PREEVENTS Track 2: Collaborative Research: Subgrid-Scale Corrections to Increase the Accuracy and Efficiency of Storm Surge Models

预防事件轨道 2：协作研究：亚网格尺度修正以提高风暴潮模型的准确性和效率

• 批准号: 1664040
• 负责人: Andrew Kennedy
• 金额: $ 93.25万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1664040&HistoricalAwards=false
• 关键词: PREEVENTS; Track; Collaborative; Research; Subgrid

When a hurricane approaches land, forecasters predict its effects on the coastal ocean, such as how high the water will rise above the normal tides (in a process called storm surge) and which regions are likely to be flooded. These predictions require many computer simulations to account for uncertainties in the storm's size, track, and intensity. To be fast, these simulations use simplified representations of the coastline and the ocean physics. Simulations with fine-scale representations have been shown to be more accurate, but they are far too slow on current supercomputers to use when time is limited to achieve reliable predictions. This trade-off has limited the accuracy of real-time simulations and increases the uncertainty for decision-makers and coastal residents. This project will develop, test, and implement ways to embed fine-scale information into coarse-scale storm surge models using high-resolution elevation maps to correct mass balances, bottom friction, and other quantities. The resulting models will keep most of the high-resolution accuracy while having speeds comparable to the simpler coarse models which will lead to more accurate pre-storm simulations, improving decision-making for policy-makers, emergency management personnel, and coastal residents. The work performed in this project will not only enable increased accuracy in ensemble surge forecasts, but will also decrease computational costs for a given accuracy in higher resolution studies. It will enable entirely new types of studies including decadal-level simulations using reanalysis products or climate model outputs. This approach also opens the way for dynamical global surge/tide simulations, which do not presently exist. Results will add little to costs, while significantly increasing accuracy. The project team will ensure adoption of these results by implementing findings into two widely-used storm surge models, by working in concert with a governmental-academic-industry advisory committee, and by disseminating results through existing model code repositories. Three graduate students and three undergraduate students per year will be trained. An immersive fluid mechanics theater will be developed both for undergraduate teaching, and as part of outreach programs for local schools.Parameterizations for unresolved processes in numerical models are standard in fields as far ranging as turbulence and porous media transport, but are sorely lacking in coastal flooding applications. As in those fields, rigorous development of up-scaled models holds the potential for a transformative leap in the way surge models are used to forecast coastal inundation. By building a framework on a sound physical foundation, and by incorporating and adapting ideas from other fields, the project team will develop novel sub-grid methods that will be physically consistent, robust, and thus flexible for widespread use. Using established theoretical methodologies coupled with existing high-resolution data and new numerical simulations, the project team will develop scale-dependent closure corrections to mass and momentum balance equations. Sub-grid closures will span a hierarchy of three approaches with increasing complexity, ranging from hand-calculable simple closures to high-order multiscale numerical corrections. This will allow for a user-chosen compromise between speed, accuracy, and data availability. By rigorously addressing this closure hierarchy, this project will develop a much stronger physical understanding of how very specific flow and land features impact hydrodynamics at different scales. Specifically, this research will lead to new insights on how coastal flooding is controlled by unresolved flows through marshes, natural channels, and man-made canals, and how best to model these unresolved scales. This will assist not only in forecast operations, but also in understanding and designing protective infrastructure.

当飓风接近陆地时，预报员预测其对沿海海洋的影响，例如水位将比正常潮汐高出多高（在一个称为风暴潮的过程中），以及哪些地区可能被洪水淹没。 这些预测需要许多计算机模拟来解释风暴的大小，路径和强度的不确定性。 为了快速，这些模拟使用简化的海岸线和海洋物理表示。 使用精细尺度表示的模拟已经被证明是更准确的，但是在当前的超级计算机上，当时间有限时，它们太慢了，无法实现可靠的预测。 这种权衡限制了实时模拟的准确性，并增加了决策者和沿海居民的不确定性。该项目将开发、测试和实施将细尺度信息嵌入粗尺度风暴潮模型的方法，使用高分辨率高程图来校正质量平衡、底部摩擦和其他量。由此产生的模型将保持大部分高分辨率的准确性，同时具有与更简单的粗糙模型相当的速度，这将导致更准确的风暴前模拟，改善决策者，应急管理人员和沿海居民的决策。在这个项目中进行的工作将不仅能够提高集合浪涌预报的准确性，但也将降低计算成本，为给定的精度在更高的分辨率的研究。它将使全新类型的研究成为可能，包括使用再分析产品或气候模型输出进行十年级模拟。这种方法也开辟了动态的全球浪涌/潮汐模拟，目前不存在的方式。结果将几乎不增加成本，同时显着提高准确性。项目小组将确保采用这些成果，办法是将研究结果纳入两个广泛使用的风暴潮模型，与政府-学术-工业咨询委员会协同工作，并通过现有的模型代码库传播研究结果。每年将培养3名研究生和3名本科生。沉浸式流体力学剧院将开发用于本科教学，并作为当地学校推广计划的一部分。数值模型中未解决过程的参数化在湍流和多孔介质传输等领域都是标准的，但在沿海洪水应用中却严重缺乏。在这些领域，严格开发的放大模型有可能在使用浪涌模型预测沿海洪水的方式上实现变革性的飞跃。通过在良好的物理基础上建立一个框架，并结合和适应来自其他领域的想法，项目团队将开发新的子网格方法，这些方法将在物理上一致，强大，因此可以灵活地广泛使用。利用现有的理论方法，加上现有的高分辨率数据和新的数值模拟，项目小组将开发质量和动量平衡方程的尺度依赖闭合校正。子网格闭包将跨越三种方法的层次结构，其复杂性不断增加，从可手工计算的简单闭包到高阶多尺度数值校正。这将允许用户在速度、准确性和数据可用性之间选择折衷方案。通过严格解决这个封闭层次，这个项目将发展一个非常强大的物理理解如何非常具体的流动和土地特征影响不同尺度的流体动力学。具体来说，这项研究将导致对沿海洪水如何通过沼泽，天然渠道和人造运河的未解决流量控制的新见解，以及如何最好地模拟这些未解决的规模。这不仅有助于预测行动，而且有助于理解和设计保护性基础设施。

项目成果

Subgrid theory for storm surge modeling

• DOI: 10.1016/j.ocemod.2019.101491
• 发表时间: 2019-12
• 期刊: Ocean Modelling
• 影响因子: 3.2
• 作者: A. Kennedy;D. Wirasaet;A. Begmohammadi;Thomas Sherman;D. Bolster;J. Dietrich

Subgrid surface connectivity for storm surge modeling

用于风暴潮建模的子网格表面连接

• DOI: 10.1016/j.advwatres.2021.103939
• 发表时间: 2021
• 期刊: Advances in Water Resources
• 影响因子: 4.7
• 作者: Begmohammadi, Amirhosein;Wirasaet, Damrongsak;Silver, Zachariah;Bolster, Diogo;Kennedy, Andrew B.;Dietrich, J.C.
• 通讯作者: Dietrich, J.C.

Subgrid corrections in finite-element modeling of storm-driven coastal flooding

风暴驱动的沿海洪水有限元建模中的亚网格修正

• DOI: 10.1016/j.ocemod.2021.101887
• 发表时间: 2021
• 期刊: Ocean Modelling
• 影响因子: 3.2
• 作者: Woodruff, Johnathan L.;Dietrich, J.C.;Wirasaet, D.;Kennedy, A.B.;Bolster, D.;Silver, Z.;Medlin, S.D.;Kolar, R.L.
• 通讯作者: Kolar, R.L.