Field Observations of the Evolution of Plunging‐Wave Shapes

O’Dea, Annika; Brodie, Katherine L.; Elgar, Steve

doi:10.1029/2021gl093664

Cited by 12 publications

(26 citation statements)

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“…Similar changes to overturn area were also evident with incident solitons on a planar beach in two-phase direct numerical simulations (DNS) modelling with from 0.018 to 0.052 (Mostert & Deike 2020). Field observations of wave overturns with random waves over a barred beach bathymetry also observed increasing non-dimensional wave-overturn area (where is the breaking wave height) for larger local varying from 0.02 to 0.026 (O'Dea, Brodie & Elgar 2021). The overturn aspect ratio was found to depend somewhat on local , where is the non-dimensional depth based on a peak wavenumber (O'Dea et al.…”

Section: Introductionmentioning

confidence: 92%

“…The overturn aspect ratio was found to depend somewhat on local , where is the non-dimensional depth based on a peak wavenumber (O'Dea et al. 2021).…”

Section: Introductionmentioning

confidence: 99%

“…For example, in one field study with natural bathymetric and wave field variations, cross-shore wind was weakly correlated to the overturn aspect ratio, with offshore (onshore) wind increasing (reducing) the aspect ratio (O'Dea et al. 2021). However, wind variation was relatively weak, and co-variation with other parameters was not considered.…”

Section: Introductionmentioning

confidence: 99%

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Cross-shore wind-induced changes to field-scale overturning wave shape

et al. 2023

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The shape of depth-limited breaking-wave overturns is important for turbulence injection, bubble entrainment and sediment suspension. Overturning wave shape depends on a nonlinearity parameter $H/h$ , where $H$ is the wave height, and $h$ is the water depth. Cross-shore wind direction (offshore/onshore) and magnitude affect laboratory shoaling wave shape and breakpoint location $X_{{bp}}$ , but wind effects on overturning wave shape are largely unstudied. We perform field-scale experiments at the Surf Ranch wave basin with fixed bathymetry and $\approx 2.25$ m shoaling solitons with small height variations propagating at $C=6.7\ \mathrm {m}\ \mathrm {s}^{-1}$ . Observed non-dimensional cross-wave wind $U_w$ was onshore and offshore, varying realistically ( $-1.2 < U_{w}/C < 0.7$ ). Georectified images, a wave staff, and lidar are used to estimate $X_{{bp}}$ , $H/h$ , overturn area $A$ and aspect ratio for 22 waves. The non-dimensionalized $X_{{bp}}$ was inversely related to $U_{w}/C$ . The non-dimensional overturn area and aspect ratio also were inversely related to $U_{w}/C$ , with smaller and narrower overturns for increasing onshore wind. No overturning shape dependence on the weakly varying $H/h$ was seen. The overturning shape variation was as large as prior laboratory experiments with strong $H/h$ variations without wind. An idealized potential air flow simulation on steep shoaling soliton shape has strong surface pressure variations, potentially inducing overturning shape changes. Through wave-overturning impacts on turbulence and sediment suspension, coastal wind variations could be relevant for near-shore morphology.

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Section: Introductionmentioning

confidence: 92%

“…The overturn aspect ratio was found to depend somewhat on local , where is the non-dimensional depth based on a peak wavenumber (O'Dea et al. 2021).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Cross-shore wind-induced changes to field-scale overturning wave shape

et al. 2023

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“…Exploration into the use of wavelengths other than the visible band (e.g., infrared, hyperspectral) and more active sensing approaches (e.g., lidar, x-band radar, synthetic aperture radar (SAR)) must continue, and will likely accelerate with decreasing costs of more sophisticated sensors. For example, 3-dimensional observations of individual breaking waves using lidar have revealed new information on the complex kinematics and geometry of spilling and plunging breakers and propagating bores [29,30,92,93]. Fusion between data sources will likely lead to an improved resolution of processes and better parameterization of those processes in numerical models [29,85].…”

