SBIR Phase I: A Physics Guided Statistical Model for Weather Extremes Under Climate Change

SBIR 第一阶段：气候变化下极端天气的物理引导统计模型

• 批准号: 1621576
• 负责人: Evan Kodra
• 金额: $ 22.5万
• 依托单位: RISQ INC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1621576&HistoricalAwards=false
• 关键词: SBIR; Phase; Physics; Guided; Statistical

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project extends to academics and industry stakeholders holding intellectual or financial interests that are impacted by climate change. Given growing evidence for climate change-driven increases in extreme weather events over recent years, it has become increasingly important for stakeholders to factor climate change into their resilience plans. Engineering firms must embed changes in risks into engineering design processes due to increased urbanization, coastal inhabitancy, and climate change impacts. Insurance companies need to base risk assessments, underwriting strategies, and reinsurance purchasing decisions on quantitative methods that appropriately consider credible, probabilistic projections of changes in extremes with appropriate uncertainty bounds. Public agencies, municipalities, and private organizations must implement resilience strategies for critical infrastructure that will withstand climate extremes at decadal to multidecadal scales. This project focuses on developing and translating patent-protected research to analytics and products that address the emerging needs of these industry stakeholders. The publications and software developed via this proposal will significantly advance best practices in hazard risk assessment and climate change adaptation, and a sample of the New England design storm curves will be made freely available to support educational and outreach efforts.This Small Business Innovation Research (SBIR) Phase I project aims to address the deep uncertainties in climate projections rooting from intrinsic variability and longstanding gaps in physics understanding. The project will consist of developing a Physics-Guided Statistical Modeling (PGSM) framework for probabilistically quantifying projected changes in regional precipitation extremes, and translating those projections to actionable, climate change-informed local design storm curves. The initial focus is on precipitation extremes given that theory and evidence suggest climate change-driven increases in storm severity in many regions, that these projections are needed to enhance design curves, and given they are crucial inputs to flood models that will be pursued aggressively in subsequent efforts. The project will culminate in multiple deliverables, including (1) peer reviewed scientific publications, (2) a proprietary spatio-temporal precipitation extremes database, and (3) design storm curves for a New England testbed, the last of which will be disseminated via a software prototype.

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力延伸到学术界和行业利益相关者持有的知识或经济利益受到气候变化的影响。鉴于越来越多的证据表明，近年来气候变化导致极端天气事件增加，利益攸关方将气候变化因素纳入其复原力计划变得越来越重要。由于城市化、沿海居民和气候变化的影响，工程公司必须将风险变化嵌入工程设计过程。保险公司需要将风险评估、承保策略和再保险购买决策建立在定量方法的基础上，这些方法适当考虑了对极端情况变化的可信概率预测，并具有适当的不确定性界限。公共机构、市政当局和私营组织必须为关键基础设施实施抵御战略，以抵御数十年到数十年尺度的极端气候。该项目的重点是开发和转化受专利保护的研究，以满足这些行业利益相关者的新兴需求的分析和产品。通过这一提议开发的出版物和软件将大大推进灾害风险评估和气候变化适应方面的最佳做法，和新英格兰设计风暴曲线的样本将免费提供，以支持教育和推广工作。第一阶段项目旨在解决气候预测中的深刻不确定性，这些不确定性源于内在的可变性和物理学理解方面的长期差距。该项目将包括开发一个物理指导的统计建模（PGSM）框架，以概率量化区域降水极端事件的预测变化，并将这些预测转化为可操作的、气候变化知情的当地设计风暴曲线。最初的重点是极端降水，因为理论和证据表明，气候变化导致许多地区的风暴强度增加，需要这些预测来提高设计曲线，并考虑到它们是洪水模型的关键输入，将在随后的工作中积极追求。该项目最终将产生多个可交付成果，包括（1）同行评审的科学出版物，（2）专有的时空降水极端数据库，以及（3）为新英格兰试验台设计风暴曲线，最后一个将通过软件原型传播。