Articles | Volume 18, issue 1
https://doi.org/10.5194/tc-18-387-2024
© 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-18-387-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Jan 2024
Research article |
| 26 Jan 2024
| 26 Jan 2024
Evaluating different geothermal heat-flow maps as basal boundary conditions during spin-up of the Greenland ice sheet
Tong Zhang
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
William Colgan
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Agnes Wansing
Institute of Geosciences, Kiel University, Kiel, Germany
Anja Løkkegaard
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Gunter Leguy
Climate and Global Dynamics Laboratory, NSF National Center for Atmospheric Research, Boulder, CO, USA
William H. Lipscomb
Climate and Global Dynamics Laboratory, NSF National Center for Atmospheric Research, Boulder, CO, USA
Cunde Xiao
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
Related authors
Chengyan Liu, Zhaomin Wang, Dake Chen, Xianxian Han, Hengling Leng, Xi Liang, Liangjun Yan, Xiang Li, Craig Stevens, Andrew Hogg, Kazuya Kusahara, Kaihe Yamazaki, Kay Ohshima, Meng Zhou, Xiao Cheng, Dongxiao Wang, Changming Dong, Jiping Liu, Qinghua Yang, Xichen Li, Ruibo Lei, Minghu Ding, Zhaoru Zhang, Dujuan Kang, Di Qi, Tongya Liu, Jihai Dong, Lu An, Ru Chen, Tong Zhang, Xiaoming Hu, Bo Han, Haibo Bi, Qi Shu, Longjiang Mu, Shiming Xu, Hu Yang, Hailong Liu, Tingfeng Dou, Zhixuan Feng, Lei Zheng, Xueyuan Tang, Guitao Shi, Yongqing Cai, Bingrui Li, Yang Wu, Xia Lin, Wenjin Sun, Yu Liu, Kai Yu, Yu Zhang, Weizeng Shao, Xiaoyu Wang, Shaojun Zheng, Chengyi Yuan, Chunxia Zhou, Jian Liu, Yang Liu, Yue Xia, Xiaoyu Pan, Jiabao Zeng, Kechen Liu, Jiahao Fan, Chen Cheng, and Qi Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-6487, https://doi.org/10.5194/egusphere-2025-6487, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We developed a high-resolution computer model to simulate how the ocean, sea ice, and ice shelves interact around Antarctica. This helps us understand their critical role in global climate and sea-level rise. Our model successfully captures essential features like major currents and seasonal ice changes. Despite some remaining biases, it provides a useful tool for predicting future changes in this vital and rapidly evolving region.
Tong Zhang, Wei Yang, Yuzhe Wang, Chuanxi Zhao, Qingyun Long, and Cunde Xiao
The Cryosphere, 19, 4487–4498, https://doi.org/10.5194/tc-19-4487-2025, https://doi.org/10.5194/tc-19-4487-2025, 2025
Short summary
Short summary
This study investigates the 2018 Sedongpu glacier detachment in Southeastern Tibet using a two-dimensional ice flow model that includes an ice stiffness and basal slip positive feedback mechanism. The model simulates rapid transitions in glacier flow, triggering detachment when ice stress exceeds yield strength. The results, including ice speed and duration, align with observations, demonstrating the potential for early warning of similar hazards in the region.
Minghu Ding, Tong Zhang, Diyi Yang, Ian Allison, Tingfeng Dou, and Cunde Xiao
The Cryosphere, 15, 4201–4206, https://doi.org/10.5194/tc-15-4201-2021, https://doi.org/10.5194/tc-15-4201-2021, 2021
Short summary
Short summary
Measurement of snow heat conductivity is essential to establish the energy balance between the atmosphere and firn, but it is still not clear in Antarctica. Here, we used data from three automatic weather stations located in different types of climate and evaluated nine schemes that were used to calculate the effective heat diffusivity of snow. The best solution was proposed. However, no conductivity–density relationship was optimal at all sites, and the performance of each varied with depth.
Chengyan Liu, Zhaomin Wang, Dake Chen, Xianxian Han, Hengling Leng, Xi Liang, Liangjun Yan, Xiang Li, Craig Stevens, Andrew Hogg, Kazuya Kusahara, Kaihe Yamazaki, Kay Ohshima, Meng Zhou, Xiao Cheng, Dongxiao Wang, Changming Dong, Jiping Liu, Qinghua Yang, Xichen Li, Ruibo Lei, Minghu Ding, Zhaoru Zhang, Dujuan Kang, Di Qi, Tongya Liu, Jihai Dong, Lu An, Ru Chen, Tong Zhang, Xiaoming Hu, Bo Han, Haibo Bi, Qi Shu, Longjiang Mu, Shiming Xu, Hu Yang, Hailong Liu, Tingfeng Dou, Zhixuan Feng, Lei Zheng, Xueyuan Tang, Guitao Shi, Yongqing Cai, Bingrui Li, Yang Wu, Xia Lin, Wenjin Sun, Yu Liu, Kai Yu, Yu Zhang, Weizeng Shao, Xiaoyu Wang, Shaojun Zheng, Chengyi Yuan, Chunxia Zhou, Jian Liu, Yang Liu, Yue Xia, Xiaoyu Pan, Jiabao Zeng, Kechen Liu, Jiahao Fan, Chen Cheng, and Qi Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-6487, https://doi.org/10.5194/egusphere-2025-6487, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We developed a high-resolution computer model to simulate how the ocean, sea ice, and ice shelves interact around Antarctica. This helps us understand their critical role in global climate and sea-level rise. Our model successfully captures essential features like major currents and seasonal ice changes. Despite some remaining biases, it provides a useful tool for predicting future changes in this vital and rapidly evolving region.
