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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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Hailstone Shapes
Abstract Hailstone growth results in a variety of hailstone shapes. These shapes hold implications for modeling of hail processes, hailstone fall behaviors including fall speeds, and remote sensing signatures of hail. This study is an in-depth analysis of natural hailstone shapes, using a large dataset of hailstones collected in the field over a 6-yr period. These data come from manual measurements with digital calipers and three-dimensional infrared laser scans. Hailstones tend to have an ellipsoidal geometry with minor-to-major axis ratios ranging from 0.4 to 0.8, and intermediate-to-major axis ratios between 0.8 and 1.0. These suggest hailstones are better represented as triaxial ellipsoids as opposed to spheres or spheroids, which is commonly assumed. The laser scans allow for precise sphericity measurements, for the first time. Hailstones become increasingly nonspherical with increasing maximum dimension, with a typical range of sphericity values of 0.57 to 0.99. These sphericity values were used to estimate the drag coefficient, which was found to have a typical range of 0.5 to over 0.9. Hailstone maximum dimension tends to be 20%–50% larger than the equivalent-volume spherical diameter. As a step toward understanding and quantifying hailstone shapes, this study may aid in better parameterizations of hail in models and remote sensing hail detection and sizing algorithms.
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- PAR ID:
- 10279387
- Date Published:
- Journal Name:
- Journal of the Atmospheric Sciences
- Volume:
- 78
- Issue:
- 2
- ISSN:
- 0022-4928
- Page Range / eLocation ID:
- 639 to 652
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract On 8 February 2018, a supercell storm produced gargantuan (> 15 cm or > 6 inches in maximum dimension) hail as it moved over the heavily populated city of Villa Carlos Paz in Córdoba Province, Argentina, South America. Observations of gargantuan hail are quite rare, but the large population density here yielded numerous witnesses and social media pictures and videos from this event that document multiple large hailstones. The storm was also sampled by the newly installed operational polarimetric C-band radar in Córdoba. During the RELAMPAGO campaign, the authors interviewed local residents about their accounts of the storm, and uncovered additional social media video and photographs revealing extremely large hail at multiple locations in town. This article documents the case, including the meteorological conditions supporting the storm (with the aid of a high-resolution WRF simulation), the storm’s observed radar signatures, and three noteworthy hailstones observed by residents. These hailstones include a freezer-preserved 4:48-inch (11:38-cm) maximum dimension stone that was scanned with a 3D infrared laser scanner, a 7:1-inch (18-cm) maximum dimension stone, and a hailstone photogrammetrically estimated to be between 7:4 and 9:3 inches (18:8-23:7- cm) in maximum dimension, which is close to or exceeds the world record for maximum dimension. Such a well-observed case is an important step forward in understanding environments and storms that produce gargantuan hail, and ultimately how to anticipate and detect such extreme events. (Capsule Summary) Gargantuan hail fell in Argentina on 8 February 2018, including one hailstone that is possibly a world-record for maximum dimension. We document eyewitness and social media accounts of the hail, and analyze the parent storm and its environment.more » « less
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Severe (>2.5 cm) hail causes >$5 billion in damage annually in the United States. However, radar sizing of hail remains challenging. Typically, spheroids are used to represent hailstones in radar forward operators and to inform radar hail-sizing algorithms. However, natural hailstones can have irregular shapes and lobes; these details significantly influence the hailstone’s scattering properties. The high-resolution 3D structure of real hailstones was obtained using a laser scanner for hail collected during the 2016–17 Insurance Institute for Business and Home Safety (IBHS) Hail Field Study. Plaster casts of several record hailstones (e.g., Vivian, South Dakota, 2010) were also scanned. The S-band scattering properties of these hailstones were calculated with the discrete dipole approximation (DDA). For comparison, scattering properties of spheroidal approximations of each hailstone (with identical maximum and minimum dimensions and mass) were calculated with the T matrix. The polarimetric radar variables have errors when using spheroids, even for small hail. Spheroids generally have smaller variations in the polarimetric variables than the real hailstones. This increased variability is one reason why the correlation coefficient [Formula: see text] tends to be lower in observations than in forward-simulated cases using spheroids. Backscatter differential phase δ also is found to have large variance, particularly for large hailstones. Irregular hailstones with a thin liquid layer produce enhanced and more variable values for reflectivity factor at horizontal polarization ZHH, differential reflectivity ZDR, specific differential phase KDP, linear depolarization ratio (LDR), and δ compared with dry hailstones; [Formula: see text] is also significantly reduced.more » « less
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Abstract. A new technique, named “HailPixel”, is introduced for measuring the maximum dimension and intermediate dimension of hailstones from aerial imagery. The photogrammetry procedure applies a convolutional neural network for robust detection of hailstones against complex backgrounds and an edge detection method for measuring the shape of identified hailstones. This semi-automated technique is capable of measuring many thousands of hailstones within a single survey, which is several orders of magnitude larger (e.g. 10 000 or more hailstones) than population sizes from existing sensors (e.g. a hail pad). Comparison with a co-located hail pad for an Argentinian hailstorm event during the RELAMPAGO project demonstrates the larger population size of the HailPixel survey significantly improves the shape and tails of the observed hail size distribution. When hail fall is sparse, such as during large and giant hail events, the large survey area of this technique is especially advantageous for resolving the hail size distribution.more » « less
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This is Part II of a multi-part series exploring the fundamental nature of hail growth through a toy model developed in Part I. The toy model uniquely parameterizes all hail growth processes by single-valued parameters with great computational efficiency. The parameters are uncoupled so that environment, storm, and hail embryo characteristics, and their impact on hail growth, can be studied independently---a task 3D trajectory models cannot perform because of their highly coupled nature. Three Monte Carlo simulations were run to compare hail growth from small and large hail embryos, and coupled and uncoupled model parameters. Hail with maximum dimension ($$D$$) $$\le25.71$$ cm grew in the physically coupled small-embryo simulation, $$D\le33.59$$ cm hail grew in the physically coupled large-embryo simulation, and $$D\le44.97$$ cm hail grew in the uncoupled large-embryo simulation. The largest hailstones from the three Monte Carlo simulations took similar trajectories, accumulating a large proportion of their mass both while suspended and during their fall. Analysis of model parameters corroborate current hail growth theory, indicating three necessary ingredients for large hail: (1) a favorable embryo size and location, (2) a long residence time in a water-rich updraft, and (3) a balance between updraft vertical velocity and hailstone fall speed. The sensitivity of hail size to these parameters is analyzed: a hailstone's potential size is limited by its updraft-pass duration and the available amount of supercooled liquid water, but hail size is most sensitive to the balance between its fall speed and its encountered updraft vertical velocity.more » « less
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1175/jas-d-20-0250.1
