不同升温阈值下中国地区极端气候事件变化预估

陈晓晨; 徐影; 姚遥

doi:10.3878/j.issn.1006-9895.1502.14224

不同升温阈值下中国地区极端气候事件变化预估

doi: 10.3878/j.issn.1006-9895.1502.14224

1.
湖南省气候中心, 长沙 410118
2.
中国气象局国家气候中心, 北京 100081;中国气象局气候研究开放实验室, 北京 100081
3.
清华大学地球系统科学研究中心, 北京 100084

基金项目: 公益性行业(气象)科研专项GYHY201306019,国家科技支撑项目2014BAJ01B01,中国气象局气候变化专项CCSF201525,中国瑞士合作项目ACCCⅡ

计量
- 文章访问数: 2242
- HTML全文浏览量: 1
- PDF下载量: 3135
- 被引次数: 0
出版历程
- 收稿日期: 2014-07-09
- 修回日期: 2015-02-05

Changes in Climate Extremes over China in a 2℃, 3℃, and 4℃ Warmer World

1.
Hunan Climate Center, Changsha 410118
2.
National Climate Center, Beijing 100081;Laboratory for Climate Studies, China Meteorological Administration, Beijing 100081
3.
Center for Earth System Science, Tsinghua University, Beijing 100084

摘要

摘要: 本文基于耦合模式比较计划第五阶段(CMIP5)的18个全球气候模式的模拟结果,预估了全球平均气温在不同典型浓度路径(RCPs)下达到2℃、3℃和4℃阈值时,中国地区气温和降水的变化,并采用了具有稳定统计意义的27个极端气候指标定量评估了全球平均气温达到不同阈值时,中国地区极端气候事件的可能变化。结果表明,未来我国平均气温增幅将高于全球平均增暖,极端暖事件(如暖夜、暖昼、热带夜)明显增多,达到4℃阈值时,暖夜指数相比参考时段增加约49.9%。极端冷事件(如冷夜、冷昼、霜冻)减少。随全球气温升高,中国北方平均降水增多。在不同升温阈值下,中国地区降水的极端性都体现出增强的趋势,强降水事件发生频率(如中雨日数、大雨日数)和强度(如五日最大降水量、极端强降水量)都明显增加。随升温阈值的升高,这些变化幅度更大,在 RCP8.5 情景下全球升温 3℃和4℃时,中国平均五日最大降水分别增加 12.5mm和17.0mm。我国西南地区极端降水强度的增幅高于其他地区。
- 阈值 /
- 极端气候 /
- 预估
Abstract: Due to human-induced global warming, global Average Surface Air Temperature(ASAT) will reach certain thresholds with reference to the pre-industrial period. Quantitative assessments of climate extremes across China when reaching these thresholds are important indicators in disaster risk management and policymaking. In this study, based on outputs of 18 General Circulation Models(GCMs) from the Coupled Model Intercomparison Project Phase 5(CMIP5), 27 climate-extreme indices computed with a consistent methodology are used to quantify the changes in the mean and extreme climate across China when the 2℃, 3℃, and 4℃ thresholds under different Representative Concentration Pathways(RCP) scenarios are exceeded. In general, the ASAT warms faster over China than the global mean in the 21st century. Extreme warm events(e.g., warm nights, warm days, and tropical nights) increase greatly, while extreme cold events(e.g., cold nights, cold days, and frost days) decrease. When the 4℃ threshold is exceeded, warm nights index(spatially averaged over China) are projected to show an increase of about 49.9% relative to the reference period. Accompanied by the increase in global mean temperature, the northern part of China will see more precipitation when the 2℃ threshold is exceeded. Extreme precipitation shows obvious intensification in both frequency and magnitude when different temperature thresholds are exceeded. China is dominated by lengthening heavy and very heavy precipitation days and increasing maximum consecutive 5-day precipitation and extremely wet days. Under the RCP8.5 scenario, the maximum consecutive 5-day precipitation amount increases by 12.5mmand 17.0mmwhen the global ASAT becomes 3℃ and 4℃ warmer, respectively. The changes are found to be more pronounced under higher temperature thresholds. Southwest China, however, exhibits larger changes in the magnitude of extreme precipitation than other regions.
- Threshold /
- Climate extremes /
- Projection

