Efficient estimation of time-mean states of ocean models using 4D-Var and implicit time-stepping

We propose an efficient method for estimating a time-mean state of an ocean model subject to given observations using implicit time-stepping. The new method uses (i) an implicit implementation of the 4D-Var method to fit the model trajectory to the observations, and (ii) a pre-processor which applie...

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Published inNonlinear processes in geophysics Vol. 14; no. 6; pp. 777 - 788
Main Authors Terwisscha van Scheltinga, A. D., Dijkstra, H. A.
Format Journal Article
LanguageEnglish
Published Gottingen Copernicus GmbH 01.01.2007
European Geosciences Union (EGU)
Copernicus Publications
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Online AccessGet full text
ISSN1607-7946
1023-5809
1607-7946
DOI10.5194/npg-14-777-2007

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Summary:We propose an efficient method for estimating a time-mean state of an ocean model subject to given observations using implicit time-stepping. The new method uses (i) an implicit implementation of the 4D-Var method to fit the model trajectory to the observations, and (ii) a pre-processor which applies a multi-channel singular spectrum analysis to enhance the signal-to-noise ratio of the observational data and to filter out the high frequency variability. This approach enables one to estimate the time-mean model state using larger time-steps than is possible with an explicit model. The performance of the method is presented for two test cases within a barotropic quasi-geostrophic nonlinear model of the wind-driven double-gyre ocean circulation. The method turns out to be accurate and, in comparison with the time-mean state computed with an explicit version of the model, relatively cheap in computational cost.
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ISSN:1607-7946
1023-5809
1607-7946
DOI:10.5194/npg-14-777-2007