Regional climate models (RCMs) have the potential for more detailed surface characteristic and mesoscale modeling results than general circulation models (GCMs).These advantages have drawn significant focus on RCM dev...Regional climate models (RCMs) have the potential for more detailed surface characteristic and mesoscale modeling results than general circulation models (GCMs).These advantages have drawn significant focus on RCM development in East Asia.The Regional Integrated Environment Modeling System,version 2.0 (RIEMS2.0),has been developed from an earlier RCM,RIEMS1.0,by the Key Laboratory of Regional ClimateEnvironment for Temperate East Asia (RCE-TEA) and Nanjing University.A numerical experiment covering 1979 to 2008 (simulation duration from 1 January 1978 to 31 December 2008) with a 50-km spatial resolution was performed to test the ability of RIEMS2.0 to simulate long-term climate and climate changes in East Asia and to provide a basis for further development and applications.The simulated surface air temperature (SAT) was compared with observed meteorological data.The results show that RIEMS2.0 simulation reproduced the SAT spatial distribution in East Asia but that it was underestimated.The simulated 30-year averaged SAT was approximately 2.0°C lower than the observed SAT.The annual and interannual variations in the averaged SAT and their anomalies were both well reproduced in the model.A further analysis of three sub-regions representing different longitudinal ranges showed that there is a good correlation and consistency between the simulated results and the observed data.The annual variations,interannual variations for the averaged SAT,and the anomalies in the three sub-regions were also captured well by the model.In summary,RIEMS2.0 shows stability and does well both in simulating the long-term SAT in East Asia and in expressing sub-regional characteristics.展开更多
The four-dimensional empirical orthogonal function (4D-EOF), which in reality is a simple combination of three-dimensional EOF (3D-EOF) and extended EOF (EEOF), is put forward in this paper to test the ability o...The four-dimensional empirical orthogonal function (4D-EOF), which in reality is a simple combination of three-dimensional EOF (3D-EOF) and extended EOF (EEOF), is put forward in this paper to test the ability of numerical model to simulate climate and its change. The 4D-EOF analysis is able to reveal not only the horizontal characteristic pattern of analyzed variable, and its corresponding annual and inter-annual variations, but also the vertical structural characteristics. The method suggested is then used to analyze the monthly mean 100-, 500-, 700-, and 1000-hPa geopotential height fields (4941 grids and grid spacing 60 km) and their anomaly fields in 1989-1998 simulated by the MM5V3 from the RMIP (Regional Climate Model Inter-comparison Project for East Asia)-II, as well as their counterparts (used as the observed fields) from the NCEP/NCAR re-analysis dataset in the same period. The ability of MM5V3 in simulating East Asian climate and its change is tested by comparing the 4D-EOF analysis results of the simulated and observed datasets. The comparative analyzed results show that the horizontal pattern of the first eigenvector of the observed monthly mean geopotential height fields and its vertical equivalent barotropic feature were well simulated; the simulations of the first two eigenvectors of the observed monthly mean geopotential height anomaly fields were also successful for their horizontal abnormal distributions and significant equivalent barotropic features in the vertical were well reproduced; and furthermore, the observed characteristics, such as the variation with height, the annual and inter-annual variations of the monthly mean geopotential height/anomaly fields were also well reflected in the simulation. Therefore, the 4D-EOF is able to comprehensively test numerical model's ability of simulating the climate and its change, and the simulation ability of MM5V3 for the climate and its change in East Asia in the 1990s was satisfactory.展开更多
基金supported by the National Basic Research Program of China under Grant 2011CB952003the Chinese Academy of Sciences Strategic Priority Program under Grant XDA05090206the National Natural Science Foundation of China under Grant 40975053
文摘Regional climate models (RCMs) have the potential for more detailed surface characteristic and mesoscale modeling results than general circulation models (GCMs).These advantages have drawn significant focus on RCM development in East Asia.The Regional Integrated Environment Modeling System,version 2.0 (RIEMS2.0),has been developed from an earlier RCM,RIEMS1.0,by the Key Laboratory of Regional ClimateEnvironment for Temperate East Asia (RCE-TEA) and Nanjing University.A numerical experiment covering 1979 to 2008 (simulation duration from 1 January 1978 to 31 December 2008) with a 50-km spatial resolution was performed to test the ability of RIEMS2.0 to simulate long-term climate and climate changes in East Asia and to provide a basis for further development and applications.The simulated surface air temperature (SAT) was compared with observed meteorological data.The results show that RIEMS2.0 simulation reproduced the SAT spatial distribution in East Asia but that it was underestimated.The simulated 30-year averaged SAT was approximately 2.0°C lower than the observed SAT.The annual and interannual variations in the averaged SAT and their anomalies were both well reproduced in the model.A further analysis of three sub-regions representing different longitudinal ranges showed that there is a good correlation and consistency between the simulated results and the observed data.The annual variations,interannual variations for the averaged SAT,and the anomalies in the three sub-regions were also captured well by the model.In summary,RIEMS2.0 shows stability and does well both in simulating the long-term SAT in East Asia and in expressing sub-regional characteristics.
基金the National Key Developing Program for Basic Science Project under Grant No. 2006CB400500China Postdoctoral Science Foundation under Grant No. 20060400492.
文摘The four-dimensional empirical orthogonal function (4D-EOF), which in reality is a simple combination of three-dimensional EOF (3D-EOF) and extended EOF (EEOF), is put forward in this paper to test the ability of numerical model to simulate climate and its change. The 4D-EOF analysis is able to reveal not only the horizontal characteristic pattern of analyzed variable, and its corresponding annual and inter-annual variations, but also the vertical structural characteristics. The method suggested is then used to analyze the monthly mean 100-, 500-, 700-, and 1000-hPa geopotential height fields (4941 grids and grid spacing 60 km) and their anomaly fields in 1989-1998 simulated by the MM5V3 from the RMIP (Regional Climate Model Inter-comparison Project for East Asia)-II, as well as their counterparts (used as the observed fields) from the NCEP/NCAR re-analysis dataset in the same period. The ability of MM5V3 in simulating East Asian climate and its change is tested by comparing the 4D-EOF analysis results of the simulated and observed datasets. The comparative analyzed results show that the horizontal pattern of the first eigenvector of the observed monthly mean geopotential height fields and its vertical equivalent barotropic feature were well simulated; the simulations of the first two eigenvectors of the observed monthly mean geopotential height anomaly fields were also successful for their horizontal abnormal distributions and significant equivalent barotropic features in the vertical were well reproduced; and furthermore, the observed characteristics, such as the variation with height, the annual and inter-annual variations of the monthly mean geopotential height/anomaly fields were also well reflected in the simulation. Therefore, the 4D-EOF is able to comprehensively test numerical model's ability of simulating the climate and its change, and the simulation ability of MM5V3 for the climate and its change in East Asia in the 1990s was satisfactory.