CMIP5多模式下的ENSO模拟评估及非对称性特征分析
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摘要
为了评估参与世界气候研究计划组织的"第五次国际耦合模式比较计划(CMIP5)"的全球气候模式对ENSO(厄尔尼诺和南方涛动)现象非对称性特征的模拟能力,采用泰勒图统计分析、合成分析等方法,对参与CMIP5计划的18个耦合模式模拟资料与观测资料进行对比分析。可得出CMIP5模式对热带太平洋的整体海温状况的模拟较好,对表征热带太平洋海温显著年际变异的4个指标海域的海温状况模拟较差。其中多模式集合平均的综合模拟能力最优,其次是CCSM4。HadCM3的综合模拟能力最差。ENSO海温异常强度的非对称特征表现为El Niňo强于La Niňa。模式对海温异常中心强度的模拟效果较理想,模拟的强度与观测的所相差在正负0.3℃左右。ENSO海温异常空间分布的非对称性特征表现在La Niňa冷异常区域比El Niňo暖异常区域大,模式对ENSO强事件的空间分布模拟较理想,与观测基本一致,但不能较好模拟弱事件海温异常区域关于赤道对称的特征。ENSO海温异常持续性的非对称性特征主要表现在La Niňa的持续时间较短,El Niňo的持续时间较长。模式都能较好模拟ENSO持续性特征,但对ENSO衰退事件的海温异常中心强度的模拟效果不理想。
In order to evaluate the CMIP5(WCRP Coupled Model Intercomparison Project Phase 5) global climate model for ENSO asymmetry feature simulation capabilities. The model and observation data were compared and analyzed by using Taylor's diagram and synthetic analysis. It can be concluded that the CMIP5 model has a good simulation effect on the overall sea surface temperature of the tropical Pacific Ocean, and has a poor simulation effect on the sea temperature conditions of the four sea areas with significant interannual variability of the Pacific SST. Among them, the multi-mode ensemble average has the best comprehensive simulation capability, followed by CCSM4, and HadCM3 has the worst comprehensive simulation capability. The asymmetrical characteristics of ENSO temperature anomalous intensity is characterized by El Niňo being stronger than La Niňa. The simulation effect of the model on the anomaly center intensity of the SST is ideal, and the simulated intensity differs from the observed intensity by about 0.3 ℃. ENSO's asymmetry characteristics of spatial distribution of SST anomaly is characterized by the fact that the La Niňa cold anomaly region is larger than the El Niňo warm anomaly region. The spatial distribution simulation of the ENSO strong event is ideal, which is consistent with the observation. However, the symmetry of the equator in the SST anomaly region cannot be simulated well for the weak event. The asymmetry of the ENSO SST anomaly is mainly characterized by the short duration of La Niňa and the longer duration of El Niňo. The model can simulate better about the persistence characteristics of ENSO, but the simulation effect on the center intensity of the sea temperature anomaly in the ENSO decay event is not ideal.
In order to evaluate the CMIP5(WCRP Coupled Model Intercomparison Project Phase 5) global climate model for ENSO asymmetry feature simulation capabilities. The model and observation data were compared and analyzed by using Taylor's diagram and synthetic analysis. It can be concluded that the CMIP5 model has a good simulation effect on the overall sea surface temperature of the tropical Pacific Ocean, and has a poor simulation effect on the sea temperature conditions of the four sea areas with significant interannual variability of the Pacific SST. Among them, the multi-mode ensemble average has the best comprehensive simulation capability, followed by CCSM4, and HadCM3 has the worst comprehensive simulation capability. The asymmetrical characteristics of ENSO temperature anomalous intensity is characterized by El Niňo being stronger than La Niňa. The simulation effect of the model on the anomaly center intensity of the SST is ideal, and the simulated intensity differs from the observed intensity by about 0.3 ℃. ENSO's asymmetry characteristics of spatial distribution of SST anomaly is characterized by the fact that the La Niňa cold anomaly region is larger than the El Niňo warm anomaly region. The spatial distribution simulation of the ENSO strong event is ideal, which is consistent with the observation. However, the symmetry of the equator in the SST anomaly region cannot be simulated well for the weak event. The asymmetry of the ENSO SST anomaly is mainly characterized by the short duration of La Niňa and the longer duration of El Niňo. The model can simulate better about the persistence characteristics of ENSO, but the simulation effect on the center intensity of the sea temperature anomaly in the ENSO decay event is not ideal.
