Measuring Hail-like Trajectories and Growth with the Hailsonde

Abstract The broad spectrum of possible hailstone shapes and internal structures is a product of the complex interplay between hailstone growth physics, aerodynamics, and in-storm conditions. As a result of this sensitivity, hailstone characteristics can be highly variable within a single deep convective cell. Recent progress in modeling individual hailstone trajectories and growth has benefited from new understanding of hail production processes; however, the representativeness remains uncertain. In situ observations along hail-like trajectories have only now become possible thanks to the miniaturization of radiosonde electronics, which, when packaged into a durable probe of similar shape and size to large hailstones, can survive the conditions inside thunderstorms while behaving like hailstones. Trajectory and icing data from these hail-like probes provide invaluable information for assessing the aforementioned hail growth simulations. On 24 July 2023, two Hailsondes were launched 4 min apart into a supercell during the Northern Hail Project (NHP) in Alberta, Canada, with the storm producing large hail exceeding 50 mm (1.96 in.) in maximum dimension during the flight. The vertical speed of both probes exceeded 37 m s −1 during balloon-assisted ascent, and, after the balloons detached, the probes continued to ascend to almost 8000 m above mean sea level (MSL). Despite traveling along similar trajectories, the sondes experienced different growth regimes. Investigation of polarimetric weather radar data shows changes in the probes’ pathways relative to the updraft and a column of enhanced specific differential phase ( K DP ), indicating the first Hailsonde likely experienced a greater raindrop collection rate, contributing to the differences in icing conditions. Significance Statement Recent modeling studies of how hailstones move and grow inside thunderstorm clouds have yielded exciting new insights for improving short-term forecasting; however, whether actual hailstones behave in a similar way remains unknown. Motivated by this question, this article presents the design and use of the first hail-like probe, named Hailsonde, that follows hail-like pathways while collecting measurements of in-storm conditions. The first successful flights during the Canadian Northern Hail Project revealed that simulated hail trajectories indeed resemble reality; however, icing conditions were sensitive to small changes in the probe pathway. Planned use of the Hailsonde in upcoming field experiments will continue to close this gap between simulations and reality.

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Publication Details

Journal
Bulletin of the American Meteorological Society
Published
2025-09-24
DOI
https://doi.org/10.1175/bams-d-24-0021.1
Citations
2
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
2.60
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article

Measuring Hail-like Trajectories and Growth with the Hailsonde

Silke Trömel, Jordan Brook, Matthew R. Kumjian, Julian Brimelow et al.
2 citations
Bulletin of the American Meteorological Society
Meteorological Phenomena and Simulations
2.60
article

Measuring Hail-like Trajectories and Growth with the Hailsonde

Silke Trömel, Jordan Brook, Matthew R. Kumjian, Julian Brimelow, Joshua Stephen Soderholm, Alain Protat, Michael Kunz, Anders Peterson
article en
2 citations

Abstract

Abstract The broad spectrum of possible hailstone shapes and internal structures is a product of the complex interplay between hailstone growth physics, aerodynamics, and in-storm conditions. As a result of this sensitivity, hailstone characteristics can be highly variable within a single deep convective cell. Recent progress in modeling individual hailstone trajectories and growth has benefited from new understanding of hail production processes; however, the representativeness remains uncertain. In situ observations along hail-like trajectories have only now become possible thanks to the miniaturization of radiosonde electronics, which, when packaged into a durable probe of similar shape and size to large hailstones, can survive the conditions inside thunderstorms while behaving like hailstones. Trajectory and icing data from these hail-like probes provide invaluable information for assessing the aforementioned hail growth simulations. On 24 July 2023, two Hailsondes were launched 4 min apart into a supercell during the Northern Hail Project (NHP) in Alberta, Canada, with the storm producing large hail exceeding 50 mm (1.96 in.) in maximum dimension during the flight. The vertical speed of both probes exceeded 37 m s −1 during balloon-assisted ascent, and, after the balloons detached, the probes continued to ascend to almost 8000 m above mean sea level (MSL). Despite traveling along similar trajectories, the sondes experienced different growth regimes. Investigation of polarimetric weather radar data shows changes in the probes’ pathways relative to the updraft and a column of enhanced specific differential phase ( K DP ), indicating the first Hailsonde likely experienced a greater raindrop collection rate, contributing to the differences in icing conditions. Significance Statement Recent modeling studies of how hailstones move and grow inside thunderstorm clouds have yielded exciting new insights for improving short-term forecasting; however, whether actual hailstones behave in a similar way remains unknown. Motivated by this question, this article presents the design and use of the first hail-like probe, named Hailsonde, that follows hail-like pathways while collecting measurements of in-storm conditions. The first successful flights during the Canadian Northern Hail Project revealed that simulated hail trajectories indeed resemble reality; however, icing conditions were sensitive to small changes in the probe pathway. Planned use of the Hailsonde in upcoming field experiments will continue to close this gap between simulations and reality.

Bulletin of the American Meteorological SocietyVol. 106(10)
Karlsruhe Institute of Technology (DE), Western University (CA), Bureau of Meteorology (AU), Sandvik (Sweden) (SE), Pennsylvania State University (US), University of Bonn (DE), The University of Queensland (AU), Embedded Systems (United States) (US)
Openalex Percentile: Top 10%
Meteorological Phenomena and Simulations
2.60
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