长江流域资源与环境 >> 2017, Vol. 26 >> Issue (05): 778-788.doi: 10.11870/cjlyzyyhj201705016

• 自然灾害 • 上一篇    下一篇

全球升温1.5℃与2.0℃情景下长江中下游地区极端降水的变化特征

刘俸霞1, 王艳君1, 赵晶1, 陈雪1, 姜彤1,2   

  1. 1. 南京信息工程大学气象灾害预报预警与评估协同中心/地理与遥感学院, 江苏 南京 210044;
    2. 中国气象局国家气候中心, 北京 100081
  • 收稿日期:2016-10-12 修回日期:2016-12-27 出版日期:2017-05-20
  • 通讯作者: 王艳君 E-mail:yjwang78@163.com
  • 作者简介:刘俸霞(1991~),女,硕士研究生,主要从事气候变化影响评估与风险管理.E-mail:liufx06250@163.com
  • 基金资助:
    国家自然科学基金项目(41571494);国家自然科学基金委-德国DFG国际合作研究组项目(GZ912)

VARIATIONS OF THE EXTERME PRECIPITATION UNDER THE GLOBAL WARMING OF 1.5℃ AND 2.0℃ IN THE MID-LOWER REACHES OF THE YANGTZE RIVER BASIN

LIU Feng-xia1, WANG Yan-jun1, ZHAO Jing1, CHEN Xue1, JIANG Tong1,2   

  1. 1. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China;
    2. National Climate Center, China Meteorological Administration, Beijing 100081, China
  • Received:2016-10-12 Revised:2016-12-27 Online:2017-05-20
  • Supported by:
    National Natural Science Foundation of China (41571494);Chinese-German Cooperation Group Project by NSFC and DFG (GZ912)

摘要: 基于长江中下游地区1961~2100年区域气候模式COSMO-CLM(CCLM)模拟与1961~2005年气象站观测的逐日降水数据,通过统计计算年降水量、强降水量、暴雨日数和极端降水贡献率4个极端降水指数,研究全球升温1.5℃与2.0℃情景下,长江中下游地区极端降水的时空变化特征。结果表明:(1)全球升温1.5℃情景下,年降水量相对于1986~2005年减少5%,强降水量、暴雨日数和极端降水贡献率分别增加7%、33%和4%;概率密度曲线表明,年降水量均值下降,强降水量、暴雨日数和极端降水贡献率均值上升,极端降水方差增大;年降水量、强降水量和暴雨日数在空间上表现为南部增加北部减少,极端降水贡献率则相反。(2)全球升温2.0℃情景下,年降水量下降3%,强降水量、暴雨日数和极端降水贡献率分别上升15%、46%和15%;年降水量均值稍有减少且方差稍有上升,强降水量、暴雨日数和极端降水贡献率均值和方差明显增加;年降水量减少区域位于长江主干以北,强降水量、暴雨日数和极端降水贡献率表现为绝大部分地区增加的空间变化特征。(3)全球升温由1.5℃至2.0℃时,年降水量、强降水量、暴雨日数和极端降水贡献率分别增加3%、7%、10%和11%;随升温幅度的增加极端降水均值和方差上升;极端降水呈增加态势的范围扩大。因此,努力将升温控制在1.5℃对降低极端降水的影响具有重要意义。

