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| Titel |
Constraining a global ecosystem model with multi-site eddy-covariance data |
| VerfasserIn |
S. Kuppel, P. Peylin, F. Chevallier, C. Bacour, F. Maignan, A. D. Richardson |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 9, no. 10 ; Nr. 9, no. 10 (2012-10-05), S.3757-3776 |
| Datensatznummer |
250007318
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| Publikation (Nr.) |
 copernicus.org/bg-9-3757-2012.pdf |
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| Zusammenfassung |
| Assimilation of in situ and satellite data in mechanistic terrestrial
ecosystem models helps to constrain critical model parameters and reduce
uncertainties in the simulated energy, water and carbon fluxes. So far the
assimilation of eddy covariance measurements from flux-tower sites has been
conducted mostly for individual sites ("single-site" optimization). Here
we develop a variational data assimilation system to optimize 21 parameters
of the ORCHIDEE biogeochemical model, using net CO2 flux (NEE) and
latent heat flux (LE) measurements from 12 temperate deciduous broadleaf
forest sites. We assess the potential of the model to simulate, with a
single set of inverted parameters, the carbon and water fluxes at these 12
sites. We compare the fluxes obtained from this "multi-site" (MS)
optimization to those of the prior model, and of the "single-site" (SS)
optimizations. The model-data fit analysis shows that the MS approach
decreases the daily root-mean-square difference (RMS) to observed data by
22%, which is close to the SS optimizations (25% on average). We also
show that the MS approach distinctively improves the simulation of the
ecosystem respiration (Reco), and to a lesser extent the gross primary productivity (GPP), although we only assimilated net CO2 flux. A
process-oriented parameter analysis indicates that the MS inversion system
finds a unique combination of parameters which is not the simple average of
the different SS sets of parameters. Finally, in an attempt to validate the
optimized model against independent data, we observe that global-scale
simulations with MS optimized parameters show an enhanced phase agreement
between modeled leaf area index (LAI) and satellite-based observations of
normalized difference vegetation index (NDVI). |
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