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A direct wave model based on the one-dimensional nonlinear equations for potential waves is used for simulation of wave field development under the action of energy input, dissipation, and nonlinear wave-wave interaction. The equations are written in conformal surface-fitted nonstationary coordinate system. New schemes for calculating the input and dissipation of wave energy are implemented. The wind input is calculated on the basis of the parameterization developed through the coupled modeling of waves and turbulent boundary layer. The wave dissipation algorithm, introduced to prevent wave breaking instability, is based on highly selective smoothing of the wave surface and surface potential. The integration is performed in Fourier domain with the number of modes M = 2048, broad enough to reproduce the energy downshifting. As the initial conditions, the wave field is assigned as train of Stokes waves with steepness ak = 0.15 at nondimensional wavenumber k = 512. Under the action of nonlinearity and energy input the spectrum starts to grow. This growth is followed by the downshifting. The total time of integration is equal to 7203 initial wave periods. During this time the energy increased by 1111 times. Peak of the spectrum gradually shifts from wavenumber nondimensional k = 512 down to k = 10. Significant wave height increases 33 times, while the peak period increases 51 times. Rates of the peak downshift and wave energy evolution are in good agreement with the JONSWAP formulation. [ABSTRACT FROM AUTHOR]

The concept of a constant-flux layer is usually employed for vertical profiling of the wind measured at some elevation near the ocean surface. The surface waves, however, modify the balance of turbulent stresses very near the surface, and therefore such extrapolations can introduce significant biases. This is particularly true for buoy measurements in extreme conditions, when the anemometer mast is within the wave boundary layer (WBL) or even below the wave crests. In this paper, field data and aWBL model are used to investigate such biases. It is shown that near the surface the turbulent stresses are less than those obtained by extrapolation using the logarithmic-layer assumption, and the mean wind speeds very near the surface, based on Lake George field observations, are up to 5% larger. The behavior is then simulated by means of a WBL model coupled with nonlinear waves, which confirmed the observations and revealed further details of complex behaviors at the wind-wave boundary layer. [ABSTRACT FROM AUTHOR]

Evolution of nonlinear wave groups to breaking under wind forcing was studied by means of a fully nonlinear numerical model and in a laboratory experiment. Dependence of distance to breaking and modulation depth (height ratio of the highest and the lowest waves in a group) on wind forcing was described. It was shown that in the presence of a certain wind forcing both distance to breaking and modulation depth decrease; the latter signifies slowing down of the instability growth. It was also shown that wind forcing significantly reduces the energy loss in a single breaking event. [ABSTRACT FROM AUTHOR]

The potential of Neural Networks (NN) to provide accurate estimates of nonlinear interactions for wind wave spectra by means of direct mapping is considered. Expanding on a previously reported feasibility study, an Empirical Orthogonal Functions (EOF) based NN for single peaked spectra is shown to be much more accurate than the well known Discrete Interaction Approximation (DIA), at the expense of a moderate increase of computational costs. This Neural Network Interaction Approximation (NNIA) gives reasonable results for modeled wave spectra, but is not yet capable of providing acceptable model integrations. Methods to expand the NNIA to be suitable for model integration are discussed. [Copyright &y& Elsevier]