Py. Letraon et al., AN IMPROVED MAPPING METHOD OF MULTISATELLITE ALTIMETER DATA, Journal of atmospheric and oceanic technology, 15(2), 1998, pp. 522-534
Objective analysis of altimetric data (sea level anomaly) usually assu
mes that measurement errors are well represented by a white noise, tho
ugh there are long-wavelength errors that are correlated over thousand
s of kilometers along the satellite tracks. These errors are typically
3 cm rms for TOPEX/Poseidon (T/P). which is not negligible in low-ene
rgy regions. Analyzing maps produced by conventional objective analysi
s thus reveals residual long-wavelength errors in the form of tracks o
n the maps. These errors induce sea level gradients perpendicular to t
he track and, therefore, high geostrophic velocities that can obscure
ocean features. To overcome this problem. an improved objective analys
is method that takes into account along-track correlated errors is dev
eloped. A specific data selection is used to allow an efficient correc
tion of long-wavelength errors while estimating the oceanic signal. Th
e influence of data selection is analyzed, and the method is first tes
ted with simulated data. The method is then applied to real T/P and ER
S-1 data in the Canary Basin (a region typical of low eddy energy regi
ons), and the results are compared to those of a conventional objectiv
e 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 meri
dional velocities is roughly 30% and 60%, respectively, of the velocit
y signal variance. The effect is larger when TIP and ERS-1 are combine
d. Correcting the long-wavelength error also considerably improves the
consistency between the T/P and ERS-1 datasets. The variance of the d
ifference (T/P-ERS-1) is reduced by a factor of 1.7 far the sea level,
1.6 for zonal velocities, and 2.3 for meridional velocities. The meth
od is finally applied globally to T/P data. It is shown that it is tra
ctable at the global scale and that it provides an improved mapping.