2 ℃温升情景下中国气象干旱特征变化

doi:10.12118/j.issn.1000-6060.2022.546

Abstract

Abstract:

Drought is one of the most widespread and destructive natural hazards, causing severe impacts on agriculture, energy, society, and ecology. Global warming results in changes in regional precipitation and evapotranspiration patterns, leading to changes in drought characteristics. China is drought prone and is also seriously affected by climate change. Therefore, it is necessary to analyze the characteristics of future meteorological drought response to climate warming in China. In this study, using historical climate simulation data and future projection data from 18 climate models of the Coupled Model Intercomparison Project phase 6 (CMIP6), the 2 ℃ temperature rise scenario was determined by applying a time sampling approach, and the standardized precipitation evapotranspiration index (SPEI) based on the Penman-Monteith method was calculated at a 1-month time scale as the meteorological drought monitoring index. Based on SPEI, drought events were identified using the three-threshold run theory, and four drought-characteristic indicators (drought frequency, average drought duration, average drought intensity, and average drought peak) were extracted for China under the historical reference period and the 2 ℃ temperature rise scenario. Finally, changes in meteorological drought characteristics in China and its seven natural regions were analyzed under the 2 ℃ temperature rise scenario using the future drought-characteristic indicator values minus those of the historical drought-characteristic indicators. The results show clear spatial differentiation patterns in the four drought-characteristic indicators under the 2 ℃ temperature rise scenario. Drought frequency is high in the northwest desert region of China, and is high in the south and low in the north of the eastern monsoon region, while average drought duration, intensity, and peak values are high in the northwest and low in the southeast. From a national perspective, average future values of drought frequency, average drought duration, average drought intensity, and average drought peak are 1.72 times·a^-1, 2.46 months, 1.37, and 1.70 respectively under the 2 ℃ temperature rise scenario, representing increases of 0.17 times·a^-1, 0.27 months, 0.14, and 0.25, respectively, compared with the historical reference period. From a regional perspective, the average values of drought frequency, average drought intensity, and average drought peak increase in all regions, while the average value of average drought duration shows a decrease only in the northeast humid/semi-humid temperate region. The region with the largest increases in values of the four drought-characteristic indicators is the northwest desert region. In summary, based on the results of the multi-model ensemble mean from the 18 CMIP6 models, we predict that more frequent and severe droughts will occur in China, and especially in northwest China, under the 2 ℃ temperature rise scenario. This prediction can serve as a warning in terms of future drought management, and the study can provide a basis for drought prevention and response decision-making in the global warming context.

Key words: meteorological drought, global warming, 2 ℃ temperature rise scenario, CMIP6, China

LU Dongyan, ZHU Xiufang, LIU Tingting, ZHANG Shizhe. Changes in meteorological drought characteristics in China under the 2 ℃ temperature rise scenario[J].Arid Land Geography, 2023, 46(8): 1227-1237.

