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| Titel |
Optimal adjustment of the atmospheric forcing parameters of ocean models using sea surface temperature data assimilation |
| VerfasserIn |
M. Meinvielle, J.-M. Brankart, P. Brasseur, B. Barnier, R. Dussin, J. Verron |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1812-0784
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| Digitales Dokument |
URL |
| Erschienen |
In: Ocean Science ; 9, no. 5 ; Nr. 9, no. 5 (2013-10-17), S.867-883 |
| Datensatznummer |
250085246
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| Publikation (Nr.) |
 copernicus.org/os-9-867-2013.pdf |
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| Zusammenfassung |
In ocean general circulation models, near-surface atmospheric variables used
to specify the atmospheric boundary condition remain one of the main sources
of error. The objective of this research is to constrain the surface forcing
function of an ocean model by sea surface temperature (SST) data
assimilation. For that purpose, a set of corrections for ERAinterim
(hereafter ERAi) reanalysis data is estimated for the period of 1989–2007, using a sequential assimilation method, with ensemble experiments to
evaluate the impact of uncertain atmospheric forcing on the ocean state. The
control vector of the assimilation method is extended to atmospheric
variables to obtain monthly mean parameter corrections by assimilating
monthly SST and sea surface salinity (SSS) climatological data in a low
resolution global configuration of the NEMO model. In this context, the
careful determination of the prior probability distribution of the parameters
is an important matter. This paper demonstrates the importance of isolating
the impact of forcing errors in the model to perform relevant ensemble
experiments.
The results obtained for every month of the period between 1989 and 2007 show
that the estimated parameters produce the same kind of impact on the SST as
the analysis itself. The objective is then to evaluate the long-term
time series of the forcing parameters focusing on trends and mean error
corrections of air–sea fluxes. Our corrections tend to equilibrate the net
heat-flux balance at the global scale (highly positive in ERAi database), and
to remove the potentially unrealistic negative trend (leading to ocean
cooling) in the ERAi net heat flux over the whole time period. More
specifically in the intertropical band, we reduce the warm bias of ERAi data
by mostly modifying the latent heat flux by wind speed intensification.
Consistently, when used to force the model, the corrected parameters lead to
a better agreement between the mean SST produced by the model and mean SST
observations over the period of 1989–2007 in the intertropical band. |
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