Excitability of Ocean Rogue Waves – Numerical Prediction and Early Warning by combining Wave Physics, Numerical Simulation and Data Driven Methods

实现海洋上的流氓波的短期预测被广泛认为是海上作业和航运的重要目标。目前，没有一个方法和方法可以被认为是令人满意的。目前的预测时间是在一分钟或更少的数量级上，这可能是最重要的原因，这是无法正确地整合到一个计算和模拟环境中的波振幅相关的色散效应，是数值上足够有效，具有实时能力。此外，从数据源提取的初始条件中的小误差在预测期间也快速增长，这对于所考虑的通常混乱的或甚至弱湍流的波动动力学是不可避免的。因此，目前的技术水平远远低于所需要的水平，也远远低于我们在非线性波动物理学方面的知识所建议的可能性，其范围在5到15分钟的数量级，甚至更长。两个关键的障碍仍然需要克服：第一，从现有的波状态测量数据，初始或初始边界条件，必须确定后续的预测过程。目前，这一身份查验程序是整个程序链中最薄弱的部分。其次，如果需要实时能力，预测过程本身需要达到更高的质量和数值效率。目前，三个相关的研究领域（i）理解流氓海浪的物理学，（ii）通过数值模拟预测流氓海浪的短期发生，以及（iii）在流氓海浪的背景下采用数据驱动的方法，在很大程度上是脱节的。我们建议整合这三个领域的知识和方法，开发新的混合方法。其愿景是预测海况演变和流氓波事件的发生，达到特定混沌海况可预测性的理论视界所给出的极限。该提案旨在研究上述所有三个领域的优化组合，以推动人们如何实现预测的边界更接近理论上可能的可预测性。我们努力克服目前的局限性相结合，利用波动物理，先进的数值模拟，数据驱动的方法。我们的目标是达到5到10分钟的预测时间。这意味着在期望的时间帧内的预测的幅度和相位误差方面的足够的精度。目标是在预测周期内将幅度和相位误差保持在+/-10%的误差范围内。我们期望这种方法随后在许多领域中找到广泛的适用性，如耐波性，船舶路由，早期预警以疏散船舶或平台上的危险区域，海上风力发电厂的建设，海洋能源装置等。

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.