采用线性回归法对长江源区2011—2021年土壤水分含量年际变化趋势进行分析,采用t检验法对长江源区2011—2021年平均气温和降水量变化与土壤水分含量变化间的相关性分析,并采用CMIP5全球气候模型的3种情景(RCP2.6、RCP4.5、RCP8.5)下耦合...采用线性回归法对长江源区2011—2021年土壤水分含量年际变化趋势进行分析,采用t检验法对长江源区2011—2021年平均气温和降水量变化与土壤水分含量变化间的相关性分析,并采用CMIP5全球气候模型的3种情景(RCP2.6、RCP4.5、RCP8.5)下耦合SWAT(Soil and Water Assessment Tool)水文模型,预测长江源区未来(2022—2100年)土壤水分年际、年内变化趋势.结果表明,长江源区2011—2021年土壤水分整体呈减少趋势,年平均气温和降水量与土壤水分变化具有明显的相关性(P<0.05). 3种RCPs气候情景下,21世纪末期(2081—2090年)土壤水分含量较21世纪中期(2041—2050年)减少,4—9月土壤水分占全年土壤水分占比较21世纪中期降低.土壤水分年际间波动较大,在50%~500%之间变动,土壤水分年内分布不均匀,1—5月土壤水分增加,6—12月土壤水分递减,1—2月土壤水分变化趋势相对平稳,年内各月份土壤水分含量差别较大.在3种RCPs气候情景下,长江源区未来土壤水分存在明显减少趋势,应加强长江源区土壤水系保护.展开更多
The Earth–Climate System Model(ECSM)is an important platform for multi-disciplinary and multi-sphere integration research,and its development is at the frontier of international geosciences,especially in the field of...The Earth–Climate System Model(ECSM)is an important platform for multi-disciplinary and multi-sphere integration research,and its development is at the frontier of international geosciences,especially in the field of global change.The research and development(R&D)of ECSM in China began in the 1980 s and have achieved great progress.In China,ECSMs are now mainly developed at the Chinese Academy of Sciences,ministries,and universities.Following a brief review of the development history of Chinese ECSMs,this paper summarized the technical characteristics of nine Chinese ECSMs participating in the Coupled Model Intercomparison Project Phase 6 and preliminarily assessed the basic performances of four Chinese models in simulating the global climate and the climate in East Asia.The projected changes of global precipitation and surface air temperature and the associated relationship with the equilibrium climate sensitivity under four shared socioeconomic path scenarios were also discussed.Finally,combined with the international situation,from the perspective of further improvement,eight directions were proposed for the future development of Chinese ECSMs.展开更多
The abilities of 12 earth system models（ESMs） from the Coupled Model Intercomparison Project Phase5（CMIP5） to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau（TP） were examine...The abilities of 12 earth system models（ESMs） from the Coupled Model Intercomparison Project Phase5（CMIP5） to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau（TP） were examined.The results show that most of the models tend to overestimate the observed leaf area index（LAI）and vegetation carbon above the ground,with the possible reasons being overestimation of photosynthesis and precipitation.The model simulations show a consistent increasing trend with observed LAI over most of the TP during the reference period of 1986-2005,while they fail to reproduce the downward trend around the headstream of the Yellow River shown in the observation due to their coarse resolutions.Three of the models：CCSM4,CESM1-BGC,and NorESM1-ME,which share the same vegetation model,show some common strengths and weaknesses in their simulations according to our analysis.The model ensemble indicates a reasonable spatial distribution but overestimated land coverage,with a significant decreasing trend（-1.48%per decade） for tree coverage and a slight increasing trend（0.58%per decade） for bare ground during the period 1950-2005.No significant sign of variation is found for grass.To quantify the relative performance of the models in representing the observed mean state,seasonal cycle,and interannual variability,a model ranking method was performed with respect to simulated LAI.INMCM4,bcc-csm-1.1m,MPI-ESM-LR,IPSL CM5A-LR,HadGEM2-ES,and CCSM4 were ranked as the best six models in reproducing vegetation dynamics among the 12 models.展开更多
