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Surf zone bathymetry and circulation predictions via data assimilation of remote sensing observations

ScholarsArchive at Oregon State University

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Title Surf zone bathymetry and circulation predictions via data assimilation of remote sensing observations
Names Wilson, G. W. (creator)
Özkan-Haller, H. T. (creator)
Holman, R. A. (creator)
Haller, M. C. (creator)
Honegger, D. A. (creator)
Chickadel, C. C. (creator)
Date Issued 2014-03-17 (iso8601)
Note This is the publisher’s final pdf. The published article is copyrighted by the American Geophysical Union and can be found at: http://onlinelibrary.wiley.com/journal/10.1002/%28ISSN%292169-9291.
Abstract Bathymetry is a major factor in determining nearshore and surf zone wave transformation and
currents, yet is often poorly known. This can lead to inaccuracy in numerical model predictions. Here
bathymetry is estimated as an uncertain parameter in a data assimilation system, using the ensemble Kalman
filter (EnKF). The system is tested by assimilating several remote sensing data products, which were
collected in September 2010 as part of a field experiment at the U.S. Army Corps of Engineers Field Research
Facility (FRF) in Duck, NC. The results show that by assimilating remote sensing data alone, nearshore
bathymetry can be estimated with good accuracy, and nearshore forecasts (e.g., the prediction of a rip current)
can be improved. This suggests an application where a nearshore forecasting model could be implemented
using only remote sensing data, without the explicit need for in situ data collection.
Genre Article
Topic nearshore
Identifier Wilson, G. W., H. T. Özkan-Haller, R. A. Holman, M. C. Haller, D. A. Honegger, and C. C. Chickadel (2014), Surf zone bathymetry and circulation predictions via data assimilation of remote sensing observations, Journal of Geophysical Research: Oceans, 119, 1993–2016. doi:10.1002/2013JC009213

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