Reference number : GC-2017-Q1-02405, amendment number : , agreement type : G, recipient legal name : Duguay, Claude (University of Waterloo), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : The Global Climate Observing System (GCOS) of the World Meteorological Organization (WMO) has recognized &ldquo;Lakes&rdquo; as one of its Essential Climate Variables (ECVs). Amongst the lake variables identified as sensitive indicators of climate change are lake surface temperature, lake area, lake water level, and more recently added are ice freeze-up and break-up dates. This decade has seen and will continue to see the launch of an unprecedented number of Earth Observation satellites from space agencies that will offer an extraordinary opportunity to observe changes and variability in these lake properties over high-latitude northern regions. This also happens at a time when unmanned aerial vehicles (UAVs), which can fill a critical measurement gap between field measurements and satellite imagery, are increasingly becoming available for rapid deployment in order to capture more local changes in lake properties occurring at even shorter time scales. 
 
Using data from these emerging remote sensing technologies, the proposed research will: (1) develop satellite-based retrieval algorithms and products of lake properties, focusing on ice cover extent/phenology, thickness and snow depth on ice; and (2) conduct process studies aimed at advancing our understanding of the response of a large, deep, lake (Great Slave Lake) and shallow lakes/ponds of the Hudson Bay Lowlands to atmospheric forcing on sub-daily to seasonal time scales during the ice and open water seasons. Particular attention will be paid to the response of lakes during transition periods (ice to open water and open water to ice; floating ice to grounded ice on shallow lakes), extended wet and dry periods, and more extreme/rapid events (e.g. following intense rainfall lasting a few hours, snowmelt lasting a few days, wind storms). 
 
The research program will produce for the first time: (1) global/regional satellite-derived ice extent and phenology products at both high temporal (1-2 days) and spatial resolutions (300 m &ndash; large lakes; 30 m small Arctic lakes) required for climate assessments, winter shipping operations and numerical weather forecasting; and (2) ice thickness and snow-on ice products needed for climate assessments and improvement of lake models. It will also generate new knowledge on the regional response of shallow lakes and Great Slave Lake to atmospheric forcing at spatial and temporal resolutions now observable with new satellite missions and UAVs. Observations from a UAV, in particular, will help document and clarify the response of ice and open water surfaces to extreme weather events that are becoming more frequent with climate warming., program purpose french : The Global Climate Observing System (GCOS) of the World Meteorological Organization (WMO) has recognized &ldquo;Lakes&rdquo; as one of its Essential Climate Variables (ECVs). Amongst the lake variables identified as sensitive indicators of climate change are lake surface temperature, lake area, lake water level, and more recently added are ice freeze-up and break-up dates. This decade has seen and will continue to see the launch of an unprecedented number of Earth Observation satellites from space agencies that will offer an extraordinary opportunity to observe changes and variability in these lake properties over high-latitude northern regions. This also happens at a time when unmanned aerial vehicles (UAVs), which can fill a critical measurement gap between field measurements and satellite imagery, are increasingly becoming available for rapid deployment in order to capture more local changes in lake properties occurring at even shorter time scales. 
 
Using data from these emerging remote sensing technologies, the proposed research will: (1) develop satellite-based retrieval algorithms and products of lake properties, focusing on ice cover extent/phenology, thickness and snow depth on ice; and (2) conduct process studies aimed at advancing our understanding of the response of a large, deep, lake (Great Slave Lake) and shallow lakes/ponds of the Hudson Bay Lowlands to atmospheric forcing on sub-daily to seasonal time scales during the ice and open water seasons. Particular attention will be paid to the response of lakes during transition periods (ice to open water and open water to ice; floating ice to grounded ice on shallow lakes), extended wet and dry periods, and more extreme/rapid events (e.g. following intense rainfall lasting a few hours, snowmelt lasting a few days, wind storms). 
 
The research program will produce for the first time: (1) global/regional satellite-derived ice extent and phenology products at both high temporal (1-2 days) and spatial resolutions (300 m &ndash; large lakes; 30 m small Arctic lakes) required for climate assessments, winter shipping operations and numerical weather forecasting; and (2) ice thickness and snow-on ice products needed for climate assessments and improvement of lake models. It will also generate new knowledge on the regional response of shallow lakes and Great Slave Lake to atmospheric forcing at spatial and temporal resolutions now observable with new satellite missions and UAVs. Observations from a UAV, in particular, will help document and clarify the response of ice and open water surfaces to extreme weather events that are becoming more frequent with climate warming., agreement title english : Lake-atmosphere interactions at northern high latitudes: Remote sensing and process studies, agreement title french : Lake-atmosphere interactions at northern high latitudes: Remote sensing and process studies, agreement number : RGPIN, agreement value : 290000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada