Altimetric Data Assimilation by EnOI and 3DVAR in a Tropical Pacific Model: Impact on the Simulation of Variability

When altimetric data is assimilated, 3DVAR and Ensemble OptimalInterpolation (EnOI) have different ways of projecting the surfaceinformation downward. In 3DVAR, it is achieved by minimizing a cost functionrelating the temperature, salinity, and sea level. In EnOI, however, thesurface information is propagated to other variables via a stationaryensemble. In this study, the differences between the two methods werecompared and their impacts on the simulated variability were evaluated in atropical Pacific model.Sea level anomalies (SLA) from the TOPEX/Poseidon were assimilated usingboth methods on data from 1997 to 2001 in a coarse resolution model. Resultsshow that the standard deviation of sea level was improved by both methods,but the EnOI was more effective in the central/eastern Pacific. Meanwhile,the SLA evolution was better reproduced with EnOI than with 3DVAR.Correlations of temperature with the reanalysis data increased with EnOI by0.1--0.2 above 200 m. In the eastern Pacific below 200 m, the correlationsalso increased by 0.2. However, the correlations decreased with 3DVAR inmany areas. Correlations with the independent TAO profiles were alsocompared at two locations. While the correlations increased by up to 0.2 atsome depths with EnOI, 3DVAR generally reduced the correlations by 0.1--0.3.Though both methods were able to reduce the model--data difference inclimatological sense, 3DVAR appears to have degraded the simulatedvariability, especially during El Nino--Southern Oscillation events. Forsalinity, similar results were found from the correlations. This tendencyshould be considered in future SLA assimilations, though the comparisons mayvary among different model implementations.