Robert S. Fausto, Penelope How, Baptiste Vandecrux, Mads C. Lund, Jason E. Box, Kenneth D. Mankoff, Signe B. Andersen, Dirk van As, Rasmus Bahbah, Michele Citterio, William Colgan, Henrik T. Jakobsgaard, Nanna B. Karlsson, Kristian K. Kjeldsen, Signe H. Larsen, Charlotte Olsen, Falk Oraschewski, Anja Rutishauser, Christopher L. Shields, Anne M. Solgaard, Ian T. Stevens, Synne H. Svendsen, Kirsty Langley, Alexandra Messerli, Anders A. Bjørk, Jonas K. Andersen, Jakob Abermann, Jakob Steiner, Rainer Prinz, Berhard Hynek, James M. Lea, Stephen Brough, and Andreas P. Ahlstrøm
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-687, https://doi.org/10.5194/essd-2025-687, 2025
Preprint under review for ESSD
Short summary
Short summary
In summary, the PROMICE | GC-NET AWS data product update represents a significant advancement in Arctic climate monitoring. Through enhanced station designs, state-of-the-art instrumentation, and a transparent, automated data processing workflow, the dataset offers an essential resource for studying the Greenland Ice Sheet and its periphery, validating climate models, and supporting global assessments of cryospheric change.
Heiko Goelzer, Petra M. Langebroek, Andreas Born, Stefan Hofer, Konstanze Haubner, Michele Petrini, Gunter Leguy, William H. Lipscomb, and Katherine Thayer-Calder
Geosci. Model Dev., 18, 7853–7867, https://doi.org/10.5194/gmd-18-7853-2025, https://doi.org/10.5194/gmd-18-7853-2025, 2025
Short summary
Short summary
On the backdrop of observed accelerating ice sheet mass loss over the last few decades, there is growing interest in the role of ice sheet changes in global climate projections. In this regard, we have coupled an Earth system model with an ice sheet model and have produced an initial set of climate projections including an interactive coupling with a dynamic Greenland ice sheet.
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.
Tong Zhang, Wei Yang, Yuzhe Wang, Chuanxi Zhao, Qingyun Long, and Cunde Xiao
The Cryosphere, 19, 4487–4498, https://doi.org/10.5194/tc-19-4487-2025, https://doi.org/10.5194/tc-19-4487-2025, 2025
Short summary
Short summary
This study investigates the 2018 Sedongpu glacier detachment in Southeastern Tibet using a two-dimensional ice flow model that includes an ice stiffness and basal slip positive feedback mechanism. The model simulates rapid transitions in glacier flow, triggering detachment when ice stress exceeds yield strength. The results, including ice speed and duration, align with observations, demonstrating the potential for early warning of similar hazards in the region.
Björn H. Heincke, Wolfgang Szwillus, Judith Freienstein, Jörg Ebbing, Carmen Gaina, Antonia Ruppel, Yixiati Dilixiati, and Agnes Wansing
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-448, https://doi.org/10.5194/essd-2025-448, 2025
Revised manuscript under review for ESSD
Short summary
Short summary
With over three-quarters of Greenland hidden beneath ice, direct geological observation is nearly impossible. Magnetic mapping provides now a passive and efficient geophysical method to image hidden subsurface features, offering a powerful tool for tectonic analysis and geological modeling in otherwise inaccessible regions. We have now developed a new magnetic anomaly map of Greenland using state-of-the-art technology providing new insight into Greenland’s buried geology.
Yifan Yang, Tingfeng Dou, Gaojie Xu, Rui Zhou, Bo Li, Letu Husi, Wenyu Wang, and Cunde Xiao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-447, https://doi.org/10.5194/essd-2025-447, 2025
Preprint under review for ESSD
Short summary
Short summary
We built an AI using China's Fengyun satellites (2009–2024) to map global atmospheric ice vital for climate. It processes tough data, making 3 public sets: orbital ice scans, monthly global maps, cloud masks. First long-term ice records over land/ocean from Chinese satellite. Offers unmatched coverage for decade climate studies despite precision limits.
Samar Minallah, William H. Lipscomb, Gunter Leguy, and Harry Zekollari
Geosci. Model Dev., 18, 5467–5486, https://doi.org/10.5194/gmd-18-5467-2025, https://doi.org/10.5194/gmd-18-5467-2025, 2025
Short summary
Short summary
We developed a new modeling framework within an Earth system model to study mountain glacier evolution under different climate scenarios, applied here to the European Alps. Substantial Alpine glacier mass loss is projected under current climate conditions, with near-total loss under further warming. This is the first use of a 3D, higher-order ice-flow model for regional glacier simulations, enabling assessment of coupled land ice–Earth system processes.
Tim van den Akker, William H. Lipscomb, Gunter R. Leguy, Willem Jan van de Berg, and Roderik S. W. van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2025-3380, https://doi.org/10.5194/egusphere-2025-3380, 2025
Short summary
Short summary
The Antarctic Ice Sheet is currently thinning, especially at major outlet glaciers. Including present-day thinning rates in models is a modeller's choice and can affect future projections. This study quantifies the impact of current imbalance on forced future projections, revealing strong regional and short-term (up to 2100) effects when these mass change rates are included.
