Articles | Volume 18, issue 1
https://doi.org/10.5194/tc-18-103-2024
© Author(s) 2024. 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-18-103-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Jan 2024
Research article |
| 04 Jan 2024
| 04 Jan 2024
Using specularity content to evaluate eight geothermal heat flow maps of Totten Glacier
Yan Huang
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Liyun Zhao
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Michael Wolovick
Glaciology Section, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
Yiliang Ma
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
John C. Moore
CORRESPONDING AUTHOR
Arctic Centre, University of Lapland, Rovaniemi, Finland
Related authors
No articles found.
Junshun Wang, Liyun Zhao, Michael Wolovick, and John C. Moore
EGUsphere, https://doi.org/10.5194/egusphere-2025-3296, https://doi.org/10.5194/egusphere-2025-3296, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
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.
Lea-Sophie Höyns, Thomas Kleiner, Andreas Rademacher, Martin Rückamp, Michael Wolovick, and Angelika Humbert
The Cryosphere, 19, 2133–2158, https://doi.org/10.5194/tc-19-2133-2025, https://doi.org/10.5194/tc-19-2133-2025, 2025
Short summary
Short summary
The sliding of glaciers over bedrock is influenced by water pressure in the underlying hydrological system and the roughness of the land underneath the glacier. We estimate this roughness through a modeling approach that optimizes this unknown parameter. Additionally, we simulate water pressure, enhancing the reliability of the computed drag at the ice sheet base. The resulting data are provided to other modelers and scientists conducting geophysical field observations.
Yiliang Ma, Liyun Zhao, Rupert Gladstone, Thomas Zwinger, Michael Wolovick, and John C. Moore
EGUsphere, https://doi.org/10.5194/egusphere-2024-1102, https://doi.org/10.5194/egusphere-2024-1102, 2024
Short summary
Short summary
Totten Glacier in Antarctica holds a sea level potential of 3.85 m. Basal sliding and sub-shelf melt rate have important impact on ice sheet dynamics. We simulate the evolution of Totten Glacier using an ice flow model with different basal sliding parameterizations as well as sub-shelf melt rates to quantify their effect on the projections. We found the modelled glacier retreat and mass loss is sensitive to the choice of basal sliding parameterizations and maximal sub-shelf melt rate.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
Short summary
Short summary
This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Abolfazl Rezaei, Khalil Karami, Simone Tilmes, and John C. Moore
Earth Syst. Dynam., 15, 91–108, https://doi.org/10.5194/esd-15-91-2024, https://doi.org/10.5194/esd-15-91-2024, 2024
Short summary
Short summary
Water storage (WS) plays a profound role in the lives of people in the Middle East and North Africa as well as Mediterranean climate "hot spots". WS change by greenhouse gas (GHG) warming is simulated with and without stratospheric aerosol intervention (SAI). WS significantly increases in the Arabian Peninsula and decreases around the Mediterranean under GHG. While SAI partially ameliorates GHG impacts, projected WS increases in dry regions and decreases in wet areas relative to present climate.
Chencheng Shen, John C. Moore, Heri Kuswanto, and Liyun Zhao
Earth Syst. Dynam., 14, 1317–1332, https://doi.org/10.5194/esd-14-1317-2023, https://doi.org/10.5194/esd-14-1317-2023, 2023
Short summary
Short summary
The Indonesia Throughflow is an important pathway connecting the Pacific and Indian oceans and is part of a wind-driven circulation that is expected to reduce under greenhouse gas forcing. Solar dimming and sulfate aerosol injection geoengineering may reverse this effect. But stratospheric sulfate aerosols affect winds more than simply ``shading the sun''; they cause a reduction in water transport similar to that we simulate for a scenario with unabated greenhouse gas emissions.
Michael Wolovick, Angelika Humbert, Thomas Kleiner, and Martin Rückamp
The Cryosphere, 17, 5027–5060, https://doi.org/10.5194/tc-17-5027-2023, https://doi.org/10.5194/tc-17-5027-2023, 2023
Short summary
Short summary
The friction underneath ice sheets can be inferred from observed velocity at the top, but this inference requires smoothing. The selection of smoothing has been highly variable in the literature. Here we show how to rigorously select the best smoothing, and we show that the inferred friction converges towards the best knowable field as model resolution improves. We use this to learn about the best description of basal friction and to formulate recommended best practices for other modelers.
