Estimating the sea state bias of the TOPEX and POSEIDON altimeters from crossover differences

Abstract

TOPEX (Ku band) and POSEIDON altimeter measurements at crossover points are used to estimate the sea state bias (SSB) of these two instruments. Different SSB models are tested, ranging from a constant fraction of the significant wave height (SWH) to more elaborate models involving up to four adjustable parameters. For TOPEX, the data show a decrease in the magnitude of the relative bias (SSB/SWH) with SWH. This behavior is well reproduced using a simple empirical model with two adjustable parameters. The three‐parameter SSB model used in the NASA geophysical data records does well in explaining the wind‐induced variations of the bias. A model including four adjustable parameters is needed to account for both the wind‐ and SWH‐related variability of the SSB. POSEIDON data analysis reveals a significantly larger SSB than for TOPEX. This bias seems to consist of a skewness plus tracker bias of −2 to −3% of SWH superimposed on a natural EM bias whose wind‐ and SWH‐related variations are similar to those of TOPEX.

Estimation of the sea state bias in radar altimeter measurements of sea level: Results from a new nonparametric method

“…This decrease in the magnitude of the relative bias with wave height was first detected by Witter and Chelton [1991a] in Geosat data. It was later observed in TOPEX and POSEIDON measurements [Gaspar et al, 1994;Chelton, 1994]. The BM4 model (equation (11)) goes some way toward parameterizing this effect, since it allows the relative bias to decrease linearly with SWH.…”

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

“…Usually, the SSB is estimated by differencing the repeated measurements either along collinear tracks [20] or at orbit crossover points [5], but [9] proposed a simpler direct technique where sea height deviations from the marine geoid are binned against altimeter U10 and SWH, becoming an easier method to implement, directly solving for SSB by imposing a constant a priori mean sea level at each altimeter observation location thus eliminating the geoid. The following equation represents this relation:…”

“…Later on, SSB estimates were obtained using fitted empirical models derived from two predictors retrieved from the analysis of altimeter data, the altimeter-derived SWH and wind speed (U10), with the latter based on radar backscatter cross-section measurements (σ 0 ). Since then, different statistical approaches have been considered to better characterize the SSB, parametric formulations of both SWH and U10 in linear, polynomial or quadratic forms, estimating a number of coefficients [5], and nonparametric techniques using different statistical approaches as the kernel smoothing method [6], local linear kernel smoothing [7] or smoothing splines [8]. Before fitting the models, SSB estimates can be retrieved by sea surface height (SSH) differences at crossover points, along collinear tracks or directly estimated from the residuals between SSH and an MSS over the SWH and U10 domain [9].…”

On the satellite altimeter crossover problem

“…For the tidal corrections we have used the Schwiderski model as given on the MDGRs, enhanced by the correction model given by Schrama and Ray (1994), but omitting their T/P-derived Sa and Ssa terms, since they include in these terms annual and semi-annual non-tidal effects we wish to see show up in our results. The four parameter model developed by Gaspar et al (1994) has been used for correcting the sea-state bias (with different correction coefficients for the TOPEX OPEX and Poseidon altimeters). The new calibration value of sigma0 recommended by Callahan et al (1994) has been used in calculating the wind speed contribution to the sea-state bias.…”