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Comparison Between GAMIL, and CAM2 on Interannual Variability Simulation


doi: 10.1007/s00376-007-0082-1

  • 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.
  • [1] WU Zhiwei, LI Jianping, 2008: Prediction of the Asian-Australian Monsoon Interannual Variations with the Grid-Point Atmospheric Model of IAP LASG (GAMIL), ADVANCES IN ATMOSPHERIC SCIENCES, 25, 387-394.  doi: 0.1007/s00376-008-0387-8
    [2] Feng ZHANG, Xin-Zhong LIANG, ZENG Qingcun, Yu GU, and Shenjian SU, 2013: Cloud-Aerosol-Radiation (CAR) ensemble monitoring system: Overall accuracy and efficiency, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 955-973.  doi: 10.1007/s00376-012-2171-z
    [3] Yu ZHAO, Anmin DUAN, Guoxiong WU, 2018: Interannual Variability of Late-spring Circulation and Diabatic Heating over the Tibetan Plateau Associated with Indian Ocean Forcing, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 927-941.  doi: 10.1007/s00376-018-7217-4
    [4] HU Ruijin, LIU Qinyu, WANG Qi, J. Stuart GODFREY, MENG Xiangfeng, 2005: The Shallow Meridional Overturning Circulation in the Northern Indian Ocean and Its Interannual Variability, ADVANCES IN ATMOSPHERIC SCIENCES, 22, 220-229.  doi: 10.1007/BF02918511
    [5] Wu Aiming, Ni Yunqi, 1997: The Influence of Tibetan Plateau on the Interannual Variability of Atmospheric Circulation over Tropical Pacific, ADVANCES IN ATMOSPHERIC SCIENCES, 14, 69-80.  doi: 10.1007/s00376-997-0045-6
    [6] LIU Xiangwen, WU Tongwen, YANG Song, LI Qiaoping, CHENG Yanjie, LIANG Xiaoyun, FANG Yongjie, JIE Weihua, NIE Suping, 2014: Relationships between Interannual and Intraseasonal Variations of the Asian-Western Pacific Summer Monsoon Hindcasted by BCC_CSM1.1(m), ADVANCES IN ATMOSPHERIC SCIENCES, 31, 1051-1064.  doi: 10.1007/s00376-014-3192-6
    [7] NIU Ning, LI Jianping, 2008: Interannual Variability of Autumn Precipitation over South China and its Relation to Atmospheric Circulation and SST Anomalies, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 117-125.  doi: 10.1007/s00376-008-0117-2
    [8] Ya GAO, Huijun WANG, Dong CHEN, 2017: Interdecadal Variations of the South Asian Summer Monsoon Circulation Variability and the Associated Sea Surface Temperatures on Interannual Scales, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 816-832.  doi: 10.1007/ s00376-017-6246-8
    [9] LI Lijuan, WANG Bin, Yuqing WANG, Hui WAN, 2007: Improvements in Climate Simulation with Modifications to the Tiedtke Convective Parameterization in the Grid-Point Atmospheric Model of IAP LASG (GAMIL), ADVANCES IN ATMOSPHERIC SCIENCES, 24, 323-335.  doi: 10.1007/s00376-007-0323-3
    [10] LI Lijuan, Yuqing WANG, WANG Bin, ZHOU Tianjun, 2008: Sensitivity of the Grid-point Atmospheric Model of IAP LASG (GAMIL1.1.0) Climate Simulations to Cloud Droplet Effective Radius and Liquid Water Path, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 529-540.  doi: 10.1007/s00376-008-0529-z
    [11] Xinyu LI, Riyu LU, Gen LI, 2021: Different Configurations of Interannual Variability of the Western North Pacific Subtropical High and East Asian Westerly Jet in Summer, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 931-942.  doi: 10.1007/s00376-021-0339-0
    [12] Jong-Kil PARK, LU Riyu, LI Chaofan, Eun Byul KIM, 2012: Interannual Variation of Tropical Night Frequency in Beijing and Associated Large-Scale Circulation Background, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 295-306.  doi: 10.1007/s00376-011-1141-1
    [13] Riyu LU, Saadia HINA, Xiaowei HONG, 2020: Upper- and Lower-tropospheric Circulation Anomalies Associated with Interannual Variation of Pakistan Rainfall during Summer, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 1179-1190.  doi: 10.1007/s00376-020-0137-0
    [14] CHEN Xiao, YAN Youfang, CHENG Xuhua, QI Yiquan, 2013: Performances of Seven Datasets in Presenting the Upper Ocean Heat Content in the South China Sea, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1331-1342.  doi: 10.1007/s00376-013-2132-1
    [15] XUE Feng, ZENG Qingcun, HUANG Ronghui, LI Chongyin, LU Riyu, ZHOU Tianjun, 2015: Recent Advances in Monsoon Studies in China, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 206-229.  doi: 10.1007/s00376-014-0015-8
    [16] HONG Bo, WANG Dongxiao, 2008: Sensitivity Study of the Seasonal Mean Circulation in the Northern South China Sea, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 824-840.  doi: 10.1007/s00376-008-0824-8
    [17] YUAN Fang, CHEN Wen, ZHOU Wen, 2012: Analysis of the Role Played by Circulation in the Persistent Precipitation over South China in June 2010, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 769-781.  doi: 10.1007/s00376-012-2018-7
    [18] Ren Baohua, Huang Ronghui, 2002: 10-25-Day Intraseasonal Variations of Convection and Circulation Associated with Thermal State of the Western Pacific Warm Pool during Boreal Summer, ADVANCES IN ATMOSPHERIC SCIENCES, 19, 321-336.  doi: 10.1007/s00376-002-0025-9
    [19] REN Baohua, HUANG Ronghui, 2003: 30-60-day Oscillations of Convection and Circulation Associated with the Thermal State of the Western Pacific Warm Pool during Boreal Summer, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 781-793.  doi: 10.1007/BF02915403
    [20] Li Weiping, Theo Chidiezie Chineke, Liu Xin, Wu Guoxiong, 2001: Atmospheric Diabatic Heating and Summertime Circulation in Asia-Africa Area, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 257-269.  doi: 10.1007/s00376-001-0018-0

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Manuscript History

Manuscript received: 10 January 2007
Manuscript revised: 10 January 2007
通讯作者: 陈斌, bchen63@163.com
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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

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.

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