Regime-Dependent Characteristics and Predictability of Cold Season Precipitation Events in the St. Lawrence River Valley

Abstract

Abstract The St. Lawrence River Valley experiences a variety of precipitation types (p-types) during the cold season, such as rain, freezing rain, ice pellets, and snow. These varied precipitation types exert considerable impacts on aviation, road transportation, power generation and distribution, and winter recreation, and are shaped by diverse multiscale processes that interact with the region’s complex topography. This study utilizes ERA5 reanalysis data, a surface cyclone climatology, and hourly station observations from Montréal, Québec and Burlington, VT, during October–April 2000–2018 to investigate the spectrum of synoptic-scale weather regimes that induce cold season precipitation across the St. Lawrence River Valley. In particular, k-means clustering and self-organizing maps (SOMs) are used to classify cyclone tracks passing near the St. Lawrence River Valley, and their accompanying thermodynamic profiles, into a set of event types that include a U.S. East Coast track, a Central U.S. track, and two Canadian clipper tracks. Composite analyses are subsequently performed to reveal the synoptic-scale environments and the characteristic p-types that most frequently accompany each event type. GEFSv12 reforecasts are then used to examine the relative predictability of cyclone characteristics and the local thermodynamic profile associated with each event type at 0–5-day forecast lead times. The analysis suggests that forecasted cyclones near the St. Lawrence River Valley develop too quickly and are located left-of-track relative to the reanalysis on average, which has implications for forecasts of the local thermodynamic profile and p-type across the region when the temperature is near 0°C.