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Wave-orbital velocities are estimated with particle image velocimetry (PIV) applied to rapid sequences of images of the surfzone surface obtained with a low-cost camera mounted on an amphibious tripod. Time series and spectra of the remotely sensed cross-shore wave-orbital velocities are converted to the depth of colocated acoustic Doppler velocimeters (ADVs), using linear finite depth theory. These converted velocities are similar to the velocities measured in situ (mean nRMSE for time series =16% and for spectra =10%). Small discrepancies between depth-attenuated surface and in situ currents may be owing to errors in the surface velocity measurements, uncertainties in the water depth, the vertical elevation of the ADVs, and the neglect of nonlinear effects when using linear finite depth theory. These results show the potential to obtain spatially dense estimates of wave velocities
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Estimating the In Situ Stratification via Remotely Sensed Internal Wave Speeds
Abstract This work tests a methodology for estimating the ocean stratification gradient using remotely sensed, high temporal and spatial resolution field measurements of internal wave propagation speeds. The internal wave (IW) speeds were calculated from IW tracks observed using a shore-based, X-band marine radar deployed at a field site on the south-central coast of California. An inverse model, based on the work of Kar and Guha, utilizes the linear internal wave dispersion relation, assuming a constant vertical density gradient is the basis for the inverse model. This allows the vertical gradient of density to be expressed as a function of the internal wave phase speed, local water depth, and a background average density. The inputs to the algorithm are the known cross-shore bathymetry, the background ocean density, and the remotely sensed cross-shore profiles of IW speed. The estimated density gradients are then compared to the synchronously measured vertical density profiles collected from an in situ instrument array. The results show a very good agreement offshore in deeper water (∼50–30 m) but more significant discrepancies in shallow water (20–10 m) closer to shore. In addition, a sensitivity analysis is conducted that relates errors in measured speeds to errors in the estimated density gradients. Significance StatementThe propagation speed of ocean internal waves inherently depends on the vertical structure of the water density, which is termed stratification. In this work, we evaluate and test with real field observations a technique to infer the ocean density stratification from internal wave propagation speeds collected from remote sensing images. Such methods offer a way to monitor ocean stratification without the need for extensive in situ measurements.
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- Award ID(s):
- 2220439
- PAR ID:
- 10630798
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Journal of Atmospheric and Oceanic Technology
- Volume:
- 41
- Issue:
- 10
- ISSN:
- 0739-0572
- Page Range / eLocation ID:
- 991 to 1001
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1175/JTECH-D-24-0001.1
