1961—2022年江西省高温致灾因子危险性分析
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江西省防灾减灾工程技术研究中心专项(JX2023M01)资助


Dangerousness Analysis of High-Temperature Disaster-Inducing Factors in Jiangxi Province
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    摘要:

    高温危险性评价是高温灾害风险评估的基础工作。本文基于江西省1961—2022年79个气象站逐日最高气温资料,采用最小二乘法和核密度估计方法,分析了江西省近62年高温日数、极端最高气温和高温强度等3个致灾因子的变化趋势,五年一遇、十年一遇、二十年一遇和五十年一遇4种重现期下各高温致灾因子取值;并结合K-means聚类分析,对江西省高温综合危险性进行了评估;最后,探讨了高温对农业影响的风险等级。结果表明:①近62年江西省三类高温致灾因子整体呈增加趋势,但存在1997年以前下降的阶段性特征;②各致灾因子的单一危险性均较高,高危险性区域占全省面积比例达到41.7%~61.4%;③高温综合危险性呈南北低中间高的空间分布格局,高危险区域主要集中在上饶东部和吉安大部;④高温对农业影响的中、高风险区与高温综合危险性分布一致,而低风险区有所扩大,主要集中在赣州南部、新余大部、南昌中北部以及九江东部。本文能够为气象灾害综合风险评估提供一定参考。

    Abstract:

    The increasing frequency, intensity and scope of extreme heat events due to climate change, which is mainly characterised by significant warming, is one of the current key climate stressors for sustainable development in terms of socio-economics, ecological balance and agricultural production in Jiangxi Province. High-temperature dangerousness evaluation is the basic work of high-temperature disaster risk assessment. However, in Jiangxi Province, the current research on high-temperature hazards mainly focuses on the analysis of trends and spatial distribution patterns, and few studies are conducted to reveal the risk of high-temperature occurrence through disaster risk theory. In this paper, based on the daily maximum temperature data of 79 meteorological stations in Jiangxi Province from 1961 to 2022, the trends of three disaster-inducing factors (the number of high-temperature days, the extreme maximum temperature and the high-temperature intensity) and their values under four return periods (1 in 5 years, 1 in 10 years, 1 in 20 years, and 1 in 50 years, respectively) are analysed using the least square method and the Kernel density estimation method, respectively. Then, through K-mean cluster analysis, the dangerousness distribution of each disaster-causing factor is obtained and a comprehensive high-temperature dangerousness map is produced. Finally, according to the disaster risk theory, the agricultural heat risk is assessed by the product of high-temperature dangerousness, agricultural exposure (quantified by land use cover) and agricultural fragility (quantified by gross domestic product kilometre gridded data). The results show that: (1) The overall trend of the number of high-temperature days, extreme maximum temperature and high-temperature intensity in Jiangxi Province during 1961-2022 shows an increasing trend, but the trend has a phased character, with a decreasing trend before 1997. (2) The dangerousness of each disaster-inducing factor is relatively high, with the proportion of high-risk areas in the province ranging from 41.7% to 61.4%. (3) The comprehensive dangerousness shows a spatial distribution pattern of low in the north and low in the centre, and the high-risk areas are mainly concentrated in the eastern part of Shangrao and most parts of Ji’an. (4) Agricultural medium-high risk zones are consistent with the spatial distribution of the dangerousness map. However, due to the uneven distribution of agricultural fragility, the low-risk zone is more surrounded by cities, and is mainly concentrated in southern Ganzhou, most of Xinyu, north-central Nanchang, and eastern Jiujiang. This paper can provide some reference for the comprehensive risk assessment of meteorological disasters.

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陈新玉,李翔翔.1961—2022年江西省高温致灾因子危险性分析[J].气象科技,2024,52(5):723~732

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  • 收稿日期:2023-10-08
  • 定稿日期:2024-07-01
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  • 在线发布日期: 2024-10-30
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