《巴黎协定》排放情景下中亚地区降水变化响应

doi:10.11821/dlxb202001003

摘要/Abstract

摘要：

为了应对全球气候变化,《巴黎协定》提出各国将以“国家自主贡献”（INDC）的方式参与全球温室气体减排行动,而在“国家自主贡献”排放目标情景下区域降水变化的格局和特征尚不清楚。中亚地区位于欧亚大陆腹地,是中国“一带一路”倡议发展的关键地区。本文研究了中亚地区的降水变化对全球INDC排放的响应,基于参与国际耦合模式比较计划第五阶段（CMIP5）的33个全球气候模式的模拟。结果表明：在INDC目标情景下,到21世纪末中亚地区的平均年降水量相对现代水平（1985—2005年平均）增加10.6%（4.6%~13.3%）,其中高纬度地区的响应大于低纬度地区。进一步看,中亚地区极端强降水事件随着气候变暖而持续增加,但极端持续干期事件在不同区域呈现不同的变化趋势。考虑极端降水事件相关风险,极端强降水和持续干期事件的人口暴露度在中亚大部分区域都增加,将全球温升控制在较低水平（如2.0 ℃或1.5 ℃）可显著降低暴露度。以上结果有助于增进对未来极端气候事件风险的认识,为中亚这一生态脆弱地区的气候变化的减缓与适应政策提供参考。

关键词: 国家自主贡献（INDC）, 降水, 极端事件, 持续干期, 暴露度

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

王芳, 张晋韬. 《巴黎协定》排放情景下中亚地区降水变化响应[J]. 地理学报, 2020, 75(1): 25-40.

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.

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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