The directional Spectra and Kinematics of Surface Gravity Waves in Tropical Storm Delia

Forristall, George Z.; Ward, E.G.; Cardone, Vincent J.; Borgmann, L. E.

doi:10.1175/1520-0485(1978)008<0888:tdsako>2.0.co;2

Cited by 70 publications

(27 citation statements)

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“…The ID wave spectrum is shown after 3 hours' duration and appears to be similar to the original, but the 2D spectrum is altered drastically. The pattern of growth of wave energy shown in these figures is consistent with the results of Forristall et al 24, Their measurements taken under hurricane conditions indicated that for frequencies above 1.5 f m' waves were traveling in the wind direction, while waves in lower frequencies veered markedly from the wind direction. A modification of Model I has been shown by Forristall et al 24 to produce this directional veering reasonably well.…”

Section: Variation Of Wind Speedsupporting

confidence: 90%

A Comparison of Various Numerical Wave Prediction Techniques

Resio

Vincent

1982

Society of Petroleum Engineers Journal

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In recent years, the number of wave prediction models has increased greatly. These models range from relatively simple parameterizations of significant wave height as a function of wind, duration, and fetch to rather sophisticated solutions for the generation, propagation. and dissipation of two-dimensional (2D) wave spectra. It sometimes is suggested that any wave model will provide reasonable answers when properly applied, and that most of the deviations between measured waves and predicted waves can be explained by discrepancies between actual and estimated wind fields. Although much of the error in wave prediction almost certainly is related to problems in determining a wind field, this paper examines the specific question of whether there are differences among these models such that even if the wind field were specified perfectly, there would remain significant deviations among predicted waves. First, wave generation under uniform wind fields is compared by use of nondimensional parameters. Then the models are compared again under conditions of time-varying, space-varying wind fields and with irregular fetch boundaries.We concluded that, in the open ocean with a longduration, slowly varying weather system, most models produce similar results; however, near a coast or in regions with rapidly varying weather systems, marked differences can be expected from the use of different models.

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Section: Variation Of Wind Speedsupporting

confidence: 90%

A Comparison of Various Numerical Wave Prediction Techniques

Resio

Vincent

1982

Society of Petroleum Engineers Journal

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“…Besides the circular RMS directional spreading metric, some other methods are: 1) the Yamarinto (1984) [also Komen et al 1994] method, 2) the Babanin and Soloviev (1998) method, 3) cos 2s method (via fitting) used in Forristall et al (1978), 4) the force-reduction method used by Forristall and Ewans (1998), and 5) the method used by Young (1999, pg. 128), which is referred to as the "mean directional width" and the "mean spectral width", which is:…”

Section: Other Methods Of Calculating Directional Spreadingmentioning

confidence: 99%

“…3. Forristall et al (1978) used the cos 2s model to quantify directional spreading. The study was motivated by the need to calculate forcing on a structure for the oil industry without assuming unidirectional waves, which would give incorrect calculations.…”

Section: Part I: a Review Of Literature Relevant To Directional Validmentioning

confidence: 99%

“…Forristall and Ewans (1998) focus specifically on directional spreading. Similar to Forristall et al (1978), the concern is the reduction (associated with directional spreading) of wave forces on structures. They use a metric associated with this force reduction, as well as the circular RMS spreading metric (both with and without frequency integration).…”

Section: Part I: a Review Of Literature Relevant To Directional Validmentioning

confidence: 99%

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On Validation of Directional Wave Predictions: Review and Discussion

Rogers¹,

Wang²

2006

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Standard Form 298 (Rev. 8-98)Prescribed by ANSI Std. Z39.18Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. This report consists of supplementary materials for an article, accepted for publication in the Journal of Atmospheric and Oceanic Technology, dealing with directional wave model validation by the same authors. These materials provide important background information for this companion paper, but were not included due to journal page limitations. Part I of this report provides a review of literature related to directional validation of wave models. Part II of this report discusses a number of issues that were raised by reviewers to the paper with particular focus on extensive non-directional validation of wave models. Also presented are validation of higher order moments, a summary of alternate methods of validation of directional spreading, a discussion of data-adaptive methods, and discussion of sensitivity of results to the handling of the high frequency range of the wave spectrum. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) SPONSOR / MONITOR'S ACRONYM(S) 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) SPONSOR / MONITOR'S REPORT NUMBER(S)

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“…From this analysis it was concluded that the "MUnchen" must have encountered maximum significant wave heights of 11 m, with peak periods of 14.3 seconds which correspond to a wave length of 320 m. These values are in close agreement with wave heights reported by ships in the same area. An earlier version of the HYPA model has been also applied to an extratropical storm in the Gulf of Alaska (Graber, 1979 Forristall et al (1978) where a modified PTB model was used to hindcast directional wave spectra generated by a tropical storm in the Gulf of Mexico.…”

Section: Hybrid Modelsmentioning

confidence: 99%

A Parametric Wind Wave Model for Arbitrary Water Depths

Graber

Madsen

1985

The Ocean Surface

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An extension of a deep water hybrid parametric wave model has been developed for arbitrary water depths. The windsea is described by the JONSWAP parameter set and by a directional parameter representing the mean direction of the windsea spectrum. This mean direction has been re-derived based on more general energy flux arguments. The windsea spectrum in finite depth is assumed to have a similarity shape which is related to the deep water energy spectrum by multiplying with a depth dependent transformation factor. This factor affects the spectral shape of the hi gh-frequency part which is proportional to f-5 in deep water and to f-in shallow water. The directional dependence of the spectrum is assumed to be cos 2 (6-60), centered around the mean wave direction. The windsea model explicitly accounts for finite depth effects such as refraction, shoaling and dissipation by bottom friction.Based on an energy flux transport equation, the full set of prognostic parameters is derived including finite depth effects. The equations of the prognostic variables are solved on a finite difference grid by means of the Lax-Wendroff method. Swell is treated in a decoupled spectral fashion. For simplicity all swell characteristics are considered straight and effects of refraction are disregarded. However, shoaling and dissipation of energy by bottom friction are included.The model has been applied to a deep water and finite depth case study. The deep water hindcast was performed for an extratropical cyclone in the Gulf of Alaska. Predicted significant wave heights and zero-crossing wave periods are compared with measurements from six stations in the Gulf of Alaska. The finite depth wave conditions are hindcasted for a complex frontal system off the North Carolina coast during ARSLOE. Predicted spectral wave parameters such as significant wave height, spectral peak frequency and mean wave direction are compared with observations from several different measurement techniques. From the same data set, observed wave spectra are compared with hindcasted model spectra. A discussion of the results for both applications is presented.

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The directional Spectra and Kinematics of Surface Gravity Waves in Tropical Storm Delia

Cited by 70 publications

References 0 publications

A Comparison of Various Numerical Wave Prediction Techniques

A Comparison of Various Numerical Wave Prediction Techniques

On Validation of Directional Wave Predictions: Review and Discussion

A Parametric Wind Wave Model for Arbitrary Water Depths

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