Development of a New Generation of Ocean Wave Prediction Tool

The accurate prediction of ocean wave-field evolutions under general offshore and coastal environments is a challenging task due to highly irregular wind distribution and wave-breaking dissipation, and to a lesser extent, current and bottom bathymetry variations. Details of the many dynamical processes involved, such as wind-wave generation, wave breaking, and bottom dissipation, are also not well understood or modeled. Until recently, phase-averaged models such as WAM (for deep ocean) and SWAN (for near-shore regions) are the only practical prediction tools available. The present models are developed based on the phase-averaged energy-balance equation with the physical effects associated with nonlinear wave interactions, wind input, and wave-breaking/bottom dissipations modeled as source terms. Typically, the Hasselmann’s integral is adopted for the evaluation of nonlinear wave interaction effects while empirical formulae with parameterizations are employed for the determination of wind pumping and wave-breaking/bottom dissipations. There has been much progress in global and regional wave predictions and good comparisons to field and laboratory measurements have been obtained in some cases. Due to necessary simplifications and assumptions inherent, however, the predictions often fall outside of the error band of the observations.

The present phase-averaged approaches suffer from a number of basic attributes that in fundamental and practical ways limit their ability to make major further improvements/advances in key areas. At a basic level, modeling of the phase-averaged wave action evolutions themselves, while computationally more expedient, does not allow the inclusion of physical processes in a direct mechanistic manner that can be obtained in direct nonlinear phase-resolved simulations. For instance, existing phase-averaged approaches are essentially based on a linearized framework for wave propagation and wave action evolution with only partial accounts of nonlinear wave-wave interactions (in terms of approximate triad and quartet resonant interactions only). The effects of wave reflection by current and bottom topography, and wave scattering by rapidly varying bottom are generally neglected. The wavenumber dependence of wave-breaking/bottom dissipations cannot be easily considered. To overcome these limitations requires a fundamental reconsideration of the basic formulation.

With recent rapid development of computational capabilities and, more significantly, fast algorithms for phase-resolved simulations of nonlinear wave-fields, the time and opportunity have arrived for the development of direct phase-resolved simulations to complement and, in the foreseeable future, to be a practical alternative to phase-averaged models for ocean wave predictions. The purpose of this project is to develop a new powerful capability, which we call SNOW (simulations of nonlinear ocean wave-field) hereafter, for predicting the evolution of large-scale nonlinear ocean wave-fields using direct physics-based phase-resolved simulations. SNOW is fundamentally different from the existing phase-averaged models in that, under SNOW, key physical mechanisms such as wave-current, wave-wind and wave-bottom interactions and wave-breaking dissipation are modeled, evaluated and calibrated in a direct physics-based context. In SNOW, detailed phase-resolved information about the wave-field is obtained, from which the statistical wave properties can also be derived. In the near term, SNOW provides a powerful framework for the assessment and improvement of phase-averaged wave-prediction models (e.g. WAM and SWAN), as well as a direct model for the evaluation and cross-calibration/validation of laboratory and field measurements. With timely development, we believe that in the foreseeable future, SNOW can serve as a powerful new modeling tool, complementing existing capabilities, for the deterministic forecasting of ocean waves for naval operations and to improving our understanding and interpretation of remotely-sensed sea-surface data.