nerc.ac.uk

Optical fibre sensing of turbulent-frequency motions in the oceanic environment

Spingys, Carl P.; Garabato, Alberto C. Naveira; Belal, Mohammad. 2024 Optical fibre sensing of turbulent-frequency motions in the oceanic environment. Scientific Reports, 14 (1). 10.1038/s41598-024-70720-z

Before downloading, please read NORA policies.
[thumbnail of s41598-024-70720-z.pdf]
Preview
Text
s41598-024-70720-z.pdf - Published Version
Available under License Creative Commons Attribution 4.0.

Download (6MB) | Preview

Abstract/Summary

Observations of turbulence in the oceanic environment are sparse, with very few cases of coherent measurements with significant spatio-temporal extent due primarily to limitations of current observational tools. Here we propose submarine cables with embedded optical fibres as a potential solution to fill this observational gap, and utilise a recent 12-h observational optical fibre data set from a fast-flowing tidal channel to demonstrate such potential. Firstly, the presence of turbulent-scale signals driven by flow-topography interaction is shown at frequencies of 1 Hz and higher. These signals are consistent with the timing of the tidal flow as recorded by a nearby conventional sensor. Secondly, we show the presence of surface gravity waves with periods of 10 s, which are tight in frequency space further offshore but leak energy into the turbulent frequency range on parts of the cable closer to shore. This is compatible with shoreward-propagating surface waves that break in shallow water. Finally, we fit a theoretical spectral structure to the observations to show that much of the collected data (i) has a spectral slope that is consistent with the turbulent inertial subrange, and (ii) has a range of spectral energy consistent with that expected from turbulence generation by bottom drag acting on the tidal flow. In combination, these results highlight the potential for optical fibre sensing of turbulence, and call for a targeted experiment to characterise the fibre’s turbulence-sensing capabilities.

Item Type: Publication - Article
Digital Object Identifier (DOI): 10.1038/s41598-024-70720-z
ISSN: 2045-2322
Date made live: 10 Sep 2024 13:21 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/537995

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...