Given remote and direct physical measurements of a realistic ocean wavefield, the goal of this work was to obtain a high-resolution description of the wavefield by integrating the measurements with phase-resolved wave prediction models including realistic environmental effects such as wind forcing and wave breaking dissipation. The measurements necessary for achieving this reconstruction were guided, and the validity, accuracy, and limitations of such wavefield reconstructions were addressed.

Wavefield Reconstruction and Forecasting using HiRes wave measurements. The regions sensed by FLIP-based radars (green regions) and ATM (blue strip), and the location of the Datawell buoys (red spot), are indicated.
A comprehensive deterministic model was developed for intermediate-scale ocean wave prediction by integrating whole-field and multiple-point measurements of the wave environment with simulation- based wavefield reconstruction. The wave reconstruction is based on phase-resolved simulation of nonlinear ocean wave (SNOW) dynamics, and utilizes hybrid (from different types of sensors) wave measurements. The simulations also incorporate physics-based wind forcing and wave-breaking dissipation models, which are developed, validated, and calibrated based on field/ laboratory measurements.

Nonlinear wavefield reconstruction is based on an iterative optimization approach using multilevel phase-resolved wave models of different nonlinearity orders. Specifically, for low-level optimization sufficient for mild waves, the linear and secondorder Stokes solutions are used. For high-level optimization necessary for steep waves, an efficient nonlinear wave simulation model (SNOW) based on a high-order spectral method is employed. Once the wavefield is reconstructed, its future evolution is given by the wave propagation model using the reconstructed wavefield as the initial condition. In wave modeling, wind forcing is included through a pressure forcing on the free surface, and wave-breaking dissipation is considered by applying an effective low-pass filter to the wave elevation and surface potential in the spectral space. Other physical effects such as those of current and finite depth are also directly considered in wave modeling.

To assess the performance of wave measurements and model predictions, direct comparisons between wave model predictions and HiRes field measurements are obtained. The comparisons indicate that phase-resolved reconstruction and forecasting of realistic ocean wavefields can be achieved by this wave prediction model and non-coherence marine radar sensed wave data. The resolution of the reconstructed and forecasted wavefield depends critically on the accuracy of sensed wave data, which is largely affected by radar-data inversion algorithm and the platform motion. Based on the reconstructed and forecasted large-scale wavefields, this work shows that it is of importance to include nonlinear effects in wavefield evolution for accurately predicting the temporal-spatial information of rogue waves and nonlinear wave statistics.

To address the key question of whether a phase-resolved wave prediction can be achieved using radar data, the reconstructed and forecasted wavefield are compared to the independent buoy measurement. For this purpose, HiRes measurements in which radar data, buoy data, and ATM data are all available were used.

Based on radar sensed wave data, a phase-resolved nonlinear wavefield was reconstructed and compared to the independent buoy data in both the time history of the wave elevation and the wave spectrum. The comparison shows that for the wave spectrum, the agreement between the radar-databased prediction and the buoy measurement is very good. The predicted time-variation of the wave elevation has a ~45% correlation with the buoy measurement.

For the wave spectrum, the radar-data-based prediction agrees very well with the independent ATM measurement. For the phase-resolved sea surface, the nonlinear phase-resolved prediction (based on radar data) achieves a ~55% correlation with the ATM measurement.

This work was done by Dick K.P. Yue and Yuming Liu of the Massachusetts Institute of Technology for the Office of Naval Research. ONR-0030

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This article first appeared in the August, 2013 issue of Defense Tech Briefs Magazine.

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