Articles | Volume 14, issue 11
https://doi.org/10.5194/tc-14-3747-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-14-3747-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Possible impacts of a 1000 km long hypothetical subglacial river valley towards Petermann Glacier in northern Greenland
Christopher Chambers
CORRESPONDING AUTHOR
Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan
Ralf Greve
Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan
Arctic Research Center, Hokkaido University, Sapporo, Japan
Bas Altena
Department of Geosciences, University of Oslo, Oslo, Norway
Institute for Marine and Atmospheric research Utrecht, Utrecht University, Utrecht, the Netherlands
Pierre-Marie Lefeuvre
Department of Geosciences, University of Oslo, Oslo, Norway
Norwegian Polar Institute, Tromsø, 9296, Norway
Related authors
No articles found.
Johanna Beckmann, Ronja Reese, Felicity S. McCormack, Sue Cook, Lawrence Bird, Dawid Gwyther, Daniel Richards, Matthias Scheiter, Yu Wang, Hélène Seroussi, Ayako Abe‐Ouchi, Torsten Albrecht, Jorge Alvarez‐Solas, Xylar S. Asay‐Davis, Jean‐Baptiste Barre, Constantijn J. Berends, Jorge Bernales, Javier Blasco, Justine Caillet, David M. Chandler, Violaine Coulon, Richard Cullather, Christophe Dumas, Benjamin K. Galton‐Fenzi, Julius Garbe, Fabien Gillet‐Chaulet, Rupert Gladstone, Heiko Goelzer, Nicholas R. Golledge, Ralf Greve, G. Hilmar Gudmundsson, Holly Kyeore Han, Trevor R. Hillebrand, Matthew J. Hoffman, Philippe Huybrechts, Nicolas C. Jourdain, Ann Kristin Klose, Petra M. Langebroek, Gunter R. Leguy, William H. Lipscomb, Daniel P. Lowry, Pierre Mathiot, Marisa Montoya, Mathieu Morlighem, Sophie Nowicki, Frank Pattyn, Antony J. Payne, Tyler Pelle, Aurélien Quiquet, Alexander Robinson, Leopekka Saraste, Erika G. Simon, Sainan Sun, Jake P. Twarog, Luke D. Trusel, Benoit Urruty, Jonas Van Breedam, Roderik S. W. van de Wal, Chen Zhao, and Thomas Zwinger
EGUsphere, https://doi.org/10.5194/egusphere-2025-4069, https://doi.org/10.5194/egusphere-2025-4069, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Antarctica holds enough ice to raise sea levels by many meters, but its future is uncertain. Warm ocean water melts ice shelves from below, letting inland ice flow faster into the sea. By 2300, Antarctica could add 0.6–4.4 m to sea levels. Our study identifies two key factors—how strongly shelves melt and how the ice responds. These explain much of the range, and refining them in models may improve future predictions.
Marius Schaefer, Ilaria Tabone, Ralf Greve, Johannes Fürst, and Matthias Braun
EGUsphere, https://doi.org/10.5194/egusphere-2025-4167, https://doi.org/10.5194/egusphere-2025-4167, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
The Northern Patagonian Icefield is the second largest ice mass of South America, located at moderate latitudes. Using an ice-flow model which uses available atmosphere data as input and explicitly models iceberg discharge, we assess its evolution. With present climate, it will lose about 25 % of its mass during this century. Climate change strongly accelerates losses and under Paris Agreement compliance it is 36 % until 2200 and up to 68 % under a business-as-usual fossil fuel scenario.
Matteo Willeit, Reinhard Calov, Stefanie Talento, Ralf Greve, Jorjo Bernales, Volker Klemann, Meike Bagge, and Andrey Ganopolski
Clim. Past, 20, 597–623, https://doi.org/10.5194/cp-20-597-2024, https://doi.org/10.5194/cp-20-597-2024, 2024
Short summary
Short summary
We present transient simulations of the last glacial inception with the coupled climate–ice sheet model CLIMBER-X showing a rapid increase in Northern Hemisphere ice sheet area and a sea level drop by ~ 35 m, with the vegetation feedback playing a key role. Overall, our simulations confirm and refine previous results showing that climate-vegetation–cryosphere–carbon cycle feedbacks play a fundamental role in the transition from interglacial to glacial states.
