Abstract

Rogue waves, also known as freak waves, have received much attention in the scientific community as well as in media and the marine industry in the past two decades. Forecasts of extreme weather events have always been welcomed by the marine industry. Therefore, the development of warning criteria for rogue waves, being scientifically challenging forecast products, has also been encouraged. Such criteria would help mariners avoid sea states where rogue waves occur. The paper summarizes the main findings of the Norwegian research project ExWaMar dedicated to development of improved warning criteria for extreme and rogue waves. Three approaches for warning criteria for extreme and rogue waves based on information provided by the weather forecast are proposed. They include use of integrated wave parameters, coupling of a phase-averaged wave spectral model and phase-resolving wave model and application of Machine Learning methodology. Challenges related to development of warning criteria for rogue waves are discussed.

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