Surface Waves Prediction Based on Long-Range Acoustic Backscattering in a Mid-Frequency Range

Underwater acoustic echosounding for surface roughness parameters retrieval is studied in a frequency band that is relatively new for such purposes. During the described 2-weeks sea experiment, 1–3 kHz tonal pulses were emitted from an oceanographic platform, located on the northern Black Sea shelf. Doppler spectra of the resulting reverberation were studied. The frequency band of the acoustic system, selected for this study, is chosen due to the fact that the sound propagation range is large enough for remote sensing in a coastal zone, and the resolution cell size does not limit the research. Backscattering of acoustical signals was received for distances around two nautical miles. However, it turned to be quite difficult to interpret the obtained data since backscattering spectrum shape was influenced by a series of effects, resulting in a complicated link to wind waves and currents’ parameters. Significant wave height and dominant wave frequency were estimated as the result of such signals processed with the use of machine learning tools. A decision-tree-based mathematical regression model was trained to solve the inverse problem. Wind waves prediction is in a good agreement with direct measurements, made on the platform, and machine learning results allow physical interpretation

Surface Waves Prediction Based on Long-Range Acoustic Backscattering in a Mid-Frequency Range

Underwater acoustic echosounding for surface roughness parameters retrieval is studied in a frequency band that is relatively new for such purposes. During the described 2-weeks sea experiment, 1–3 kHz tonal pulses were emitted from an oceanographic platform, located on the northern Black Sea shelf. Doppler spectra of the resulting reverberation were studied. The frequency band of the acoustic system, selected for this study, is chosen due to the fact that the sound propagation range is large enough for remote sensing in a coastal zone, and the resolution cell size does not limit the research. Backscattering of acoustical signals was received for distances around two nautical miles. However, it turned to be quite difficult to interpret the obtained data since backscattering spectrum shape was influenced by a series of effects, resulting in a complicated link to wind waves and currents’ parameters. Significant wave height and dominant wave frequency were estimated as the result of such signals processed with the use of machine learning tools. A decision-tree-based mathematical regression model was trained to solve the inverse problem. Wind waves prediction is in a good agreement with direct measurements, made on the platform, and machine learning results allow physical interpretation

On Capabilities of Tracking Marine Surface Currents Using Artificial Film Slicks

It is known that films on the sea surface can appear due to ship pollution, river and collector drains, as well as natural biological processes. Marine film slicks can indicate various geophysical processes in the upper layer of the ocean and in the atmosphere. In particular, slick signatures in SAR-imagery of the sea surface at low and moderate wind speeds are often associated with marine currents. Apart from the current itself, other factors such as wind and the physical characteristics of films can significantly influence the dynamics of slick structures. In this paper, a prospective approach aimed at measuring surface currents is developed. The approach is based on the investigation of the geometry of artificial banded slicks formed under the action of marine currents and on the retrieval of the current characteristics from this geometry. The developed approach is applied to quasi stationary slick bands under conditions when the influence of the film spreading effects can be neglected. For the stationary part of the slick band where transition processes of the band formation, e.g., methods of application of surfactants on water, film spreading processes, possible wind transformation etc., become negligible, some empirical relations between the band geometrical characteristics and the characteristics of the surface currents are obtained. The advantage of the approach is a possibility of getting information concerning the spatial structure of marine currents along the entire slick band. The suggested approach can be efficient for remote sensing data verification