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Rogue Wave Detection

Date:
November 19, 2007
Source:
University of Alcalá
Summary:
Giant waves, also known as monster waves, have been talked about by sailors for centuries, often related to unexplained disappearances at sea, but no one quite believed them. They have been considered merely a myth until recently, when new studies using technological developments like buoys, radars and satellites have scientifically proven the existence of rouge waves, and that they exist in much higher numbers than it was ever expected.
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Giant waves, also known as monster waves, have been talked about by sailors for centuries, often related to unexplained disappearances at sea, but no one quite believed them. They have been considered merely a myth until recently, when new studies using technological developments like buoys, radars and satellites have scientifically proven the existence of rouge waves, and that they exist in much higher numbers than it was ever expected.

These rogue waves could be the cause of tragic accidents at sea, not only because of their immense power and heights that reach over 30 meters, but it is their unpredictable nature that poses a bigger threat; they emerge as unexpected mighty walls of water towering from calm seas. This is why Jose Carlos Nieto, a researcher from the Universidad de Alcalá, Madrid in collaboration with the German research centre GKSS have developed a software tool that can detect these waves and monitor their evolution in time and space.

There are currently other methods of detection, like wave rider buoys to measure the height of waves at sea, but the information they provide is not as complete since buoys only measure the waves at a single point at sea, thus lacking the spatial dimension. This software detects the wave front from a radar image and is now being commercialised by a spin-off company of the GKSS.

The image of the sea that forms on a radar screen is the result of different mechanisms of interaction between the electromagnetic energy emitted by the radar and the sea surface. The detection of the reflected energy from the wave by the system does not depend so much on the wave’s height, but on other factors such as the wind and wave inclination.

The tool developed by Professor Nieto from the signal theory department of the Universidad de Alcalá translates the radar image into a measurement of the elevation of the waves. The software uses a mathematical model to evaluate and process by different mechanisms the radar image that is generated and another model to determine the spatial and temporal dimensions of the waves.

In the radar images above, the image on the left corresponds to the raw radar image, while the one on the right is the image once processed by the software. Thanks to the colour code it can be appreciated that higher waves propagate as a group. This effect is called wave grouping and has a great relevance for the safety of marine structures such as ships, dikes, platforms. The software can be used to provide warning of an approaching extreme wave, giving time to prepare and minimise its effects.

The accurate wave dynamics that the software provides could also be used to predict the precise trajectory of oil spills and other contaminants that float on the sea, and it is on this application that most of the current investigation is being carried out at the Universidad de Alcalá by Professor Nieto, member of the High frequency technology group, among other specialists like physicists and telecommunications engineers from the signal theory department of the UAH.


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Materials provided by University of Alcalá. Note: Content may be edited for style and length.


Cite This Page:

University of Alcalá. "Rogue Wave Detection." ScienceDaily. ScienceDaily, 19 November 2007. <www.sciencedaily.com/releases/2007/11/071117091502.htm>.
University of Alcalá. (2007, November 19). Rogue Wave Detection. ScienceDaily. Retrieved October 11, 2024 from www.sciencedaily.com/releases/2007/11/071117091502.htm
University of Alcalá. "Rogue Wave Detection." ScienceDaily. www.sciencedaily.com/releases/2007/11/071117091502.htm (accessed October 11, 2024).

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