[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.

No abstract

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

This paper provides an overview of the SWIM (Surface Waves Investigation and Monitoring) instrument which will be one of the two payload instruments carried by CFOSAT (China France Oceanography SATellite) with a planned launch date in mid-2018. SWIM is a real aperture wave scatterometer operated at near-nadir incidence angles and dedicated to the measurement of directional spectra of ocean waves. The SWIM flight model is currently being assembled and tested, its performance is being assessed and its prototype data processing algorithm is being developed. The aim of this paper is to provide a complete overview on the motivations and scientific requirements of this mission, together with a description of the design and characteristics of the SWIM instrument, and the analysis of its expected performances based on a pre-launch study. An end-to-end simulator has been developed to evaluate the quality of the data products, thus allowing the overall performance of the instrument to be assessed. Simulations run with two subsets of full orbit subsets show that the performances of the instrument and the inversion algorithms will meet the scientific requirements for the mission.

[1] Radar observations of the sea surface at C-Band and small incidence angles are used to investigate some properties of the surface slope probability density function (pdf). The method is based on the analysis of the variation of the radar cross-section with incidence angle, assuming a backscattering process following the Geometrical Optics theory. First, we assess the limit of this model in our experimental configuration by using simulations of radar cross-sections with a more accurate backscattering model, namely the Physical Optics model. We show that roughness properties with scales larger than 12 cm can be analyzed in our configuration (C-Band, incidence 7 to 16°). The radar data are then analyzed in terms of filtered mean square slope under the assumption of a Gaussian slope pdf. Dependence of the radar-derived mean square slopes (mss) with wind speed is analyzed, thanks to wind estimates obtained by using coincident observations of the same radar at larger incidence (around 32°). Furthermore an analysis of the anisotropy of the mean square slope is proposed. The results are discussed in comparison with those of Munk (1954a, 1954b), and with the mean square slopes derived from two surface models (Elfouhaily et al., 1997 andKudryavtsev et al., 2003). We find that the radar-derived values are in good agreement with Cox and Munk results, taking into account the filtering effect on radar-derived values. We also show that the surface model of Elfouhaily et al. yields good agreement for the omni directional mss, but a too large anisotropy of the mss. The model of Kudryavtsev provides a reasonable anisotropy of the mss, but overestimates the mss values in all directions. Finally, we propose an analysis of the radar data under a non-Gaussian assumption for the slope pdf, by applying the compound model suggested by Chapron et al. (2000) to our observations. To our knowledge, it is the first time that peakedness values are explicitly derived from radar observations, and documented as a function of azimuth and wind speed. We show that the peakedness (or kurtosis) of the slope pdf is not zero but weak (peakedness factor reaching about 0.20), and slightly increases with wind speed.Citation: Hauser, D., G. Caudal, S. Guimbard, and A. A. Mouche (2008), A study of the slope probability density function of the ocean waves from radar observations,

[1] The FETCH campaign was for a large part devoted to the measurement and analysis of turbulent fluxes in fetch-limited conditions. Turbulent measurements were performed on board the R/V L'Atalante, on an ASIS spar buoy and on aircraft. On the R/V L'Atalante, turbulent data were obtained from a sonic anemometer and from a microwave refractometer. The main focus of this paper is to present results of momentum and heat fluxes obtained from the R/V L'Atalante, using the inertial-dissipation method and taking into account flow distortion effects. Numerical simulations of airflow distortion caused by the ship structure have been performed to correct the wind measurements on the R/V L'Atalante during the FETCH experiment. These simulations include different configurations of inlet velocities and six relative wind directions. The impact of airflow distortion on turbulent flux parameterizations is presented in detail. The results show a very large dependence on azimuth angle. When the ship is heading into the wind (relative wind direction within ±38°of the bow), the airflow distortion leads to an overestimation of the drag coefficient, associated with a wind speed reduction at the sensor location. For relative wind directions of more than ±38°from the bow, flow distortion causes the wind to accelerate at the sensor location, which leads to an underestimate of the drag coefficient. The vertical displacement of the flow streamlines could not be fully established by numerical simulation, but the results are in qualitative agreement with those inferred from the data by prescribing the consistency of momentum flux as a function of azimuth angle. Both show that the vertical elevation of the flow can be considered as constant (1.21 m from numerical simulations) only within about ±20°from bow axis. Values of vertical displacements up to 5 m are found from the data for high wind speeds and beam-on flows. Our study also shows that the relative contributions of the streamline vertical displacement and the mean wind speed underestimate or overestimate vary significantly with relative wind direction. The relative contribution due to vertical streamline displacement is higher for heat flux than for momentum flux. The consistency of our correction for airflow distortion is assessed by the fact that the correction reduces the standard deviation of the drag coefficient: only if this correction is taken into account, do the curves of the drag coefficient versus wind speed become similar for data corresponding to wind in the bow direction and from the side. When the complete numerical airflow correction is applied to the data set limited to relative wind directions at ±30°from the bow axis, the drag coefficient formula is C D10N Â 1000 = 0.56 + 0.063 U 10N , for U 10N > 6 m s À1 . This formula provides C D10N values comparable to the ones found from the ASIS buoy data for wind speeds of about 13 m s À1 . They are however smaller by 9% at higher winds (>15 m s À1 ). This formula is also similar, within a few percent, to the parameterizati...

No abstract