Mechanisms for Severe Wind Production in Nocturnal and Transitioning Convection

夜间稳定边界层（NSBL）发展时，中尺度对流系统（MCS）从地面到高空对流的转变以及随后的组织和演变还没有得到很好的理解，使强风的预报变得复杂。 在从离散单体到MCS的过渡过程中，可能会产生强烈的地面风，但这些风的开始，加强和停止的过程是不确定的。可能的水凝物的类型，分布，和这些MCS内的演变，以及NSBL，环境切变和其他因素的演变特性在启动和维持强烈的，表面到达下沉气流中发挥重要作用。该研究将通过MCS和过渡到MCS的对流系统运动学，热力学和微物理学的表征，以及这些如何受到当地环境的影响，调查在NSBL存在的情况下，强风引起的下沉气流如何到达地表。这项研究使用了计划于2015年进行的平原夜间高架对流（PECAN）项目的数据，除了已经从实地方案收集的但不太完整的数据集之外。PECAN从大量不同的观测数据中获得的运动学、热力学和微物理数据将使人们能够研究产生强风的MCSs的起始/过渡、演化、内部运动学和微物理学。多多普勒分析将用于量化通过MCS深度的3D风。内部微物理过程将从雷达反射率和双偏振场和表面disdrometer数据推断。探测系统和风廓线仪将用于诊断大气稳定性、NSBL的深度、垂直风结构和夜间低空急流（LLJ）的位置。将使用移动的中网和固定气象站（包括Pod和PISA）来量化地面冷池的强度和水平范围，并量化地面的强风。智力优势：多平台综合观测研究将导致更好地了解夜间MCS演变的微物理，热力学和运动学过程，从白天到夜间/MCS组织的过渡，以及在强风事件期间如何受到NSBL的影响。该研究将导致更好地了解导致严重夜间风发生（或不发生）的因素。这项研究还将提供基本分析，以了解产生强风的MCS是高架系统、地面系统还是混合系统，这些系统的微物理组成，以及这些系统在发生强风之前、期间和之后的运动学，以及它们如何受到当地环境的影响。分析，结果，并从研究中提高科学的理解将提供给建模和预测社区。通过与模式输出和预测的比较，改进数值模式，从而预测夜间强风产生MCS的发生、严重程度和时间，将受益于这些细尺度观测分析。更好的理解，导致更好的预测将有助于减轻这些强风产生事件的影响。通过制定一个侧重于雷达和中尺度观测的东南太平洋气候行动专门大学课程来教育学生，参与东南太平洋气候行动的实地阶段以及随后的分析工作，将有助于培养下一代科学家。

The transition from surface-based to elevated convection and the subsequent organization and evolution of mesoscale convective systems (MCSs) as the nocturnal stable boundary layer (NSBL) develops is not well understood, complicating the forecastability of severe winds. During the transition from discrete cells to an MCS, severe surface winds may be generated but the processes responsible for the onset, intensification, and cessation of these winds are uncertain. Likely the hydrometeor type, distribution, and evolution within these MCSs, as well as the evolving properties of the NSBL, environmental shear and other factors play important roles in the initiation and maintenance of intense, surface-reaching downdrafts. The research will investigate how intense-wind-causing downdrafts reach the surface in the presence of a NSBL through characterization of the MCS and transitioning-to-MCS convective system kinematics, thermodynamics and microphysics, and how these are influenced by the local environment.This study uses data from the Plains Elevated Convection at Night (PECAN) project, planned for 2015, in addition to already collected but less complete data sets from the field programs. PECAN kinematic, thermodynamic and microphysical data obtained from a large and diverse array of observing data will enable the study of initiation/transition, evolution, internal kinematics and microphysics of severe-wind-producing MCSs. Multiple-Doppler analysis will be used to quantify the 3D winds through the depth of the MCS. Internal microphysical processes will be inferred from the radar reflectivity and dual-polarization fields and surface disdrometer data. Sounding systems and wind profilers will be used to diagnose atmospheric stability, depth of the NSBL, vertical wind structure and the location of the nocturnal low-level jet (LLJ). Mobile mesonet and stationary weather stations including Pods and PISAs, will be used to quantify the strength and horizontal extent of the surface cold pool, and quantify severe winds at the surface. Intellectual Merit:The multi-platform integrated observational study will result in a better understanding of the microphysical, thermodynamic and kinematic processes underlying nocturnal MCS evolution, transition from daytime to nocturnal/MCS organization, and how these are influenced by the NSBL during severe wind events. The research will result in a better understanding of the factors leading to the occurrence (or non-occurrence) of severe nocturnal winds. This research will also provide analyses fundamental to understanding whether severe-wind producing MCSs are elevated, surfaced-based, or hybrid systems, the microphysical composition of these systems, and the kinematics of these systems before, during, and after the occurrence of severe surface winds, and how they are affected by the local environment.Broader Impacts:Analyses, results, and improved scientific understanding from the research will be made available to the modeling and forecasting communities. Improvements to numerical models and hence the forecasting of the occurrence, severity and timing of nocturnal severe-wind producing MCSs will benefit from these fine-scale observational analyses through comparison with model output and predictions. Better understanding, leading to improved forecasts will aid in mitigating the impact of these severe-wind producing events. Education of students through the development of a PECAN-specific university course focusing on radar and mesoscale observations, participation in the field phase of PECAN, and subsequent analysis efforts will help train the next generation of scientists.