Hélène Seroussi, Vincent Verjans, Sophie Nowicki, Antony J. Payne, Heiko Goelzer, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Torsten Albrecht, Xylar Asay-Davis, Alice Barthel, Reinhard Calov, Richard Cullather, Christophe Dumas, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Nicolas C. Jourdain, Thomas Kleiner, Eric Larour, Gunter R. Leguy, Daniel P. Lowry, Chistopher M. Little, Mathieu Morlighem, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Ronja Reese, Nicole-Jeanne Schlegel, Andrew Shepherd, Erika Simon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Luke D. Trusel, Jonas Van Breedam, Peter Van Katwyk, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 17, 5197–5217, https://doi.org/10.5194/tc-17-5197-2023, https://doi.org/10.5194/tc-17-5197-2023, 2023
Short summary
Short summary
Mass loss from Antarctica is a key contributor to sea level rise over the 21st century, and the associated uncertainty dominates sea level projections. We highlight here the Antarctic glaciers showing the largest changes and quantify the main sources of uncertainty in their future evolution using an ensemble of ice flow models. We show that on top of Pine Island and Thwaites glaciers, Totten and Moscow University glaciers show rapid changes and a strong sensitivity to warmer ocean conditions.
Bas Altena, Andreas Kääb, and Bert Wouters
The Cryosphere, 16, 2285–2300, https://doi.org/10.5194/tc-16-2285-2022, https://doi.org/10.5194/tc-16-2285-2022, 2022
Short summary
Short summary
Repeat overflights of satellites are used to estimate surface displacements. However, such products lack a simple error description for individual measurements, but variation in precision occurs, since the calculation is based on the similarity of texture. Fortunately, variation in precision manifests itself in the correlation peak, which is used for the displacement calculation. This spread is used to make a connection to measurement precision, which can be of great use for model inversion.
Paul Willem Leclercq, Andreas Kääb, and Bas Altena
The Cryosphere, 15, 4901–4907, https://doi.org/10.5194/tc-15-4901-2021, https://doi.org/10.5194/tc-15-4901-2021, 2021
Short summary
Short summary
In this study we present a novel method to detect glacier surge activity. Surges are relevant as they disturb the link between glacier change and climate, and studying surges can also increase understanding of glacier flow. We use variations in Sentinel-1 radar backscatter strength, calculated with the use of Google Earth Engine, to detect surge activity. In our case study for the year 2018–2019 we find 69 cases of surging glaciers globally. Many of these were not previously known to be surging.
Matthias Scheiter, Marius Schaefer, Eduardo Flández, Deniz Bozkurt, and Ralf Greve
The Cryosphere, 15, 3637–3654, https://doi.org/10.5194/tc-15-3637-2021, https://doi.org/10.5194/tc-15-3637-2021, 2021
Short summary
Short summary
We simulate the current state and future evolution of the Mocho-Choshuenco ice cap in southern Chile (40°S, 72°W) with the ice-sheet model SICOPOLIS. Under different global warming scenarios, we project ice mass losses between 56 % and 97 % by the end of the 21st century. We quantify the uncertainties based on an ensemble of climate models and on the temperature dependence of the equilibrium line altitude. Our results suggest a considerable deglaciation in southern Chile in the next 80 years.
Cited articles
Barnes, R., Lehman, C., and Mulla, D.: Priority-flood: An optimal
depression-filling and watershed-labeling algorithm for digital elevation
models, Comput. Geosci., 62, 117–127, https://doi.org/10.1016/j.cageo.2013.04.024,
2014. a
Bernales, J., Rogozhina, I., Greve, R., and Thomas, M.: Comparison of hybrid schemes for the combination of shallow approximations in numerical simulations of the Antarctic Ice Sheet, The Cryosphere, 11, 247–265, https://doi.org/10.5194/tc-11-247-2017, 2017. a
Calov, R., Beyer, S., Greve, R., Beckmann, J., Willeit, M., Kleiner, T., Rückamp, M., Humbert, A., and Ganopolski, A.: Simulation of the future sea level contribution of Greenland with a new glacial system model, The Cryosphere, 12, 3097–3121, https://doi.org/10.5194/tc-12-3097-2018, 2018. a, b