文摘采用线性回归法对长江源区2011—2021年土壤水分含量年际变化趋势进行分析,采用t检验法对长江源区2011—2021年平均气温和降水量变化与土壤水分含量变化间的相关性分析,并采用CMIP5全球气候模型的3种情景(RCP2.6、RCP4.5、RCP8.5)下耦合SWAT(Soil and Water Assessment Tool)水文模型,预测长江源区未来(2022—2100年)土壤水分年际、年内变化趋势.结果表明,长江源区2011—2021年土壤水分整体呈减少趋势,年平均气温和降水量与土壤水分变化具有明显的相关性(P<0.05). 3种RCPs气候情景下,21世纪末期(2081—2090年)土壤水分含量较21世纪中期(2041—2050年)减少,4—9月土壤水分占全年土壤水分占比较21世纪中期降低.土壤水分年际间波动较大,在50%~500%之间变动,土壤水分年内分布不均匀,1—5月土壤水分增加,6—12月土壤水分递减,1—2月土壤水分变化趋势相对平稳,年内各月份土壤水分含量差别较大.在3种RCPs气候情景下,长江源区未来土壤水分存在明显减少趋势,应加强长江源区土壤水系保护.
基金Supported by the International Partnership Program of Chinese Academy of Sciences(134111KYSB20160031)National Natural Science Foundation of China(41875132).
文摘The Earth–Climate System Model(ECSM)is an important platform for multi-disciplinary and multi-sphere integration research,and its development is at the frontier of international geosciences,especially in the field of global change.The research and development(R&D)of ECSM in China began in the 1980 s and have achieved great progress.In China,ECSMs are now mainly developed at the Chinese Academy of Sciences,ministries,and universities.Following a brief review of the development history of Chinese ECSMs,this paper summarized the technical characteristics of nine Chinese ECSMs participating in the Coupled Model Intercomparison Project Phase 6 and preliminarily assessed the basic performances of four Chinese models in simulating the global climate and the climate in East Asia.The projected changes of global precipitation and surface air temperature and the associated relationship with the equilibrium climate sensitivity under four shared socioeconomic path scenarios were also discussed.Finally,combined with the international situation,from the perspective of further improvement,eight directions were proposed for the future development of Chinese ECSMs.
基金Supported by the National Basic Research and Development (973) Program of China(2010CB950503 and 2013CB956004)Research Fund for Climate Change of the China Meteorological Administration(CCSF201403)
文摘The abilities of 12 earth system models（ESMs） from the Coupled Model Intercomparison Project Phase5（CMIP5） to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau（TP） were examined.The results show that most of the models tend to overestimate the observed leaf area index（LAI）and vegetation carbon above the ground,with the possible reasons being overestimation of photosynthesis and precipitation.The model simulations show a consistent increasing trend with observed LAI over most of the TP during the reference period of 1986-2005,while they fail to reproduce the downward trend around the headstream of the Yellow River shown in the observation due to their coarse resolutions.Three of the models：CCSM4,CESM1-BGC,and NorESM1-ME,which share the same vegetation model,show some common strengths and weaknesses in their simulations according to our analysis.The model ensemble indicates a reasonable spatial distribution but overestimated land coverage,with a significant decreasing trend（-1.48%per decade） for tree coverage and a slight increasing trend（0.58%per decade） for bare ground during the period 1950-2005.No significant sign of variation is found for grass.To quantify the relative performance of the models in representing the observed mean state,seasonal cycle,and interannual variability,a model ranking method was performed with respect to simulated LAI.INMCM4,bcc-csm-1.1m,MPI-ESM-LR,IPSL CM5A-LR,HadGEM2-ES,and CCSM4 were ranked as the best six models in reproducing vegetation dynamics among the 12 models.
