Articles | Volume 18, issue 4
https://doi.org/10.5194/essd-18-2635-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-2635-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Ice front positions for Greenland glaciers (2002–2021): a spatially extensive seasonal record and benchmark dataset for algorithm validation
Xi Lu
State Key Laboratory of Precision Geodesy, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430077, China
College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing 100049, China
now at: School of Geography and Sustainable Development, University of St Andrews, St Andrews, UK
State Key Laboratory of Precision Geodesy, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430077, China
College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing 100049, China
Daan Li
College of Urban and Environmental Sciences, Yancheng Teachers University, Yancheng 224002, China
State Key Laboratory of Precision Geodesy, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430077, China
College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing 100049, China
Andrew J. Sole
School of Geography and Planning, University of Sheffield, Sheffield, S10 2TN, UK
Stephen J. Livingstone
School of Geography and Planning, University of Sheffield, Sheffield, S10 2TN, UK
Related authors
Xiaoguang Pang, Liming Jiang, Yuxuan Wu, Xi Lu, Yi Liu, Xiaoen Li, and Tingting Yao
EGUsphere, https://doi.org/10.5194/egusphere-2025-5838, https://doi.org/10.5194/egusphere-2025-5838, 2026
Short summary
Short summary
Ice thickness models based on laminar flow theory often rely on conventional assumptions regarding basal sliding parameterization when studying alpine glaciers. This paper presents the Ice Thickness Model considering Sliding Law (ITMSL) model, which integrates a basal sliding law with laminar flow theory, with the objective of simulating basal sliding to enhance the accuracy of ice thickness inversion.
Xiaoguang Pang, Liming Jiang, Yuxuan Wu, Xi Lu, Yi Liu, Xiaoen Li, and Tingting Yao
EGUsphere, https://doi.org/10.5194/egusphere-2025-5838, https://doi.org/10.5194/egusphere-2025-5838, 2026
Short summary
Short summary
Ice thickness models based on laminar flow theory often rely on conventional assumptions regarding basal sliding parameterization when studying alpine glaciers. This paper presents the Ice Thickness Model considering Sliding Law (ITMSL) model, which integrates a basal sliding law with laminar flow theory, with the objective of simulating basal sliding to enhance the accuracy of ice thickness inversion.
Izabela Szuman, Jakub Z. Kalita, Christiaan R. Diemont, Stephen J. Livingstone, Chris D. Clark, and Martin Margold
The Cryosphere, 18, 2407–2428, https://doi.org/10.5194/tc-18-2407-2024, https://doi.org/10.5194/tc-18-2407-2024, 2024
Short summary
Short summary
A Baltic-wide glacial landform-based map is presented, filling in a geographical gap in the record that has been speculated about by palaeoglaciologists for over a century. Here we used newly available bathymetric data and provide landform evidence of corridors of fast ice flow that we interpret as ice streams. Where previous ice-sheet-scale investigations inferred a single ice source, our mapping identifies flow and ice margin geometries from both Swedish and Bothnian sources.
Tao Li, Yuanlin Hu, Bin Liu, Liming Jiang, Hansheng Wang, and Xiang Shen
The Cryosphere, 17, 5299–5316, https://doi.org/10.5194/tc-17-5299-2023, https://doi.org/10.5194/tc-17-5299-2023, 2023
Short summary
Short summary
Raw DEMs are often misaligned with each other due to georeferencing errors, and a co-registration process is required before DEM differencing. We present a comparative analysis of the two classical DEM co-registration and three residual correction algorithms. The experimental results show that rotation and scale biases should be considered in DEM co-registration. The new non-parametric regression technique can eliminate the complex systematic errors, which existed in the co-registration results.
