Influence of sea surface wind wave turbulence upon wind-induced circulation, tide–surge interaction and bed stress

Abstract

A three-dimensional finite volume unstructured mesh model of the west coast of Britain, with high resolution in the coastal regions, is used to investigate the role of wind wave turbulence and wind and tide forced currents in producing maximum bed stress in the eastern Irish Sea. The spatial distribution of the maximum bed stress, which is important in sediment transport problems, is determined, together with how it is modified by the direction of wind forced currents, tide-surge interaction and a surface source of wind wave turbulence associated with wave breaking. Initial calculations show that to first order the distribution of maximum bed stress is determined by the tide. However, since maximum sediment transport occurs at times of episodic events, such as storm surges, their effects upon maximum bed stresses are examined for the case of strong northerly, southerly and westerly wind forcing. Calculations show that due to tide-surge interaction both the tidal distribution and the surge are modified by non-linear effects. Consequently, the magnitude and spatial distribution of maximum bed stress during major wind events depends upon wind direction. In addition calculations show that a surface source of turbulence due to wind wave breaking in shallow water can influence the maximum bed stress. In turn, this influences the wind forced flow and hence the movement of suspended sediment. Calculations of the spatial variability of maximum bed stress indicate the level of measurements required for model validation.

Editorial—The 3rd International Workshop on Modeling the Ocean (IWMO 2011)

“…The subjects of papers in this special issue include four on data assimilations-hindcast and/or test forecast (i.e., using past data but without data assimilation; Isobe et al 2012;Miyazawa et al 2012;Yin et al 2012;Yao et al 2012), one on process sensitivity (Xing et al 2012), one on ice floe observation with modeling (Shu et al 2012), and two on processes with observational and modeling analyses (Ezer et al 2012;Wada et al 2012).…”