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| Titel |
Quantifying the model structural error in carbon cycle data assimilation systems |
| VerfasserIn |
S. Kuppel, F. Chevallier, P. Peylin |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 6, no. 1 ; Nr. 6, no. 1 (2013-01-11), S.45-55 |
| Datensatznummer |
250017358
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| Publikation (Nr.) |
 copernicus.org/gmd-6-45-2013.pdf |
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| Zusammenfassung |
| This study explores the impact of the structural error of biosphere models
when assimilating net ecosystem exchange (NEE) measurements or CO2
concentration measurements to optimise uncertain model parameters within
carbon cycle data assimilation systems (CCDASs). This error has been proven
difficult to identify and is often neglected in the total uncertainty
budget. We propose a simple method which is derived from the
model-minus-observation mismatch statistics. This diagnosis is applied to a
state-of-the-art biogeochemical model using measurements of the net surface
CO2 flux at twelve sites located in temperate, deciduous, broadleaf
forests. We find that the structural model error in the NEE space has a
standard deviation of 1.5 to 1.7 gC m−2 d−1, without a
significant correlation structure beyond the lag of a few days, and a large
spatial structure that can be approximated with an exponential decay of
e-folding length of 500 km. In the space of concentrations, its characteristics
are commensurate with the transport errors, both for surface air sample
measurements and total column measurements. The inferred characteristics are
confirmed by complementary optimality diagnostics performed after site-scale
parameter optimisations. |
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