Lauren D. Rawlins, David M. Rippin, Andrew J. Sole, Stephen J. Livingstone, and Kang Yang
The Cryosphere, 17, 4729–4750, https://doi.org/10.5194/tc-17-4729-2023, https://doi.org/10.5194/tc-17-4729-2023, 2023
Short summary
Short summary
We map and quantify surface rivers and lakes at Humboldt Glacier to examine seasonal evolution and provide new insights of network configuration and behaviour. A widespread supraglacial drainage network exists, expanding up the glacier as seasonal runoff increases. Large interannual variability affects the areal extent of this network, controlled by high- vs. low-melt years, with late summer network persistence likely preconditioning the surface for earlier drainage activity the following year.
Yubin Fan, Chang-Qing Ke, Xiaoyi Shen, Yao Xiao, Stephen J. Livingstone, and Andrew J. Sole
The Cryosphere, 17, 1775–1786, https://doi.org/10.5194/tc-17-1775-2023, https://doi.org/10.5194/tc-17-1775-2023, 2023
Short summary
Short summary
We used the new-generation ICESat-2 altimeter to detect and monitor active subglacial lakes in unprecedented spatiotemporal detail. We created a new inventory of 18 active subglacial lakes as well as their elevation and volume changes during 2019–2020, which provides an improved understanding of how the Greenland subglacial water system operates and how these lakes are fed by water from the ice surface.
Sophie Goliber, Taryn Black, Ginny Catania, James M. Lea, Helene Olsen, Daniel Cheng, Suzanne Bevan, Anders Bjørk, Charlie Bunce, Stephen Brough, J. Rachel Carr, Tom Cowton, Alex Gardner, Dominik Fahrner, Emily Hill, Ian Joughin, Niels J. Korsgaard, Adrian Luckman, Twila Moon, Tavi Murray, Andrew Sole, Michael Wood, and Enze Zhang
The Cryosphere, 16, 3215–3233, https://doi.org/10.5194/tc-16-3215-2022, https://doi.org/10.5194/tc-16-3215-2022, 2022
Short summary
Short summary
Terminus traces have been used to understand how Greenland's glaciers have changed over time; however, manual digitization is time-intensive, and a lack of coordination leads to duplication of efforts. We have compiled a dataset of over 39 000 terminus traces for 278 glaciers for scientific and machine learning applications. We also provide an overview of an updated version of the Google Earth Engine Digitization Tool (GEEDiT), which has been developed specifically for the Greenland Ice Sheet.
Benjamin Joseph Davison, Tom Cowton, Andrew Sole, Finlo Cottier, and Pete Nienow
The Cryosphere, 16, 1181–1196, https://doi.org/10.5194/tc-16-1181-2022, https://doi.org/10.5194/tc-16-1181-2022, 2022
Short summary
Short summary
The ocean is an important driver of Greenland glacier retreat. Icebergs influence ocean temperature in the vicinity of glaciers, which will affect glacier retreat rates, but the effect of icebergs on water temperature is poorly understood. In this study, we use a model to show that icebergs cause large changes to water properties next to Greenland's glaciers, which could influence ocean-driven glacier retreat around Greenland.
Peter A. Tuckett, Jeremy C. Ely, Andrew J. Sole, James M. Lea, Stephen J. Livingstone, Julie M. Jones, and J. Melchior van Wessem
The Cryosphere, 15, 5785–5804, https://doi.org/10.5194/tc-15-5785-2021, https://doi.org/10.5194/tc-15-5785-2021, 2021
Short summary
Short summary
Lakes form on the surface of the Antarctic Ice Sheet during the summer. These lakes can generate further melt, break up floating ice shelves and alter ice dynamics. Here, we describe a new automated method for mapping surface lakes and apply our technique to the Amery Ice Shelf between 2005 and 2020. Lake area is highly variable between years, driven by large-scale climate patterns. This technique will help us understand the role of Antarctic surface lakes in our warming world.
