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Non-traditional stochastic models for ocean waves

Lindgren, Georg LU orcid ; Bolin, David LU and Lindgren, Finn LU (2010) In The European Physical Journal. Special Topics 185. p.209-224
Abstract
We present two flexible stochastic models for 2D and 3D ocean waves with potential to reproduce severe and non-homogeneous sea conditions. The first family consists of generalized Lagrange models for the movements of individual water particles. These models can generate crest-trough and front-back statistically asymmetric waves, with the same degree of asymmetry as measured ocean waves. They are still in the Gaussian family and it is possible to calculate different slope distributions exactly from a wave energy spectrum. The second model is a random field model that is generated by a nested stochastic partial differential equation. This model can be adapted to spatially non-homogeneous sea conditions and it can approximate standard wave... (More)
We present two flexible stochastic models for 2D and 3D ocean waves with potential to reproduce severe and non-homogeneous sea conditions. The first family consists of generalized Lagrange models for the movements of individual water particles. These models can generate crest-trough and front-back statistically asymmetric waves, with the same degree of asymmetry as measured ocean waves. They are still in the Gaussian family and it is possible to calculate different slope distributions exactly from a wave energy spectrum. The second model is a random field model that is generated by a nested stochastic partial differential equation. This model can be adapted to spatially non-homogeneous sea conditions and it can approximate standard wave spectra. One advantage with this model is that Hilbert space approximations can be used to obtain computationally efficient representations with Markov-type properties that facilitate the use of sparse matrix techniques in simulation and estimation. (Less)
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author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Lagrange waves, SPDE, Slepian models
in
The European Physical Journal. Special Topics
volume
185
pages
209 - 224
publisher
Springer
external identifiers
  • wos:000281112000018
  • scopus:77955907231
ISSN
1951-6355
DOI
10.1140/epjst/e2010-01250-y
language
English
LU publication?
yes
id
9c001113-9c7b-426c-b429-07722c9dc313 (old id 1666394)
date added to LUP
2016-04-01 13:47:22
date last changed
2022-01-27 21:05:02
@article{9c001113-9c7b-426c-b429-07722c9dc313,
  abstract     = {{We present two flexible stochastic models for 2D and 3D ocean waves with potential to reproduce severe and non-homogeneous sea conditions. The first family consists of generalized Lagrange models for the movements of individual water particles. These models can generate crest-trough and front-back statistically asymmetric waves, with the same degree of asymmetry as measured ocean waves. They are still in the Gaussian family and it is possible to calculate different slope distributions exactly from a wave energy spectrum. The second model is a random field model that is generated by a nested stochastic partial differential equation. This model can be adapted to spatially non-homogeneous sea conditions and it can approximate standard wave spectra. One advantage with this model is that Hilbert space approximations can be used to obtain computationally efficient representations with Markov-type properties that facilitate the use of sparse matrix techniques in simulation and estimation.}},
  author       = {{Lindgren, Georg and Bolin, David and Lindgren, Finn}},
  issn         = {{1951-6355}},
  keywords     = {{Lagrange waves; SPDE; Slepian models}},
  language     = {{eng}},
  pages        = {{209--224}},
  publisher    = {{Springer}},
  series       = {{The European Physical Journal. Special Topics}},
  title        = {{Non-traditional stochastic models for ocean waves}},
  url          = {{http://dx.doi.org/10.1140/epjst/e2010-01250-y}},
  doi          = {{10.1140/epjst/e2010-01250-y}},
  volume       = {{185}},
  year         = {{2010}},
}