Interactions Between Squall Lines and Isolated Supercell Thunderstorms via Storm-Generated Perturbations to the Local Environment

这项研究的目标是确定准线性对流系统（飑线）和超级单体雷暴在两者接近时如何通过改变其局部环境来相互作用。观测技术和数值模拟的结合将用于：1)确定由于两种风暴类型之间的接近而导致的风暴结构和强度的共同变化，以及2)将这些变化与风暴本身引起的特定环境扰动联系起来。迄今为止，人们已经对背景环境参数（如不稳定和风切变）在调节对流风暴组织和强度中的作用进行了广泛的研究，但尚不清楚风暴对这些参数的扰动如何影响邻近的对流风暴。这代表了知识库中的一个重要空白，因为广泛的恶劣天气暴发往往会出现多种风暴类型（例如，飑线和超级单体）在彼此接近的情况下演变。提高我们对这些风暴如何相互作用的理解，将使预报员在发布短期预报和恶劣天气警报时更好地了解预计会发生什么。知识价值：由于预报界试图通过诸如“预报预警计划”等新项目改善恶劣天气预警，需要克服的关键挑战之一是提高当前对地方尺度环境异质性及其对严重雷暴演变的影响的理解。该研究将通过研究局部风暴引起的环境扰动在调节强风暴组织和强度方面所起的作用来解决这一挑战。这项工作的结果将用于开发概念模型，以帮助预报员理解和预测风暴引起的环境异质性的影响，尽管无法直接观察到这些扰动。此外，我们对对流风暴动力学的了解大多来自于对雷暴或对流系统在相对“良好”条件下的研究。通过调查多个风暴如何相互作用，这项研究将是有意义的，因为它将提供一个测试，当多个风暴相互作用时，这些广义概念模型是否适用。更广泛的影响：这个研究项目的“大局”目标是通过提高对飑线和超级单体雷暴如何相互作用的理解来改善短期恶劣天气预报。这将导致更准确和具体的恶劣天气警报，从而成为在恶劣天气爆发期间更有效地保护生命和财产的手段。该项目将在整个项目过程中支持两名研究生。这样，该计划将进一步整合研究与教育，让学生参与其中，并为他们提供宝贵的第一手研究经验。研究结果将通过在国家和区域会议上的发言以及通过同行评议的期刊文章传播。此外，PI计划将数据和例子纳入他在南达科他州矿业与技术学院的常规课程中。

The goal of this research award is to determine how quasi-linear convective systems (squall lines) and supercell thunderstorms interact by modifying their local environments when the two are in close proximity. A combination of observational techniques and numerical simulations will be utilized to: 1) identify common changes to storm structure and intensity that occur as a result of the proximity between the two storm types, and 2) relate these changes to specific environmental perturbations induced by the storms themselves. To date there has been extensive study on the role that background environmental parameters such as instability and wind shear play in modulating convective storm organization and intensity, but it is unclear how storm-generated perturbations to these parameters may influence neighboring convective storms. This represents an important gap in the knowledge base as widespread severe weather outbreaks often see multiple storm types (e.g., squall lines and supercells) evolving in close proximity to one another. Improving our understanding of how these storms interact will provide forecasters with a better idea of what to expect when issuing short-term forecasts and severe weather warnings.Intellectual Merit: As the forecasting community seeks to improve severe weather warnings through new programs such as the Warn on Forecast Initiative, one of the key challenges to overcome is to improve the current understanding of local-scale environmental heterogeneity and its effect on severe thunderstorm evolution. The study will address this challenge by examining the role that localized, storm-induced perturbations to the environment play in modulating severe storm organization and intensity. The results of the work will be used to develop conceptual models to help forecasters understand and anticipate the effects of storm-induced environmental heterogeneity, despite not being able to observe these perturbations directly. Furthermore, much of what is known about convective storm dynamics comes from studies of thunderstorms or convective systems under comparatively "well-behaved" conditions. By investigating how multiple storms interact, the research will be significant as it will provide a test as to whether these generalized conceptual models apply when multiple storms are interacting.Broader Impacts: The "big picture" goal for this research project is to improve short-term severe weather forecasts by improving the understanding of how squall lines and supercell thunderstorms interact. This should lead to more accurate and specific severe weather warnings, and thus a more effective means of protecting life and property during severe weather outbreaks. The project will support two graduate students over the course of the project. In doing so, the project will further the integration of research and education, engaging the students and providing them with valuable first-hand research experience. Results will be disseminated through presentations at national and regional conferences as well as through peer-reviewed journal articles. Additionally, the PI plans to incorporate data and examples into his regular coursework at the South Dakota School of Mines and Technology.