Ships could predict giant, dangerous waves minutes before they happen

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Photo by Quick PS on Unsplash
Photo by Quick PS on Unsplash

Rogue, unusually large waves at sea can be uncomfortable and even dangerous for those aboard ships, but international researchers have developed a tool they say can give ships a five-minute warning before a rogue wave occurs. The team trained an AI on millions of samples of sea surface elevation measurements from 172 buoys near the US and Pacific. When asked to predict rogue waves on an entirely new dataset, the researchers say the AI was able to correctly predict 75% of rogue waves a minute before they hit, and 73% of waves five minutes before they hit. The researchers say a tool like this could one day allow ships to warn their workers to take cover, perform emergency shutdowns or change the ship's path to minimise the impact.

Media release

From: Springer Nature

Engineering: Tool predicts rogue waves up to five minutes in advance

A new tool that can be used to predict the emergence of unusually large and unpredictable waves at sea — known as rogue waves — up to five minutes into the future is presented in a study published in Scientific Reports. The authors suggest that the tool could be used to issue advance warnings to ships and offshore platforms to enable those working on them to seek shelter, perform emergency shutdowns, or manoeuvre to minimise the impacts of approaching rogue waves.

The tool developed by Thomas Breunung and Balakumar Balachandran consists of a neural network that has been trained to distinguish ocean waves that will be followed by rogue waves, from those that will not. The authors trained the neural network using a dataset consisting of 14 million 30 minute-long samples of sea surface elevation measurements from 172 buoys located near the shores of the continental United States and the Pacific Islands. They used their tool to predict the emergence of rogue waves using a separate dataset consisting of 40,000 sea surface elevation measurements from the same buoys.

The authors found that their tool was able to correctly predict the emergence of 75% of rogue waves one minute into the future and 73% of rogue waves five minutes into the future. The tool was also able to predict the emergence of rogue waves near two buoys not included within the datasets used in training with 75% accuracy one minute into the future. This highlights that the tool may be capable of predicting rogue waves at new locations.

The authors suggest that the accuracy and advance warning time of their tool’s forecasts could be further improved by incorporating water depth, wind speed, and wave location data. Future research could also enable the heights of upcoming rogue waves or the times at which they may emerge to be predicted, they add.

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conference:
Scientific Reports
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Organisation/s: University of Maryland, USA
Funder: The authors gratefully acknowledge the support of the National Science Foundation Grant No. CMMI1854532. They are also thankful to Samarpan Chakraborty, Samuel Dipasqua, Soheil Feizi, Kayo Ide, Aya Abdelsalam Ismail, and Vinu Sankar Sadasivan of the University of Maryland, College Park, for stimulating discussions related to this work. Moreover, the opportunity to present a selection of the presented results68 at the 42nd International Conference on Ocean, Offshore and Artic Engineering (OMAE) in Melbourne, Australia and the feedback received in the session is gratefully acknowledged. The data36 were available from the Coastal Data Information Program (CDIP), Integrative Oceanography Division, operated by the Scripps Institution of Oceanography, under the sponsorship of the U.S. Army Corps of Engineers and the California Department of Parks and Recreation. The authors acknowledge the University of Maryland supercomputing resources (http:// hpcc. umd. edu) made available for conducting the research reported in this paper.
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