Izabela Szuman, Jakub Z. Kalita, Marek W. Ewertowski, Chris D. Clark, Stephen J. Livingstone, and Leszek Kasprzak
Earth Syst. Sci. Data, 13, 4635–4651, https://doi.org/10.5194/essd-13-4635-2021, https://doi.org/10.5194/essd-13-4635-2021, 2021
Short summary
Short summary
The Baltic Ice Stream Complex was the most prominent ice stream of the last Scandinavian Ice Sheet, controlling ice sheet drainage and collapse. Our mapping effort, based on a lidar DEM, resulted in a dataset containing 5461 landforms over an area of 65 000 km2, which allows for reconstruction of the last Scandinavian Ice Sheet extent and dynamics from the Middle Weichselian ice sheet advance, 50–30 ka, through the Last Glacial Maximum, 25–21 ka, and Young Baltic advances, 18–15 ka.
Cited articles
Andersen, J. K., Fausto, R. S., Hansen, K., Box, J. E., Andersen, S. B., Ahlstrøm, A. P., As, D. v., Citterio, M., Colgan, W. T., Karlsson, N. B., Kjeldsen, K. K., Korsgaard, N. J., Larsen, S. H., Mankoff, K. D., Pedersen, A. Ø., Shields, C. L., Solgaard, A. M., and Vandecrux, B.: Update of annual calving front lines for 47 marine terminating outlet glaciers in Greenland (1999–2018), Geol. Surv. Den. Greenl., https://doi.org/10.34194/GEUSB-201943-02-02, 2019.
Baumhoer, C. A., Dietz, A. J., Kneisel, C., and Kuenzer, C.: Automated Extraction of Antarctic Glacier and Ice Shelf Fronts from Sentinel-1 Imagery Using Deep Learning, Remote Sens.-Basel, 11, 2529, https://doi.org/10.3390/rs11212529, 2019.
Bevan, S. L., Luckman, A. J., and Murray, T.: Glacier dynamics over the last quarter of a century at Helheim, Kangerdlugssuaq and 14 other major Greenland outlet glaciers, The Cryosphere, 6, 923–937, https://doi.org/10.5194/tc-6-923-2012, 2012.
Bézu, C. and Bartholomaus, T. C.: Greenland Ice Sheet's Distinct Calving Styles Are Identified in Terminus Change Timeseries, Geophys. Res. Lett., 51, e2024GL110224, https://doi.org/10.1029/2024GL110224, 2024.
Bjørk, A. A., Kruse, L. M., and Michaelsen, P. B.: Brief communication: Getting Greenland's glaciers right – a new data set of all official Greenlandic glacier names, The Cryosphere, 9, 2215–2218, https://doi.org/10.5194/tc-9-2215-2015, 2015.
Black, T. and Joughin, I.: MEaSUREs Weekly to Monthly Greenland Outlet Glacier Terminus Positions from Sentinel-1 Mosaics (NSIDC-0781, Version 1), NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/DGBOSSIULSTD, 2022.
Black, T. E. and Joughin, I.: Weekly to monthly terminus variability of Greenland's marine-terminating outlet glaciers, The Cryosphere, 17, 1–13, https://doi.org/10.5194/tc-17-1-2023, 2023.
Brough, S., Carr, J. R., Ross, N., and Lea, J. M.: Exceptional Retreat of Kangerlussuaq Glacier, East Greenland, Between 2016 and 2018, Front. Earth Sci.-Switz., 7, https://doi.org/10.3389/feart.2019.00123, 2019.
Brough, S., Carr, J. R., Ross, N., and Lea, J. M.: Ocean-Forcing and Glacier-Specific Factors Drive Differing Glacier Response Across the 69° N Boundary, East Greenland, J. Geophys. Res.-Earth, 128, e2022JF006857, https://doi.org/10.1029/2022JF006857, 2023.
Carr, J. R., Vieli, A., and Stokes, C.: Influence of sea ice decline, atmospheric warming, and glacier width on marine-terminating outlet glacier behavior in northwest Greenland at seasonal to interannual timescales, J. Geophys. Res.-Earth, 118, 1210–1226, https://doi.org/10.1002/jgrf.20088, 2013.
Cassotto, R., Fahnestock, M., Amundson, J. M., Truffer, M., and Joughin, I.: Seasonal and interannual variations in ice melange and its impact on terminus stability, Jakobshavn Isbræ, Greenland, J. Glaciol., 61, 76–88, https://doi.org/10.3189/2015JoG13J235, 2017.
