Articles | Volume 20, issue 2
https://doi.org/10.5194/tc-20-835-2026
© 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/tc-20-835-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Feb 2026
Research article |
| 02 Feb 2026
| 02 Feb 2026
Quantifying temperature-sliding inconsistency in thermomechanical coupling: a comparative analysis of geothermal heat flux datasets at Totten Glacier
Junshun Wang
State Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Liyun Zhao
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Michael Wolovick
Center for Industrial Mathematics (ZeTeM), University of Bremen, Bremen, Germany
Glaciology Section, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
John C. Moore
CORRESPONDING AUTHOR
Arctic Centre, University of Lapland, Rovaniemi, Finland
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Cited articles
Albrecht, T., Winkelmann, R., and Levermann, A.: Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM) – Part 1: Boundary conditions and climatic forcing, The Cryosphere, 14, 599–632, https://doi.org/10.5194/tc-14-599-2020, 2020.
An, M., Wiens, D. A., Zhao, Y., Feng, M., Nyblade, A., Kanao, M., Li, Y., Maggi, A., and Lévêque, J.: Temperature, lithosphere-asthenosphere boundary, and heat flux beneath the Antarctic Plate inferred from seismic velocities, J. Geophys. Res.-Sol. Ea., 120, 8720–8742, https://doi.org/10.1002/2015JB011917, 2015.
Artemieva, I. M.: Antarctica ice sheet basal melting enhanced by high mantle heat, Earth-Sci. Rev., 226, 103954, https://doi.org/10.1016/j.earscirev.2022.103954, 2022.
Azuma, N. and Higashi, A.: Formation Processes of Ice Fabric Pattern in Ice Sheets, Ann. Glaciol., 6, 130–134, https://doi.org/10.3189/1985AoG6-1-130-134, 1985.
Benn, D. I., Luckman, A., Åström, J. A., Crawford, A. J., Cornford, S. L., Bevan, S. L., Zwinger, T., Gladstone, R., Alley, K., Pettit, E., and Bassis, J.: Rapid fragmentation of Thwaites Eastern Ice Shelf, The Cryosphere, 16, 2545–2564, https://doi.org/10.5194/tc-16-2545-2022, 2022.
Brondex, J., Gagliardini, O., Gillet-Chaulet, F., and Durand, G.: Sensitivity of grounding line dynamics to the choice of the friction law, J. Glaciol., 63, 854–866, https://doi.org/10.1017/jog.2017.51, 2017.
Brondex, J., Gillet-Chaulet, F., and Gagliardini, O.: Sensitivity of centennial mass loss projections of the Amundsen basin to the friction law, The Cryosphere, 13, 177–195, https://doi.org/10.5194/tc-13-177-2019, 2019.
Budd, W. F. and Jacka, T. H.: A review of ice rheology for ice sheet modelling, Cold Reg. Sci. Technol., 16, 107–144, https://doi.org/10.1016/0165-232X(89)90014-1, 1989.
Budd, W. F., Keage, P. L., and Blundy, N. A.: Empirical Studies of Ice Sliding, J. Glaciol., 23, 157–170, https://doi.org/10.3189/S0022143000029804, 1979.
Burton-Johnson, A., Dziadek, R., and Martin, C.: Review article: Geothermal heat flow in Antarctica: current and future directions, The Cryosphere, 14, 3843–3873, https://doi.org/10.5194/tc-14-3843-2020, 2020.
Choi, Y., Seroussi, H., Morlighem, M., Schlegel, N.-J., and Gardner, A.: Impact of time-dependent data assimilation on ice flow model initialization and projections: a case study of Kjer Glacier, Greenland, The Cryosphere, 17, 5499–5517, https://doi.org/10.5194/tc-17-5499-2023, 2023.
Cornford, S. L., Martin, D. F., Payne, A. J., Ng, E. G., Le Brocq, A. M., Gladstone, R. M., Edwards, T. L., Shannon, S. R., Agosta, C., van den Broeke, M. R., Hellmer, H. H., Krinner, G., Ligtenberg, S. R. M., Timmermann, R., and Vaughan, D. G.: Century-scale simulations of the response of the West Antarctic Ice Sheet to a warming climate, The Cryosphere, 9, 1579–1600, https://doi.org/10.5194/tc-9-1579-2015, 2015.
