1961—2022年江西省高溫致災因子危險性分析
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江西省防災減災工程技術研究中心專項(JX2023M01)資助


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

    高溫危險性評價是高溫災害風險評估的基礎工作。本文基于江西省1961—2022年79個氣象站逐日最高氣溫資料,采用最小二乘法和核密度估計方法,分析了江西省近62年高溫日數、極端最高氣溫和高溫強度等3個致災因子的變化趨勢,五年一遇、十年一遇、二十年一遇和五十年一遇4種重現期下各高溫致災因子取值;并結合K-means聚類分析,對江西省高溫綜合危險性進行了評估;最后,探討了高溫對農業影響的風險等級。結果表明:①近62年江西省三類高溫致災因子整體呈增加趨勢,但存在1997年以前下降的階段性特征;②各致災因子的單一危險性均較高,高危險性區域占全省面積比例達到41.7%~61.4%;③高溫綜合危險性呈南北低中間高的空間分布格局,高危險區域主要集中在上饒東部和吉安大部;④高溫對農業影響的中、高風險區與高溫綜合危險性分布一致,而低風險區有所擴大,主要集中在贛州南部、新余大部、南昌中北部以及九江東部。本文能夠為氣象災害綜合風險評估提供一定參考。

    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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陳新玉,李翔翔.1961—2022年江西省高溫致災因子危險性分析[J].氣象科技,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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  • 在線發布日期: 2024-10-30
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