Variability of Mesoscale Cloud and Precipitation Structures during Near-Freezing Surface Conditions Using Ground-Based Radar Observations from WINTRE-MIX

While near-freezing precipitation events have large impacts on human and natural systems, fundamental challenges remain in our ability to adequately observe, diagnose, simulate, and predict these events. The Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX) was designed to study the multiscale processes influencing the variability and predictability of p-type (rain, drizzle, freezing rain, freezing drizzle, wet snow, ice pellets, and snow) and the amount under near-freezing surface conditions. The experiment was conducted in February-March 2022 in the vicinity of Montreal. The field campaign utilized operational networks (New York State Mesonet, Canada Foundation of Innovation Climate Sentinels) and research instruments like the NRC Convair-580 research aircraft with a suite of in-situ and remote sensors, one C-band on Wheels (COW), and two X-band Doppler on Wheels (DOWs) radars, four mobile sounding systems, and four manual p-type observation stations. We will analyze the variability of mesoscale cloud and precipitation structures and mesoscale flow during near-freezing conditions using ground-based radars. Small-scale vertical motions within clouds (convective generating cells, coherent wave motions, and shear-driven turbulence) are shown to enhance the formation of ice in supercooled clouds, leading to the enhancement of surface snow or rain. Mesoscale precipitation bands, produced by either convergence of mesoscale terrain-channeled flows or by embedded disturbances within synoptic storms, locally enhance vertical motion, increase cloud depth, and intensify precipitation rates.