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

这个项目是为了研究一种叫做降暴的危险天气现象。下爆是一种快速下降的气柱，可以产生强烈的破坏性风，对航空、基础设施、牲畜和人类生命构成威胁。气象学家依靠气象雷达数据来探测正在形成的下爆，但由于它们相对来说是局部的，发展速度很快，因此通常很难提前发布预警。然而，最近雷达技术的进步使人们能够更好地了解导致下爆的因素，但尚未对这些特征进行全面的研究。通过更好地了解下爆的原因以及这些因素在现有雷达数据中的表现，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，从而提供更早的警报，减少误报，为人们提供更多的时间安全寻找避难所。此外，由于计算机在决定何时发布恶劣天气警报方面发挥着越来越大的作用，从本研究中获得的见解将有助于确定天气模型模拟下爆的可靠性，并为未来的自动下爆检测提供基础。该项目包括指导一名研究生成为下一代大气科学家。本研究试图以一种互补的方式使用下暴的观测和数值模拟，以了解驱动下暴的负浮力来源与观测到的双极化雷达变量之间的关系。一种新的细胞跟踪算法将用于全面调查下爆的极化特征及其在各种热力学环境和地理区域的可变性。此外，与正演极化雷达操作员耦合的具有光谱bin微物理的一维模型将用于模拟下暴，并定量检查环境、负浮力来源（即降水负荷和绝热冷却）以及由此产生的下暴强度与模拟极化变量的演变和空间分布之间的关系。根据前两个部分的发现，本研究的第三部分将评估现有的对流解析模型与整体微物理方案的能力，以实际模拟下爆，并确定限制其实用性的任何缺陷。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.