引文
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[25] 曹璐.两类ENSO事件的监测及大气的响应[D].南京:南京大学,2011.
[2] Cai W,Santoso A,Wang G,et al.ENSO and greenhouse warming[J].Nature Climate Change,2015,5(9).
[3] Cai W,Wang G,Santoso A,et al.Increased frequency of extreme La Nina events under greenhouse warming[J].Nature Climate Change,2015,5(2):132-137.
[4] 胡增臻,王绍武.与ENSO现象有关的全球灾害性天气气候现象[J].灾害学,1990(1):76-79.
[5] 王小玲,宋文玲.ENSO与登陆我国热带气旋的关系研究热带气象学报[J].2009,25(5):576-580.
[6] 李威,翟盘茂.中国极端强降水日数与ENSO的关系[J].气候变化研究进展,2009,5(6):336-342.
[7] 宋迅殊.ENSO事件非对称性成因研究[J].海洋学研究,2013(1):35-44.
[8] An S I,Jin F F.Nonlinearity and Asymmetry of ENSO[J].Journal of Climate,2004,17(11):2033-2038.
[9] 徐康.东部和中部型ENSO模态及其对中国降水影响的差异[D].南京:南京信息工程大学,2013.
[10] Choi K Y,Vecchi G A,Wittenberg A T.ENSO Transition,Duration,and Amplitude Asymmetries:Role of the Nonlinear Wind Stress Coupling in a Conceptual Model[J].Journal of Climate,2013,26(23):9462-9476.
[11] Kim S T,Yu J Y.The two types of ENSO in CMIP5 models[J].Geophysical Research Letters,2012,39(11):221-228.
[12] 王澄海,吴永萍,崔洋.CMIP研究计划的进展及其在中国地区的检验和应用前景[J].地球科学进展,2009,24(5):461-468.
[13] 周天军,邹立维,吴波,等.中国地球气候系统模式研究进展:CMIP计划实施近20年回顾[J].气象学报,2014,72(5):892-907.
[14] 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.
[15] Bellenger H,Guilyardi E,Leloup J,et al.ENSO representation in climate models:from CMIP3 to CMIP5[J].Climate Dynamics,2014,42(7-8):1999-2018.
[16] 郭彦,董文杰,任福民,等.CMIP5模式对中国年平均气温模拟及其与CMIP3模式的比较[J].气候变化研究进展,2013,9(3):181-186.
[17] 周天军,陈晓龙,董璐,等.Chinese Contribution to CMIP5:An Overview of Five Chinese Models' Performances[J].气象学报((英文版),2014,28(4):481-509.
[18] Rao J,Ren R C.Statistical Characteristics of ENSO Events in CMIP5 Models[J].大气和海洋科学快报(Atmospheric and Oceanic Science Letters),2014,7(6):546-552.
[19] 张芳,董敏,吴统文.CMIP5模式对ENSO现象的模拟能力评估[J].气象学报,2014(1):30-48.
[20] Trenberth K E.The definition of El Niňo[J].Bulletin of the American Meteorological Society,1997,78(12):2771-2777.
[21] Taylor K E.Summarizing multiple aspects of model performance in a single diagram[J].Journal of Geophysical Research Atmospheres,2001,106(D7):7183-7192.
[22] Gleckler P J,Taylor K E.Doutriaux C.Performance metrics for climate models[J].Journal of Geophysical Research Atmospheres,2008,113(D6):102-124.
[23] 蒋帅,江志红,李伟,等.CMIP5模式对中国极端气温及其变化趋势的模拟评估[J].气候变化研究进展,2017,13(1):11-24.
[24] 池建军,骆永军.Ni(n)o综合区对研究ENSO的效果评估[J].气象研究与应用,2009,30(1):8-11.
[25] 曹璐.两类ENSO事件的监测及大气的响应[D].南京:南京大学,2011.