Improving the Representation of Hail in the Thompson Microphysics Scheme

Anders A. Jensen, Gregory Thompson, Kyoko Ikeda, Sarah A. Tessendorf

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Methods to improve the representation of hail in the Thompson–Eidhammer microphysics scheme are explored. A new two-moment and predicted density graupel category is implemented into the Thompson–Eidhammer scheme. Additionally, the one-moment graupel category’s intercept parameter is modified, based on hail observations, to shift the properties of the graupel category to become more hail-like since the category is designed to represent both graupel and hail. Finally, methods to diagnose maximum expected hail size at the surface and aloft are implemented. The original Thompson–Eidhammer version, the newly implemented two-moment and predicted density graupel version, and the modified (to be more hail-like) one-moment version are evaluated using a case that occurred during the Plains Elevated Convection at Night (PECAN) field campaign, during which hail-producing storms merged into a strong mesoscale convective system. The three versions of the scheme are evaluated for their ability to predict hail sizes compared to observed hail sizes from storm reports and estimated from radar, their ability to predict radar reflectivity signatures at various altitudes, and their ability to predict cold-pool features like temperature and wind speed. One key benefit of using the two-moment and predicted density graupel category is that the simulated reflectivity values in the upper levels of discrete storms are clearly improved. This improvement coincides with a significant reduction in the areal extent of graupel aloft, also seen when using the updated one-moment scheme. The two-moment and predicted density graupel scheme is also better able to predict a wide variety of hail sizes at the surface, including large (.2-in. diameter) hail that was observed during this case.

Original languageEnglish
Pages (from-to)2307-2332
Number of pages26
JournalMonthly Weather Review
Volume151
Issue number9
DOIs
StatePublished - Sep 2023

Keywords

  • Cloud microphysics
  • Deep convection
  • Hail
  • Numerical weather prediction/forecasting

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