Collaborative Research: RAPID--The Influence of Terrain on Tornado Characteristics Following the 10-11 December 2021 Tornado Outbreak

合作研究：RAPID——2021年12月10日至11日龙卷风爆发后地形对龙卷风特征的影响

• 批准号: 2221977
• 负责人: Christopher Godfrey
• 金额: $ 3.51万
• 依托单位: University of North Carolina at Asheville
• 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: 2022-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2221977&HistoricalAwards=false
• 关键词: Collaborative; Research; RAPID; Influence; Terrain

Recent observational and modeling studies of the influence of terrain on tornadoes have universally cited the need for further research. The 10-11 December 2021 tornado outbreak provides a unique and valuable opportunity to fill knowledge gaps by conducting both aerial and ground evaluations in forested areas damaged by strong tornadoes that passed over complex terrain. The primary objective of this Rapid Response Research (RAPID) project is to provide a preliminary evaluation of the influence of terrain on tornado characteristics. The project team will conduct a high-resolution assessment of forest damage and terrain based on aerial imagery and ground surveys, and then develop a quantitative comparison of damage levels and tornado characteristics across terrain features using GIS tools, machine learning, and analytical vortex models. Results will inform simple engineering models to assess risk to the built and natural environment and will enhance general awareness of the threat of tornadoes in areas where the public may not recognize the dangers. Existing research into the influence of terrain on tornado characteristics has substantial limitations, including a limited number of case studies, idealized simulation parameters, and inconclusive or contradictory results. A novel research approach will test the hypotheses that 1) tornado intensity decreases (increases) as the vortex moves uphill (downhill), 2) higher (lower) surface roughness leads to stronger (weaker) near-surface winds, and 3) terrain features can deflect the path of a tornado in predictable ways. This approach employs the structure-from-motion (SfM) photogrammetric range imaging technique to provide an extremely high-resolution characterization of both terrain and treefall at centimeter scales through the development of 2-D orthomosaics and 3-D point clouds that include information on the size, location, and disposition of hundreds of thousands of trees. The data collected here and the subsequent analyses will help the meteorological and engineering communities to move toward scientific consensus regarding the influence of terrain on tornadic circulations and will allow for new and more detailed research studies. Although large eddy simulation (LES) tests are beyond the scope of the work, the data collected here will also enable next-generation LES studies with far greater realism than has previously been possible.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.

关于地形对龙卷风的影响的最新观察和建模研究已普遍认为需要进一步研究。 2021年12月10日至11日，龙卷风爆发为填补知识空白的独特而有价值的机会，通过在森林地区进行空中和地面评估，并在森林地区进行地面评估，而森林地区受到经过复杂地形的强烈龙卷风的破坏。这项快速响应研究（快速）项目的主要目标是对地形对龙卷风特征的影响进行初步评估。项目团队将根据空中图像和地面调查对森林损害和地形进行高分辨率评估，然后使用GIS工具，机器学习和分析涡流模型对跨地形特征的损伤水平和龙卷风特征进行定量比较。结果将为简单的工程模型提供信息，以评估对建筑和自然环境的风险，并将在公众可能无法承认危险的地区提高人们对龙卷风威胁的普遍认识。现有对地形对龙卷风特征影响的研究具有很大的局限性，包括案例研究数量有限，理想化的仿真参数以及不确定或矛盾的结果。一种新型的研究方法将检验以下假设：1）随着涡流移动（下坡）的移动，龙卷风强度降低（增加），2）较高（较低）的表面粗糙度会导致更强（较弱的）近表面风，3）地形特征可以在可预测的方式中偏转龙卷风的路径。该方法采用摄影范围成像技术采用结构 - 摄影范围成像技术，通过开发2-D Orthomosaics以及包括有关大小，位置和处置的信息的3-D点云，以厘米尺度的地形和树层以厘米尺度提供极高的高分辨率表征。此处收集的数据以及随后的分析将有助于气象和工程社区在地形对龙卷风循环的影响方面达成科学共识，并允许进行新的，更详细的研究。尽管大型涡流模拟（LES）测试超出了工作的范围，但此处收集的数据还将实现与以前更多的现实主义更大的下一代LES研究。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估来通过评估来获得支持的。