The potential roles of preexisting airmass boundaries on a tornadic supercell observed by TORUS on 28 May 2019

IF 2.8 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Kristen L. Axon, Adam L. Houston, Conrad L. Ziegler, Christopher C. Weiss, Erik N. Rasmussen, Michael C. Coniglio, Brian Argrow, Eric Frew, Sara Swenson, Anthony E. Reinhart, Matthew B. Wilson
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引用次数: 0

Abstract

Abstract On 28 May 2019, a tornadic supercell, observed as part of TORUS (Targeted Observation by UAS and Radars of Supercells) produced an EF-2 tornado near Tipton, KS. The supercell was observed to interact with multiple preexisting airmass boundaries. These boundaries and attendant air masses were examined using unoccupied aircraft system (UAS), mobile mesonets, radiosondes, and dual-Doppler analyses derived from TORUS mobile radars. The cool side air mass of one of these boundaries was found to have higher equivalent potential temperature and backed winds relative to the warm side air mass; features associated with MAHTEs (mesoscale air masses with high theta-E). It is hypothesized that these characteristics may have facilitated tornadogenesis. The two additional boundaries were produced by a nearby supercell and appeared to weaken the tornadic supercell. This work represents the first time that UAS have been used to examine the impact of preexisting airmass boundaries on a supercell, and it provides insights into the influence environmental heterogeneities can have on the evolution of a supercell.
2019年5月28日TORUS观测到的龙卷风超级单体中预先存在的气团边界的潜在作用
2019年5月28日,一个龙卷风超级单体在堪萨斯州蒂普顿附近产生了EF-2龙卷风,这是TORUS(无人机和超级单体雷达的目标观测)的一部分。观察到超级单体与多个预先存在的气团边界相互作用。使用无人飞机系统(UAS)、移动中网、无线电探空仪和来自TORUS移动雷达的双多普勒分析来检查这些边界和伴随的气团。其中一个边界的冷侧气团相对于暖侧气团具有更高的等效位温和逆风;与MAHTEs(具有高theta-E的中尺度气团)相关的特征。据推测,这些特征可能促进了龙卷风的形成。这两个额外的边界是由附近的超级单体产生的,似乎削弱了龙卷风超级单体。这项工作代表了首次使用无人机来检查预先存在的气团边界对超级单体的影响,并且它提供了对环境异质性可能对超级单体进化的影响的见解。
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来源期刊
Monthly Weather Review
Monthly Weather Review 地学-气象与大气科学
CiteScore
6.40
自引率
12.50%
发文量
186
审稿时长
3-6 weeks
期刊介绍: Monthly Weather Review (MWR) (ISSN: 0027-0644; eISSN: 1520-0493) publishes research relevant to the analysis and prediction of observed atmospheric circulations and physics, including technique development, data assimilation, model validation, and relevant case studies. This research includes numerical and data assimilation techniques that apply to the atmosphere and/or ocean environments. MWR also addresses phenomena having seasonal and subseasonal time scales.
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