Catania, G. A., Stearns, L. A., Sutherland, D. A., Fried, M. J., Bartholomaus, T. C., Morlighem, M., Shroyer, E., and Nash, J.: Geometric Controls on Tidewater Glacier Retreat in Central Western Greenland, J. Geophys. Res.-Earth, 123, 2024–2038, https://doi.org/10.1029/2017JF004499, 2018.
Catania, G. A., Stearns, L. A., Moon, T. A., Enderlin, E. M., and Jackson, R. H.: Future Evolution of Greenland's Marine-Terminating Outlet Glaciers, J. Geophys. Res.-Earth, 125, e2018JF004873, https://doi.org/10.1029/2018JF004873, 2020.
Cheng, D. L., Hayes, W., and Larour, E.: CALFIN Subseasonal Greenland Glacial Terminus Positions (NSIDC-0764, Version 1), NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/7FILV218JZA2, 2021a.
Cheng, D., Hayes, W., Larour, E., Mohajerani, Y., Wood, M., Velicogna, I., and Rignot, E.: Calving Front Machine (CALFIN): glacial termini dataset and automated deep learning extraction method for Greenland, 1972–2019, The Cryosphere, 15, 1663–1675, https://doi.org/10.5194/tc-15-1663-2021, 2021b.
Choi, Y., Morlighem, M., Rignot, E., and Wood, M.: Ice dynamics will remain a primary driver of Greenland ice sheet mass loss over the next century, Commun. Earth Environ., 2, 26, https://doi.org/10.1038/s43247-021-00092-z, 2021.
Fahrner, D., Lea, J. M., Brough, S., Mair, D. W. F., and Abermann, J.: Linear response of the Greenland ice sheet's tidewater glacier terminus positions to climate, J. Glaciol., 67, 193–203, https://doi.org/10.1017/jog.2021.13, 2021.
Fahrner, D., Slater, D. A., Kc, A., Cenedese, C., Sutherland, D. A., Enderlin, E., de Jong, M. F., Kjeldsen, K. K., Wood, M., Nienow, P., Nowicki, S., and Wagner, T. J. W.: A Frontal Ablation Dataset for 49 Tidewater Glaciers in Greenland, Sci. Data, 12, 601, https://doi.org/10.1038/s41597-025-04948-3, 2025.
Fitzpatrick, A. A. W., Hubbard, A., Joughin, I., Quincey, D. J., As, D. V., Mikkelsen, A. P. B., Doyle, S. H., Hasholt, B., and Jones, G. A.: Ice flow dynamics and surface meltwater flux at a land-terminating sector of the Greenland ice sheet, J. Glaciol., 59, 687–696, https://doi.org/10.3189/2013JoG12J143, 2013.
Frederikse, T., Landerer, F., Caron, L., Adhikari, S., Parkes, D., Humphrey, V. W., Dangendorf, S., Hogarth, P., Zanna, L., Cheng, L., and Wu, Y.-H.: The causes of sea-level rise since 1900, Nature, 584, 393–397, https://doi.org/10.1038/s41586-020-2591-3, 2020.
Fried, M. J., Catania, G. A., Stearns, L. A., Sutherland, D. A., Bartholomaus, T. C., Shroyer, E., and Nash, J.: Reconciling Drivers of Seasonal Terminus Advance and Retreat at 13 Central West Greenland Tidewater Glaciers, J. Geophys. Res.-Earth, 123, 1590–1607, https://doi.org/10.1029/2018jf004628, 2018.
Fürst, J. J., Goelzer, H., and Huybrechts, P.: Ice-dynamic projections of the Greenland ice sheet in response to atmospheric and oceanic warming, The Cryosphere, 9, 1039–1062, https://doi.org/10.5194/tc-9-1039-2015, 2015.