Figures/Tables 7

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References 37

[1]	Rogelj J, den Elzen M, Höhne N, et al. Paris Agreement climate proposals need a boost to keep warming well below 2 ℃[J]. Nature, 2016, 534(7609): 631-639. doi: 10.1038/nature18307
[2]	IPCC. Climate change 2021:The physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[M]. Cambridge: Cambridge University Press, 2023.
[3]	翟盘茂, 刘静. 气候变暖背景下的极端天气气候事件与防灾减灾[J]. 中国工程科学, 2012, 14(9): 55-63.
	[Zhai Panmao, Liu Jing. Extreme weather/climate events and disaster prevention and mitigation under global warming background[J]. Strategic Study of CAE, 2012, 14(9): 55-63.]
[4]	尹晗, 李耀辉. 我国西南干旱研究最新进展综述[J]. 干旱气象, 2013, 31(1): 182-193. doi: 10.11755/j.issn.1006-7639(2013)-01-0182
	[Yin Han, Li Yaohui. Summary of advance on drought study in southwest China[J]. Journal of Arid Meteorology, 2013, 31(1): 182-193.] doi: 10.11755/j.issn.1006-7639(2013)-01-0182
[5]	刘宪锋, 朱秀芳, 潘耀忠, 等. 农业干旱监测研究进展与展望[J]. 地理学报, 2015, 70(11): 1835-1848. doi: 10.11821/dlxb201511012
	[Liu Xianfeng, Zhu Xiufang, Pan Yaozhong, et al. Agricultural drought monitor: Progress, challenges and prospect[J]. Acta Geographica Sinica, 2015, 70(11): 1835-1848.] doi: 10.11821/dlxb201511012
[6]	中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. GB/T 20481-2017. 气象干旱等级[S]. 北京: 中国标准出版社, 2017.
	[General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China, Standardization Administration of the People’s Republic of China. GB/T 20481-2017. Grades of meteorological drought[S]. Beijing: Standards Press of China, 2017.]
[7]	王劲松, 李耀辉, 王润元, 等. 我国气象干旱研究进展评述[J]. 干旱气象, 2012, 30(4): 497-508.
	[Wang Jinsong, Li Yaohui, Wang Runyuan, et al. Preliminary analysis on the demand and review of progress in the field of meteorological drought research[J]. Journal of Arid Meteorology, 2012, 30(4): 497-508.]
[8]	中国水旱灾害防御公报编写组. 《中国水旱灾害防御公报2020》概要[J]. 中国防汛抗旱, 2021, 31(11): 26-32.
	[Compilation group of China Flood and Drought Disaster Prevention Bulletin. Summary of China flood and drought disaster prevention bulletin 2020[J]. China Flood & Drought Management, 2021, 31(11): 26-32.]
[9]	Yu M, Li Q, Hayes M J, et al. Are droughts becoming more frequent or severe in China based on the standardized precipitation evapotranspiration index: 1951—2010?[J]. International Journal of Climatology, 2014, 34(3): 545-558. doi: 10.1002/joc.3701
[10]	李忆平, 李耀辉. 气象干旱指数在中国的适应性研究进展[J]. 干旱气象, 2017, 35(5): 709-723. doi: 10.11755/j.issn.1006-7639(2017)-05-0709
	[Li Yiping, Li Yaohui. Advances in adaptability of meteorological drought indices in China[J]. Journal of Arid Meteorology, 2017, 35(5): 709-723.] doi: 10.11755/j.issn.1006-7639(2017)-05-0709
[11]	Palmer W C. Meteorological drought[M]. Washington, DC: US Department of Commerce, Weather Bureau, 1965.
[12]	Mckee T B, Doesken N J, Kleist J. The relationship of drought frequency and duration to time scales[C]//Proceedings of the 8^th Conference on Applied Climatology. Boston, MA: American Meteorological Society, 1993: 179-183.
[13]	Vicente-Serrano S M, Beguería S, López-Moreno J I. A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index[J]. Journal of Climate, 2010, 23(7): 1696-1718. doi: 10.1175/2009JCLI2909.1
[14]	王东, 张勃, 安美玲, 等. 基于SPEI的西南地区近53 a干旱时空特征分析[J]. 自然资源学报, 2014, 29(6): 1003-1016. doi: 10.11849/zrzyxb.2014.06.009
	[Wang Dong, Zhang Bo, An Meiling, et al. Temporal and spatial distributions of drought in southwest China over the past 53 years based on standardized precipitation evapotranspiration index[J]. Journal of Natural Resources, 2014, 29(6): 1003-1016.] doi: 10.11849/zrzyxb.2014.06.009
[15]	廖要明, 张存杰. 基于MCI的中国干旱时空分布及灾情变化特征[J]. 气象, 2017, 43(11): 1402-1409.
	[Liao Yaoming, Zhang Cunjie. Spatio-temporal distribution characteristics and disaster change of drought in China based on meteorological drought composite index[J]. Meteorological Monthly, 2017, 43(11): 1402-1409.]
[16]	费振宇, 孙宏巍, 金菊良, 等. 近50年中国气象干旱危险性的时空格局探讨[J]. 水电能源科学, 2014, 32(12): 5-10.
	[Fei Zhenyu, Sun Hongwei, Jin Juliang, et al. Temporal and spatial patterns of meteorological drought hazard in China for recent 50 years[J]. Water Resources and Power, 2014, 32(12): 5-10.]
[17]	Su B, Huang J, Fischer T, et al. Drought losses in China might double between the 1.5 ℃ and 2.0 ℃ warming[J]. Proceedings of the National Academy of Sciences of the United States of America, 2018, 115(42): 10600-10605.
[18]	Ma Z, Sun P, Zhang Q, et al. The characteristics and evaluation of future droughts across China through the CMIP6 multi-model ensemble[J]. Remote sensing (Basel, Switzerland), 2022, 14(1097): 1097, doi: 10.3390/rs14051097. doi: 10.3390/rs14051097
[19]	袁文平, 周广胜. 干旱指标的理论分析与研究展望[J]. 地球科学进展, 2004, 19(6): 982-991. doi: 10.11867/j.issn.1001-8166.2004.06.0982
