Correcting the Sea Surface Temperature by Data Assimilation Over the Persian Gulf

Abstract

In this paper, the impact of sea surface temperature (SST) data assimilation on the results of a finite volume community ocean model has been examined by using the nudging scheme. In this regard, the advanced very high-resolution radiometer satellite SST data were selected as the observational data for assimilation. The numerical modeling was performed over the Persian Gulf from 1998 to 2003 in two different modes: with and without SST data assimilation. The performance of data assimilation with the nudging scheme was evaluated by comparing the simulated SST with the in situ SST measurements and optimum interpolation SST data. Both the spatial and temporal comparisons show the efficiency of assimilation in correcting the model results. The spatial root mean square error in the assimilated run depicts meaningful improvements in the whole of the domain. Also, the temporal comparisons of the results show the capability of assimilation in lowering the model output errors. The simulated SST obtained by applying the data assimilation in the shallow parts of the Persian Gulf matched exactly with the measured ones, especially near the Hormuz Strait. Finally, the results show significant improvements in the SST simulated by using the nudging schemes.