A review of hail growth by stochastic collection in a comulonimbus model

Abstract

A study of severe convective storms, including tornadoes, indicates that hail is almost always associated with them. Large hail, often having physical characteristics which denote wet growth, is frequently observed to fall in advance of large, damaging tornadoes. Results obtained from a cumulus model, which includes hail growth by stochastic coalescence, support these observations. Hail, rather than rain, is responsible for the large radar reflectivities, and primarily responsible for the mass loading of the updraft, because its size is not dynamically limited as is that of a large raindrop. The applicability of the model, a one-dimensional, time dependent model, is discussed and then the characteristics of hail growth are examined in a variety of conditions, which are determined in nature by aerosols through their capability to initiate condensation, coalescence and drop freezing. Conditions favorable for both dry and wet growth are simulated, corresponding to a cumulonimbus which develops in a shearing environment.