A COMPARATIVE-STUDY OF TROPICAL PACIFIC SEA-SURFACE HEIGHT VARIABILITY - TIDE GAUGES VERSUS THE NATIONAL-METEOROLOGICAL-CENTER DATA-ASSIMILATING OCEAN GENERAL-CIRCULATION MODEL, 1982-1992

To help assess the effectiveness of the model-based analysis and predi ction procedures at the National Meteorological Center (NMC), we compa re the seasonal and nonseasonal components of sea level from 44 tide g auges in the tropical Pacific with those of the dynamic heights output by two 11-year model reanalyses (1982-1992) at the same locations, wh ich differ mainly in their wind forcing. Both reanalyses assimilate oc ean thermal data and incorporate most of the procedures used by NMC in producing operational ocean analyses and experimental coupled model c limate forecasts. The reanalyses reproduce the broad patterns of annua l amplitude and phase and of seasonal and nonseasonal variance, except for severe underestimates along the eastern boundary, especially nort h of the equator. The annual cycles and interannual departures of zona l flow indices estimated from selected island pairs near the dateline show good correspondence for the North Equatorial Countercurrent (NECC ) and somewhat flawed and noisy comparisons for the North Equatorial C urrent (NEC) and South Equatorial Current(SEC). The reanalyses also re produce the large-scale time and space patterns of nonseasonal variabi lity in the first three empirical orthogonal functions (EOFs); which t ogether explain about 65% of the anomalous variability and characteriz e the El Nino-Southern Oscillation cycle. The first two EOF modes desc ribe the westward migration of three ENSO episodes, and the third mode appears to capture differences between episodes. However, the reanaly sis based on the anomalous winds generated by the NMC medium-range for ecast model shows significant discrepancies in the large-scale spatial and temporal variability. These discrepancies disappear in the reanal ysis based on departures of the Florida State University analyzed wind fields. Hence the wind forcing critically affects the reanalysis in s pite of the assimilation of ocean thermal data. Future improvements in the atmospheric model to produce a more realistic evolution of the wi nd field can therefore lead to significantly better model integrations in the analysis and initialization mode (with data assimilation) as w ell as in the coupled model forecast mode.