Jun Wang, John C. Moore, and Liyun Zhao
Earth Syst. Dynam., 14, 989–1013, https://doi.org/10.5194/esd-14-989-2023, https://doi.org/10.5194/esd-14-989-2023, 2023
Short summary
Short summary
Apparent temperatures and PM2.5 pollution depend on humidity and wind speed in addition to surface temperature and impact human health and comfort. Apparent temperatures will reach dangerous levels more commonly in the future because of water vapor pressure rises and lower expected wind speeds, but these will also drive changes in PM2.5. Solar geoengineering can significantly reduce the frequency of extreme events relative to modest and especially
business-as-usualgreenhouse scenarios.
Abolfazl Rezaei, Khalil Karami, Simone Tilmes, and John C. Moore
Atmos. Chem. Phys., 23, 5835–5850, https://doi.org/10.5194/acp-23-5835-2023, https://doi.org/10.5194/acp-23-5835-2023, 2023
Short summary
Short summary
Teleconnection patterns are important characteristics of the climate system; well-known examples include the El Niño and La Niña events driven from the tropical Pacific. We examined how spatiotemporal patterns that arise in the Pacific and Atlantic oceans behave under stratospheric aerosol geoengineering and greenhouse gas (GHG)-induced warming. In general, geoengineering reverses trends; however, the changes in decadal oscillation for the AMO, NAO, and PDO imposed by GHG are not suppressed.
Daniele Visioni, Ben Kravitz, Alan Robock, Simone Tilmes, Jim Haywood, Olivier Boucher, Mark Lawrence, Peter Irvine, Ulrike Niemeier, Lili Xia, Gabriel Chiodo, Chris Lennard, Shingo Watanabe, John C. Moore, and Helene Muri
Atmos. Chem. Phys., 23, 5149–5176, https://doi.org/10.5194/acp-23-5149-2023, https://doi.org/10.5194/acp-23-5149-2023, 2023
Short summary
Short summary
Geoengineering indicates methods aiming to reduce the temperature of the planet by means of reflecting back a part of the incoming radiation before it reaches the surface or allowing more of the planetary radiation to escape into space. It aims to produce modelling experiments that are easy to reproduce and compare with different climate models, in order to understand the potential impacts of these techniques. Here we assess its past successes and failures and talk about its future.
Yangxin Chen, Duoying Ji, Qian Zhang, John C. Moore, Olivier Boucher, Andy Jones, Thibaut Lurton, Michael J. Mills, Ulrike Niemeier, Roland Séférian, and Simone Tilmes
Earth Syst. Dynam., 14, 55–79, https://doi.org/10.5194/esd-14-55-2023, https://doi.org/10.5194/esd-14-55-2023, 2023
Short summary
Short summary
Solar geoengineering has been proposed as a way of counteracting the warming effects of increasing greenhouse gases by reflecting solar radiation. This work shows that solar geoengineering can slow down the northern-high-latitude permafrost degradation but cannot preserve the permafrost ecosystem as that under a climate of the same warming level without solar geoengineering.
Aobo Liu, John C. Moore, and Yating Chen
Earth Syst. Dynam., 14, 39–53, https://doi.org/10.5194/esd-14-39-2023, https://doi.org/10.5194/esd-14-39-2023, 2023
Short summary
Short summary
Permafrost thaws and releases carbon (C) as the Arctic warms. Most earth system models (ESMs) have poor estimates of C stored now, so their future C losses are much lower than using the permafrost C model with climate inputs from six ESMs. Bias-corrected soil temperatures and plant productivity plus geoengineering lowering global temperatures from a no-mitigation baseline scenario to a moderate emissions level keep C in the soil worth about USD 0–70 (mean 20) trillion in climate damages by 2100.
Jun Wang, John C. Moore, Liyun Zhao, Chao Yue, and Zhenhua Di
Earth Syst. Dynam., 13, 1625–1640, https://doi.org/10.5194/esd-13-1625-2022, https://doi.org/10.5194/esd-13-1625-2022, 2022
Short summary
Short summary
We examine how geoengineering using aerosols in the atmosphere might impact urban climate in the greater Beijing region containing over 50 million people. Climate models have too coarse resolutions to resolve regional variations well, so we compare two workarounds for this – an expensive physical model and a cheaper statistical method. The statistical method generally gives a reasonable representation of climate and has limited resolution and a different seasonality from the physical model.
