Abstract
Hail processes in deep convection can have a substantial impact on precipitation characteristics as well as on dynamic and thermodynamic properties of convective downdrafts and cold pools, yet the realistic representation of hail in many cloud-resolving models employing bulk microphysical schemes is challenging. The limits imposed by fixing one or two of the distribution parameters in many one- and two-moment bulk microphysics schemes often lead to particularly poor representations of particles within the tails of size distribution spectra; an especially important consideration for hail, which covers a broad range of sizes in nature. In order to improve the representation of hail distributions in simulations of deep moist convection in cloud-resolving numerical models, a new triple-moment bulk hail microphysics scheme (3MHAIL) is presented and evaluated. The 3MHAIL scheme predicts the relative dispersion parameter for a gamma distribution function via prognostication of the sixth moment (related to the reflectivity factor) of the distribution in addition to the mass mixing ratio and number concentration (third and zeroeth moments, respectively) thereby allowing for a fully prognostic distribution function. Significant improvement in the representation of sedimentation, melting, and formation processes of hail are achieved with the 3MHAIL scheme compared to lower-order moment schemes.
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