Clayton, L., Attig, J. W., and Mickelson, D. M.: Tunnel channels formed in
Wisconsin during the last glaciation, in: Glacial Processes Past and
Present, Geological Society of America, Boulder, Colorado, USA, https://doi.org/10.1130/0-8137-2337-X.69,
1999. a
Cuffey, K. M. and Paterson, W. S. B.: The Physics of Glaciers, Elsevier,
Amsterdam, the Netherlands etc., 4th edn., ISBN 9780123694614, 2010. a
Donoser, M. and Bischof, H.: Efficient Maximally Stable Extremal Region
(MSER) Tracking, in: 2006 IEEE Computer Society Conference on Computer Vision
and Pattern Recognition (CVPR'06), vol. 1, 553–560,
https://doi.org/10.1109/CVPR.2006.107, 2006. a
Ekholm, S., Keller, K., Bamber, J. L., and Gogineni, S. P.: Unusual surface
morphology from digital elevation models of the Greenland ice sheet,
Geophys. Res. Lett., 25, 3623–3626, https://doi.org/10.1029/98GL02589, 1998. a, b, c, d
Goelzer, H., Nowicki, S., Payne, A., Larour, E., Seroussi, H., Lipscomb, W. H., Gregory, J., Abe-Ouchi, A., Shepherd, A., Simon, E., Agosta, C., Alexander, P., Aschwanden, A., Barthel, A., Calov, R., Chambers, C., Choi, Y., Cuzzone, J., Dumas, C., Edwards, T., Felikson, D., Fettweis, X., Golledge, N. R., Greve, R., Humbert, A., Huybrechts, P., Le clec'h, S., Lee, V., Leguy, G., Little, C., Lowry, D. P., Morlighem, M., Nias, I., Quiquet, A., Rückamp, M., Schlegel, N.-J., Slater, D. A., Smith, R. S., Straneo, F., Tarasov, L., van de Wal, R., and van den Broeke, M.: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6, The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, 2020. a, b
Greve, R.: Thermomechanisches Verhalten polythermer Eisschilde – Theorie,
Analytik, Numerik, Doctoral thesis, Department of Mechanics, Darmstadt
University of Technology, Germany, https://doi.org/10.5281/zenodo.3815324, 1995. a
Greve, R.: Application of a polythermal three-dimensional ice sheet model to
the Greenland ice sheet: Response to steady-state and transient climate
scenarios, J. Climate, 10, 901–918,
https://doi.org/10.1175/1520-0442(1997)010<0901:AOAPTD>2.0.CO;2, 1997. a
Greve, R.: Geothermal heat flux distribution for the Greenland ice sheet,
derived by combining a global representation and information from deep ice
cores, Polar Data J., 3, 22–36, https://doi.org/10.20575/00000006, 2019. a, b, c, d
Greve, R. and Blatter, H.: Comparison of thermodynamics solvers in the
polythermal ice sheet model SICOPOLIS, Polar Sci., 10, 11–23,
https://doi.org/10.1016/j.polar.2015.12.004, 2016. a
Greve, R. and the SICOPOLIS Developer Team: SICOPOLIS v5.1, Zenodo,
https://doi.org/10.5281/zenodo.3727511, 2019. a, b
Greve, R., Chambers, C., and Calov, R.: ISMIP6 future projections for the
Greenland ice sheet with the model SICOPOLIS, Technical report, Zenodo,
https://doi.org/10.5281/zenodo.3971251, 2020. a
Kleiner, T. and Humbert, A.: Numerical simulations of major ice streams in
western Dronning Maud Land, Antarctica, under wet and dry basal
conditions, J. Glaciol., 60, 215–232, https://doi.org/10.3189/2014JoG13J006, 2014. a
Klokočník, J., Kostelecký, J., Cílek, V., Bezděk, A., and Pešek, I.:
Gravito-topographic signal of the Lake Vostok area, Antarctica, with the most
recent data, Polar Sci., 17, 59–74,
https://doi.org/10.1016/j.polar.2018.05.002, 2018. a
Kobashi, T., Kawamura, K., Severinghaus, J. P., Barnola, J.-M., Nakaegawa, T.,
Vinther, B. M., Johnsen, S. J., and Box, J. E.: High variability of
Greenland surface temperature over the past 4000 years estimated from
trapped air in an ice core, Geophys. Res. Lett., 38, L21501,
https://doi.org/10.1029/2011GL049444, 2011. a
Le Brocq, A. M., Payne, A. J., and Siegert, M. J.: West Antarctic balance
calculations: impact of flux-routing algorithm, smoothing algorithm and
topography, Comput. Geosci., 32, 1780–1795,
https://doi.org/10.1016/j.cageo.2006.05.003, 2006. a
Legleiter, C. J. and Kyriakidis, P. C.: Spatial prediction of river channel
topography by kriging, Earth Surf. Process. Landf., 33, 841–867,
https://doi.org/10.1002/esp.1579, 2008. a