Gardner, A. S., Fahnestock, M. A., and Scambos, T. A.: MEaSUREs ITS_LIVE Landsat Image-Pair Glacier and Ice Sheet Surface Velocities (1), Jet Propulsion Laboratory, NASA [data set], https://doi.org/10.5067/IMR9D3PEI28U, 2019.
Goliber, S. and Black, T.: TermPicks: A century of Greenland glacier terminus data for use inmachine learning applications (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.6557981, 2021.
Goliber, S., Black, T., Catania, G., Lea, J. M., Olsen, H., Cheng, D., Bevan, S., Bjørk, A., Bunce, C., Brough, S., Carr, J. R., Cowton, T., Gardner, A., Fahrner, D., Hill, E., Joughin, I., Korsgaard, N. J., Luckman, A., Moon, T., Murray, T., Sole, A., Wood, M., and Zhang, E.: TermPicks: a century of Greenland glacier terminus data for use in scientific and machine learning applications, The Cryosphere, 16, 3215–3233, https://doi.org/10.5194/tc-16-3215-2022, 2022.
Greene, C. A., Gardner, A. S., Wood, M., and Cuzzone, J. K.: Ubiquitous acceleration in Greenland Ice Sheet calving from 1985 to 2022, Nature, 625, 523–528, https://doi.org/10.1038/s41586-023-06863-2, 2024.
Grimes, M., Carrivick, J. L., and Smith, M. W.: Spatial heterogeneity, terminus environment effects and acceleration in mass loss of glaciers and ice caps across Greenland, Global Planet. Change, 239, 104505, https://doi.org/10.1016/j.gloplacha.2024.104505, 2024.
Hall, D. K., Riggs, G. A., Salomonson, V. V., DiGirolamo, N. E., and Bayr, K. J.: MODIS snow-cover products, Remote Sens. Environ., 83, 181–194, https://doi.org/10.1016/S0034-4257(02)00095-0, 2002.
Herrmann, O., Gourmelon, N., Seehaus, T., Maier, A., Fürst, J. J., Braun, M. H., and Christlein, V.: Out-of-the-box calving-front detection method using deep learning, The Cryosphere, 17, 4957–4977, https://doi.org/10.5194/tc-17-4957-2023, 2023.
Holt, E., Nienow, P., and Medina-Lopez, E.: Terminus thinning drives recent acceleration of a Greenlandic lake-terminating outlet glacier, J. Glaciol., 70, https://doi.org/10.1017/jog.2024.30, 2024.
Howat, I. M. and Eddy, A.: Multi-decadal retreat of Greenland's marine-terminating glaciers, J. Glaciol., 57, 389–396, https://doi.org/10.3189/002214311796905631, 2017.
Joughin, I.: MEaSUREs Greenland Image Mosaics from Sentinel-1A and -1B (4), NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/WXQ366CP8YDE, 2021.
KC, A., Enderlin, E. M., Fahrner, D., Moon, T., and Carroll, D.: Seasonality in terminus ablation rates for the glaciers in Greenland (Kalaallit Nunaat), The Cryosphere, 19, 3089–3106, https://doi.org/10.5194/tc-19-3089-2025, 2025.
Kehrl, L. M., Joughin, I., Shean, D. E., Floricioiu, D., and Krieger, L.: Seasonal and interannual variabilities in terminus position, glacier velocity, and surface elevation at Helheim and Kangerlussuaq Glaciers from 2008 to 2016, J. Geophys. Res.-Earth, 122, 1635–1652, https://doi.org/10.1002/2016jf004133, 2017.
Lea, J. M.: The Google Earth Engine Digitisation Tool (GEEDiT) and the Margin change Quantification Tool (MaQiT) – simple tools for the rapid mapping and quantification of changing Earth surface margins, Earth Surf. Dynam., 6, 551–561, https://doi.org/10.5194/esurf-6-551-2018, 2018.
Loebel, E., Scheinert, M., Horwath, M., Humbert, A., Sohn, J., Heidler, K., Liebezeit, C., and Zhu, X. X.: Calving front monitoring at a subseasonal resolution: a deep learning application for Greenland glaciers, The Cryosphere, 18, 3315–3332, https://doi.org/10.5194/tc-18-3315-2024, 2024.
