Comparison Between GAMIL, and CAM2 on Interannual            Variability Simulation

YANG Junli; WANG Bin; GUO Yufu; WAN Hui; JI Zhongzhen

doi:10.1007/s00376-007-0082-1

Volume 24 Issue 1

Jan. 2007

Article Contents

Article > ADVANCES IN ATMOSPHERIC SCIENCES > 2007 > 24(1): 82-88

Comparison Between GAMIL, and CAM2 on Interannual Variability Simulation

1.
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029; Graduate University of the Chinese Academy of Sciences, Beijing 100039,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029; Graduate University of the Chinese Academy of Sciences, Beijing 100039,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

doi: 10.1007/s00376-007-0082-1

Abstract
References
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Abstract:
Recently, a new atmospheric general circulation model (GAMIL: Grid-point Atmospheric Model of IAP LASG) has been developed at the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), which is based on the Community Atmospheric Model Version 2 (CAM2) of the National Center for Atmospheric Research (NCAR). Since the two models have the same physical processes but different dynamical cores, the interannual variability simulation performances of the two models are compared. The ensemble approach is used to reduce model internal variability. In general, the simulation performances of the two models are similar. Both models have good performance in simulating total space-time variability and the Southern Oscillation Index. GAMIL performs better in the Eastern Asian winter circulation simulation than CAM2, and the model internal variability of GAMIL has a better response to external forcing than that of CAM2. These indicate that the improvement of the dynamic core is very important. It is also verified that there is less predictability in the middle and high latitudes than in the low latitudes.Recently, a new atmospheric general circulation model (GAMIL: Grid-point Atmospheric Model of IAP LASG) has been developed at the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), which is based on the Community Atmospheric Model Version 2 (CAM2) of the National Center for Atmospheric Research (NCAR). Since the two models have the same physical processes but different dynamical cores, the interannual variability simulation performances of the two models are compared. The ensemble approach is used to reduce model internal variability. In general, the simulation performances of the two models are similar. Both models have good performance in simulating total space-time variability and the Southern Oscillation Index. GAMIL performs better in the Eastern Asian winter circulation simulation than CAM2, and the model internal variability of GAMIL has a better response to external forcing than that of CAM2. These indicate that the improvement of the dynamic core is very important. It is also verified that there is less predictability in the middle and high latitudes than in the low latitudes.
- interannual variability,
- circulation,
- ensemble,
- GAMIL,
- CAM2
References

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