Convectively-induced wind gusts and associated environments in Southern Brazil

Abstract This study investigates convective wind gusts measured by the Brazilian National Meteorological Institute (INMET) automated surface weather station (AWS) network in southern Brazil from 2005 to 2015. Gusts starting at 10 m s $$^{-1}$$ were sampled, with those exceeding 25 m s $$^{-1}$$ being classified as severe. Severe wind gusts were more frequent in spring and summer, mainly occurring from mid-afternoon to overnight hours. The western portion of southern Brazil recorded the highest number of severe gusts. Atmospheric variables measured by the AWSs during the gust occurrences were analyzed to detect cold pools and mesohighs. For severe gusts, the median pressure [temperature] variation was + 4.6 hPa [ $$-$$ 6.5 K], with a 95th percentile [5th percentile] of + 8.2 hPa [ $$-$$ 13.0 K]. Proximal convective parameters from ERA5 reanalysis were used to assess the atmospheric environments associated with the convective gusts. Emphasis was placed on the ability of these parameters to differentiate between severe and weak gust environments. Higher convective available potential energy (CAPE), steeper mid-level lapse rates, and stronger deep-layer wind shear (DLS) were observed for severe gusts. However, significant overlap in the magnitude of the convective parameters across different wind intensities was found, with only the 0–6 km mean wind and the downdraft CAPE showing some skill in highlighting the severe gust environments. A linear discriminant analysis using mixed-layer CAPE and DLS was performed, with the resulting discriminant displaying a good performance in distinguishing between severe and weak wind gust environments.

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Publication Details

Journal
Climate Dynamics
Published
2025-08-26
DOI
https://doi.org/10.1007/s00382-025-07811-8
Citations
1
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
1.30

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article

Convectively-induced wind gusts and associated environments in Southern Brazil

Vanessa Ferreira, Letícia de Oliveira Santos, Ernani de Lima Nascimento
1 citations
Climate Dynamics
Meteorological Phenomena and Simulations
1.30
article

Convectively-induced wind gusts and associated environments in Southern Brazil

Vanessa Ferreira, Letícia de Oliveira Santos, Ernani de Lima Nascimento
article en
1 citations

Abstract

Abstract This study investigates convective wind gusts measured by the Brazilian National Meteorological Institute (INMET) automated surface weather station (AWS) network in southern Brazil from 2005 to 2015. Gusts starting at 10 m s $$^{-1}$$ were sampled, with those exceeding 25 m s $$^{-1}$$ being classified as severe. Severe wind gusts were more frequent in spring and summer, mainly occurring from mid-afternoon to overnight hours. The western portion of southern Brazil recorded the highest number of severe gusts. Atmospheric variables measured by the AWSs during the gust occurrences were analyzed to detect cold pools and mesohighs. For severe gusts, the median pressure [temperature] variation was + 4.6 hPa [ $$-$$ 6.5 K], with a 95th percentile [5th percentile] of + 8.2 hPa [ $$-$$ 13.0 K]. Proximal convective parameters from ERA5 reanalysis were used to assess the atmospheric environments associated with the convective gusts. Emphasis was placed on the ability of these parameters to differentiate between severe and weak gust environments. Higher convective available potential energy (CAPE), steeper mid-level lapse rates, and stronger deep-layer wind shear (DLS) were observed for severe gusts. However, significant overlap in the magnitude of the convective parameters across different wind intensities was found, with only the 0–6 km mean wind and the downdraft CAPE showing some skill in highlighting the severe gust environments. A linear discriminant analysis using mixed-layer CAPE and DLS was performed, with the resulting discriminant displaying a good performance in distinguishing between severe and weak wind gust environments.

Climate DynamicsVol. 63(9)
Universidade Federal de Santa Maria (BR), Technical University of Munich (DE)
Technische Universität München
Openalex Percentile: Top 19%
Meteorological Phenomena and Simulations
1.30
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