Incorporating State-Dependent Temperature–Salinity Constraints in the Background Error Covariance of Variational Ocean Data Assimilation

Abstract Several studies have illustrated how the univariate assimilation of temperature data can have a detrimental effect on the ocean-state variables (salinity, currents, etc.) not directly constrained by the data. In this paper, the authors describe how the salinity adjustment method proposed by Troccoli and Haines can be included as a multivariate temperature–salinity (T–S) constraint within a background-error covariance model for variational data assimilation. The method is applied to a three-dimensional variational assimilation (3DVAR) system for a tropical Pacific version of the Ocean Parallelise (OPA) ocean general circulation model. An identical twin experiment is presented first to illustrate how the method is effective in reconstructing a density profile using only temperature observations from that profile. The 3DVAR system is then cycled over the period 1993–98 using in situ temperature data from the Global Temperature and Salinity Pilot Programme. Relative to a univariate (T) 3DVAR, the mul...

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