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.

这项小型企业创新研究（SBIR）I阶段项目的更广泛的影响/商业潜力扩展到持有受气候变化影响的知识或财务利益的学者和行业利益相关者。鉴于近年来极端天气事件中气候变化驱动的增长的证据越来越多，利益相关者将气候​​变化纳入其弹性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中。保险公司需要基于风险评估，承保策略以及对定量方法的再保险购买决策，这些方法适当地考虑了具有适当不确定性范围的极端变化的可信，概率预测。公共机构，市政当局和私人组织必须针对关键基础设施实施弹性策略，这将承受在十年降低到多年阶段的极端气候。该项目着重于将受专利保护的研究开发和翻译为解决这些行业利益相关者新兴需求的分析和产品。 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.该项目将包括开发物理引导的统计建模（PGSM）框架，用于概率量化区域降水极端的预测变化，并将这些预测转化为可行的，气候变化的本地设计风暴曲线。鉴于理论和证据表明许多地区的风暴严重程度增加，最初的重点是极端降水，因此需要这些预测以增强设计曲线，并且鉴于它们对洪水模型至关重要，在后来的努力中将积极追求。该项目将在多个可交付成果中达到高潮，包括（1）同行评审的科学出版物，（2）专有时空降水极端数据库，以及（3）新英格兰测试台设计的风暴曲线，其中最后一个将通过软件原型进行分发。