Abstract

The main objective of the present work is the probabilistic representation of coastal storms’ parameters through non-parametric probability distributions that can give satisfactory estimates in the whole range of the variables’ values. Their proper probabilistic representation can provide crucial information for many applications including the probabilistic design of marine and coastal structures. Different non-parametric univariate distributions in combination with different copula types or the conditional model are applied, to check the closeness of their fit to the available bivariate coastal storm data (e.g., the storms’ maximum wave height and the associated peak wave period). Moreover, except for the classical kernel distribution, a new, recently developed Box-Cox transformed kernel method is also examined and applied. The latter has been already evaluated so far to sea states data but not to storm data. Therefore, the adopted methodology is implemented to real coastal storms in two different locations, derived from wave recordings from Mykonos (Greece) and Barcelona (Spain). Furthermore, some of the significant statistical properties of the observed coastal storms, such as the calm period, the duration, and the shape (triangular or trapezoid) are also detected. From the present analysis, the derived methodology for representing accurately coastal storms is clarified, giving thus a useful tool to engineers and researchers to consider extreme events probability of occurrence, which is essential for the design of coastal structures and consequently for the protection of coastal communities.

DOI

10.1016/j.apor.2023.103563

Publication Date

2023-06-01

Publication Title

Applied Ocean Research

Volume

135

Publisher

Elsevier BV

ISSN

0141-1187

Embargo Period

2024-11-22

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