Shfaqat A. Khan, Helene Seroussi, Mathieu Morlighem, William Colgan, Veit Helm, Gong Cheng, Danjal Berg, Valentina R. Barletta, Nicolaj K. Larsen, William Kochtitzky, Michiel van den Broeke, Kurt H. Kjær, Andy Aschwanden, Brice Noël, Jason E. Box, Joseph A. MacGregor, Robert S. Fausto, Kenneth D. Mankoff, Ian M. Howat, Kuba Oniszk, Dominik Fahrner, Anja Løkkegaard, Eigil Y. H. Lippert, Alicia Bråtner, and Javed Hassan
Earth Syst. Sci. Data, 17, 3047–3071, https://doi.org/10.5194/essd-17-3047-2025, https://doi.org/10.5194/essd-17-3047-2025, 2025
Short summary
Short summary
The surface elevation of the Greenland Ice Sheet is changing due to surface mass balance processes and ice dynamics, each exhibiting distinct spatiotemporal patterns. Here, we employ satellite and airborne altimetry data with fine spatial (1 km) and temporal (monthly) resolutions to document this spatiotemporal evolution from 2003 to 2023. This dataset of fine-resolution altimetry data in both space and time will support studies of ice mass loss and be useful for GIS ice sheet modeling.
Tim van den Akker, William H. Lipscomb, Gunter R. Leguy, Willem Jan van de Berg, and Roderik S. W. van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2025-441, https://doi.org/10.5194/egusphere-2025-441, 2025
Short summary
Short summary
Ice sheet models to simulate future sea level rise require parameterizations, like for the friction at the bedrock. Studies have quantified the effect of using different parameterizations, and some have concluded that projections are sensitive to the choice of the specific parameterization. In this study, we show that you can make an ice sheet model sensitive to the basal friction parameterization, and that for equally defendable modellers choices you can also make the model insensitive to this.
William H. Lipscomb, David Behar, and Monica Ainhorn Morrison
The Cryosphere, 19, 793–803, https://doi.org/10.5194/tc-19-793-2025, https://doi.org/10.5194/tc-19-793-2025, 2025
Short summary
Short summary
As communities try to adapt to climate change, they look for "actionable science" that can inform decision-making. There are risks in relying on novel results that are not yet accepted by the science community. We propose a practical criterion for determining which scientific claims are actionable. We show how premature acceptance of sea-level-rise predictions can lead to confusion and backtracking, and we suggest best practices for communication between scientists and adaptation planners.
Tim van den Akker, William H. Lipscomb, Gunter R. Leguy, Jorjo Bernales, Constantijn J. Berends, Willem Jan van de Berg, and Roderik S. W. van de Wal
The Cryosphere, 19, 283–301, https://doi.org/10.5194/tc-19-283-2025, https://doi.org/10.5194/tc-19-283-2025, 2025
Short summary
Short summary
In this study, we present an improved way of representing ice thickness change rates in an ice sheet model. We apply this method using two ice sheet models of the Antarctic Ice Sheet. We found that the two largest outlet glaciers on the Antarctic Ice Sheet, Thwaites Glacier and Pine Island Glacier, will collapse without further warming on a timescale of centuries. This would cause a sea level rise of about 1.2 m globally.
Michele Petrini, Meike D. W. Scherrenberg, Laura Muntjewerf, Miren Vizcaino, Raymond Sellevold, Gunter R. Leguy, William H. Lipscomb, and Heiko Goelzer
The Cryosphere, 19, 63–81, https://doi.org/10.5194/tc-19-63-2025, https://doi.org/10.5194/tc-19-63-2025, 2025
Short summary
Short summary
Anthropogenic warming is causing accelerated Greenland ice sheet melt. Here, we use a computer model to understand how prolonged warming and ice melt could threaten ice sheet stability. We find a threshold beyond which Greenland will lose more than 80 % of its ice over several thousand years, due to the interaction of surface and solid-Earth processes. Nearly complete Greenland ice sheet melt occurs when the ice margin disconnects from a region of high elevation in western Greenland.
Mira Berdahl, Gunter R. Leguy, William H. Lipscomb, Bette L. Otto-Bliesner, Esther C. Brady, Robert A. Tomas, Nathan M. Urban, Ian Miller, Harriet Morgan, and Eric J. Steig
Clim. Past, 20, 2349–2371, https://doi.org/10.5194/cp-20-2349-2024, https://doi.org/10.5194/cp-20-2349-2024, 2024
Short summary
Short summary
Studying climate conditions near the Antarctic ice sheet (AIS) during Earth’s past warm periods informs us about how global warming may influence AIS ice loss. Using a global climate model, we investigate climate conditions near the AIS during the Last Interglacial (129 to 116 kyr ago), a period with warmer global temperatures and higher sea level than today. We identify the orbital and freshwater forcings that could cause ice loss and probe the mechanisms that lead to warmer climate conditions.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
Short summary
Short summary
We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Judith Freienstein, Wolfgang Szwillus, Agnes Wansing, and Jörg Ebbing
Solid Earth, 15, 513–533, https://doi.org/10.5194/se-15-513-2024, https://doi.org/10.5194/se-15-513-2024, 2024
Short summary
Short summary
Geothermal heat flow influences ice sheet dynamics, making its investigation important for ice-covered regions. Here we evaluate the sparse measurements for their agreement with regional solid Earth models, as well as with a statistical approach. This shows that some points should be excluded from regional studies. In particular, the NGRIP point, which strongly influences heat flow maps and the distribution of high basal melts, should be statistically considered an outlier.
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.
Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
Short summary
Short summary
The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
Anja Løkkegaard, Kenneth D. Mankoff, Christian Zdanowicz, Gary D. Clow, Martin P. Lüthi, Samuel H. Doyle, Henrik H. Thomsen, David Fisher, Joel Harper, Andy Aschwanden, Bo M. Vinther, Dorthe Dahl-Jensen, Harry Zekollari, Toby Meierbachtol, Ian McDowell, Neil Humphrey, Anne Solgaard, Nanna B. Karlsson, Shfaqat A. Khan, Benjamin Hills, Robert Law, Bryn Hubbard, Poul Christoffersen, Mylène Jacquemart, Julien Seguinot, Robert S. Fausto, and William T. Colgan
The Cryosphere, 17, 3829–3845, https://doi.org/10.5194/tc-17-3829-2023, https://doi.org/10.5194/tc-17-3829-2023, 2023
Short summary
Short summary
This study presents a database compiling 95 ice temperature profiles from the Greenland ice sheet and peripheral ice caps. Ice viscosity and hence ice flow are highly sensitive to ice temperature. To highlight the value of the database in evaluating ice flow simulations, profiles from the Greenland ice sheet are compared to a modeled temperature field. Reoccurring discrepancies between modeled and observed temperatures provide insight on the difficulties faced when simulating ice temperatures.
