The simulations are directly related to wind-wave tank experiments carried out for a range of steady wind velocities. A mitigating solution is offered.Ī numerical model that allows one to study numerically the evolution of waves along the test section of a wind-wave tank is offered. 4) The coarse resolution in National Data Buoy Center (NDBC) wave spectra causes large data scatter in the computed LPMSS in very high winds (greater than 20 m/s). In low-wind conditions (wind speed less than 5 m/s), the swell contribution is difficult to assess because of inaccuracy in identifying the weak windsea system. 3) Swell contribution to the L-band LPMSS is almost negligible for wind speed greater than 5 m/s (less than 5% in 99% of observations).

The normalized difference decreases with increasing wind speed and decreasing IWA. 2) Low-pass mean square slopes (LPMSSs) integrated to 5 and 11 rad/m are computed to quantify their difference as a function of wind speed and inverse wave age (IWA). Several related issues are discussed: high-frequency wave spectrum, integration limit, swell contribution, and measurements in extreme winds: 1) it is well known since the 1970s that with stationary sensors, extending the frequency range in measuring elevation spectrum does not yield useful short-wave information because of the low signal level and large Doppler frequency shift involved in measuring short waves. Examples are presented with wind and dominant wave data from ocean buoys and hurricane hunters. This article describes a method to obtain the L-band tilting ocean surface roughness using wind speed and windsea dominant wave period coupled with a wind-wave spectrum model. Waves much shorter than those measured by operational systems make significant contribution to the ocean surface roughness. Further discussions on the limitations of the conventional Fourier analysis and the Hilbert–Huang transform are also provided. We propose three integral quantities to characterize the spatially-variant wave field, including the direction angle, the characteristic wavenumber, and the wave energy. We also calculate the Hilbert spectrum and identify the features of coastal wave processes including refraction, shoaling and breaking. The impact of varying bathymetry is observed on the raw data obtained from the simulation and the large-scale components obtained from the empirical mode decomposition of the raw data. We then conduct wave-phase-resolved simulations based on a high-order spectral method, where the initial wave conditions are constructed for sea states with various wave field properties and the bathymetry profile varies continuously from deep water to shallow water. To address this issue, we propose a data-driven analysis framework based on the adaptive two-dimensional Hilbert–Huang transform, the accuracy of which is first demonstrated using synthetic wave data. The spatial inhomogeneity of the coastal wave field poses challenges to conventional Fourier analysis.

Quantitative characterization of the wave field nearshore is critical for coastal applications.

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