Representing surface wind stress response to mesoscale SST perturbations in western coast of South America using Tikhonov regularization method

Interaction between mesoscale perturbations of sea surface temperature (SSTmeso) and wind stress (WSmeso) has great influences on the ocean upwelling system and turbulent mixing in the atmospheric boundary layer. Using daily Quik-SCAT wind speed data and AMSR-E SST data, SSTmeso and WSmeso fields in the western coast of South America are extracted by using a locally weighted regression method (LOESS). The spatial patterns of SSTmeso and WSmeso indicate strong mesoscale SST-wind stress coupling in the region. The coupling coefficient between SSTmeso and WSmeso is about 0.009 5 N/(m(2.)degrees C) in winter and 0.008 2 N/(m(2.)degrees C) in summer. Based on mesoscale coupling relationships, the mesoscale perturbations of wind stress divergence (Div(WSmeso)) and curl (Curl (WSmeso)) can be obtained from the SST gradient perturbations, which can be further used to derive wind stress vector perturbations using the Tikhonov regularization method. The computational examples are presented in the western coast of South America and the patterns of the reconstructed WSmeso are highly consistent with SSTmeso, but the amplitude can be underestimated significantly. By matching the spatially averaged maximum standard deviations of reconstructed WSmeso magnitude and observations, a reasonable magnitude of WSmeso can be obtained when a rescaling factor of 2.2 is used. As current ocean models forced by prescribed wind cannot adequately capture the mesoscale wind stress response, the empirical wind stress perturbation model developed in this study can be used to take into account the feedback effects of the mesoscale wind stress-SST coupling in ocean modeling. Further applications are discussed for taking into account the feedback effects of the mesoscale coupling in large-scale climate models and the uncoupled ocean models.