Angelika Humbert, Julia Christmann, Hugh F. J. Corr, Veit Helm, Lea-Sophie Höyns, Coen Hofstede, Ralf Müller, Niklas Neckel, Keith W. Nicholls, Timm Schultz, Daniel Steinhage, Michael Wolovick, and Ole Zeising
The Cryosphere, 16, 4107–4139, https://doi.org/10.5194/tc-16-4107-2022, https://doi.org/10.5194/tc-16-4107-2022, 2022
Short summary
Short summary
Ice shelves are normally flat structures that fringe the Antarctic continent. At some locations they have channels incised into their underside. On Filchner Ice Shelf, such a channel is more than 50 km long and up to 330 m high. We conducted field measurements of basal melt rates and found a maximum of 2 m yr−1. Simulations represent the geometry evolution of the channel reasonably well. There is no reason to assume that this type of melt channel is destabilizing ice shelves.
Haoran Kang, Liyun Zhao, Michael Wolovick, and John C. Moore
The Cryosphere, 16, 3619–3633, https://doi.org/10.5194/tc-16-3619-2022, https://doi.org/10.5194/tc-16-3619-2022, 2022
Short summary
Short summary
Basal thermal conditions are important to ice dynamics and sensitive to geothermal heat flux (GHF). We estimate basal thermal conditions of the Lambert–Amery Glacier system with six GHF maps. Recent GHFs inverted from aerial geomagnetic observations produce a larger warm-based area and match the observed subglacial lakes better than the other GHFs. The modelled basal melt rate is 10 to hundreds of millimetres per year in fast-flowing glaciers feeding the Amery Ice Shelf and smaller inland.
Mengdie Xie, John C. Moore, Liyun Zhao, Michael Wolovick, and Helene Muri
Atmos. Chem. Phys., 22, 4581–4597, https://doi.org/10.5194/acp-22-4581-2022, https://doi.org/10.5194/acp-22-4581-2022, 2022
Short summary
Short summary
We use data from six Earth system models to estimate Atlantic meridional overturning circulation (AMOC) changes and its drivers under four different solar geoengineering methods. Solar dimming seems relatively more effective than marine cloud brightening or stratospheric aerosol injection at reversing greenhouse-gas-driven declines in AMOC. Geoengineering-induced AMOC amelioration is due to better maintenance of air–sea temperature differences and reduced loss of Arctic summer sea ice.
Yijing Lin, Yan Liu, Zhitong Yu, Xiao Cheng, Qiang Shen, and Liyun Zhao
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-325, https://doi.org/10.5194/tc-2021-325, 2021
Preprint withdrawn
Short summary
Short summary
We introduce an uncertainty analysis framework for comprehensively and systematically quantifying the uncertainties of the Antarctic mass balance using the Input and Output Method. It is difficult to use the previous strategies employed in various methods and the available data to achieve the goal of estimation accuracy. The dominant cause of the future uncertainty is the ice thickness data gap. The interannual variability of ice discharge caused by velocity and thickness is also nonnegligible.
Chao Yue, Louise Steffensen Schmidt, Liyun Zhao, Michael Wolovick, and John C. Moore
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-318, https://doi.org/10.5194/tc-2021-318, 2021
Revised manuscript not accepted
Short summary
Short summary
We use the ice sheet model PISM to estimate Vatnajökull mass balance under solar geoengineering. We find that Stratospheric aerosol injection at the rate of 5 Tg yr−1 reduces ice cap mass loss by 4 percentage points relative to the RCP4.5 scenario. Dynamic mass loss is a significant component of mass balance, but insensitive to climate forcing.
Rupert Gladstone, Benjamin Galton-Fenzi, David Gwyther, Qin Zhou, Tore Hattermann, Chen Zhao, Lenneke Jong, Yuwei Xia, Xiaoran Guo, Konstantinos Petrakopoulos, Thomas Zwinger, Daniel Shapero, and John Moore
Geosci. Model Dev., 14, 889–905, https://doi.org/10.5194/gmd-14-889-2021, https://doi.org/10.5194/gmd-14-889-2021, 2021
Short summary
Short summary
Retreat of the Antarctic ice sheet, and hence its contribution to sea level rise, is highly sensitive to melting of its floating ice shelves. This melt is caused by warm ocean currents coming into contact with the ice. Computer models used for future ice sheet projections are not able to realistically evolve these melt rates. We describe a new coupling framework to enable ice sheet and ocean computer models to interact, allowing projection of the evolution of melt and its impact on sea level.
