Mixed-phase precipitation in mountainous regions has large temporal and spatial variability (Buytaert et al., 2006;Costa-Cabral et al., 2013); and in comparatively warm environments like the Sierra Nevada, solid precipitation amounts (i.e., snowfall) are sensitive to small elevation-dependent temperature changes. Accurate estimates of precipitation partitioning into rain and snow are crucial as a primary input for hydrologic predictions and process studies (Henn et al., 2018;Morin et al., 2006;Sharma et al., 2012). This is because the amount and spatial pattern of mixed-phase winter precipitation in mountainous regions, where snowfall can account for a considerable portion of annual precipitation, play a crucial role in determining local-to-regional water supply and flood risk. For example, winter precipitation combined with snowpack storage in the Sierra Nevada provides the major water source for urban, irrigation, hydroelectric, and ecosystem uses in California (Bales et al., 2006;Pandey et al., 1999), where its Mediterranean climate leads to wet winters and dry summers. Besides the sparse availability (Avanzi et al., 2021), maintenance, and representativeness issues of precipitation gauges in high-elevation regions, the systematic bias introduced by wind-induced undercatch is also a considerable source of uncertainty (