The Prediction of Nearshore Wind-induced Surface Currents from Wind Velocities Measured at Nearby Land Stations

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  • 1 British Maritime Technology Ceemaid Ltd, Southampton, Hampshire, United Kingdom
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Abstract

This paper aims to find a fast and efficient way to predict the wind-induced components of surface currents in a nearshore coastal area of several hundred square kilometers from wind velocities measured at nearby land stations. Ocean Surface Current Radar (OSCR) data collected in Poole Bay were used in the development of a predictive empirical methodology. The OSCR system measured the simultaneous surface currents at 260 positions (called OSCR cells), covering an area of about 270 km2 in which OSCR cells form a grid with a 1-km mesh.

In the conventional point-by-point approach, the time series of the surface currents at each OSCR cell is related to the forcing wind, producing a set of statistical parameters. The resultant database, with this set of parameters for each OSCR cell, is very large. Using the rotary empirical orthogonal function (EOF) approach, the low-frequency wind-induced components of the OSCR data over the whole region of deployment in Poole Bay can be characterized by a single EOF mode. The time variation of this EOF mode correlates strongly with that of the wind stress, and the coupling was found to be anisotropic (i.e., dependent on the wind direction). A phenomenological parameterized model was used to describe this anisotropic coupling. With only six time-independent real statistical parameters, the model predicts, with an accuracy of the order of 90%, the low-frequency wind-induced components of the surface currents in Poole Bay from the wind velocities measured at a nearby land station.

Abstract

This paper aims to find a fast and efficient way to predict the wind-induced components of surface currents in a nearshore coastal area of several hundred square kilometers from wind velocities measured at nearby land stations. Ocean Surface Current Radar (OSCR) data collected in Poole Bay were used in the development of a predictive empirical methodology. The OSCR system measured the simultaneous surface currents at 260 positions (called OSCR cells), covering an area of about 270 km2 in which OSCR cells form a grid with a 1-km mesh.

In the conventional point-by-point approach, the time series of the surface currents at each OSCR cell is related to the forcing wind, producing a set of statistical parameters. The resultant database, with this set of parameters for each OSCR cell, is very large. Using the rotary empirical orthogonal function (EOF) approach, the low-frequency wind-induced components of the OSCR data over the whole region of deployment in Poole Bay can be characterized by a single EOF mode. The time variation of this EOF mode correlates strongly with that of the wind stress, and the coupling was found to be anisotropic (i.e., dependent on the wind direction). A phenomenological parameterized model was used to describe this anisotropic coupling. With only six time-independent real statistical parameters, the model predicts, with an accuracy of the order of 90%, the low-frequency wind-induced components of the surface currents in Poole Bay from the wind velocities measured at a nearby land station.

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