Cited articles
Adusumilli, S., Fricker, H. A., Medley, B., Padman, L., and Siegfried, M. R.: Interannual variations in meltwater input to the Southern Ocean from Antarctic ice shelves, Nat. Geosci., 13, 616–620, https://doi.org/10.1038/s41561-020-0616-z, 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, 359–383, https://doi.org/10.1002/2015JB011917, 2015 (data available at: http://www.seismolab.org/model/antarctica/lithosphere/AN1-HF.tar.gz, last access: 11 April 2023).
Bell, R. E., Studinger, M., Shuman, C. A., Fahnestock, M. A., and Joughin, I.: Large subglacial lakes in East Antarctica at the onset of fast-flowing ice streams, Nature, 445, 904–907, https://doi.org/10.1038/nature05554, 2007.
Bullard, E. C.: The disturbance of the temperature gradient in the earth's crust by inequalities of height, Geophysical Supplements, Mon. Not. R. Astron. Soc., 4, 360–362, https://doi.org/10.1111/j.1365-246X.1938.tb01760.x, 1938.
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.
Colgan, W., MacGregor, J. A., Mankoff, K. D., Haagenson, R., Rajaram, H., Martos, Y. M., Morlighem, M., Fahnestock, M. A., and Kjeldsen, K. K.: Topographic correction of geothermal heat flux in Greenland and Antarctica, J. Geophys. Res.-Earth, 126, e2020JF005598, https://doi.org/10.1029/2020JF005598, 2021.
Comiso, J. C.: Variability and Trends in Antarctic Surface Temperatures from In Situ and Satellite Infrared Measurements, J. Climate, 13, 1674–1696, https://doi.org/10.1175/1520-0442(2000)013<1674:VATIAS>2.0.CO;2, 2000.
Dow, C.: Aurora Subglacial Basin GlaDs inputs, outputs and geophysical data, Zenodo [data set], https://doi.org/10.5281/zenodo.3525474, 2019.
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.
Fisher, A. T., Mankoff, K. D., Tulaczyk, S. M., Tyler, S. W., Foley, N., and The Wissard Science Team: High geothermal heat flux measured below the West Antarctic Ice Sheet, Sci. Adv., 1, e1500093, https://doi.org/10.1126/sciadv.1500093, 2015.
Fox Maule, C., Purucker, M. E., Olsen, N., and Mosegaard, K.: Heat flux anomalies in Antarctica revealed by satellite magnetic data, Science, 309, 464–467, https://doi.org/10.1126/science.1106888, 2005.
Fricker, H. A., Siegfried, M. R., Carter, S. P., and Scambos, T. A.: A decade of progress in observing and modelling Antarctic subglacial water systems, Phil. Trans. R. Soc. A., 374, 20140294, https://doi.org/10.1098/rsta.2014.0294, 2016.
Gagliardini, O., Zwinger, T., Gillet-Chaulet, F., Durand, G., Favier, L., de Fleurian, B., Greve, R., Malinen, M., Martín, C., Råback, P., Ruokolainen, J., Sacchettini, M., Schäfer, M., Seddik, H., and Thies, J.: Capabilities and performance of Elmer/Ice, a new-generation ice sheet model, Geosci. Model Dev., 6, 1299–1318, https://doi.org/10.5194/gmd-6-1299-2013, 2013.
Geuzaine, C. and Remacle, J.-F.: Gmsh: A 3-D finite element mesh generator with built-in pre- and post-processing facilities, Int. J. Numer. Meth. Eng., 79, 1309–1331, https://doi.org/10.1002/nme.2579, 2009.
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.
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.
Greve, R. and Blatter, H.: Dynamics of Ice Sheets and Glaciers, Advances in Geophysical and Environmental Mechanics and Mathematics, edited by: Hutter, K., Springer, ISBN 978-3-642-03414-5, 2009.
Haeger, C., Petrunin, A. G., and Kaban, M. K.: Geothermal heat flow and thermal structure of the Antarctic lithosphere, Geochem. Geophys. Geosyst., 23, e2022GC010501, https://doi.org/10.1029/2022GC010501, 2022.
