Numerical Wave Modelling – A Review

Thomas, Teema; Dwarakish, G. S.

doi:10.1016/j.aqpro.2015.02.059

Cited by 65 publications

(28 citation statements)

References 17 publications

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“…Information on the state of the sea in coastal areas is of great interest, as waves are a crucial factor for important activities conducted at sea. Therefore, an accurate wave forecast and hindcast are very important for marine traffic, recreational activities on the water, urban development near the coast, ecosystem restoration, renewable energies and offshore management (Gautier and Caires, 2015;Thomas and Dwarakish, 2015). Global ocean wave forecasts with coarser spatial resolution have already reached a remarkable level of accuracy (Janssen and Bidlot, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…In many studies, the meteorological input has already been found to be a crucial factor for conducting good wave fore-casts (Teixeira et al, 1995;Cavaleri andBertotti, 2003b, 2004;Cavaleri et al, 2007;Thomas and Dwarakish, 2015;Van Vledder and Akpınar, 2015). The wind data used to force a wave model need to be very accurate since, in coastal areas, the fetch is limited and small islands can block wave propagation.…”

Section: Introductionmentioning

confidence: 99%

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Synergy of wind wave model simulations and satellite observations during extreme events

et al. 2018

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Abstract. In this study, the quality of wave data provided by the new Sentinel-3A satellite is evaluated and the sensitivity of the wave model to wind forcing is tested. We focus on coastal areas, where altimeter data are of lower quality and wave modelling is more complex than for the open ocean. In the first part of the study, the sensitivity of the wave model to wind forcing is evaluated using data with different temporal and spatial resolution, such as ERA-Interim and ERA5 reanalyses, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis and short-range forecasts, German Weather Service (DWD) forecasts and regional atmospheric model simulations (coastDat). Numerical simulations show that the wave model forced using the ERA5 reanalyses and that forced using the ECMWF operational analysis/forecast demonstrate the best capability over the whole study period, as well as during extreme events. To further estimate the variance of the significant wave height of ensemble members for different wind forcings, especially during extreme events, an empirical orthogonal function (EOF) analysis is performed. In the second part of the study, the satellite data of Sentinel-3A, Jason-2 and CryoSat-2 are assessed in comparison with in situ measurements and spectral wave model (WAM) simulations. Intercomparisons between remote sensing and in situ observations demonstrate that the overall quality of the former is good over the North Sea and Baltic Sea throughout the study period, although the significant wave heights estimated based on satellite data tend to be greater than the in situ measurements by 7 to 26 cm. The quality of all satellite data near the coastal area decreases; however, within 10 km off the coast, Sentinel-3A performs better than the other two satellites. Analyses in which data from satellite tracks are separated in terms of onshore and offshore flights have been carried out. No substantial differences are found when comparing the statistics for onshore and offshore flights. Moreover, no substantial differences are found between satellite tracks under various metocean conditions. Furthermore, the satellite data quality does not depend on the wind direction relative to the flight direction. Thus, the quality of the data obtained by the new Sentinel-3A satellite over coastal areas is improved compared to that of older satellites.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Synergy of wind wave model simulations and satellite observations during extreme events

et al. 2018

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“…This first generation exclude nonlinear wave-wave interactions, such that this generation of wave model is a relatively very simple model. An improvement is introduced in the second generation wave model, that uses wind and incorporate a simple nonlinear wave-wave interactions (Thomas & Dwarakish, 2015). In this model it is introduced a type of wave model that can be categorized as decoupled propagation model (DP), coupled hybrid (CH) and coupled discrete (CD).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The third generation wave model is developed to improve mathematical model of the previous generation, such as to include refraction, shoaling, force by wind, triad wave-wave interactions, dissipation due to bottom and breaking (Thomas & Dwarakish, 2015). The most popular third generation wave model that are used for for wave simulation and prediction are WAVE WATCH III (Tolman et al 1999), WAM model (WAMDI group, 1988) and SWAN model (Booij et al 1999).…”

Section: Literature Reviewmentioning

confidence: 99%

Wind Wave Prediction by using Autoregressive Integrated Moving Average model : Case Study in Jakarta Bay

Adytia

Yonanta

Subasita

2019

ijoict

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Prediction of wind wave is highly needed to support safe navigation, especially for ship. Besides that, loading and unloading activities in a harbour, as well as for design purpose of coastal and offshore structures, data of prediction of wave height are needed. Based on its nature, the wind wave has random behaviour that is highly depending on behaviour of wind as the main driving force. In this paper, we propose a prediction method for wind wave by using Autoregressive Integrated Moving Average or ARIMA. To obtain historical data of wind wave, we perform wave simulation by using a phase-averaged wave model SWAN (Simulating Wave Near Shore). From the simulation, time series of wind wave is obtained. The prediction of wind wave is performed to calculate forecast of 24 hours ahead. Here, we perform wind wave prediction in a location in Jakarta Bay, Indonesia. We perform several combination of ARIMA model to obtain best fit model for wind wave prediction in the location in Jakarta Bay. Results of prediction show that ARIMA model give an accurate prediction especially for short term prediction.

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“…During the past few decades, many wind-wave models, ranging from simple formulas to more sophisticated numerical models (e.g., SWAN, WAM, and SLOSH), have been proposed for various applications. Nevertheless, the sophisticated numerical models are developed and orientated for applications from ocean to coastal scales in general in which the spatiotemporal resolutions of the output wind and wave fields are not appreciable for the dynamic analysis of coastal infrastructures [22]. As an alternative, some spectrum-based methods, such as spectral representation method (SRM), are still used widely for structural engineering field, which utilizes only a few parameters as input (e.g., wind speed and fetch) for generating the wind and wave fields with small spatiotemporal scale [23].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Ride Comfort and Driving Safety for Moving Vehicles on Slender Coastal Bridges

Zhu

Zhang

2018

Journal of Vibration and Acoustics

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Evaluating driving safety of moving vehicles on slender coastal bridges as well as bridge safety is important to provide supporting data to make decisions on continuing or closing the operations of bridges under extreme weather conditions. However, such evaluations could be complicated due to the complex dynamic interactions of vehicle-bridge-wind-wave (VBWW) system. The present study proposes a comprehensive evaluation methodology on vehicle ride comfort and driving safety on the slender coastal bridges subject to vehicle, wind, and wave loads. After a brief introduction of the VBWW coupling dynamic system and obtaining the dynamic responses of the vehicles, the vehicle ride comfort is evaluated using the advanced procedures as recommended in the ISO 2631-1 standard based on the overall vibration total value (OVTV). The vehicle driving safety is analyzed based on two evaluation criteria, i.e., the roll safety criteria (RSC) and the sideslip safety criteria (SSC), through the vehicle contact force responses at the wheels. Finally, the proposed methodology is applied to a long-span cable-stayed bridge for the vehicle ride comfort and driving safety evaluation.

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Numerical Wave Modelling – A Review

Cited by 65 publications

References 17 publications

Synergy of wind wave model simulations and satellite observations during extreme events

Synergy of wind wave model simulations and satellite observations during extreme events

Wind Wave Prediction by using Autoregressive Integrated Moving Average model : Case Study in Jakarta Bay

Evaluation of Ride Comfort and Driving Safety for Moving Vehicles on Slender Coastal Bridges

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