Ensemble Optimal Interpolation: multivariate properties in the Gulf of Mexico

In a paper published in Tellus A Drs. Francois Counillon and Laurent Bertino present an ocean model system for the Gulf of Mexico and the ensemble optimal interpolation (EnOI) methods developed under Counillon Ph.D. studies at the Nansen Center.

The EnOI extracts its covariance matrix from a historical ensemble and allows for a multivariate update at a small computational cost. The Sea Level Anomaly (SLA) is used for assimilation, as it provides an integral representation of the circulation in the area. The multivariate updates are compared with the known properties of the circulation of the area. The multivariate correlations are analyzed at two characteristic locations: in the central part of the Gulf of Mexico, and in the upper-slope of the northern shelf. The multivariate relationships between variables are reasonably linear. They are realistic in the center of the basin, but show some limitations in the upper shelf. Our data assimilation set-up produces only minor imbalance, even when the observation error is purposely reduced (hereafter referred as “strong assimilation”). The multivariate assimilation update can initiate a density perturbation in the isopycnal layers, or artificial caballing. This introduces some high-frequency noise in the model, which are damped within two days. The data assimilation system is finally demonstrated for the shedding of Eddy Yankee, for which it beats persistence.


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