René R. Wijngaard, Adam R. Herrington, William H. Lipscomb, Gunter R. Leguy, and Soon-Il An
The Cryosphere, 17, 3803–3828, https://doi.org/10.5194/tc-17-3803-2023, https://doi.org/10.5194/tc-17-3803-2023, 2023
Short summary
Short summary
We evaluate the ability of the Community Earth System Model (CESM2) to simulate cryospheric–hydrological variables, such as glacier surface mass balance (SMB), over High Mountain Asia (HMA) by using a global grid (~111 km) with regional refinement (~7 km) over HMA. Evaluations of two different simulations show that climatological biases are reduced, and glacier SMB is improved (but still too negative) by modifying the snow and glacier model and using an updated glacier cover dataset.
William Colgan, Christopher Shields, Pavel Talalay, Xiaopeng Fan, Austin P. Lines, Joshua Elliott, Harihar Rajaram, Kenneth Mankoff, Morten Jensen, Mira Backes, Yunchen Liu, Xianzhe Wei, Nanna B. Karlsson, Henrik Spanggård, and Allan Ø. Pedersen
Geosci. Instrum. Method. Data Syst., 12, 121–140, https://doi.org/10.5194/gi-12-121-2023, https://doi.org/10.5194/gi-12-121-2023, 2023
Short summary
Short summary
We describe a new drill for glaciers and ice sheets. Instead of drilling down into the ice, via mechanical action, our drill melts into the ice. Our goal is simply to pull a cable of temperature sensors on a one-way trip down to the ice–bed interface. Here, we describe the design and testing of our drill. Under laboratory conditions, our melt-tip drill has an efficiency of ∼ 35 % with a theoretical maximum penetration rate of ∼ 12 m h−1. Under field conditions, our efficiency is just ∼ 15 %.
Elizabeth R. Thomas, Diana O. Vladimirova, Dieter R. Tetzner, B. Daniel Emanuelsson, Nathan Chellman, Daniel A. Dixon, Hugues Goosse, Mackenzie M. Grieman, Amy C. F. King, Michael Sigl, Danielle G. Udy, Tessa R. Vance, Dominic A. Winski, V. Holly L. Winton, Nancy A. N. Bertler, Akira Hori, Chavarukonam M. Laluraj, Joseph R. McConnell, Yuko Motizuki, Kazuya Takahashi, Hideaki Motoyama, Yoichi Nakai, Franciéle Schwanck, Jefferson Cardia Simões, Filipe Gaudie Ley Lindau, Mirko Severi, Rita Traversi, Sarah Wauthy, Cunde Xiao, Jiao Yang, Ellen Mosely-Thompson, Tamara V. Khodzher, Ludmila P. Golobokova, and Alexey A. Ekaykin
Earth Syst. Sci. Data, 15, 2517–2532, https://doi.org/10.5194/essd-15-2517-2023, https://doi.org/10.5194/essd-15-2517-2023, 2023
Short summary
Short summary
The concentration of sodium and sulfate measured in Antarctic ice cores is related to changes in both sea ice and winds. Here we have compiled a database of sodium and sulfate records from 105 ice core sites in Antarctica. The records span all, or part, of the past 2000 years. The records will improve our understanding of how winds and sea ice have changed in the past and how they have influenced the climate of Antarctica over the past 2000 years.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
Short summary
Short summary
By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Constantijn J. Berends, Roderik S. W. van de Wal, Tim van den Akker, and William H. Lipscomb
The Cryosphere, 17, 1585–1600, https://doi.org/10.5194/tc-17-1585-2023, https://doi.org/10.5194/tc-17-1585-2023, 2023
Short summary
Short summary
The rate at which the Antarctic ice sheet will melt because of anthropogenic climate change is uncertain. Part of this uncertainty stems from processes occurring beneath the ice, such as the way the ice slides over the underlying bedrock.
Inversion methodsattempt to use observations of the ice-sheet surface to calculate how these sliding processes work. We show that such methods cannot fully solve this problem, so a substantial uncertainty still remains in projections of sea-level rise.
Mira Berdahl, Gunter Leguy, William H. Lipscomb, Nathan M. Urban, and Matthew J. Hoffman
The Cryosphere, 17, 1513–1543, https://doi.org/10.5194/tc-17-1513-2023, https://doi.org/10.5194/tc-17-1513-2023, 2023
Short summary
Short summary
Contributions to future sea level from the Antarctic Ice Sheet remain poorly constrained. One reason is that ice sheet model initialization methods can have significant impacts on how the ice sheet responds to future forcings. We investigate the impacts of two key parameters used during model initialization. We find that these parameter choices alone can impact multi-century sea level rise by up to 2 m, emphasizing the need to carefully consider these choices for sea level rise predictions.
Zhiheng Du, Jiao Yang, Lei Wang, Ninglian Wang, Anders Svensson, Zhen Zhang, Xiangyu Ma, Yaping Liu, Shimeng Wang, Jianzhong Xu, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5349–5365, https://doi.org/10.5194/essd-14-5349-2022, https://doi.org/10.5194/essd-14-5349-2022, 2022
Short summary
Short summary
A dataset of the radiogenic strontium and neodymium isotopic compositions from the three poles (the third pole, the Arctic, and Antarctica) were integrated to obtain new findings. The dataset enables us to map the standardized locations in the three poles, while the use of sorting criteria related to the sample type permits us to trace the dust sources and sinks. The purpose of this dataset is to try to determine the variable transport pathways of dust at three poles.
