CMIP5全球气候模式对中国黄河流域气候模拟能力的评估
|
摘要
利用格点化观测资料,对第5次耦合模式比较计划(Coupled Model Intercomparison Project phase 5,CMIP5)提供的18个全球气候模式在黄河流域的模拟能力进行评估和客观选择。结果表明:基于1961—2005年黄河流域逐日的气温和降水观测资料,对黄河流域气候进行了模拟评估,通过对气候平均态、年际变率、季节循环、年际变化主要模态及概率密度函数等方面的模拟能力进行统计评价,分析得到所有模式模拟能力的综合评分排序,剔除较差的模式样本。最终选择的5个全球气候模式分别为MIROC-ESM-CHEM、CSIRO-Mk3-6-0、NorESM1-M、CNRM-CM5和EC-EARTH,5个全球气候模式综合评分较优,且基本可以覆盖18个CMIP5模式对黄河流域未来平均气温预估的不确定性分布,形成了可用于黄河流域气候变化研究的多模式集合系统。
Based on gridded observation dataset,multi-criteria assessment on daily surface air temperature and precipitation(1961-2005) from 18 CMIP5(Coupled Model Intercomparison Project phase 5) models were conducted over the Yellow River Basin.A suite of statistics is calculated,including climatological mean,interannual variation,seasonal cycle,interannual modes,and probability distribution function,to evaluate their performances.According to the comprehensive rank,the models with poor validation are excluded.Five models,i.e.,MIROC-ESMCHEM,CSIRO-Mk3-6-0,NorESM1-M,CNRM-CM5,and EC-EARTH are therefore recommended for the regional multi-model climate change projections over the Yellow River basin.The selected subset can also sample the range of uncertainty represented by the full ensemble.
Based on gridded observation dataset,multi-criteria assessment on daily surface air temperature and precipitation(1961-2005) from 18 CMIP5(Coupled Model Intercomparison Project phase 5) models were conducted over the Yellow River Basin.A suite of statistics is calculated,including climatological mean,interannual variation,seasonal cycle,interannual modes,and probability distribution function,to evaluate their performances.According to the comprehensive rank,the models with poor validation are excluded.Five models,i.e.,MIROC-ESMCHEM,CSIRO-Mk3-6-0,NorESM1-M,CNRM-CM5,and EC-EARTH are therefore recommended for the regional multi-model climate change projections over the Yellow River basin.The selected subset can also sample the range of uncertainty represented by the full ensemble.
引文
[1]Shi H L,Hu C H,Wang Y G,et al.Analyses of trends and causes for variations in runoff and sediment load of the Yellow River[J].International Journal of Sediment Research,2017,32(2):171-179.
[2]Knutti R,Furrer R,Tebaldi C,et al.Challenges in combining projections from multiple climate models[J].Journal of Climate,2010,23(10):2739-2758.
[3]Gleckler P J,Taylor K E,Doutriaux C.Performance metrics for climate models[J].Journal of Geophysical Research:Atmospheres,2008,113(D6):D06104.
[4]赵宗慈,罗勇,黄建斌.对地球系统模式评估方法的回顾[J].气候变化研究进展,2013,9(1):1-8.
[5]Rupp D E,Abatzoglou J T,Mote P W.Projections of21st century climate of the Columbia River Basin[J].Climate Dynamics,2017,49(5/6):1783-1799.
[6]McSweeney C F,Jones R G,Booth B B B.Selecting ensemble members to provide regional climate change information[J].Journal of Climate,2012,25(20):7100-7121.
[7]许崇海,沈新勇,徐影.IPCC AR4模式对东亚地区气候模拟能力的分析[J].气候变化研究进展,2007,3(5):287-292.
[8]Jiang D B,Tian Z P.East Asian monsoon change for the 21st century:Results of CMIP3 and CMIP5 models[J].Chinese Science Bulletin,2013,58(12):1427-1435.
[9]林壬萍,周天军.参加CMIP 5计划的四个中国模式模拟的东亚地区降水结构特征及未来变化[J].大气科学,2015,39(2):338-356.
[10]江志红,陈威霖,宋洁,等.7个IPCC AR4模式对中国地区极端降水指数模拟能力的评估及其未来情景预估[J].大气科学,2009,33(1):109-120.
[11]陈晓晨,徐影,许崇海,等.CMIP 5全球气候模式对中国地区降水模拟能力的评估[J].气候变化研究进展,2014,10(3):217-225.
