Winter precipitation (rain and snowfall) has widespread impacts on communities through regional ecology, hydrological planning, and socioeconomic effects. In this presentation, I will feature important findings from winter weather regime-based studies leveraging precipitation observations from a long-term, ground-based instrument suite in the Northern Great Lakes region. Realistic estimates of rain and snowfall in weather forecasting and climate models are challenging due to uncertainties in cloud and precipitation parameterization schemes. Additionally, remote-sensing observations require assumptions about hydrometeor microphysical and radiative properties. High temporal resolution, multi-instrument observations of clouds and precipitation can help better constrain processes in models and refine retrieval assumptions, leading to more accurate quantification of accumulation. I will highlight the advantage of utilizing long-term observations to examine key physical and dynamical precipitation processes through the lens of regime partitioning. Precipitation regimes are determined using observations of macrophysical and microphysical properties, large-scale environmental conditions, and thermodynamic profile characteristics. Key findings demonstrate that regime-dependent characteristics of precipitation lead to distinct differences in frequency, intensity, and phase, microphysical properties, and overall accumulation. Additionally, I will demonstrate how winter precipitation regimes in the Northern Great Lakes region are tied to significant seasonal and subseasonal, synoptic, and thermodynamic conditions such as atmospheric blocking and anomalous moisture transport (atmospheric rivers).