Source Terms in a Third-Generation Wind Wave Model

Tolman, Hendrik L.; Chalikov, Dmitry

doi:10.1175/1520-0485(1996)026<2497:stiatg>2.0.co;2

Cited by 465 publications

(329 citation statements)

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“…Simulation has been performed using a generator that calculated a spectral function composed of several Pierson-Moskowitz spectra for different peak frequencies oriented randomly in [0,2π] interval. Comparison of simulated spectra with spectra simulated by WAVEWATCH model [3,4] shows that this approach allowed us to simulate reasonably realistic and complicated spectra describing a broad range of wave systems. Spectra with four peaks were used in calculations below.…”

Section: Resultsmentioning

confidence: 99%

Using Neural Network parameterizations of the Nonlinear Energy Transfer for Application in Wave Models

Tolman¹,

Chalikov²,

Krasnopolsky³

2001

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LONG-TERM GOALSConsidering the crucial importance of nonlinear interaction S nl for the development of third generation wave models the long-term goal of this work is to improve accuracy of calculating nonlinear interaction S nl in wind wave models, and hence improving wave prediction in general. OBJECTIVESThe objective of this work is to develop a computationally cheap yet accurate approximation for S nl . APPROACHThe approach is based on the neural networks (NN) technique. It is used to accelerate the calculations and improve the accuracy of the parameterization of nonlinear interaction S nl . The nonlinear interaction source term can be considered as a nonlinear mapping between a source term S nl and a spectrum Fwhere T in is the exact nonlinear operator given by the full Bolzmann interaction integral [1]. This algorithm is a factor 10 4 too expensive for use in operational wave models. We intend to use the NN technique to produce a cheap and accurate alternative approach.

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Section: Resultsmentioning

confidence: 99%

Using Neural Network parameterizations of the Nonlinear Energy Transfer for Application in Wave Models

Tolman¹,

Chalikov²,

Krasnopolsky³

2001

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“…According to Espejo et al (2014), the results of wave climate analysis in areas dominated by mixed seas by using spectral parameters only may be misleading, because the entire spectrum is treated as one wave system. Another contribution to the underestimation of Tp values can be related to the source term physic package of WW3 and SWAN: Tolman-Chalikov (Tolman and Chalikov 1996). Chawla et al (2013) mentioned that DIA parameterization (parameterization that verifies wave-wave interaction) used on this package can lead to a less intense down shifting of the spectral peak on simulations, which results in underestimation of Tp in storm events.…”

Section: Table III Statistical Parameters Obtained By Q-q Comparison mentioning

confidence: 99%

Performance assessment of the database downscaled ocean waves (DOW) on Santa Catarina coast, South Brazil

Silva

Klein

González

et al. 2015

An. Acad. Bras. Ciênc.

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This work presents a validation of wave parameters from the new sixty years Downscaled Ocean Waves (DOW) reanalysis database. This study compares quantiles of the Gumbel distribution of Hs (significant wave height) and Tp (peak period) from simulated data with an 11 months' time series obtained from a buoy moored seaward on the Santa Catarina coast. Analysis by means of Gumbel distribution quantiles allows more weight to be given to the highest values of the time series, which are especially important in design projects. The statistical parameters used to verify the fit between the measured and the modeled data included: RMSE, BIAS, Scatter Index and Pearson Correlation Coefficient. Mean direction (θm) validation was conducted qualitatively. The database showed good fit of the mean conditions, especially Hs which was well reproduced by the wave model. Underestimation of Tp, related mainly to the low spatial and temporal resolution of wind data used to generate waves, highlights this general modeling problem. Based on calculated statistical parameters, DOW data were considered comparable to the values obtained by measurements; however, such data must be cautiously used for extreme events analysis and in areas of bimodal sea conditions, where major deficiencies in the database were observed.

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“…Este modelo fue validado a escala global con datos provenientes de boyas de oleaje y con datos de altimetría satelital (ERS-1) con óptimos resultados [16,17], obteniendo errores cuadráticos del 15 % con respecto a la altura media del oleaje registrada por boyas escalares y altimetría satelital.…”

Section: Metodologíaunclassified

Determinación del clima de oleaje medio y extremal en el norte del Golfo de Urabá

Orejarena¹,

Díaz²,

Paz³

et al. 2013

BCCIOH

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3Determinación del RESUMEN determinó el clima de oleaje medio y extremal a partir de una serie de oleaje sintético de once años, obtenido del modelo global de oleaje WaveWatch III. La serie de altura de oleaje (Hs) fue ajustada a diferentes funciones de distribución de probabilidad (Weibull de mínimos, Normal, Log-normal, Gumbel de máximos), encontrando que ésta se ajustaba mejor a la función de distribución Weibull de mínimos, al igual que la serie de periodo pico (Tp). Se encontraron alturas de ola de 1,13 y 2,5 m que corresponden a probabilidades de no excedencia de 50 y 95 %, respectivamente. Esta serie de oleaje de de ola de 4,9 m para periodos de retorno de 100 años. Los resultados de la presente investigación son de relevancia para el posterior análisis de la evolución morfológica del Golfo de Urabá; así como para el diseño, funcionalidad y estabilidad de obras de ingeniería sobre el borde costero. PALABRAS CLAVES:Golfo de Urabá, WaveWatch III, régimen medio de oleaje, régimen extremal de oleaje. ABSTRACTThe average and extreme wave climate at north of the Gulf of Urabá was evaluated and determined from 11 years of synthetic wave serie derived from the global model surf WaveWatch III, in order to evaluate different oceanographic scenarios. The series of wave height ( Hs ) was adjusted to different probability distribution functions ( minimum happened for the number of peak wave period ( Tp ) . Waves heights were found from 1.13 and 2.5 m, wich correspond years. These results are relevant to the subsequent analysis of the morphological evolution of the Gulf of Urabá, as well as for the design, functionality and stability of engineering works on the waterfront KEY WORDS: Gulf of Uraba, WaveWatch III, average wave regime, extreme wave regime.

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Source Terms in a Third-Generation Wind Wave Model

Cited by 465 publications

References 0 publications

Using Neural Network parameterizations of the Nonlinear Energy Transfer for Application in Wave Models

Using Neural Network parameterizations of the Nonlinear Energy Transfer for Application in Wave Models

Performance assessment of the database downscaled ocean waves (DOW) on Santa Catarina coast, South Brazil

Determinación del clima de oleaje medio y extremal en el norte del Golfo de Urabá

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