Developing a Structural, Morphological, and Microphysical Understanding of Left-moving Supercells

发展对左移超级细胞的结构、形态和微观物理理解

• 批准号: 2218623
• 负责人: Matthew Van Den Broeke
• 金额: $ 47.35万
• 依托单位: University of Nebraska-Lincoln
• 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: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2218623&HistoricalAwards=false
• 关键词: Developing; Structural; Morphological; Microphysical; Understanding

Left-moving (LM) supercell thunderstorms produce a large number of severe weather reports every year, including many high-impact hail events. Radar represents a way to study these storms. New polarimetric radar technology has now been in operation long enough to allow development of a large sample of LM supercells. Using this dataset, the project will focus on when these storms occur through examination of their environments, what they look like under different environmental conditions, and how these storms’ radar signatures might be used to anticipate associated severe weather events. This will be the first large-scale study of LM supercells, and is anticipated to advance scientific understanding of these storms in a way that may lead to improved severe weather warnings for the benefit of society. An educational component will provide training to students from middle school through graduate school. A LM supercell dataset anticipated to contain 600+ individual storms for which polarimetric radar observations are available will be constructed using data from the Storm Prediction Center and manual analysis of recent radar datasets. Environments of these storms will be characterized using model output data and clustered using self-organizing maps. Polarimetric radar characteristics of the updraft, hail, and inflow regions will be quantified using the Supercell Polarimetric Observation Research Kit. Environmental clustering will be used to characterize the environments in which LM supercells occur and how their radar presentation and impacts vary across environments. LM supercells have similarities to more common right-moving storms, and the structure, microphysics, and temporal evolution of storms in the LM dataset will be compared to these characteristics in sets of right-moving storms which have been studied prior. Severe weather outcomes in LM storms will be put in the context of radar signature evolution and environmental characteristics, allowing development of models describing events which lead to severe weather production in LM supercells. The project will also include development of a mobile severe weather workshop with hands-on experimental components for middle school students. This workshop will be developed by graduate students as part of their professional development, and will be presented by students and faculty to rural and Native American students in the central Great Plains region.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.

左动物（LM）产生大量的恶劣天气报道，使许多高影响力的冰雹不一致。超级电池将重点介绍这些暴风雨的现象，它们看起来像是在不同的环境条件下的天气事件。导致对社会的好处的严重警告。使用模型输出数据和使用自组织的图表进行了量化。将在一组右转的风暴中的特征，这些风暴在雷达签名演变和环境方面的赌注中，赌注中有赌注，从而允许开发模型事件，这些事件导致LM Supercells的严重天气产生。与中学生的动手实验组成部分的讲习班。使用Toundation的知识分子IT和更广泛的影响审查标准进行支持评估。