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• W2466551611 abstract "Quality control procedures aiming at identifying observations suspected of gross errors are an important component of modern ocean data assimilation systems. On the one hand, assimilating observations whose departures from the background state are large may result in detrimental analyses and compromise the stability of the ocean analysis system. On the other hand, the rejection of these observations may prevent the analysis from ingesting useful information, especially in areas of large variability. In this work, we investigate the quality control of in-situ hydrographic profiles through modifying the probability density function (PDF) of the observational errors and relaxing the assumption of Gaussian PDF. The new PDF is heavier-tailed than Gaussian, thus accommodating the assimilation of observations with large misfits, albeit with smaller weight given to them in the analysis. This implies a different observational term in the analysis equation, and an adaptive quality control procedure based on the innovation statistics themselves. Implemented in a global ocean variational data assimilation system at moderate horizontal resolution, the scheme proves robust and successful in assimilating more observations with respect to the simpler background quality check scheme. This leads to better skill scores against both conventional and satellite observing systems. This approach proves superior also to the case where no quality control is considered. Furthermore, the implementation considers switching on the modified cost function at the 10th iteration of the minimization so that innovation statistics are based on a good approximation of the analysis. Neglecting this strategy and turning on the variational quality control since the beginning of the minimization exhibits worse scores, qualitatively similar to those of the experiment without quality control, suggesting that in this case quality control procedures are too gentle. A specific study investigating the upper ocean salinity in the Tropical Atlantic ocean is also presented and confirms the ability of the new scheme in making a better use of the in-situ observing system." @default.
• W2466551611 created "2016-07-22" @default.
• W2466551611 creator A5018567274 @default.
• W2466551611 date "2016-08-01" @default.
• W2466551611 modified "2023-09-27" @default.
• W2466551611 title "Variational quality control of hydrographic profile data with non-Gaussian errors for global ocean variational data assimilation systems" @default.
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• W2466551611 doi "https://doi.org/10.1016/j.ocemod.2016.06.011" @default.
• W2466551611 hasPublicationYear "2016" @default.
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