HTML全文

参考文献(35)

[1]	Chen H P. 2013. Projected change in extreme rainfall events in China by the end of the 21st century using CMIP5 models[J]. Chinese Science Bulletin, 58(12):1462-1472.
[2]	Chen H P, Sun J Q. 2009. How the "best" models project the future precipitation change in China[J]. Adv. Atmos. Sci., 26(4):773-782.
[3]	Chen L, Frauenfeld O W. 2014. Surface air temperature changes over the twentieth and twenty-first centuries in China simulated by 20 CMIP5 models[J]. J. Climate, 27(11):3920-3937.
[4]	Gleick P H, Adams R M, Amasino R M, et al. 2010. Climate change and the integrity of science[J]. Science, 328(5979):689-690.
[5]	Deser C, Phillips A, Bourdette V, et al. 2012. Uncertainty in climate change projections:The role of internal variability[J]. Climate Dyn., 38(3-4):527-546.
[6]	Held I M, Soden B J. 2006. Robust responses of the hydrological cycle to global warming[J]. J. Climate, 19(21):5686-5699.
[7]	胡芩, 姜大膀, 范广洲. 2014. CMIP5 全球气候模式对青藏高原地区气候模拟能力评估[J]. 大气科学, 38(5):924-938, doi:10.3878/j.issn.1006-9895.2013.13197. Hu Q, Jiang D B, Fan G Z. 2014. Evaluation of CMIP5 models over the Qinghai-Tibetan Plateau[J]. Chinese Journal of Atmospheric Sciences(in Chinese), 38(5):924-938, doi:10.3878/j.issn.1006-9895.2013.13197.
[8]	IPCC. 2013. Climate Change 2013:The Physical Science Basis[M]//Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, USA:Cambridge University Press, 89pp.
[9]	姜大膀, 富元海. 2012. 2℃ 全球变暖背景下中国未来气候变化预估[J].大气科学, 36(2):234-246. Jiang D B, Fu Y H. 2012. Climate change over China with a 2℃ global warming[J]. Chinese Journal of Atmospheric Sciences(in Chinese), 36(2):234-246.
[10]	Jiang D B, Zhang Y, Sun J Q. 2009. Ensemble projection of 1-3℃ warming in China[J]. Chinese Science Bulletin, 54(18):3326-3334.
[11]	金晨曦, 周天军. 2014. 参加 CMIP5 的四个中国气候模式模拟的东亚冬季风年际变率[J]. 大气科学, 38(3):453-468, doi:10.3878/j.issn.1006-9895.2013.13180. Jin C X, Zhou T J. 2014. Analysis of the interannual variations of the East Asian winter monsoon simulation by four CMIP5 GCMs[J]. Chinese Journal of Atmospheric Sciences(in Chinese), 38(3):453-468, doi:10.3878/j.issn.1006-9895.2013.13180.
[12]	Joshi M, Sutton R, Lowe J, et al. 2011. Projections of when temperature change will exceed 2℃ above pre-industrial levels[J]. Nature Climate Change, 1(8):407-412.
[13]	Knutti R, Sedláček J. 2013. Robustness and uncertainties in the new CMIP5 climate model projections[J]. Nature Climate Change, 3(4):369-373.
[14]	Lang X M, Sui Y. 2013. Changes in mean and extreme climates over China with a 2℃ global warming[J]. Chinese Science Bulletin, 58(12):1453-1461.
[15]	Li J F, Zhang Q, Chen Y D, et al. 2013. GCMs-based spatiotemporal evolution of climate extremes during the 21st century in China[J]. J.Geophys. Res., 118(19):11017-11035.
[16]	Meinshausen M, Meinshausen N, Hare W, et al. 2009. Greenhouse-gas emission targets for limiting global warming to 2℃[J]. Nature, 458(7242):1158-1162.
[17]	Mitchell J F B, Wilson C A, Cunnington W M. 1987. On CO2 climate sensitivity and model dependence of results[J]. Quart. J. Roy. Meteor.Soc., 113(475):293-322.
[18]	Previdi M, 2010. Radiative feedbacks on global precipitation[J]. Environ.Res. Lett., 5:025211.
