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

这项研究奖的目的是确定当准线性对流系统和超级单体雷暴接近时，它们如何通过改变它们的局部环境来相互作用。观测技术和数值模拟的结合将被用来：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。到目前为止，人们对背景环境参数，如不稳定和风切变在调节对流风暴组织和强度中所起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。这代表着知识库中的一个重要缺口，因为大范围的恶劣天气爆发通常会看到多种风暴类型(例如，咆哮线和超级单体)在彼此附近演变。提高我们对这些风暴如何相互作用的理解，将为预报员在发布短期预报和恶劣天气警告时提供更好的想法。智慧的优点：随着预测界寻求通过新的项目，如预报警告倡议，改善恶劣天气警告，需要克服的关键挑战之一是提高目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。这项研究将通过研究局部化的风暴诱导的环境扰动在调节严重风暴组织和强度方面所起的作用来应对这一挑战。这项工作的结果将被用于开发概念模型，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，人们对对流风暴动力学的许多了解都来自于对相对“良好”条件下的雷暴或对流系统的研究。通过调查多个风暴如何相互作用，这项研究将具有重要意义，因为它将提供一个测试，即这些概念性模型是否适用于多个风暴相互作用的情况。广泛影响：这项研究项目的“大局”目标是通过提高对斜线和超级单体雷暴相互作用的理解，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告，从而成为在恶劣天气爆发期间保护生命和财产的更有效手段。该项目将在整个项目过程中支持两名研究生。通过这样做，该项目将进一步整合研究和教育，让学生参与进来，并为他们提供宝贵的第一手研究经验。结果将通过在国家和区域会议上的发言以及同行评议的期刊文章来传播。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.