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 

机构地区：[1]School of Geographical Sciences,Nanjing University of Information Science&Technology,Nanjing 210044,China [2]Academy of Environmental Planning&Design CO.,LTD.,Nanjing University,Nanjing 210093,China [3]School of Remote Sensing and Geomatics Engineering,Nanjing University of Information Science&Technology,Nanjing 210044,China

出　　处：《Chinese Geographical Science》2022年第6期963-978,共16页中国地理科学（英文版）

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

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 temperatures.By 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 method.The yearly average high-temperature intensity and high-temperature days are finally calculated as high-temperature danger factors.Socioeconomic 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 agglomerations.The results show that the spatial distribution features of high-temperature risk in different return periods are similar.The 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 scale.In terms of time variation,the high-temperature risk index and its spatial distribution difference gradually decreases with increasing return period.In different cities,the high-temperature risk in the central area of the city is generally higher than that in the surrounding suburban areas.Jinhua,Hangzhou of Zhejiang Province and Xuancheng of Anhui Province are the top three cities with high-temperature risk in the study area.

关 键 词：high-temperature risk generalized extreme value method recurrence period remote sensing SPATIALIZATION 

分 类 号：P407[天文地球—大气科学及气象学] P429