Abstract
Abstract The investigation of ocean surface topography variation by low-resolution mode (LRM) altimeters at length scales shorter than 100 km is limited by cm-scale measurement noise. Spectral analysis of along-track altimeter data has been used to highlight the issue and to illustrate that one significant noise source stems from correlation between significant wave height (SWH) and range errors that is inherent to any waveform retracking algorithm. This paper focuses on improved characterization and reduction of these high-rate correlated errors that arise from this altimeter measurement process. Specifically, it addresses the effects of sea-state related errors in high rate (20-Hz) Jason-3 satellite sea level data that may possibly impact both short-scale and longer-scale data via interplay with the sea state bias (SSB) correction. Among the suite of standard corrections used to extract sea surface height (SSH) from the raw altimeter range, the empirical SSB term is designed to remove correlation between range and SWH measurements, but not explicitly short-scale error between the two. In this paper, we report that the efficacy of the SSB correction varies with wavelength and it does not remove all correlated signal at high wavenumbers. Following several recent studies, an independent high-frequency adjustment (HFA) is developed to remove these residual correlated errors. Both SSB and HFA are applied on SSH estimations at the 20-Hz rate, improving both 20-Hz and 1-Hz data. Jason-3 data are used as a test bed. Both corrections and net results are specific to MLE4 Jason-3 waveform retracking. Because the reported updated SSB models provide nearly unbiased continuity from Jason-1 to Jason-3 SSB time-series and the MLE4 retracking algorithm is the standard for these missions, the Jason-3 HFA solution can be applied to earlier Jason data with implications for improving the combined 16-year Jason record. By design, the HFA does not impact wavelengths greater than 200 km which is the acting domain of the SSB correction. Applying both the SSB and HFA corrections leads to a global SSH variance reduction nearing 35% in average. The SSH denoising approach through the computation of an additional HFA term is applicable for any LRM ocean altimeter.
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