||Physical surface roughness represents the actual elevation variations in various scales at the air-sea interface. It is affected by the gravity waves and the aerodynamic factors in the atmospheric boundary layer. It is one of the most crucial factors that determine the momentum, heat and water vapor exchange between the air and sea. Due to the shoaling of gravity waves in the coastal ocean, sea surface roughness features significant deviation compared with those observed in deep seas. The understanding of the characteristics of surface roughness in coastal ocean is of great importance since it has much influence on the climate change, water cycle, carbon cycle, wind driven current/storm surge predictions and the assessment and operation of offshore wind energy conversion.|
So far, parameters of Drag coefficient, Cd and Aerodynamic Roughness length Z0 are used to infer the sea surface roughness. However, they do not fully reflect the contribution of gravity waves to the surface roughness. In order to realize the characteristics of the sea surface roughness in the coastal ocean, the Mean Square Slope, MSS of surface elevation was adopted as the index to describe the sea surface roughness.
In-situ observations were carried out at National Central University Coastal Observatory, TaiCOAST station located at the western coast of Taiwan. Synchronized observations of atmospheric boundary layer air-sea flux, gravity waves and current profiles, shore-based microwave radars were implemented during the period of northeast monsoon, i.e. from January 14, 2011 to January 31, 2011.
The Drag coefficient is estimated using eddy-covariance method. The Roughness length is estimated by using the wind profile method and the spectral method. MSS is estimated from the surface elevation recorded by the three bottom-mounted Acoustic Doppler Current Profilers (ADCP). The surface tracking mode was implemented to obtain high resolution water elevation from the acoustic transducers. The wavenumber spectra were then calculated from the frequency spectra using the linear wave dispersion relationship. The slope spectrum can be derived and the MSS can be estimated by taking the integral of the slope spectrum. The magnitude of MSS is highly influenced by the spectral tail of full-range wavenumber spectrum. For non-saturated limited depth waves, it is not yet clear about the tail shape in high wavenumber range. In present study, six hypothetic spectral shapes were tested. Moreover, the criteria that distinguishes the spectral bands that governed by three wave interactions or quadruplet wave interactions, was determined. By using the criteria, the MSS that obtained from the lower-frequency slope spectra are associated with gravity waves; whereas those from high-frequency are associated with the turbulence.
In present study, we use the absolute S-band radar backscatter intensity as reference to determine the tail property at the high wavenumber bands as well as the above-mentioned criteria. The result showed that the tail of full-range wavenumber spectrum is proportional to k-4. The best-fitted wavenumber cut-off wavenumber is about 42.3‧g/U102 . Futhermore, we discuss the dependency of the high-frequency MSS to the wind speed, and the low-frequency MSS to the wave age. The results show consistency with previous studies by Cox and Munk (1954). Moreover, when the wave age approximately equal to 0.8, the low-frequency MSS decreases. It is similar to the previous studies by Donelan(1990). Finally, an estimation of the contribution from the gravity waves to the surface roughness is about two-thirds at coastal oceans.
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