VORTEX2: A Study of Tornado and Tornadic Thunderstorm Dynamics through High-Resolution Simulation, Advanced Data Assimilation and Prediction

龙卷风旋转起源的验证实验#2 （VORTEX 2）是对导致龙卷风形成的因素的多尺度调查。旋涡2是旋涡1的后续，旋涡1的实地阶段是在1994年和1995年春季进行的。涡旋1号提高了对龙卷风和非龙卷风风暴的运动结构的认识，并为超级单体风暴和龙卷风形成的演变对非常精细的空间尺度非均质性的敏感性提供了一些线索。VORTEX 2社区打算扩展和建立在VORTEX 1的结果之上。进一步了解龙卷风的障碍之一是对大气状态缺乏足够高分辨率的完整观测。“漩涡2号”的野外阶段将收集前所未有的对流风暴和龙卷风及其环境的观测资料。来自风暴分析和预测中心（CAPS）的一个团队将参与涡旋2号现场实验，并在四个主要领域进行研究：1)生成实时高分辨率（1-2公里）风暴规模集合和确定性预测；2)开展超高分辨率（低至几米）龙卷风案例数值模拟实验，对概念模型进行动态理解和验证；3)研究微物理过程及其参数化对雷暴下降气流、冷池和阵风锋动力学的影响及其在龙卷风形成中的作用；4)将常规观测和特殊观测同化到非常高分辨率的四维数据集中，以提高对雷暴到龙卷风尺度的动力学和可预测性的理解，并研究特殊现场数据对NWP和初始条件敏感性的影响。智力价值：该项目预计将对解决有关龙卷风形成和衰减、龙卷风雷暴动力学及其与风暴环境的相互作用、龙卷风雷暴中微物理过程的作用以及龙卷风和龙卷风雷暴的可预测性等许多科学问题作出重大贡献。所获得的知识将有助于更好地评估龙卷风在超级单体雷暴中发生的可能性，从而在预测龙卷风强度和寿命方面取得进展。更广泛的影响：这项研究将直接解决天气研究最重要的目标之一——提高准确预测强烈危险天气的能力。该项目将使研究生和年轻的博士后科学家接触重大的科学领域实验，并为他们提供处理实验数据集的实践经验。它将在先进数据同化和高分辨率模拟以及NWP等日益重要的领域为他们提供急需的教育和培训。研究结果将通过该小组与业务数据同化系统和预测模型的工作，以及通过他们参与NOAA危险天气试验台（HWT）春季预报实验，直接应用于业务。后者使气象预报员和大学科学家能够接触到最先进的预报能力和产品。

The Verification of Origins of Rotation in Tornadoes Experiment #2 (VORTEX 2) is a multi-scale investigation of factors that lead to tornadogenesis. VORTEX 2 is a follow on to VORTEX 1 whose field phase was conducted during the Spring of 1994 and 1995. The VORTEX 1 advanced knowledge of the kinematic structures of tornadic and nontornadic storms and provided some hints as to the sensitivity of the evolution of supercell storms and tornadogenesis to very fine spatial scale heterogeneity. The VORTEX 2 community intends to extend and build upon the results of VORTEX 1. One of the obstacles in furthering understanding of tornadoes is the lack of complete observations of the atmospheric state at a sufficiently high resolution. The field phase of VORTEX 2 will collect unprecedented observations at the scales of convective storms and tornadoes and of their environment. A team from the Center for Analysis and Prediction of Storms (CAPS) will participation in the VORTEX 2 field experiment and conduct research in four principal areas: 1) Generate real-time high resolution (1-2 km) storm-scale ensemble and deterministic forecasts; 2) Conduct ultra-high (down to few meters) resolution numerical simulation experiments for tornado cases for dynamic understanding and validation of conceptual models; 3) Study the impact of microphysical processes and their parameterizations on thunderstorm downdraft, cold pool, and gust front dynamics and their roles in tornadogenesis; 4) Assimilate routine and special observations into very-high resolution four dimensional data sets to advance understanding of dynamics as well as predictability at the thunderstorm through tornado scales and for studying the impact of special field data on NWP and initial condition sensitivities. Intellectual merit: The project is expected to contribute significantly to addressing many of the scientific questions concerning tornadogenesis and decay, tornadic thunderstorm dynamics and their interaction with storm environment, the role of microphysical processes within tornadic thunderstorms, and the predictability of tornadoes and tornadic thunderstorms. The knowledge gained will allow better assessment of the probability of tornadoes occurring in supercell thunderstorms and thus will lead to advances in forecasting tornado intensity and longevity. Broader Impacts: The research will directly address one of the most important goals of weather research -- to improve the ability to accurately predict intense hazardous weather. This project will expose graduate students and young post-doctoral scientists to a major scientific field experiment and give them hands-on experiences working with experimental data sets. It will provide much needed education and training for them in the increasingly important areas of advanced data assimilation and high-resolution simulation and NWP. The research findings will have a direct path to operations through the group's work with operational data assimilation systems and prediction models and through their participation in the NOAA Hazardous Weather Testbed (HWT) Spring Forecast Experiments. The latter exposes operational weather forecasters, as well as university scientists, to cutting-edge forecasting capabilities and products.