A KU-BAND LABORATORY EXPERIMENT ON THE ELECTROMAGNETIC BIAS

Sea-surface electromagnetic bias (EM bias), the difference between the mean reflecting surface and the geometric mean sea level, must be accurately determined to realize the full potential of satellite altimeters. A uniformly valid algorithm relating the normalized (or nondimensional) EM bias, i.e., ''bias/significant wave height,'' to physical variables has not yet been established, so we conducted laboratory experiments to guide model development. Simultaneous and collocated measurements of surface topography and altimeter back-scattered power were made in the large IMST wind-wave facility for a wide range of wind and mechanically generated wave conditions. A small microwave footprint on the water surface was produced by a focused-beam 13.5 GHz radar system that has a high signal-to-noise ratio. Consequently specular facets are easily identifiable and the data show that troughs are on average better reflectors than crests. Dimensional relations seldom yield robust algorithms and in fact, although rather high correlation is found between normalized EM bias and either wind speed or wave height, the laboratory coefficients are considerably greater than those of in situ algorithms. Nondimensional parameterization is more useful for deriving scaling laws, and when the normalized EM bias is displayed as a function of wave height skewness or wave age, laboratory and field data converge into consistent trends. In particular, normalized bias decreases with wave age, but unfortunately, even the wave age model does not account for the effects of mechanically generated waves, which produce appreciable scatter relative to the pure wind cases. Thus, we propose a two-parameter model using 1) a nondimensional wave height, which is computed for local winds, and 2) a significant slope, which is computed for nonlocally generated waves. Analysis of the laboratory data shows that the normalized EM bias for mixed conditions is well modeled as a product of these two parameters.