Dawson, E. J., Schroeder, D. M., Chu, W., Mantelli, E., and Seroussi, H.: Ice mass loss sensitivity to the Antarctic ice sheet basal thermal state, Nat. Commun., 13, 4957, https://doi.org/10.1038/s41467-022-32632-2, 2022.
Dow, C. F., McCormack, F. S., Young, D. A., Greenbaum, J. S., Roberts, J. L., and Blankenship, D. D.: Totten Glacier subglacial hydrology determined from geophysics and modeling, Earth Planet. Sc. Lett., 531, 115961, https://doi.org/10.1016/j.epsl.2019.115961, 2020.
Dziadek, R., Gohl, K., Diehl, A., and Kaul, N.: Geothermal heat flux in the Amundsen Sea sector of West Antarctica: New insights from temperature measurements, depth to the bottom of the magnetic source estimation, and thermal modeling, Geochem. Geophy. Geosy., 18, 2657–2672, https://doi.org/10.1002/2016GC006755, 2017.
Fisher, A. T., Mankoff, K. D., Tulaczyk, S. M., Tyler, S. W., and Foley, N.: High geothermal heat flux measured below the West Antarctic Ice Sheet, Sci. Adv., 1, e1500093, https://doi.org/10.1126/sciadv.1500093, 2015.
Fowler, A. C.: A theoretical treatment of the sliding of glaciers in the absense of cavitation, Philos. Trans. R. Soc. Lond. Ser. Math. Phys. Sci., 298, 637–681, https://doi.org/10.1098/rsta.1981.0003, 1981.
Fujita, S. and Mae, S.: Strain in the ice sheet deduced from the crystal-orientation fabrics from bare icefields adjacent to the Sør-Rondane Mountains, Dronning Maud Land, East Antarctica, J. Glaciol., 40, 135–139, https://doi.org/10.3189/S0022143000003907, 1994.
Gagliardini, O., Cohen, D., Råback, P., and Zwinger, T.: Finite-element modeling of subglacial cavities and related friction law, J. Geophys. Res.-Earth, 112, F02027, https://doi.org/10.1029/2006JF000576, 2007.
Gerber, T. A., Lilien, D. A., Rathmann, N. M., Franke, S., Young, T. J., Valero-Delgado, F., Ershadi, M. R., Drews, R., Zeising, O., Humbert, A., Stoll, N., Weikusat, I., Grinsted, A., Hvidberg, C. S., Jansen, D., Miller, H., Helm, V., Steinhage, D., O'Neill, C., Paden, J., Gogineni, S. P., Dahl-Jensen, D., and Eisen, O.: Crystal orientation fabric anisotropy causes directional hardening of the Northeast Greenland Ice Stream, Nat. Commun., 14, 2653, https://doi.org/10.1038/s41467-023-38139-8, 2023.
Gillet-Chaulet, F., Gagliardini, O., Seddik, H., Nodet, M., Durand, G., Ritz, C., Zwinger, T., Greve, R., and Vaughan, D. G.: Greenland ice sheet contribution to sea-level rise from a new-generation ice-sheet model, The Cryosphere, 6, 1561–1576, https://doi.org/10.5194/tc-6-1561-2012, 2012.
Gladstone, R., Schäfer, M., Zwinger, T., Gong, Y., Strozzi, T., Mottram, R., Boberg, F., and Moore, J. C.: Importance of basal processes in simulations of a surging Svalbard outlet glacier, The Cryosphere, 8, 1393–1405, https://doi.org/10.5194/tc-8-1393-2014, 2014.
Greenbaum, J. S., Blankenship, D. D., Young, D. A., Richter, T. G., Roberts, J. L., Aitken, A. R. A., Legresy, B., Schroeder, D. M., Warner, R. C., van Ommen, T. D., and Siegert, M. J.: Ocean access to a cavity beneath Totten Glacier in East Antarctica, Nat. Geosci., 8, 294–298, https://doi.org/10.1038/ngeo2388, 2015.
Haeger, C., Petrunin, A. G., and Kaban, M. K.: Geothermal Heat Flow and Thermal Structure of the Antarctic Lithosphere, Geochem. Geophys. Geosy., 23, e2022GC010501, https://doi.org/10.1029/2022GC010501, 2022.
