Explaining Rogue Waves in the Ocean Through Observations and Modelling

Rogue waves are large, unexpected surface waves on the ocean that can cause catastrophic damage to offshore structures and vessels. These 'freak' or 'monster' waves are suspected to have capsized hundreds of ocean-going vessels and resulted in an unfortunate loss of life. A range of proposed explanations exist for the formation of rogue wave events including the effect of localised currents, abrupt depth transitions, modulation instability, dispersive (and directional) focusing enhanced by second-order bound nonlinearity, and Greenspan resonance through interaction with atmospheric convective storms. All are able to create rogue waves given the right set of theoretical conditions. However, debate is ongoing as to the dominant mechanism(s) for rogue wave formation in real seas.

This project aims to make significant progress in our understanding for real ocean settings, primarily through the generation and analysis of numerical models created to assess regions (and time scales), where rogue wave observations have been made. This will be supported by a novel analysis of unexploited ocean datasets that contain rogue wave measurements (or indirectly hint at their occurrence).

A suggested route to achieving the project aims is to develop spectral wave models to hindcast the wave conditions in the region of observed rogue wave events. The spectral conditions can then be used, in combination with local bathymetry, to drive a phase-resolved model (e.g. nonlinear potential flow) over a localised region. The statistical and spectral analysis of the resulting conditions can be used to identify a) did the model capture an enhanced likelihood of rogue wave events? and b) if so, what is the dominant cause?

If the approach is successful in identifying the dominant cause(s) of rogue waves in oceans, then this will make significant advances in our understanding of rogue wave formation in real seas in addition to validating the methodology developed throughout the project for their assessment. The implications of these findings have the potential to be fundamentally significant with wide-ranging practical implications. With improved understanding, appropriate extreme 'design' conditions can be defined for the de-risking of offshore vessels and structures, and if locations and/or time scales can be identified which have an increased risk potential, these can potentially be avoided. Consequently, the results have the potential to reduce capital loss as well as loss of life.

In addition, the work underpinning this project has the potential to answer a range of further unanswered additional research questions surrounding rogue waves. Key future research questions may include:

1. Could these rogue waves (or the increased likelihood of) have been predicted?
2. How spatially localised is the increased likelihood of rogue wave events?
3. Using the developed framework, is it possible to identify 'ideal' (worst-case) input conditions for creating rogue wave events?
4. Will rogue waves will become more common in the future climate? To address this question, we could produce a dataset of extreme waves from an ensemble of wave models forced by winds from climate projections.