Lu, X., Sole, A., Livingstone, S. J., Cheng, G., Jiang, L., Chudley, T., Noël, B., and Li, D.: Ice Thickness-Induced Variations in Effective Pressure and Basal Conditions Influence Seasonal and Multi-Annual Ice Velocity at Sermeq Kujalleq (Jakobshavn Isbræ), Geophys. Res. Lett., 52, e2024GL111092, https://doi.org/10.1029/2024GL111092, 2025.
Mohajerani, Y., Wood, M., Velicogna, I., and Rignot, E.: Detection of Glacier Calving Margins with Convolutional Neural Networks: A Case Study, Remote Sens.-Basel, 11, 74, https://doi.org/10.3390/rs11010074, 2019.
Moon, T. and Joughin, I.: Changes in ice front position on Greenland's outlet glaciers from 1992 to 2007, J. Geophys. Res., 113, https://doi.org/10.1029/2007jf000927, 2008.
Moon, T., Joughin, I., and Smith, B.: Seasonal to multiyear variability of glacier surface velocity, terminus position, and sea ice/ice mélange in northwest Greenland, J. Geophys. Res.-Earth, 120, 818–833, https://doi.org/10.1002/2015jf003494, 2015.
Mouginot, J., Rignot, E., Bjork, A. A., van den Broeke, M., Millan, R., Morlighem, M., Noel, B., Scheuchl, B., and Wood, M.: Forty-six years of Greenland Ice Sheet mass balance from 1972 to 2018, P. Natl. Acad. Sci. USA, 116, 9239–9244, https://doi.org/10.1073/pnas.1904242116, 2019.
Murray, T., Selmes, N., James, T. D., Edwards, S., Martin, I., O'Farrell, T., Aspey, R., Rutt, I., Nettles, M., and Bauge, T.: Dynamics of glacier calving at the ungrounded margin of Helheim Glacier, southeast Greenland, J. Geophys. Res.-Earth, 120, 964–982, https://doi.org/10.1002/2015JF003531, 2015a.
Murray, T., Scharrer, K., Selmes, N., Booth, A. D., James, T. D., Bevan, S. L., Bradley, J., Cook, S., Llana, L. C., Drocourt, Y., Dyke, L. F. V., Goldsack, A., Hughes, A. L. H., Luckman, A. J., and McGovern, J.: Extensive Retreat of Greenland Tidewater Glaciers, 2000–2010, Arct. Antarct. Alp. Res., https://doi.org/10.1657/AAAR0014-049, 2015b.
Nick, F. M., Vieli, A., Andersen, M. L., Joughin, I., Payne, A., Edwards, T. L., Pattyn, F., and van de Wal, R. S. W.: Future sea-level rise from Greenland's main outlet glaciers in a warming climate, Nature, 497, 235–238, https://doi.org/10.1038/nature12068, 2013.
Otosaka, I. N., Shepherd, A., Ivins, E. R., Schlegel, N.-J., Amory, C., van den Broeke, M. R., Horwath, M., Joughin, I., King, M. D., Krinner, G., Nowicki, S., Payne, A. J., Rignot, E., Scambos, T., Simon, K. M., Smith, B. E., Sørensen, L. S., Velicogna, I., Whitehouse, P. L., A, G., Agosta, C., Ahlstrøm, A. P., Blazquez, A., Colgan, W., Engdahl, M. E., Fettweis, X., Forsberg, R., Gallée, H., Gardner, A., Gilbert, L., Gourmelen, N., Groh, A., Gunter, B. C., Harig, C., Helm, V., Khan, S. A., Kittel, C., Konrad, H., Langen, P. L., Lecavalier, B. S., Liang, C.-C., Loomis, B. D., McMillan, M., Melini, D., Mernild, S. H., Mottram, R., Mouginot, J., Nilsson, J., Noël, B., Pattle, M. E., Peltier, W. R., Pie, N., Roca, M., Sasgen, I., Save, H. V., Seo, K.-W., Scheuchl, B., Schrama, E. J. O., Schröder, L., Simonsen, S. B., Slater, T., Spada, G., Sutterley, T. C., Vishwakarma, B. D., van Wessem, J. M., Wiese, D., van der Wal, W., and Wouters, B.: Mass balance of the Greenland and Antarctic ice sheets from 1992 to 2020, Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, 2023.