Huybrechts, P.: A 3-D model for the Antarctic ice sheet: a sensitivity study on the glacial-interglacial contrast, Clim. Dynam., 5, 79–92, https://doi.org/10.1007/BF00207423, 1990.
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.
Larour, E., Morlighem, M., Seroussi, H., Schiermeier, J., and Rignot, E.: Ice flow sensitivity to geothermal heat flux of Pine Island Glacier, Antarctica, J. Geophys. Res.-Earth, 117, F04023, https://doi.org/10.1029/2012jf002371, 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.
Li, X., Rignot, E., Mouginot, J., and Scheuchl, B.: Ice flow dynamics and mass loss of Totten Glacier, East Antarctica, from 1989 to 2015, Geophys. Res. Lett., 43, 6366–6373, https://doi.org/10.1002/2016GL069173, 2016.
Livingstone, S. J., Utting, D. J., Ruffell, A., Clark, C. D., Pawley, S., Atkinson, N., and Fowler, A. C.: Discovery of relict subglacial lakes and their geometry and mechanism of drainage, Nat. Commun., 7, ncomms11767, https://doi.org/10.1038/ncomms11767, 2016.
Livingstone, S. J., Li, Y., Rutishauser, A., Sanderson, R. J., Winter, K., Mikucki, J. A., Björnsson, H., Bowling, J. S., Chu, W., Dow, C. F., Fricker, H. A., McMillan, M., Ng, F. S. L., Ross, N., Siegert, M. J., Siegfried, M., and Sole, A. J.: Subglacial lakes and their changing role in a warming climate, Nat. Rev. Earth Environ., 3, 106–124, https://doi.org/10.1038/s43017-021-00246-9, 2022 (data available at: https://static-content.springer.com/esm/art%3A10.1038%2Fs43017-021-00246-9/MediaObjects/43017_2021_246_MOESM1_ESM.xlsx, last access: 24 December 2023).
Lösing, M. and Ebbing, J.: Predicting geothermal heat flow in Antarctica with a machine learning approach, J. Geophys. Res.-Earth, 126, e2020JB021499, https://doi.org/10.1029/2020JB021499, 2021.
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.
Morlighem, M.: MEaSUREs BedMachine Antarctica, Version 2, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/E1QL9HFQ7A8M, 2020.
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., 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., Van den Broeke, M. R., Van Ommen, T. D., Van Wessem, M., 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, Version 2, National Snow and Ice Data Center [data set], https://doi.org/10.5067/AXE4121732AD, 2017.
Pattyn, F.: Antarctic subglacial conditions inferred from a hybrid ice sheet/ice stream model, Earth Planet. Sc. Lett., 295, 451–461, https://doi.org/10.1016/j.epsl.2010.04.025, 2010.
Pittard, M., Roberts, J., Galton-Fenzi, B., and Watson, C.: 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.
Pollack, H. N., Hurter, S. J., and Johnson, J. R.: Heat flow from the Earth's interior: Analysis of the global data set, Rev. Geophys., 31, 267, https://doi.org/10.1029/93RG01249, 1993.
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.
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.
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.
Rignot, E., Jacobs, S., Mouginot, J., Scheuchl, B., Fretwell, P., Pritchard, H. D., Vaughan, D. G., Bamber, J. L., Barrand, N. E., Bell, R., Bianchi, C., Bingham, R. G., Blankenship, D. D., Casassa, G., Catania, G., Callens, D., Conway, H., Cook, A. J., Corr, H. F. J., Damaske, D., Damm, V., Ferraccioli, F., Forsberg, R., Fujita, S., Gim, Y., Gogineni, P., Griggs, J. A., Hindmarsh, R. C. A., Holmlund, P., Holt, J. W., Jacobel, R. W., Jenkins, A., Jokat, W., Jordan, T., King, E. C., Kohler, J., Krabill, W., Riger-Kusk, M., Langley, K. A., Leitchenkov, G., Leuschen, C., Luyendyk, B. P., Matsuoka, K., Mouginot, J., Nitsche, F. O., Nogi, Y., Nost, O. A., and Popov, S. V.: Ice-shelf melting around Antarctica, Science, 341, 266–270, https://doi.org/10.1126/science.1235798, 2013.
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.
