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キーワード:
eddy covariance technique
global vegetation model
terrestrial
biosphere
tropical forests
CO2
transport
inversion
dioxide
exchange
leaves
要旨:
This paper combines an atmospheric transport model and a terrestrial ecosystem model to estimate gross primary productivity (GPP) and net ecosystem productivity (NEP) of the land biosphere. Using atmospheric CO2 observations in a Carbon Cycle Data Assimilation System (CCDAS) we estimate a terrestrial global GPP of 146 +/- 19 GtC/yr. However, the current observing network cannot distinguish this best estimate from a different assimilation experiment yielding a terrestrial global GPP of 117 GtC/yr. Spatial estimates of GPP agree with data-driven estimates in the extratropics but are overestimated in the poorly observed tropics. The uncertainty analysis of previous studies was extended by using two atmospheric transport models and different CO2 observing networks. We find that estimates of GPP and NEP are less sensitive to these choices than the form of the prior probability for model parameters. NEP is also found to be significantly sensitive to the transport model and this sensitivity is not greatly reduced compared to direct atmospheric transport inversions, which optimize NEP directly.
