Journal of Geophysical Research: Atmospheres

A climatology of snowfall-temperature relationships in Canada


  • Robert E. Davis,

  • Michael B. Lowit,

  • Paul C. Knappenberger,

  • David R. Legates


A better understanding of potential climate change impacts on the global hydrological cycle requires knowledge of the interaction between air temperature and water in its various forms. One important example is the effect of air temperature on snowfall. Proper parameterization of the snowfall-temperature relationship in climate models is essential for accurate prediction of future snowfall changes that might arise from high-latitude warming. On a climatological basis, at any location, air temperature and snowfall can be correlated positively (higher temperatures increase atmospheric moisture and snowfall through the Clausius-Clapeyron relationship) or negatively (precipitation falls as rain instead of snow). Examination of 50 years of monthly snowfall water equivalent and mean temperature data indicates that the snowfall-temperature relationship is positive in the high latitudes and negative in southern Canada, along both coasts, and east of the Rockies. The “zero line” (the transition zone north of which warmer months receive more snowfall than colder months) migrates southward from autumn to winter so that by January most of eastern and northwestern Canada has a positive snowfall-temperature slope. The primary exception to a straightforward relationship between slope and latitude occurs east of the Rockies, where anomalous negative slopes extend far to the north. In this region, dry, adiabatically warmed air from downslope or circulation effects may reduce the number of snow events and modify the slope of the snowfall-temperature curve. Based on first principles and Canadian observations, we develop a function relating temperature to snowfall that attempts to account for the complex spatial and seasonal nature of the snowfall-temperature relationship. Given the importance of snowfall in the global radiation balance, this analysis could be used to improve climate change predictions.