NSFGEO-NERC: Collaborative: Toward a New Picture of the Multifaceted Meteotsunami

这是一个全面的调查的meteotsunami（MT）的演变及其与海洋环境的相互作用。MT是海啸时间尺度（分钟到小时）的海平面振荡，由大气扰动（如飑线和锋面通道）产生。MT事件在世界各地都很常见并有记录。与海啸一样，强烈的MT对人类生命和沿海基础设施构成严重威胁。该团队建议进行为期3年的现场实验，以收集路易斯安那州以外前所未有的高分辨率观测结果（选择高MT概率，各种底部摩擦和现有的NOAA和BOEM观测），以充分捕捉MT从生成到其海岸线表现的非线性转换。理论分析和数值模拟将结合观测数据来预测MT在接近海岸时如何转变。该项目利用了英国研究人员，他们将与该团队免费合作（根据双边协议，由英国自然环境研究理事会（NERC）资助）。拟议的数据收集和由此产生的公共数据库将提供一个独特的高分辨率信息来源，从而产生一个基本上全新的MT图像。新数据将产生强大的统计数据，并允许测试所有未来的理论和数值发展。因此，MT过程中的数值模型和它们的能力，预测MT事件的代表性将得到改善。了解MT的演变和改进MT预警战略将保护小型渔船和沿海社区。该项目还将升级墨西哥湾的波流浪涌信息系统，使其具有新的高分辨率观测能力。两个博士与海啸相比，MT的演变是更加非线性的，并且更强烈地受到底部摩擦的影响。因此，在地震海啸研究中获得的知识不容易转移到MT研究。这些事件是由大气扰动产生的，这种扰动以海洋响应的速度移动，海洋响应被假定为线性长波传播。然而，由于现有观测的空间和时间分辨率很差，这一假设尚未得到严格检验。拟议的工作是基于这样的假设，即在一个通用的普劳德曼共振MT事件捕获波也被激发。虽然通常不那么危险，但它们可能代表了这个过程的重要部分，并表现为主波的前兆。这项工作的重点是MT的传播阶段：MT的自由和被困组件的非线性演化的理论描述将被开发，包括孤立波，并将被验证为真实的地形，并占现实的底部摩擦。数据分析和模型开发将被纳入一个评估-学习-纠正的循环，这将改善对过程的描述和预测MT事件的能力。根据这一项目的调查结果，可以开发和测试有效的数字模型和预警战略。目前，MT预警系统主要依赖于大气数据的解释。该项目新的高分辨率观测结果将用于将实时海洋反应要素纳入该周期。

This is a comprehensive investigation of the meteotsunami (MT) evolution and its interaction with the ocean environment. MT is sea-level oscillations in the tsunami time scale (minutes to hours) generated by atmosphere perturbations, such as squall lines and frontal passages. MT events are common and documented all over the world. Like tsunami, strong MTs pose a serious threat to human life and coastal infrastructure. The team proposes to conduct a 3-year field experiment to collect unprecedented high-resolution observations off Louisiana (chosen for high MT probability, various bottom friction and existing NOAA and BOEM observations) to fully capture the nonlinear transformation of a MT from generation to its shoreline manifestation. Theoretical analyses and numerical simulations will be combined with the observational data to predict how the MTs transform as they approach shore. The project leverages UK researchers who will collaborate with the team at no cost (being funded by UK Natural Environment Research Council (NERC) under the bilateral agreement). The proposed data collection and the resulting public database will provide a unique source of high-resolution information, leading to an essentially new picture of MT. The new data will produce robust statistics and allow for testing of all future theoretical and numerical developments. Thus, representation of the MT process in numerical models and their ability to predict MT events will be improved. Understanding the MT evolution and improving MT early-warning strategies will protect small fishing vessels and coastal communities. The project will also upgrade the Wave-Current-Surge Information System in the Gulf of Mexico with new high-resolution observation capabilities. Two Ph.D. students will be trained and outreach activities through local K-12 education are planned over the course of the project.Compared to tsunami, MT evolution is much more nonlinear and more strongly affected by bottom friction. Thus, knowledge acquired in the study of seismic tsunami is not readily transferable to MT research. The events are generated by an atmospheric disturbance that moves at the speed of the oceanic response, which is assumed to propagate as a linear long wave. However, this assumption has not yet been critically tested because of the poor spatial and temporal resolution of available observations. The proposed work is based on the hypothesis that in a generic Proudman-resonated MT event trapped waves are also excited. Although usually less dangerous, they might represent an important part of the process, and behave as precursors to the main wave. The work focuses on the propagation stage of MT: a theoretical description of the nonlinear evolution of both free and trapped components of MT will be developed, including solitary waves, and will be validated for the real topography, and accounting for realistic bottom friction. Data analysis and model development will be integrated into an evaluate-learn-correct cycle that will improve representation of the process and ability to anticipate MT events. Effective numerical models and early-warning strategies could be developed and tested following the findings of this project. Presently, MT early-warning systems mostly rely on interpreting atmospheric data. The new high-resolution observations from this project will be used to incorporate in this cycle elements of real-time ocean response.