Skip Nav Destination
Filter
Filter
Filter
Filter
Filter

Update search

Filter

- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number

- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number

- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number

- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number

- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number

- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number

### NARROW

Format

Subjects

Date

Availability

1-3 of 3

Keywords: prediction

Close
**Follow your search**

Access your saved searches in your account

Would you like to receive an alert when new items match your search?

*Close Modal*

Sort by

Proceedings Papers

Publisher: Society of Underwater Technology

Paper presented at the Modelling the Offshore Environment: Proceedings of an International Conference, April 1–2, 1987

Paper Number: SUT-AUTOE-v12-013

... an extensive data set from the BP Fomes field. Discussion then moves to the descnption of the long-term wave c h a t e and the modehg of mdivldual storm events. Some useful extensions to the presently avadable models are descnbed, covenng the jomt probabilities of H , and T, and the

**prediction**of storm...
Abstract

The adequacy or otherwise of various existing theoretical models for surface elevation, wave height, period and wave group statistics are tested against an extensive data set from the BP Forties field. Discussion then moves to the description of the long-term wave climate and the modelling of individual storm events. Some useful extensions to the presently available models are described, covering the joint probabilities of H s and T z and the prediction of storm duration and intensity. INTRODUCTION It is common practice to differentiate between the properties of wave climates and random seas as judged (a) in the short term, over durations of 20minutes to three hours when statistical properties of the sea are assumed sensibly constant and (b) in the long-term, when non-stationary, seasonal and annual variability is central to the prediction of weather windows, fatigue environments and extreme design wave. In the short term, the work of Rice, Longuest-Higgins and many others established the properties of a linear random wave theory with a Gaussian distributed surface elevation spectra and the well known Rayleigh wave height distribution for zero-crossing waves. The analysis of long-term data has necessarily been more reliant upon empirical distributions. Ochi(1982) provides a most useful review of both short- and long-term models. The programme of probabilistic description of random seas mainly using surface elevation (¿) data collected by a Waverider buoy at the BP Forties field during six particularly severe storms, and data from Forties and elsewhere, spanning several years, in terms of summary statistics such as significant wave height (H s and average zero-crossing period (T z ). It has been shown (James, 1986) that non-linearities in wave records from floating measurement systems can be suppressed, or at least attenuated, by the horizontal motion of the buoy. Therefore, the data used in the first section of this discussion has been drawn from one of the fixed instruments mounted on the Forties FB platform. Non-Liner Surface Elevation Properties It has been commonly noted that there are consistent departures from the symmetrical Gaussian distribution of surface elevation in terms of positive skewness coefficients which may be related to finite amplitude, non-linear effects accentuating crest heights against trough depths. Variations of the Gram-Charlier perturbation on a Gaussian distribution have been proposed by Longuet-Higgins (1963) and Bitner (1980). Normalising surface elevation as y= ¿/ ¿' , Longuet-Higgins proposed the probability density function (pdf) of y as (Formula available in full paper) Where H J (y) is the J th Hermite polynomial, and¿, is µJ/s ¿ J , with µ J being the J th central moment of the surface elevation: (Formula available in full paper) Perhaps of more interest than the instantaneous surface elevation, the cumulative distribution function (cdf) of those crests (a c ) and troughs (a t ) which constitute individual up-crossing wave heights (H=a c + a t ) can be approximated on the basis of narrow-bonded seas for which ¿ and ¿ (= d¿/dt) are statistically independent by (Formula available in full paper) Where p(a c is the pdf of surface elevation form equation (1) and ¿ m is the mode (mpv) of the pdf Figure 1 shows the distribution of normalized crests.

Proceedings Papers

Publisher: Society of Underwater Technology

Paper presented at the Modelling the Offshore Environment: Proceedings of an International Conference, April 1–2, 1987

Paper Number: SUT-AUTOE-v12-031

...On the

**Prediction**of Extreme Waves from Wave Hindcast of the Most Severe Storms S. Hauer, R&D Department, Statoll, Norway INTRODUCTION The design wave method 1s frequently adopted for d e t e m g the design values c o n c e m g wave-mduced response. For most purposes the wave height is taken...
Abstract

