Use of TOPEX/Poseidon Sea Level Data for Ocean Analyses and ENSO Prediction: Some Early Results

Abstract

In this study, two sets of Pacific Ocean analyses for 1993?96 were analyzed. Both analyses were produced with the assimilation of subsurface temperature data from expendable bathythermographs and tropical atmosphere?ocean moorings. In addition one analysis also assimilated sea level data from TOPEX/Poseidon. Sea level variability in the two analyses agreed well with each other, and both agree with tide gauge and altimetry data for 1993?95. However, beginning in late 1995 through 1996, large sea level differences of 5?8 cm were found in the tropical western Pacific between the two analyses. Furthermore, large sea level discrepancies were also found between dynamic height estimated from TAO temperatures and tide gauge?altimetry observations in the same region during 1996. These discrepancies are consistent with the sea level differences between the two model based analyses. Historical conductivity?temperature?depth data along 165°E near the equator were also analyzed and it was found that salinity variability on interannual timescale can result in a sea level variability of at least ?5 dyn cm to +6 dyn cm. These results suggest that the sea level discrepancy in 1996 is likely due to inadequate salinity information both in estimating dynamic height from TAO temperature and in the data assimilation system used here, which corrects only temperature field. The sea level error that resulted from inadequate salinity variability has a significant projection onto the second sea level anomaly EOF, which is linked to the onset phase of ENSO. This suggests that the error in the ocean initial conditions due to underestimate of interannual salinity variations in 1996 could impact the accuracy of ENSO prediction. Results from a twin experiment that uses two summer 1996 ocean initial conditions to hindcast for winter 1996/97 equatorial Pacific SST anomalies appear to support this hypothesis. The results also pointed to a weakness of the present univariate assimilation system, which corrects only temperature. The improved sea level variability comes at the expense of reduced accuracy in temperature. A better solution would be a bivariate data assimilation system, which corrects both salinity and temperature, producing more accurate and consistent ocean initial conditions for ENSO prediction.