Huang, Y., Zhao, L., Wolovick, M., Ma, Y., and Moore, J. C.: Using specularity content to evaluate eight geothermal heat flow maps of Totten Glacier, The Cryosphere, 18, 103–119, https://doi.org/10.5194/tc-18-103-2024, 2024.
Jordan, T. M., Martín, C., Brisbourne, A. M., Schroeder, D. M., and Smith, A. M.: Radar Characterization of Ice Crystal Orientation Fabric and Anisotropic Viscosity Within an Antarctic Ice Stream, J. Geophys. Res.-Earth, 127, e2022JF006673, https://doi.org/10.1029/2022JF006673, 2022.
Kamb, B.: Sliding motion of glaciers: Theory and observation, Rev. Geophys., 8, 673–728, https://doi.org/10.1029/RG008i004p00673, 1970.
Kang, H., Zhao, L., Wolovick, M., and Moore, J. C.: Evaluation of six geothermal heat flux maps for the Antarctic Lambert–Amery glacial system, The Cryosphere, 16, 3619–3633, https://doi.org/10.5194/tc-16-3619-2022, 2022.
Kim, B.-H., Seo, K.-W., Lee, C.-K., Kim, J.-S., Lee, W. S., Jin, E. K., and Van Den Broeke, M.: Partitioning the drivers of Antarctic glacier mass balance (2003–2020) using satellite observations and a regional climate model, P. Natl. Acad. Sci. USA, 121, e2322622121, https://doi.org/10.1073/pnas.2322622121, 2024.
Larour, E., Seroussi, H., Morlighem, M., and Rignot, E.: Continental scale, high order, high spatial resolution, ice sheet modeling using the Ice Sheet System Model (ISSM), J. Geophys. Res., 117, F01022, https://doi.org/10.1029/2011JF002140, 2012.
Le Brocq, A. M., Payne, A. J., and Vieli, A.: An improved Antarctic dataset for high resolution numerical ice sheet models (ALBMAP v1), Earth Syst. Sci. Data, 2, 247–260, https://doi.org/10.5194/essd-2-247-2010, 2010a.
Le Brocq, A. M., Payne, A. J., and Vieli, A.: Antarctic dataset in NetCDF format, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.734145, 2010b.
Lipscomb, W. H., Leguy, G. R., Jourdain, N. C., Asay-Davis, X., Seroussi, H., and Nowicki, S.: ISMIP6-based projections of ocean-forced Antarctic Ice Sheet evolution using the Community Ice Sheet Model, The Cryosphere, 15, 633–661, https://doi.org/10.5194/tc-15-633-2021, 2021.
Lhermitte, S., Sun, S., Shuman, C., Wouters, B., Pattyn, F., Wuite, J., Berthier, E., and Nagler, T.: Damage accelerates ice shelf instability and mass loss in Amundsen Sea Embayment, P. Natl. Acad. Sci. USA, 117, 24735–24741, https://doi.org/10.1073/pnas.1912890117, 2020.
Lösing, M. and Ebbing, J.: Predicting Geothermal Heat Flow in Antarctica With a Machine Learning Approach, J. Geophys. Res.-Sol. Ea., 126, e2020JB021499, https://doi.org/10.1029/2020JB021499, 2021.
MacAyeal, D. R.: A tutorial on the use of control methods in ice-sheet modeling, J. Glaciol., 39, 91–98, https://doi.org/10.3189/S0022143000015744, 1993.
Martín, C., Gudmundsson, G. H., Pritchard, H. D., and Gagliardini, O.: On the effects of anisotropic rheology on ice flow, internal structure, and the age-depth relationship at ice divides, J. Geophys. Res.-Earth, 114, F04001, https://doi.org/10.1029/2008JF001204, 2009.
Martos, Y. M.: Antarctic geothermal heat flux distribution and estimated Curie Depths, links to gridded files, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.882503, 2017.
Martos, Y. M., Catalán, M., Jordan, T. A., Golynsky, A., Golynsky, D., Eagles, G., and Vaughan, D. G.: Heat Flux Distribution of Antarctica Unveiled, Geophys. Res. Lett., 44, 11417–11426, https://doi.org/10.1002/2017GL075609, 2017.
McCormack, F. S., Roberts, J. L., Dow, C. F., Stål, T., Halpin, J. A., Reading, A. M., and Siegert, M. J.: Fine-Scale Geothermal Heat Flow in Antarctica Can Increase Simulated Subglacial Melt Estimates, Geophys. Res. Lett., 49, e2022GL098539, https://doi.org/10.1029/2022GL098539, 2022.
