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The equatorial sea level analysis of the National Centers for Environmental Predictions deviates by as much as 8 cm from independent TOPEX/Poseidon (T/P) observations. This may be due to the model’s underestimation of salinity variability. Therefore, methods are developed to improve the model’s salinity field through T/P data assimilation and use of sea surface salinity (SSS) observations. In regions where temperature is well known, salinity estimates are made with the use of climatological temperature–salinity (T–S) correlations. These estimates are improved by combining T–S with SSS observations and corrected with dynamic height, which provides information on salinity variability. Tests with independent conductivity temperature depth data show that the combination of T–S with SSS significantly improves salinity estimates. In the western Pacific, the maximum root-mean-square (rms) estimation error of 0.55 psu is reduced to 0.42 psu by the use of SSS in the salinity estimate. Correction with dynamic height reduces this rms to 0.22 psu. Also in other parts of the tropical Pacific Ocean the salinity estimation errors are reduced by a factor of 2 by combination of the T–S estimate with SSS and dynamic height. This study provides the first step toward an assimilation scheme in which salinity is corrected with the use of T/P sea level observations.
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Vossepoel et al. (1999) studied this question.
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