《巴黎协定》排放情景下中亚地区降水变化响应

doi:10.11821/dlxb202001003

Abstract

Abstract:

To limit global mean warming to below 2.0 ℃ in accordance with the Paris Agreement, countries submitted their Intended Nationally Determined Contributions (INDC) for emission reductions. Those emissions will be the key determinant to the future climate change impacts. However, it remains unclear what the resulting changes in the regional precipitation and its extremes would be under the INDC pledges. Here, we analyze the response of precipitation in Central Asia to emission scenarios under warming resulting from the INDC pledges (as of May 2019), based on an ensemble of comprehensive Earth System Models from the Coupled Climate Model Intercomparison Project Phase 5 (CMIP5). Our results show an increase in the mean precipitation in Central Asia by the end of the 21st century by 10.6% (4.6%-13.3%) for INDC-pledge scenario. However, spatial heterogeneity of precipitation changes reflects the complexity of precipitation responses in future climate projections. Furthermore, heavy precipitation events will strengthen with the enhanced warming, but the trend of dry spell events increases or decreases in different regions. Considering the impacts of precipitation-related extremes, we find that the projected population exposure to heavy rainfall and dry spell events will significantly increase in most Central Asian regions. Limiting warming to lower levels (such as 2.0 ℃ or 1.5 ℃) would reduce the population exposure to heavy rainfall, thereby avoiding impacts associated with more intense precipitation extremes. These results contribute to an improved understanding of future risk from climate extremes, which is paramount for mitigation and adaptation activities for Central Asia, an ecologically fragile area.

Key words: INDC pledge, precipitation, extreme events, dry spells, extreme precipitation exposure

WANG Fang, ZHANG Jintao. Response of precipitation change in Central Asia to emission scenarios consistent with the Paris Agreement[J].Acta Geographica Sinica, 2020, 75(1): 25-40.

