CPOM study evaluates satellite methods for estimating supraglacial lake depth published in The Cryosphere

During the melt season (typically from May to September) on the Greenland ice sheet, water collects in depressions on the surface of the ice, creating supraglacial lakes. If these lakes have enough water and the right conditions, they can crack open (hydrofracture) which allows water to flow from the ice surface down to the bedrock underneath, where it acts like a lubricant. These lakes on the Greenland ice sheet are incredibly important, but identifying exactly how deep they are using satellite data is difficult.

This research compares different ways of measuring the depth of these supraglacial lakes, using tools including a radiative transfer equation (RTE), ArcticDEM digital elevation models, and ICESat-2 photon refraction. The team of researchers led by CPOM PhD Researcher Laura Melling (Lancaster University) applied these methods to five lakes in southwest Greenland.

The paper examines the uncertainty in these estimates, which affects our understanding of the total lake volume and how that, in turn, can interfere with predictions about how fast the ice is moving. This work demonstrates how combining information from multiple different satellite sources can improve our ability to track meltwater on top of the Greenland Ice Sheet.

Figure 1: The locations of the five supraglacial lakes in relation to the study region. Contour lines calculated from the ArcticDEM 100 m mosaic are visible on the base map as dashed grey lines. The inset map indicates the location of the study area within Greenland. Panels (1)–(5) show Lake 1 to Lake 5 in detail, where the background is a true-colour image acquired on the date shown in Table A1 for each lake. The manually delineated lake outline is given in red, and the ICESat-2 transect is given in orange. The ICESat-2 ground tracks were cropped to the lake edges. The background images in panels (1)–(5) are the Sentinel-2 tiles detailed in Table A1. The base map data are courtesy of Earthstar Geographics via Esri.
Credit: Melling et al., Feb 2024, https://doi.org/10.5194/tc-18-543-2024

Authors include: CPOM PhD Researcher Laura Melling (Lancaster University), CPOM Associate Investigator Amber Leeson, CPOM Principal Investigator Malcolm McMillan (Lancaster University), CPOM Senior Research Associate Jennifer Maddalena (Lancaster University), Jade Bowling (Lancaster University), CPOM PhD Researcher Emily Glen (Lancaster University), Louise Sandberg Sørensen (Technical University of Denmark), Mai Winstrup (Technical University of Denmark), and Rasmus Lørup Arildsen (Technical University of Denmark).

Read the full paper here.