Sensitivity of Simulated Rain Microphysics to Rain Drop Parameters and Comparison with Observations

Abstract:

Accurate representation of precipitation microphysics remains a challenge in numerical modeling. Model simulations using two-moment bulk microphysics require a priori choices, such as the rain shape parameter (ν), which is used to determine the relative numbers of smaller and larger raindrops comprising the rain drop size distribution (DSD) for a simulation. Selection of ν is often arbitrary, due in part to limited observations. In contrast, a priori assumptions about ν are unnecessary in model simulations using bin microphysics because the shape of the distribution is predicted. Herein, the sensitivity of rainfall characteristics to ν is assessed using a suite of high-resolution numerical model simulations for both a continental deep convective supercell and a maritime warm rain event. The two cases are simulated using bin and bulk microphysical parameterizations. The microphysical process rates and budgets are analyzed to examine sensitivity of the microphysical fields to the prescribed ν. As ν is increased, the supercell case shows increased reflectivity, and the warm rain case shows an increase in surface precipitation rate. The simulations using bulk microphysics show differences in evolution, precipitation characteristics, and microphysical process rates when compared to the bin microphysics simulations for both cases.

The microphysical processes and rainfall characteristics of the bulk and bin simulations are evaluated relative to observations using a framework previously developed which applies principal component analysis (PCA) to an extensive disdrometer dataset. The framework describes the co-variability of six surface rain DSD parameters and provides a means for inferring microphysical processes from surface observations.The PCA framework is applied to the simulation output allowing for a comparison of the variability between the simulated events and observations. In both simulated cases of convection, higher values of ν in the bulk microphysics simulations correspond, in this framework, more closely with the observations. These findings demonstrate the importance of assumptions constraining rain DSDs in microphysical parameterizations and provide a model-to-observation comparison to help guide a priori choices of ν in numerical model simulations.