Roberts, J., Galton-Fenzi, B. K., Paolo, F. S., Donnelly, C., Gwyther, D. E., Padman, L., Young, D., Warner, R., Greenbaum, J., Fricker, H. A., Payne, A. J., Cornford, S., Le Brocq, A., Van Ommen, T., Blankenship, D., and Siegert, M. J.: Ocean forced variability of Totten Glacier mass loss, Geological Society, London, Special Publications, 461, 175–186, https://doi.org/10.1144/SP461.6, 2018.
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.
Schroeder, D. M., Blankenship, D. D., Raney, R. K., and Grima, C.: Estimating Subglacial Water Geometry Using Radar Bed Echo Specularity: Application to Thwaites Glacier, West Antarctica, IEEE Geosci. Remote Sens. Lett., 12, 443–447, https://doi.org/10.1109/LGRS.2014.2337878, 2015.
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 (data available at: https://sites.google.com/view/weisen/research-products?authuser=0, last access: 11 April 2023).
Stål, T., Reading, A. M., Halpin, J. A., and Whittaker, J. M.: Antarctic geothermal heat flow model: Aq1, Geochem. Geophys. Geosyst., 22, e2020GC009428, https://doi.org/10.1029/2020GC009428, 2021.
Studinger, M., Bell, R. E., Karner, G. D., Tikku, A. A., Holt, J. W., Morse, D. L., Richter, T. G., Kempf, S. D., Peters, M. E., Blankenship, D. D., Sweeney, R. E., and Rystrom, V. L.: Ice cover, landscape setting, and geological framework of Lake Vostok, East Antarctica, Earth Planet. Sc. Lett., 205, 195–210, https://doi.org/10.1016/S0012-821X(02)01041-5, 2003.
Talalay, P., Li, Y., Augustin, L., Clow, G. D., Hong, J., Lefebvre, E., Markov, A., Motoyama, H., and Ritz, C.: Geothermal heat flux from measured temperature profiles in deep ice boreholes in Antarctica, The Cryosphere, 14, 4021–4037, https://doi.org/10.5194/tc-14-4021-2020, 2020.
Van Liefferinge, B. and Pattyn, F.: Using ice-flow models to evaluate potential sites of million year-old ice in Antarctica, Clim. Past, 9, 2335–2345, https://doi.org/10.5194/cp-9-2335-2013, 2013.
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.
Wolovick, M. J., Moore, J. C., and Zhao, L.: Joint inversion for surface accumulation rate and geothermal heat flow from ice-penetrating radar observations at Dome A, East Antarctica. Part I: model description, data constraints, and inversion results, J. Geophys. Res.-Earth, 126, e2020JF005937, https://doi.org/10.1029/2020JF005937, 2021.
Wright, A. and Siegert, M.: A fourth inventory of Antarctic subglacial lakes, Antarct. Sci., 24, 659–664, https://doi.org/10.1017/S095410201200048X, 2012.
Wright, A. P., Young, D. A., Roberts, J. L., Schroeder, D. M., Bamber, J. L., Dowdeswell, J. A., Young, N. W., Le Brocq, A. M., Warner, R. C., Payne, A. J., Blankenship, D. D., Van Ommen, T. D., and Siegert, M. J.: Evidence of a hydrological connection between the ice divide and ice sheet margin in the Aurora Subglacial Basin, East Antarctica, J. Geophys. Res., 117, 2011JF002066, https://doi.org/10.1029/2011JF002066, 2012.
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, Phil. Trans. R. Soc. A., 374, 20140297, https://doi.org/10.1098/rsta.2014.0297, 2016.
Zhao, C., Gladstone, R. M., Warner, R. C., King, M. A., Zwinger, T., and Morlighem, M.: Basal friction of Fleming Glacier, Antarctica – Part 1: Sensitivity of inversion to temperature and bedrock uncertainty, The Cryosphere, 12, 2637–2652, https://doi.org/10.5194/tc-12-2637-2018, 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.
Short summary
Geothermal heat flux (GHF) is an important factor affecting the basal thermal environment of an ice sheet and crucial for its dynamics. But it is poorly defined for the Antarctic ice sheet. We simulate the basal temperature and basal melting rate with eight different GHF datasets. We use specularity content as a two-sided constraint to discriminate between local wet or dry basal conditions. Two medium-magnitude GHF distribution maps rank well, showing that most of the inland bed area is frozen.
Geothermal heat flux (GHF) is an important factor affecting the basal thermal environment of an...
