Storm waves focusing and steepening in the Agulhas current: Satellite observations and modeling - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Remote Sensing of Environment Année : 2018

Storm waves focusing and steepening in the Agulhas current: Satellite observations and modeling

Résumé

Strong ocean currents can modify the height and shape of ocean waves, possibly causing extreme sea states in particular conditions. The risk of extreme waves is a known hazard in the shipping routes crossing some of the main current systems. Modeling surface current interactions in standard wave numerical models is an active area of research that benefits from the increased availability and accuracy of satellite observations. We report a typical case of a swell system propagating in the Agulhas current, using wind and sea state measurements from several satellites, jointly with state of the art analytical and numerical modeling of wave-current interactions. In particular, Synthetic Aperture Radar and altimeter measurements are used to show the evolution of the swell train and resulting local extreme waves. A ray tracing analysis shows that the significant wave height variability at scales <~100 km is well associated with the current vorticity patterns. Predictions of the WAVEWATCH III numerical model in a version that accounts for wave-current interactions are consistent with observations, although their effects are still under-predicted in the present configuration. From altimeter measurements, very large significant wave height gradients are shown to be well captured, and also associated with the current vorticity patterns at global scale.
Fichier principal
Vignette du fichier
57867.pdf (4.34 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-04202161 , version 1 (06-10-2023)

Identifiants

Citer

Yves Quilfen, M. Yurovskaya, Bertrand Chapron, Fabrice Ardhuin. Storm waves focusing and steepening in the Agulhas current: Satellite observations and modeling. Remote Sensing of Environment, 2018, 216, pp.561-571. ⟨10.1016/j.rse.2018.07.020⟩. ⟨hal-04202161⟩
18 Consultations
1 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More