Morlighem, M.: MEaSUREs BedMachine Antarctica, Version 2, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], Boulder, Colorado USA, https://doi.org/10.5067/E1QL9HFQ7A8M, 2020.
Morlighem, M., Seroussi, H., Larour, E., and Rignot, E.: Inversion of basal friction in Antarctica using exact and incomplete adjoints of a higher-order model, J. Geophys. Res.-Earth, 118, 1746–1753, https://doi.org/10.1002/jgrf.20125, 2013.
Morlighem, M., Rignot, E., Binder, T., Blankenship, D., Drews, R., Eagles, G., Eisen, O., Ferraccioli, F., Forsberg, R., Fretwell, P., Goel, V., Greenbaum, J. S., Gudmundsson, H., Guo, J., Helm, V., Hofstede, C., Howat, I., Humbert, A., Jokat, W., Karlsson, N. B., Lee, W. S., Matsuoka, K., Millan, R., Mouginot, J., Paden, J., Pattyn, F., Roberts, J., Rosier, S., Ruppel, A., Seroussi, H., Smith, E. C., Steinhage, D., Sun, B., Broeke, M. R. V. D., Ommen, T. D. V., Wessem, M. V., and Young, D. A.: Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet, Nat. Geosci., 13, 132–137, https://doi.org/10.1038/s41561-019-0510-8, 2020.
Mouginot, J., Scheuchl, B., and Rignot, E.: MEaSUREs Antarctic Boundaries for IPY 2007-2009 from Satellite Radar, NSIDC-0709, Version 2, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], Boulder, Colorado, USA, https://doi.org/10.5067/AXE4121732AD, 2017.
Nye, J. F.: Glacier sliding without cavitation in a linear viscous approximation, Proc. R. Soc. Lond. Math. Phys. Sci., 315, 381–403, https://doi.org/10.1098/rspa.1970.0050, 1970.
Park, I.-W., Jin, E. K., Morlighem, M., and Lee, K.-K.: Impact of boundary conditions on the modeled thermal regime of the Antarctic ice sheet, The Cryosphere, 18, 1139–1155, https://doi.org/10.5194/tc-18-1139-2024, 2024.
Paterson, W. S. B.: Why ice-age ice is sometimes “soft,” Cold Reg. Sci. Technol., 20, 75–98, https://doi.org/10.1016/0165-232X(91)90058-O, 1991.
Pattyn, F.: Sea-level response to melting of Antarctic ice shelves on multi-centennial timescales with the fast Elementary Thermomechanical Ice Sheet model (f.ETISh v1.0), The Cryosphere, 11, 1851–1878, https://doi.org/10.5194/tc-11-1851-2017, 2017.
Payne, A. J., Nowicki, S., Abe-Ouchi, A., Agosta, C., Alexander, P., Albrecht, T., Asay-Davis, X., Aschwanden, A., Barthel, A., Bracegirdle, T. J., Calov, R., Chambers, C., Choi, Y., Cullather, R., Cuzzone, J., Dumas, C., Edwards, T. L., Felikson, D., Fettweis, X., Galton-Fenzi, B. K., Goelzer, H., Gladstone, R., Golledge, N. R., Gregory, J. M., Greve, R., Hattermann, T., Hoffman, M. J., Humbert, A., Huybrechts, P., Jourdain, N. C., Kleiner, T., Munneke, P. K., Larour, E., Le Clec'H, S., Lee, V., Leguy, G., Lipscomb, W. H., Little, C. M., Lowry, D. P., Morlighem, M., Nias, I., Pattyn, F., Pelle, T., Price, S. F., Quiquet, A., Reese, R., Rückamp, M., Schlegel, N., Seroussi, H., Shepherd, A., Simon, E., Slater, D., Smith, R. S., Straneo, F., Sun, S., Tarasov, L., Trusel, L. D., Van Breedam, J., Van De Wal, R., Van Den Broeke, M., Winkelmann, R., Zhao, C., Zhang, T., and Zwinger, T.: Future Sea Level Change Under Coupled Model Intercomparison Project Phase 5 and Phase 6 Scenarios From the Greenland and Antarctic Ice Sheets, Geophys. Res. Lett., 48, e2020GL091741, https://doi.org/10.1029/2020GL091741, 2021.
