Abstract
Abstract The surface restoring condition of satellite-derived sea surface temperatures (SSTs) is validated as a feasible assimilation method with an ocean circulation model that incorporates the strongly nonlinear mixed layer model. The restoring treatment is an empirical method for correcting the heat flux in order to pull the predicted SST toward the observed SST; it is referred to as the nudging method in this study. A one-dimensional experiment is conducted to evaluate the skill of the nudging method. The mixed layer model (MLM) used in the experiment is a second-order turbulence closure model that has a strong nonlinearity. The skill of the nudging method is compared with that of an ensemble Kalman filter, which is a statistically optimal method for nonlinear dynamic models. Although the nudging method is statistically suboptimal, the result of the experiment shows that the skill of this method is comparable when using an appropriate restoring time scale. A three-dimensional experiment using an ocean general circulation model (OGCM), which incorporates the same MLM as that used in the one-dimensional experiment, is also conducted to further examine the skill of the nudging method. By applying the nudging method to the OGCM, the model improves the estimated thermal structure not only near the surface, but also in the subsurface layers.
Published Version
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