Conference Paper

Improving the estimation of the sea level anomaly slppe

Authors: Mailhes Corinne, Besson Olivier, Guillot Amandine and Le Gac Sophie

in Proc. IEEE Int. Geosci. Remote Sens. Symp. (IGARSS), Hawaï, USA, 19-24 July 2020.

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Satellite altimeters provide sea level measurements along satellite track. A mean profile based on the measurements averaged over a time period is then subtracted to estimate the sea level anomaly (SLA). In the spectral domain, SLA is characterized by a power spectral density of the form one over a power of the frequency where the power (the slope) is a parameter of great interest for ocean monitoring. However, this information lies in a narrow frequency band, located at very low frequencies, which calls for some specific spectral analysis methods. This paper studies a new parametric method based on an autoregressive model combined with a warping of the frequency scale (denoted as ARWARP). A statistical validation is proposed on simulated SLA signals, showing the performance of slope estimation using this ARWARP spectral estimator, compared to classical Fourier-based methods. Application to Sentinel-3 real data highlights the main advantage of the ARWARP model, making possible SLA slope estimation on a short signal segment, i.e., with a high spatial resolution.

Signal and image processing / Earth observation

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