An Improved Mapping Method of Multisatellite Altimeter Data

Objective analysis of altimetric data (sea level anomaly) usually assumes that measurement errors are well represented by a white noise, though there are long-wavelength errors that are correlated over thousands of kilometers along the satellite tracks. These errors are typically 3 cm rms for TOPEX/Poseidon (T/P), which is not negligible in low-energy regions. Analyzing maps produced by conventional objective analysis thus reveals residual long-wavelength errors in the form of tracks on the maps. These errors induce sea level gradients perpendicular to the track and, therefore, high geostrophic velocities that can obscure ocean features. To overcome this problem, an improved objective analysis method that takes into account along-track correlated errors is developed. A specific data selection is used to allow an efficient correction of long-wavelength errors while estimating the oceanic signal. The influence of data selection is analyzed, and the method is first tested with simulated data. The method is then applied to real T/P and ERS-1 data in the Canary Basin (a region typical of low eddy energy regions), and the results are compared to those of a conventional objective analysis method. The correction for the along-track long-wavelength error has a very significant effect. For T/P and ERS-1 separately, the mapping difference between the two methods is about 2 cm rms (20\% of the signal variance). The variance of the difference in zonal and meridional velocities is roughly 30\% and 60\%, respectively, of the velocity signal variance. The effect is larger when T/P and ERS-1 are combined. Correcting the long-wavelength error also considerably improves the consistency between the T/P and ERS-1 datasets. The variance of the difference (T/P\textendashERS-1) is reduced by a factor of 1.7 for the sea level, 1.6 for zonal velocities, and 2.3 for meridional velocities. The method is finally applied globally to T/P data. It is shown that it is tractable at the global scale and that it provides an improved mapping.