Abstract
A method for expedient characterization of maximum nearshore wave heights due to hurricanes is described. This method, referred to as the wave response function (WRF) method, relates hurricane parameters to maximum wave heights by fitting coefficients from the modified Shore Protection Manual (SPM) forecasting method to results from numerical surge-wave models. The method was applied to numerous locations along the U.S. Gulf Coast: Corpus Christi, Texas; Gulfport, Mississippi; and Panama City, Florida. The WRF method is shown to have the most skill of all similar methods tested. Similar accuracy levels were obtained across all test sites. Data from Hurricane Ike in 2008 provided validation for the method. Although not intended for forecasting, this approach can be applied to risk analysis and extreme value statistics with significantly less computational effort than the use of numerical models.
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Acknowledgments
The research presented in this paper was funded by the National Sea Grant College Program of the U.S. Department of Commerce’s National Oceanic and Atmospheric Administration (NOAA) (Grant No. NA10OAR4170099). The views expressed in this paper are those of the authors and do not necessarily reflect views of NOAA or any of its subagencies. The use of trade names does not constitute an endorsement in the use of these products by the U.S. Government. The authors would also like to thank Dr. Donald Slinn of the University of Florida and Ms. Mary Cialone of the Coastal and Hydraulics Laboratory, U.S. Army Engineer Research and Development Center for the modeled fields used for the Panama City, Florida, and Gulfport, Mississippi, sites, respectively. Discussions with Dr. Jennifer Irish of Virginia Tech were helpful in the development of this work.
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Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 143 • Issue 2 • March 2017
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© 2016 American Society of Civil Engineers.
History
Received: Sep 15, 2015
Accepted: Jun 7, 2016
Published online: Aug 11, 2016
Discussion open until: Jan 11, 2017
Published in print: Mar 1, 2017
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