Knowledge about water wave conditions a few minutes in advance is highly beneficial for ocean engineering activities, such as sea-keeping, helicopter landing and loading operations. Thus, several lines of research are currently aiming at the development of efficient methods for the reconstruction of initial wave surfaces from sea state measurement data and the subsequent prediction of the wave evolution into the near future. Although the integration of some physical wave mechanisms into wave models is still complicated, state-of-the-art wave reconstruction and prediction methods can be considered to be sufficiently accurate for most sea states and basic wave phenomena.

Instead, ocean waves whose height exceeds twice the significant wave height of the surrounding waves are referred to as rogue waves and their prediction and identification of precursors is challenging. This is because rogue waves can be described as “waves that appear from nowhere and disappear without a trace” (Akhmediev et al. 2009) and the combination of nonlinear physical mechanisms that generate these waves are not yet fully understood. Even though rogue waves are rarely reported, especially these wave events may have devastating effects on ships and offshore structures. For example there are reports from cruise vessels encountering rogue waves, some escaped with no more than a fright whereas others suffered disastrous consequences (e.g., Schulz (2001); Bertotti and Cavaleri (2008); Lemire (2005)).

At present, the three research fields of (i) understanding the physics of ocean waves, (ii) predicting the spatio-temporal evolution of ocean waves by numerical simulation, and (iii) employing machine learning methods in the context of ocean waves, are largely disconnected. Individual methods from the three fields described do not seem to be able to predict the sea state evolution and the occurrence of rogue wave events up to the limit given by the theoretical horizon of predictability. For this reason, the objective of the project Excitability of Ocean Rogue Waves is to integrate knowledge from nonlinear wave physics and computer simulation with machine learning methods. Using these novel hybrid approaches, we aim to come closer to the predictability of rogue waves, but also to improve wave prediction methods in general, considering the requirements of reconstruction and prediction accuracy and real-time capability.

Projektinformation:

Erregbarkeit extremer Meereswellen - Numerische Vorhersage und Frühwarnung durch Kombination von Verfahren der Wellenphysik, der numerischen Simulation von Bewegungsgleichungen und datenbasierter Verfahren,

DFG, Projektnummer 277972093, 1.04.2022 – 30.9.2025, Prof. Norbert Hoffmann

Bibliography:

N. Akhmediev, A. Ankiewicz and M. Taki, Waves that appear from nowhere and disappear without a trace, Phys. Lett. A 373, 675 (2009).

Bertotti, L. and Cavaleri, L. (2008). Analysis of the Voyager storm. Ocean Engineering, Vol. 35(1), pages 1 – 5.

Lemire, J. (2005). Freak wave rocks cruise. www.cbmu.com/news.php.

Schulz, M. (2001). "Ich spürte den Atem Gottes". Der Spiegel. No. 51/2001.