We investigate how well the 1975-1992 sea level interannual variabilit
y in the tropical Pacific is captured by dynamic height from temperatu
re profiles. For each temperature profile, a surface dynamic height re
lative to 300 m is estimated, assuming a constant temperature-salinity
relationship. After multiplication by a latitudinally varying factor
and the removal of a seasonal cycle, the dynamic height deviations fit
the tide gauge sea level variability to within the sampling errors, e
xcept at a few sites near the equator west of the date line, where sur
face salinity variability is large. The dynamic height data are assimi
lated into a wind-forced linear numerical model of the sea level in th
e tropical Pacific, applying a Kalman filter in a space of reduced dim
ension. A limited number of empirical orthogonal functions of the unfi
ltered run (1975-1992) define the reduced space, into which the Kalman
Filter covariance evolution calculation is done [Cane et at, 1996]. E
xperiments indicate that results are better with 32 functions than wit
h a smaller number but are not improved by retaining more functions. T
he resulting analyzed fields of sea level are compared to withheld dyn
amic height estimates from moorings, sea level data from tide gauges,
and sea level analyses made with the same Kalman filter formalism appl
ied to tide gauge measurements. The comparisons to observations sugges
t that the temperature profiles were usually sufficient to constrain t
he monthly analyzed fields to be close to the observed sea level with
errors typically less than 3 cm neat the equator. The comparison to ti
de gauge sea level reveals that this analysis is often more accurate t
han the analysis of tide gauge sea level data with which it shares man
y characteristics. Near the equator west of the date line, salinity va
riations ate large and their neglect in estimating dynamic height has
a negative impact on the analysis. The analyzed signal is underestimat
ed in the southwest Pacific and at more than 20 degrees off the equato
r. The reanalysis of the temperature data done with a primitive equati
on model at the National Meteorological Center (NMC) [Ji et at, 1995;
Enfield and Harris, 1995] does not share this problem. On the other ha
nd, NMC reanalysis (RA4) departs more from the observations elsewhere,
although more data were included than in our analysis.