中国脱贫县破纪录极端天气事件研究

doi:10.12006/j.issn.1673-1719.2024.267

摘要/Abstract

摘要： 脱贫地区作为高脆弱性地区，往往承受着更高的自然灾害致贫返贫风险，而目前有关我国脱贫县未来面临的破纪录极端天气危险性认识不足。文中基于NEX-GDDP-CMIP6全球降尺度气候情景的22个模式数据，结合8个极端天气指标，探讨中国832个脱贫县和其他县极端天气时空分布规律。结果表明：中国面临着严峻的极端高温威胁。1950—2014年极端高温事件的频次呈快速增加趋势，在高排放情景下（SSP3-7.0)，2040年中国84.82%的县份暖夜日数（TN_90p）破纪录概率将突破80%，到2050年83.40%的县份暖昼日数（TX_90p）破纪录概率将突破80%。脱贫县面临更严重的极端高温威胁，高温热浪（HW）破纪录概率显著高于其他县，同时TX_90p破纪录概率将于2030—2040年间超过50%，早于其他县10年。胡焕庸线西部脱贫县历史复合干旱-热浪（CDHW）增长速率是其他地区的10余倍，未来破纪录概率是东部脱贫县的1~2倍。其中，新疆、内蒙古西部、青海及云南南部的脱贫县是CDHW破纪录概率高值区；胡焕庸线沿线区域（南北两翼)、海南岛、黄渤海沿岸区及新疆西北部拥有更高的连续洪水-热浪（SFH）破纪录概率。研究结果表明中国脱贫县受破纪录极端天气威胁更高。为有效防范应对极端天气，提出了水利设施、防灾减灾设施、巨灾保险、公众宣传教育等方面政策建议。

关键词: 气候变化, 胡焕庸线, 脱贫县, 破纪录概率, 极端高温, 极端降水, 复合极端事件

Abstract:

Poverty-alleviated regions are particularly vulnerable to reverting back to poverty due to natural disasters. However, there is limited understanding of the potential future risks posed by record-breaking extreme weather in China’s poverty-alleviated counties. Data from 22 models, based on the NEX-GDDP-CMIP6 global downscaling climate scenarios and combined with 8 extreme weather indices, were used to analyze the spatio-temporal distribution patterns of extreme weather across 832 poverty-alleviated counties and other counties in China. The results are as follows. China faces significant threats from extreme heats. From 1950 to 2014, the frequency of extreme heat events increased rapidly. Under the SSP3-7.0 high-emission scenario, it is projected that 84.82% of Chinese counties will experience a record-breaking possibility greater than 80% for warm nights (TN_90p) by 2040, while 83.40% are expected to surpass this threshold for warm days (TX_90p) by 2050. Poverty-alleviated counties face a more severe threat from extreme heats than other counties. The record-breaking probability of heatwave (HW) in these counties is significantly higher than in other counties. Between 2030 and 2040, the probability of TX_90p record-breaking events in poverty-alleviated counties is projected to exceed 50%, a decade earlier than in other counties. The analysis of compound drought and heatwave (CDHW) events from 1950 to 2014 shows that poverty-alleviated counties west of the Hu Line experienced a growth rate more than ten times that of other regions. The record-breaking probability of CDHW in western poverty-alleviated counties is 1 to 2 times higher than in eastern poverty-alleviated counties in the future. Specifically, poverty-alleviated counties in Xinjiang, western Inner Mongolia, Qinghai, and southern Yunnan are identified as high-risk areas for record-breaking CDHW probabilities. Regions along the Hu-Line (especially its northern and southern flanks), Hainan Island, the coastal zones of the Yellow Sea and Bohai Sea, and northwestern Xinjiang exhibit significantly higher record-breaking possibility for sequential precipitation-humid heatwave (SFH) events. The study indicates that China’s poverty-alleviated counties are more vulnerable to record-breaking extreme weather. To effectively mitigate and adapt to extreme weather, policy recommendations are proposed on water infrastructure, disaster mitigation, catastrophe insurance, and public awareness and education.

Key words: Climate change, Hu Line, China’s poverty-alleviated counties, Record-breaking probability, Extreme heat, Extreme precipitation, Compound extreme event

陈思达, 刘凯, 李博浩, 汪明. 中国脱贫县破纪录极端天气事件研究[J]. 气候变化研究进展, 2025, 21(3): 327-339.

CHEN Si-Da, LIU Kai, LI Bo-Hao, WANG Ming. The analysis of record-breaking probability of extreme weather in China’s poverty-alleviated counties[J]. Climate Change Research, 2025, 21(3): 327-339.

图/表 7

图1 研究区概况

Fig. 1 Overview of the study area

表1 极端天气指数定义

Table 1 Definition of extreme weather index

图2 中国基准期极端天气指数变化注：*、**分别表示p<0.05、p<0.01。

Fig. 2 The changes in extreme weather indices during the baseline period in China

图3 中国各县2020—2100年极端天气破纪录概率变化注：*、**分别表示p<0.05、p<0.01。

Fig. 3 The changes in record-breaking probability of extreme weather from 2020 to 2100 in China

图4 SSP3-7.0情景下极端降水破纪录概率注：柱状图纵轴表示特定极端气候事件在统计年限内的破纪录概率，横轴表示处于各概率区间的县份数量占该类型县份总数的比例，下同。

Fig. 4 The record-breaking probability of extreme precipitation under the SSP3-7.0 scenario

图5 SSP3-7.0情景下极端高温破纪录概率

Fig. 5 The record-breaking probability of extreme heat under the SSP3-7.0 scenario

图6 SSP3-7.0情景下复合极端天气破纪录概率

Fig. 6 The record-breaking probability of compound extreme events under the SSP3-7.0 scenario

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