Abstract

A new microphysics scheme has been developed based on the prediction of bulk particle properties for a single ice-phase category, in contrast to the traditional approach of separating ice into various predefined species (e.g., cloud ice, snow, and graupel). In this paper, the new predicted partic... Show moreA new microphysics scheme has been developed based on the prediction of bulk particle properties for a single ice-phase category, in contrast to the traditional approach of separating ice into various predefined species (e.g., cloud ice, snow, and graupel). In this paper, the new predicted particle properties (P3) scheme, described in Part I of this series, is tested in three-dimensional simulations using the Weather Research and Forecasting (WRF) Model for two contrasting well-observed cases: a midlatitude squall line and winter orographic precipitation. Results are also compared with simulations using other schemes in WRF. Simulations with P3 can produce a wide variety of particle characteristics despite having only one free ice-phase category. For the squall line, it produces dense, fast-falling, hail-like ice near convective updraft cores and lower-density, slower-falling ice elsewhere. Sensitivity tests show that this is critical for simulating high precipitation rates observed along the leading edge of the storm. In contrast, schemes that represent rimed ice as graupel, with lower fall speeds than hail, produce lower peak precipitation rates and wider, less distinct, and less realistic regions of high convective reflectivity. For the orographic precipitation case, P3 produces areas of relatively fast-falling ice with characteristics of rimed snow and low- to medium-density graupel on the windward slope. This leads to less precipitation on leeward slopes and more on windward slopes compared to the other schemes that produce large amounts of snow relative to graupel (with generally the opposite for schemes with significant graupel relative to snow). Overall, the new scheme produces reasonable results for a reduced computational cost. Show less