Wave modeling and extreme value analysis off the northern coast of the Persian Gulf

Moeini, Mohammad Hadi; Etemad‐Shahidi, Amir; Chegini, Vahid

doi:10.1016/j.apor.2009.10.005

Cited by 89 publications

(35 citation statements)

References 17 publications

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“…In this case, low waves are generally overestimated. Similar results can be found in Moeini et al (2010) for another area in the Persian Gulf. It is worth noticing that the wave periods are still underestimated at this station after adaptation of the model parameter based on the modeled wave height.…”

Section: Data Assimilationsupporting

confidence: 77%

“…As seen in Fig. 2, high waves are generally underestimated by the SWAN model at Bushehr station mainly due to the underestimation of driving wind field (Moeini et al 2010). The wave periods are significantly underestimated at this station.…”

Section: Simulationmentioning

confidence: 96%

“…At first, it can be used to improve different output variables such as wave height and period separately. Secondly, a wider range of output data can be improved using this method (Moeini et al 2010). Finally, this assimilation approach will cover almost all of the error sources including forcing terms and wave model evolution.…”

Section: Introductionmentioning

confidence: 99%

“…Moeini et al (2010) evaluated the quality of two sources of wind data, i.e., the ECMWF modeled winds and the measured data, for wave modeling in the Persian Gulf. They employed the third generation SWAN model for wave simulation and compared the results with one station recorded wave data.…”

Section: Introductionmentioning

confidence: 99%

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Wave data assimilation using a hybrid approach in the Persian Gulf

et al. 2012

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The main goal of this study is to develop an efficient approach for the assimilation of the hindcasted wave parameters in the Persian Gulf. Hence, the third generation SWAN model was employed for wave modeling forced by the 6-h ECMWF wind data with a resolution of 0.5°. In situ wave measurements at two stations were utilized to evaluate the assimilation approaches. It was found that since the model errors are not the same for wave height and period, adaptation of model parameter does not result in simultaneous and comprehensive improvement of them. Therefore, an approach based on the error prediction and updating of output variables was employed to modify wave height and period. In this approach, artificial neural networks (ANNs) were used to estimate the deviations between the simulated and measured wave parameters. The results showed that updating of output variables leads to significant improvement in a wide range of the predicted wave characteristics. It was revealed that the best input parameters for error prediction networks are mean wind speed, mean wind direction, wind duration, and the wave parameters. In addition, combination of the ANN estimated error with numerically modeled wave parameters leads to further improvement in the predicted wave parameters in contrast to direct estimation of the parameters by ANN.

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Section: Data Assimilationsupporting

confidence: 77%

Section: Simulationmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Wave data assimilation using a hybrid approach in the Persian Gulf

et al. 2012

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“…The winds and wave parameters, e.g., wind speed, wind direction, significant wave height (SWH) and mean wave period can be openly accessed from public datasets. ECMWF operational data are widely used for regional oceanography research [21,22], in particular, ECMWF wind and wave data are considered to be a reliable source in the development of wind [23,24] and wave [25] retrieval algorithms for synthetic aperture radar (SAR). However, ECMWF wave data are not applicable for wave distribution analysis because individual wind-sea and swell are absent in the datasets.…”

Section: Data Collectionmentioning

confidence: 99%

Analysis of Wave Distribution Simulated by WAVEWATCH-III Model in Typhoons Passing Beibu Gulf, China

Shao

Sheng

et al. 2018

Atmosphere

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Abstract:The Beibu Gulf is an important offshore region in the South China Sea for the fishing industry and other human activities. In 2017, typhoons Doksuri and Khanun passed the Beibu Gulf in two paths, at maximum wind speeds of up to 50 m/s. Typhoon Doksuri passed the Beibu Gulf through the open waters of the South China Sea and Typhoon Khanun moved towards the Beibu Gulf through the narrow Qiongzhou Strait. The aim of this study is to analyze the typhoon-induced wave distribution in the Beibu Gulf. WAVEWATCH-III (WW3) is a third-generation numeric wave model developed by the National Oceanic and Atmospheric Administration (NOAA), which has been widely used for sea wave research. The latest version of the WW3 (5.16) model provides three packages of nonlinear term for four wave components (quadruplets) wave-wave interactions, including Discrete Interaction Approximation (DIA), Full Boltzmann Integral (WRT), and Generalized Multiple DIA (GMD) with two kinds of coefficients, herein called GMD1 and GMD2. These four packages have been conveniently implemented for simulating wave fields in two typhoons after taking winds from the European Centre for Medium-Range Weather Forecasts (ECMWF) at 0.125 • grids as the forcing fields. It was found that the GMD2 package was the recommended option of the nonlinear term for quadruplets wave-wave interactions due to the minimum error when comparing a number of simulated results from the WW3 model with significant wave height (SWH) from ECMWF and altimeter Jason-2. Then the wave distribution simulated by the WW3 model employing the GMD2 package was analyzed. In the case of Typhoon Doksuri, wind-sea dominated in the early and middle stages while swell dominated at the later stage. However, during Typhoon Khanun, wind-sea dominated throughout and swell distributed outside the bay around the east of Hainan Island, because the typhoon-induced swell at mesoscale was difficult to propagate into the Beibu Gulf through the narrow Qiongzhou Strait.

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Effect of subseabed salt domes on Tidal Residual currents in the Persian Gulf

et al. 2016

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Geological studies in the Persian Gulf (PG) have revealed the existence of subseabed salt‐domes. With suitable filtering of a high‐resolution PG seabed topography, it is seen that the domes leave their signature in the seabed, i.e., numerous hills and valleys with amplitudes of several tens of meters and radii from a few up to tens of kilometers. It was suspected that the “shark skin” of the PG seabed may affect the tidal residual flow. The interaction of tidal dynamics and these obstacles was investigated in a nonlinear hydrodynamic numerical tidal model of the PG. The model was first used to characterize flow patterns of residual currents generated by a tidal wave passing over symmetric, elongated and tilted obstacles. Thereafter it was applied to the entire PG. The model was forced at its open boundary by the four dominant tidal constituents residing in the PG. Each tidal constituent was simulated separately. Results, i.e., tidal residual currents in the PG, as depicted by Lagrangian trajectories reveal a stationary flow that is very rich in eddies. Each eddy can be identified with a topographic obstacle. This confirms that the tidal residual flow field is strongly influenced by the nonlinear interaction of the tidal wave with the bottom relief which, in turn, is deformed by salt‐domes beneath the seabed. Different areas of maximum residual current velocities are identified for major tidal constituents. The pattern of trajectories indicates the presence of two main cyclonic gyres and several adjacent gyres rotating in opposite directions and a strong coastal current in the northern PG.

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Wave modeling and extreme value analysis off the northern coast of the Persian Gulf

Cited by 89 publications

References 17 publications

Wave data assimilation using a hybrid approach in the Persian Gulf

Wave data assimilation using a hybrid approach in the Persian Gulf

Analysis of Wave Distribution Simulated by WAVEWATCH-III Model in Typhoons Passing Beibu Gulf, China

Effect of subseabed salt domes on Tidal Residual currents in the Persian Gulf

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