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Extreme storm surge hazard estimation in lower Manhattan

Madeleine Lopeman (), George Deodatis and Guillermo Franco

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2015, vol. 78, issue 1, 355-391

Abstract: The coastal destruction wreaked by Hurricane Sandy in 2012 prompted motivation to estimate the event’s return period. The Clustered Separated Peaks-over-threshold Simulation (CSPS) method for estimating return periods uses a Monte Carlo simulation of storm surge activity based on statistics derived from tidal gauge data at the Battery, New York in lower Manhattan. The data are separated into three independent components (storm surge, tidal cycle and sea level rise) because different physical processes govern different components of water level. Peak storm surge heights are fit to the generalized Pareto distribution, chosen for its ability to fit a wide tail to limited data. The algorithm incorporates the evolution of storm surge over surge duration. The CSPS suggests that the return period of Hurricane Sandy’s peak water level is 103 years (95% confidence interval 38–452 years), significantly lower than previously published return periods. The estimated 100-year water level is 5.23 m above the station datum (or 3.39 m above the North American Vertical Datum of 1988, or 3.45 m above mean sea level). With 1 m of sea level rise (holding all other climatological conditions constant), this water level would become the 28-year event. Although the method’s exclusion of surge-tide interaction and its reliance on a 90-year tidal gauge time history may limit the reliability of high return period estimates, application of the CSPS method to lower Manhattan suggests that storm surge hazard in the New York Harbor has, until now, been underestimated. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: Storm surge; Natural hazards; Extreme events; Peaks-over-threshold; Hurricane Sandy; Climate change (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11069-015-1718-6

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