Technical Papers
Oct 12, 2017

Sensitivity of Storm Surge Predictions to Atmospheric Forcing during Hurricane Isaac

Publication: Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 144, Issue 1

Abstract

Storm surge and overland flooding can be predicted with computational models at high levels of resolution. To improve efficiency in forecasting applications, surge models often use atmospheric forcing from parametric vortex models, which represent the surface pressures and wind fields with a few storm parameters. The future of storm surge prediction could involve real-time coupling of surge and full-physics atmospheric models; thus, their accuracies must be understood in a real hurricane scenario. The authors compare predictions from a parametric vortex model (using forecast tracks from the National Hurricane Center) and a full-physics coupled atmosphere-wave-ocean model during Hurricane Isaac (2012). The predictions are then applied within a tightly coupled, wave and surge modeling system describing the northern Gulf of Mexico and the floodplains of southwest Louisiana. It is shown that, in a hindcast scenario, a parametric vortex model can outperform a data-assimilated wind product, and given reasonable forecast advisories, a parametric vortex model gives reasonable surge forecasts. However, forecasts using a full-physics coupled model outperformed the forecast advisories and improved surge forecasts. Both approaches are valuable for forecasting the coastal impacts associated with tropical cyclones.

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Acknowledgments

This research was made possible by a grant from the Gulf of Mexico Research Initiative. Data are publicly available through the Gulf of Mexico Research Initiative Information & Data Cooperative (GRIIDC) at https://data.gulfresearchinitiative.org and with the following Digital Object Identifiers (DOIs): 10.7266/N7QR4V62, (Dietrich et al. 2017a), 10.7266/N7GB2251 (Dietrich et al. 2017b), and 10.7266/N7BK19F9 (Dietrich et al. 2017c).

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Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 144Issue 1January 2018

History

Received: Dec 21, 2016
Accepted: Jun 6, 2017
Published online: Oct 12, 2017
Published in print: Jan 1, 2018
Discussion open until: Mar 12, 2018

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J. C. Dietrich, Aff.M.ASCE [email protected]
Assistant Professor, Dept. of Civil, Construction, and Environmental Engineering, North Carolina State University, 2501 Stinson Dr., Raleigh, NC 27607 (corresponding author). E-mail: [email protected]
A. Muhammad [email protected]
Project Manager, United Airlines, 165 W Superior St., Apt. 2903, Chicago, IL 60654. E-mail: [email protected]
Postdoctoral Researcher, Rosenstiel School of Marine and Atmospheric Science, Univ. of Miami, 4600 Rickenbacker Causeway, Miami, FL 33149. E-mail: [email protected]
Postdoctoral Researcher, Institute for Computational Engineering and Sciences, Univ. of Texas at Austin, 201 East 24th St., Stop C0200, Austin, TX 78712. E-mail: [email protected]
C. N. Dawson [email protected]
Professor, Institute for Computational Engineering and Sciences, Univ. of Texas at Austin, 201 East 24th St., Stop C0200, Austin, TX 78712. E-mail: [email protected]
Professor, Rosenstiel School of Marine and Atmospheric Science, Univ. of Miami, 4600 Rickenbacker Causeway, Miami, FL 33149. E-mail: [email protected]
R. A. Luettich Jr. [email protected]
Professor, Institute of Marine Sciences, Univ. of North Carolina at Chapel Hill, 3431 Arendell St., Morehead City, NC 28557. E-mail: [email protected]

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