Analysis demonstrates intense wind gusts linked to the tropopause in cyclone Leslie landfall, suggesting forecasting improvements are needed.
On 13 October 2018, the coastal area of central Portugal was hit by an intense windstorm due to the landfall of post‐tropical cyclone Leslie , that just hours prior had been a hurricane. This windstorm produced record‐breaking winds of 176 km·h −1 in Figueira da Foz, which may have been caused by a rare occurrence of a sting jet (SJ). This study aims to understand the physical mechanisms behind this windstorm, using a state‐of‐the‐art numerical simulation model, Weather Research and Forecast (WRF)‐Advanced Research WRF core (ARW) v4.5.1, to reproduce its atmospheric properties and evolution. The simulation closely mirrored the observations, albeit with a slight southward shift in Leslie 's path. Nevertheless, the modelled impact areas closely matched with in situ observations and media reports. The intense wind gusts, which coincided with a mid‐tropospheric wind descent, exceeded 100 km·h −1 during Leslie 's approach. Subsequent folding of the tropopause facilitated an unstable environment conducive to vertical motion, sustaining high surface winds after landfall. Synoptic field analysis at peak impact time revealed intense winds along the bent‐back front, with saturated air masses advancing towards the coast while vertical profiles showed strong subsiding jets. Lagrangian air particle analysis illustrated that trajectories originating from the west and descending rapidly prior to landfall are reminiscent of SJ patterns. Notably, particles from the north followed lower trajectories, suggesting cold conveyor belt dynamics. Mesoscale instability analysis highlighted the prevalence of slantwise movement, with convective downdrafts and a transition from a predominantly conditional symmetric instability (CSI) release state to a mix of CSI, Inertial Instability and Symmetric Instability mechanisms after landfall. This article highlights the complexity of such a system and the need for further study to improve forecasting and warning systems in a warming climate where such cyclones are likely to increase in frequency and intensity.
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Lima et al. (2025) studied this question.
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