Mapping the mean sea surface elevation field from satellite altimetry data using optimal interpolation

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Abstract
Optimal interpolation technique is applied to satellite altimetry data in order to recover a sea surface elevation signal from the data, which includes a large satellite radial orbit error, also to make a map of temporal mean sea surface dynamic topography (SSDT, the mean surface height relative to the geoid). The method is applied to Seasat data for a study area southeast of Japan, for which a fairly precise gravimetric geoid is available. Estimated mean elevation field relative to the best available geoid qualitatively shows existence of the Kuroshio in a limited local area close to Honshu, Japan. But for the whole of the area studied, the elevation field is much more rugged than expected mean SSDT and appears to include a relatively large geoid error; namely, the mapped mean sea surface elevation field cannot describe the mean SSDT field. Instead, correction of the provided geoid is evaluated by this altimetrically estimated elevation field together with the mean SSDT estimated from hydrographic data.