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A new strategy for assimilating SST data for ENSO predictions

With a simple 3D Var assimilation scheme, a new strategy for assimilating sea surface temperature (SST) observations has been proposed in this paper. The strategy involves assimilating two proxy data, SST and subsurface thermal data, into the ocean model. An ensemble of predictions for the Niño3 region SST anomalies (SSTA) is performed to validate the new strategy. The results show that the new strategy can effectively improve Niño3 SSTA predictions at all lead times, in particular for lead times over 6 months, and for the predictions of El Niño episodes. The prediction skills of the Niño3 SSTA attained by the new scheme can be as high as those attained by the assimilation of subsurface data and sea level height. Comparisons between two schemes of SST assimilations suggest that the impact of observations on the initializations of ENSO predictions could greatly depend on how the observations were assimilated.