Day-ahead (20–22 h) 3-km grid spacing convection-allowing model forecasts are performed for a severe hail event that occurred in Denver, Colorado, on 8 May 2017 using six different multimoment microphysics (MP) schemes including: the Milbrandt–Yau double-moment (MY2), Thompson (THO), NSSL double-moment (NSSL), Morrison double-moment graupel (MOR-G) and hail (MOR-H), and Predicted Particle Properties (P3) schemes. Hail size forecasts diagnosed using the Thompson hail algorithm and storm surrogates predict hail coverage. For this case hail forecasts predict the coverage of hail with a high level of skill but underpredict hail size. The storm surrogate updraft helicity predicts the coverage of severe hail with the most skill for this case. Model data are analyzed to assess the effects of microphysical treatments related to rimed ice. THO uses diagnostic equations to increase the size of graupel within the hail core. MOR-G and MOR-H predict small rimed ice aloft; excessive size sorting and increased fall speeds cause MOR-H to predict more and larger surface hail than MOR-G. The MY2 and NSSL schemes predict large, dense rimed ice particles because both schemes predict separate hail and graupel categories. The NSSL scheme predicts relatively little hail for this case; however, the hail size forecast qualitatively improves when the maximum size of both hail and graupel is considered. The single ice category P3 scheme only predicts dense hail near the surface while above the melting layer large concentrations of low-density ice dominate.
Hail and graupel are linked to lightning production and are important components of cloud evolution. Hail can also cause significant damage when it precipitates to the surface. The accurate prediction of the amount and location of hail and graupel and the effects on the other hydrometeor species depends upon the size distribution assumed. Here, we use ~310 km of in situ observations from flights of the South Dakota School of Mines and Technology T-28 storm-penetrating aircraft to constrain the representation of the particle size distribution (PSD) of hail. The maximum ~1-km hail water content encountered was 9 g m−3. Optical probe PSD measurements are normalized using two-moment normalization relations to obtain an underlying exponential shape. By linking the two normalizing moments through a power law, a parameterization of the hail PSD is provided based on the hail water content only. Preliminary numerical weather simulations indicate that the new parameterization produces increased radar reflectivity relative to commonly used PSD representations.
more » « less- NSF-PAR ID:
- 10085506
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Journal of Applied Meteorology and Climatology
- Volume:
- 58
- Issue:
- 2
- ISSN:
- 1558-8424
- Page Range / eLocation ID:
- p. 231-245
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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