alexa Climate Change Impact on Probability Analysis of Hurric
ISSN: 2157-7617

Journal of Earth Science & Climatic Change
Open Access

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Research Article

Climate Change Impact on Probability Analysis of Hurricanes

Keshtpoor M* and Mark Osler
Michael Baker International, Alexandria, VA 22304, USA
Corresponding Author : Keshtpoor M
Michael Baker International
Alexandria, VA 22304, USA
Tel: (571) 357-6002
E-mail: [email protected]
Received: January 03, 2016; Accepted: January 20, 2016; Published: January 26, 2016
Citation: Keshtpoor M, Osler M (2016) Climate Change Impact on Probability Analysis of Hurricanes. J Earth Sci Clim Change. 6:317. doi:10.4172/2157-7617.1000317
Copyright: © 2016 Keshtpoor M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Coastal flood risk due to cyclonic storms is a significant topic of concern for coastal communities. Planning and
engineering efforts within these communities often require estimates of water surface elevations associated with specific
return periods. In order to generate the surge elevations for prospective return periods, Joint Probability Method (JPM)
techniques are often used [1,2]. Within a JPM approach, statistical representations of cyclonic storm characteristics
(i.e. storm frequency, intensity, and radius to maximum wind) are parameterized, along with an associated probability
distribution for each parameter. The probability distributions for each of the major hurricane characteristics are based
on local historical climatology. A key assumption in the development of the probability distribution for the storm
parameters is that each is statistically stationary. Global climate models suggest that characteristics of cyclonic storms
may be impacted by climate change. Such changes would challenge the assumption of statistical stationary within the
traditional JPM approach. Here, a straightforward windowing approach is proposed to account for possible variation of
characteristics. This approach results in more recent storm events having a larger impact on the probability distribution
of storm parameters, should such an adjustment be judged necessary by the JPM practitioner. The application of the
proposed approach is demonstrated by applying on sample data sets of hurricanes at the mid-Atlantic region and South


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