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- Title
Optimization of Terrestrial Ecosystem Model Parameters Using Atmospheric CO<sub>2</sub> Concentration Data With the Global Carbon Assimilation System (GCAS).
- Authors
Chen, Zhuoqi; Chen, Jing M.; Zhang, Shupeng; Zheng, Xiaogu; Ju, Weiming; Mo, Gang; Lu, Xiaoliang
- Abstract
Abstract: The Global Carbon Assimilation System that assimilates ground‐based atmospheric CO2 data is used to estimate several key parameters in a terrestrial ecosystem model for the purpose of improving carbon cycle simulation. The optimized parameters are the leaf maximum carboxylation rate at 25°C ( V max 25), the temperature sensitivity of ecosystem respiration (Q10), and the soil carbon pool size. The optimization is performed at the global scale at 1° resolution for the period from 2002 to 2008. The results indicate that vegetation from tropical zones has lower V max 25 values than vegetation in temperate regions. Relatively high values of Q10 are derived over high/midlatitude regions. Both V max 25 and Q10 exhibit pronounced seasonal variations at middle‐high latitudes. The maxima in V max 25 occur during growing seasons, while the minima appear during nongrowing seasons. Q10 values decrease with increasing temperature. The seasonal variabilities of V max 25 and Q10 are larger at higher latitudes. Optimized V max 25 and Q10 show little seasonal variabilities at tropical regions. The seasonal variabilities of V max 25 are consistent with the variabilities of LAI for evergreen conifers and broadleaf evergreen forests. Variations in leaf nitrogen and leaf chlorophyll contents may partly explain the variations in V max 25. The spatial distribution of the total soil carbon pool size after optimization is compared favorably with the gridded Global Soil Data Set for Earth System. The results also suggest that atmospheric CO2 data are a source of information that can be tapped to gain spatially and temporally meaningful information for key ecosystem parameters that are representative at the regional and global scales.
- Publication
Journal of Geophysical Research. Biogeosciences, 2017, Vol 122, Issue 12, p3218
- ISSN
2169-8953
- Publication type
Article
- DOI
10.1002/2016JG003716