Regional Frequency Analysis of Extreme Wave Heights: Trading Space for Time

Gelder, Pieter van; Ronde, John de; Neykov, N. M.; Neytchev, P. N.

doi:10.1061/40549(276)85

Cited by 14 publications

(11 citation statements)

References 22 publications

(18 reference statements)

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“…Another approach for predicting the maximum wave height over a spatial area were proposed in , based on 4D video data of sea states acquired through a wave acquisition stereo system (WASS) and using Euler Characteristics' theory. A regional frequency analysis of extreme wave heights, analyzing peaks-overthreshold wave data from nine locations along the Dutch North Sea coast was reported in Van Gelder et al (2001). The different locations could be considered as a homogeneous region and it was shown that the Generalized Pareto Distribution is an optimal regional probability distribution for the extreme wave heights for the region.…”

Section: Spatio-temporal Models For Extreme Wavesmentioning

confidence: 99%

“…Regional frequency analysis are widely used in hydrology and there are abundant literature on applications to extreme rainfall (Yang et al 2010;Nguyen et al 2002;Fowler and Kilsby 2003) and flooding (Leclerc and Ourada 2007;Saf 2010). Regional frequency analysis has also been applied in ocean engineering problems such as modelling of significant wave heights (Van Gelder et al 2001;Ma et al 2006) and the height of wave crests (Izadparast and Niedzwecki 2009).…”

Section: Regional Frequency Analysismentioning

confidence: 99%

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Long-term time-dependent stochastic modelling of extreme waves

Vanem

2010

Stoch Environ Res Risk Assess

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This paper presents a literature survey on timedependent statistical modelling of extreme waves and sea states. The focus is twofold: on statistical modelling of extreme waves and space-and time-dependent statistical modelling. The first part will consist of a literature review of statistical modelling of extreme waves and wave parameters, most notably on the modelling of extreme significant wave height. The second part will focus on statistical modelling of time-and space-dependent variables in a more general sense, and will focus on the methodology and models used also in other relevant application areas. It was found that limited effort has been put on developing statistical models for waves incorporating spatial and long-term temporal variability and it is suggested that model improvements could be achieved by adopting approaches from other application areas. In particular, Bayesian hierarchical space-time models were identified as promising tools for spatio-temporal modelling of extreme waves. Finally, a review of projections of future extreme wave climate is presented.

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Section: Spatio-temporal Models For Extreme Wavesmentioning

confidence: 99%

Section: Regional Frequency Analysismentioning

confidence: 99%

Long-term time-dependent stochastic modelling of extreme waves

Vanem

2010

Stoch Environ Res Risk Assess

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“…There are numerous studies regarding wave height distributions, regional failure probabilities such as de Haan and de Ronde (1998), Van Gelder et al (2000), and references therein. However, studies regarding extreme wave height co-movements can hardly be found in the literature.…”

Section: The Problemmentioning

confidence: 99%

The estimation of M4 processes with geometric moving patterns

Zhang

2006

AISM

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There are many parameters in multivariate maxima of moving maxima processes-or M4 processes. However, the more parameters there are, the more difficult it is to estimate them. It is not just an issue of numerical stability, of course. The statistical precision of the estimates will be poor if the number of parameters is too large. We consider asymmetric geometric structures which correspond to special moving patterns of extreme observations in observed time series. We study the model identifiability and propose parameter estimators. All proposed estimators are shown to be consistent and asymptotically joint normal. Simulation study and real data modeling of North Sea wave height data are illustrated.

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“…This method stems from the index flood model of (Darlymple 1960) and have been widely used in hydrology and meteorology to improve the estimation of flood hazard. Applications for coastal hazards are less frequent: (Goda et al 2010;Van Gelder et al 2000) conducted a RFA to the estimation of extreme waves, while (Bardet et al 2011;Bernardara et al 2011) dealt with extreme storm surges. (Stedinger and Lu 1995) showed RFA can provide more reliable estimations of extreme quantiles than local analyses.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Regional Frequency Analysis to the Estimation of Extreme Storm Surges

Weiss¹,

Bernardara²,

Benoît³

2012

Int. Conf. Coastal. Eng.

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Regional frequency analysis (RFA) is performed to estimate extreme storm surges along the French coasts of the Atlantic Ocean, the English Channel and the Southern part of the North Sea. An insight on the formation of physically homogeneous regions from a criterion of propagation of storms is provided. The treatment of the pairwise dependence structure within a given region through a spatial extreme value copula is also considered, leading to a model coupling physically-based RFA and spatial dependence to describe the probabilistic behavior of extreme storm surges.

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Regional Frequency Analysis of Extreme Wave Heights: Trading Space for Time

Abstract: In this paper a regional frequency analysis is suggested in order to obtain more accurate estimations for the tails of wave height distribution functions. A case study with wave height data on the Norts Sea is presented.

Cited by 14 publications

References 22 publications

Long-term time-dependent stochastic modelling of extreme waves

Long-term time-dependent stochastic modelling of extreme waves

The estimation of M4 processes with geometric moving patterns

Assessment of the Regional Frequency Analysis to the Estimation of Extreme Storm Surges

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