DECADAL ANALYSIS PRODUCED FROM AN OCEAN DATA ASSIMILATION SYSTEM

A global oceanic four-dimensional data assimilation system has been de veloped for use in initializing coupled ocean-atmosphere general circu lation models and also to study interannual variability. The data inse rted into a high-resolution global ocean model consist of conventional sea surface temperature observations and vertical temperature profile s. The data are inserted continuously into the model by updating the m odel's temperature solution every time step. This update is created us ing a statistical interpolation routine applied to all data in a 30-da y window for three consecutive time steps and then the correction is h eld constant for nine time steps. Not updating every time step allows for a more computationally efficient system without affecting the qual ity of the analysis. The data assimilation system was run over a 10-yr period from 1979 to 1988. The resulting analysis product was compared with independent analysis including model-derived fields like velocit y. The large-scale features seem consistent with other products based on observations. Using the mean of the 10-yr period as a climatology, the data assimilation system was compared with the Levitus climatologi cal atlas. Looking at the sea surface temperature and the seasonal cyc le, as represented by the mixed-layer depth, the agreement is quite go od, however, some systematic differences do emerge. Special attention is given to the tropical Pacific examining the El Nino signature. Two other assimilation schemes based on the coupled model using Newtonian nudging of SST and then SST and surface winds are compared to the full data assimilation system. The heat content variability in the data as similation seemed faithful to the observations. Overall, the results a re encouraging, demonstrating that the data assimilation system seems to be able to capture many of the large-scale general circulation feat ures that are observed, both in a climatological sense and in the temp oral variability.