| 中国不同气候区的高温危险性分析 |
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| 引用本文： | 郭春华,朱秀芳,孙劭,唐明秀,徐昆,张世喆.中国不同气候区的高温危险性分析[J].热带气象学报,2023(1):66-77. |
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| 作者姓名： | 郭春华 朱秀芳 孙劭 唐明秀 徐昆 张世喆 |
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| 作者单位： | 1. 北京师范大学环境演变与自然灾害教育部重点实验室，北京 100875；2. 北京师范大学地理科学学部遥感科学与工程研究院，北京 100875;3. 中国气象科学研究院灾害天气国家重点实验室，北京 100081 |
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| 基金项目： | 国家自然科学基金面上基金项目(42077436)；;国家重点研发计划项目(2019YFA0606900)共同资助； |
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| 摘 要： | 高温危险性评价是高温灾害风险评价的重要组成部分和基础工作。基于过去60年(1961—2020年)的日最高温度数据，选择高温日数、最高温度、高温强度三个指标，逐站点使用核密度函数估算三个高温指标的概率密度函数，计算了四个重现期(即五年一遇、十年一遇、二十年一遇和五十年一遇)下的三个指标的取值，进而通过K-means非监督聚类得到各指标下的高温危险性等级分布图，然后将各指标叠加，对我国不同气候区的综合高温危险性进行了评估。研究表明：(1)从高温日数来看，发生高温可能性最大的地区位于我国西北干旱(半干旱)区和华中、华南地区的交界部分；(2)从最高温度来看，发生高温可能性最大的区域是西北干旱(半干旱)区和华北地区，华中地区的最高温度在不同重现期下的增强最显著；(3)从高温强度来看，发生高温可能性最大的区域是西北干旱(半干旱)区，西南地区和青藏高原地区内不同区域的高温强度差异较大，需局部防范高温灾害；(4)随着重现期年限的增长，不同高温指标值均明显增长，高值区域面积逐渐增加。全国高温综合高危险性等级地区主要位于西北干旱(半干旱)地区、华北地区南部、华中地区、华南地区和西南地区北部，其余气候区少量...
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| 关 键 词： | 高温 危险性评价 重现期 核密度函数 聚类 |
ANALYSIS OF HIGH TEMPERATURE HAZARD IN DIFFERENT CLIMATE REGIONS OF CHINA |
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| GUO Chunhu,ZHU Xiufang,SUN Shao,TANG Mingxiu,XU Kun,ZHANG Shizhe.ANALYSIS OF HIGH TEMPERATURE HAZARD IN DIFFERENT CLIMATE REGIONS OF CHINA[J].Journal of Tropical Meteorology,2023(1):66-77. |
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| Authors: | GUO Chunhu ZHU Xiufang SUN Shao TANG Mingxiu XU Kun ZHANG Shizhe |
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| Institution: | 1. Key Laboratory of Environmental Change and Natural Disasters, Ministry of Education, Beijing Normal University, Beijing 100875, China;2. Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China;3. State Key Laboratory of Severe Weather/Chinese Academy of Meteorological Sciences, Beijing 100081, China |
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| Abstract: | Hazardness assessment is the basis and an important part of high temperature hazard research. Based on the daily maximum temperature data of the past 60 years from 1961 to 2020, three indicators were calculated and used to describe the hazard of high temperature, and they were the number of high temperature days, maximum temperature, and high temperature intensity. We used the kernel density estimation to calculate the values of the three indexes under four return periods (5, 10, 20, and 50 years). Furthermore, through K-means unsupervised clustering, the distribution of high temperature risk levels for each indicator was obtained, and then the indicators were superimposed to evaluate the comprehensive high temperature risk of different climate regions in China. The results show that: (1) From the perspective of high temperature days, the area with the greatest possibility of high temperature is the arid (semi-arid) region in the northwest, and the junction of central and South China. (2) From the point of view of the highest temperature, the regions with the greatest possibility of high temperature are northwest arid (semi-arid) region and North China, and the highest temperature in central China increases most significantly in different return periods. (3) From the perspective of high temperature intensity, the region with the highest possibility of high temperature is the arid (semi-arid) region in northwest China. The high temperature intensity in different areas of southwest China and the Qinghai Tibet Plateau is quite different, so local prevention of high temperature is necessary. (4) With the increase of the duration of return periods, the values of different high temperature indexes increase obviously, and the range of high value area expands gradually. The high-temperature comprehensive high-risk areas in China are mainly located in the arid (semi-arid) regions of northwest China, southern North China, central China, South China, and northern southwest China. Relatively high-risk areas are mainly distributed in the northern part of North China, part of eastern China, part of the arid (semi-arid) area of the northwest, and a small part of the southwest. The areas with medium risk are mainly distributed in the western part of the eastern region. The prevention of high temperature in these areas needs to be strengthened. |
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| Keywords: | high temperature hazardness assessment return period Kernel density function clustering |
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