Dynamic and statistical analysis of giant hail environments in northeast Italy

Abstract On July 24, 2023, the new European record for hail size was set in northeast (NE) Italy with a 19‐cm wide hailstone recorded during a supercell outbreak. During this event, severe storms were triggered in the Alps, moved eastward, intensified rapidly in the foothills, and generated damaging hailstorms in the plains. A detailed analysis of the available observations and numerical simulations highlights that the atmospheric environment was unusual. A high‐ tongue over the Adriatic Sea was lifted by a southerly flow above the cold pool generated by the thunderstorm outflow associated with an initial supercell. This raised the most unstable layer to 1–2 km above mean sea level in the area affected by the record‐breaking hailstorm. The vertical profile was characterized by moderate potential instability (likely a value of fed the storms) and an intense southwesterly flow in the mid‐troposphere. Additionally, there was anomalously high water‐vapor transport in the layer 2–5 km above mean sea level. Consequently, high instability seems unnecessary for the occurrence of giant hailstorms in the region. This hypothesis is assessed with a statistical analysis performed for the 2018–2023 period in NE Italy using hail reports and observed soundings. The results show that hail size has a much lower correlation with potential instability compared with kinematic parameters of the mid‐troposphere and water‐vapor transport –. Furthermore, thermodynamic parameters have better skill in predicting the occurrence of hail or large hail , while kinematic parameters of the mid‐troposphere are better predictors for very large and giant hail events.

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Publication Details

Journal
Quarterly Journal of the Royal Meteorological Society
Published
2025-03-05
DOI
https://doi.org/10.1002/qj.4945
Citations
8
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
10.41

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article

Dynamic and statistical analysis of giant hail environments in northeast Italy

Martin Setvák, Mario Marcello Miglietta, Nicola Carlon, Francesco De Martin et al.
8 citations
Quarterly Journal of the Royal Meteorological Society
Meteorological Phenomena and Simulations
10.41
article

Dynamic and statistical analysis of giant hail environments in northeast Italy

Martin Setvák, Mario Marcello Miglietta, Nicola Carlon, Francesco De Martin, Agostino Manzato
article en
8 citations

Abstract

Abstract On July 24, 2023, the new European record for hail size was set in northeast (NE) Italy with a 19‐cm wide hailstone recorded during a supercell outbreak. During this event, severe storms were triggered in the Alps, moved eastward, intensified rapidly in the foothills, and generated damaging hailstorms in the plains. A detailed analysis of the available observations and numerical simulations highlights that the atmospheric environment was unusual. A high‐ tongue over the Adriatic Sea was lifted by a southerly flow above the cold pool generated by the thunderstorm outflow associated with an initial supercell. This raised the most unstable layer to 1–2 km above mean sea level in the area affected by the record‐breaking hailstorm. The vertical profile was characterized by moderate potential instability (likely a value of fed the storms) and an intense southwesterly flow in the mid‐troposphere. Additionally, there was anomalously high water‐vapor transport in the layer 2–5 km above mean sea level. Consequently, high instability seems unnecessary for the occurrence of giant hailstorms in the region. This hypothesis is assessed with a statistical analysis performed for the 2018–2023 period in NE Italy using hail reports and observed soundings. The results show that hail size has a much lower correlation with potential instability compared with kinematic parameters of the mid‐troposphere and water‐vapor transport –. Furthermore, thermodynamic parameters have better skill in predicting the occurrence of hail or large hail , while kinematic parameters of the mid‐troposphere are better predictors for very large and giant hail events.

Quarterly Journal of the Royal Meteorological SocietyVol. 151(769)
Agenzia Regionale per la Protezione Ambientale del Piemonte (IT), Czech Hydrometeorological Institute (CZ), Institute of Atmospheric Sciences and Climate (IT), National Research Council (IT), University of Bologna (IT)
Ministero dell'Università e della Ricerca
Openalex Percentile: Top 1%
Meteorological Phenomena and Simulations
10.41
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