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Abstract This study uses a new, unique dataset created by combining multi-Doppler radar wind and reflectivity analysis, diabatic Lagrangian analysis (DLA) retrievals of temperature and water substance, and a complex hail trajectory model to create millions of numerically simulated hail trajectories in the Kingfisher, Oklahoma, supercell on 29 May 2012. The DLA output variables are used to obtain a realistic, 4D depiction of the storm’s thermal and hydrometeor structure as required input to the detailed hail growth trajectory model. Hail embryos are initialized in the hail growth module every 3 min of the radar analysis period (2251–0000 UTC) to produce over 2.7 million hail trajectories. A spatial integration technique considering all trajectories is used to identify locations within the supercell where melted particles and subsevere and severe hailstones reside in their lowest and highest concentrations. It is found that hailstones are more likely to reside for longer periods closer to the downshear updraft within the midlevel mesocyclone in a region of decelerated midlevel mesocyclonic horizontal flow, termed the downshear deceleration zone (DDZ). Additionally, clusters of trajectories are analyzed using a trajectory clustering method. Trajectory clusters show there are many trajectory pathways that result in hailstones ≥ 4.5 cm, including trajectories that begin upshear of the updraft away from ideal growth conditions and trajectories that grow within the DDZ. There are also trajectory clusters with similar shapes that experience widely different environmental and hailstone characteristics along the trajectory. Significance StatementThe purpose of this study is to understand how hail grew in a thunderstorm that was observed by numerous instruments. The observations were input into a hail trajectory model to simulate hail growth. We found a part of the storm near the updraft where hailstones could remain aloft longer and therefore grow larger. Most modeled severe hailstones were found in the storm in this region. However, we also found that there are many different pathways hailstones can take to become large, although there are still some common characteristics among the pathways.
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Automating the analysis of hailstone layers
Abstract. The layered structures inside hailstones provide a direct indication of their shape and properties at various stages during growth. Given the myriadof different trajectories that can exist, and the sensitivity of rime deposit type to environmental conditions, it must be expected that manydifferent perturbations of hailstone properties occur within a single hailstorm; however, some commonalities are likely in the shared early stagesof growth, for hailstones of similar size (especially those that grow along similar trajectories) and final growth near the melting level. Itremains challenging to extract this information from a large sample of hailstones because of the time required to prepare cross sections andaccurately measure individual layers. To reduce the labour and potential errors introduced by manual analysis of hailstones, an automated method formeasuring layers from cross section photographs is introduced and applied to a set of hailstones collected in Melbourne, Australia. This work ismotivated by new hail growth simulation tools that model the growth of layers within individual hailstones, for which accurate measurements ofobserved hailstone cross sections can be applied as validation. A first look at this new type of evaluation for hail growth simulations isdemonstrated.
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- Award ID(s):
- 1855063
- PAR ID:
- 10474430
- Publisher / Repository:
- European Geophysical Union
- Date Published:
- Journal Name:
- Atmospheric Measurement Techniques
- Volume:
- 16
- Issue:
- 3
- ISSN:
- 1867-8548
- Page Range / eLocation ID:
- 695 to 706
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/amt-16-695-2023
