Variability characteristics and risk assessment of regional high temperature, drought and their compound events in Hubei Province

doi:10.11755/j.issn.1006-7639-2024-06-0825

Abstract

Abstract:

In order to assess the potential impact of climate change on agriculture and develop scientific adaptation strategies, the variability characteristics and risk on agriculture of regional high temperature, drought and their compound events in Hubei Province were identified and analyzed based on daily temperature, precipitation and other observations from 76 national meteorological stations during 1994-2023. The analysis employed classification standards for regional high temperature process and monitoring and assessment methods for drought process. The results show that regional high temperature events occurred an average of 4.3 times per year, with an overall increasing trend and 61.2% of severe and strong events occurred in July and August. Regional drought events occurred an average of 1.5 times per year, showing a deceasing trend before 2010 and increasing trend thereafter, with slightly higher frequencies in winter and spring than in summer and autumn. Regional compound high temperature and drought events mainly occurred from June to August, with an significant increase in frequency after 2010. The spatial distribution of intensity and agricultural risk for regional high temperature and drought events was generally similar. High intensity and high risk areas for high temperature events were mainly located in eastern Hubei, while low intensity areas were in the southwest. For drought events, high intensity and high risk areas were mainly located in central-eastern Hubei, decreasing towards surroundings regions. The agricultural risk of compound high temperature and drought events showed a decreasing trend from east to west. The most widely distributed risk levels for regional high temperature, drought and their compound events were classified as high-risk, moderate-risk and extreme high-risk areas, accounting for 37.6%, 53.8% and 46.6% of Hubei Province’s total area, respectively. In the background of global warming and increasing frequency of extreme weather events, the probability and risk of regional extreme high temperature, drought and their compound events are expected to rise in eastern Hubei Province.

Key words: regional compound high temperature and drought events, risk, information diffusion method, Hubei Province

摘要：

为评估气候变化对农业的潜在影响并科学地制定应对策略，本文基于1994—2023年湖北省76个国家级气象观测站逐日气温、降水等资料，根据区域性高温天气过程等级划分标准及干旱过程监测评估方法，识别和分析了湖北省区域性高温、干旱事件及其复合事件的变化特征和农业致灾危险性。结果表明，湖北省区域性高温事件平均每年发生4.3次，总体呈增加趋势，其中61.2%的特强和强高温事件集中在7—8月；区域性干旱事件平均每年发生1.5次，2010年前呈减少趋势，之后转为增加，冬春季的发生频次略高于夏秋季；区域性高温干旱复合事件多发生在6—8月，2010年后发生频次明显增加。区域性高温和干旱事件的强度及其农业致灾危险性的空间分布基本相似，高温事件的高强度和高危险区主要位于湖北省东部，而低值区位于西南部；干旱事件则以中部偏东区域为高值区，并向周围递减；高温干旱复合事件的致灾危险性从东部向西部递减。区域性高温、干旱及其复合事件分布最广的危险等级区域分别为高危险区、中危险区和极高危险区，其面积分别占湖北省总面积的37.6%、53.8%、46.6%。在全球气候变暖和极端天气事件频发的背景下，湖北省东部区域性极端高温、干旱及其复合事件的发生概率及致灾危险性预计将会增加。

关键词: 区域性高温干旱复合事件, 危险性, 信息扩散方法, 湖北省

CLC Number:

P466

ZHANG Yucui, TAN Jianghong, YAN Caixia. Variability characteristics and risk assessment of regional high temperature, drought and their compound events in Hubei Province[J]. Journal of Arid Meteorology, 2024, 42(6): 825-835.

张玉翠, 谭江红, 闫彩霞. 湖北省区域性高温、干旱及其复合事件变化特征及危险性评估[J]. 干旱气象, 2024, 42(6): 825-835.

Figures/Tables 13

Fig.1 Topography and distribution of meteorological stations in Hubei Province

Tab.1 Comprehensive strength grades of high temperature of each station

j	Z_k百分位数取值区间
1	≥95%
2	[85%，95%）
3	[60%，85%）
4	<60%
5	非高温日

Tab.2 Grades of regional high temperature events

等级	RS
特强	1≤RS<2
强	2≤RS<3
中等	3≤RS<4
弱	RS≥4

Tab.3 Strength grades of meteorological drought based on MCI

干旱强度等级	MCI
无旱	-0.5<MCI
轻旱	-1.0<MCI≤-0.5
中旱	-1.5<MCI≤-1.0
重旱	-2.0<MCI≤-1.5
特旱	MCI≤-2.0