	[Yuan Wenping, Zhou Guangsheng. Theoretical study and research prospect on drought indices[J]. Advances in Earth Science, 2004, 19(6): 982-991.] doi: 10.11867/j.issn.1001-8166.2004.06.0982
[20]	赵松乔. 中国综合自然地理区划的一个新方案[J]. 地理学报, 1983(1): 1-10. doi: 10.11821/xb198301001
	[Zhao Songqiao. A new scheme for comprehensive physical regionalization in China[J]. Acta Geographica Sinica, 1983(1): 1-10.] doi: 10.11821/xb198301001
[21]	Ayantobo O O, Li Y, Song S, et al. Probabilistic modelling of drought events in China via 2-dimensional joint Copula[J]. Journal of Hydrology, 2018, 559: 373-391. doi: 10.1016/j.jhydrol.2018.02.022
[22]	Zhang G, Su X, Singh V P, et al. Appraising standardized moisture anomaly index (SZI) in drought projection across China under CMIP6 forcing scenarios[J]. Journal of Hydrology: Regional Studies, 2021, 37: 100898, doi: 10.1016/j.ejrh.2021.100898. doi: 10.1016/j.ejrh.2021.100898
[23]	Yao N, Li L, Feng P, et al. Projections of drought characteristics in China based on a standardized precipitation and evapotranspiration index and multiple GCMs[J]. Science of the Total Environment, 2020, 704: 135245, doi: 10.1016/j.scitotenv.2019.135245. doi: 10.1016/j.scitotenv.2019.135245
[24]	张丽霞, 陈晓龙, 辛晓歌. CMIP6情景模式比较计划(ScenarioMIP)概况与评述[J]. 气候变化研究进展, 2019, 15(5): 519-525.
	[Zhang Lixia, Chen Xiaolong, Xin Xiaoge. Short commentary on CMIP6 scenario model intercomparison project (ScenarioMIP)[J]. Climate Change Research, 2019, 15(5): 519-525.]
[25]	IPCC. Global warming of 1.5 ℃: IPCC special report on impacts of global warming of 1.5 ℃ above pre-industrial levels in context of strengthening response to climate change, sustainable development, and efforts to eradicate poverty[M]. Cambridge: Cambridge University Press, 2022.
[26]	James R, Washington R, Schleussner C, et al. Characterizing half-a-degree difference: A review of methods for identifying regional climate responses to global warming targets[J]. WIREs Climate Change, 2017, 8(2): e457, doi: 10.1002/wcc.457. doi: 10.1002/wcc.457
[27]	王林, 陈文. 标准化降水蒸散指数在中国干旱监测的适用性分析[J]. 高原气象, 2014, 33(2): 423-431. doi: 10.7522/j.issn.1000-0534.2013.00048
	[Wang Lin, Chen Wen. Applicability analysis of standardized precipitation evapotranspiration index in drought monitoring in China[J]. Plateau Meteorology, 2014, 33(2): 423-431.] doi: 10.7522/j.issn.1000-0534.2013.00048
[28]	Beguería S, Vicente-Serrano S M, Reig F, et al. Standardized precipitation evapotranspiration index (SPEI) revisited: Parameter fitting, evapotranspiration models, tools, datasets and drought monitoring[J]. International Journal of Climatology, 2014, 34(10): 3001-3023. doi: 10.1002/joc.2014.34.issue-10
[29]	Su B, Huang J, Mondal S K, et al. Insight from CMIP6 SSP-RCP scenarios for future drought characteristics in China[J]. Atmospheric Research, 2021, 250: 105375, doi: 10.1016/j.atmosres.2020.105375. doi: 10.1016/j.atmosres.2020.105375
[30]	张世喆, 朱秀芳, 刘婷婷, 等. 基于多维Copula的中国干旱特征及危险性分析[J]. 干旱区地理, 2022, 45(2): 333-345.
	[Zhang Shizhe, Zhu Xiufang, Liu Tingting, et al. Drought characteristics and risk hazard in China based on multidimensional Copula model[J]. Arid Land Geography, 2022, 45(2): 333-345.]
[31]	Xu Y, Zhang X, Hao Z, et al. Projections of future meteorological droughts in China under CMIP6 from a three-dimensional perspective[J]. Agricultural Water Management, 2021, 252: 106849, doi: 10.1016/j.agwat.2021.106849. doi: 10.1016/j.agwat.2021.106849
[32]	Song Z, Xia J, She D, et al. Assessment of meteorological drought change in the 21^st century based on CMIP6 multi-model ensemble projections over mainland China[J]. Journal of Hydrology, 2021, 601: 126643, doi: 10.1016/j.jhydrol.2021.126643. doi: 10.1016/j.jhydrol.2021.126643
[33]	姜萍, 丁文广, 肖静, 等. 新疆植被NPP及其对气候变化响应的海拔分异[J]. 干旱区地理, 2021, 44(3): 849-857.
	[Jiang Ping, Ding Wenguang, Xiao Jing, et al. Altitudinal difference of vegetation NPP and its response to climate change in Xinjiang[J]. Arid Land Geography, 2021, 44(3): 849-857.]
[34]	姚旭阳, 张明军, 张宇, 等. 中国西北地区气候转型的新认识[J]. 干旱区地理, 2022, 45(3): 671-683.
	[Yao Xuyang, Zhang Mingjun, Zhang Yu, et al. New insights into climate transition in northwest China[J]. Arid Land Geography, 2022, 45(3): 671-683.]
[35]	Chen L, Frauenfeld O W. A comprehensive evaluation of precipitation simulations over China based on CMIP5 multimodel ensemble projections[J]. Journal of Geophysical Research: Atmospheres, 2014, 119(10): 5767-5786. doi: 10.1002/2013JD021190
[36]	Tian J, Zhang Z, Ahmed Z, et al. Projections of precipitation over China based on CMIP6 models[J]. Stochastic Environmental Research and Risk Assessment, 2021, 35(4): 831-848. doi: 10.1007/s00477-020-01948-0
[37]	Ukkola A M, De Kauwe M G, Roderick M L, et al. Robust future changes in meteorological drought in CMIP6 projections despite uncertainty in precipitation[J]. Geophysical Research Letters, 2020, 47(11): e2020GL087820, doi: 10.1029/2020GL087820. doi: 10.1029/2020GL087820

