In preparation for her upcoming PhD thesis defence, Janine Baijnath-Rodino will present her research at our seminar this month. Her presentation is entitled:
Climatological
Trends
and
Predictions
in
Snowfall
over
the
Canadian
Snowbelts of
the
Laurentian
Great
Lakes
Basin.
Please join us with your tough questions to help Janine prepare. Her abstract follows:
"The leeward shores of the Laurentian Great Lakes are highly susceptible to lake-induced snowfall that is either driven by extratropical cyclones or lake effect processes. During the late autumn and winter season, cold air advection over relatively warm lakes induces instability in the lower planetary boundary layer (PBL). This process facilitates the exchange of moisture and energy fluxes and fuels the development of snowfall. In addition, the large thermal capacity of the lakes can enhance existing precipitation that is associated with frontal boundaries moving over the Great Lakes Basin (GLB). Lake-induced snowfall can produce whiteout snowsqualls and heavy snowfall accumulations in highly localized areas, which can affect residential, agricultural, economic, and recreational sectors within the GLB. Therefore, the dangerous impacts of lake-induced snowfall on snowbelt communities warrant the need for improved spatiotemporal investigations in observed and predicted snowfall.
Despite many snowfall studies, three gaps have been identified. The first gap suggests that minimal snowfall research has been conducted for the Ontario snowbelts of Lake Superior and Lake Huron-Georgian Bay (hereinafter referred to as Lake Huron). The second gap identifies that there has been limited investigations conducted on climatological trends in snowfall and LES predictor variables. The third gap suggests that most lake-induced snowfall studies have employed coarse global climate models (GCMs) and regional climate models (RCMs) at spatial resolutions that make it difficult to delineate meso-beta scale LES snow bands. Thus, the objective of this study is to conduct historical spatiotemporal trends in snowfall and LES predictor variables, and to examine the predictive performance of a RCM in capturing LES events for the under-studied regions of the Canadian Laurentian Great Lakes' snowbelts."