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Volume 28 Issue 5

Sep.  2011

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2011 >  28(5): 1129-1142

Coupling a Terrestrial Biogeochemical Model to the Common Land Model

  • 1.

    State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA,CSIRO Marine and Atmospheric Research, Aspendale, Victoria, Australia,State Key Laboratory of Earth Surface Processes and Resource Ecology,College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875 and South China Botanical Garden, the Chinese Academy of Sciences, Guangzhou 510650


doi: 10.1007/s00376-010-0131-z

  • A terrestrial biogeochemical model (CASACNP) was coupled to a land surface model (the Common Land Model, CoLM) to simulate the dynamics of carbon substrate in soil and its limitation on soil respiration. The combined model, CoLM{\_}CASACNP, was able to predict long-term carbon sources and sinks that CoLM alone could not. The coupled model was tested using measurements of belowground respiration and surface fluxes from two forest ecosystems. The combined model simulated reasonably well the diurnal and seasonal variations of net ecosystem carbon exchange, as well as seasonal variation in the soil respiration rate of both the forest sites chosen for this study. However, the agreement between model simulations and actual measurements was poorer under dry conditions. The model should be tested against more measurements before being applied globally to investigate the feedbacks between the carbon cycle and climate change.
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    [3] Dongxu YANG, Huifang ZHANG, Yi LIU, Baozhang CHEN, Zhaonan CAI, Daren LÜ, 2017: Monitoring Carbon Dioxide from Space: Retrieval Algorithm and Flux Inversion Based on GOSAT Data and Using CarbonTracker-China, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 965-976.  doi: 10.1007/s00376-017-6221-4
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    • Manuscript History

    Manuscript received: 10 September 2011
    Manuscript revised: 10 September 2011
    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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    Coupling a Terrestrial Biogeochemical Model to the Common Land Model

    • 1. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA,CSIRO Marine and Atmospheric Research, Aspendale, Victoria, Australia,State Key Laboratory of Earth Surface Processes and Resource Ecology,College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875 and South China Botanical Garden, the Chinese Academy of Sciences, Guangzhou 510650
    • Manuscript received: 2011-09-10
    • Manuscript revised: 2011-09-10

    Abstract: A terrestrial biogeochemical model (CASACNP) was coupled to a land surface model (the Common Land Model, CoLM) to simulate the dynamics of carbon substrate in soil and its limitation on soil respiration. The combined model, CoLM{\_}CASACNP, was able to predict long-term carbon sources and sinks that CoLM alone could not. The coupled model was tested using measurements of belowground respiration and surface fluxes from two forest ecosystems. The combined model simulated reasonably well the diurnal and seasonal variations of net ecosystem carbon exchange, as well as seasonal variation in the soil respiration rate of both the forest sites chosen for this study. However, the agreement between model simulations and actual measurements was poorer under dry conditions. The model should be tested against more measurements before being applied globally to investigate the feedbacks between the carbon cycle and climate change.

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