INTRODUCTOIN The design wave method is frequently adopted for determining the design values concerning wave-induced response. For most purposes the wave height is taken to be the 100-year height, while a reasonable range is given for the corresponding wave period. In order to predict the ?100-year wave? for a given area, data on the long-term wave conditions are needed, either as measurements or in terms of reliable hindcast data. Subsequently, we will consider hindcast data from the central North Sea. The data are not calibrated against measurements, but for the present study this represents no problem since the extremes obtained by different methods are merely considered relative to each other. Estimates For The 100-Year Significant Wave Height The marginal distribution estimated from all six-hourly hindcast values is shown in Fig. 1. It is seen that the upper tail (h>5m) can be very well fitted by two-parameter Weibull distribution, i.e. (Formula available in full paper) By defining the 100-year value as the value which is expected to be exceeded for d hours (accumulated duration) during 100 years, one has (Table available in full paper) Fig. 1 Marginal distribution for the significant wave height: hindcast data, Central North Sea(available in full paper) The duration associated with the 100-year event does not necessarily correspond to only one exceedance. It expresses the expected cumulated duration above the level during a 100-year period. This is in contrast to various ‘severe storm’ consideration where we essentially predict the characteristic largest storm peak during a 100 year period. The duration of the storm peak is most probably comparable to the time of averaging associated with the input data. When predicting extreme individual waves (or load effects) this should be kept in mind, since it is the cumulated duration of exceedances which governs the extremes. The 100-year values for the significant wave height are frequently also estimated by considering only the most severe storms. The first problem in this approach is the formulation of a proper storm selection criterion. This is crucial if a hindcast is to be carried out only for the selected cases. However, in the present study, continuous hindcast data are available and we can easily identify the most severe storm simply by introducing a certain threshold level. The peak values for the storm exceeding 7 m are given in Table 1. For two years, no storms above this limit occurred and for these years the yearly maxima are give. The storm consideration may be formulated in two different ways: Include all storms above the given threshold and fit a probabilistic model to the sample of peak values. The probability level corresponding to the 100-year event is given by where ñ h is the expected annual number of storms exceeding the threshold level, h (Formula available in full paper) Include only the largest storm during specified time periods, e.g. annual maxima. It is reasonable to believe that an extreme value distribution of Type. Table 1 Peak value for storms exceeding 7 m (available in full paper)

Proceedings Papers

Publisher: Society of Underwater Technology

Paper presented at the Modelling the Offshore Environment: Proceedings of an International Conference, April 1–2, 1987

Paper Number: SUT-AUTOE-v12-117

...Wave

**Prediction**by an Empirical Ray Tracing Model A. J. Ellzott, Unit for Coastal and Estuarine Studies, Marine Science Laboratories, UK A ray tracmg model that mcludes the effects of refraction m shallow water has been developed to allow the evaluation of a set of empmcal formulae...
Abstract

A ray tracing model that includes the effects of refraction in shallow water has been developed to allow the evaluation of a set of empirical formulae for the prediction of directional wave spectra. The formulae have been tested by hindcasting the waves at eight offshore sites in the North Sea during WHIST storms 3, 5 and 6. At the peak of a storm the model predicted significant wave heights that agreed with observed values to within the ±10% accuracy suggested by the Department of Energy. Although the model is first-generation and cannot resolve non-linear interactions, it is computationally efficient and may be suitable for many engineering applications. In particular, it could be used in sensitivity tests for determining the grid spacing and coastal wind correction factors that should be applied during the use of second-and third-generation wave models. The good results obtained during high wave conditions are the result of the high directional resolution of the model coupled with the use of a realistic formula for the energy in the saturated wave spectrum. INTRODUCTION Hydrodynamic models of the currents and surface elevations associated with tides and surges can give results of high accuracy (e.g. Heaps and Jones, 1979). This is because the physics of the problem is well understood, and the equations that describe the motion contain only a relatively small amount of empiricism (with empirical formulae being used to represent the surface and bottom stresses, and the vertical eddy viscosity in the case of a three-dimensional model), in contrast wave models contain a fair degree of empiricism. For example, the BMO model (Gloding 1983), which is a second-generation model, attempts to take account of the effect of the non-linear interactions by replacing the wind-sea part of the spectrum by a JONSWAP spectrum with the same energy. Consequently, the model results depend not only on the empirical formulae used to describe the wave growth, but also on the empirical constants that appear in the JONSWAP spectrum. The lack of our understanding of the true physics of wave generation is reflected in the predictions made by wave models which can show appreciable errors. The Department of Energy has suggested that a wave model should be accurate to±10% of peak wave height, and existing second-generation models have been evaluated by applying them to the WHIST storms (Department of Energy, 1986). Recent wave models (the third-generation models) are becoming even more complex as they attempt to solve explicitly the non-linear interactions, thus necessitating the use of high-powered computers. Ultimately, this may lead to a better understanding of the physics of wave generation, but it limits the work to those researchers who have access to parallel processing computers, and the computational costs are likely to be high. An alternative approach is to accept the empirical nature of much wave modelling, and to investigate the use of purely empirical methods for the practical prediction of wave spectra. This may not advance our understanding of wave dynamics, but may produce practical models that will be suitable for many engineering problems.