Explaining Rogue Waves in the Ocean Through Observations and Modelling

无赖海浪是海洋上巨大的、意想不到的表面波，可能会对近海结构和船只造成灾难性的破坏。据怀疑，这些“怪胎”或“怪物”巨浪倾覆了数百艘远洋轮船，并造成了不幸的生命损失。对于流浪事件的形成有一系列已提出的解释，包括局域电流的影响、深度突变、调制不稳定性、由二阶约束非线性增强的色散(和定向)聚焦以及通过与大气对流风暴的相互作用而产生的格林斯潘共振。只要有一套正确的理论条件，所有人都能创造出无赖的波。然而，关于真实海洋中形成无赖波的主要机制(S)的争论仍在继续。这个项目的目的是在我们对真实海洋环境的理解方面取得重大进展，主要是通过建立和分析数值模式来评估已经进行了无赖波观测的区域(和时间尺度)。这将得到对包含无赖海浪测量(或间接暗示其发生)的未开发海洋数据集的新分析的支持。实现该项目目标的建议途径是开发频谱海浪模型，对观测到的无赖海浪事件区域的海浪条件进行事后预测。然后，可以使用光谱条件，结合局部水深测量，在局部区域上驱动相分辨模型(例如，非线性势流)。对结果条件的统计和频谱分析可以用来识别a)该模型是否捕捉到了流氓波事件的增强可能性？B)如果是，主要原因是什么？如果该方法成功地确定了海洋中无赖波形成的主要原因(S)，那么这将在我们对真实海洋中无赖波形成的理解方面取得重大进展，此外还将验证整个项目为评估这些无赖波而开发的方法。这些发现的影响有可能从根本上具有重大意义，具有广泛的实际影响。有了更好的理解，可以为近海船舶和结构的降低风险定义适当的极端“设计”条件，如果能够确定具有更高风险潜力的地点和/或时间尺度，这些可能是可以避免的。因此，这些结果有可能减少资本损失和生命损失。此外，支持该项目的工作有可能回答围绕流氓海浪的一系列进一步尚未回答的额外研究问题。未来的关键研究问题可能包括：1.这些无赖波(或增加的可能性)是否已经被预测到？2.无赖波事件发生的可能性在空间上有多大的局部性？3.使用开发的框架，是否有可能确定产生无赖波事件的“理想”(最坏情况)输入条件？4.无赖波在未来的气候中是否会变得更加常见？为了解决这个问题，我们可以从气候预测的风强迫的海浪模型集合中产生极端海浪的数据集。

Rogue waves are large, unexpected surface waves on the ocean that can cause catastrophic damage to offshore structures and vessels. These 'freak' or 'monster' waves are suspected to have capsized hundreds of ocean-going vessels and resulted in an unfortunate loss of life. A range of proposed explanations exist for the formation of rogue wave events including the effect of localised currents, abrupt depth transitions, modulation instability, dispersive (and directional) focusing enhanced by second-order bound nonlinearity, and Greenspan resonance through interaction with atmospheric convective storms. All are able to create rogue waves given the right set of theoretical conditions. However, debate is ongoing as to the dominant mechanism(s) for rogue wave formation in real seas.This project aims to make significant progress in our understanding for real ocean settings, primarily through the generation and analysis of numerical models created to assess regions (and time scales), where rogue wave observations have been made. This will be supported by a novel analysis of unexploited ocean datasets that contain rogue wave measurements (or indirectly hint at their occurrence).A suggested route to achieving the project aims is to develop spectral wave models to hindcast the wave conditions in the region of observed rogue wave events. The spectral conditions can then be used, in combination with local bathymetry, to drive a phase-resolved model (e.g. nonlinear potential flow) over a localised region. The statistical and spectral analysis of the resulting conditions can be used to identify a) did the model capture an enhanced likelihood of rogue wave events? and b) if so, what is the dominant cause?If the approach is successful in identifying the dominant cause(s) of rogue waves in oceans, then this will make significant advances in our understanding of rogue wave formation in real seas in addition to validating the methodology developed throughout the project for their assessment. The implications of these findings have the potential to be fundamentally significant with wide-ranging practical implications. With improved understanding, appropriate extreme 'design' conditions can be defined for the de-risking of offshore vessels and structures, and if locations and/or time scales can be identified which have an increased risk potential, these can potentially be avoided. Consequently, the results have the potential to reduce capital loss as well as loss of life.In addition, the work underpinning this project has the potential to answer a range of further unanswered additional research questions surrounding rogue waves. Key future research questions may include:1. Could these rogue waves (or the increased likelihood of) have been predicted?2. How spatially localised is the increased likelihood of rogue wave events?3. Using the developed framework, is it possible to identify 'ideal' (worst-case) input conditions for creating rogue wave events?4. Will rogue waves will become more common in the future climate? To address this question, we could produce a dataset of extreme waves from an ensemble of wave models forced by winds from climate projections.