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 ...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.展开更多
Heavy rains and floods are long considered critical societal concerns due to adverse effects on society,environment,and economies.The best appropriate identification for rainfall distribution is equally of significant...Heavy rains and floods are long considered critical societal concerns due to adverse effects on society,environment,and economies.The best appropriate identification for rainfall distribution is equally of significant concern to society and planners due to its application in the hydrological and water resources management sectors,and agricultural planning.Two methods for extreme values theory namely the annual maximum(AM)series method and the peaksover-threshold(POT)method are generally employed for extreme values analyses.This study therefore compared the results of both methods for ARC2 daily rainfall data at Bamako-Senou station for the period 1991-2021.Five(05)commonly used distribution functions,namely the Normal,Log-Normal(LN),Gumbel type I,Gamma and Pearson type 3(P3)distributions were used to fit the AM data.The method of moments(MOM)and the method of maximum likelihood estimation(MLE)were employed for parameters estimation in AM analyses.The generalized Pareto(GP)distribution was also used to fit the peaks over threshold(POT)method.The results indicated that the P3 distribution gave better result than other distributions when parameters were estimated with the MLE.The LN distribution was also best fit distribution to AM series when parameters were estimated with the MOM.The P3 distribution gave higher quantile estimates than other distributions.The POT method gave better results for quantiles estimation than the AM series.It is recommended that further study should include various truncation levels and tests for the choice of an optimal threshold in the POT method.展开更多
基金Under the auspices of National Key R&D Program of China(No.2019YFC1510203)National Natural Science Foundation of China(No.42171101,41871028)。
文摘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.
文摘Heavy rains and floods are long considered critical societal concerns due to adverse effects on society,environment,and economies.The best appropriate identification for rainfall distribution is equally of significant concern to society and planners due to its application in the hydrological and water resources management sectors,and agricultural planning.Two methods for extreme values theory namely the annual maximum(AM)series method and the peaksover-threshold(POT)method are generally employed for extreme values analyses.This study therefore compared the results of both methods for ARC2 daily rainfall data at Bamako-Senou station for the period 1991-2021.Five(05)commonly used distribution functions,namely the Normal,Log-Normal(LN),Gumbel type I,Gamma and Pearson type 3(P3)distributions were used to fit the AM data.The method of moments(MOM)and the method of maximum likelihood estimation(MLE)were employed for parameters estimation in AM analyses.The generalized Pareto(GP)distribution was also used to fit the peaks over threshold(POT)method.The results indicated that the P3 distribution gave better result than other distributions when parameters were estimated with the MLE.The LN distribution was also best fit distribution to AM series when parameters were estimated with the MOM.The P3 distribution gave higher quantile estimates than other distributions.The POT method gave better results for quantiles estimation than the AM series.It is recommended that further study should include various truncation levels and tests for the choice of an optimal threshold in the POT method.