Le Meur, E. and Huybrechts, P.: A comparison of different ways of dealing with
isostasy: examples from modelling the Antarctic ice sheet during the last
glacial cycle, Ann. Glaciol., 23, 309–317, 1996. a
MacGregor, J. A., Fahnestock, M. A., Catania, G. A., Aschwanden, A., Clow,
G. D., Colgan, W. T., Gogineni, S. P., Morlighem, M., Nowicki, S. M. J.,
Paden, J. D., Price, S. F., and Seroussi, H.: A synthesis of the basal
thermal state of the Greenland Ice Sheet, J. Geophys. Res.-Earth Surf.,
121, 1328–1350, https://doi.org/10.1002/2015JF003803, 2016. a
Merwade, V. M., Maidment, D. R., and Goff, J. A.: Anisotropic considerations
while interpolating river channel bathymetry, J. Hydrol., 331, 731–741,
https://doi.org/10.1016/j.jhydrol.2006.06.018, 2006. a
Mooers, H. D.: On the formation of the tunnel valleys of the Superior lobe,
central Minnesota, Quaternary Res., 32, 24–35, 1989. a
Morlighem, M., Williams, C. N., Rignot, E., An, L., Arndt, J. E., Bamber,
J. L., Catania, G., Chauché, N., Dowdeswell, J. A., Dorschel, B., Fenty,
I., Hogan, K., Howat, I., Hubbard, A., Jakobsson, M., Jordan, T. M.,
Kjeldsen, K. K., Millan, R., Mayer, L., Mouginot, J., Noël, B. P. Y.,
O'Cofaigh, C., Palmer, S., Rysgaard, S., Seroussi, H., Siegert, M. J.,
Slabon, P., Straneo, F., van den Broeke, M. R., Weinrebe, W., Wood, M., and
Zinglersen, K. B.: BedMachine v3: Complete bed topography and ocean
bathymetry mapping of Greenland from multibeam echo sounding combined with
mass conservation, Geophys. Res. Lett., 44, 11051–11061,
https://doi.org/10.1002/2017GL074954, 2017. a, b, c, d, e, f, g, h
Nielsen, L. T., Aðalgeirsdóttir, G., Gkinis, V., Nuterman, R., and
Hvidberg, C. S.: The effect of a Holocene climatic optimum on the evolution
of the Greenland ice sheet during the last 10 kyr, J. Glaciol., 64,
477–488, https://doi.org/10.1017/jog.2018.40, 2018. a
Nye, J. F.: Water at the bed of a glacier, in: Symposium on the Hydrology of
Glaciers, IAHS Publication No. 95, pp. 189–194, International Association of
Hydrological Sciences, 1973. a
Popov, S. V. and Masolov, V. N.: Forty-seven new subglacial lakes in the
0–110∘ E sector of East Antarctica, J. Glaciol., 53, 289–297,
https://doi.org/10.3189/172756507782202856, 2007. a
Remy, F. and Legresy, B.: Subglacial hydrological networks in Antarctica and
their impact on ice flow, Ann. Glaciol., 39, 67–72,
https://doi.org/10.3189/172756404781814401, 2004. a
Röthlisberger, H.: Water pressure in subglacial channels, J. Glaciol., 11,
177–203, https://doi.org/10.3189/S0022143000022188, 1972. a
Rückamp, M., Greve, R., and Humbert, A.: Comparative simulations of the
evolution of the Greenland ice sheet under simplified Paris Agreement
scenarios with the models SICOPOLIS and ISSM, Polar Sci., 21, 14–25,
https://doi.org/10.1016/j.polar.2018.12.003, 2019. a
Shreve, R. L.: Movement of water in glaciers, J. Glaciol., 11, 205–214,
https://doi.org/10.3189/S002214300002219X, 1972. a, b
van der Veen, C. J., Leftwich, T., von Frese, R., Csatho, B. M., and Li, J.:
Subglacial topography and geothermal heat flux: Potential interactions with
drainage of the Greenland ice sheet, Geophys. Res. Lett., 34, L12501,
https://doi.org/10.1029/2007GL030046, 2007. a
Zwally, H. J., Giovinetto, M. B., Beckley, M. A., and Saba, J. L.: Antarctic
and Greenland drainage systems, GSFC Cryospheric Sciences Laboratory,
Greenbelt, MD, USA, available at:
http://icesat4.gsfc.nasa.gov/cryo_data/ant_grn_drainage_systems.php (last access: 19 October 2020),
2012. a
Short summary
The topography of the rock below the Greenland ice sheet is not well known. One long valley appears as a line of dips because of incomplete data. So we use ice model simulations that unblock this valley, and these create a watercourse that may represent a form of river over 1000 km long under the ice. When we melt ice at the bottom of the ice sheet only in the deep interior, water can flow down the valley only when the valley is unblocked. It may have developed while an ice sheet was present.
The topography of the rock below the Greenland ice sheet is not well known. One long valley...