关键词: 全球升温1.5℃和2.0℃, 极端降水, 时空变化, CCLM模式, 长江中下游地区

Abstract: Based on the daily precipitation data of a high-resolution regional climate model (COSMO model in Climate Mode, CCLM) simulated for the period 1961-2100 and the 90 meteorological stations observed during 1961-2005 over the mid-lower reaches of the Yangtze River Basin, four typical extreme precipitation indices, i.e. annual precipitation, intensive precipitation, heavy rain days, and contribution ratio of intensive precipitation, were calculated separately. The spatiotemporal variations of extreme precipitation under the global warming of 1.5℃ and 2.0℃ were analyzed in detail. The results showed that:(1) In the 1.5℃ warming period, annual precipitation in the mid-lower reaches of the Yangtze River Basin will decrease by 5%, but intensive precipitation, heavy rain days, and contribution ratio of intensive precipitation will increase by 7%, 33% and 4%, respectively, relative to the reference period (1986-2005). The probability density curves showed that under the global warming of 1.5℃, the mean value of annual precipitation will decrease, but intensive precipitation, heavy rain days, and contribution ratio of intensive precipitation will increase, and the variances of extreme precipitation will increase, relative to the reference period. Compared with extreme precipitation in the reference period, the spatial distribution of annual precipitation, intensive precipitation, and heavy rain days show an increasing trend in the southern part of the mid-lower reaches of the Yangtze River Basin and a decreasing trend in the northern part, however, contribution ratio of intensive precipitation has the opposite result in the 1.5℃ warming period. (2) In the 2.0℃ warming period, annual precipitation will decrease by 3%, but intensive precipitation, heavy rain days, and contribution ratio of intensive precipitation will increase by 15%, 46% and 15%, respectively, relative to the reference period. The probability density curves showed that under the global warming of 2.0℃, The mean value and variance of annual precipitation will decrease and increase respectively, but intensive precipitation, heavy rain days, and contribution ratio of intensive precipitation will increase significantly, relative to the reference period. The region of annual precipitation reduction is located in the north of the mid-lower reaches of the Yangtze River Basin, but intensive precipitation, heavy rain days, and contribution ratio of intensive precipitation show that extreme precipitation will increase in most areas. (3)With a global warming of 1.5℃ to 2.0℃, annual precipitation, intensive precipitation, heavy rain days, and contribution ratio of intensive precipitation will increase by 3%, 7%, 10% and 11%, respectively, relative to the reference period. The mean values and variances of extreme precipitation are projected to increase with the rising of temperature, by analyzing the probability density curves. The area and scope of extreme precipitation with increasing trend in a 2.0℃ warming will expand to larger than that of the extreme precipitation with same reference period in a 1.5℃ warming. Aforementioned findings revealed that compared to the extreme precipitation in a 2.0℃ warming, the temperature will be controlled strenuously at 1.5℃ warming that is of great significance to reduce the adverse effects of extreme precipitation.

Key words: global warming of 1.5℃ and 2.0℃, extreme precipitation, spatiotemporal variations, CCLM, the mid-lower reaches of the Yangtze River basin

中图分类号: 

