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| Titel |
Development of an ensemble-adjoint optimization approach to derive uncertainties in net carbon fluxes |
| VerfasserIn |
T. Ziehn, M. Scholze, W. Knorr |
| 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 ; 4, no. 4 ; Nr. 4, no. 4 (2011-11-18), S.1011-1018 |
| Datensatznummer |
250001917
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| Publikation (Nr.) |
 copernicus.org/gmd-4-1011-2011.pdf |
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| Zusammenfassung |
| Accurate modelling of the carbon cycle strongly depends on the
parametrization of its underlying processes. The Carbon Cycle Data
Assimilation System (CCDAS) can be used as an estimator algorithm to
derive posterior parameter values and uncertainties for the Biosphere
Energy Transfer and Hydrology scheme (BETHY). However, the
simultaneous optimization of all process parameters can be
challenging, due to the complexity and non-linearity of the BETHY
model. Therefore, we propose a new concept that uses
ensemble runs and the adjoint optimization approach of CCDAS to derive
the full probability density function (PDF) for posterior soil carbon
parameters and the net carbon flux at the global scale. This method
allows us to optimize only those parameters that can be constrained best by
atmospheric carbon dioxide (CO2) data. The prior uncertainties
of the remaining parameters are included in a consistent way through
ensemble runs, but are not constrained by data. The final PDF for the
optimized parameters and the net carbon flux are then derived by
superimposing the individual PDFs for each ensemble member. We find
that the optimization with CCDAS converges much faster, due to the
smaller number of processes involved. Faster convergence
also gives us much increased confidence
that we find the global minimum in the reduced parameter space. |
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