EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

A probabilistic prediction of rogue waves

Johannes Gemmrich1, Leah Cicon1, Benoit Pouliot2, and Natacha Bernier2
Johannes Gemmrich et al.
  • 1University of Victoria, Victoria, BC, Canada
  • 2Environment and Climate Change Canada, Dorval, QC, Canada

Rogue waves are individual ocean surface waves with a height greater than 2.2 times the significant wave height.  They can pose a danger to marine operations, onshore and offshore structures, and beachgoers, especially when encountered in high sea states. The prediction of bulk sea state parameters like significant wave height, period, direction, and swell components is satisfactorily addressed in current operational wave models. Individual wave heights cannot be predicted by those spectral models, and the prediction of rogue wave occurrence has to be in a probabilistic sense.

Previous attempts on such a prediction are based on the Benjamin Feir Index (BFI), which reflects the nonlinear process of modulation instability as the dominant generation mechanism for rogue waves. However, there is increasing evidence that BFI has limited predictive power in the real ocean. Recent studies established the average crest-trough correlation as the strongest single variable to correlate with rogue wave probability.

We demonstrate that crest-trough correlation can be forecast by an operational WAVEWATCHIII wave model with moderate accuracy. Using multi-year wave buoy observations from the northeast Pacific we establish the functional relation between crest-trough correlation and rogue wave occurrence rate, thus calibrating predicted crest-trough correlations into probabilistic rogue wave predictions. Combined with the predicted significant wave heights we can identify regions of enhanced rogue wave risk. Results from a case study of a large storm off Canada’s west coast are presented to evaluate the regional wave model at high seas, and to present the rogue wave probability forecast based on crest-trough correlation.

How to cite: Gemmrich, J., Cicon, L., Pouliot, B., and Bernier, N.: A probabilistic prediction of rogue waves, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3573,, 2023.