The East Asian summer monsoon （EASM） is a distinctive component of the Asian climate system and critically influences the economy and society of the region.To understand the ability of AGCMs in capturing the major f...The East Asian summer monsoon （EASM） is a distinctive component of the Asian climate system and critically influences the economy and society of the region.To understand the ability of AGCMs in capturing the major features of EASM,10 models that participated in Coupled Model Intercomparison Project/Atmospheric Model Intercomparison Project （CMIP5/AMIP）,which used observational SST and sea ice to drive AGCMs during the period 1979-2008,were evaluated by comparing with observations and AMIP Ⅱ simulations.The results indicated that the multi-model ensemble （MME） of CMIP5/AMIP captures the main characteristics of precipitation and monsoon circulation,and shows the best skill in EASM simulation,better than the AMIP Ⅱ MME.As for the Meiyu/Changma/Baiyu rainbelt,the intensity of rainfall is underestimated in all the models.The biases are caused by a weak western Pacific subtropical high （WPSH） and accompanying eastward southwesterly winds in group Ⅰ models,and by a too strong and west-extended WPSH as well as westerly winds in group Ⅱ models.Considerable systematic errors exist in the simulated seasonal migration of rainfall,and the notable northward jumps and rainfall persistence remain a challenge for all the models.However,the CMIP5/AMIP MME is skillful in simulating the western North Pacific monsoon index （WNPMI）.展开更多
根据1961~2005年长江流域气象站点的实测月降水量和气温数据,采用第5期全球耦合模式比较计划CMIP5（the Fifth Phase of Coupled Model Intercomparison Project）中24个全球气候模式（GCM）的模拟结果,通过计算模拟变量和观测变量平均...根据1961~2005年长江流域气象站点的实测月降水量和气温数据,采用第5期全球耦合模式比较计划CMIP5（the Fifth Phase of Coupled Model Intercomparison Project）中24个全球气候模式（GCM）的模拟结果,通过计算模拟变量和观测变量平均值的相对误差、归一化的均方根误差、时间和空间相关系数,采用M-K趋势分析方法,分别选用在长江流域模拟气温和降水较好的5个模式进行集合平均,从时间的演变规律和空间的分布特征两方面,检验该模式集合对长江流域模拟气温和降水的能力。研究结果表明：各个模式模拟气温的能力要明显好于模拟降水的能力,但模拟气温较好的模式模拟降水的能力并不一定突出;模式集合的结果表明：在时间尺度上,模式集合平均结果与观测值拟合程度较好,且模式集合的结果振荡幅度较观测值小;在空间尺度上,模式集合的空间分布趋势与观测值大致相同,说明采用的模式集合结果用于预估未来长江流域降水的时空分布特征和演变规律是可行的。展开更多
2000年后全球气温的增温率显著下降,全球进入变暖减缓期。本文基于CRU（Climatic Research Unit）观测资料,分析讨论了2000年后全球及欧亚中高纬度地区全球变暖的减缓特征,评估了CMIP5（Coupled Model Intercomparison Project Phase 5...2000年后全球气温的增温率显著下降,全球进入变暖减缓期。本文基于CRU（Climatic Research Unit）观测资料,分析讨论了2000年后全球及欧亚中高纬度地区全球变暖的减缓特征,评估了CMIP5（Coupled Model Intercomparison Project Phase 5）试验多模式对全球变暖减缓的模拟及未来气温变化预估。结果表明,2000年后全球陆地平均地面气温的增温率大幅下降至0.14°C（10 a）-1,仅为1976~1999年加速期增温率的一半。全球陆地13个区域中有9个地区的增温率小于2000年前,4个地区甚至出现了降温。其中以欧亚中高纬地区最为特殊。加速期（1976~1999年）增温率达到0.50°C（10 a）-1,为全球陆地最大,2000年后陡降至-0.17°C（10 a）-1,为全球最强降温区,为全球变暖的减缓贡献了49.13%。并且具有显著的季节依赖,减缓期冬季增温率下降了-2.68°C（10a）-1,而秋季升高了0.86°C（10 a）-1,呈现反位相变化特征。CMIP5多模式计划中仅BCC-CSM1.1在RCP2.6情景下和MRI-ESM1模式在RCP8.5下的模拟较好地预估了全球及欧亚中高纬地区在2000年后增温率的下降以及欧亚中高纬秋、冬温度的反位相变化特征。BCC-CSM1.1在RCP2.6情景下预估欧亚中高纬地区2012年后温度距平保持在1.2°C左右,2020年后跃至2°C附近振荡。而MRI-ESM1在RCP8.5情景下预估的欧亚中高纬度温度在2030年前一直维持几乎为零的增温率,之后迅速升高。展开更多
基金supported by the National High Technology Research and Development Program of China (Grant No. 2010AA012305)the General Project of the National Natural Science Foundation of China (Grant No. 41275108)+1 种基金the National Basic Research Program of China (Grant No. 2010CB950504)the Fundamental Research Funds for the Central Universities (Grant No. 2012YBXS27)
文摘The East Asian summer monsoon （EASM） is a distinctive component of the Asian climate system and critically influences the economy and society of the region.To understand the ability of AGCMs in capturing the major features of EASM,10 models that participated in Coupled Model Intercomparison Project/Atmospheric Model Intercomparison Project （CMIP5/AMIP）,which used observational SST and sea ice to drive AGCMs during the period 1979-2008,were evaluated by comparing with observations and AMIP Ⅱ simulations.The results indicated that the multi-model ensemble （MME） of CMIP5/AMIP captures the main characteristics of precipitation and monsoon circulation,and shows the best skill in EASM simulation,better than the AMIP Ⅱ MME.As for the Meiyu/Changma/Baiyu rainbelt,the intensity of rainfall is underestimated in all the models.The biases are caused by a weak western Pacific subtropical high （WPSH） and accompanying eastward southwesterly winds in group Ⅰ models,and by a too strong and west-extended WPSH as well as westerly winds in group Ⅱ models.Considerable systematic errors exist in the simulated seasonal migration of rainfall,and the notable northward jumps and rainfall persistence remain a challenge for all the models.However,the CMIP5/AMIP MME is skillful in simulating the western North Pacific monsoon index （WNPMI）.
文摘根据1961~2005年长江流域气象站点的实测月降水量和气温数据,采用第5期全球耦合模式比较计划CMIP5（the Fifth Phase of Coupled Model Intercomparison Project）中24个全球气候模式（GCM）的模拟结果,通过计算模拟变量和观测变量平均值的相对误差、归一化的均方根误差、时间和空间相关系数,采用M-K趋势分析方法,分别选用在长江流域模拟气温和降水较好的5个模式进行集合平均,从时间的演变规律和空间的分布特征两方面,检验该模式集合对长江流域模拟气温和降水的能力。研究结果表明：各个模式模拟气温的能力要明显好于模拟降水的能力,但模拟气温较好的模式模拟降水的能力并不一定突出;模式集合的结果表明：在时间尺度上,模式集合平均结果与观测值拟合程度较好,且模式集合的结果振荡幅度较观测值小;在空间尺度上,模式集合的空间分布趋势与观测值大致相同,说明采用的模式集合结果用于预估未来长江流域降水的时空分布特征和演变规律是可行的。