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
Short summary
Short summary
The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
Joseph A. MacGregor, Winnie Chu, William T. Colgan, Mark A. Fahnestock, Denis Felikson, Nanna B. Karlsson, Sophie M. J. Nowicki, and Michael Studinger
The Cryosphere, 16, 3033–3049, https://doi.org/10.5194/tc-16-3033-2022, https://doi.org/10.5194/tc-16-3033-2022, 2022
Short summary
Short summary
Where the bottom of the Greenland Ice Sheet is frozen and where it is thawed is not well known, yet knowing this state is increasingly important to interpret modern changes in ice flow there. We produced a second synthesis of knowledge of the basal thermal state of the ice sheet using airborne and satellite observations and numerical models. About one-third of the ice sheet’s bed is likely thawed; two-fifths is likely frozen; and the remainder is too uncertain to specify.
Mimmi Oksman, Anna Bang Kvorning, Signe Hillerup Larsen, Kristian Kjellerup Kjeldsen, Kenneth David Mankoff, William Colgan, Thorbjørn Joest Andersen, Niels Nørgaard-Pedersen, Marit-Solveig Seidenkrantz, Naja Mikkelsen, and Sofia Ribeiro
The Cryosphere, 16, 2471–2491, https://doi.org/10.5194/tc-16-2471-2022, https://doi.org/10.5194/tc-16-2471-2022, 2022
Short summary
Short summary
One of the questions facing the cryosphere community today is how increasing runoff from the Greenland Ice Sheet impacts marine ecosystems. To address this, long-term data are essential. Here, we present multi-site records of fjord productivity for SW Greenland back to the 19th century. We show a link between historical freshwater runoff and productivity, which is strongest in the inner fjord – influenced by marine-terminating glaciers – where productivity has increased since the late 1990s.
William Colgan, Agnes Wansing, Kenneth Mankoff, Mareen Lösing, John Hopper, Keith Louden, Jörg Ebbing, Flemming G. Christiansen, Thomas Ingeman-Nielsen, Lillemor Claesson Liljedahl, Joseph A. MacGregor, Árni Hjartarson, Stefan Bernstein, Nanna B. Karlsson, Sven Fuchs, Juha Hartikainen, Johan Liakka, Robert S. Fausto, Dorthe Dahl-Jensen, Anders Bjørk, Jens-Ove Naslund, Finn Mørk, Yasmina Martos, Niels Balling, Thomas Funck, Kristian K. Kjeldsen, Dorthe Petersen, Ulrik Gregersen, Gregers Dam, Tove Nielsen, Shfaqat A. Khan, and Anja Løkkegaard
Earth Syst. Sci. Data, 14, 2209–2238, https://doi.org/10.5194/essd-14-2209-2022, https://doi.org/10.5194/essd-14-2209-2022, 2022
Short summary
Short summary
We assemble all available geothermal heat flow measurements collected in and around Greenland into a new database. We use this database of point measurements, in combination with other geophysical datasets, to model geothermal heat flow in and around Greenland. Our geothermal heat flow model is generally cooler than previous models of Greenland, especially in southern Greenland. It does not suggest any high geothermal heat flows resulting from Icelandic plume activity over 50 million years ago.
Adrian K. Turner, William H. Lipscomb, Elizabeth C. Hunke, Douglas W. Jacobsen, Nicole Jeffery, Darren Engwirda, Todd D. Ringler, and Jonathan D. Wolfe
Geosci. Model Dev., 15, 3721–3751, https://doi.org/10.5194/gmd-15-3721-2022, https://doi.org/10.5194/gmd-15-3721-2022, 2022
Short summary
Short summary
We present the dynamical core of the MPAS-Seaice model, which uses a mesh consisting of a Voronoi tessellation with polygonal cells. Such a mesh allows variable mesh resolution in different parts of the domain and the focusing of computational resources in regions of interest. We describe the velocity solver and tracer transport schemes used and examine errors generated by the model in both idealized and realistic test cases and examine the computational efficiency of the model.
Alexander Robinson, Daniel Goldberg, and William H. Lipscomb
The Cryosphere, 16, 689–709, https://doi.org/10.5194/tc-16-689-2022, https://doi.org/10.5194/tc-16-689-2022, 2022
Short summary
Short summary
Here we investigate the numerical stability of several commonly used methods in order to determine which of them are capable of resolving the complex physics of the ice flow and are also computationally efficient. We find that the so-called DIVA solver outperforms the others. Its representation of the physics is consistent with more complex methods, while it remains computationally efficient at high resolution.
Kenneth D. Mankoff, Xavier Fettweis, Peter L. Langen, Martin Stendel, Kristian K. Kjeldsen, Nanna B. Karlsson, Brice Noël, Michiel R. van den Broeke, Anne Solgaard, William Colgan, Jason E. Box, Sebastian B. Simonsen, Michalea D. King, Andreas P. Ahlstrøm, Signe Bech Andersen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, https://doi.org/10.5194/essd-13-5001-2021, 2021
Short summary
Short summary
We estimate the daily mass balance and its components (surface, marine, and basal mass balance) for the Greenland ice sheet. Our time series begins in 1840 and has annual resolution through 1985 and then daily from 1986 through next week. Results are operational (updated daily) and provided for the entire ice sheet or by commonly used regions or sectors. This is the first input–output mass balance estimate to include the basal mass balance.
