Collaborative Research: Understanding Tornado Development and Maintenance in Supercells with an Emphasis on "High-End" Events

合作研究：了解超级单体中龙卷风的发展和维护，重点是“高端”事件

基本信息

批准号：
1832327
负责人：
Leigh Orf
金额：
$ 59.04万
依托单位：
University of Wisconsin-Madison
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：
2019-03-15 至 2023-02-28
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1832327&HistoricalAwards=false
关键词：
Collaborative Research Understanding Tornado Development

项目摘要

In 2011, tornadoes in the United States killed 553 people and caused $28 billion in property damage. Most of the damage and fatalities were caused by violent tornadoes spawned by supercell thunderstorms, with six tornadoes receiving EF5 rankings, the most violent category of the Enhanced Fujita scale. Last year, several outbreaks occurred with over 140 confirmed tornadoes rated between EF2 and EF4 that resulted in substantial damage and over 30 deaths. While significant advances in our knowledge of supercell thunderstorms and tornadoes have occurred in recent decades, understanding of the fundamental processes occurring within supercells that result in tornadoes remains elusive. This void in knowledge is especially concerning for violent tornadoes that are responsible for a disproportionate number of fatalities and injuries as well as damage. Until these tornado genesis and maintenance processes are understood, our ability to forecast such events is severely limited. The primary goal of this research is to improve the fundamental understanding of processes underlying the formation and maintenance of tornadoes in supercell thunderstorms, especially as these processes relate to violent tornadoes. This knowledge is critical for improving tornado forecasts, tornado warning lead times, and estimations of potential tornado strength and longevity, and is especially applicable to tornadoes of strong and violent intensity. In conjunction with an awarded NSF grant providing continued access to the NSF-funded Blue Waters supercomputer, the research will analyze petabytes of data to study the processes occurring in supercells that result in tornadoes of varying strength, longevity, and structure.Intellectual Merit:Despite advances in observational and modeling/computing technology, much still needs to be understood about the evolution of tornadoes. Few computer simulations exist in which a well-resolved tornado forms within its parent supercell, and this work uses the highest resolution simulations of violently tornadic supercells conducted to date. A control simulation with 30 meter grid spacing has been completed where twenty fields in a volume centered on the tornado during its entire life cycle have been saved to disk every model time step, which will facilitate the most accurate analysis possible. 20 m and 15 m simulations containing long-track EF5 tornadoes have also been completed, and additional runs at these resolutions will be executed as needed. Tools to efficiently interrogate and analyze model data saved every time step will be improved and new tools will be developed. New simulations will be conducted in other environments in which violent tornadoes were observed. By analyzing simulated storms in different environments and comparing tornadogenesis failure cases to cases where violent tornadoes occur, the research team aims to identify processes common within unusually violent supercells involved in the formation and maintenance of tornadoes.Broader Impacts:A better fundamental understanding of tornado development in supercell thunderstorms should help guide future field programs in which new features identified in these numerical simulations are targeted for study, and ultimately lead to improvements in our ability to accurately forecast significant tornadic events and increase tornado warning lead times. Improving our fundamental understanding of tornado maintenance, made possible through analysis of the simulations described, should provide insight critical for National Weather Service forecasters to better predict, once a tornado has developed, how long a particular tornado may last. This type of information is invaluable, especially when pertaining to high-end, long-track events. The improved understanding of tornadoes in addition to cutting-edge visualizations of this research will facilitate science education in forums ranging from formal courses for students to learning venues for the general public.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.

2011年，美国的龙卷风造成553人死亡，并造成280亿美元的财产损失。大多数损坏和死亡是由超级单体雷暴引发的猛烈龙卷风造成的，其中六场龙卷风获得 EF5 排名，这是增强型藤田等级中最猛烈的类别。去年，多起暴发的 EF2 至 EF4 级龙卷风已确认超过 140 场，造成重大损失和 30 多人死亡。尽管近几十年来我们对超级单体雷暴和龙卷风的认识取得了重大进展，但对超级单体内导致龙卷风的基本过程的了解仍然难以捉摸。对于猛烈的龙卷风来说，这种知识空白尤其令人担忧，龙卷风造成了不成比例的死亡、受伤和破坏。在了解这些龙卷风的起源和维护过程之前，我们预测此类事件的能力受到严重限制。这项研究的主要目标是提高对超级单体雷暴中龙卷风形成和维持过程的基本了解，特别是当这些过程与猛烈龙卷风相关时。这些知识对于改进龙卷风预报、龙卷风警报提前时间以及潜在龙卷风强度和寿命的估计至关重要，并且特别适用于强烈和猛烈的龙卷风。结合国家科学基金会授予的拨款，继续使用国家科学基金会资助的 Blue Waters 超级计算机，该研究将分析 PB 级数据，以研究超级细胞中发生的过程，这些过程会导致不同强度、寿命和结构的龙卷风。尽管观测和建模/计算技术取得了进步，但关于龙卷风的演变仍然有很多需要了解的地方。很少有计算机模拟能够在其母体超级单体内形成分辨率良好的龙卷风，而这项工作使用了迄今为止对猛烈龙卷风超级单体进行的最高分辨率模拟。已经完成了 30 米网格间距的控制模拟，其中在龙卷风整个生命周期中以龙卷风为中心的体积中的 20 个场已在每个模型时间步长中保存到磁盘中，这将有助于进行最准确的分析。包含长轨迹 EF5 龙卷风的 20 m 和 15 m 模拟也已完成，并将根据需要执行这些分辨率下的额外运行。将改进有效询问和分析每个步骤保存的模型数据的工具，并将开发新工具。新的模拟将在观察到猛烈龙卷风的其他环境中进行。通过分析不同环境中的模拟风暴，并将龙卷风发生失败的案例与猛烈龙卷风发生的案例进行比较，研究小组旨在确定参与龙卷风形成和维持的异常猛烈超级单体中常见的过程。更广泛的影响：对龙卷风发展有更好的基本了解超级单体雷暴中的研究应有助于指导未来的现场计划，其中这些数值模拟中确定的新特征是研究的目标，并最终提高我们准确预测重大龙卷风事件并延长龙卷风预警提前时间的能力。通过对所描述的模拟进行分析，提高我们对龙卷风维护的基本了解，应该为国家气象局预报员提供至关重要的见解，以便更好地预测龙卷风一旦形成，特定龙卷风可能会持续多久。此类信息非常宝贵，尤其是在涉及高端、长期赛事时。除了这项研究的尖端可视化之外，对龙卷风的进一步了解将促进从学生的正式课程到公众的学习场所等论坛的科学教育。该奖项反映了 NSF 的法定使命，并通过评估被认为值得支持利用基金会的智力优势和更广泛的影响审查标准。