Tab.4 Strength grades of regional drought events in Hubei Province

等级	强度（Z_i）	Z_i百分位数取值区间
特强	Z_i≥16.59	≥95%
强	10.22≤Z_i<16.59	[80%，95%）
中等	6.26≤Z_i<10.22	[50%，80%）
弱	Z_i<6.26	Z_i<50%

Fig.2 Spatial distribution of multi-year average high temperature (a) and drought (b) days (Unit: d) in Hubei Province during 1994-2023

Fig.3 Interannual variation of average high temperature (a) and drought (b) days (Unit: d) with different grades in Hubei Province during 1994-2023

Fig.4 Interannual variation of occurrence frequency of regional high temperature events in Hubei Province during 1994-2023

Fig.5 Interannual variation of occurrence frequency of regional drought events in Hubei Province during 1994-2023

Fig. 6 Time sequence of high temperature years, drought years and their compound years in Hubei Province during 1994-2023

Fig.7 Spatial distribution of strength （a） and agricultural risk （b） for regional high temperature events in Hubei Province during 1994-2023

Fig.8 Spatial distribution of strength （a） and agricultural risk （b） for regional drought events in Hubei Province during 1994-2023

Fig.9 Spatial distribution of agricultural risk caused by regional compound high temperature and drought events in Hubei Province during 1994-2023

