Advanced Search
Article Contents

Performance of a Reconfigured Atmospheric General Circulation Model at Low Resolution


doi: 10.1007/s00376-007-0712-7

  • Paleoclimate simulations usually require model runs over a very long time. The fast integration version of a state-of-the-art general circulation model (GCM), which shares the same physical and dynamical processes but with reduced horizontal resolution and increased time step, is usually developed. In this study, we configure a fast version of an atmospheric GCM (AGCM), the Grid Atmospheric Model of IAP/LASG (Institute of Atmospheric Physics/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics), at low resolution (GAMIL-L, hereafter), and compare the simulation results with the NCEP/NCAR reanalysis and other data to examine its performance. GAMIL-L, which is derived from the original GAMIL, is a finite difference AGCM with 72×40 grids in longitude and latitude and 26 vertical levels. To validate the simulated climatology and variability, two runs were achieved. One was a 60-year control run with fixed climatological monthly sea surface temperature (SST) forcing, and the other was a 50-yr (1950--2000) integration with observational time-varying monthly SST forcing. Comparisons between these two cases and the reanalysis, including intra-seasonal and inter-annual variability are also presented. In addition, the differences between GAMIL-L and the original version of GAMIL are also investigated. The results show that GAMIL-L can capture most of the large-scale dynamical features of the atmosphere, especially in the tropics and mid latitudes, although a few deficiencies exist, such as the underestimated Hadley cell and thereby the weak strength of the Asia summer monsoon. However, the simulated mean states over high latitudes, especially over the polar regions, are not acceptable. Apart from dynamics, the thermodynamic features mainly depend upon the physical parameterization schemes. Since the physical package of GAMIL-L is exactly the same as the original high-resolution version of GAMIL, in which the NCAR Community Atmosphere Model (CAM2) physical package was used, there are only small differences between them in the precipitation and temperature fields. Because our goal is to develop a fast-running AGCM and employ it in the coupled climate system model of IAP/LASG for paleoclimate studies such as ENSO and Australia-Asia monsoon, particular attention has been paid to the model performances in the tropics. More model validations, such as those ran for the Southern Oscillation and South Asia monsoon, indicate that GAMIL-L is reasonably competent and valuable in this regard.
  • [1] SUN Shufen, YAN Jinfeng, XIA Nan, SUN Changhai, 2007: Development of a Model for Water and Heat Exchange Between the Atmosphere and a Water Body, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 927-938.  doi: 10.1007/s00376-007-0927-7
    [2] Tido SEMMLER, Thomas JUNG, Marta A. KASPER, Soumia SERRAR, 2018: Using NWP to Assess the Influence of the Arctic Atmosphere on Midlatitude Weather and Climate, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 5-13.  doi: 10.1007/s00376-017-6290-4
    [3] JIA Xiaolong, LI Chongyin, LING Jian, Chidong ZHANG, 2008: Impacts of a GCM's Resolution on MJO Simulation, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 139-156.  doi: 10.1007/s00376-008-0139-9
    [4] Donglin GUO, Huijun WANG, 2016: Comparison of a Very-fine-resolution GCM with RCM Dynamical Downscaling in Simulating Climate in China, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 559-570.  doi: 10.1007/s00376-015-5147-y
    [5] Yang Xiaosong, Lin Zhaohui, Dai Yongjiu, Guo Yufu, 2001: Validation of IAP94 Land Surface Model over the Huaihe River Basin with HUBEX Field Experiment Data, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 139-154.  doi: 10.1007/s00376-001-0009-1
    [6] LI Qian, SUN Shufen, DAI Qiudan, 2009: The Numerical Scheme Development of a Simplified Frozen Soil Model, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 940-950.  doi: 10.1007/s00376-009-7174-z
    [7] CAO Lijuan, DONG Wenjie, XU Yinlong, ZHANG Yong, Michael SPARROW, 2007: Validating the Runoff from the PRECIS Model Using a Large-Scale Routing Model, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 855-862.  doi: 10.1007/s00376-007-0855-6
    [8] SUN Yang, WANG Yuesi, XIU Tianyang, WANG Yinghong, XU Xin, 2007: Establishment and Evaluation of a Method for Analyzing Atmospheric Volatile Organic Compounds, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 679-687.  doi: 10.1007/s00376-007-0679-4
    [9] CHEN Hua, GUO Jing, XIONG Wei, GUO Shenglian, Chong-Yu XU, 2010: Downscaling GCMs Using the Smooth Support Vector Machine Method to Predict Daily Precipitation in the Hanjiang Basin, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 274-284.  doi: 10.1007/s00376-009-8071-1
    [10] Akio KITOH, Masahiro HOSAKA, Yukimasa ADACHI, Kenji KAMIGUCHI, 2005: Future Projections of Precipitation Characteristics in East Asia Simulated by the MRI CGCM2, ADVANCES IN ATMOSPHERIC SCIENCES, 22, 467-478.  doi: 10.1007/BF02918481
    [11] CHEN Feng, and XIE Zhenghui, 2013: An evaluation of RegCM3_CRES for regional climate modeling in China, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1187-1200.  doi: 10.1007/s00376-012-2114-8
    [12] Yu Rucong, Li Wei, Zhang Xuehong, LiuYimin, Yu Yongqiang, Liu Hailong, Zhou Tianjun, 2000: Climatic Features Related to Eastern China Summer Rainfalls in the NCAR CCM3, ADVANCES IN ATMOSPHERIC SCIENCES, 17, 503-518.  doi: 10.1007/s00376-000-0014-9
    [13] WU Tongwen, WU Guoxiong, 2004: An Empirical Formula to Compute Snow Cover Fraction in GCMs, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 529-535.  doi: 10.1007/BF02915720
    [14] YAN Li, WANG Panxing, YU Yongqiang, LI Lijuan, WANG Bin, 2010: Potential Predictability of Sea Surface Temperature in a Coupled Ocean--Atmosphere GCM, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 921-936.  doi: 10.1007/s00376-009-9062-y
    [15] WU Tongwen, WANG Zaizhi, LIU Yimin, YU Rucong, WU Guoxiong, 2004: An Evaluation of the Effects of Cloud Parameterization in the R42L9 GCM, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 153-162.  doi: 10.1007/BF02915701
    [16] Boyin HUANG, ZHU Jiang, YANG Haijun, 2014: Mechanisms of Atlantic Meridional Overturning Circulation (AMOC) Variability in a Coupled Ocean-Atmosphere GCM, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 241-251.  doi: 10.1007/s00376-013-3021-3
    [17] Liu Hui, Zhang Xuehong, 1999: A Study of SST Warming Trend in the Western Equatorial Pacific in a Coupled Ocean-Atmosphere-Land GCM, ADVANCES IN ATMOSPHERIC SCIENCES, 16, 24-30.  doi: 10.1007/s00376-999-0002-7
    [18] HUANG Ying, QIAN Yongfu, 2007: Analysis of the Simulated Climatic Characters of the South Asia High with a Flexible Coupled Ocean--Atmosphere GCM, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 136-146.  doi: 10.1007/s00376-007-0136-4
    [19] SUN Jianqi, Joong Bae AHN, 2011: A GCM-Based Forecasting Model for the Landfall of Tropical Cyclones in China, ADVANCES IN ATMOSPHERIC SCIENCES, 28, 1049-1055.  doi: 10.1007/s00376-011-0122-8
    [20] Dai Yongjiu, Xue Feng, Zeng Qingcun, 1998: A Land Surface Model (IAP94) for Climate Studies Part II: Implementation and Preliminary Results of Coupled Model with IAP GCM, ADVANCES IN ATMOSPHERIC SCIENCES, 15, 47-62.  doi: 10.1007/s00376-998-0017-5

