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Volume 25 Issue 4

Jul.  2008

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2008 >  25(4): 619-631

An Updated Coupled Model for Land-Atmosphere Interaction. Part I: Simulations of Physical Processes

  • 1.

    State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029; National Climate Center, Beijing 100081; Graduate University of Chinese Ac;National Climate Center, Beijing 100081;START Regional Research Center for Temperate East Asia, 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


doi: 10.1007/s00376-008-0619-y

  • A new two-way land-atmosphere interaction model (R42_AVIM) is fulfilled by coupling the spectral atmospheric model (SAMIL_R42L9) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP/CAS) with the land surface model, Atmosphere-Vegetation-Interaction-Model (AVIM). In this coupled model, physical and biological components of AVIM are both included. Climate base state and land surface physical fluxes simulated by R42_AVIM are analyzed and compared with the results of R42_SSIB [which is coupled by SAMIL_R42L9 and Simplified Simple Biosphere (SSIB) models]. The results show the performance of the new model is closer to the observations. It can basically guarantee that the land surface energy budget is balanced, and can simulate June--July--August (JJA) and December-January-February (DJF) land surface air temperature, sensible heat flux, latent heat flux, precipitation, sea level pressure and other variables reasonably well. Compared with R42_SSIB, there are obvious improvements in the JJA simulations of surface air temperature and surface fluxes. Thus, this land-atmosphere coupled model will offer a good experiment platform for land-atmosphere interaction research.
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    [2] 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
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    [5] Chujie GAO, Haishan CHEN, Shanlei SUN, Bei XU, Victor ONGOMA, Siguang ZHU, Hedi MA, Xing LI, 2018: Regional Features and Seasonality of Land-Atmosphere Coupling over Eastern China, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 689-701.  doi: 10.1007/s00376-017-7140-0
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    [10] WANG Gaili, LIU Liping, DING Yuanyuan, 2012: Improvement of Radar Quantitative Precipitation Estimation Based on Real-Time Adjustments to Z--R Relationships and Inverse Distance Weighting Correction Schemes, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 575-584.  doi: 10.1007/s00376-011-1139-8
    [11] CHEN Haoming, YUAN Weihua, LI Jian, YU Rucong, 2012: A Possible Cause for Different Diurnal Variations of Warm Season Rainfall as Shown in Station Observations and TRMM 3B42 Data over the Southeastern Tibetan Plateau, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 193-200.  doi: 10.1007/s00376-011-0218-1
    [12] Rong KONG, Ming XUE, Edward R. MANSELL, Chengsi LIU, Alexandre O. FIERRO, 2024: Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI 3DVar, EnKF, and Hybrid En3DVar for the Analysis and Short-Term Forecast of a Supercell Storm Case, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 263-277.  doi: 10.1007/s00376-023-2340-2
    [13] GAO Rong, DONG Wenjie, WEI Zhigang, 2008: Simulation and Analysis of China Climate Using Two-Way Interactive Atmosphere-Vegetation Model (RIEMS-AVIM), ADVANCES IN ATMOSPHERIC SCIENCES, 25, 1085-1097.  doi: 10.1007/s00376-008-1085-2
    [14] SHI Xiaoying, MAO Jiafu, WANG Yingping, DAI Yongjiu, TANG Xuli, 2011: Coupling a Terrestrial Biogeochemical Model to the Common Land Model, ADVANCES IN ATMOSPHERIC SCIENCES, 28, 1129-1142.  doi: 10.1007/s00376-010-0131-z
    [15] Liu Hui, Wu Guoxiong, 1997: Impacts of Land Surface on Climate of July and Onset of Summer Monsoon: A Study with an AGCM plus SSiB, ADVANCES IN ATMOSPHERIC SCIENCES, 14, 289-308.  doi: 10.1007/s00376-997-0051-8
    [16] LU Daren, YI Fan, XU Jiyao, 2004: Advances in Studies of the Middle and Upper Atmosphere and Their Coupling with the Lower Atmosphere, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 361-368.  doi: 10.1007/BF02915564
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    [18] Ji jinjun, 1989: Atmosphere-Ocean Coupling Schemes in a One-Dimensional Climate Model, ADVANCES IN ATMOSPHERIC SCIENCES, 6, 275-288.  doi: 10.1007/BF02661534
    [19] Liu Hui, Jin Xiangze, Zhang Xuehong, Wu Guoxiong, 1996: A Coupling Experiment of an Atmosphere and an Ocean Model with a Monthly Anomaly Exchange Schem, ADVANCES IN ATMOSPHERIC SCIENCES, 13, 133-146.  doi: 10.1007/BF02656857
    [20] FENG Lin, WU Dexing, LIN Xiaopei, MENG Xiangfeng, 2010: The Effect of Regional Ocean-Atmosphere Coupling on the Long-term Variability in the Pacific Ocean, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 393-402.  doi: 10.1007/s00376-009-8195-3
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    • Manuscript History

    Manuscript received: 10 July 2008
    Manuscript revised: 10 July 2008
    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

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    An Updated Coupled Model for Land-Atmosphere Interaction. Part I: Simulations of Physical Processes

    • 1. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029; National Climate Center, Beijing 100081; Graduate University of Chinese Ac;National Climate Center, Beijing 100081;START Regional Research Center for Temperate East Asia, 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
    • Manuscript received: 2008-07-10
    • Manuscript revised: 2008-07-10

    Abstract: A new two-way land-atmosphere interaction model (R42_AVIM) is fulfilled by coupling the spectral atmospheric model (SAMIL_R42L9) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP/CAS) with the land surface model, Atmosphere-Vegetation-Interaction-Model (AVIM). In this coupled model, physical and biological components of AVIM are both included. Climate base state and land surface physical fluxes simulated by R42_AVIM are analyzed and compared with the results of R42_SSIB [which is coupled by SAMIL_R42L9 and Simplified Simple Biosphere (SSIB) models]. The results show the performance of the new model is closer to the observations. It can basically guarantee that the land surface energy budget is balanced, and can simulate June--July--August (JJA) and December-January-February (DJF) land surface air temperature, sensible heat flux, latent heat flux, precipitation, sea level pressure and other variables reasonably well. Compared with R42_SSIB, there are obvious improvements in the JJA simulations of surface air temperature and surface fluxes. Thus, this land-atmosphere coupled model will offer a good experiment platform for land-atmosphere interaction research.

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