Issue |
E3S Web Conf.
Volume 376, 2023
International Scientific and Practical Conference “Environmental Risks and Safety in Mechanical Engineering” (ERSME-2023)
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Article Number | 03021 | |
Number of page(s) | 9 | |
Section | III Civil and Environmental Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202337603021 | |
Published online | 31 March 2023 |
Statistical modeling of the sea surface in the presence of abnormal waves
Marine Hydrophysical Institute, RAS, Kapitanskaya str., 2, 299011, Sevastopol, Russia
* Corresponding author: sevzepter@mail.ru
A wide range of fundamental and applied problems requires a detailed description of the statistics of abnormal sea waves (freak waves or rouge waves). These waves are characterized not only by a change in ener-gy, but also by strong nonlinearity, leading to extreme values of the higher cumulants. The possibilities and limitations of modeling the probability density function (PDF) of sea surface elevations by a two-component Gaussian mixture at extreme values of skewness and excess kurtosis are analyzed. The parameters of a two-component Gaussian mixture are calcu-lated from known values of statistical moments. Model PDFs in the form of a two-component Gaussian mixture are compared with PDFs based on direct wave measurement data, and also compared with the known Gram-Charlier distribution. It is shown that with positive values of the excess kurtosis, the PDF in the form of a two-component Gaussian mixture can be constructed at the limit values of the skewness and excess kurtosis ob-tained in different regions of the World Ocean. With large negative values of the kurtosis, the shape of the probability density function is strongly dis-torted, which indicates the limit of applicability of a two-component Gaussian mixture to the description of such situations.
Key words: Two-Component Gaussian Mixture / Sea Surface / Elevation Distribution
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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