Abstract
We demonstrate the implementation and validation of a surf zone forecasting system, which uses remote sensing observations to control errors in surf zone bathymetry. This system uses ensemble-based sequential data assimilation techniques, which are adaptable to arbitrary geophysical observations, and/or arbitrary improvements to model physics. The system is validated using data from a 2010 field experiment at Duck, NC (U.S.A.), and is shown to produce accurate corrections to bathymetry, leading to improvements in prediction of currents.
Highlights
The dynamic nature of nearshore bathymetry is an important factor for prediction in the surf zone
A number of bathymetry estimation methods have been proposed using measurements of surface wave celerity obtained from remote sensing
The present work suggests remote sensing data alone is sufficient to provide useful information on surf zone bathymetry. This information can be used to control bathymetry error in a numerical model. This represents progress towards a surf zone forecasting system which can be driven by remote sensing data alone, without relying on continual bathymetric surveys
Summary
The dynamic nature of nearshore bathymetry is an important factor for prediction in the surf zone. Bathymetry error can play a leading order role in the accuracy of predicted waves and currents. This was demonstrated well by Allard et al (2008), who implemented and tested a sophisticated nearshore forecasting system, and identified bathymetric uncertainty (due to movement of sand bars) as a primary source of model error. Direct observation of bathymetry is often prohibitively expensive or even impossible depending on the region being studied For this and other reasons, innovative methods for estimating bathymetry have been developed by various authors. A number of bathymetry estimation methods have been proposed using measurements of surface wave celerity obtained from remote sensing. Even better accuracy can be obtained if measurements are integrated sequentially over a long period of time, as in the beach profile estimator developed by VanDongeren et al (2008) which is being extended for fully-3D bathymetric estimates using full-field video imagery by Holman et al (2012)
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