序号	模式名称	机构简称	国家	经纬向格点数
1	ACCESS-CM2	CSIRO-ARCCSS	澳大利亚	192×144
2	ACCESS-ESM1-5	CSIRO	澳大利亚	192×145
3	CanESM5	CCCma	加拿大	128×64
4	CAS-ESM2-0	CAS	中国	256×128
5	CMCC-ESM2	CMCC	意大利	288×192
6	EC-Earth3	EC-Earth-Consortium	欧盟	512×256
7	EC-Earth3-Veg	EC-Earth-Consortium	欧盟	512×256
8	EC-Earth3-Veg-LR	EC-Earth-Consortium	欧盟	320×160
9	FGOALS-g3	CAS	中国	180×80
10	FIO-ESM-2-0	FIO-QLNM	中国	288×192
11	GFDL-ESM4	NOAA-GFDL	美国	288×180
12	INM-CM4-8	INM	俄罗斯	180×120
13	INM-CM5-0	INM	俄罗斯	180×120
14	IPSL-CM6A-LR	IPSL	法国	144×143
15	MIROC6	MIROC	日本	256×128
16	MPI-ESM1-2-HR	DKRZ	德国	384×192
17	MPI-ESM1-2-LR	MPI-M	德国	192×96
18	MRI-ESM2-0	MRI	日本	320×160

Changes in meteorological drought characteristics in China under the 2 ℃ temperature rise scenario

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