Hurricane Ivan, a category 4 storm, passed directly over six wave-tide gauges deployed by the Naval Research Laboratory on the outer continental shelf in the northeastern Gulf of Mexico. Waves were observed with significant wave heights reaching 17.9 meters and maximum crest-to-trough individual wave heights of 27.7 meters (91 feet). Analysis suggests that significant wave heights likely surpassed 21 meters (69 feet) and that maximum crest-to-trough individual wave heights exceeded 40 meters (132 feet) near the eyewall.

Coexistence of wind sea generated locally and swell radiated from distant storms often results in double-peaked or multiple-peaked spectra. Identification and separation of the wave energies of wind sea and swell provide a more realistic description of the sea state, which is of great importance to scientific and engineering applications. This paper describes a method based on the peak frequency of a newly defined steepness function to separate the wave energies of wind sea and swell from the omnidirectional wave spectra. This steepness method does not rely on the availability of the information of wind velocities and wave directions and can be easily implemented for operational uses. Verification results using directional wave data collected from buoys in the Gulf of Mexico and offshore California are presented. Abstract Coexistence of wind sea generated locally and swell radiated from distant storms often results in double-peaked or multiple-peaked spectra. Identification and separation of the wave energies of wind sea and swell provide a more realistic description of the sea state, which is of great importance to scientific and engineering applications. This paper describes a method based on the peak frequency of a newly defined steepness function to separate the wave energies of wind sea and swell from the omnidirectional wave spectra. This steepness method does not rely on the availability of the information of wind velocities and wave directions and can be easily implemented for operational uses. Verification results using directional wave data collected from buoys in the Gulf of Mexico and offshore California are presented.

Recent results of numerical wave models have shown that the presence of a bimodal directional spreading is a robust feature at wavenumbers above the spectral peak. This directional bimodality is controlled mainly by directional transfer of energy through nonlinear wave–wave interactions. The bimodal feature has also been observed in the directional spectra derived from the spatial topography of ocean surface waves acquired by stereo-photography, image radars, and an airborne scanning lidar system. In this study, a comprehensive data analysis of the evolution of the wave directional distribution during two active wave growth periods in Lake Michigan is conducted. The wind and wave measurements are acquired by two heave–pitch–roll buoys moored at a nearshore and an offshore station. An empirical method averaging the results of the maximum likelihood method and maximum entropy method is used to estimate the directional distribution from buoy measurements. The study shows that the bimodal distributio... Abstract Recent results of numerical wave models have shown that the presence of a bimodal directional spreading is a robust feature at wavenumbers above the spectral peak. This directional bimodality is controlled mainly by directional transfer of energy through nonlinear wave–wave interactions. The bimodal feature has also been observed in the directional spectra derived from the spatial topography of ocean surface waves acquired by stereo-photography, image radars, and an airborne scanning lidar system. In this study, a comprehensive data analysis of the evolution of the wave directional distribution during two active wave growth periods in Lake Michigan is conducted. The wind and wave measurements are acquired by two heave–pitch–roll buoys moored at a nearshore and an offshore station. An empirical method averaging the results of the maximum likelihood method and maximum entropy method is used to estimate the directional distribution from buoy measurements. The study shows that the bimodal distributio...

Laboratory experiments were conducted to evaluate the feasibility of profiling and characterizing subsurface bubble plumes following a breaking wave event from an above-water Light Detection and Ranging (LiDAR) system. Measurements of LiDAR backscatter profiles of bubble plumes under mechanically generated breaking waves in a wave tank were collected and analyzed. After onset of wave breaking, the LiDAR backscatter increases rapidly by injected bubble plumes of active wave breaking. This intensification reaches a depth of one wave height within one wave period. After active wave breaking, the LiDAR backscatter from dissipated bubble plumes in the upper layer of water column decreases very slowly. The temporal variations of LiDAR backscatter are comparable to the collocated in-water measurements of optical backscatter at 850 nm wavelength and acoustic backscatter at 2000 kHz frequency. The decay rate of LiDAR backscatter of dissipated bubble plumes follows a power-law function consistent with decay rate of void fraction measurements in previous studies. This study demonstrates the viability and potential of using above-water LiDAR remote sensing to characterize subsurface bubble plumes.

This report consists of supplementary materials for an article, accepted for publication in the Journal of Atmospheric and Oceanic Technology, dealing with directional wave model validation by the same authors. These materials provide important background information for this companion paper, but were not included due to journal page limitations. Part I of this report provides a review of literature related to directional validation of wave models. Part II of this report discusses a number of issues that were raised by reviewers to the paper with particular focus on extensive non-directional validation of wave models. Also presented are validation of higher order moments, a summary of alternate methods of validation of directional spreading, a discussion of data-adaptive methods, and discussion of sensitivity of results to the handling of the high frequency range of the wave spectrum.