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PREEVENTS Track 2: Collaborative Research: COEXIST: COnnected EXtremes In Space and Time

预防事件轨道 2：协作研究：共存：空间和时间上的互联极端

基本信息

批准号：
1854940
负责人：
James Done
金额：
$ 71.92万
依托单位：
University Corporation For Atmospheric Res
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-06-01 至 2025-05-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1854940&HistoricalAwards=false
关键词：
PREEVENTS Track Collaborative Research COEXIST

项目摘要

The project goal is to improve our ability to withstand extreme floods and droughts. A single flood or drought event can cause problems, yet the devastation wrought by a series of back-to-back floods or dramatic swings between drought and flood conditions can be much worse. California, for example, is all too familiar with dangerous mudslides triggered by flash flooding on top of burn scars left over from prior drought conditions. The central U.S. is also no stranger to back-to-back expansive flooding episodes that drive destructive surges down the major rivers. These grouped events seriously test our ability to manage flood and drought and ensure protection of lives and property. Scientists do not fully understand the weather conditions that cause these grouped events. Nor do they know how good we are at forecasting them 2 weeks to 2 months in advance. Experts from insurance, reservoir design and emergency responders will gather with scientists to identify how these grouped events cause problems. This knowledge will then be used to craft the research necessary to support solutions. New scientific discoveries are anticipated about what causes floods and droughts to group together across the U.S. This new knowledge will then be used to develop ways to forecasts these grouped events 2 weeks to 2 months in advance. These new forecasting approaches will support our ability to prepare and reduce impacts. Through supporting enhanced protection of lives and livelihoods this project ultimately strengthens our national welfare and economic competitiveness. In addition to new science and better forecasts the project has a number of other potential benefits. The integration of research and education is central to the project, and will be achieved through the training and career development of the project team and one graduate student. The project is also committed to diversity and inclusion. Participation of underrepresented groups will be broadened through the mentoring of students underrepresented in science each summer. To promote additional scientific research the project will adhere to, and promote, best practices in open, accessible and reproducible science. The project will also engage non-scientists through a series of media interviews, newspaper/TV appearances, and science writing regarding the special risks to humans and environment posed by connected floods and droughts, and strategies to reduce their impacts. The work is structured around three objectives: 1) Identify potentially connective regimes and formulate hypotheses about the underlying shared processes by applying statistical models to observation-based datasets of U.S. extreme wet and dry events; 2) Advance the hypotheses by conducting a targeted suite of multi-scale dynamical model experiments for at least six instances of connected events; 3) Understand shared predictability sources by developing and testing a suite of prototype sub-seasonal to seasonal statistical-dynamical forecast systems. Potential contributions include understanding the shared physical processes connecting extreme wet and dry events, demonstrating extended forecast capacity for wet and dry extremes using forecast systems that emphasize connecting processes, and transforming how scientists conceptualize extreme events. Key project outcomes include a physical-process based definition of connected extremes, and a novel generalized research framework that co-advances shared-process understanding and forecast capacity.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.

该项目的目标是提高我们抵御极端水旱灾害的能力。一次洪水或干旱事件可能会造成问题，但一系列背靠背的洪水或干旱和洪水条件之间的剧烈波动造成的破坏可能要严重得多。例如，加利福尼亚州对山洪暴发引发的危险泥石流再加上之前干旱条件留下的烧伤伤疤再熟悉不过。美国中部地区也对接二连三的大规模洪灾事件并不陌生，这些洪灾事件会导致破坏性的洪水沿着主要河流涌入。这些群体性事件严重考验着我们管理水旱灾害、保障生命财产安全的能力。科学家们并不完全了解导致这些成组事件的天气条件。他们也不知道我们有多擅长提前两周到两个月预测他们。来自保险、水库设计和应急人员的专家将与科学家们齐聚一堂，确定这些组合事件是如何造成问题的。然后，这些知识将被用来编制支持解决方案所需的研究。关于是什么原因导致洪水和干旱在美国各地聚集在一起，预计会有新的科学发现。这些新知识将被用来开发方法，提前两周到两个月预测这些聚集在一起的事件。这些新的预测方法将支持我们准备和减少影响的能力。通过支持加强对生命和生计的保护，该项目最终加强了我们的国家福利和经济竞争力。除了新的科学和更好的预测外，该项目还有许多其他潜在的好处。研究和教育的融合是项目的核心，将通过项目团队和一名研究生的培训和职业发展来实现。该项目还致力于多样性和包容性。代表不足的群体的参与将通过每年夏天对科学领域代表不足的学生的指导来扩大。为了促进更多的科学研究，该项目将坚持并促进开放、可获得和可重复的科学方面的最佳做法。该项目还将通过一系列媒体采访、报纸/电视露面和科学写作，吸引非科学家参与，讨论相关的洪水和干旱对人类和环境构成的特殊风险，以及减少其影响的战略。这项工作围绕三个目标进行：1)通过将统计模型应用于美国极端潮湿和干燥事件的基于观测的数据集，确定潜在的联系机制，并制定关于潜在共享过程的假设；2)通过对至少六个相关事件实例进行一套有针对性的多尺度动力模式实验，推进假设；3)通过开发和测试一套从亚季节性到季节性的统计-动力预报系统原型，了解共享的可预测性来源。潜在的贡献包括了解极端潮湿和干燥事件之间的共同物理过程，使用强调相互联系的过程的预报系统展示对极端潮湿和干燥事件的扩展预报能力，以及改变科学家对极端事件的概念化。主要项目成果包括基于物理过程的相互关联极端的定义，以及共同促进共享过程理解和预测能力的新的通用研究框架。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。