Impact of high‐frequency waves on the ocean altimeter range bias

Abstract

[1] New aircraft observations are presented on the range determination error in satellite altimetry associated with ocean waves. Laser-based measurements of the cross correlation between the gravity wave slope and elevation are reported for the first time. These observations provide direct access to a long, O(10 m), gravity wave statistic central to nonlinear wave theory prediction of the altimeter sea state bias. Coincident Ka-band radar scattering data are used to estimate an electromagnetic (EM) range bias analogous to that in satellite altimetry. These data, along with ancillary wind and wave slope variance estimates, are used alongside existing theory to evaluate the extent of long-versus shortwave, O(cm), control of the bias. The longer wave bias contribution to the total EM bias is shown to range from 25 to as much as 100%. Moreover, on average the term is linearly related to wind speed and to the gravity wave slope variance, consistent with WNL theory. The EM bias associated with interactions between long and short waves is obtained assuming the effect is additive to the independently observed long-wave factor. This second component is also a substantial contributor, is observed to be quadratic in wind speed or wave slope, and dominates at moderate wind speeds. The behavior is shown to be consistent with EM bias prediction based in hydrodynamic modulation theory. Study implications for improved correction of the on-orbit satellite sea state bias are discussed.

Small‐scale open ocean currents have large effects on wind wave heights

“…That error can be reduced with accurate estimates of wave parameters both along and across the satellite track. Airborne measurements [ Vandemark et al ., ] give a sea state bias (SSB) in Ka‐band that is of the order of 3% of the significant wave height H s [ Valladeau et al ., ]. Without any information on the cross‐track variations in H s , and assuming that the SSB is fully determined by H s alone, the spectrum of range error at 50 km away from the nadir would be times the wave height spectrum shown in Figure .…”

Impact of Surface Waves on SWOT’s Projected Ocean Accuracy

“…Measurements at Ka band indicate the EM bias ranges from 1% to 3% of the SWH [19]. The backscattering in Equation (8) modulates the radar response such that measured height is a nonlinear function of the wave height, in a similar fashion as the surfboard sampling, also spreading the wave energy to longer wavelengths that are not filtered.…”

“…Although only approximate, this model is sufficient to demonstrate the non-linear sampling phenomena we are examining. A full assessment of realistic EM bias will require better models for both tilt and hydrodynamic modulations to take into account non-linear ocean features in modulation and slope [10,19].…”

“…To first order, if the radar footprint is large compared to the spatial scale of height variability, the effect of ocean waves on scattering can be viewed as due to an effective volume scattering layer. In order to quantify the impact of the volume scattering introduced by the waves, and following a similar approach as presented by Rodriguez and Martin [7], we model the statistics of the ocean surface height with a Gaussian probability function, (ℎ) = is the topographic mean height at a given point, and ℎ is the ocean height standard deviation, which is, relative, related to the significant wave height as = 4 ℎ [19]. The interferometric phase, , is approximately given by [7,8]:…”

“Choppy wave” model for nonlinear gravity waves

“…As already pointed out [ Elfouhaily et al , 1999], it can be crucial to determined the required input undressed spectrum for which the simulated moments remain consistent with a measured spectrum. The CWM can then be used to define an inversion scheme to consistently evaluate the first‐order cumulants (elevation skewness, the elevation and slope cross skewness) to evaluate the predicted long wave geometrical contribution to altimeter sea state bias [ Elfouhaily et al , 2000; Vandemark et al , 2005].…”