Sequential weak constraint parameter estimation in an ecosystem model


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gkivman [ at ] awi-bremerhaven.de

Abstract

A Sequential Importance Resampling filter is applied to assimilate dataof the Bermuda Atlantic Time-series Study for the periodDecember 1988 to January 1994 into a 9-compartments ecosystemmodel. The filter provides an opportunity to combine state and parameterestimations. We detected notable seasonality of some model parameters.A filtered solution is in close agreement with the data and is superiorto that obtained with fixed model parameters. The seasonal dependenceof the initial slope of the P-I curve agrees with other known estimates.The seasonality of the phytoplankton specific mortality rate obtainedcan point out that either the phytoplankton mortality parameterizationhas to be improved or the Chl:C ratio varies in time. Being of the samecomputational cost as the Ensemble Kalman filter, the data assimilationapproach used can be implemented for on-line tuning and operationalprediction the ecosystem dynamics with a coupledhydrodynamical-ecosystem model.



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Scopus/ISI peer-reviewed
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Published
Eprint ID
4738
DOI 10.1016/j.jmarsys.2003.06.001

Cite as
Loza, S. , Kivman, G. , Schröter, J. and Wenzel, M. (2003): Sequential weak constraint parameter estimation in an ecosystem model , Journal of Marine Systems, 43 , pp. 31-49 . doi: 10.1016/j.jmarsys.2003.06.001


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