Excitability of Ocean Rogue Waves – Numerical Prediction and Early Warning by combining Wave Physics, Numerical Simulation and Data Driven Methods
Achieving short-term predictions of rogue waves on the ocean is widely considered an important objective for offshore operations and shipping. At present none of the approaches and methods published or used today can be considered satisfying. Prediction times at present are on the order of a minute or less. Probably the most important reason for this is the inability to integrate the wave amplitude dependent dispersion effects properly into a computating and simulation environment that is numerically efficient enough to have real-time capability. Furthermore, also small errors in the initial conditions extracted from the data sources grow quickly during the prediction, which is unavoidable with a view to the usually chaotic or even weakly turbulent wave dynamics under consideration. The present state-of-the-art is thus far below what is needed, and it is far below what our knowledge on nonlinear wave physics suggests is possible, which ranges in the order of five to fifteen minutes, or even beyond. Two key obstacles still need to be overcome: First, from the available wave-state measurement data, initial or initial-boundary conditions have to be identified for the subsequent prediction process. At present this identification process forms the weakest part in the process chain. Second, the prediction processes themselves need to reach a substantially higher quality and numerical efficiency, if real-time capability is intended. At present three related research fields of (i) understanding the physics of rogue ocean waves, (ii) predicting the short-term occurrence of rogue ocean waves by numerical simulation, and (iii) employing data driven methods in the context of rogue ocean waves, are largely disconnected. We propose to integrate the three fields of knowledge and methods to develop novel hybrid approaches. The vision is to predict the sea state evolution and the occurrence of rogue wave events up to the limit given by the theoretical horizon of predictability of the specific chaotic sea state. This proposal aims at studying optimised combinations of all three fields mentioned to push the boundary of how one can achieve predictions closer to the theoretically possible horizon of predictability. We strive to overcome the present limitations by a combination of exploiting wave physics, advanced numerical simulation, and data driven methods. It is our aim to reach prediction times of 5 to 10 minutes. This implies a sufficient accuracy in terms of amplitude and phase error of the prediction within the desired time frame. The objective is to keep both amplitude and phase errors within an error bound of +/- 10 % within the prediction period. We expect such a method to subsequently find wide applicability in many fields, like sea-keeping, ship routing, early warning to evacuate dangerous zones on ships or platforms, construction of offshore wind plants, ocean energy devices, etc.