MCA Pilot PUI: Validating and Constraining Catastrophe Models with Paleo Tropical Cyclone Data for Enhanced Risk Management

热带气旋对人口稠密的沿海社区构成严重威胁。对于佛罗里达海岸线来说尤其如此。沿着佛罗里达海岸，人口和财产的分散集中导致了最近人类暴露于TC登陆的快速增加。飓风伊恩于2022年9月28日在佛罗里达西南海岸登陆。这场风暴具有飓风通常具有的三种危害：风、雨和风暴潮。但到目前为止，最具灾难性的影响来自风暴潮。迈尔斯堡海滩的高水位达到近16英尺。飓风伊恩可能是美国历史上损失最大的自然灾害之一，价值1129亿美元。在风险行业，这种低概率、高影响的事件被称为“尾部风险事件”。尾部风险事件通常会导致广泛的经济混乱，而且它们也往往与大量毁灭性的生命损失有关。这项研究将通过古风暴学将西南佛罗里达飓风记录追溯到数千年前。将分析来自沿海“蓝洞”的沉积物岩心，以重建该地区TC的历史。这将导致对TC沿美国海岸线沿着的频率分布有更可靠的了解，从而减少TC造成的生命和基础设施损失。该项目还将与更广泛的风险管理和建模社区建立联系。这些伙伴关系将确保古研究能够适当地与灾难风险决策者联系起来。生成的项目数据不仅将被风险行业使用，也将被其他利益相关者使用。其他利益相关者包括农业企业;栖息地恢复团体;沿海土地管理者;个人财产所有者，市政当局，科学家和企业。这些数据还可用于与应急管理人员、媒体、社区领导人和整个社区的外联。该项目还将通过支持STEM中代表性不足的少数群体，对STEM的多样性产生重大影响。该中期职业发展（MCA）项目将涉及四个不同但高度相互关联的跨学科活动：1）在伍兹霍尔海洋研究所（WHOI）的指导和合作下，该团队将建立在西南佛罗里达的长期TC数据集的基础上，通过增加西南佛罗里达蓝洞的新重建; 2）在合作伙伴Oasis的指导和合作下，PI将接受Oasis损失建模框架（LMF）的培训，参加培训研讨会和部署模型，并了解如何使用灾难（Cat）模型来告知风险观点; 3）在合作伙伴Reask的指导和合作下，PI将学习如何开发随机TC数据集，如何将其输入动态风暴潮模型，以及如何将其联合收割机组合以产生风险估计。这项研究将确定随机目录中哪些类型的风暴能够存款地质TC层，并完成对感兴趣的实地地点的敏感性分析;和4）在合作伙伴Maximum Information的指导和合作下，研究将带来新的强烈TC登陆古数据集，这些数据集在时间上比现有的仪器历史记录大一个数量级，风险建模公司和（再）保险公司。总之，本研究期间计算的估计古TC重现期将用于基线Cat模型验证、校准和确定性情景（应力）测试（告知最大可能/可能损失的观点）。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Tropical cyclones (TCs) are a serious threat for densely populated coastal communities. This is particularly true for the Florida coastline. Along the Florida coast, sprawling concentrations of people and properties have resulted in a recent rapid increase in human exposure to TC landfalls. Hurricane Ian made landfall on the Southwest Florida coast on September 28, 2022. This storm presented all three of the hazards commonly associated with hurricanes: wind, rain, and storm-tide surge. But by far the most catastrophic impacts were from the storm-tide surge. High water marks on Fort Myers Beach reached near 16 feet. Hurricane Ian could be one of the costliest natural disasters in US history at $112.9 billion USD. In the risk industry, such low-probability, high-impact events like these are known as “Tail-Risk Events.” Tail-Risk Events often cause widespread economic chaos, and they are also often associated with substantial and devastating loss of life. This research will extend the Southwest Florida hurricane record back thousands of years by means of Paleotempestology. Sediment cores from coastal “blue holes” will be analyzed to reconstruct the history of TCs in the area. This will result in a more robust understanding of the TC frequency distribution along the US coastline, thereby reducing the loss of life and infrastructure attributable to TCs. This project will also connect to the broader risk management and modelling communities. These partnerships will ensure that the paleo research can appropriately attach to catastrophe risk decision-makers. Project data generated will not only be used by the risk industry, but by other stakeholders as well. The other stakeholders include agricultural businesses; habitat restoration groups; coastal land managers; individual property owners, municipalities, scientists, and business. The data can further be used to outreach to emergency managers, the media, community leaders and the community at large. This project will also have a significant impact on diversity in STEM by supporting underrepresented minorities in STEM.This Mid-Career Advancement (MCA) project will involve four different, but highly interconnected and interdisciplinary activities: 1) With the mentorship and collaboration from the Woods Hole Oceanographic Institution (WHOI) the team will build on Southwest Florida’s long-term TC dataset, by adding new reconstructions from Southwest Florida blue holes; 2) With the mentorship and collaboration from partner Oasis the PI will receive training on the Oasis Loss Modeling Framework (LMF), attend training workshops and deploy models, and learn about how catastrophe (Cat) models are used to inform views of risk; 3) With the mentorship and collaboration from partner Reask the PI will learn how stochastic TC data sets are developed, how they feed into dynamical storm surge models, and how they combine to produce risk estimates. The research will identify what types of storms in stochastic catalogues are able to deposit geologic TC layers and complete sensitivity analyses for field sites of interest; and 4) With the mentorship and collaboration from partner Maximum Information the research will bring new intense TC landfall paleo datasets, that are temporally an order of magnitude greater than the existing instrumental historical record, to risk modeling firms and (re)insurance companies. In summary, the estimated paleo TC return periods calculated during this study will be used in baseline Cat model validation, calibration and deterministic scenario (stress) testing (which inform views of Maximum Probable/Possible Loss).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.