Since no consensus has been reached in previous studies about how the summer climate in China will evolve in the first half of the 21st century, this issue is addressed here through sensitivity experiments by forcing ...Since no consensus has been reached in previous studies about how the summer climate in China will evolve in the first half of the 21st century, this issue is addressed here through sensitivity experiments by forcing an atmospheric general circulation model (AGCM), the Geophysical Fluid Dynamics Laboratory (GFDL)'s Atmospheric Model Version 2.0 (AM2) with projected sea surface temperature (SST) trend. A total of two SST trends from the Intergovernmental Panels on Climate Change (IPCC) Special Report on Emissions Scenario (SRES) AlB are used. The two trends are from two coupled climate system models, the National Center for Atmospheric Research (NCAR) Community Climate System Model Version 3.0 (CCSM3) and the GFDL Climate Model Version 2.0 (CM2), respectively. Results consistently suggest a substantial warming and drying trend over much of China, with a surface air temperature increase of 1.0-2.0℃ and a 10%-20% decrease in rainfall. Exceptions are the areas from northwestern China to western North China as well as the southern Tibetan Plateau, which are projected to be wetter with a rainfall anomaly percentage increase of 10%-50%. The drying in eastern North China has not been documented to date but appears to be reasonable. Physically, it is attributed to anomalous northeasterly winds at the rear of a low-level cyclone over the South China Sea, the Philippines and the subtropical western North Pacific. These conditions, which govern the climate of eastern China, are forced by the northward shift of convection over warm waters due to additional warming.展开更多
Climate prediction using a coupled model with a one-tier scheme is an important research direction. In this study, based on 1974- 2001 hindcasts obtained from the "Development of a European Multimodel Ensemble sy...Climate prediction using a coupled model with a one-tier scheme is an important research direction. In this study, based on 1974- 2001 hindcasts obtained from the "Development of a European Multimodel Ensemble system for seasonal to inTERannual prediction" (DEMETER) project, the capability of coupled general circulation models (CGCMs) to predict six climatic factors that have a close relationship with the western North Pacific typhoon activity is investigated over summer (June-October). Results indicate that all six DEMETER CGCMs well predict the six factors. Using the statistical relationship between these six factors and the typhoon frequency, the ability of the CGCMs to predict typhoon frequency is further explored. It is found that the six CGCMs also well predict the variability in typhoon frequency. Comparison analysis shows that the prediction skill of the statistical downscaling method is much better than that of the raw CGCMs. In addition, the six-model ensemble has the best prediction performance. This study suggests that combining a multi-model ensemble and statistical downscaling greatly improves the CGCM prediction skill, and will be an important research direction for typhoon prediction.展开更多
基金supported by the National Natural Science Foundation of China under Grant Nos. 90711004 and 40775053"One Hundred Talent Plan" of the Chinese Academy of Sciences
文摘Since no consensus has been reached in previous studies about how the summer climate in China will evolve in the first half of the 21st century, this issue is addressed here through sensitivity experiments by forcing an atmospheric general circulation model (AGCM), the Geophysical Fluid Dynamics Laboratory (GFDL)'s Atmospheric Model Version 2.0 (AM2) with projected sea surface temperature (SST) trend. A total of two SST trends from the Intergovernmental Panels on Climate Change (IPCC) Special Report on Emissions Scenario (SRES) AlB are used. The two trends are from two coupled climate system models, the National Center for Atmospheric Research (NCAR) Community Climate System Model Version 3.0 (CCSM3) and the GFDL Climate Model Version 2.0 (CM2), respectively. Results consistently suggest a substantial warming and drying trend over much of China, with a surface air temperature increase of 1.0-2.0℃ and a 10%-20% decrease in rainfall. Exceptions are the areas from northwestern China to western North China as well as the southern Tibetan Plateau, which are projected to be wetter with a rainfall anomaly percentage increase of 10%-50%. The drying in eastern North China has not been documented to date but appears to be reasonable. Physically, it is attributed to anomalous northeasterly winds at the rear of a low-level cyclone over the South China Sea, the Philippines and the subtropical western North Pacific. These conditions, which govern the climate of eastern China, are forced by the northward shift of convection over warm waters due to additional warming.
基金supported by the Special Fund forPublic Welfare Industry (meteorology) (GYHY200906018)the Key Program of the Chinese Academy of Sciences (KZCX2-YW-Q03-3)+1 种基金the National Basic Research Program of China (2009CB421406)the Norwegian Research Council Project "East-Asia DecCen."
文摘Climate prediction using a coupled model with a one-tier scheme is an important research direction. In this study, based on 1974- 2001 hindcasts obtained from the "Development of a European Multimodel Ensemble system for seasonal to inTERannual prediction" (DEMETER) project, the capability of coupled general circulation models (CGCMs) to predict six climatic factors that have a close relationship with the western North Pacific typhoon activity is investigated over summer (June-October). Results indicate that all six DEMETER CGCMs well predict the six factors. Using the statistical relationship between these six factors and the typhoon frequency, the ability of the CGCMs to predict typhoon frequency is further explored. It is found that the six CGCMs also well predict the variability in typhoon frequency. Comparison analysis shows that the prediction skill of the statistical downscaling method is much better than that of the raw CGCMs. In addition, the six-model ensemble has the best prediction performance. This study suggests that combining a multi-model ensemble and statistical downscaling greatly improves the CGCM prediction skill, and will be an important research direction for typhoon prediction.