Interannual Variability of Near‐Inertial Energy in the South China Sea and Western North Pacific

Lu, Huaihao; Chen, Zhiwu; Liu, Zhiyu; Wang, Chunzai; Xu, Jiexin; Gong, Yunhui; Cai, Shuqun

doi:10.1029/2022gl100984

Cited by 5 publications

(4 citation statements)

References 36 publications

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“…By considering the irregular swell as a superposition of regular swells whose elementary amplitudes are given by the spectrum, it is again possible to calculate the power transported by the waves. We can see that the "drop" in linear power compared to a regular swell is 60% [30].…”

Section: Application To Sea States : Sea State Energy Spectrummentioning

confidence: 95%

Prospects for the Characterization of the Fundamental Parameters Linked to the Energy Spectrum of the Aeolian Sea State in Benin Coastal Zone

Tokpohozin,

Chidikofan,

Kpomahou

et al. 2023

CJAST

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The Beninese coast, like most coastal regions, is subject to various hydrodynamic factors that are likely to be modified by climate change. On the coast, the coasts are constantly subject to the action of waves, currents and wind. This work, carried out near the port of Cotonou, aims to provide representative statistics on the direction of the fundamental parameters of the wind seas, their height in the area close to the coast, where the swell is not yet subject to the action of the funds. Based on in situ data measurements with mooring systems at tide gauge - meteorological stations during the hydrodynamic measurement campaign and carried out at 10-minute time steps, on a regular basis over a period of four consecutive years by NORTECKMED in collaboration with the Millenium Challenge Account (MCA-Benin) within the framework of the extension of the Autonomous Port of Cotonou, the statistical distribution of the characteristic parameters of the waves (height, direction of propagation and period) is elaborated. Thus, the significant height Hs , the peak period or the stable average wave period Tp ≈ Tms and the most frequent direction of propagation Dp are evaluated. A frequency characterization of the period Tc , the wavelength Lc and the height Hc of short swells, generated by local winds, is obtained using the Pierson-Moskowitz frequency spectrum. In short, the four years of data made it possible to carry out statistical production and simulations of wind, tide and wave data in order to determine the significant heights Hs , the peak period Tp, the linear energy power available and the link between Hs and Tp according to the Beaufort scales. Likewise, we made a characterization of short swells (wind seas) based on the value of the local wind speed, the Pierson-Moskowitz frequency spectrum and a representation of the wave propagation directions.

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Section: Application To Sea States : Sea State Energy Spectrummentioning

confidence: 95%

Prospects for the Characterization of the Fundamental Parameters Linked to the Energy Spectrum of the Aeolian Sea State in Benin Coastal Zone

Tokpohozin,

Chidikofan,

Kpomahou

et al. 2023

CJAST

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“…Given that the density difference in the oceans is very small, buoyancy, rather than gravity, provides the restoring force for internal waves, causing their amplitudes grow to hundreds of metres (Duda et al 2004;Klymak et al 2006;Ramp, Yang & Bahr 2010;Alford et al 2015;Huang et al 2016). Internal waves impact many ocean processes, which include momentum and energy transformation (Sutherland 2010;Sarkar & Scotti 2017), underwater navigation (Gong et al 2022;Wang et al 2022) and air-sea interaction (Lu et al 2022). Hence it is of great importance to study the properties of large-amplitude internal waves.…”

Section: Introductionmentioning

confidence: 99%

“…2022) and air–sea interaction (Lu et al. 2022). Hence it is of great importance to study the properties of large-amplitude internal waves.…”

Section: Introductionmentioning

confidence: 99%

High-level Green–Naghdi model for large-amplitude internal waves in deep water

Zhao,

Zhang,

Wang

et al. 2024

J. Fluid Mech.

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In this paper, a high-level Green–Naghdi (HLGN) model for large-amplitude internal waves in a two-layer fluid system, where the upper-fluid layer is of finite depth and the lower-fluid layer is of infinite depth, is developed under the rigid-lid free-surface approximation. The equations of the present HLGN model follow Euler's equations under the sole assumption that the horizontal and vertical velocity distributions along the vertical column are presented by known shape functions for each layer. The linear dispersion relations of the HLGN model for different levels are presented and compared with those obtained by other strongly nonlinear models for deep water, including the fully nonlinear models that include the dispersion effects $O(\mu )$ (where $\mu$ is the ratio of the upper-fluid layer depth to a typical wavelength) derived by Choi & Camassa (Phys. Rev. Lett., vol. 77, 1996, pp. 1759–1762) and $O(\mu ^2)$ derived by Debsarma et al. (J. Fluid Mech., vol. 654, 2010, pp. 281–303). It is shown that the HLGN model has a wider application range than other models. Solutions of travelling large-amplitude internal solitary waves in the absence and presence of background shear-current are then investigated by using the HLGN model. For the no-current cases, results obtained by the HLGN model show better agreement with Euler's solution on wave profile, velocity profile at the maximum interface displacement and wave speed compared with those obtained by other models. For the background shear-current cases, results obtained by the HLGN model also show good agreement with those obtained by solving the Dubreil-Jacotin–Long equation.

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“…ocean interior due to their large amount of energy and strong velocity shear in the vertical direction (Hebert and Moum, 1994;Ferrari and Wunsch, 2009;Alford et al, 2016;Lu et al, 2022). Although previous studies show that the NIWs can be generated by various processes, such as the spontaneous emission or breaking of lee waves, wind disturbances represent the most important generation mechanism of NIWs in the ocean (Pollard and Millard, 1970;D'Asaro, 1985;D'Asaro et al, 1995;Firing et al, 1997).…”

mentioning

confidence: 99%

Spatial and seasonal variations of near-inertial kinetic energy in the upper Ross Sea and the controlling factors

et al. 2023

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The spatial distribution and seasonal variation of near-inertial kinetic energy (NIKE) in the upper Ross Sea (RS) are examined using the 1/4° NEMO3.6-LIM3 sea ice physical–biological coupled model. The annual-mean surface and mixed layer-integrated NIKE have large values at the shelf break around Iselin Bank and the northeast area outside the continental shelf. The spatial distribution of the surface and mixed layer-integrated NIKE in the austral summer RS is mainly controlled by the near-inertial wind stress magnitude (NIWSM), which acts as the energy source. The northeast high NIKE agrees with the large NIWSM there. Semidiurnal tides only contribute to the NIKE peak around the Iselin Bank and shelf break. The change of mixed layer depth (MLD) can induce spatial discrepancies between surface and mixed layer-integrated NIKE. The shallower MLD in the western RS limits the near-inertial energy in a thin layer, which has induced the large surface NIKE there. The NIKE in the upper RS has a pronounced seasonal variation with the largest surface and mixed layer-integrated NIKE both observed during austral summer. The seasonal variation of NIWSM and sea ice concentration play an important role in inducing the seasonal variation of NIKE. While the NIWSM acts as the main energy source of NIKE, the presence of sea ice can prevent the wind from directly acting on the surface ocean, inducing the low NIKE during austral winter.

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Interannual Variability of Near‐Inertial Energy in the South China Sea and Western North Pacific

Cited by 5 publications

References 36 publications

Prospects for the Characterization of the Fundamental Parameters Linked to the Energy Spectrum of the Aeolian Sea State in Benin Coastal Zone

Prospects for the Characterization of the Fundamental Parameters Linked to the Energy Spectrum of the Aeolian Sea State in Benin Coastal Zone

High-level Green–Naghdi model for large-amplitude internal waves in deep water

Spatial and seasonal variations of near-inertial kinetic energy in the upper Ross Sea and the controlling factors

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