[12]Huang D Q,Zhu J,Zhang Y C,et al.Uncertainties on the simulated summer precipitation over Eastern China from the CMIP5 models[J].Journal of Geophysical Research:Atmospheres,2013,118(16):9035-9047.
[13]张武龙,张井勇,范广洲.CMIP5模式对我国西南地区干湿季降水的模拟和预估[J].大气科学,2015,39(3):559-570.
[14]Bao J W,Feng J M.Intercomparison of CMIP5 simulations of summer precipitation,evaporation,and water vapor transport over Yellow and Yangtze River basins[J].Theoretical and Applied Climatology,2016,123(3/4):437-452.
[15]王涛,王乙舒,崔妍,等.气候模式对东北三省降水模拟能力评估及预估[J].气象与环境学报,2016,32(5):52-60.
[16]王国庆,张建云,金君良,等.基于RCP情景的黄河流域未来气候变化趋势[J].水文,2014,34(2):8-13.
[17]Taylor K E.Summarizing multiple aspects of model performance in a single diagram[J].Journal of Geophysical Research:Atmospheres,2001,106(D7):7183-7192.
[18]Pierce D W,Barnett T P,Santer B D,et al.Selecting global climate models for regional climate change studies[J].Proceedings of the National Academy of Sciences of the United States of America,2009,106(21):8441-8446.
[19]Watterson I G,Hirst A C,Rotstayn L D.A skill score based evaluation of simulated Australian climate[J].Australian Meteorological and Oceanographic Journal,2013,63(1):181-190.
[20]Rupp D E,Abatzoglou J T,Hegewisch K C,et al.Evaluation of CMIP5 20th century climate simulations for the Pacific Northwest USA[J].Journal of Geophysical Research:Atmospheres,2013,118(19):10884-10906.
[21]田亮,江志红,陈威霖.CMIP5气候模式对东亚夏季平均环流场模拟能力的评估[J].气候与环境研究,2016,21(4):380-392.
[22]Ahmadalipour A,Rana A,Moradkhani H,et al.Multicriteria evaluation of CMIP5 GCMs for climate change impact analysis[J].Theoretical and Applied Climatology,2017,128(1/2):71-87.
[23]吴佳,高学杰.一套格点化的中国区域逐日观测资料及与其它资料的对比[J].地球物理学报,2013,56(4):1102-1111.
[24]Taylor K E,Stouffer R J,Meehl G A.An overview of CMIP5 and the experiment design[J].Bulletin of the American Meteorological Society,2012,93(4):485-498.
[25]Perkins S E,Pitman A J,Holbrook N J,et al.Evaluation of the AR4 climate models'simulated daily maximum temperature,minimum temperature,and precipitation over Australia using probability density functions[J].Journal of Climate,2007,20(17):4356-4376.
[26]Fu G B,Liu Z F,Charles S P,et al.A score-based method for assessing the performance of GCMs:A case study of southeastern Australia[J].Journal of Geophysical Research:Atmospheres,2013,118(10):4154-4167.
[27]North G R,Bell T L,Cahalan R F,et al.Sampling errors in the estimation of empirical orthogonal functions[J].Monthly Weather Review,1982,110(7):699-706.
[28]Gao X S,Shi Y,Han Z Y,et al.Performance of RegCM4 over major river basins in China[J].Advances in Atmospheric Sciences,2017,34(4):441-455.
[29]童尧,高学杰,韩振宇,等.基于Reg CM4的中国区域日尺度降水模拟误差订正[J].大气科学,2017,41(6):1156-1166.
[2]Knutti R,Furrer R,Tebaldi C,et al.Challenges in combining projections from multiple climate models[J].Journal of Climate,2010,23(10):2739-2758.
[3]Gleckler P J,Taylor K E,Doutriaux C.Performance metrics for climate models[J].Journal of Geophysical Research:Atmospheres,2008,113(D6):D06104.
[4]赵宗慈,罗勇,黄建斌.对地球系统模式评估方法的回顾[J].气候变化研究进展,2013,9(1):1-8.
[5]Rupp D E,Abatzoglou J T,Mote P W.Projections of21st century climate of the Columbia River Basin[J].Climate Dynamics,2017,49(5/6):1783-1799.
[6]McSweeney C F,Jones R G,Booth B B B.Selecting ensemble members to provide regional climate change information[J].Journal of Climate,2012,25(20):7100-7121.
