Measuring Hail-like Trajectories and Growth with the Hailsonde
Bibliographic record
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".