A data set of sea surface stereo images to resolve space-time wave fields
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Title
- A data set of sea surface stereo images to resolve space-time wave fields
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Author(s)
- Guimarães P.V.; Ardhuin F.; Bergamasco F.; Leckler F.; Filipot J.-F.; Shim, Jae seol; Dulov V.; Benetazzo A.
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Alternative Author(s)
- 심재설
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Publication Year
- 2020-05
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Abstract
- Measurement(s)stereo image center dot wave height center dot peak wave period center dot wave directionTechnology Type(s)Camera Device center dot computational modeling techniqueFactor Type(s)geographic locationSample Characteristic - Environmentsea surface layerSample Characteristic - LocationBlack Sea center dot Adriatic Sea center dot Yellow Sea center dot Iroise Sea Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12181158
Stereo imaging of the sea surface elevation provides unique field data to investigate the geometry and dynamics of oceanic waves. Typically, this technique allows retrieving the 4-D ocean topography (3-D space + time) at high frequency (up to 15-20 Hz) over a sea surface region of area similar to 10(4) m(2). Stereo data fill the existing wide gap between sea surface elevation time-measurements, like the local observation provided by wave-buoys, and large-scale ocean observations by satellites. The analysis of stereo images provides a direct measurement of the wavefield without the need of any linear-wave theory assumption, so it is particularly interesting to investigate the nonlinearities of the surface, wave-current interaction, rogue waves, wave breaking, air-sea interaction, and potentially other processes not explored yet. In this context, this open dataset aims to provide, for the first time, valuable stereo measurements collected in different seas and wave conditions to invite the ocean-wave scientific community to continue exploring these data and to contribute to a better understanding of the nature of the sea surface dynamics.
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ISSN
- 2052-4463
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URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/38666
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DOI
- 10.1038/s41597-020-0492-9
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Bibliographic Citation
- Scientific Data, v.7, no.1, 2020
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Publisher
- Nature Research
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Type
- Article
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Language
- English
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Document Type
- Data Paper
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