A Conceptually Simple Modeling Approach for Jason-1 Sea State Bias Correction Based on 3 Parameters Exclusively Derived from Altimetric Information

Abstract

Abstract:A conceptually simple formulation is proposed for a new empirical sea state bias (SSB) model using information retrieved entirely from altimetric data. Nonparametric regression techniques are used, based on penalized smoothing splines adjusted to each predictor and then combined by a Generalized Additive Model. In addition to the significant wave height (SWH) and wind speed (U10), a mediator parameter designed by the mean wave period derived from radar altimetry, has proven to improve the model performance in explaining some of the SSB variability, especially in swell ocean regions with medium-high SWH and low U10. A collinear analysis of scaled sea level anomalies (SLA) variance differences shows conformity between the proposed model and the established SSB models. The new formulation aims to be a fast, reliable and flexible SSB model, in line with the well-settled SSB corrections, depending exclusively on altimetric information. The suggested method is computationally efficient and capable of generating a stable model with a small training dataset, a useful feature for forthcoming missions.

Assessment of Altimetric Range and Geophysical Corrections and Mean Sea Surface Models—Impacts on Sea Level Variability around the Indonesian Seas

“…The electromagnetic bias is due to the fact that ocean wave troughs are better radar reflectors than wave crests, thus overestimating the measured satellite-to-surface range. The tracker bias is caused by onboard tracker instrument errors and errors associated with the re-tracking algorithm, while skewness is linked to the effect of a non-Gaussian surface height distribution, inducing an error due to the difference between the determined median sea surface and the true mean sea surface [62,63]. The sea state bias is associated to the ionosphere, due to the frequency-dependent nature of these corrections.…”

Improving Jason-2 Sea Surface Heights within 10 km Offshore by Retracking Decontaminated Waveforms

“…A summary of the significant achievements was given in [24], including improvements in waveform retracking, tropospheric corrections, tide models, and dynamic atmosphere corrections. There are also some studies on SSB correction, aiming at better modelling the error induced by ocean surface waves, whitecaps and foam [25][26][27][28][29]. Among these improvements, waveform retracking is getting considerable attention in recent years, because of its evident effect on the enhancement of altimeter measurements.…”

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

“…The parameterizations in terms of wind speed U 10 show, in particular, a pronounced regional dependence (Fu and Glazman, 1991) that can be explained mostly by the incompleteness of the set of predictors H s , U 10 (σ 0 ) for wave dynamics and, then, for the SSB assessment. Using the characteristic wave period as an additional predictor shows some success in the empirical models of SSB (Pires, Fernandes, Gommenginger et al, 2016, 2018. However, the wave period, being a function of altimeter measured H s and σ 0 does not extend the number of independent physical predictors only changing the ansatz of the parametric formula.…”