Optimizing Photosynthetic and Respiratory Parameters Based on the Seasonal Variation Pattern in Regional Net Ecosystem Productivity Obtained from Atmospheric Inversion

Zhuoqi Chen, Beijing Normal University, College of Global Change and Earth System Science, Beijing, China, Jing Chen, University of Toronto, Geography and Planning, Toronto, ON, Canada, Xiaogu Zheng, Beijing Normal University, Beijing, China, Fei Jiang, Nanjing University, Nanjing, China, Shupeng Zhang, Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China, Weimin Ju, Nanjing University, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing, China, Wenping Yuan, Sun Yat‐Sen University, School of Atmospheric Sciences, Guangzhou, China and Gang Mo, University of Toronto, Toronto, ON, Canada
Abstract:
In this study, we explore the feasibility of optimizing ecosystem photosynthetic and respiratory parameters from the seasonal variation pattern of the net carbon flux. An optimization scheme is proposed to estimate two key parameters (Vcmax and Q10) by exploiting the seasonal variation in the net ecosystem carbon flux retrieved by an atmospheric inversion system. This scheme is implemented to estimate Vcmax and Q10 of the Boreal Ecosystem Productivity Simulator (BEPS) to improve its NEP simulation in the Boreal North America (BNA) region. Simultaneously, in-situ NEE observations at six eddy covariance sites are used to evaluate the NEE simulations. The results show that the performance of the optimized BEPS is superior to that of the BEPS with the default parameter values. These results have the implication on using atmospheric CO2 data for optimizing ecosystem parameters through atmospheric inversion or data assimilation techniques.
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