Collaborative Research: Observing and Understanding Planetary Boundary Layer (PBL) Heterogeneities and Their Impacts on Tornadic Storms during VORTEX-SE 2018 Field Experiment

高影响天气现象，如大风、冰雹和暴雨，具有巨大的社会经济影响。然而，预报严重的高影响天气事件，特别是龙卷风，仍然具有挑战性。历史上，龙卷风研究一直集中在大平原地区，而美国东南部也经常经历毁灭性的龙卷风。两地环境条件的显著差异和夜间龙卷风在东南地区的频繁发生，给观测和认识东南地区龙卷风的形成和发展带来了挑战。龙卷风旋转起源的验证实验-东南（VORTEX-SE）是一个研究项目，旨在了解东南地区的环境如何影响该地区龙卷风的形成、强度、结构和路径。在2018年的VORTEX-SE现场活动期间，一架飞机在龙卷风周围飞行，收集了前所未有的先进测量数据。在丘陵森林地形的地面上不容易进行这种观测。该研究将利用独特的观测资料和先进的计算机模型来了解龙卷风风暴的气流结构及其形成的特殊环境。从研究中获得的新知识将有助于改善美国各地的龙卷风预报。该项目将为研究生提供大气测量技术、数据分析和计算机建模方面的支持和培训，并使他们成为未来恶劣天气研究和预测领域的科学家。研究小组将进行观测数据分析和先进的数据同化，将观测和大气预测模型结合起来。这次前所未有的观测包括一个先进的向下指向紧凑型拉曼激光雷达（CRL），一个水平扫描下机身（LF）雷达，以及NOAA P-3飞机上的双尾部多普勒雷达（tdr）。CRL能够测量移动风暴上游大气边界层的水汽、温度和气溶胶剖面的高时空分辨率。结合P-3的现场测量和LF和TDR雷达观测，预计将对龙卷风环境进行前所未有的表征。此外，将进行龙卷风解析数值模拟，并将应用变分和基于集合的数据分析和同化技术。本研究的主要目标包括：(1)利用涡旋涡旋仪（CRL）测量数据表征对流风暴周围PBL的空间异质性和时间演变；(2)综合P-3和其他观测资料，分析和了解PBL非均质性对龙卷风风暴的影响；(3)利用先进的资料同化方法，通过模式模拟，识别和理解龙卷风风暴的关键物理过程。机载雷达和激光雷达数据与高分辨率模型模拟的协同作用将有助于为潜在的未来面向过程的现场实验铺平道路。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。

High-impact weather phenomena such as high winds, hail, and heavy rainfall have huge socio-economic impacts. However, forecast for severe high-impact weather events, especially tornadoes, remains challenging. Historically, tornado research has been concentrated in the Great Plains while the Southeastern U.S. commonly experiences devastating tornadoes as well. Significant differences in environmental conditions over the two regions and frequent occurrence of tornadoes at night in the Southeast (SE) pose challenges to observing and understanding the formation and development of tornadoes in the SE. The Verification of the Origins of Rotation in Tornadoes Experiment - Southeast (VORTEX-SE) is a research program designed to understand how environments in the SE affect the formation, intensity, structure, and path of tornadoes in this region. During the VORTEX-SE field campaign in 2018, unprecedented advanced measurements from an airplane flying around tornadoes have been collected. Such observations cannot be done easily on the ground with hilly forest terrain. The study will utilize the unique observations and advanced computer models to understand airflow structures of tornadic storms and special environments for their formation. New knowledge gained from the research will contribute to improvement of tornado forecasting across the U.S. This project will provide support and training to graduate students in atmospheric measurement technologies, data analysis, and computer modeling and prepare them to become future scientists in severe weather research and prediction.The research team will conduct observational data analysis and advanced data assimilation that integrate observations and atmospheric prediction models. The unprecedented observation includes an advanced downward-pointing Compact Raman Lidar (CRL), a horizontally scanning lower fuselage (LF) radar, and dual Tail Doppler Radars (TDRs) onboard of a NOAA P-3 aircraft. The CRL is capable of measuring high-spatial and temporal resolution of water vapor, temperature, and aerosol profiles in the atmospheric boundary layer upstream of moving storms. Together with the P-3's in-situ measurements and the LF and TDR radar observations, unprecedented characterization of tornadic environments is expected. In addition, tornado-resolving numerical simulations will be performed, and variational, and ensemble-based data analysis and assimilation techniques will be applied. The primary goals of the project include: (1) characterization of spatial heterogeneities and temporal evolution of the PBL around convective storms in the VORTEX-SE domain with CRL measurements; (2) analysis and understanding of the impact of PBL heterogeneities on tornadic storms by synthesizing P-3 and other available observations; (3) identification and understanding of key physical processes involved in the tornadic storms through model simulations with advanced data assimilation methods. The synergy of airborne radar and lidar data with high-resolution model simulations will help pave the way for potentially transformative future process-oriented field experiments.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.