RAPID: Sensing and Modeling Infrastructure for Storm Surge Monitoring and Forecasting in Coastal Zones

RAPID：沿海地区风暴潮监测和预报的传感和建模基础设施

基本信息

批准号：
1763203
负责人：
Jason Hallstrom
金额：
$ 9.95万
依托单位：
Florida Atlantic University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-07-01 至 2020-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1763203&HistoricalAwards=false
关键词：
RAPID Sensing Modeling Infrastructure Storm

项目摘要

The Atlantic Coast is threatened by disasterous storms every year. The dangers of high winds are widely publicized, but flooding has been responsible for more than half of all associated deaths. Unfortunately, existing forecasting capabilities are limited. Failure to predict significant flooding is of obvious concern, but the risks associated with perpetually inflated forecasts could be equally damaging. A citizen who evacuated Hurricane Irma's path based on storm surge warnings, only to return home to limited flooding, might consider ignoring future surge forecasts. Depending on the storm, that decision could be an enormous mistake. This project addresses surge forecasting limitations. The intellectual merit of this project lies in computer and network systems research and computational earth systems modeling research to be undertaken along two connected paths. First, the project will pursue the design, implementation, and evaluation of a fundamentally new approach to achieving high-precision in situ measurement of storm-induced surge in challenging environments. Second, the project will pursue fundamental extensions to an existing modeling system comprising coupled atmospheric, oceanic, and hydrologic models. The work will focus on assimilation of in situ surge measurements to anchor and refine model outputs prior to, during, and after tropical storms.The broader impacts of this project will be significant: The world's coastal population is growing at an unprecedented rate. In the past four decades, the U.S. coastal population grew by 45%, with more than half of the population living in coastal counties. In the coming decades, coastal states' urban centers are expected to continue to grow. The resulting population density presents significant challenges. The ability of state and local governments to efficiently prepare for and respond to storm surge events is critical. This project will support significant progress toward the development of reliable storm surge monitoring and modeling systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

大西洋海岸每年都受到灾难性风暴的威胁。大风的危险已被广泛宣传，但洪水造成的死亡人数占所有相关死亡人数的一半以上。不幸的是，现有的预测能力有限。未能预测重大洪水显然令人担忧，但与永久夸大的预测相关的风险也可能同样具有破坏性。根据风暴潮警报撤离飓风艾尔玛路径的公民，返回家时却遭遇有限的洪水，他可能会考虑忽略未来的风暴潮预测。根据风暴的情况，这个决定可能会是一个巨大的错误。该项目解决了激增预测的局限性。该项目的智力优势在于沿着两条相连的路径进行计算机和网络系统研究以及计算地球系统建模研究。首先，该项目将寻求一种全新方法的设计、实施和评估，以在具有挑战性的环境中实现风暴潮引起的高精度原位测量。其次，该项目将寻求对现有建模系统的根本扩展，该系统包括耦合的大气、海洋和水文模型。这项工作将侧重于同化现场浪涌测量，以在热带风暴之前、期间和之后锚定和完善模型输出。该项目的更广泛影响将是巨大的：世界沿海人口正在以前所未有的速度增长。过去四十年，美国沿海人口增长了45%，其中一半以上的人口居住在沿海县。未来几十年，沿海各州的城市中心预计将继续增长。由此产生的人口密度带来了重大挑战。州和地方政府有效准备和应对风暴潮事件的能力至关重要。该项目将支持在开发可靠的风暴潮监测和建模系统方面取得重大进展。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。