Information Science&TechnologyNanjing 210044China 

出 版 物：《Chinese Geographical Science》 (中国地理科学（英文版）)

年 卷 期：2022年第32卷第6期

页      面：963-978页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0706[理学-大气科学] 

基　　金：Under the auspices of National Key R&D Program of China(No.2019YFC1510203) National Natural Science Foundation of China(No.42171101,41871028) 

主　　题：high-temperature risk generalized extreme value method recurrence period remote sensing spatialization 

摘      要：Against the background of global warming,research on the spatial distribution of high-temperature risk is of great significance to effectively prevent the adverse effects of high *** using air temperature data from 1951 to 2018 measured by meteorological stations located in the Yangtze River Delta urban agglomeration,the daily maximum air temperature distribution is interpolated at a resolution of 1 km based on the local thin disk smooth spline function;the high-temperature threshold for return periods of 5,10,20 and 30 yr are then calculated by using the generalized extreme value *** yearly average high-temperature intensity and high-temperature days are finally calculated as high-temperature danger *** statistical data and remotely sensed image data in 2018 are used as the background data to calculate the spatial distribution of high-temperature vulnerability factors and prevention capacity factors,which are then used to compute the high-temperature risk index during different recurrence periods in the Yangtze River Delta urban *** results show that the spatial distribution features of high-temperature risk in different return periods are *** high-temperature risk index gradually increases from northeast to southwest and from east coast to inland,which has obvious latitude variation characteristics and a relationship with the comprehensive influence of the underlying surface and urban *** terms of time variation,the high-temperature risk index and its spatial distribution difference gradually decreases with increasing return *** different cities,the high-temperature risk in the central area of the city is generally higher than that in the surrounding suburban ***,Hangzhou of Zhejiang Province and Xuancheng of Anhui Province are the top three cities with high-temperature risk in the study area.