edu.ucar.opensky::articles:42807 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T17:56:08.229759 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.net/ark:/85065/d7571hb5 https://doi.org/10.24381/cds.713858f6 https Related Dataset #1 Arctic regional reanalysis on single levels from 1991 to present https://doi.org/10.5281/ZENODO.14587026 https Related Dataset #2 Data and Code for: "Greenland Ice Sheet wide supraglacial lake evolution and dynamics: insights from the 2018 and 2019 melt seasons" https://doi.org/10.5281/zenodo.4813833 https Related Dataset #3 Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet - data https://doi.org/10.48550/arXiv.1909.07872 https Related Preprint #1 sktime: A Unified Interface for Machine Learning with Time Series https://doi.org/10.5065/D6RX99HX https Related Service #1 Cheyenne: SGI ICE XA Cluster Greenland ice sheet wide supraglacial lake evolution and dynamics: Insights from the 2018 and 2019 melt seasons 2025-02-01T00:00:00Z publication https://n2t.net/ark:/85065/d7571hb5 https://doi.org/10.1029/2024EA003793 Dunmire, D. author Subramanian, A. C. author Hossain, E. author Gani, M. O. author Banwell, A. F. author Younas, H. author Myers, Brendan author UCAR/NCAR - Library publisher Supraglacial lakes on the Greenland Ice Sheet (GrIS) can impact both the ice sheet surface mass balance and ice dynamics. Thus, understanding the evolution and dynamics of supraglacial lakes is important to provide improved parameterizations for ice sheet models to enable better projections of future GrIS changes. In this study, we utilize the growing inventory of optical and microwave satellite imagery to automatically determine the fate of Greenland&#8208;wide supraglacial lakes during 2018 and 2019; low and high melt seasons respectively. We develop a novel time series classification method to categorize lakes into four classes: (a) Refreezing, (b) rapidly draining, (c) slowly draining, and (d) buried. Our findings reveal significant interannual variability between the two melt seasons, with a notable increase in the proportion of draining lakes, and a particular dominance of slowly draining lakes, in 2019. We also find that as mean lake depth increases, so does the percentage of lakes that drain, indicating that lake depth may influence hydrofracture potential. We further observe rapidly draining lakes at higher elevations than the previously hypothesized upper&#8208;elevation hydrofracture limit (1,600&#160;m), and that non&#8208;draining lakes are generally deeper during the lower melt 2018 season. Our automatic classification approach and the resulting 2&#8208;year ice&#8208;sheet&#8208;wide data set provide new insights into GrIS supraglacial lake dynamics and evolution, offering a valuable resource for future research. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication <span style="font-family:Arial;font-size:10pt;font-style:normal;" data-sheets-root="1">Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</span> None eng geoscientificInformation