Department of Applied Geomatics
University of Sherbrooke
Alexandre Langlois (Regular member)
Introduction: The accelerated warming currently observed in the Arctic is leading to a series of positive climate feedbacks which is generally densifying the snow cover. Snow density in the Arctic is critical to the survival of several ungulate species given that it is governing foraging conditions. Density above a certain threshold can lead to nutrient deficiencies and even to starvation in extreme cases. Snow densification caused by strong winds and rain-on-snow events is poorly understood, especially with regard to the spatiotemporal variability of the processes governing densification. An FMCW radar would enable the study of the spatial variability of snow density and stratigraphy in the Canadian Arctic to address this science gap. This radar would enable the analysis of numerous snow cover variables over large areas, compared to the single geographic location of a snowpit. This assessment would be conducted prior and after strong wind and/or rain-on-snow events to quantify their impact on snow. Objectives: The main objective of this research project is to develop an algorithm capable of retrieving snow density from FMCW radar signatures in order to characterize the spatial variability and impact of wind on the densification of the snow cover. The main objective is based on four specific goals: to develop and validate an algorithm retrieving snow density and stratigraphy using an FMCW radar; to map the spatial variability of snow depth, stratigraphy and density using the radar mounted on a drone; to evaluate the impact of strong winds on the density of snow cover; to integrate modifications to the densification scheme within the 'Outil de Spatialisation de SNOWPACK en Arctique' (OSSA) to improve the representation of wind effect in the snow simulations. Study sites: The research will take place in Cambridge Bay, Nunavut, in the Intensive Monitoring Area of the Canadian High-Arctic Research Station. It’s an area where the snow cover has been studied for years, enabling an easy access to reference values. Material and methods: The elaboration of an algorithm to retrieve snow density and stratigraphy will be conducted using a portable FMCW radar. The validation of the snow depth, density and snow-water equivalent of the different snow layers will be done by digging snowpits. Afterwards, a radar will be mounted on a drone that will fly over multiple sites before and after strong wind and/or rain-on-snow events enabling the creation of a map of the various characteristics of the snow cover’s stratigraphy. To validate the maps, a few snow pits will be dug on the site every time the drone will be flown. Once the impact if strong winds quantified, it will be possible to integrate this knowledge into the OSSA, to enhance the precision of the snow cover simulation over the entire Canadian archipelago. Expected results: The main expected results are: development of an algorithm able to extract the density and stratigraphy of the snow cover; creation of spatiotemporal maps of density and snow depth; improvement of the parametrization of density in the OSSA.
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