Numerical modeling of maximum hail in deep convection
Gerhard W. Reuter, University of Alberta, Edmonton, AB, Canada; and F. Jia
A time-dependent cumulus model coupled with a hail growth model is developed to simulate hail growth and forecast maximum hail size. Observed soundings were used to initialize the coupled cumulus-hail model to simulate hailstorms for three summers. For each day, the forecast hail size on the ground was compared with daily observations of maximum hail size collected within the Alberta Hail Project area.
The cumulus-hail model was skillful in forecasting the occurrence and size of hail. The forecasting of maximum hail size was improved by including the parameterization of precipitation in the cumulus model. Overall, the model improved forecasting of maximum hail size compared against the operationally used method, HAILCAST, which was based on a steady-state cloud model. This improvement was attributed to the employment of the time-dependent cloud model as the evolution of the fields of cloud water and updraft provided more realistic surrounding conditions for hail growth.
Poster Session 4, Forecasting Techniques and Warning Decision Making Posters I
Tuesday, 12 October 2010, 3:00 PM-4:30 PM, Grand Mesa Ballroom ABC
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