  • P467
[1] IPCC.Climate change 2013:the physical science basis.IPCC working group I contribution to AR5[M].Cambridge,UK,New York,USA:Cambridge University Press,2013.
[2] 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.Geneva,Switzerland:IPCC,2014:151.
[3] UNFCCC.Decision 1/CP.21[R].The Paris Agreement.Paris:UNFCCC,2015.
[4] 秦大河.中国极端天气气候事件和灾害风险管理与适应国家评估报告[M].北京:科学出版社,2015:203-204.[QIN D H.Chinese managing the risks of extreme events and disasters to advance climate change adaptation[M].Beijing:Science Press,2015:203-204.]
[5] 陈金明,陆桂华,吴志勇,等.长江流域极端降水过程事件的年内分布特征[J].长江流域资源与环境,2014,23(4):588-594.[CHEN J M,LU G H,WU Z Y,et al.Inner-annual distribution characteristics of the extreme precipitation processes events over the Yangtze River Basin[J].Resources and Environment in the Yangtze Basin,2014,23(4):588-594.]
[6] 肖艳,黎祖贤,章新平,等.近48年来湘江流域极端降水事件特征分析[J].长江流域资源与环境,2010,19(11):1356-1362.[XIAO Y,LI Z X,ZHANG X P,et al.Research on extreme precipitation event characteristics of Xiangjiang River Basin in recent 48 years[J].Resources and Environment in the Yangtze Basin,2010,19(11):1356-1362.]
[7] 张飞跃,姜彤,苏布达,等.CMIP5多模式集合对南亚大河气候变化模拟评估及未来情景预估[J].热带气象学报,2016,32(5):734-742.[ZHANG F Y,JIANG T,SU B D,et al.Simulation and projection of climate change in the south Asian River Basin by CMIP5 multi-model ensembles[J].Journal of Tropical Meteorology,2016,32(5):734-742.]
[8] SU B D,HUANG J L,GEMMER M,et al.Statistical downscaling of CMIP5 multi-model ensemble for projected changes of climate in the Indus River Basin[J].Atmospheric Research,2016,178-179:138-149.
[9] 景丞,王艳君,姜彤,等.CMIP5多模式对朝鲜干旱模拟与预估[J].干旱区资源与环境,2016,30(12):95-102.[JING C,WANG Y J,JIANG T,et al.Simulation and estimation of droughts in North Korea by CMIP5 multi-model ensembles[J].Journal of Arid Land Resources and Environment,2016,30(12):95-102.]
[10] WARSZAWSKI L,FRIELER K,HUBER V,et al.The inter-sectoral impact model intercomparison project (ISI-MIP):project framework[J].Proceedings of the National Academy of Sciences of the United States of America,2014,111(9):3228-3232.
[11] 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℃[J].Earth System Dynamics,2016,7(2):327-351.
[12] SU B D,HUANG J L,ZENG X F,et al.Impacts of climate change on streamflow in the upper Yangtze River basin[J].Climatic Change,2017,141(3):533-546.
[13] 张世法,顾颖,林锦.气候模式应用中的不确定性分析[J].水科学进展,2010,21(4):504-511.[ZHANG S F,GU Y,LIN J.Uncertainty analysis in the application of climate models[J].Advances in Water Science,2010,21(4):504-511.]
[14] XU Y,XU C H.Preliminary assessment of simulations of climate changes over China by CMIP5 multi-models[J].Atmospheric and Oceanic Science Letters,2012,5(6):489-494.
[15] GIORGI F,JONES C,ASRAR G R.Addressing climate information needs at the regional level:the CORDEX framework[J].WMO Bulletin,2009,58(3):175-183.
[16] ALTINSOY H,OZTURK T,TURKES M,et al.Simulating the climatology of extreme events for the central Asia domain using the RegCM 4.0 regional climate model[M]//HELMIS C,NASTOS P.Advances in Meteorology,Climatology and Atmospheric Physics.Berlin Heidelberg:Springer,2013:365-370.
[17] GAO X J,WANG M L,GIORGI F.Climate change over China in the 21st century as simulated by BCC_CSM1.1-RegCM4.0[J].Atmospheric and Oceanic Science Letters,2013,6(5):381-386.
[18] RAO K K,PATWARDHAN S K,KULKARNI A,et al.Projected changes in mean and extreme precipitation indices over India using PRECIS[J].Global Planetary Change,2014,113:77-90.
[19] ROCKEL B,WILL A,HENSE A.The regional climate model COSMO-CLM (CCLM)[J].Meteorologische Zeitschrift,2008,17(4):347-348.
[20] 谈丰,苏布达,高超,等.高精度区域气候模式对淮河流域降水的模拟评估[J].长江流域资源与环境,2012,21(10):1236-1242.[TAN F,SU B D,GAO C,et al.High-resolution regional climate model (CCLM) for simulation of precipitation in the Huaihe River Basin,China[J].Resources and Environment in the Yangtze Basin,2012,21(10):1236-1242.]
[21] FISCHER T,MENZ C,SU B D,et al.Simulated and projected climate extremes in the Zhujiang River Basin,South China,using the regional climate model COSMO-CLM[J].International Journal of Climatology,2013,33(14):2988-3001.