[19]	O'Gorman P, Allan R, Byrne M, et al. 2012. Energetic constraints on precipitation under climate change[J]. Surv. Geophys., 33(3-4):585-608.
[20]	Schneider S H, Semenov S, Patwardhan A, et al. 2007. Assessing key vulnerabilities and the risk from climate change[M]//Parry M L,Canziani O F, Palutikof J P, et al. Climate Change 2007:Impacts,Adaptation and Vulnerability. Contribution of Working Group Ⅱ to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK:Cambridge University Press, 976pp.
[21]	《第二次气候变化国家评估报告》编写委员会. 2011. 第二次气候变化国家评估报告[M]. 北京:科学出版社, 710pp. "Second National Assessment Report on Climate Change" Writing Committee. 2011.
[22]	Second National Assessment Report on Climate Change(in Chinese)[M].Beijing:Science Press, 710pp.
[23]	Sillmann J, Kharin V V, Zwiers F W, et al. 2013. Climate extremes indices in the CMIP5 multimodel ensemble. Part 2. Future climate projections[J].J. Geophys. Res., 118(6):2473-2493.
[24]	Sui Y, Lang X M, Jiang D B. 2014. Time of emergence of climate signals over China under the RCP4.5 scenario[J]. Climatic Change, 125(2):265-276.
[25]	Taylor K E, Stouffer R J, Meehl G A. 2012. An overview of CMIP5 and the experiment design[J]. Bull. Amer. Meteor. Soc., 93(4):485-498.
[26]	The World Bank. 2012. Turn down the heat:Why a 4℃ warmer world must be avoided[R]. Washington DC:The World Bank, 84pp.
[27]	Xu C H, Xu Y. 2012. The projection of temperature and precipitation over China under RCP scenarios using a CMIP5 multi-model ensemble[J].Atmospheric and Oceanic Science Letters, 5(6):527-533.
[28]	Yao Y, Luo Y, Huang J B. 2012. Evaluation and projection of temperature extremes over China based on CMIP5 model[J]. Adv. Climate Change Res., 3(4):179-185.
[29]	Yao Y, Luo Y, Huang J B, et al. 2013. Comparison of monthly temperature extremes simulated by CMIP3 and CMIP5 models[J]. J. Climate, 26(19):7692-7707.
[30]	Zeng N, Ding Y H, Pan J H, et al. 2008. Climate change-The Chinese challenge[J]. Science, 319(5864):730-731.
[31]	张莉, 丁一汇, 吴统文, 等. 2013. CMIP5 模式对 21 世纪全球和中国年平均地表气温变化和2℃ 升温阈值的预估[J]. 气象学报, 71(6):1047-1060. Zhang L, Din Y H, Wu T W, et al. 2013. The 21st century annual mean surface air temperature change and the 2℃ warming threshold over the globe and China as projected by the CMIP5 models[J].Acta Meteorologica Sinica(in Chinese), 71(6):1047-1060.
[32]	Zhang Y. 2012. Projections of 2.0℃ warming over the globe and China under RCP4.5[J]. Atmos. Oceanic Sci. Lett., 5:514-520.
[33]	Zhang X B, Alexander L, Hegerl G C, et al. 2011. Indices for monitoring changes in extremes based on daily temperature and precipitation data[J].Wiley Interdisciplinary Reviews:Climate Change, 2(6):851-870.
[34]	Zhou T J, Yu R C. 2006. Twentieth-century surface air temperature over China and the globe simulated by coupled climate models[J]. J. Climate,19(22):5843-5858.
[35]	周秀华, 肖子牛. 2014. 基于 CMIP5 资料的云南及周边地区未来 50 年气候预估[J]. 气候与环境研究, 19(5):601-613, doi:10.3878/j.issn.1006-9585.2013.13080. Zhou X H, Xiao Z N. 2014. Climate projection over Yunnan Province and the surrounding regions based on CMIP5 data[J]. Climatic and Environmental Research(in Chinese), 19(5):601-613,doi:10.3878/j.issn.1006-9585.2013.13080.