Hierarchy of microphysical parameterizations suitable for cloud and mesoscale forecast models

There have been a considerable amount of research on the modeling of microphysical processes that lead to formation of precipitation within dynamical frameworks. This research has been concerned with many time and spatial scales, and physics mechanisms. While the most general theme often is to understand the role of natural and anthropogenic aerosols to precipitation formation, other purposes such as the prediction of specific physical phenomena such as rain, snow, and hail on the ground, aircraft icing conditions aloft, and precipitation enhancement potential remain important goals. The present paper will present a hierarchy of microphysical parameterizations schemes to represent the major physical process characteristics of precipitation development in wintertime mid-latitude storms. The present approach utilizes classical spectral functions to represent each hydro-meteor class (i.e. cloud water, rain water, pristine ice, snow ,and grauple) in an explicit equation set. The hierarchy of schemes range from more complex two parameter functions to simplified one parameter representations of each class. The present work examines the suitability of the spectral assumptions commonly used to reduce the number of variables from two parameter to one parameter representations. The present paper will present results using the non-hydrostatic Weather Research and Forecast Model (WRF) on the well documented case study of Dec 13-14,2001 from the IMPROVE 2 field experiment.