Evaluation of Rimed-Ice Parameterization using an Idealized Supercell Storm and Polarimetric Radar Data Simulator
Microphysics uncertainty remains a large source of model error, especially in high resolution models with deep convection. Currently, multi-category, multi-moment bulk microphysics schemes (BMPs) are popular in storm-scale modeling. Among hydrometeor categories, rimed-ice parameterization significantly influences storm evolution through latent heat release associated with phase change. Representation of processes involving rimed ice presents large differences among various microphysics schemes. In this study, we apply a polarimetric radar data simulator to idealized supercell storms simulated using four advanced two-moment (2M) microphysics schemes in the WRF model that use different approaches for rimed-ice parameterization: the Morrison (2M graupel-like or hail-like category), Milbrandt-Yau (both 2M graupel-like and hail-like), NSSL (both 2M graupel-like and hail-like, with predicted [variable] graupel density), and the new predicted particle properties (P3) scheme, which prognoses ice and rime mixing ratio, ice number concentration, and rime volume for a single ice category. Each scheme’s ability to reproduce typical polarimetric signatures associated with rimed-ice microphysics will be evaluated, and the characteristics and biases of each scheme’s rimed-ice distribution are discussed.