Minghu Ding, Tong Zhang, Diyi Yang, Ian Allison, Tingfeng Dou, and Cunde Xiao
The Cryosphere, 15, 4201–4206, https://doi.org/10.5194/tc-15-4201-2021, https://doi.org/10.5194/tc-15-4201-2021, 2021
Short summary
Short summary
Measurement of snow heat conductivity is essential to establish the energy balance between the atmosphere and firn, but it is still not clear in Antarctica. Here, we used data from three automatic weather stations located in different types of climate and evaluated nine schemes that were used to calculate the effective heat diffusivity of snow. The best solution was proposed. However, no conductivity–density relationship was optimal at all sites, and the performance of each varied with depth.
Robert S. Fausto, Dirk van As, Kenneth D. Mankoff, Baptiste Vandecrux, Michele Citterio, Andreas P. Ahlstrøm, Signe B. Andersen, William Colgan, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, Søren Nielsen, Allan Ø. Pedersen, Christopher L. Shields, Anne M. Solgaard, and Jason E. Box
Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, https://doi.org/10.5194/essd-13-3819-2021, 2021
Short summary
Short summary
The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheet properties since 2007. Here, we present our data product from weather and ice sheet measurements from a network of automatic weather stations mainly located in the melt area of the ice sheet. Currently the PROMICE automatic weather station network includes 25 instrumented sites in Greenland.
Gunter R. Leguy, William H. Lipscomb, and Xylar S. Asay-Davis
The Cryosphere, 15, 3229–3253, https://doi.org/10.5194/tc-15-3229-2021, https://doi.org/10.5194/tc-15-3229-2021, 2021
Short summary
Short summary
We present numerical features of the Community Ice Sheet Model in representing ocean termini glaciers. Using idealized test cases, we show that applying melt in a partly grounded cell is beneficial, in contrast to recent studies. We confirm that parameterizing partly grounded cells yields accurate ice sheet representation at a grid resolution of ~2 km (arguably 4 km), allowing ice sheet simulations at a continental scale. The choice of basal friction law also influences the ice flow.
Yetang Wang, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Shugui Hou, and Cunde Xiao
Earth Syst. Sci. Data, 13, 3057–3074, https://doi.org/10.5194/essd-13-3057-2021, https://doi.org/10.5194/essd-13-3057-2021, 2021
Short summary
Short summary
Accurate observation of surface mass balance (SMB) under climate change is essential for the reliable present and future assessment of Antarctic contribution to global sea level. This study presents a new quality-controlled dataset of Antarctic SMB observations at different temporal resolutions and is the first ice-sheet-scale compilation of multiple types of measurements. The dataset can be widely applied to climate model validation, remote sensing retrievals, and data assimilation.
Mira Berdahl, Gunter Leguy, William H. Lipscomb, and Nathan M. Urban
The Cryosphere, 15, 2683–2699, https://doi.org/10.5194/tc-15-2683-2021, https://doi.org/10.5194/tc-15-2683-2021, 2021
Short summary
Short summary
Antarctic ice shelves are vulnerable to warming ocean temperatures and have already begun thinning in response to increased basal melt rates. Sea level is expected to rise due to Antarctic contributions, but uncertainties in rise amount and timing remain largely unquantified. To facilitate uncertainty quantification, we use a high-resolution ice sheet model to build, test, and validate an ice sheet emulator and generate probabilistic sea level rise estimates for 100 and 200 years in the future.
Tingfeng Dou, Cunde Xiao, Jiping Liu, Qiang Wang, Shifeng Pan, Jie Su, Xiaojun Yuan, Minghu Ding, Feng Zhang, Kai Xue, Peter A. Bieniek, and Hajo Eicken
The Cryosphere, 15, 883–895, https://doi.org/10.5194/tc-15-883-2021, https://doi.org/10.5194/tc-15-883-2021, 2021
Short summary
Short summary
Rain-on-snow (ROS) events can accelerate the surface ablation of sea ice, greatly influencing the ice–albedo feedback. We found that spring ROS events have shifted to earlier dates over the Arctic Ocean in recent decades, which is correlated with sea ice melt onset in the Pacific sector and most Eurasian marginal seas. There has been a clear transition from solid to liquid precipitation, leading to a reduction in spring snow depth on sea ice by more than −0.5 cm per decade since the 1980s.
William H. Lipscomb, Gunter R. Leguy, Nicolas C. Jourdain, Xylar Asay-Davis, Hélène Seroussi, and Sophie Nowicki
The Cryosphere, 15, 633–661, https://doi.org/10.5194/tc-15-633-2021, https://doi.org/10.5194/tc-15-633-2021, 2021
Short summary
Short summary
This paper describes Antarctic climate change experiments in which the Community Ice Sheet Model is forced with ocean warming predicted by global climate models. Generally, ice loss begins slowly, accelerates by 2100, and then continues unabated, with widespread retreat of the West Antarctic Ice Sheet. The mass loss by 2500 varies from about 150 to 1300 mm of equivalent sea level rise, based on the predicted ocean warming and assumptions about how this warming drives melting beneath ice shelves.
Cited articles
Alley, R., Pollard, D., Parizek, B., Anandakrishnan, S., Pourpoint, M., Stevens, N., MacGregor, J., Christianson, K., Muto, A., and Holschuh, N.: Possible role for tectonics in the evolving stability of the Greenland Ice Sheet, J. Geophys. Res.-Earth, 124, 97–115, https://doi.org/10.1029/2018JF004714, 2019.
Artemieva, I. M.: Lithosphere thermal thickness and geothermal heat flux in Greenland from a new thermal isostasy method, Earth-Sci. Rev., 188, 469–481, https://doi.org/10.1016/j.earscirev.2018.10.015, 2019.
Aschwanden, A., Fahnestock, M., and Truffer, M.: Complex Greenland outlet glacier flow captured, Nat. Commun., 7, 10524, https://doi.org/10.1038/ncomms10524, 2016.
