Advanced Search
Article Contents

An Updated Coupled Model for Land-Atmosphere Interaction. Part II: Simulations of Biological Processes


doi: 10.1007/s00376-008-0632-1

  • In Part I, the authors succeeded in 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) and analyzed the climate basic state and land surface physical fluxes simulated by R42\_AVIM. In this Part II, we further evaluate the simulated results of the biological processes, including leaf area index (LAI), biomass and net primary productivity (NPP) etc. Results indicate that R42\_AVIM can simulate the global distribution of LAI and has good consistency with the monthly mean LAI provided by Max Planck Institute for Meteorology. The simulated biomass corresponds reasonably to the vegetation classifications. In addition, the simulated annual mean NPP has a consistent distribution with the data provided by IGBP and MODIS, and compares well with the work in literature. This land-atmosphere coupled model will offer a new experiment tool for the research on the two-way interaction between climate and biosphere, and the global terrestrial ecosystem carbon cycle.
  • [1] ZENG Hongling, WANG Zaizhi, JI Jinjun, WU Guoxiong, 2008: An Updated Coupled Model for Land-Atmosphere Interaction. Part I: Simulations of Physical Processes, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 619-631.  doi: 10.1007/s00376-008-0619-y
    [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
    [3] WU Tongwen, LIU Ping, WANG Zaizhi, LIU Yimin, YU Rucong, WU Guoxiong, 2003: The Performance of Atmospheric Component Model R42L9 of GOALS/LASG, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 726-742.  doi: 10.1007/BF02915398
    [4] WANG Zaizhi, WU Guoxiong, WU Tongwen, YU Rucong, 2004: Simulation of Asian Monsoon Seasonal Variations with Climate Model R42L9/LASG, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 879-889.  doi: 10.1007/BF02915590
    [5] 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
    [6] HU Yinqiao, CHEN Jinbei, ZHENG Yuanrun, LI Guoqing, ZUO Hongchao, 2006: Some Phenomena of the Interaction Between Vegetation and a Atmosphere on Multiple Scales, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 639-648.  doi: 10.1007/s00376-006-0639-4
    [7] Siyu CHEN, Dan ZHAO, Jianping HUANG, Jiaqi HE, Yu CHEN, Junyan CHEN, Hongru BI, Gaotong LOU, Shikang DU, Yue ZHANG, Fan YANG, 2023: Mongolia Contributed More than 42% of the Dust Concentrations in Northern China in March and April 2023, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 1549-1557.  doi: 10.1007/s00376-023-3062-1
    [8] ZHANG Xinping, YAO Tandong, LIU Jingmiao, TIAN Lide, Masayoshi NAKAWO, 2003: Simulations of Stable Isotopic Fractionation in Mixed Cloud in Middle Latitudes―Taking the Precipitation at ürǖmqi as an Example, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 261-268.  doi: 10.1007/s00376-003-0012-9
    [9] Ghulam RASUL, Qamar-uz-Zaman CHAUDHRY, ZHAO Sixiong, ZENG Qingcun, 2004: A Diagnostic Study of Record Heavy Rain in Twin Cities Islāmābad-Rāwalpindi, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 976-988.  doi: 10.1007/BF02915599
    [10] Xue Feng, Bi Xunqiang, Lin Yihua, 2001: Modelling the Global Monsoon System by IAP 9L AGCM, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 404-412.  doi: 10.1007/BF02919319
    [11] 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
    [12] LIU Qinyu, WU Shu, YANG Jianling, HU Haibo, HU Ruijin, LI Lijuan, 2006: A Review of Ocean-Atmosphere Interaction Studies in China, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 982-991.  doi: 10.1007/s00376-006-0982-5
    [13] 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
    [14] Li Yinpeng, Ji Jinjun, 2001: Model Estimates of Global Carbon Flux between Vegetation and the Atmosphere, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 807-818.
    [15] ZENG Xiaodong, WANG Aihui, ZENG Qingcun, Robert E. DICKINSON, Xubin ZENG, Samuel S. P. SHEN, 2006: Intermediately Complex Models for the Hydrological Interactions in the Atmosphere-Vegetation-Soil System, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 127-140.  doi: 10.1007/s00376-006-0013-6
    [16] Chineke Theo Chidiezie, Bi Xunqiang, Wang Huijun, Xue Feng, 1997: The African Climate as Predicted by the IAP Grid-Point Nine-Layer Atmospheric General Circulation Model (IAP-9L-AGCM), ADVANCES IN ATMOSPHERIC SCIENCES, 14, 409-416.  doi: 10.1007/s00376-997-0060-7
    [17] 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
    [18] ZHI Hai, WANG Panxing, DAN Li, YU Yongqiang, XU Yongfu, ZHENG Weipeng, 2009: Climate-Vegetation Interannual Variability in a Coupled Atmosphere-Ocean-Land Model, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 599-612.  doi: 10.1007/s00376-009-0599-6
    [19] Hamza VARIKODEN, A. A. SAMAH, C. A. BABU, 2010: The Cold Tongue in the South China Sea during Boreal Winter and Its Interaction with the Atmosphere, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 265-273.  doi: 10.1007/s00376-009-8141-4
    [20] LIU Zhengyu, WU Shu, ZHANG Shaoqing, LIU Yun, RONG Xinyao, , 2013: Ensemble Data Assimilation in a Simple Coupled Climate Model: The Role of Ocean-Atmosphere Interaction, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1235-1248.  doi: 10.1007/s00376-013-2268-z

Get Citation+

Export:  

Share Article

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

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

An Updated Coupled Model for Land-Atmosphere Interaction. Part II: Simulations of Biological 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;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

Abstract: In Part I, the authors succeeded in 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) and analyzed the climate basic state and land surface physical fluxes simulated by R42\_AVIM. In this Part II, we further evaluate the simulated results of the biological processes, including leaf area index (LAI), biomass and net primary productivity (NPP) etc. Results indicate that R42\_AVIM can simulate the global distribution of LAI and has good consistency with the monthly mean LAI provided by Max Planck Institute for Meteorology. The simulated biomass corresponds reasonably to the vegetation classifications. In addition, the simulated annual mean NPP has a consistent distribution with the data provided by IGBP and MODIS, and compares well with the work in literature. This land-atmosphere coupled model will offer a new experiment tool for the research on the two-way interaction between climate and biosphere, and the global terrestrial ecosystem carbon cycle.

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return