Figures/Tables 12

Fig. 1

Tab. 1

Tab. 2

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Tab. 3

Fig. 8

Fig. 9

References 43

[1]	UNFCCC. Adoption of the Paris Agreement: Proposal by the President. Geneva, 2015.
[2]	UNFCCC. Synthesis Report on the Aggregate Effect of the Intended Nationally Determined Contributions. Paris, 2015.
[3]	Gupta S, Tirpak D, Burger N , et al. Policies, instruments, and co-operative arrangements//Metz O B, Bosch P, Dave R, et al. Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK, and New York, USA: Cambridge University Press, 2007: 745-807.
[4]	Li Donghuan, Zou Liwei, Zhou Tianjun . Changes of extreme indices over China in response to 1.5 ℃ global warming projected by a regional climate model. Advances in Earth Science, 2017,32(4):446-457.
	[ 李东欢, 邹立维, 周天军 . 全球1.5 ℃温升背景下中国极端事件变化的区域模式预估. 地球科学进展, 2017,32(4):446-457.]
[5]	Hao Ying, Ma Jingjin, An Jingjin , et al. Projected changes in climate and river discharge in the Chaobai River Basin under 1.5 ℃ and 2.0 ℃ global warming. Climate Change Research, 2018,14(3):237-246.
	[ 郝莹, 马京津, 安晶晶 , 等. 全球1.5 ℃和2.0 ℃温升下潮白河流域气候和径流量变化预估. 气候变化研究进展, 2018,14(3):237-246.]
[6]	Schleussner C F, Lissner T K, Fischer E M , et al. Differential climate impacts for policy-relevant limits to global warming: The case of 1.5 ℃ and 2 ℃. Earth System Dynamics, 2016,7(2):327-351.
[7]	Mitchell D, Achutarao K, Allen M , et al. Half a degree additional warming, prognosis and projected impacts (HAPPI): Background and experimental design. Geoscientific Model Development, 2017,10(2):571-583.
[8]	Zhang W, Zhou T, Zou L , et al. Reduced exposure to extreme precipitation from 0.5 ℃ less warming in global land monsoon regions. Nature Communications, 2018,9(1):3153.
[9]	Sanderson B M O'neill B C Tebaldi C . What would it take to achieve the Paris temperature targets? Geophysical Research Letters, 2016,43(13):7133-7142.
[10]	Rogelj J, Den Elzen M, Höhne N , et al. Paris Agreement climate proposals need a boost to keep warming well below 2 ℃. Nature, 2016,534:631-639.
[11]	UNEP. The Emissions Gap Report. Nairobi, 2017.
[12]	Fawcett A A, Iyer G C, Clarke L E , et al. Climate Policy. Can Paris pledges avert severe climate change? Science, 2015,350(6265):1168-1169.
[13]	Lioubimtseva E, Cole R, Adams J M , et al. Impacts of climate and land-cover changes in arid lands of Central Asia. Journal of Arid Environments, 2005,62(2):285-308.
[14]	Zhang M, Chen Y, Shen Y , et al. Tracking climate change in Central Asia through temperature and precipitation extremes. Journal of Geographical Sciences, 2019,29(1):3-28.
[15]	Deng Haijun, Chen Yaning . The glacier and snow variations and their impact on water resources in mountain regions: A case study in Tianshan Mountains of Central Asia. Acta Geographica Sinica, 2018,73(7):1309-1323.
	[ 邓海军, 陈亚宁 . 中亚天山山区冰雪变化及其对区域水资源的影响. 地理学报, 2018,73(7):1309-1323.]
[16]	Li Xinwu, Zhang Li, Guo Huadong , et al. Space recognition of eco-environment global change response of arid and semi-arid region of the Silk Road Economic Belt. Bulletin of Chinese Academy of Sciences, 2016,31(5):559-566.
	[ 李新武, 张丽, 郭华东 , 等. “丝绸之路经济带”干旱—半干旱区生态环境全球变化响应的空间认知. 中国科学院院刊, 2016,31(5):559-566.]
[17]	Han Qifei, Lu Yan, Li Chaofan . Impact of climate change on grassland carbon cycling in Central Asia. Arid Land Geography, 2018,41(6):1351-1357.
	[ 韩其飞, 陆研, 李超凡 . 气候变化对中亚草地生态系统碳循环的影响研究. 干旱区地理, 2018,41(6):1351-1357.]
[18]	Chen Y, Li Z, Li W , et al. Water and ecological security: Dealing with hydroclimatic challenges at the heart of China's Silk Road. Environmental Earth Sciences, 2016,75(10):881.
[19]	Howard K W F, Howard K K . The new "Silk Road Economic Belt" as a threat to the sustainable management of Central Asia's transboundary water resources. Environmental Earth Sciences, 2016,75(11):976.
[20]	Li P, Qian H, Zhou W . Finding harmony between the environment and humanity: An introduction to the thematic issue of the Silk Road. Environmental Earth Sciences, 2017,76(3):105.
[21]	IPCC. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK, and New York, USA: Cambridge University Press, 2014.
[22]	IPCC. Global Warming of 1.5 ℃. Cambridge, UK, and New York, USA: Cambridge University Press, 2018.
[23]	UNFCCC. National Inventory Submissions, 2019.
[24]	Wang F, Tokarska K B, Zhang J , et al. Climate warming in response to emission reductions consistent with the Paris Agreement. Advances in Meteorology, 2018,2018:1-9.
[25]	Addressing Global Warming. https://climateactiontracker.org/global/temperatures/.
[26]	Wang F, Ge Q, Chen D , et al. Global and regional climate responses to national-committed emission reductions under the Paris agreement. Geografiska Annaler: Series A, Physical Geography, 2018,100(3):240-253.
[27]	Taylor K E, Stouffer R J, Meehl G A . An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 2011,93(4):485-498.
[28]	Reichler T, Kim J . How well do coupled models simulate today's climate? Bulletin of the American Meteorological Society, 2008,89(3):303-312.
[29]	Pierce D W, Barnett T P, Santer B D , et al. Selecting global climate models for regional climate change studies. Proceedings of the National Academy of Sciences, 2009,106(21):8441-8446.
[30]	Ziese M, Rauthe-Schöch A, Becker A , et al. GPCC Full Data Daily Version. 2018 at 10°: Daily Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historic Data [DB/OL]. Doi: 10.5676/DWD_GPCC/FD_D_V2018_100.
[31]	Robert V, Andreas G, Stefan S , et al. The European climate under a 2 ℃ global warming. Environmental Research Letters, 2014,9(3):034006.
[32]	Huang J, Yu H, Dai A , et al. Drylands face potential threat under 2 ℃ global warming target. Nature Climate Change, 2017,7:417-422.
[33]	Zhang X, Alexander L, Hegerl G C , et al. Indices for monitoring changes in extremes based on daily temperature and precipitation data. Wiley Interdisciplinary Reviews: Climate Change, 2011,2(6):851-870.
[34]	Dai A . Increasing drought under global warming in observations and models. Nature Climate Change, 2012,3:52-58.
[35]	Prudhomme C, Giuntoli I, Robinson E L , et al. Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment. Proceedings of the National Academy of Sciences, 2014,111(9):3262-3267.
[36]	Hirabayashi Y, Mahendran R, Koirala S , et al. Global flood risk under climate change. Nature Climate Change, 2013,3:816-821.
[37]	Lavell A, Oppenheimer M, Diop C , et al. Climate change: New dimensions in disaster risk, exposure, vulnerability, and resilience// Field C B, Barros V, Stocker T F, et al. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge, UK, and New York, USA: Cambridge University Press, 2012: 25-64.
[38]	Cox D R, Hinkley D V . Theoretical Statistics. London: Chapman and Hall, 1974: 511.
[39]	Jones B, O'neill B C . Spatially explicit global population scenarios consistent with the shared socioeconomic pathways. Environmental Research Letters, 2016,11(8):084003.
[40]	Vuuren D P V, Edmonds J, Kainuma M , et al. The representative concentration pathways: An overview. Climatic Change, 2011,109(1-2):5-31.
[41]	Hoegh-Guldberg O, Jacob D, Taylor M , et al. Impacts of 1.5 ℃ global warming on natural and human systems//Masson-Delmotte V, Zhai P, Pörtner H O, et al. Global warming of 1.5 ℃. An IPCC Special Report on the Impacts of Global Warming of 1.5 ℃ above Pre-industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty. Cambridge, UK, and New York, USA: Cambridge University Press, 2018.
[42]	Sanderson B M, Xu Y, Tebaldi C , et al. Community climate simulations to assess avoided impacts in 1.5 and 2  ℃ futures. Earth System Dynamics, 2017,8(3):827-847.
[43]	Jiang D, Sui Y, Lang X . Timing and associated climate change of a 2 ℃ global warming. International Journal of Climatology, 2016,36(14):4512-4522.

