PREEVENTS: Workshop on Integrated Framework for Modeling and Prediction of Extreme Events; College Park, Maryland; Summer 2016

预防措施：极端事件建模和预测综合框架研讨会；

• 批准号: 1638499
• 负责人: A Surjalal Sharma
• 金额: $ 5万
• 依托单位: University of Maryland, College Park
• 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 2017-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1638499&HistoricalAwards=false
• 关键词: PREEVENTS; Workshop; Integrated; Framework; Modeling

PREEVENTS: Workshop on Uncertainty Quantification in Forecasting Extreme Space WeatherThe project is to organize and provide travel support for a three-day workshop that targets the understanding of extreme events in space weather. The extreme nature of events arises when many conditions reinforce disturbances, such as geospace storms and substorms. The identification and characterization of these conditions are essential to uncertainty quantification and to improvements in modeling and prediction. The workshop will bring together experts in geospace modeling and simulation to explore common issues in the modeling and prediction of space weather using data-driven and first-principles approaches. A primary objective will be the identification of what is needed for the development of an integrated framework for uncertainty quantification that leverages advances in the two approaches to accelerate research to improve space weather forecasting. This is an important next step that will most likely lead to innovative and synergistic approaches to developing future capabilities. An important output of the workshop will be a comprehensive report on the current state of, and future outlook for, modeling and prediction of extreme space weather events and the associated natural hazards. The workshop provides a rare and valuable opportunity to broaden the education of postdocs, graduate and undergraduate students and enable networking. The workshop will contribute to the development of a multi-disciplinary community for disaster science, which is critical to accelerate the development of a framework for extreme event prediction and mitigation.The understanding of the statistics of rare events and their variability is critical to uncertainty quantification in space weather forecasting, and the paucity of data of extreme events requires development of new techniques. The nonlinear coupling among the different multiphysical processes underlying extreme events, and the incomplete knowledge of the underlying processes themselves, are among the main sources of uncertainty in first principles models. An essential step to improving forecasts of extreme space weather is uncertainty quantification, which is inherently interdisciplinary, requiring a comprehensive effort that brings together disciplinary researchers, computational scientists, modelers, and statisticians. The workshop provides a forum for identifying and exploring important synergisms in forecasting extreme events in space weather and its outcomes can impact extreme events forecasting in general.

以往活动：预测极端空间天气中的不确定性量化讲习班该项目将组织为期三天的讲习班并提供旅行支助，该讲习班的目标是了解空间天气中的极端事件。 当许多条件加强扰动时，如地球空间风暴和亚暴，事件的极端性质就会出现。 这些条件的识别和表征是必不可少的不确定性量化和改进建模和预测。讲习班将汇集地球空间建模和模拟方面的专家，探讨使用数据驱动和第一原理方法进行空间气象建模和预测方面的共同问题。 一个主要目标将是确定制定不确定性量化综合框架所需的内容，该框架将利用这两种方法的进展来加快改进空间气象预报的研究。 这是下一个重要步骤，很可能导致采取创新和协同办法来发展未来的能力。 讲习班的一项重要产出将是一份关于极端空间气象事件及相关自然灾害建模和预测的现状和未来展望的综合报告。 研讨会提供了一个难得的宝贵机会，以扩大博士后，研究生和本科生的教育，并使网络。 讲习班将有助于发展灾害科学多学科界，这对于加快制定极端事件预测和减缓框架至关重要，了解罕见事件的统计数据及其变异性对于量化空间气象预测中的不确定性至关重要，极端事件数据的缺乏要求开发新技术。极端事件背后的不同多物理过程之间的非线性耦合，以及对底层过程本身的不完全了解，是第一原理模型中不确定性的主要来源。 改进极端空间天气预报的一个重要步骤是不确定性量化，这本质上是跨学科的，需要将学科研究人员、计算科学家、建模人员和统计学家聚集在一起的全面努力。 讲习班为确定和探索空间气象极端事件预测方面的重要协同作用提供了一个论坛，讲习班的成果可对一般极端事件预测产生影响。