Porter, C., Howat, I., Noh, M.-J., Husby, E., Khuvis, S., Danish, E., Tomko, K., Gardiner, J., Negrete, A., Yadav, B., Klassen, J., Kelleher, C., Cloutier, M., Bakker, J., Enos, J., Arnold, G., Bauer, G., and Morin, P.: ArcticDEM – Strips, Version 4.1, Harvard Dataverse [data set], https://doi.org/10.7910/DVN/C98DVS, 2022.
Rignot, E. and Kanagaratnam, P.: Changes in the Velocity Structure of the Greenland Ice Sheet, Science, 311, 986–990, https://doi.org/10.1126/science.1121381, 2006.
Rignot, E. and Mouginot, J.: Ice flow in Greenland for the International Polar Year 2008–2009, Geophys. Res. Lett., 39, https://doi.org/10.1029/2012GL051634, 2012.
Sakakibara, D. and Sugiyama, S.: Seasonal ice-speed variations in 10 marine-terminating outlet glaciers along the coast of Prudhoe Land, northwestern Greenland, J. Glaciol., 66, 25–34, https://doi.org/10.1017/jog.2019.81, 2019.
Sundal, A. V., Shepherd, A., Nienow, P., Hanna, E., Palmer, S., and Huybrechts, P.: Melt-induced speed-up of Greenland ice sheet offset by efficient subglacial drainage, Nature, 469, 521–524, https://doi.org/10.1038/nature09740, 2011.
Tedstone, A. J., Nienow, P. W., Gourmelen, N., Dehecq, A., Goldberg, D., and Hanna, E.: Decadal slowdown of a land-terminating sector of the Greenland Ice Sheet despite warming, Nature, 526, 692–695, https://doi.org/10.1038/nature15722, 2015.
Wood, M., Rignot, E., Fenty, I., An, L., Bjork, A., van den Broeke, M., Cai, C., Kane, E., Menemenlis, D., Millan, R., Morlighem, M., Mouginot, J., Noel, B., Scheuchl, B., Velicogna, I., Willis, J. K., and Zhang, H.: Ocean forcing drives glacier retreat in Greenland, Sci. Adv., 7, https://doi.org/10.1126/sciadv.aba7282, 2021.
Xi, L., Liming, J., Daan, L., Yi, L., Andrew, S., and Stephen J., L.: Ice front positions for Greenland glaciers (2002–2021): a spatially extensive seasonal record and benchmark dataset for algorithm validation (5.0), Zenodo [data set], https://doi.org/10.5281/zenodo.19181770, 2026.
Zhang, E.: AutoTerm: A “big data” repository of glacier termini delineated using deep learning (Version 4), Zenodo [data set], https://doi.org/10.5281/zenodo.7782039, 2022.
Zhang, E., Catania, G., and Trugman, D. T.: AutoTerm: an automated pipeline for glacier terminus extraction using machine learning and a “big data” repository of Greenland glacier termini, The Cryosphere, 17, 3485–3503, https://doi.org/10.5194/tc-17-3485-2023, 2023.
Short summary
Greenland Terminus Position Dataset (GrTPD) is a new manually delineated dataset of glacier terminus positions for the Greenland Ice Sheet, providing spatially extensive and seasonally targeted coverage across marine-, land-, and lake-terminating glaciers. The dataset includes 19 171 terminus delineations for 465 glaciers spanning 2002–2021, derived from multi-source optical and SAR satellite imagery using standardized workflows.
Greenland Terminus Position Dataset (GrTPD) is a new manually delineated dataset of glacier...
Altmetrics
Final-revised paper
Preprint