Observational and Numerical Modeling Study of Downburst Generation Using Dual-Polarization Radar

使用双偏振雷达产生下击暴的观测和数值模拟研究

• 批准号: 2110709
• 负责人: Jacob Carlin
• 金额: $ 29.75万
• 依托单位: University of Oklahoma Norman Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2110709&HistoricalAwards=false
• 关键词: Observational; Numerical; Modeling; Study; Downburst

This project is to study a hazard weather phenomenon known as downbursts. The Downbursts are rapidly descending columns of air that can cause strong, damaging winds that pose a threat to aviation, infrastructure, livestock, and human life. Meteorologists rely on weather radar data to detect developing downbursts, but because they are relatively localized and can develop quickly, it is often difficult to issue warnings for them in advance. However, recent advancements in radar technology now permit improved insight into the factors that lead to downbursts, but a comprehensive study examining such signatures has yet to be performed. By better understanding the causes of downbursts and what these factors look like in their existing radar data, forecasters will be able to better anticipate their occurrence and intensity before they reach the ground, and thus provide earlier warnings with fewer false alarms and more time for people to safely seek shelter. In addition, as computers play an increasingly large role in deciding when to issue severe weather warnings, the insights gained from this study will help determine how reliably weather models simulate downbursts and provide the basis for future automated downburst detection. The project involves mentoring a graduate student to be the next generation of atmospheric scientists. This study seeks to use both observations and numerical simulations of downbursts in a complementary manner to understand the relation between the sources of negative buoyancy that drive downbursts and their manifestation in observed dual-polarization radar variables. A novel cell-tracking algorithm will be used to comprehensively survey the polarimetric characteristics of downbursts and their variability across a variety of thermodynamic environments and geographic regions. Additionally, a one-dimensional model with spectral bin microphysics that is coupled to a forward polarimetric radar operator will then be used to simulate downbursts and quantitatively examine the association between the environment, sources of negative buoyancy (i.e., precipitation loading and diabatic cooling), and the resultant downburst intensity with the evolution and spatial distribution of the simulated polarimetric variables. Informed by the findings of the first two components, the third part of this study will evaluate the ability for existing convection-resolving models with bulk microphysics schemes to realistically simulate downbursts and identify any deficiencies limiting their usefulness.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.

这个项目是为了研究一种称为下击暴流的灾害性天气现象。下击暴流是快速下降的气柱，可能会造成强烈的破坏性大风，对航空、基础设施、牲畜和人类生命构成威胁。气象学家依靠天气雷达数据来探测正在发展的下击暴流，但由于它们相对局部化，发展速度很快，往往很难提前发布警报。然而，最近雷达技术的进步现在可以更好地洞察导致下击暴流的因素，但还没有进行一项全面的研究来检查这种信号。通过更好地了解下击暴流的原因以及这些因素在他们现有的雷达数据中是什么样子，天气预报员将能够在它们到达地面之前更好地预测它们的发生和强度，从而为更早的预警提供更少的错误警报和更多的时间让人们安全地寻找避难所。此外，随着计算机在决定何时发布恶劣天气警报方面发挥越来越大的作用，从这项研究中获得的见解将有助于确定天气模型模拟下击暴流的可靠性，并为未来的自动下击暴流检测提供基础。该项目包括指导一名研究生成为下一代大气科学家。这项研究试图以互补的方式利用观测和数值模拟下击暴流，以了解驱动下击暴流的负浮力来源与它们在观测到的双极化雷达变星中的表现之间的关系。一种新的单体跟踪算法将被用来全面调查下击暴流的偏振特征及其在各种热力学环境和地理区域的变异性。此外，一个具有光谱面元微物理的一维模式将被用来模拟下击暴流，并定量研究环境、负浮力来源(即降水负荷和非绝热冷却)以及由此产生的下击暴流强度与模拟的极化变量的演变和空间分布之间的联系。根据前两部分的研究结果，这项研究的第三部分将评估现有的对流解析模式与大规模微物理方案模拟下击暴流的能力，并找出限制其使用的任何缺陷。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。