Large Scale Processes Leading to Enhanced Lake Effect Snow Events

Accurate lake-effect and lake-enhanced snow forecasts pose challenges due to numerical weather prediction (NWP) models struggling to consistently pinpoint snow location, intensity, and duration. Lake-enhanced storm systems, characterized as deeper synoptic snowfall events intensified by lake surface and shore topographic processes transiting the Great Lakes region, remain relatively understudied yet constitute significant long-lived snowfall events. Recent ground-based observational studies have highlighted abrupt shifts in local macro- and microphysical attributes related to these enhanced systems, triggering notable increases in snow particle size distributions and snow-liquid ratios as the synoptic system passes through the Great Lakes region. In this work, we will use surface-based observations, such as the Micro Rain Radar (MRR; profiling radar) and Precipitation Imaging Package (PIP; snow particle imager), from the NWS Marquette, MI office and output from NWP model simulations to better grasp the regional cloud microphysics, boundary layer thermodynamics, and surface conditions that drive these impactful lake-enhanced snow systems and their unique microphysical properties. Our primary aim is to enhance our understanding of the features that trigger these amplified systems, thereby refining our ability to forecast snow precipitation, Snow-to-Liquid Ratio (SLR), and accumulation more effectively.