A method for adaptive habit prediction in bulk microphysical models. Part III: Applications and studies within a two-dimensional kinematic model

Prior studies of mixed-phase clouds predict a single axis length assuming spherical particles or mass–dimensional relationships derived from in situ data. These methods cannot mechanistically evolve particle shape, leading to inaccuracies in estimates of mixed-phase lifetime.

Parts I and II of this study report on the development and parcel model testing of an adaptive habit parameterization that predicts two bulk crystal lengths. The method is implemented into a two-dimensional kinematic model in which the dynamic flow field is prescribed, allowing for sedimentation and separate advection of length mixing ratios. Similar to other studies, results show that mass–dimensional relationships produce large variation of phase, despite similar choice in particle type.