Large-Scale Errors in ERS Altimeter Data

A method is described for mapping time-uncorrelated large-scale errors in satellite altimeter sea surface heights. Standard deviations of differences between pairs of successive measurements at track crossovers are computed, and the functional dependence of these deviations on absolute time difference is used to estimate the errors of individual measurements. This is first applied to all of ERS-1,2 altimeter data in the Pacific Ocean, yielding average errors of 3.2 cm in the deep ocean (>1 km) and 4.7 cm in the shallow seas (<1 km). The procedure is repeated for variable latitude bands, each with a full range of possible time differences, yielding a meridional profile of computed errors, ranging from 2.6 cm near the Antarctic continent (67–60S) and South Subtropical regions (25–5S) to 3.5 cm in the Antarctic Circumpolar Current (60–45S) and the Northern Hemisphere Subtropical and Subpolar Gyres. Finally, coarse-resolution maps of these errors are produced by subdividing the Pacific Ocean into latitude-longitude bins, each large enough to contain a sufficient number of samples for the functional fits. The larger errors are in Northwest and Subtropical Pacific, especially in South China Sea (4.3 to 4.5 cm) and off northern Australia (5.4 cm), while the smaller errors (2.5 to 3 cm) are in Northeast Pacific, central Tropical Pacific and near Antarctica in Southeast Pacific Ocean. These are lower bounds on altimeter errors, as they do not include contributions from time-correlated errors. We find that the computed error fields are not correlated with sea level standard deviations, thus disproving the notion that altimeter error variance can be scaled with the variance of sea surface height data.