[7]许崇海,沈新勇,徐影.IPCC AR4模式对东亚地区气候模拟能力的分析[J].气候变化研究进展,2007,3(5):287-292.
[8]Jiang D B,Tian Z P.East Asian monsoon change for the 21st century:Results of CMIP3 and CMIP5 models[J].Chinese Science Bulletin,2013,58(12):1427-1435.
[9]林壬萍,周天军.参加CMIP 5计划的四个中国模式模拟的东亚地区降水结构特征及未来变化[J].大气科学,2015,39(2):338-356.
[10]江志红,陈威霖,宋洁,等.7个IPCC AR4模式对中国地区极端降水指数模拟能力的评估及其未来情景预估[J].大气科学,2009,33(1):109-120.
[11]陈晓晨,徐影,许崇海,等.CMIP 5全球气候模式对中国地区降水模拟能力的评估[J].气候变化研究进展,2014,10(3):217-225.
[12]Huang D Q,Zhu J,Zhang Y C,et al.Uncertainties on the simulated summer precipitation over Eastern China from the CMIP5 models[J].Journal of Geophysical Research:Atmospheres,2013,118(16):9035-9047.
[13]张武龙,张井勇,范广洲.CMIP5模式对我国西南地区干湿季降水的模拟和预估[J].大气科学,2015,39(3):559-570.
[14]Bao J W,Feng J M.Intercomparison of CMIP5 simulations of summer precipitation,evaporation,and water vapor transport over Yellow and Yangtze River basins[J].Theoretical and Applied Climatology,2016,123(3/4):437-452.
[15]王涛,王乙舒,崔妍,等.气候模式对东北三省降水模拟能力评估及预估[J].气象与环境学报,2016,32(5):52-60.
[16]王国庆,张建云,金君良,等.基于RCP情景的黄河流域未来气候变化趋势[J].水文,2014,34(2):8-13.
[17]Taylor K E.Summarizing multiple aspects of model performance in a single diagram[J].Journal of Geophysical Research:Atmospheres,2001,106(D7):7183-7192.
[18]Pierce D W,Barnett T P,Santer B D,et al.Selecting global climate models for regional climate change studies[J].Proceedings of the National Academy of Sciences of the United States of America,2009,106(21):8441-8446.
[19]Watterson I G,Hirst A C,Rotstayn L D.A skill score based evaluation of simulated Australian climate[J].Australian Meteorological and Oceanographic Journal,2013,63(1):181-190.
[20]Rupp D E,Abatzoglou J T,Hegewisch K C,et al.Evaluation of CMIP5 20th century climate simulations for the Pacific Northwest USA[J].Journal of Geophysical Research:Atmospheres,2013,118(19):10884-10906.
[21]田亮,江志红,陈威霖.CMIP5气候模式对东亚夏季平均环流场模拟能力的评估[J].气候与环境研究,2016,21(4):380-392.
[22]Ahmadalipour A,Rana A,Moradkhani H,et al.Multicriteria evaluation of CMIP5 GCMs for climate change impact analysis[J].Theoretical and Applied Climatology,2017,128(1/2):71-87.
[23]吴佳,高学杰.一套格点化的中国区域逐日观测资料及与其它资料的对比[J].地球物理学报,2013,56(4):1102-1111.
[24]Taylor K E,Stouffer R J,Meehl G A.An overview of CMIP5 and the experiment design[J].Bulletin of the American Meteorological Society,2012,93(4):485-498.
[25]Perkins S E,Pitman A J,Holbrook N J,et al.Evaluation of the AR4 climate models'simulated daily maximum temperature,minimum temperature,and precipitation over Australia using probability density functions[J].Journal of Climate,2007,20(17):4356-4376.
[26]Fu G B,Liu Z F,Charles S P,et al.A score-based method for assessing the performance of GCMs:A case study of southeastern Australia[J].Journal of Geophysical Research:Atmospheres,2013,118(10):4154-4167.
[27]North G R,Bell T L,Cahalan R F,et al.Sampling errors in the estimation of empirical orthogonal functions[J].Monthly Weather Review,1982,110(7):699-706.
[28]Gao X S,Shi Y,Han Z Y,et al.Performance of RegCM4 over major river basins in China[J].Advances in Atmospheric Sciences,2017,34(4):441-455.
[29]童尧,高学杰,韩振宇,等.基于Reg CM4的中国区域日尺度降水模拟误差订正[J].大气科学,2017,41(6):1156-1166.