Peyaud, V., Bouchayer, C., Gagliardini, O., Vincent, C., Gillet-Chaulet, F., Six, D., and Laarman, O.: Numerical modeling of the dynamics of the Mer de Glace glacier, French Alps: comparison with past observations and forecasting of near-future evolution, The Cryosphere, 14, 3979–3994, https://doi.org/10.5194/tc-14-3979-2020, 2020.
Pittard, M. L., Roberts, J. L., Galton-Fenzi, B. K., and Watson, C. S.: Sensitivity of the Lambert-Amery glacial system to geothermal heat flux, Ann. Glaciol., 57, 56–68, https://doi.org/10.1017/aog.2016.26, 2016.
Pollard, D. and DeConto, R. M.: A simple inverse method for the distribution of basal sliding coefficients under ice sheets, applied to Antarctica, The Cryosphere, 6, 953–971, https://doi.org/10.5194/tc-6-953-2012, 2012.
Pritchard, H. D., Arthern, R. J., Vaughan, D. G., and Edwards, L. A.: Extensive dynamic thinning on the margins of the Greenland and Antarctic ice sheets, Nature, 461, 971–975, https://doi.org/10.1038/nature08471, 2009.
Pritchard, H. D., Fretwell, P. T., Fremand, A. C., Bodart, J. A., Kirkham, J. D., Aitken, A., Bamber, J., Bell, R., Bianchi, C., Bingham, R. G., Blankenship, D. D., Casassa, G., Christianson, K., Conway, H., Corr, H. F. J., Cui, X., Damaske, D., Damm, V., Dorschel, B., Drews, R., Eagles, G., Eisen, O., Eisermann, H., Ferraccioli, F., Field, E., Forsberg, R., Franke, S., Goel, V., Gogineni, S. P., Greenbaum, J., Hills, B., Hindmarsh, R. C. A., Hoffman, A. O., Holschuh, N., Holt, J. W., Humbert, A., Jacobel, R. W., Jansen, D., Jenkins, A., Jokat, W., Jong, L., Jordan, T. A., King, E. C., Kohler, J., Krabill, W., Maton, J., Gillespie, M. K., Langley, K., Lee, J., Leitchenkov, G., Leuschen, C., Luyendyk, B., MacGregor, J. A., MacKie, E., Moholdt, G., Matsuoka, K., Morlighem, M., Mouginot, J., Nitsche, F. O., Nost, O. A., Paden, J., Pattyn, F., Popov, S., Rignot, E., Rippin, D. M., Rivera, A., Roberts, J. L., Ross, N., Ruppel, A., Schroeder, D. M., Siegert, M. J., Smith, A. M., Steinhage, D., Studinger, M., Sun, B., Tabacco, I., Tinto, K. J., Urbini, S., Vaughan, D. G., Wilson, D. S., Young, D. A., and Zirizzotti, A.: Bedmap3 updated ice bed, surface and thickness gridded datasets for Antarctica, Sci. Data, 12, 414, https://doi.org/10.1038/s41597-025-04672-y, 2025.
Purucker, M.: Geothermal heat flux data set based on low resolution observations collected by the CHAMP satellite between 2000 and 2010, and produced from the MF-6 model following the technique described in Fox Maule et al. (2005), Interactive System for Ice sheet Simulation [data set], https://core2.gsfc.nasa.gov/research/purucker/heatflux_mf7_foxmaule05.txt (last access: 24 December 2023), 2012.
Rathmann, N. M. and Lilien, D. A.: Inferred basal friction and mass flux affected by crystal-orientation fabrics, J. Glaciol., 68, 236–252, https://doi.org/10.1017/jog.2021.88, 2022.
Reading, A. M., Stål, T., Halpin, J. A., Lösing, M., Ebbing, J., Shen, W., McCormack, F. S., Siddoway, C. S., and Hasterok, D.: Antarctic geothermal heat flow and its implications for tectonics and ice sheets, Nat. Rev. Earth Environ., 3, 814–831, https://doi.org/10.1038/s43017-022-00348-y, 2022.