Bueler, E. and van Pelt, W.: Mass-conserving subglacial hydrology in the Parallel Ice Sheet Model version 0.6, Geosci. Model Dev., 8, 1613–1635, https://doi.org/10.5194/gmd-8-1613-2015, 2015.
Colgan, W., MacGregor, J., Mankoff, K., Haagenson, R., Rajaram, H., Martos, Y., Morlighem, M., Fahnestock, M., and Kjeldsen, K.: Topographic Correction of Geothermal Heat Flux in Greenland and Antarctica, J. Geophys. Res.-Earth, 126, e2020JF005598, https://doi.org/10.1029/2020JF005598, 2021.
Colgan, W., Wansing, A., Mankoff, K., Lösing, M., Hopper, J., Louden, K., Ebbing, J., Christiansen, F. G., Ingeman-Nielsen, T., Liljedahl, L. C., MacGregor, J. A., Hjartarson, Á., Bernstein, S., Karlsson, N. B., Fuchs, S., Hartikainen, J., Liakka, J., Fausto, R. S., Dahl-Jensen, D., Bjørk, A., Naslund, J.-O., Mørk, F., Martos, Y., Balling, N., Funck, T., Kjeldsen, K. K., Petersen, D., Gregersen, U., Dam, G., Nielsen, T., Khan, S. A., and Løkkegaard, A.: Greenland Geothermal Heat Flow Database and Map (Version 1), Earth Syst. Sci. Data, 14, 2209–2238, https://doi.org/10.5194/essd-14-2209-2022, 2022.
Cuffey, K. M. and Paterson, W. S. B.: The Physics of Glaciers, Elsevier, Burlington, ISBN 978-0-123-69461-4, 2010.
Fahnestock, M., Abdalati, W., Joughin, I., Brozena, J., and Gogineni, P.: High Geothermal Heat Flow, Basal Melt, and the Origin of Rapid Ice Flow in Central Greenland, Science, 294, 2338–2342, https://doi.org/10.1126/science.1065370, 2001.
Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., and Gallée, H.: Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model, The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, 2017.
Fox Maule, C., Purucker, M. E., and Olsen, N.: Inferring magnetic crustal thickness and geothermal heat flux from crustal magnetic field models, Danish Climate Centre Report, 9–09, 2009.
Fuchs, S., Beardsmore, G., Chiozzi, P., Gola, G., Gosnold, W., Harris, R., Jennings, S., Liu, S., Negrete-Aranda, R., Neumann, F., Norden, B., Poort, J., Rajver, D., Ray, L., Richards, M., Smith, J., Tanaka, A., and Verdoya, M.: A new database structure for the IHFC Global Heat Flow Database, International Journal of Terrestrial Heat Flow and Applied Geothermics, 22, 1–4, https://doi.org/10.31214/ijthfa.v4i1.62, 2021.
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.
Goldberg, D. N.: A variationally derived, depth-integrated approximation to a higher-order glaciological flow model, J. Glaciol., 57, 157–170, https://doi.org/10.3189/002214311795306763, 2011.
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 Journal, 3, 22–36, https://doi.org/10.20575/00000006, 2019.
Helsen, M. M., van de Berg, W. J., van de Wal, R. S. W., van den Broeke, M. R., and Oerlemans, J.: Coupled regional climate–ice-sheet simulation shows limited Greenland ice loss during the Eemian, Clim. Past, 9, 1773–1788, https://doi.org/10.5194/cp-9-1773-2013, 2013.
Hoffman, M. J., Perego, M., Price, S. F., Lipscomb, W. H., Zhang, T., Jacobsen, D., Tezaur, I., Salinger, A. G., Tuminaro, R., and Bertagna, L.: MPAS-Albany Land Ice (MALI): a variable-resolution ice sheet model for Earth system modeling using Voronoi grids, Geosci. Model Dev., 11, 3747–3780, https://doi.org/10.5194/gmd-11-3747-2018, 2018.
Hooke, R.: Principles of Glacier Mechanics, Cambridge University Press, ISBN 978-1108446075, 2019.
Jessop, A., Hobart, M., and Sclater, J.: The World Heat Flow Data Collection-1975, Geothermal Series Number 5, Geological Survey of Canada, Ottawa, Canada, https://doi.org/10013/epic.40176.d002, 1976.
Karlsson, N., Solgaard, A., Mankoff, K., Gillet-Chaulet, F., MacGregor, J., Box, J., Citterio, M., Colgan, W., Larsen, S., Kjeldsen, K., Korsgaard, N., Benn, D., Hewitt, I., and Fausto, R.: A first constraint on basal melt-water production of the Greenland ice sheet, Nat. Commun., 12, 3461, https://doi.org/10.1038/s41467-021-23739-z, 2021.
Leguy, G. R., Lipscomb, W. H., and Asay-Davis, X. S.: Marine ice sheet experiments with the Community Ice Sheet Model, The Cryosphere, 15, 3229–3253, https://doi.org/10.5194/tc-15-3229-2021, 2021.
Lipscomb, W. H., Price, S. F., Hoffman, M. J., Leguy, G. R., Bennett, A. R., Bradley, S. L., Evans, K. J., Fyke, J. G., Kennedy, J. H., Perego, M., Ranken, D. M., Sacks, W. J., Salinger, A. G., Vargo, L. J., and Worley, P. H.: Description and evaluation of the Community Ice Sheet Model (CISM) v2.1, Geosci. Model Dev., 12, 387–424, https://doi.org/10.5194/gmd-12-387-2019, 2019.
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.