Section: Understanding Physical Processesmentioning

confidence: 99%

The Coastal Imaging Research Network (CIRN)

Palmsten

Brodie

2022

Remote Sensing

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The Coastal Imaging Research Network (CIRN) is an international group of researchers who exploit signatures of phenomena in imagery of coastal, estuarine, and riverine environments. CIRN participants develop and implement new coastal imaging methodologies. The research objective of the group is to use imagery to gain a better fundamental understanding of the processes shaping those environments. Coastal imaging data may also be used to derive inputs for model boundary and initial conditions through assimilation, to validate models, and to make management decisions. CIRN was officially formed in 2016 to provide an integrative, multi-institutional group to collaborate on remotely sensed data techniques. As of 2021, the network is a collaboration between researchers from approximately 16 countries and includes investigators from universities, government laboratories and agencies, non-profits, and private companies. CIRN has a strong emphasis on education, exemplified by hosting annual “boot camps” to teach photogrammetry fundamentals and toolboxes from the CIRN code repository, as well as hosting an annual meeting for its members to present coastal imaging research. In this review article, we provide context for the development of CIRN as well as describe the goals and accomplishments of the CIRN community. We highlight components of CIRN’s resources for researchers worldwide including an open-source GitHub repository and coding boot camps. Finally, we provide CIRN’s perspective on the future of coastal imaging.

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“…The use of stereo photogrammetry (Bergamasco et al., 2017; de Vries et al., 2011) for this purpose is promising, but applications and validations in the nearshore are still limited. On the contrary, scanning lidar can provide direct and highly accurate space‐time measurements of the surface elevation (Carini et al., 2021a; Martins et al., 2016; O’Dea et al., 2021, among others). Lidar requires specular reflection from the surface and thus either low incidence angles, or the presence of foam, water droplets, or enough small scale roughness at the surface.…”

Section: Introductionmentioning

confidence: 99%

Surface Wave and Roller Dissipation Observed With Shore‐Based Doppler Marine Radar

2022

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The Earth's coastlines are facing sea level rise and increased human interventions. Predicting long-term coastal changes is of major importance to ensure efficient planning and design of coastal structures, as well as sustainable management of the coastal zone. Furthermore, a proper incorporation of nearshore processes into earth system models is required to efficiently predict the future changes of the coastal morphology, that is, coastal morphodynamics. Long-term measurements of nearshore hydrodynamics, in particular the spatial distribution of wave heights, are rarely available but often required to develop, validate, or calibrate parameterizations of nearshore processes.Breaking surface waves are important drivers of nearshore hydro-and morphodynamics. When a wave breaks, its height and thus the energy that is contained in the wave motion at the scale of the breaker decreases. The vast majority of the extracted wave energy is irreversibly converted (dissipated) to currents (slowly varying mean flow, e.g., Longuet-Higgins & Stewart, 1964), vorticity (Clark et al., 2012, turbulence (chaotic oscillations at higher frequencies, e.g., Feddersen & Trowbridge, 2005), heat (e.g., Sinnett & Feddersen, 2014), sea spray (Van Eijk et al., 2011), sound and air entrainment (Deane, 1997), and re-suspension of sediments (Voulgaris & Collins, 2000). Therefore, wave breaking and the associated wave energy dissipation link the wave energy flux to mixing and sediment transport. A "direct measurement of wave dissipation is equivalent to measuring the forcing for nearshore flow" (Holman & Haller, 2013). However, deployment and maintenance of in-situ sensors (e.g.,

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Field Observations of the Evolution of Plunging‐Wave Shapes

Cited by 12 publications

References 50 publications

Cross-shore wind-induced changes to field-scale overturning wave shape

Cross-shore wind-induced changes to field-scale overturning wave shape

The Coastal Imaging Research Network (CIRN)

Surface Wave and Roller Dissipation Observed With Shore‐Based Doppler Marine Radar

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