Reese, R., Garbe, J., Hill, E. A., Urruty, B., Naughten, K. A., Gagliardini, O., Durand, G., Gillet-Chaulet, F., Gudmundsson, G. H., Chandler, D., Langebroek, P. M., and Winkelmann, R.: The stability of present-day Antarctic grounding lines – Part 2: Onset of irreversible retreat of Amundsen Sea glaciers under current climate on centennial timescales cannot be excluded, The Cryosphere, 17, 3761–3783, https://doi.org/10.5194/tc-17-3761-2023, 2023.
Rignot, E., Mouginot, J., and Scheuchl, B.: MEaSUREs InSAR-Based Antarctica Ice Velocity Map, Version 2, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/D7GK8F5J8M8R, 2017.
Rignot, E., Mouginot, J., Scheuchl, B., Van Den Broeke, M., Van Wessem, M. J., and Morlighem, M.: Four decades of Antarctic Ice Sheet mass balance from 1979–2017, P. Natl. Acad. Sci. USA, 116, 1095–1103, https://doi.org/10.1073/pnas.1812883116, 2019.
Ross, N., Bingham, R. G., Corr, H. F. J., Ferraccioli, F., Jordan, T. A., Le Brocq, A., Rippin, D. M., Young, D., Blankenship, D. D., and Siegert, M. J.: Steep reverse bed slope at the grounding line of the Weddell Sea sector in West Antarctica, Nat. Geosci., 5, 393–396, https://doi.org/10.1038/ngeo1468, 2012.
Robel, A. A., Schoof, C., and Tziperman, E.: Rapid grounding line migration induced by internal ice stream variability, J. Geophys. Res.-Earth, 119, 2430–2447, https://doi.org/10.1002/2014JF003251, 2014.
Schannwell, C., Drews, R., Ehlers, T. A., Eisen, O., Mayer, C., Malinen, M., Smith, E. C., and Eisermann, H.: Quantifying the effect of ocean bed properties on ice sheet geometry over 40 000 years with a full-Stokes model, The Cryosphere, 14, 3917–3934, https://doi.org/10.5194/tc-14-3917-2020, 2020.
Schoof, C.: On the mechanics of ice-stream shear margins, J. Glaciol., 50, 208–218, https://doi.org/10.3189/172756504781830024, 2004.
Schoof, C.: The effect of cavitation on glacier sliding, Proc. R. Soc. Math. Phys. Eng. Sci., 461, 609–627, https://doi.org/10.1098/rspa.2004.1350, 2005.
Schroeder, D. M., Blankenship, D. D., and Young, D. A.: Evidence for a water system transition beneath Thwaites Glacier, West Antarctica, P. Natl. Acad. Sci. USA, 110, 12225–12228, https://doi.org/10.1073/pnas.1302828110, 2013.
Seroussi, H., Nowicki, S., Simon, E., Abe-Ouchi, A., Albrecht, T., Brondex, J., Cornford, S., Dumas, C., Gillet-Chaulet, F., Goelzer, H., Golledge, N. R., Gregory, J. M., Greve, R., Hoffman, M. J., Humbert, A., Huybrechts, P., Kleiner, T., Larour, E., Leguy, G., Lipscomb, W. H., Lowry, D., Mengel, M., Morlighem, M., Pattyn, F., Payne, A. J., Pollard, D., Price, S. F., Quiquet, A., Reerink, T. J., Reese, R., Rodehacke, C. B., Schlegel, N.-J., Shepherd, A., Sun, S., Sutter, J., Van Breedam, J., van de Wal, R. S. W., Winkelmann, R., and Zhang, T.: initMIP-Antarctica: an ice sheet model initialization experiment of ISMIP6, The Cryosphere, 13, 1441–1471, https://doi.org/10.5194/tc-13-1441-2019, 2019.
Shackleton, C., Matsuoka, K., Moholdt, G., Van Liefferinge, B., and Paden, J.: Stochastic Simulations of Bed Topography Constrain Geothermal Heat Flow and Subglacial Drainage Near Dome Fuji, East Antarctica, J. Geophys. Res.-Earth, 128, e2023JF007269, https://doi.org/10.1029/2023JF007269, 2023.
Shapiro, N. M. and Ritzwoller, M. H.: Inferring surface heat flux distributions guided by a global seismic model: particular application to Antarctica, Earth Planet. Sc. Lett., 223, 213–224, https://doi.org/10.1016/j.epsl.2004.04.011, 2004.
