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A hybrid variational-ensemble data assimilation scheme to estimate thevertical and horizontal parts of the background error covariance matrix foran ocean variational data assimilation system is presented and tested in alimited-area ocean model implemented in the western Mediterranean Sea. Anextensive data set collected during the Recognized Environmental PictureExperiments conducted in June 2014 by the Centre for Maritime Research andExperimentation has been used for assimilation and validation. The hybridscheme is used to both correct the systematic error introduced in the systemfrom the external forcing (initialisation, lateral and surface open boundaryconditions) and model parameterisation, and improve the representation ofsmall-scale errors in the background error covariance matrix. An ensemblesystem is run offline for further use in the hybrid scheme, generated throughperturbation of assimilated observations. Results of four differentexperiments have been compared. The reference experiment uses the classicalstationary formulation of the background error covariance matrix and has nosystematic error correction. The other three experiments account for, or not,systematic error correction and hybrid background error covariance matrixcombining the static and the ensemble-derived errors of the day. Results showthat the hybrid scheme when used in conjunction with the systematic errorcorrection reduces the mean absolute error of temperature and salinity misfitby 55 and 42 % respectively, versus statistics arising from standardclimatological covariances without systematic error correction

A hybrid variational-ensemble data assimilation scheme with systematic error correction for limited-area ocean models