Evidence of Ocean Waves Signature in the Space-Time Turbulent Spectra of the Lower Marine Atmosphere Measured by a Scanning LiDAR

To achieve more accurate weather and climate forecasting, and propose efficient engineering solutions for exploiting offshore renewable energies, it is imperative to accurately describe the atmospheric turbulent flow in the offshore environment. The ocean's dynamics raise specific challenges for the aforementioned applications, as they significantly alter the atmospheric flow through complex wind-wave interactions. These interactions are important in fairly common situations and notably in old-sea conditions, where ocean waves travel fast, under comparatively slow wind velocities. In the present study, a scanning LiDAR (sLiDAR) was deployed on the shore to study micro-scale wind-wave interactions by performing horizontal scans 18 m above the ocean, and as far as 2 km from the coast. In the proposed configuration, and in the test cases presented in old seas, the sLiDAR captures wave-induced disturbances propagating into the lower part of the marine atmospheric boundary layer. Based on measurements of high-resolution space-time maps of the Radial Wind Speed, an original two-dimensional spectral analysis of the space-time auto-correlation functions was performed. Unlike more conventional data-processing techniques, and as long as the waves travel sufficiently (similar to twofold) faster than the mean wind at the measurement height, the upward transfer of motions from the waves to the wind can be clearly distinguished from the atmospheric turbulence in the wave-number-angular-frequency (k-w) turbulent spectra. These are the first space-time auto-correlation functions of the wind velocity fluctuations obtained at micro-scales above the ocean. The analyses demonstrate sLiDAR systems' applicability in measuring k-w-dependent turbulent spectra in the coastal environment. The findings present new perspectives for the study of micro-scale wind-wave interactions.

Automated summary

Accurately describing atmospheric turbulent flow in the offshore environment is crucial for more accurate weather and climate forecasting and efficient engineering solutions for exploiting offshore renewable energies. This study deployed a scanning LiDAR to study micro-scale wind-wave interactions and discovered the effects of waves on wind speed, providing new perspectives for the study of micro-scale wind-wave interactions.