Collaborative Research: CAS - Climate: Improving Nonstationary Intensity-Duration-Frequency Analysis of Extreme Precipitation by Advancing Knowledge on the Generating Mechanisms

合作研究：CAS - 气候：通过增进对生成机制的认识来改进极端降水的非平稳强度-持续时间-频率分析

• 批准号: 2221808
• 负责人: Kenneth Kunkel
• 金额: $ 22.18万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2221808&HistoricalAwards=false
• 关键词: Collaborative; Research; CAS; Climate; Improving

2221803 (Mascaro) and 2221808 (Kunkel). This project will address fundamental questions at the intersection of climate dynamics and civil engineering aimed at improving the design of infrastructure systems under climate change. Current procedures to design infrastructure against extreme precipitation and associated flooding rely on intensity-duration-frequency (IDF) curves. These curves are generated through statistical analyses of historical rain gage records under the assumptions of stationarity ("the future is the same as the past") and existence of a homogeneous statistical population ("the statistical variability of precipitation caused by multiple generating mechanisms is explained by a single distribution"). These assumptions have been recently challenged by theoretical arguments and climate simulations, which suggest that extreme precipitation (EP) statistics are expected to change in a future warmer climate. The main goal of this project is to advance knowledge on changes in the generating mechanisms of sub-daily and daily EP and use this new knowledge to develop a novel physics-driven statistical framework to inform the development of improved nonstationary IDF curves. Two research hypotheses will be investigated: (1) The occurrence and/or thermodynamic and dynamic components of the generating mechanisms of EP are changing in time, leading to changes in IDF design values; and (2) improved nonstationary IDF curves can be developed through statistical models that incorporate information on changes in the generating mechanisms of EP simulated by climate models. The research hypotheses will be tested using hourly and daily rainfall records, atmospheric re-analyses, and climate simulations in multiple regions of the U.S. spanning a wide range of dominant mechanisms of EP, including fronts, extratropical cyclones, tropical cyclones, mesoscale convective systems, air mass convection, and North American monsoon. New knowledge on the physical mechanisms leading to the non-stationarity of EP statistics at sub-daily and daily durations in the U.S. will be acquired by applying deep learning techniques. Novel methods for detection, physical validation, and uncertainty quantification of regional trends in EP and in occurrence and characteristics of the generating mechanisms will be designed by combining statistical tests and historical climate simulations from the Coupled Model Intercomparison Project Phase 6. This knowledge will inform a nonstationary statistical model for IDF analysis of EP that accounts for mixed populations. Regionalization techniques will be designed to reduce uncertainty in parameter estimation and incorporate regional changes in the physical mechanisms affecting EP. A Bayesian framework will be adopted to account for uncertainty. The added value of the nonstationary statistical model compared to current stationary approaches will be assessed through cross-validation bootstrapping experiments. The statistical model will be then applied with changes in EP mechanisms simulated by selected general circulation models under different future scenarios and used to compute new design metrics accounting for nonstationary extreme regimes. The methodological advancements are intended to address critical limitations of current stationary IDF design methods. Most importantly, there are multiple generating mechanisms for EP whose frequency and intensity may change in different ways in response to anthropogenically-forced climate change. The research will develop a framework for the objective incorporation of this knowledge into IDF curves, providing more robust estimates of future changes. This project is targeted to have multiple broader impacts. It seeks to improve infrastructure design and management against EP under climate change, which would (i) reduce storm-related damages ($261.1 billion from 2001 to 2020 in the U.S.), thus benefitting society; and (ii) increase the resilience of critical infrastructure, thus improving national security. The project will develop an outreach program that involves practitioner education through ongoing collaborations of the investigators with engineering and construction firms, public agencies, and the American Society of Civil Engineers. Additionally, the project will develop new aspects of curricula at the investigators’ institutions in the areas of engineering, hydrology, and atmospheric sciences.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.

2221803（Mascaro）和2221808（Kunkel）。该项目将解决气候动力学和土木工程交叉的基本问题，旨在改善气候变化下基础设施系统的设计。目前设计基础设施抵御极端降水和相关洪水的程序依赖于强度-持续时间-频率（IDF）曲线。这些曲线是在平稳性（“未来与过去相同”）和存在同质统计总体（“由多种生成机制引起的降水统计变异性由单一分布解释”）的假设下，通过对历史雨量计记录的统计分析生成的。这些假设最近受到了理论论证和气候模拟的挑战，这表明极端降水（EP）统计数据预计将在未来气候变暖时发生变化。该项目的主要目标是提高对亚日常和日常EP生成机制变化的认识，并利用这些新知识开发一种新的物理驱动的统计框架，以指导改进的非平稳IDF曲线的开发。两个研究假设将进行调查：（1）发生和/或热力学和动力学组件的产生机制的EP是随着时间的推移而变化，从而导致在IDF的设计值的变化;和（2）改进的非平稳的IDF曲线可以通过统计模型，纳入信息的变化，产生机制的EP气候模式模拟。研究假设将使用美国多个地区的每小时和每日降雨记录，大气再分析和气候模拟进行测试。这些地区涵盖了EP的各种主要机制，包括锋面，热带气旋，热带气旋，中尺度对流系统，气团对流和北美季风。通过应用深度学习技术，将获得有关导致美国亚日常和日常持续时间EP统计数据非平稳性的物理机制的新知识。新的方法检测，物理验证，和不确定性量化的区域趋势EP和发生和特征的生成机制将设计相结合的统计测试和历史气候模拟耦合模式相互比较项目第6阶段。这方面的知识将通知非平稳统计模型，占混合人口的EP的IDF分析。将设计区域化技术，以减少参数估计的不确定性，并将区域变化纳入影响EP的物理机制。将采用贝叶斯框架来解释不确定性。非平稳统计模型相比，目前的固定方法的附加值将通过交叉验证自举实验进行评估。然后，统计模型将应用于EP机制的变化模拟选定的大气环流模型在不同的未来情景下，并用于计算新的设计指标占非平稳极端制度。方法上的改进旨在解决当前固定式IDF设计方法的关键局限性。最重要的是，EP有多种生成机制，其频率和强度可能会以不同的方式响应于气候变化。该研究将开发一个框架，将这些知识客观地纳入IDF曲线，对未来变化提供更可靠的估计。该项目旨在产生多方面的广泛影响。它旨在改善气候变化下的基础设施设计和管理，以应对EP，这将（i）减少与风暴相关的损失（2001年至2020年美国为2611亿美元），从而造福社会;以及（ii）提高关键基础设施的复原力，从而改善国家安全。该项目将开发一个外展计划，涉及从业者教育，通过不断合作的调查人员与工程和建筑公司，公共机构和美国土木工程师协会。此外，该项目将在工程、水文和大气科学领域为研究机构开发新的课程。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。