Radar observations of the ocean surface are becoming increasingly important. Common applications are wind retrieval and global weather forecasting and characterization. Because of the common use of ocean radar measurements, it is important to understand the sensitivity of the backscatter to both radar parameters and surface parameters. At near-normal incidence angles, it has been assumed that the radar backscatter exhibits little or no azimuth dependence (Colton, 1989). However, recent data taken by the BYU YSCAT radar system suggests that this is not the case. At an incidence angle of 10°, the YSCAT radar data shows from a fraction of a decibel to up to 10 decibels of azimuth modulation, depending on the surface conditions. In this thesis, a physical optics approach is used with a two-dimensional surface model to derive the electromagnetic backscatter from the ocean surface. If the waves on the ocean surface are directed, azimuth modulation is predicted at near-normal incidence angles. The effects of surface and radar parameters on the azimuth modulation are studied, and the results are compared to data taken by the YSCAT radar system. It is shown that the theory correctly predicts of the shape of the curve when the normalized radar cross-section is plotted as a function of azimuth angle. The theory also predicts the correct trend of the modulation magnitude as function the surface roughness. However, the simplifications in the model limit its prediction of the frequency dependence of the modulation. Relaxing some of the assumptions of the model is likely to correct this problem.

YSCAT is a unique ultrawideband microwave scatterometer developed to investigate the sea surface under a variety of environmental and radar parameters. The YSCAT94 experiment consisted of a six month deployment on the WAVES research tower operated by the Canada Center for inland Waters (CCIW). Over 3500 hours of data were collected at 2Γ 3.05Γ 5.3Γ 10.02Γ and 14 GHz and at a variety of wind speeds, relative azimuth angles, and incidence angle. A low wind speed "rolloff" of the normalized radar cross section (σ°) in YSCAT94 data is found and quantified. The rolloff wind speedΓ γΓ is estimated through regression estimation analysis using an Epanechnikov kernel. For YSCAT94 data, the rolloff is most noticeable at mid-range incidence angles with γ values ranging from 3 to 6 m/s. In order to characterized YSCAT94 backscatter distributions, a second order polynomial in log space is developed as a model for the probability of the radar cross sectionΓρ(σ°). Following Gotwols and ThompsonΓρ(σ°) is found to adhere to a log-normal distribution for horizontal polarization and a generalized log-normal distribution for vertical polarization. If ρ(α|σ°) is assumed to be Rayleigh distributed, the instantaneous amplitude distribution ρ(α) is found to be the integral of a Rayleigh/generalized log-normal distribution. A robust algorithm is developed to fit this probability density function to YSCAT94 backscatter distributions. The mean and variance of the generalized log-normal distribution are derived to facilitate this algorithm. Over 2700 distinct data cases sorted according to five different frequencies, horizontal and vertical polarizations, upwind and downwind, eight different incidence angles Γ1-10 m/s wind speeds, and 0.1-0.38 mean wave slope are considered. Definite trends are recognizable in the fitted parameters a1Γ a2Γ and C of the Rayleigh/generalized log-normal distribution when sorted according to wind speed and mean wave slope. At mid-range incidence angles, the Rayleigh/generalized log-normal distribution is found to adequately characterize both low and high amplitude portions of YSCAT94 backscatter distributions. However, at higher incidence angels (50°and 60°) the more general Weibull/generalized log-normal distributions is found to better characterized the low amplitude portion of the backscatter distributions.