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- W4240985009 abstract "Abstract. A hybrid variational-ensemble data assimilation scheme to estimate the vertical and horizontal parts of the background-error covariance matrix for an ocean variational data assimilation system is presented and tested in a limited area ocean model implemented in the western Mediterranean Sea. An extensive dataset collected during the Recognized Environmental Picture Experiments conducted in June 2014 by the Centre for Maritime Research and Experimentation has been used for assimilation and validation. The hybrid scheme is used to both correct the systematic error introduced in the system from the external forcing (initial, lateral and surface open boundary conditions) and model parameterization and improve the representation of small scale errors in the Background Error Covariance matrix. An ensemble system is run off-line for further use in the hybrid scheme, generated through perturbation of assimilated observations. Results of four different experiments have been compared. The reference experiment uses the classical static formulation of the background error covariance matrix and has no systematic error correction. The other three experiments account, or not, for systematic error correction and hybrid daily estimates of the background error covariance matrix combining the static and the ensemble derived errors statistics. Results show that the hybrid scheme when used in conjunction with the systematic error correction reduce the mean absolute error of temperature and salinity misfit by 55 % and 42 % respectively versus statistics arising from standard climatological covariances without systematic error correction." @default.
- W4240985009 created "2022-05-12" @default.
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- W4240985009 date "2016-05-23" @default.
- W4240985009 modified "2023-09-24" @default.
- W4240985009 title "A Hybrid Variational-Ensemble data assimilation scheme with systematic error correction for limited area ocean model" @default.
- W4240985009 doi "https://doi.org/10.5194/os-2016-35" @default.
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