Convection-Permitting Ensemble Forecasts of the 10–12 December 2013 Lake-Effect Snow Event: Sensitivity to Microphysical Parameterizations

Lake-effect snow (LeS) presents a substantial forecast challenge for convection-permitting models, due in part to uncertainties in the parameterization of microphysical processes. Here we focus on understanding these uncertainties for a LeS event that occurred during 10–12 December 2013 during the Ontario Winter Lake-effect Systems (OWLeS) field campaign. Throughout this event, long-lake-axis-parallel snowbands persisted downwind of the eastern shore of Lake Ontario, leading to snowfall accumulations as high as 101.5 cm (liquid precipitation equivalent of 62.5 mm) on the Tug Hill Plateau.

We run nested simulations of the 10–12 December 2013 LeS event at 12-, 4-, and 1.33-km horizontal grid spacing using the Weather Research and Forecasting (WRF) model configured similarly to the operational High-Resolution Rapid Refresh model. Sensitivity experiments are conducted by simulating the event with different microphysical schemes. Large differences between these microphysics experiments are found in the LeS band intensity and morphology, with smaller differences in the band timing and position. Maximum storm-total liquid precipitation equivalent amounts among microphysics ensemble members range from 30 to 60 mm.

Results from the WRF simulations are compared to detailed observations from OWLeS, including NEXRAD radar data and surface snowfall and crystal habit observations. Additionally, measurements from the University of Wyoming King Air aircraft, including vertically pointing cloud radars and in-situ flight-level thermodynamic and microphysical observations, are used to compare observed and modeled cloud structures. By analyzing the cloud microphysics, such as the supercooled liquid water content, hydrometeor size distributions, and precipitation fallspeed, we compare the observed and modeled lake-effect cloud properties and assess which microphysics schemes are most accurately simulating cloud processes during this LeS event.