A probabilistic prediction of rogue waves from a WAVEWATCH III® model for the Northeast Pacific

Abstract

Abstract Rogue waves are stochastic, individual ocean surface waves that are disproportionately large compared to the background sea state. They present considerable risk to mariners and offshore structures especially when encountered in large seas. Current rogue wave forecasts are based on nonlinear processes quantified by the Benjamin Feir Index (BFI). However, there is increasing evidence that the BFI has limited predictive power in the real ocean and that rogue waves are largely generated by bandwidth controlled linear superposition. Recent studies have shown that the bandwidth parameter crest-trough correlation, r shows the highest univariate correlation with rogue wave probability. We corroborate this result and demonstrate that r has the highest predictive power for rogue wave probability from the analysis of open ocean and coastal buoys in the Northeast Pacific. This work further demonstrates that crest-trough correlation can be forecast by a regional WAVEWATCHIII ® wave model with moderate accuracy. This result leads to the proposal of a novel empirical rogue wave risk assessment probability forecast based on r . Semi-logarithmic fits between r and rogue wave probability were applied to generate the rogue wave probability forecast. A sample rogue wave probability forecast is presented for a large storm October 21-22, 2021.