Get Citation+

Export:  

Share Article

Manuscript History

Manuscript received: 10 July 2007
Manuscript revised: 10 July 2007
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Performance of a Reconfigured Atmospheric General Circulation Model at Low Resolution

  • 1. Department of Atmospheric Sciences, School of Physics, Peking University, Beijing 100871,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,Department of Atmospheric Sciences, School of Physics, Peking University, Beijing 100871,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,\\[.1cm] 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

Abstract: Paleoclimate simulations usually require model runs over a very long time. The fast integration version of a state-of-the-art general circulation model (GCM), which shares the same physical and dynamical processes but with reduced horizontal resolution and increased time step, is usually developed. In this study, we configure a fast version of an atmospheric GCM (AGCM), the Grid Atmospheric Model of IAP/LASG (Institute of Atmospheric Physics/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics), at low resolution (GAMIL-L, hereafter), and compare the simulation results with the NCEP/NCAR reanalysis and other data to examine its performance. GAMIL-L, which is derived from the original GAMIL, is a finite difference AGCM with 72×40 grids in longitude and latitude and 26 vertical levels. To validate the simulated climatology and variability, two runs were achieved. One was a 60-year control run with fixed climatological monthly sea surface temperature (SST) forcing, and the other was a 50-yr (1950--2000) integration with observational time-varying monthly SST forcing. Comparisons between these two cases and the reanalysis, including intra-seasonal and inter-annual variability are also presented. In addition, the differences between GAMIL-L and the original version of GAMIL are also investigated. The results show that GAMIL-L can capture most of the large-scale dynamical features of the atmosphere, especially in the tropics and mid latitudes, although a few deficiencies exist, such as the underestimated Hadley cell and thereby the weak strength of the Asia summer monsoon. However, the simulated mean states over high latitudes, especially over the polar regions, are not acceptable. Apart from dynamics, the thermodynamic features mainly depend upon the physical parameterization schemes. Since the physical package of GAMIL-L is exactly the same as the original high-resolution version of GAMIL, in which the NCAR Community Atmosphere Model (CAM2) physical package was used, there are only small differences between them in the precipitation and temperature fields. Because our goal is to develop a fast-running AGCM and employ it in the coupled climate system model of IAP/LASG for paleoclimate studies such as ENSO and Australia-Asia monsoon, particular attention has been paid to the model performances in the tropics. More model validations, such as those ran for the Southern Oscillation and South Asia monsoon, indicate that GAMIL-L is reasonably competent and valuable in this regard.

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return