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Abstract Hail research and forecasting models necessarily involve explicit or implicit—and uncertain—physical assumptions regarding hailstones’ shape, tumbling behavior, fall speed, and thermal energy transfer. Whereas most models assume spherical hailstones, we relax this assumption by using hailstone shape data from field observations to establish empirical size–shape relationships with reasonable degrees of randomness considering hailstones’ natural shape variability, capturing the observed distribution of triaxial ellipsoidal shapes. We also incorporate explicit, random tumbling of individual hailstones during their growth to simulate their free-falling behavior and the resultant changes in cross-sectional area (which affects growth by hydrometeor collection). These physical attributes are incorporated in calculating hailstones’ fall speeds, using either empirical relationships or analytical relationships based on each hailstone’s Best and Reynolds numbers. Options for drag coefficient modification are added to emulate hailstones’ rough surfaces (lobes), which then modifies their thermal energy and vapor exchange with the environment. We investigate how applying these physical assumptions about nonspherical hail to the Penn State hail growth trajectory model, coupled with Cloud Model 1 supercell simulations, impacts hail production and examine the reasons behind the resulting variability in hail statistics. The choice of hailstone size–mass relation and fall speed scheme have the strongest influence on hail sizes. Using nonspherical, tumbling hailstones reduces the number of large hailstones produced. Applying shape-specific thermal energy transfer coefficients subtly increases sizes; the effects of lobes vary depending on the fall speed scheme used. These physical assumptions, although adding complexity to modeling, can be parameterized efficiently and potentially used in microphysics schemes. Significance StatementIn numerical modeling of hailstorms, we usually consider hailstones to be spherical to simplify calculations, but in nature, hailstones generally are not spheres and can be rather lumpy and have spikes. The purpose of this study is to examine how the model result would change when nonspherical hailstone shape is implemented. We examine the relationship between hailstone shape and physical processes during hail growth in effort to explain why these changes occur and offer insights on how nonspherical hailstone shape may be parameterized in bulk microphysics schemes.
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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
