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Remote sensing-based ecosystem–atmosphere simulation scheme (EASS)—Model formulation and test with multiple-year data

Author

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  • Chen, Baozhang
  • Chen, Jing M.
  • Ju, Weimin

Abstract

A new remote-sensing-based land surface model, named ecosystem–atmosphere simulation scheme (EASS), is introduced in this paper. The principle motivation for formulating EASS is to provide realistic partition of energy fluxes at regional scales as well as consistent estimates of carbon assimilation rates. EASS has the following characteristics: (i) satellite data are used to describe the spatial and temporal information on vegetation, and in particular, we use a foliage clumping index (Ω) in addition to leaf area index to characterize the effects of three-dimensional canopy structure on radiation, energy and carbon fluxes; (ii) energy and water exchanges and carbon assimilation in the soil–vegetation–atmosphere system are fully coupled and are simulated simultaneously; (iii) the energy and carbon assimilation fluxes are calculated with stratification of sunlit and shaded leaves to avoid shortcomings of the “big-leaf” assumption. Model experiments shows that the simulation realism and accuracy by the new strategy are enhanced about 9–14% compared with the “big-leaf model”. Moreover, Ω is useful for accurate separation of sunlit and shaded leaves in the canopy. The accuracy in simulation of energy and carbon fluxes increase about 5–8% by considering the effects of Ω on the radiation interception and the separation of sunlit and shaded leaves; (iv) snow and soil simulations are emphasized by including a flexible and multiple layer scheme. EASS has been tested and validated against multiple-year observed data at several sites. EASS is proved to be overall successful in capturing variations in energy fluxes, canopy and soil temperatures, and soil moisture over diurnal, synoptic, seasonal and inter-annual temporal scales.

Suggested Citation

  • Chen, Baozhang & Chen, Jing M. & Ju, Weimin, 2007. "Remote sensing-based ecosystem–atmosphere simulation scheme (EASS)—Model formulation and test with multiple-year data," Ecological Modelling, Elsevier, vol. 209(2), pages 277-300.
    • Handle: RePEc:eee:ecomod:v:209:y:2007:i:2:p:277-300
    DOI: 10.1016/j.ecolmodel.2007.06.032
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    Citations

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    Cited by:

    1. He, Liming & Chen, Jing M. & Liu, Jane & Mo, Gang & Bélair, Stéphane & Zheng, Ting & Wang, Rong & Chen, Bin & Croft, Holly & Arain, M.Altaf & Barr, Alan G., 2014. "Optimization of water uptake and photosynthetic parameters in an ecosystem model using tower flux data," Ecological Modelling, Elsevier, vol. 294(C), pages 94-104.
    2. Zhu, Lin & Chen, Jing M. & Qin, Qiming & Li, Jianping & Wang, Lianxi, 2009. "Optimization of ecosystem model parameters using spatio-temporal soil moisture information," Ecological Modelling, Elsevier, vol. 220(18), pages 2121-2136.
    3. Mercedeh Taheri & Abdolmajid Mohammadian & Fatemeh Ganji & Mostafa Bigdeli & Mohsen Nasseri, 2022. "Energy-Based Approaches in Estimating Actual Evapotranspiration Focusing on Land Surface Temperature: A Review of Methods, Concepts, and Challenges," Energies, MDPI, vol. 15(4), pages 1-57, February.
    4. Liu, Zhenhai & Chen, Bin & Wang, Shaoqiang & Wang, Qinyi & Chen, Jinghua & Shi, Weibo & Wang, Xiaobo & Liu, Yuanyuan & Tu, Yongkai & Huang, Mei & Wang, Junbang & Wang, Zhaosheng & Li, Hui & Zhu, Tongt, 2021. "The impacts of vegetation on the soil surface freezing-thawing processes at permafrost southern edge simulated by an improved process-based ecosystem model," Ecological Modelling, Elsevier, vol. 456(C).

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