Modelling significant wave height in the North Atlantic

The surface of the ocean, and so such quantities as the significant wave height, can be thought of as a random surface in space which develops over time. In this paper, we explore certain types of random fields (in space and time) as models for the significant wave height and fit these models to dat...

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Main Authors: Baxevani, Anastassia, Rychlik, Igor, Wilson, Richard J.
Format: Conference Object
Language:English
Published: 2003
Subjects:
Online Access:https://espace.library.uq.edu.au/view/UQ:d504d2e
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spelling ftunivqespace:oai:espace.library.uq.edu.au:UQ:d504d2e 2023-05-15T17:34:09+02:00 Modelling significant wave height in the North Atlantic Baxevani, Anastassia Rychlik, Igor Wilson, Richard J. 2003-12-01 https://espace.library.uq.edu.au/view/UQ:d504d2e eng eng Gaussian random fields Isotropy Random surface Satellite data Significant wave height Stationary Variogram 2102 Energy Engineering and Power Technology 2210 Mechanical Engineering 2212 Ocean Engineering Conference Paper 2003 ftunivqespace 2020-12-29T00:46:15Z The surface of the ocean, and so such quantities as the significant wave height, can be thought of as a random surface in space which develops over time. In this paper, we explore certain types of random fields (in space and time) as models for the significant wave height and fit these models to data obtained from the TOPEX-Poseidon satellite. The data consist of observations along different one-dimensional tracks over time. It is assumed that, for the region of ocean considered and for a fixed time, the data can be considered stationary. Further-more, the shape of the data suggests that it is reasonable to use a lognormal distribution. As the covariance function may change over time, the model chosen is fitted to the data for each time separately. The data over space exhibit variation at different scales and hence the covariance function needs to reflect this property. Consequently, a mixture of Gaussian functions is assumed for the covariance function. To fit the model to the data, the theoretical variogram is fitted to the empirical variogram using weighted least squares. Stochastic models for the variation of the parameter values were investigated. The results of fitting these models are discussed and interpreted. Conference Object North Atlantic The University of Queensland: UQ eSpace
institution Open Polar
collection The University of Queensland: UQ eSpace
op_collection_id ftunivqespace
language English
topic Gaussian random fields
Isotropy
Random surface
Satellite data
Significant wave height
Stationary
Variogram
2102 Energy Engineering and Power Technology
2210 Mechanical Engineering
2212 Ocean Engineering
spellingShingle Gaussian random fields
Isotropy
Random surface
Satellite data
Significant wave height
Stationary
Variogram
2102 Energy Engineering and Power Technology
2210 Mechanical Engineering
2212 Ocean Engineering
Baxevani, Anastassia
Rychlik, Igor
Wilson, Richard J.
Modelling significant wave height in the North Atlantic
topic_facet Gaussian random fields
Isotropy
Random surface
Satellite data
Significant wave height
Stationary
Variogram
2102 Energy Engineering and Power Technology
2210 Mechanical Engineering
2212 Ocean Engineering
description The surface of the ocean, and so such quantities as the significant wave height, can be thought of as a random surface in space which develops over time. In this paper, we explore certain types of random fields (in space and time) as models for the significant wave height and fit these models to data obtained from the TOPEX-Poseidon satellite. The data consist of observations along different one-dimensional tracks over time. It is assumed that, for the region of ocean considered and for a fixed time, the data can be considered stationary. Further-more, the shape of the data suggests that it is reasonable to use a lognormal distribution. As the covariance function may change over time, the model chosen is fitted to the data for each time separately. The data over space exhibit variation at different scales and hence the covariance function needs to reflect this property. Consequently, a mixture of Gaussian functions is assumed for the covariance function. To fit the model to the data, the theoretical variogram is fitted to the empirical variogram using weighted least squares. Stochastic models for the variation of the parameter values were investigated. The results of fitting these models are discussed and interpreted.
format Conference Object
author Baxevani, Anastassia
Rychlik, Igor
Wilson, Richard J.
author_facet Baxevani, Anastassia
Rychlik, Igor
Wilson, Richard J.
author_sort Baxevani, Anastassia
title Modelling significant wave height in the North Atlantic
title_short Modelling significant wave height in the North Atlantic
title_full Modelling significant wave height in the North Atlantic
title_fullStr Modelling significant wave height in the North Atlantic
title_full_unstemmed Modelling significant wave height in the North Atlantic
title_sort modelling significant wave height in the north atlantic
publishDate 2003
url https://espace.library.uq.edu.au/view/UQ:d504d2e
genre North Atlantic
genre_facet North Atlantic
_version_ 1766132890727350272