Tidal motions in the Dover Straits as a variational inverse of the sea level and surface velocity data

Abstract

The M 2 tidal component of the flow in the Dover Straits is reconstructed using a natural combination of two independent data sources: HF Ocean Surface Current Radar (HF OSCR) system and coastal tidal measurements. The method used is the variational data assimilation technique into a quasi-linearized finite element tidal model. The model uses triangular elements with horizontal resolution varying from 800 to 1200 m. It is controlled by the boundary conditions at open boundaries, which are adjusted to fit the available data in an optimal way. A “weak” formulation of the dynamical constraints is used. The interpolation scheme allows small (0.01%) deviations from the exact dynamics specified by the model. The optimal state of M 2 parameters (sea surface elevation and depth-averaged velocities) is used to map both the M 2 tidal flux through the strait and the M 2 energy flux. The respective values obtained are the tidal flux amplitude 1.18±0.09×10 6 m 3 s −1, the net residual transport (Stoke's drift) 40±3×10 3 m 3 s −1, and the net energy flux 1.19±0.09×10 10 W. These figures within the statistically estimated error band are in the close agreement with those obtained by Prandle et al., 1993. A rigorous error analysis is performed using an explicit inversion of the Hessian matrix, associated with the assimilation scheme. As a result, error charts for M 2 velocities and sea surface elevation are obtained. It is shown that OSCR data combined with coastal level measurements and constrained by dynamics is able to provide quite accurate velocity estimates whose errors vary within the range of 0.05–0.45 m s −1 depending upon the location. Error maps also enable us to determine areas requiring better coverage by data, thus forming a basis of optimization approach to the design of the HFR measurements. The use of variational assimilation technique in providing integrated interpolation patterns from various sources of data demonstrates its capabilities in relation to future oceanographic monitoring systems of shelf circulation.