Examining Outer Band Supercell Environments in Landfalling Tropical Cyclones using Ground-Based Radar Analyses

IF 2.8 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Monthly Weather Review Pub Date : 2024-07-04 DOI:10.1175/mwr-d-23-0287.1
A. A. Alford, Benjamin Schenkel, Samuel Hernandez, Jun A. Zhang, M. Biggerstaff, Emily Blumenauer, T. Sandmæl, S. Waugh
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Abstract

Supercells in landfalling tropical cyclones (TCs) often produce tornadoes within 50 km of the coastline. The prevalence of TC tornadoes near the coast is not explained by the synoptic environments of the TC, suggesting a mesoscale influence is likely. Past case studies point to thermodynamic contrasts between ocean and land or convergence along the coast as a possible mechanism for enhancing supercell mesoscyclones and storm intensity. This study augments past work by examining the changes in the hurricane boundary layer over land in context of vertical wind shear. Using ground-based single- and dual-Doppler radar analyses, we show that the reduction of the boundary layer wind results in a increase in vertical wind shear/storm relative helicity inland of the coast. We also show that convergence along the coast may be impactful to supercells as they cross the coastal boundary. Finally, we briefly document the changes in mesocyclone vertical vorticity to assess how the environmental changes may impact individual supercells.
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利用地基雷达分析研究登陆热带气旋的外带超级暴风环境
登陆热带气旋(TC)中的超级气团经常在海岸线 50 公里范围内产生龙卷风。热带气旋龙卷风在海岸附近的盛行无法用热带气旋的同步环境来解释,这表明很可能受到中尺度的影响。过去的案例研究指出,海洋与陆地之间的热动力对比或沿岸的辐合可能是增强超大型中气旋和风暴强度的机制。本研究在垂直风切变的背景下考察了陆地上空飓风边界层的变化,从而对过去的工作进行了补充。我们利用地面单多普勒和双多普勒雷达分析表明,边界层风力的减弱导致海岸内陆垂直风切变/风暴相对螺旋度的增加。我们还表明,沿岸的辐合可能会对穿过沿岸边界的超级暴风圈产生影响。最后,我们简要记录了中气旋垂直涡度的变化,以评估环境变化如何影响单个超级气旋。
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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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