SCIENTIA GEOGRAPHICA SINICA ›› 2022, Vol. 42 ›› Issue (7): 1260-1271.doi: 10.13249/j.cnki.sgs.2022.07.013

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Seasonal Parameterization Scheme of Key Photosynthetic Parameter and Simulation Effect Evaluation of DLM-FvCB Model

Lin Xiaofeng1,2(), Chen Baozhang3,4,*()   

  1. 1. College of Harbour and Coastal Engineering, Jimei University, Xiamen 361021, Fujian, China
    2. National Geographic Conditions Monitoring Research Center, Jimei University, Xiamen 361021, Fujian, China
    3. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    4. University of Chinese Academy of Sciences, Beijing 100049 , China
  • Received:2021-03-21 Revised:2021-07-25 Online:2022-07-10 Published:2022-09-07
  • Contact: Chen Baozhang;
  • Supported by:
    Natural Science Foundation of Fujian Province of China(2021J05169);National Key Research and Development Program of China(2018YFA0606001);National Key Research and Development Program of China(2017YFA0604302)


The key photosynthetic parameter of maximum carboxylation rate (Vcmax25) in Dynamic Land Surface Model (DLM) was parameterized at monthly and yearly time scales, respectively, for 15 flux towers (60 site-years data) including nine vegetation functional types (PFTs) by using variable-controlling iteration method. The GPP simulation results of the two parameterization schemes are compared and analyzed by using the observation data of the remaining station years not involved in parameterization. The results indicate that: 1) the Vcmax25 varied seasonally obviously for all PFTs. Specifically, the variation of Vcmax25 was largest in winter and least in summer. The fluctuation of Vcmax25 was similar among different biomes and was nearly twice in boreal climate region as much as that in temperate climate region. 2) The accuracy of GPP estimation using the seasonal parameterization scheme of Vcmax25 was obviously improved, among which the forest and shrub increased the most significantly in winter (R2 increased by 35.7%, RMSE decreased by 23.24%), followed by spring and autumn, and the least in summer. Even with seasonal fluctuation of parameter considered, DLM-FvCB still difficult well capture the GPP variations for C3 grassland. This study suggests an important consideration of temporal parameterization in further improvement of modelling GPP in land-surface model.

Key words: Gross Primary Production (GPP), Land Surface Model (LSM), maximum carboxylation rate, FLUXNET, seasonal fluctuation

CLC Number: 

  • Q945.11