743 Investigating the Sensitivity of Nucleation Parameterization on Ice Growth

Tuesday, 9 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Lauriana C. Gaudet, Univ. at Albany, SUNY, Albany, NY; and K. Sulia

The accurate prediction of precipitation from lake-effect snow events associated with the Great Lakes region depends on the parameterization of thermodynamic and microphysical processes, including the formation and subsequent growth of frozen hydrometeors. More specifically, the formation of ice hydrometeors has been represented through varying forms of ice nucleation parameterizations considering the different nucleation modes (e.g., deposition, condensation-freezing, homogeneous). These parameterizations have been developed from in-situ measurements and laboratory observations. A suite of nucleation parameterizations consisting of those published in Meyers et al. (1992) and DeMott et al. (2010) as well as varying ice nuclei data sources are coupled with the Adaptive Habit Model (AHM, Harrington et al. 2013), a microphysics module where ice crystal aspect ratio and density are predicted and evolve in time. Simulations are run with the AHM which is implemented in the Weather Research and Forecasting (WRF) model to investigate the effect of ice nucleation parameterization on the non-spherical growth and evolution of ice crystals and the subsequent effects on liquid-ice cloud-phase partitioning. Specific lake-effect storms that were observed during the Ontario Winter Lake-Effect Systems (OWLeS) field campaign (Kristovich et al. 2017) are examined to elucidate this potential microphysical effect. Analysis of these modeled events is aided by dual-polarization radar data from the WSR-88D in Montague, New York (KTYX). This enables a comparison of the modeled and observed polarmetric and microphysical profiles of the lake-effect clouds, which involves investigating signatures of reflectivity, specific differential phase, correlation coefficient, and differential reflectivity. Microphysical features of lake-effect bands, such as ice, snow, and liquid mixing ratios, ice crystal aspect ratio, and ice density are analyzed to understand signatures in the aforementioned modeled dual-polarization radar variables. Hence, this research helps to determine an ice nucleation scheme that will best model observations of lake-effect clouds producing snow off of Lake Ontario and Lake Erie, and analyses will highlight the sensitivity of the evolution of the cases to a given nucleation scheme.
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