Year

2014

Season

Spring

Paper Type

Master's Thesis

College

College of Computing, Engineering & Construction

Degree Name

Master of Science in Civil Engineering (MSCE)

Department

Engineering

NACO controlled Corporate Body

University of North Florida. School of Engineering

First Advisor

Dr. Donald T. Resio

Second Advisor

Dr. Nicholas Hudyma

Third Advisor

Dr. Peter Bacopoulos

Department Chair

Dr. Murat Tiryakioglu

College Dean

Dr. Mark A. Tumeo

Abstract

Tropical cyclones (TCs) Irene and Sandy caused major damages in back to back years to the most densely populated city in the United States stunning the residents with storms linked to seemingly impossible probabilities. Such activity has raised questions about the effect of non-stationary aspects within atmospheric circulation on storm behavior and some assumptions inherent in previous hazard studies of the New York City (NYC) area. This study analyzes statistical aspects of hazard quantification for this area related to this non-stationarity and statistical characterization. In particular this study investigates the presence of multiple populations of storms, it also tests current assumptions inherent in these previous studies which produce surge hazards which differ significantly and it investigates a natural relationship between storm characteristics and large scale climate variations through Empirical Orthogonal Functions (EOF) of the sea surface pressure.

The findings of this study show that there is a statistically significant influence of climate variability on storm frequency, intensity and direction within the Battery and vicinity (BAV, Battery Park and surrounding region). Variations in large-scale atmospheric pressure patterns as well as sea surface temperature appear to be significantly affecting the surge hazard for this region.

This study also shows there is a statistically significant relationship between storm heading and intensity as well as the presence of multiple populations of storms driven by different atmospheric states that behave with alternate characteristics. These multiple populations appear to be significantly influencing the overall average of storm behavior causing inaccurate assumptions in hazard quantification which leads to misestimation in risks.

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