Publication Date:
2022-05-26
Description:
Author Posting. © American Geophysical Union, 2017. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 122 (2017): 3218–3237, doi:10.1002/2016JG003716.
Description:
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 (V25
max),
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 V25
max values than vegetation in temperate regions. Relatively high
values of Q10 are derived over high/midlatitude regions. Both V25
max and Q10 exhibit pronounced seasonal
variations at middle-high latitudes. The maxima in V25
max occur during growing seasons, while the minima
appear during nongrowing seasons. Q10 values decrease with increasing temperature. The seasonal
variabilities of V25
max and Q10 are larger at higher latitudes. Optimized V25
max and Q10 show little seasonal
variabilities at tropical regions. The seasonal variabilities of V25
max 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 V25
max. 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.
Description:
National Key R&D Program of China Grant Number: 2016YFA0600204;
National Natural Science Foundation of China Grant Number: 41571338
Description:
2018-06-23
Keywords:
Global Carbon Assimilation System
;
Atmospheric CO2 concentration data
;
Ecosystem model parameters
Repository Name:
Woods Hole Open Access Server
Type:
Article
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