极值指数名称	定义	单位
极端强降水量(Rx5day)	连续5 d最大降水量	mm
持续干期(CDD)	最长连续无雨日(日降水< 1 mm)数	d

模式名称	机构名称	国家	水平分辨率 (全球网格数)
ACCESS1-0	澳大利亚联邦科学与工业研究组织/气象局	澳大利亚	192×145
ACCESS1-3	澳大利亚联邦科学与工业研究组织/气象局	澳大利亚	192×145
BCC-CSM1-1	中国气象局国家气候中心	中国	128×64
BCC-CSM1-1-m	中国气象局国家气候中心	中国	320×160
BNU-ESM	北京师范大学	中国	128×64
CanESM2	加拿大气候模拟与分析中心	加拿大	128×64
CCSM4	美国国家大气研究中心	美国	288×192
CESM1-BGC	美国国家大气研究中心	美国	288×192
CMCC-CESM	意大利地中海气候中心	意大利	96×96
CMCC-CM			480×240
CMCC-CMS			192×96
CNRM-CM5	法国气象研究中心	法国	256×128
CSIRO-Mk3-6-0	澳大利亚联邦科学与工业研究组织/昆士兰洲气候变化研究中心	澳大利亚	192×96
EC-EARTH	EC-EARTH研究联合体	荷兰/冰岛	320×160
FGOALS-g2	中国科学院大气物理研究所	中国	128×60
FGOALS-s2	中国科学院大气物理研究所		128×108
GFDL-CM3	美国地球物理流体动力学实验室	美国	144×90
GFDL-ESM2G			144×90
GFDL-ESM2M			144×90
HadGEM2-CC	英国哈德莱气象中心	英国	192×145
HadGEM2-ES	英国哈德莱气象中心	英国	192×145
INM-CM4	俄罗斯科学院计算数学研究所	俄罗斯	180×120
IPSL-CM5A-LR	法国Pierre Simon物理学研究所	法国	96×96
IPSL-CM5A-MR			144×143
IPSL-CM5B-LR			96×96
MIROC5	日本海洋地球科学与技术局、大气海洋研究所和国家环境变化研究所	日本	256×128
MIROC-ESM			128×64
MIROC-ESM-CHEM			128×64
MPI-ESM-LR	德国普朗克气象研究所	德国	192×96
MPI-ESM-MR	德国普朗克气象研究所	德国	192×96
MRI-CGCM3	日本气象研究所	日本	320×160
MRI-ESM1	日本气象研究所	日本	320×160
NorESM1-M	挪威气候中心	挪威	144×96

极值指数	目标情景	KAZ	UZB	TKM	KGZ	TJK
Rx5day	1.5 ℃温升	1.68	1.87	1.77	1.59	1.75
	2.0 ℃温升	2.09	1.94	1.81	1.96	2.02
	INDC	2.96	2.13	2.27	2.59	2.74
	1.5 ℃温升	1.28	1.01	1.03	1.01	1.20
CDD	2.0 ℃温升	1.41	1.10	1.34	1.32	1.33
	INDC	1.33	1.27	1.61	1.64	1.48

