Bayesian estimation of ice sticking efficiencies using profiling radar Doppler spectra and in situ measurements of ice properties

Ice-ice collision sticking efficiencies strongly impact the ice aggregation process in stratiform precipitation that, in turn, affects stratiform rain properties. Despite the importance of ice aggregation, ice sticking efficiencies are poorly known and model parameterizations vary by orders of magnitude. Here we take advantage of Doppler spectra obtained during a trailing-stratiform mesoscale convective system from profiling S- and K-band radars during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma. These observations are used as probabilistic constraint on ice sticking efficiency within equilibrium solutions of one-dimensional column model simulations with size-resolved microphysics that use ice particle size distributions measured in situ as upper boundary conditions. A Markov chain Monte Carlo sampler is used to estimate the probability density function of ice sticking efficiency for various temperature levels. Results indicate that sticking efficiencies vary as a function of temperature, and are considerably different than those used in microphysical parameterization schemes. Preliminary results will also be shown using these derived ice sticking efficiencies in three-dimensional NASA-unified WRF simulations of the observed storm.