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Abstract:
Supraglacial lakes (SGLs) are an important interface between glaciers and the atmosphere, especially on the Greenland Ice Sheet. Forming seasonally due to surface melt, these lakes contain and drain meltwater through surface channels and moulins, vertical channels flowing to the bedrock. While progress has been made to be able to accurately quantify the surface area of SGLs, the volume of water contained within them is determined less certainly, creating challenges for accurate surface mass balance calculations. The launch of ICESat-2 in 2018, however, provided a new tool for lake depth extraction. Precise lake profiles can be obtained from ICESat-2’s laser, but the long revisit time does not facilitate close monitoring of such dynamic process. Thus, this research project demonstrates an effective way to correlate lake depth profiles extracted from ICESat-2 data to Sentinel-2 multispectral images. Since Sentinel-2 captures images with a near daily revisit time in northern Greenland, this allows the lake volumes to be closely tracked over the melt season. This remote sensing research is also accompanied by several SGL bathymetry maps, gathered by in situ sonar observations in Northeastern Greenland. These data provide reliable ground truth sources against which our ICESat-2/Sentinel-2 lake depth algorithm can be validated.
