The leewards shores of the Laurentian Great Lakes are highly susceptible to lake‐induced snowfall. During the late autumn and winter season, cold air advection over relatively warm lakes can induce instability in the lower planetary boundary layer (PBL), facilitating the exchange of moisture and energy fluxes and fuelling the development of snowfall. Snowfall in this region can have disastrous impacts on local communities such as the November 2014 Buffalo storm that caused 13 fatalities. This paper discusses historical snowfall trends along the Canadian leewards shores of Lakes Superior and Huron‐Georgian Bay and explores several lake‐induced predictor variables that may influence the snowfall trends. Spatio‐temporal snowfall and total precipitation trends were computed for the 1980–2015 period over the Great Lakes Basin (GLB) using the Daymet (version 3) gridded estimated data set. Results show a significant decrease in snowfall, at a rate of 40 cm/36 years, and a significant decrease in total precipitation of 20 mm/36 years, along the Ontario snowbelts of Lake Superior and partially along that of Lake Huron‐Georgian Bay at the 95% confidence level during the cold season. Attributions to these negative spatio‐temporal trends are explored using data from the North American Regional Reanalysis (NARR) and the Canadian Ice Service (CIS) data sets. Predictor variables show significant warming in lake surface temperature (LST) at a rate of over 6 K/36 years for Lake Superior, significant decrease in ice cover fraction for both lakes, and an increase in the vertical temperature gradient (VTG) between the LST and the 850 mb level. While the behavioural trends of these variables are believed to enhance snowfall through increased evaporation, there are other complex processes involved, such as inefficient moisture recycling and increased moisture storage in warmer air masses that may inhibit the development of snowfall along the immediate leewards shores of Lake Superior.

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The Laurentian Great Lakes Basin (GLB) is prone to snowfall events developed from extratropical cyclones or lake-effect processes. Monitoring extreme snowfall trends in response to climate change is essential for sustainability and adaptation studies because climate change could significantly influence variability in precipitation during the 21st century. Many studies investigating snowfall within the GLB have focused on specific case study events with apparent under examinations of regional extreme snowfall trends. The current research explores the historical extremes in snowfall by assessing the intensity, frequency, and duration of snowfall within Ontario’s GLB. Spatiotemporal snowfall and precipitation trends are computed for the 1980 to 2015 period using Daymet (Version 3) monthly gridded interpolated datasets from the Oak Ridge National Laboratory. Results show that extreme snowfall intensity, frequency, and duration have significantly decreased, at the 90% confidence level, more so for the Canadian leeward shores of Lake Superior than that of Lake Huron, for the months of December and January. To help discern the spatiotemporal trends is snowfall extremes, several trend analyses for lake-induced predictor variables were analysed for two cities, Wawa and Wiarton, along the snowbelts of Lakes Superior and Huron, respectively. These variables include monthly maximum and minimum air temperature, maximum wind gust velocity, lake surface temperature, and maximum annual ice cover concentration. Resultant significant increase in December’s maximum and minimum air temperature for the city of Wawa may be a potential reason for the decreased extreme snowfall trends.

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