Sea state bias in altimetry measurements within the theory of similarity for wind-driven seas

TL;DR

This paper applies the theory of similarity to analyze sea state bias in altimetry measurements, demonstrating that wave pseudo-age and steepness can reliably estimate SSB across different datasets, paving the way for improved physical models.

Contribution

It introduces a novel application of similarity theory to model sea state bias in altimetry, emphasizing the use of wave pseudo-age and steepness for more accurate estimates.

Findings

SSB distributions are consistent across different satellite data when recast onto wave pseudo-age and steepness.

The similarity approach shows robustness and physical relevance in SSB analysis.

Results support developing a new parametric SSB model based on physical wave parameters.

Abstract

The theory of similarity for wind-driven seas is applied to the physical analysis of the problem of sea state bias (SSB) in altimetry measurements. Dimensionless wave steepness and pseudo-age derived from altimetry measurements are expected to provide {physically relevant and accurate enough} SSB estimates. Analysis of Jason-1,2,3 and SARAL/AltiKa data within the approach shows the similarity and robustness of SSB distributions re-casted onto space of wave pseudo-age and steepness. This result is considered as a ground for developing a new parametric model of SSB and for analysis of underlying physical effects.