Probability distributions for maximum wave and crest heights

Prevosto, Marc; Krogstad, Harald E.; Robin, Agnès

doi:10.1016/s0378-3839(00)00017-x

Cited by 79 publications

(50 citation statements)

References 19 publications

(27 reference statements)

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“…This distribution gives results in good agreement with both field data [Prevosto and Forristall, 2004] and other secondorder crest height models [Prevosto et al, 2000;Al-Humoud et al, 2002;Fedele and Arena, 2005].…”

Section: Introductionsupporting

confidence: 76%

Return period of nonlinear high wave crests

Arena

Pavone

2006

J. Geophys. Res.

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[1] This paper deals with the long-term statistics for extreme nonlinear crest heights. First, a new analytical solution for the return period R(h), of a sea storm in which the maximum nonlinear crest height exceeds a fixed threshold h, is obtained by applying the 'Equivalent Triangular Storm' model and a second-order crest height distribution. The probability P(h c max > hj[0, L]) that maximum nonlinear crest height in the time span L exceeds a fixed threshold is then derived from R(h) solution, assuming that the occurrence of storms with highest crest larger than h is given by a Poisson process. In the applications, both R(h) and P(h c max > hj[0, L]) are calculated for some locations. It is shown that narrowband second-order approach is slightly conservative, with respect to the more general condition of crest distribution for second-order three-dimensional waves. Finally, a comparison with Boccotti, Jasper and Krogstad models is presented.

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Section: Introductionsupporting

confidence: 76%

Return period of nonlinear high wave crests

Arena

Pavone

2006

J. Geophys. Res.

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“…com/). The results reconfirm previous studies (Nordenstrøm 1973;Thornton and Guza 1983;Soares 1999, 2000;Prevosto et al 2000;Muraleedharan et al 2007;Gonzalez-Marco et al 2008) proposing the Weibull distribution as a very good choice for fitting significant wave height data (see for example Fig. 2).…”

Section: Statistical Approaches-methodologysupporting

confidence: 80%

Wave height characteristics in the north Atlantic ocean: a new approach based on statistical and geometrical techniques

Galanis

Chu

Kallos

et al. 2011

Stoch Environ Res Risk Assess

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The main characteristics of the significant wave height in an area of increased interest, the north Atlantic ocean, are studied based on satellite records and corresponding simulations obtained from the numerical wave prediction model WAM. The two data sets are analyzed by means of a variety of statistical measures mainly focusing on the distributions that they form. Moreover, new techniques for the estimation and minimization of the discrepancies between the observed and modeled values are proposed based on ideas and methodologies from a relatively new branch of mathematics, information geometry. The results obtained prove that the modeled values overestimate the corresponding observations through the whole study period. On the other hand, 2-parameter Weibull distributions fit well the data in the study. However, one cannot use the same probability density function for describing the whole study area since the corresponding scale and shape parameters deviate significantly for points belonging to different regions. This variation should be taken into account in optimization or assimilation procedures, which is possible by means of information geometry techniques.

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“…These displacements unfortunately are not available for the buoys of Ortona and Monopoli. However, during the WAVEMOD project (Prevosto et al, 2000), continuous data recordings were available and made it possible to really check the dependency of maxima in adjacent wave records of duration 30 min, and no dependency on a statistically significant level was revealed. The Borgman model has been also validated numerically via Monte Carlo simulations (Forristall, 2008).…”

Section: Wave Extremesmentioning

confidence: 99%

Wave climate of the Adriatic Sea: a future scenario simulation

Benetazzo

Fedele

Carniel

et al. 2012

Nat. Hazards Earth Syst. Sci.

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Abstract. We present a study on expected wind wave severity changes in the Adriatic Sea for the period 2070–2099 and their impact on extremes. To do so, the phase-averaged spectral wave model SWAN is forced using wind fields computed by the high-resolution regional climate model COSMO-CLM, the climate version of the COSMO meteorological model downscaled from a global climate model running under the IPCC-A1B emission scenario. Namely, the adopted wind fields are given with a horizontal resolution of 14 km and 40 vertical levels, and they are prepared by the Italian Aerospace Research Centre (CIRA). Firstly, in order to infer the wave model accuracy in predicting seasonal variability and extreme events, SWAN results are validated against a control simulation, which covers the period 1965–1994. In particular, numerical predictions of the significant wave height Hs are compared against available in-situ data. Further, a statistical analysis is carried out to estimate changes on wave storms and extremes during the simulated periods (control and future scenario simulations). In particular, the generalized Pareto distribution is used to predict changes of storm peak Hs for frequent and rare storms in the Adriatic Sea. Finally, Borgman's theory is applied to estimate the spatial pattern of the expected maximum wave height Hmax during a storm, both for the present climate and that of the future scenario. Results show a future wave climate in the Adriatic Sea milder than the present climate, even though increases of wave severity can occur locally.

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Probability distributions for maximum wave and crest heights

Cited by 79 publications

References 19 publications

Return period of nonlinear high wave crests

Return period of nonlinear high wave crests

Wave height characteristics in the north Atlantic ocean: a new approach based on statistical and geometrical techniques

Wave climate of the Adriatic Sea: a future scenario simulation

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