[22] 陶辉,黄金龙,翟建青,等.长江流域气候变化高分辨率模拟与RCP4.5情景下的预估[J].气候变化研究进展,2013,9(4):246-251.[TAO H,HUANG J L,ZHAI J Q,et al.Simulation and Projection of climate changes under the RCP4.5 scenario in the Yangtze River Basin based on CCLM[J].Progressus Inquisitiones de Mutatione Climatis,2013,9(4):246-251.]
[23] 熊喆,延晓东.黑河流域高分辨率区域气候模式建立及其对降水模拟验证[J].科学通报,2014,59(7):605-614.[XIONG Z,YAN X D.Building a high-resolution regional climate model for the Heihe River Basin and simulating precipitation over this region[J].Chinese Science Bulletin,2013,58(36):4670-4678.]
[24] 黄金龙,陶辉,苏布达,等.塔里木河流域极端气候事件模拟与RCP4.5情景下的预估研究[J].干旱区地理,2014,37(3):490-498.[HUANG J L,TAO H,SU B D,et al.Simulation of climate extreme events in the Tarim River Basin and projection under the RCP4.5 scenario[J].Arid Land Geography,2014,37(3):490-498.]
[25] 苏布达,姜彤.长江流域降水极值时间序列的分布特征[J].湖泊科学,2008,20(1):123-128.[SU B D,JIANG T.Distribution feature of time series of extreme precipitation over the Yangtze River Basin[J].Journal of Lake Sciences,2008,20(1):123-128.]
[26] 陈海山,朱月佳,刘蕾.长江中下游地区冬季极端降水事件与天气尺度瞬变波活动的可能联系[J].大气科学,2013,37(4):801-814.[CHEN H S,ZHU Y J,LIU L.Relationship of synoptic-scale transient eddies and extreme winter precipitation events in the middle and lower reaches of the Yangtze River[J].Chinese Journal of Atmospheric Sciences,2013,37(4):801-814.]
[27] BAI L Y,RONG Y S.Reanalysis of the characteristics of extreme rainfall in the Yangtze River basin during recent 50 years[J].Journal of Water Resources Research,2015,4(1):88-100.
[28] SU B D,KUNDZEWICZ Z W,JIANG T.Simulation of extreme precipitation over the Yangtze River Basin using Wakeby distribution[J].Theoretical and Applied Climatology,2009,96(3/4):209-219.
[29] GUO J L,GUO S L,LI Y,et al.Spatial and temporal variation of extreme precipitation indices in the Yangtze River basin,China[J].Stochastic Environmental Research and Risk Assessment,2013,27(2):459-475.
[30] 王蒙,殷淑燕.近52a长江中下游地区极端降水的时空变化特征[J].长江流域资源与环境,2015,24(7):1221-1229.[WANG M,YIN S Y.Spatio-temporal variations of the extreme precipitation of middle and lower reaches of the Yangtze River in recent 52 years[J].Resources and Environment in the Yangtze Basin,2015,24(7):1221-1229.]
[31] SUI Y,LANG X M,JIANG D B.Temperature and precipitation signals over China with a 2℃ global warming[J].Climate Research,2015,64(3):227-242.
[32] KOUTROULIS A G,GRILLAKIS M G,DALIAKOPOULOS I N,et al.Cross sectoral impacts on water availability at+2℃ and+3℃ for east Mediterranean island states:the case of Crete[J].Journal of Hydrology,2016,532:16-28.
[33] STEVENS B,GIORGETTA M,ESCH M,et al.Atmospheric component of the MPI-M earth system model:ECHAM6[J].Journal of Advances in Modeling Earth Systems,2013,5(2):146-172.
[34] TIEDTKE M.A comprehensive mass flux scheme for cumulus parameterization in large-scale models[J].Monthly Weather Review,1989,117(8):1779-1800.
[35] RITTER B,GELEYN J F.A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations[J].Monthly Weather Review,1992,120(2):303-325.
[36] LOTT F,MILLER M J.A new subgrid-scale orographic drag parametrization:its formulation and testing[J].Quarterly Journal of the Royal Meteorological Society,1997,123(537):101-127.
[37] SCHRODIN R,HEISE W.A new multi-layer soil model[J].COSMO Newsl,2002,2:149-151.
[38] DOMS G,FÖRSTNER J,HEISE E,et al.A description of the nonhydrostatic regional COSMO model,part Ⅱ:physical parameterization[EB/OL].Offenbach,Germany:Deutscher Wetterdienst,2011.http://www.cosmo-model.org.
[39] FRICH P,ALEXANDER L V,DELLA-MARTA P,et al.Observed coherent changes in climatic extremes during the second half of the twentieth century[J].Climate Research,2002,19(3):193-212.
[40] ENDO N,MATSUMOTO J,LWIN T.Trends in precipitation extremes over southeast Asia[J].SOLA,2009,5:168-171.
[41] GAO X J,SHI Y,ZHANG D F,et al.Uncertainties in monsoon precipitation projections over China:results from two high-resolution RCM simulations[J].Climate Research,2012,52:213-226.
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