Articles | Volume 19, issue 7
https://doi.org/10.5194/tc-19-2635-2025
https://doi.org/10.5194/tc-19-2635-2025
Research article
 | 
22 Jul 2025
Research article |  | 22 Jul 2025

Volumetric evolution of supraglacial lakes in southwestern Greenland using ICESat-2 and Sentinel-2

Tiantian Feng, Xinyu Ma, and Xiaomin Liu

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Cited articles

Arthur, J. F., Stokes, C., Jamieson, S. S., Carr, J. R., and Leeson, A. A.: Recent understanding of Antarctic supraglacial lakes using satellite remote sensing, Prog. Phys. Geog., 44, 837–869, https://doi.org/10.1177/0309133320916114, 2020. 
Banwell, A. F., Arnold, N. S., Willis, I. C., Tedesco, M., and Ahlstrøm, A. P.: Modeling supraglacial water routing and lake filling on the Greenland Ice Sheet, J. Geophys. Res.-Earth, 117, F04012, https://doi.org/10.1029/2012JF002393, 2012. 
Box, J. E. and Ski, K.: Remote sounding of Greenland supraglacial melt lakes: implications for subglacial hydraulics, J. Glaciol., 53, 257–265, https://doi.org/10.3189/172756507782202883, 2007. 
Box, J. E., Hubbard, A., Bahr, D. B., Colgan, W. T., Fettweis, X., Mankoff, K. D., Wehrlé, A., Noël, B., van den Broeke, M. R., Wouters, B., Bjørk, A. A., and Fausto, R. S.: Greenland ice sheet climate disequilibrium and committed sea-level rise, Nat. Clim. Change, 12, 808–813, https://doi.org/10.1038/s41558-022-01441-2, 2022. 
Breiman, L.: Random Forests, Machine Learning, 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001. 
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Short summary
During the melting season, substantial quantities of surface meltwater converge in topographically depressed regions, forming supraglacial lakes (SGLs). We extract SGL area and profile depth using remote sensing data and then invert the depth of entire SGLs based on the machine learning method. By applying the above-mentioned methods, we capture the volumetric evolution of SGLs throughout the entire melt season of 2022 in southwestern Greenland.
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