

FOLLOWUS
1.First Institute of Oceanography, and Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266061, China
2.Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China
3.Shandong Key Laboratory of Marine Science and Numerical Modeling, Qingdao 266061, China
4.Ocean University of China, College of Oceanic and Atmospheric Sciences, Qingdao 266071, China
Tingting ZHANG,zhangtt@fio.org.cn
Received:10 June 2021,
Accepted:26 September 2021,
Online First:04 December 2021,
Published:2022-09
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Xingjie JIANG, Tingting ZHANG, Dalu GAO, et al. Estimating the evolution of sea state non-Gaussianity based on a phase-resolving model[J]. Journal of Oceanology and Limnology, 2022, 40(5): 1909-1923.
Xingjie JIANG, Tingting ZHANG, Dalu GAO, et al. Estimating the evolution of sea state non-Gaussianity based on a phase-resolving model[J]. Journal of Oceanology and Limnology, 2022, 40(5): 1909-1923. DOI: 10.1007/s00343-021-1236-1.
The occurrence of rogue waves is closely related to the non-Gaussianity of sea states
and this non-Gaussianity can be estimated using corresponding two-dimensional wave spectra. This paper presents an approach to non-Gaussianity estimation based on a phase-resolving model called the high-order spectral method (HOSM). Based on numerous HOSM simulations
a set of precalculated non-Gaussianity indicators was established that could be applied to real sea states without any calibration of spectral shapes. With a newly developed extraction approach
the indicators for given two-dimensional wave spectra could then be conveniently extracted from the precalculated dataset. The feasibility of the newly developed approach in a real wave environment is verified. Using the estimation approach
phase-resolved non-Gaussianity can now be illustrated throughout the evolution of sea states of interest
not just at a few specific times; and the level of non-Gaussianity at any time in a duration can be identified according to the statistics (e.g.
quantities) of the phase-resolved indicators
that are obtained throughout the duration concerned.
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