[1] Data from five recent field campaigns are selected for pure wind sea, deep water, and fully rough flow conditions. The combined data set includes a wide range of wave ages, with high variability in both friction velocity and wave phase speed. These data, which are expected to follow Monin-Obukhov similarity scaling, are used to investigate the influence of wave age on wind stress. The relationship between the dimensionless roughness and inverse wave age is found to be z o /s = 13.4 (u * /c p ) 3.4 , where z o is the surface roughness length, s is the standard deviation of the surface elevation, u * is the friction velocity, and c p is the wave phase speed at the peak of the spectrum. This relationship, which represents a significant dependence of roughness on wave age, was obtained using a procedure that minimizes the effects of spurious correlation in u * . It is also shown to be consistent with the wave age relationship derived using an alternate form of the dimensionless roughness, namely, the Charnock parameter z o g/u * 2 , where g is the gravitational constant.

[1] Multiscale composite models based on the Bragg theory are widely used to study the normalized radar cross-section (NRCS) over the sea surface. However, these models are not able to correctly reproduce the NRCS in all configurations and wind wave conditions. We have developed a physical model that takes into account, not only the Bragg mechanism, but also the non-Bragg scattering mechanism associated with wave breaking. A single model was built to explain on the same physical basis both the background behavior of the NRCS and the wave radar Modulation Transfer Function (MTF) at HH and VV polarization. The NRCS is assumed to be the sum of a Bragg part (two-scale model) and of a non-Bragg part. The description of the sea surface is based on the short wind wave spectrum (wavelength from few millimeters to few meters) developed by Kudryavtsev et al. [1999] and wave breaking statistics proposed by Phillips [1985]. We assume that non-Bragg scattering is supported by quasi-specular reflection from very rough wave breaking patterns and that the overall contribution is proportional to the white cap coverage of the surface. A comparison of the model NRCS with observations is presented. We show that neither pure Bragg nor composite Bragg model is able to reproduce observed feature of the sea surface NRCS in a wide range of radar frequencies, wind speeds, and incidence and azimuth angles. The introduction of the non-Bragg part in the model gives an improved agreement with observations. In Part 2, we extend the model to the wave radar MTF problem.

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This paper describes first results obtained from the SWIM (Surface Waves Investigation and Monitoring) instrument carried by CFOSAT (China France Oceanography Satellite), which was launched on October 29 th , 2018. SWIM is a Ku-Band radar with a near-nadir scanning beam geometry. It was designed to measure the spectral properties of surface ocean waves. First, the good behavior of the instrument is illustrated. It is then shown that the nadir products (significant wave height, normalized radar cross-section and wind speed) exhibit an accuracy similar to standard altimeter missions, thanks to a new retracking algorithm, which compensates a lower sampling rate compared to standard altimetry missions. The off-nadir beam observations are analyzed in details. The normalized radar cross-section varies with incidence and wind speed as expected from previous studies presented in the literature. We illustrate that, in order to retrieve the wave spectra from the radar backscattering fluctuations, it is crucial to apply a speckle correction derived from the observations. Directional spectra of ocean waves and their mean parameters are then compared to wave model data at the global scale and to in situ data from a selection of case studies. The good efficiency of SWIM to provide the spectral properties of ocean waves in the wavelength range [70m-500m] is illustrated. The main limitations are discussed, and the perspectives to improve data quality are presented. 1