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

龙卷风实验2(旋涡2)中旋转起源的验证是对导致龙卷风发生的因素进行的多尺度调查。涡旋2是涡旋1的后续，涡旋1的场阶段是在1994年和1995年春季进行的。涡旋1提高了对龙卷风和非龙卷风的运动学结构的认识，并提供了一些关于超单体风暴和龙卷风的演化对非常精细的空间尺度非均质性的敏感性的线索。涡旋2社区打算在涡旋1结果的基础上扩展和发展。进一步了解龙卷风的障碍之一是缺乏对足够高分辨率的大气状态的完整观测。涡旋2的场相将在对流风暴和龙卷风及其环境的尺度上收集前所未有的观测。来自风暴分析和预报中心(CAPS)的一个小组将参加涡旋2现场试验，并在四个主要领域进行研究：1)产生实时高分辨率(1-2公里)风暴尺度集合和确定性预报；2)进行龙卷风个例的超高分辨率(低至几米)数值模拟试验，以动态地理解和验证概念模式；3)研究微物理过程及其参数化对雷暴下沉气流、冷池和阵风锋面动力学的影响及其在龙卷风发生中的作用；4)将常规观测和特殊观测同化为极高分辨率的四维资料集，以通过龙卷风尺度提高对雷暴的动力学和可预报性，并研究特殊场资料对数值预报和初始条件敏感性的影响。学术价值：预计该项目将大大有助于解决与龙卷风发生和衰变、龙卷风雷暴动力学及其与风暴环境的相互作用、龙卷风雷暴内微物理过程的作用以及龙卷风和龙卷风雷暴的可预测性有关的许多科学问题。所获得的知识将使人们能够更好地评估在超级单体雷暴中发生龙卷风的可能性，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。这个项目将让研究生和年轻的博士后科学家接触到一个重大的科学现场实验，并让他们获得使用实验数据集的实践经验。它将在高级数据同化、高分辨率模拟和数值预报等日益重要的领域为他们提供急需的教育和培训。这些研究成果将通过该小组使用业务数据同化系统和预测模型的工作，以及通过参与NOAA危险天气试验床(HWT)春季预报试验，为业务提供直接的途径。后者使业务天气预报员以及大学科学家接触到尖端预报能力和产品。

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.