Løkkegaard, A., Mankoff, K. D., Zdanowicz, C., Clow, G. D., Lüthi, M. P., Doyle, S. H., Thomsen, H. H., Fisher, D., Harper, J., Aschwanden, A., Vinther, B. M., Dahl-Jensen, D., Zekollari, H., Meierbachtol, T., McDowell, I., Humphrey, N., Solgaard, A., Karlsson, N. B., Khan, S. A., Hills, B., Law, R., Hubbard, B., Christoffersen, P., Jacquemart, M., Seguinot, J., Fausto, R. S., and Colgan, W. T.: Greenland and Canadian Arctic ice temperature profiles database, The Cryosphere, 17, 3829–3845, https://doi.org/10.5194/tc-17-3829-2023, 2023.
Lucazeau, F.: Analysis and Mapping of an Updated Terrestrial Heat Flow Data Set, Geochem. Geophy. Geosy., 20, 4001–4024, https://doi.org/10.1029/2019GC008389, 2019.
MacGregor, J., Fahnestock, M., Colgan, W., Larsen, N., Kjeldsen, K., and Welker, J.: The age of surface-exposed ice along the northern margin of the Greenland Ice Sheet, J. Glaciol., 66, 667–684, https://doi.org/10.1017/jog.2020.62, 2020.
MacGregor, J. A., Chu, W., Colgan, W. T., Fahnestock, M. A., Felikson, D., Karlsson, N. B., Nowicki, S. M. J., and Studinger, M.: GBaTSv2: a revised synthesis of the likely basal thermal state of the Greenland Ice Sheet, The Cryosphere, 16, 3033–3049, https://doi.org/10.5194/tc-16-3033-2022, 2022.
Martos, Y., Jordan, T., Catalán, M., Jordan, T., Bamber, J., and Vaughan, D.: Geothermal heat flux reveals the Iceland hotspot track underneath Greenland, Geophys. Res. Lett., 45, 8214–8222, https://doi.org/10.1029/2018GL078289, 2018.
Morlighem, M., Williams, C., Rignot, E., An, L., Arndt, J., Bamber, J., Catania, G., Chauché, N., Dowdeswell, J., Dorschel, B., Fenty, I., Hogan, K., Howat, I., Hubbard, A., Jakobsson, M., Jordan, T., Kjeldsen, K., Millan, R., Mayer, L., Mouginot, J., Noël, B., O'Cofaigh, C., Palmer, S., Rysgaard, S., Seroussi, H., Siegert, M., Slabon, P., Straneo, F., van den Broeke, M., Weinrebe, W., Wood, M., and Zinglersen, K.: BedMachine v3: Complete bed topography and ocean bathymetry mapping of Greenland from multi-beam echo sounding combined with mass conservation, Geophys. Res. Lett., 44, 11051–11061, https://doi.org/10.1002/2017GL074954, 2017.
Otto-Bliesner, B., Marshall, S., Overpeck, J., Miller, G., and Hu, A.: Simulating Arctic Climate Warmth and Icefield Retreat in the Last Interglaciation, Science, 311, 1751–1753, https://doi.org/10.1126/science.1120808, 2006.
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, 267–280, https://doi.org/10.1029/93RG01249, 1993.
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.
Quiquet, A., Ritz, C., Punge, H. J., and Salas y Mélia, D.: Greenland ice sheet contribution to sea level rise during the last interglacial period: a modelling study driven and constrained by ice core data, Clim. Past, 9, 353–366, https://doi.org/10.5194/cp-9-353-2013, 2013.
Rezvanbehbahani, S., Stearns, L., Kadivar, A., Walker, J., and van der Veen, C.: Predicting the Geothermal Heat Flux in Greenland: A Machine Learning Approach, Geophys. Res. Lett., 44, 12271–12279, https://doi.org/10.1002/2017GL075661, 2017.
Rogozhina, I., Petrunin, A., Vaughan, A., Steinberger, B., Johnson, J., Kaban, M., Calov, R., Rickers, F., Thomas, M., and Koulakov, I.: Melting at the base of the Greenland ice sheet explained by Iceland hotspot history, Nat. Geosci., 9, 366–369, https://doi.org/10.1038/ngeo2689, 2016.
Shapiro, N. and Ritzwoller, M.: 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.
Smith-Johnsen, S., de Fleurian, B., Schlegel, N., Seroussi, H., and Nisancioglu, K.: Exceptionally high heat flux needed to sustain the Northeast Greenland Ice Stream, The Cryosphere, 14, 841–854, https://doi.org/10.5194/tc-14-841-2020, 2020.
Stone, E. J., Lunt, D. J., Annan, J. D., and Hargreaves, J. C.: Quantification of the Greenland ice sheet contribution to Last Interglacial sea level rise, Clim. Past, 9, 621–639, https://doi.org/10.5194/cp-9-621-2013, 2013.
Tarasov, L. and Peltier, W. R.: Greenland glacial history, borehole constraints, and Eemian extent, J. Geophys. Res.-Sol. Ea., 108, 2143, https://doi.org/10.1029/2001JB001731, 2003.
van der Veen, C., Leftwich, T., Von Frese, R., Csatho, B., 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.
Weertman, J.: The Unsolved General Glacier Sliding Problem, J. Glaciol., 23, 97–115, https://doi.org/10.3189/S0022143000029762, 1979.
Zhang, T., Colgan, W., and Wansing, A.: Greenland Geothermal Heatflow, Zenodo [data set], https://doi.org/10.5281/zenodo.7891577, 2023.
Short summary
The geothermal heat flux determines how much heat enters from beneath the ice sheet, and thus impacts the temperature and the flow of the ice sheet. In this study we investigate how much geothermal heat flux impacts the initialization of the Greenland ice sheet. We use the Community Ice Sheet Model with two different initialization methods. We find a non-trivial influence of the choice of heat flow boundary conditions on the ice sheet initializations for further designs of ice sheet modeling.
The geothermal heat flux determines how much heat enters from beneath the ice sheet, and thus...