Response of precipitation change in Central Asia to emission scenarios consistent with the Paris Agreement

RichHTML

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

Figures/Tables 12

References 43

Related Articles 15

Metrics

Comments

[1]	WEN Qingzhi, SUN Peng, ZHANG Qiang, YAO Rui. A multi-scalar drought index for global warming: The non-stationary standardized precipitation evaporation index (NSPEI) and spatio-temporal patterns of future drought in China [J]. Acta Geographica Sinica, 2020, 75(7): 1465-1482.
[2]	LI Shuangshuang, WANG Chengbo, YAN Junping, LIU Xianfeng. Variability of the event-based extreme precipitation in the south and north Qinling Mountains [J]. Acta Geographica Sinica, 2020, 75(5): 989-1007.
[3]	HE Liye, CHENG Shanjun, MA Ning, GUO Jun. Intraseasonal evolution of the key areas of precipitation in the Haihe River Basin and quantitative analysis of its associated atmospheric circulation during summer [J]. Acta Geographica Sinica, 2020, 75(1): 41-52.
[4]	LIU Xiaoqiong, WU Zezhou, LIU Yansui, ZHAO Xinzheng, RUI Yang, ZHANG Jian. Spatial-temporal characteristics of precipitation from 1960 to 2015 in the Three Rivers' Headstream Region, Qinghai, China [J]. Acta Geographica Sinica, 2019, 74(9): 1803-1820.
[5]	ZENG Suikang,YONG Bin. Evaluation of the GPM-based IMERG and GSMaP precipitation estimates over the Sichuan region [J]. Acta Geographica Sinica, 2019, 74(7): 1305-1318.
[6]	LU Fuzhi,LU Huayu. A high-resolution grid dataset of air temperature and precipitation for Qinling-Daba Mountains in central China and its implications for regional climate [J]. Acta Geographica Sinica, 2019, 74(5): 875-888.
[7]	YANG Jiawei, CHEN Hua, HOU Yukun, ZHAO Ying, CHEN Qihui, XU Chongyu, CHEN Jie. A method to identify the drought-flood transition based on the meteorological drought index [J]. Acta Geographica Sinica, 2019, 74(11): 2358-2370.
[8]	XIN Rui, DUAN Keqin. Numerical simulation and spatial distribution of summer precipitation in the Qinling Mountains [J]. Acta Geographica Sinica, 2019, 74(11): 2329-2341.
[9]	YIN Zhan'e,TIAN Pengfei,CHI Xiaoxiao. Multi-scenario-based risk analysis of precipitation extremes in China during the past 60 years (1951-2011) [J]. Acta Geographica Sinica, 2018, 73(3): 405-413.
[10]	ZHU Xiudi, ZHANG Qiang, SUN Peng. Effects of urbanization on spatio-temporal distribution of precipitations in Beijing and its related causes [J]. Acta Geographica Sinica, 2018, 73(11): 2086-2104.
[11]	ZHANG Xiaodong,ZHU Wenbo,ZHANG Jingjing,ZHU Lianqi,ZHAO Fang,CUI Yaoping. Phenology of forest vegetation and its response to climate change in the Funiu Mountains [J]. Acta Geographica Sinica, 2018, 73(1): 41-53.
[12]	Dongliang ZHANG, Bo LAN, Yunpeng YANG. Comparison of precipitation variations at different time scales in the northern and southern Altai Mountains [J]. Acta Geographica Sinica, 2017, 72(9): 1569-1579.
[13]	Yuanyaun WANG, Zheng GUO, Guicai LI, Zhaodi GUO. Precipitation estimation and analysis of the Three Gorges Dam region (1979-2014) by combining gauge measurements and MSWEP with generalized additive model [J]. Acta Geographica Sinica, 2017, 72(7): 1207-1220.
[14]	Shaohong WU, Tao PAN, Yanhua LIU, Haoyu DENG, Kewei JIAO, Qing LU, Aiqing FENG, Xiliu YUE, Yunhe YIN, Dongsheng ZHAO, Jiangbo GAO. Comprehensive climate change risk regionalization of China [J]. Acta Geographica Sinica, 2017, 72(1): 3-17.
[15]	Xuemei LIU, Mingjun ZHANG, Shengjie WANG, Jie WANG, Peipei ZHAO, Panpan ZHOU. Diurnal variation of summer precipitation and its influencing factors of the Qilian Mountains during 2008-2014 [J]. Acta Geographica Sinica, 2016, 71(5): 754-767.