Evaluation of two WAM white capping parameterizations using parallel unstructured SWAN with application to the Northern Gulf of Mexico, USA

Siadatmousavi, Seyed Mostafa; Jose, Felix; Stone, Gregory W.

doi:10.1016/j.apor.2010.12.002

Cited by 40 publications

(8 citation statements)

References 49 publications

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“…It is an appropriate approach for simulation of wave height as a result of generation and growth by local wind, and the default method for resolving whitecapping dissipation in SWAN and other popular spectral models like WAM and Mike21-SW. To achieve higher simulation accuracies for wave height and wave period, calibrations of the model for the whitecapping parameter and the wave period parameter delta are necessary (Allahdadi et al, 2017;Siadatmousavi et al, 2012;Niroomandi et al, 2018;Allahdadi et al, 2004a). However, wave model applications for different regions (including open-ocean and shelf waters) show that Komen-type methods tend to underestimate both peak and mean wave periods (SWAN, 2015;van Vledder et al, 2016;Siadatmousavi et al, 2011). For the case of pure wind-wave growth, this problem is the result of underestimating the spectral energy at low frequencies.…”

Section: Introductionmentioning

confidence: 99%

Predicting ocean waves along the US east coast during energetic winter storms: sensitivity to whitecapping parameterizations

Allahdadi

Neary

2019

Ocean Sci.

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Abstract. The performance of two methods for quantifying whitecapping dissipation incorporated in the Simulating Waves Nearshore (SWAN) wave model is evaluated for waves generated along and off the US east coast under energetic winter storms with a predominantly westerly wind. Parameterizing the whitecapping effect can be done using the Komen-type schemes, which are based on mean spectral parameters, or the saturation-based (SB) approach of van der Westhuysen (2007), which is based on local wave parameters and the saturation level concept of the wave spectrum (we use “Komen” and “Westhuysen” to denote these two approaches). Observations of wave parameters and frequency spectra at four National Data Buoy Center (NDBC) buoys are used to evaluate simulation results. Model–data comparisons show that when using the default parameters in SWAN, both Komen and Westhuysen methods underestimate wave height. Simulations of mean wave period using the Komen method agree with observations, but those using the Westhuysen method are substantially lower. Examination of source terms shows that the Westhuysen method underestimates the total energy transferred into the wave action equations, especially in the lower frequency bands that contain higher spectral energy. Several causes for this underestimation are identified. The primary reason is the difference between the wave growth conditions along the east coast during winter storms and the conditions used for the original whitecapping formula calibration. In addition, some deficiencies in simulation results are caused along the coast by the “slanting fetch” effect that adds low-frequency components to the 2-D wave spectra. These components cannot be simulated partly or entirely by available source terms (wind input, whitecapping, and quadruplet) in models and their interaction. Further, the effect of boundary layer instability that is not considered in the Komen and Westhuysen whitecapping wind input formulas may cause additional underestimation.

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Section: Introductionmentioning

confidence: 99%

Predicting ocean waves along the US east coast during energetic winter storms: sensitivity to whitecapping parameterizations

Allahdadi

Neary

2019

Ocean Sci.

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“…Strictly speaking, both coefficients cannot be interpreted independently of each other: for example, the choice of the coefficient Cdis depends on the set value of dis. In addition, the optimum setup of Cdis and dis parameters is largely determined by the physical conditions for the generation and propagation of surface waves [13,14].…”

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Wave Climate of the Coastal Zone of the Crimean Peninsula

Divinsky¹,

Kosyan²

2018

PhO

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The main goal of the present paper is to assess climatic features of the wind wave and swell distribution in the coastal zone of the Crimean Peninsula. Method of research is the mathematical modeling. The modern spectral wave model DHI MIKE 21 SW is used. The model was preliminary calibrated for the purpose of correct dividing the mixed surface waves into the components corresponding to pure wind waves and swell. The basic calibration parameters are the coefficients conditioning numerical interpretation of the energy dissipation processes resulting from white-capping (wave breaks in deep water). The research has resulted in creating a database of integral parameters of the wind waves and swell in the Black Sea for 1979-2016 with the 1-hour time resolution. The features of spatial distribution of the wind wave and swell powers, and also some statistical characteristics of wave variability are analyzed for the sea areas adjacent to the Crimean coast. It is shown that the swell contribution to the total wave energy of the surface waves increases from the western coast of the Crimea Peninsula towards the eastern one. Nearby the western coast, the swell contribution (in the average annual balance) constitutes about 15%, whereas nearby the southeastern one it exceeds 30%.

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“…Кроме того, оптимальная настройка параметров C dis и  dis во многом определяется физическими условиями генерации и распростране-ния поверхностного волнения [13,14].…”

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Wave climate of the coastal zone of the Crimea Peninsula

Divinský¹,

Kosyan²

2018

MGZh

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Основная цель представленной работы -оценка климатических особенностей распределения ветровых волн и зыби в прибрежной зоне Крымского полуострова. Метод исследований -математическое модели-рование. Используется современная спектральная волновая модель DHI MIKE 21 SW. Проведена предва-рительная калибровка модели с целью корректного разделения смешанного поверхностного волнения на компоненты, соответствующие чисто ветровым волнам и зыби. Основными калибровочными параметрами являются коэффициенты, определяющие численную интерпретацию процессов потери энергии вследствие забурунивания (обрушения волн на глубокой воде). В результате проведенной работы создан банк данных интегральных параметров ветрового волнения и зыби на акватории Черного моря за период 1979-2016 гг. с дискретностью 1 ч. Для Крымского побережья проанализированы особенности пространственного распределения мощностей ветрового волнения и зыби, а также некоторые статистические характеристики волновой изменчивости. Показано, что вклад волн зыби в суммарную волновую энергию поверхностного волнения увеличивается по направлению от западной части прибрежной зоны Крымского полуострова к восточной. В западной части доля зыби (в среднегодовом балансе) составляет ~15%, в юго-восточной этот вклад превышает 30%. The main goal of the present paper is to assess climatic features of the wind waves' and swell distribution in the coastal zone of the Crimea Peninsula. The method of research is mathematical modeling. The modern spectral wave model DHI MIKE 21 SW is used. The model was preliminary calibrated for the purpose of correct dividing the mixed surface waves into the components corresponding to pure wind waves and swell. The basic calibration parameters are the coefficients conditioning numerical interpretation of the energy dissipation processes resulting from white-capping (wavebreaks in deep water). The research has resulted in creating a database of integral parameters of the wind waves and swell in the Black Sea for 1979-2016 with the time resolution 1 hour. The features of spatial distribution of the wind waves' and swell powers, and also some statistical characteristics of wave variability are analyzed for the sea areas adjacent to the Crimean coast. It is shown that the swell contribution to the total wave energy of the surface waves increases from the western coast of the Crimea Peninsula towards the eastern one. Nearby the western coast, the swell contribution (in the average annual balance) constitutes about 15%, whereas nearby the southeastern coast it exceeds 30%.

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Evaluation of two WAM white capping parameterizations using parallel unstructured SWAN with application to the Northern Gulf of Mexico, USA

Cited by 40 publications

References 49 publications

Predicting ocean waves along the US east coast during energetic winter storms: sensitivity to whitecapping parameterizations

Predicting ocean waves along the US east coast during energetic winter storms: sensitivity to whitecapping parameterizations

Wave Climate of the Coastal Zone of the Crimean Peninsula

Wave climate of the coastal zone of the Crimea Peninsula

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