Data assimilation with the EnKF in a 1-D numerical model of a North Sea station

A series of numerical experiments for data assimilation with the Ensemble Kalman Filter (EnKF) in a shallow water model are reported. Temperature profiles measured at a North Sea location, 55°30ˊ North and 0°55ˊ East (referred to as the CS station of the NERC North Sea project), are assimilated in 1...

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Bibliographic Details
Published in:Ocean dynamics 2009-12, Vol.59 (6), p.983-996
Main Authors: Ponsar, Stéphanie, Luyten, Patrick
Format: Article
Language:English
Subjects:
Atmospheric Sciences
Data collection
Earth and Environmental Science
Earth Sciences
Fluid- and Aerodynamics
Geophysics/Geodesy
Marine
Mathematical models
Monitoring/Environmental Analysis
Oceanography
Shallow water
Water column
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Summary:A series of numerical experiments for data assimilation with the Ensemble Kalman Filter (EnKF) in a shallow water model are reported. Temperature profiles measured at a North Sea location, 55°30ˊ North and 0°55ˊ East (referred to as the CS station of the NERC North Sea project), are assimilated in 1-D simulations. Comparison of simulations without assimilation to model results obtained when assimilating data with the EnKF allows us to assess the filter performance in reproducing features of the observations not accounted for by the model. The quality of the model error sampling is tested as well as the validity of the Gaussian hypothesis underlying the analysis scheme of the EnKF. The influence of the model error parameters and the frequency of the data assimilation are investigated and discussed. From these experiments, a set of optimal parameters for the model error sampling are deduced and used to test the behavior of the EnKF when propagating surface information into the water column.
ISSN:1616-7341
1616-7228
DOI:10.1007/s10236-009-0224-3