Shen, W., Wiens, D. A., Lloyd, A. J., and Nyblade, A. A.: A Geothermal Heat Flux Map of Antarctica Empirically Constrained by Seismic Structure, Geophys. Res. Lett., 47, e2020GL086955, https://doi.org/10.1029/2020GL086955, 2020.
Siahaan, A., Smith, R. S., Holland, P. R., Jenkins, A., Gregory, J. M., Lee, V., Mathiot, P., Payne, A. J., Ridley, J. K., and Jones, C. G.: The Antarctic contribution to 21st-century sea-level rise predicted by the UK Earth System Model with an interactive ice sheet, The Cryosphere, 16, 4053–4086, https://doi.org/10.5194/tc-16-4053-2022, 2022.
Smith-Johnsen, S., Schlegel, N.-J., De Fleurian, B., and Nisancioglu, K. H.: Sensitivity of the Northeast Greenland Ice Stream to Geothermal Heat, J. Geophys. Res.-Earth, 125, e2019JF005252, https://doi.org/10.1029/2019JF005252, 2020.
Stål, T., Reading, A. M., Halpin, J. A., and Whittaker, J. M.: Antarctic Geothermal Heat Flow Model: Aq1, Geochem. Geophy. Geosy., 22, e2020GC009428, https://doi.org/10.1029/2020GC009428, 2021.
Sun, S., Cornford, S. L., Moore, J. C., Gladstone, R., and Zhao, L.: Ice shelf fracture parameterization in an ice sheet model, The Cryosphere, 11, 2543–2554, https://doi.org/10.5194/tc-11-2543-2017, 2017.
Tsai, V. C., Stewart, A. L., and Thompson, A. F.: Marine ice-sheet profiles and stability under Coulomb basal conditions, J. Glaciol., 61, 205–215, https://doi.org/10.3189/2015JoG14J221, 2015.
Van Liefferinge, B., Pattyn, F., Cavitte, M. G. P., Karlsson, N. B., Young, D. A., Sutter, J., and Eisen, O.: Promising Oldest Ice sites in East Antarctica based on thermodynamical modelling, The Cryosphere, 12, 2773–2787, https://doi.org/10.5194/tc-12-2773-2018, 2018.
Weertman, J.: On the Sliding of Glaciers, J. Glaciol., 3, 33–38, https://doi.org/10.3189/S0022143000024709, 1957.
Young, D. A., Schroeder, D. M., Blankenship, D. D., Kempf, S. D., and Quartini, E.: The distribution of basal water between Antarctic subglacial lakes from radar sounding, Philos. Trans. R. Soc. Math. Phys. Eng. Sci., 374, 20140297, https://doi.org/10.1098/rsta.2014.0297, 2016.
Zhao, L., Moore, J. C., Sun, B., Tang, X., and Guo, X.: Where is the 1-million-year-old ice at Dome A?, The Cryosphere, 12, 1651–1663, https://doi.org/10.5194/tc-12-1651-2018, 2018.
Zhao, L., Wolovick, M., Huang, Y., Moore, J. C. and Ma, Y.: Totten Glacier Thermal Structure, Zenodo [data set], https://doi.org/10.5281/zenodo.7825456, 2023.
Zhang, X.: Near-surface air temperature data of Antarctic ice sheet (2001–2018), National Tibetan Plateau/Third Pole Environment Data Center [data set], https://doi.org/10.11888/Atmos.tpdc.272234, 2022.
Zhang, X., Dong, X., Zeng, J, Hou, S., Smeets, P., Reijmer, C. H., and Wang, Y.: Spatiotemporal Reconstruction of Antarctic Near-Surface Air Temperature from MODIS Observations, J. Climate, 35, 5537–5553, 2022.
Zwinger, T., Schäfer, M., Martín, C., and Moore, J. C.: Influence of anisotropy on velocity and age distribution at Scharffenbergbotnen blue ice area, The Cryosphere, 8, 607–621, https://doi.org/10.5194/tc-8-607-2014, 2014.
Short summary
Ice sheet models adjust basal sliding with assumed ice temperatures so that surface speeds match observations, leading to inconsistencies between basal thermal state and sliding fields. We propose a method to quantify these inconsistencies without requiring any subglacial measurements. This method is applied to ice sheet model of Totten Glacier using eight geothermal heat flux (GHF) datasets, yielding rankings of GHF that align with those based on radar data.
Ice sheet models adjust basal sliding with assumed ice temperatures so that surface speeds match...
