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| Titel |
Optimizing CO2 observing networks in the presence of model error: results from TransCom 3 |
| VerfasserIn |
R. J. Rayner |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 4, no. 2 ; Nr. 4, no. 2 (2004-03-03), S.413-421 |
| Datensatznummer |
250001600
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| Publikation (Nr.) |
 copernicus.org/acp-4-413-2004.pdf |
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| Zusammenfassung |
| We use a genetic algorithm to construct optimal observing networks
of atmospheric concentration for inverse determination of net
sources. Optimal networks are those that produce a minimum in
average posterior uncertainty plus a term representing the divergence
among source estimates for different transport models. The addition of this
last term modifies the choice of observing sites, leading to
larger networks than would be chosen under the traditional
estimated variance metric. Model-model differences behave like
sub-grid heterogeneity and optimal networks try to average over some
of this.
The optimization does not, however,
necessarily reject apparently difficult sites to model. Although the results
are so conditioned on the experimental set-up that the specific
networks chosen are unlikely to be the best choices in the real
world, the counter-intuitive behaviour of the optimization suggests
the model error contribution should be taken into account when
designing observing networks. Finally we
compare the flux and total uncertainty estimates from the optimal network with those from
the 3 control case. The
3 control case performs well under the chosen uncertainty
metric and the flux estimates are close to those from the optimal
case. Thus the 3 findings would have been similar if
minimizing the total uncertainty guided their network choice. |
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