References 42

[1]	范进进, 秦鹏程, 史瑞琴, 等, 2022. 气候变化背景下湖北省高温干旱复合灾害变化特征[J]. 干旱气象, 40(5): 780-790. DOI
[2]	高歌, 黄大鹏, 赵珊珊, 2019. 基于信息扩散方法的中国台风灾害年月尺度风险评估[J]. 气象, 45(11): 1 600-1 610
[3]	高歌, 李莹, 陈涛, 等, 2023. 2004—2019年中国干旱多承灾体灾损风险特征评估[J]. 气象, 49(5): 611-623.
[4]	高洁, 肖红茹, 郭善云, 2023. 2022年夏季四川持续高温干旱特征及成因分析[J]. 沙漠与绿洲气象, 17(5): 118-126.
[5]	何慧根, 张驰, 吴遥, 等, 2023. 重庆夏季高温干旱特征及其对拉尼娜事件的响应[J]. 干旱气象, 41(6): 873-883.
[6]	姜颖迪, 王卫光, 魏佳, 等, 2022. 1961—2017年中国热浪特征及其对植被的影响[J]. 中国农村水利水电(3): 25-31.
[7]	姜雨彤, 侯爱中, 郝增超, 等, 2023a. 长江流域2022年高温干旱事件演变及历史对比[J]. 水力发电学报, 42(8): 1-9.
[8]	姜雨彤, 郝增超, 冯思芳, 等, 2023b. 长江与黄河流域复合高温干旱事件时空演变特征[J]. 水资源保护, 39(2): 70-77.
[9]	孔锋, 2020. 1961—2018年中国极端冷暖事件变化及其空间差异特征[J]. 水利水电技术, 51(9): 34-44.
[10]	李瑞英, 吕桂恒, 郝晓雷, 等, 2024. 鲁西南区域性高温干旱复合事件特征及危险性分析[J]. 中国农业气象, 45(6): 657-668.
[11]	李杨, 张雯, 陈云浩, 等, 2019. 基于自适应帕默尔指数的1961—2015年全国干旱时空特征分析[J]. 水利水电技术, 50(1): 43-51.
[12]	廖要明, 张存杰, 2017. 基于MCI的中国干旱时空分布及灾情变化特征[J]. 气象, 43(11): 1 402-1 409
[13]	刘素英, 张伟, 曾佩生, 等, 2022. 基于MCI指数的宜宾市干旱时空变化特征[J]. 高原山地气象研究, 42(增刊2): 118-123.
[14]	刘文英, 孙素琴, 朱星球, 等, 2024. 江西省区域性高温和干旱过程分析与评估[J]. 干旱气象, 42(2): 187-196. DOI
[15]	梅梅, 高歌, 李莹, 等, 2023. 1961—2022年长江流域高温干旱复合极端事件变化特征[J]. 人民长江, 54(2): 12-20.
[16]	钱潭锐, 逯家彤, 粟晓玲, 等, 2024. 基于复合事件指数的西北地区高温干旱复合事件风险评估[J]. 水资源与水工程学报, 35(1): 82-89.
[17]	全国气候与气候变化标准化技术委员会, 2017. 气象干旱等级:GB/T 20481—2017[S]. 北京: 中国标准出版社.
[18]	全国气候与气候变化标准化技术委员会, 2021. 区域性干旱过程监测评估方法:QX/T 597—2021[S]. 北京: 气象出版社.
[19]	全国气象防灾减灾标准化技术委员会, 2014. 区域性高温天气过程等级划分 QX/T 228—2014[S]. 北京: 气象出版社.
[20]	舒章康, 李文鑫, 张建云, 等, 2022. 中国极端降水和高温历史变化及未来趋势[J]. 中国工程科学, 24(5): 116-125. DOI
[21]	孙蕊, 邓彪, 王顺久, 等, 2023. 2022年夏季四川省区域性高温和干旱过程监测评估[J]. 高原山地气象研究, 43(2): 72-80.
[22]	王昀, 王丽娟, 陆晓娟, 等, 2023. 2023年上半年我国干旱的特征及其成因分析[J]. 干旱气象, 41(6): 884-896.
[23]	武新英, 郝增超, 张璇, 等, 2021. 中国夏季复合高温干旱分布及变异趋势[J]. 水利水电技术:中英文, 52(12): 90-98.
[24]	徐慧, 江善虎, 任立良, 等, 2024. 气候变化背景下赣江流域复合高温干旱事件时空演变特征[J]. 水利水电技术:中英文, 55(4): 1-11.
[25]	许丹, 龙俐, 张东海, 等, 2023. 基于MCI干旱综合指数的贵州省干旱时空分布及灾情变化特征[J]. 干旱气象, 41(6): 897-909.
[26]	余荣, 翟盘茂, 2021. 关于复合型极端事件的新认识和启示[J]. 大气科学学报, 44(5): 645-649.
[27]	俞昕, 张琪, 杨再强, 2023. 基于Copula函数分析华北地区年高温干旱复合事件发生特征[J]. 中国农业气象, 44(8): 695-706.
[28]	张强, 2022. 科学解读“2022年长江流域重大干旱”[J]. 干旱气象, 40(4): 545-548. DOI
[29]	张玮煊, 刁鹏, 巴音才次克, 等, 2023. 基于SPEI的开都河流域干旱时空演变特征分析[J]. 沙漠与绿洲气象, 17(6): 102-110.
[30]	中国气象局气候变化中心, 2024. 中国气候变化蓝皮书:2024[M]. 北京: 科学出版社.
[31]	CHU Z, GUO J P, ZHAO J F, 2017. Impacts of future climate change on agroclimatic resources in Northeast China[J]. Journal of Geographical Sciences, 27(9): 1 044-1 058
[32]	FENG S F, HAO Z C, ZHANG X, et al, 2019. Probabilistic evaluation of the impact of compound dry-hot events on global maize yields[J]. Science of the Total Environment, 689: 1 228-1 234
[33]	IPCC, 2022. Climate change 2021: The physical science basis[M]. Cambridge and New York: Cambridge University Press.
[34]	MAZDIYASNI O, AGHAKOUCHAK A, 2015. Substantial increase in concurrent droughts and heatwaves in the United States[J]. Proceedings of the National Academy of Sciences of the United States of America, 112(37): 11 484-11 489
[35]	MUKHERJEE S, MISHRA A K, 2021. Increase in compound drought and heatwaves in a warming world[J]. Geophysical Research Letters, 48(1): e2020GL090617. DOI: 10.1029/2020GL090617.
[36]	SHARMA S, MUJUMDAR P, 2017. Increasing frequency and spatial extent of concurrent meteorological droughts and heatwaves in India[J]. Scientific Reports, 7(1): 15582. DOI: 10.1038/s41598-017-15896-3. PMID
[37]	SHI Z T, JIA G S, ZHOU Y Y, et al, 2021. Amplified intensity and duration of heatwaves by concurrent droughts in China[J]. Atmospheric Research, 261: 105743. DOI: 10.1016/j.atmosres.2021.105743.
[38]	SUZUKI N, RIVERO R M, SHULAEV V, et al, 2014. Abiotic and biotic stress combinations[J]. The New Phytologist, 203(1): 32-43.
[39]	WANG R, LÜ G N, NING L, et al, 2021. Likelihood of compound dry and hot extremes increased with stronger dependence during warm seasons[J]. Atmospheric Research, 260: 105692. DOI: 10.1016/j.atmosres.2021.105692.
[40]	YU R, ZHAI P M, 2020. Changes in compound drought and hot extreme events in summer over populated Eastern China[J]. Weather and Climate Extremes, 30: 100295. DOI: 10.1016/j.wace.2020.100295.
[41]	ZHANG Y, HAO Z C, FENG S F, et al, 2022. Changes and driving factors of compound agricultural droughts and hot events in Eastern China[J]. Agricultural Water Management, 263: 107485. DOI: 10.1016/j.agwat.2022.107485.
[42]	ZHOU P, LIU Z Y, 2018. Likelihood of concurrent climate extremes and variations over China[J]. Environmental Research Letters, 13(9): 094023. DOI: 10.1088/1748-9326/aade9e.