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，天气预报员会预测它对沿海海洋的影响，比如海水会比正常潮汐高出多高（这个过程被称为风暴潮），以及哪些地区可能被淹没。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。为了快速起见，这些模拟使用海岸线和海洋物理的简化表示。精细表示的模拟已被证明更准确，但在目前的超级计算机上，在时间有限的情况下，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、测试和实施一些方法，利用高分辨率高程图将精细尺度信息嵌入到粗尺度风暴潮模型中，以校正质量平衡、底部摩擦和其他数量。由此产生的模型将保持大部分高分辨率的精度，同时具有与更简单的粗模型相当的速度，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不仅可以提高集合浪涌预测的准确性，而且还可以减少在高分辨率研究中给定精度的计算成本。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式输出的十年级模拟。这种方法也为动态的全球潮/潮模拟开辟了道路，目前还不存在。结果将增加很少的成本，同时显著提高准确性。项目团队将通过将研究结果应用到两个广泛使用的风暴潮模型中，通过与政府-学术-行业咨询委员会合作，以及通过现有模型代码库传播结果，来确保这些结果的采用。每年将培养3名研究生和3名本科生。一个沉浸式流体力学剧场将为本科教学开发，并作为当地学校推广项目的一部分。数值模型中未解决过程的参数化在湍流和多孔介质输运等领域是标准的，但在沿海洪水应用中却非常缺乏。正如在这些领域一样，大规模模型的严格开发有可能在风暴潮模型用于预测沿海洪水的方式上实现革命性的飞跃。通过在坚实的物理基础上建立一个框架，并结合和调整来自其他领域的想法，项目团队将开发出新的子网格方法，这些方法在物理上是一致的、健壮的，因此可以灵活地广泛使用。利用已建立的理论方法，结合现有的高分辨率数据和新的数值模拟，项目团队将开发依赖于尺度的质量和动量平衡方程的闭合修正。子网格闭包将跨越三种方法的层次结构，其复杂性日益增加，从可手工计算的简单闭包到高阶多尺度数值校正。这将允许用户选择速度、准确性和数据可用性之间的折衷。通过严格解决这个封闭层次，该项目将对非常具体的流动和土地特征如何在不同尺度上影响水动力学有更强的物理理解。具体来说，这项研究将带来新的见解，了解沿海洪水是如何通过沼泽、自然渠道和人工运河的未解决的流量来控制的，以及如何最好地模拟这些未解决的尺度。这不仅有助于预测操作，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.