Survey of stochastic models for wind and sea state time series

Type Article
Date 2007-04
Language English
Author(s) Monbet Valérie1, 2, Ailliot P1, Prevosto MarcORCID2
Affiliation(s) 1 : Univ S Brittany, Dept Appl Stat, F-56017 Vannes, France.
2 : IFREMER, Ctr Brest, ERT HO, Hydrodynam & Metocean, F-29280 Plouzane, France.
Source Probabilistic Engineering Mechanics (0266-8920) (Elsevier), 2007-04 , Vol. 22 , N. 2 , P. 113-126
DOI 10.1016/j.probengmech.2006.08.003
WOS© Times Cited 59
Keyword(s) Model validation, Simulation, Nonlinear time series, Wind, Sea state
Abstract The knowledge of sea state and wind conditions is of central importance for many offshore and nearshore operations. In this paper, we make a complete survey of stochastic models for sea state and wind time series. We begin with methods based on Gaussian processes, then non-parametric resampling methods for time series are introduced followed by various parametric models. We also propose an original statistical method, based on Monte Carlo goodness-of-fit tests, for model validation and comparison and this method is illustrated on an example of multivariate sea state time series. (C) 2006 Elsevier Ltd. All rights reserved.
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