Articles | Volume 19, issue 10
https://doi.org/10.5194/tc-19-4327-2025
© Author(s) 2025. 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-19-4327-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Brief communication
| 
07 Oct 2025
Brief communication |
| 07 Oct 2025
| 07 Oct 2025
Brief communication: Enabling open cryosphere research with Ghub
Department of Earth Sciences, State University of New York at Buffalo, Buffalo, NY, 14260, USA
Berkeley Geochronology Center, Berkeley, CA, 94709, USA
Sophie A. Goliber
Department of Earth Sciences, State University of New York at Buffalo, Buffalo, NY, 14260, USA
Renette Jones-Ivey
Department of Earth Sciences, State University of New York at Buffalo, Buffalo, NY, 14260, USA
Justin Quinn
NASA Jet Propulsion Laboratory, La Canada Flintridge, CA, 91011, USA
Abani Patra
Department of Computer Science, Tufts University, Medford, MA, 02155, USA
Kristin Poinar
Department of Earth Sciences, State University of New York at Buffalo, Buffalo, NY, 14260, USA
RENEW Institute, State University of New York at Buffalo, Buffalo, NY, 14260, USA
Sophie Nowicki
Department of Earth Sciences, State University of New York at Buffalo, Buffalo, NY, 14260, USA
RENEW Institute, State University of New York at Buffalo, Buffalo, NY, 14260, USA
Beata M. Csatho
Department of Earth Sciences, State University of New York at Buffalo, Buffalo, NY, 14260, USA
Jason P. Briner
Department of Earth Sciences, State University of New York at Buffalo, Buffalo, NY, 14260, USA
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Joseph P. Tulenko, Greg Balco, Michael A. Clynne, and L. J. Patrick Muffler
Geochronology, 6, 639–652, https://doi.org/10.5194/gchron-6-639-2024, https://doi.org/10.5194/gchron-6-639-2024, 2024
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Cosmogenic nuclide exposure dating is an exceptional tool for reconstructing glacier histories, but reconstructions based on common target nuclides (e.g., 10Be) can be costly and time-consuming to generate. Here, we present a cost-effective proof-of-concept 21Ne exposure age chronology from Lassen Volcanic National Park, CA, USA, that broadly agrees with nearby 10Be chronologies but at lower precision.
Joseph P. Tulenko, Jason P. Briner, Nicolás E. Young, and Joerg M. Schaefer
Clim. Past, 20, 625–636, https://doi.org/10.5194/cp-20-625-2024, https://doi.org/10.5194/cp-20-625-2024, 2024
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We take advantage of a site in Alaska – where climate records are limited and a former alpine glacier deposited a dense sequence of moraines spanning the full deglaciation – to construct a proxy summer temperature record. Building on age constraints for moraines in the valley, we reconstruct paleo-glacier surfaces and estimate the summer temperatures (relative to the Little Ice Age) for each moraine. The record suggests that the influence of North Atlantic climate forcing extended to Alaska.
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Clim. Past, 20, 91–106, https://doi.org/10.5194/cp-20-91-2024, https://doi.org/10.5194/cp-20-91-2024, 2024
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Available data suggest that Alaska was not as cold as many of the high-latitude areas of the Northern Hemisphere during the Last Ice Age. These results come from isolated climate records, climate models, and data synthesis projects. We used the extents of mountain glaciers during the Last Ice Age and Little Ice Age to show precipitation gradients across Alaska and provide temperature data from across the whole state. Our findings support a relatively warm Alaska during the Last Ice Age.
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EGUsphere, https://doi.org/10.5194/egusphere-2025-2780, https://doi.org/10.5194/egusphere-2025-2780, 2025
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We investigated retreat of the Greenland Ice Sheet during the last deglaciation by dating glacial deposits exposed as the ice margin retreated. Our results from eastern and northeastern Greenland reveal ice margin retreat rates of 43 m/yr and 28 m/yr at two marine-terminating outlet glaciers. These retreat rates are consistent with late glacial and Holocene estimates across East Greenland, and are comparable to modern retreat rates observed in northeastern and northwestern Greenland.
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The Cryosphere, 19, 2067–2086, https://doi.org/10.5194/tc-19-2067-2025, https://doi.org/10.5194/tc-19-2067-2025, 2025
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Understanding the history and drivers of Greenland Ice Sheet change is important for forecasting future ice sheet retreat. We combined geologic mapping and cosmogenic nuclide measurements to investigate how the Greenland Ice Sheet formed the landscape of Inglefield Land, northwestern Greenland. We found that Inglefield Land was covered by warm- and cold-based ice during multiple glacial cycles and that much of Inglefield Land is an ancient landscape.
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Gavin A. Schmidt, Kenneth D. Mankoff, Jonathan L. Bamber, Dustin Carroll, David M. Chandler, Violaine Coulon, Benjamin J. Davison, Matthew H. England, Paul R. Holland, Nicolas C. Jourdain, Qian Li, Juliana M. Marson, Pierre Mathiot, Clive R. McMahon, Twila A. Moon, Ruth Mottram, Sophie Nowicki, Anne Olivé Abelló, Andrew G. Pauling, Thomas Rackow, and Damien Ringeisen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1940, https://doi.org/10.5194/egusphere-2025-1940, 2025
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The impact of increasing mass loss from the Greenland and Antarctic ice sheets has not so far been included in historical climate model simulations. This paper describes the protocols and data available for modeling groups to add this anomalous freshwater to their ocean modules to better represent the impacts of these fluxes on ocean circulation, sea ice, salinity and sea level.
Elaine T. Spiller, Luke A. McGuire, Palak Patel, Abani Patra, and E. Bruce Pitman
EGUsphere, https://doi.org/10.22541/essoar.173687440.07138680/v1, https://doi.org/10.22541/essoar.173687440.07138680/v1, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Fire in steep landscapes increases the potential for debris flows that can develop during intense rainstorms. To explore possible debris flow hazards, we utilize a computational model of the physical processes of debris flow initiation and runout. Such process-based models are computationally intensive and of limited use in rapid hazard assessments. Thus we build statistical surrogate of these physical models to examine how inundation footprints vary with rainfall intensity and time since fire.
Peter Van Katwyk, Baylor Fox-Kemper, Sophie Nowicki, Hélène Seroussi, and Karianne J. Bergen
EGUsphere, https://doi.org/10.5194/egusphere-2025-870, https://doi.org/10.5194/egusphere-2025-870, 2025
Preprint archived
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We present ISEFlow, a machine learning emulator that predicts how the melting of the Antarctic and Greenland ice sheets will contribute to sea level. ISEFlow is fast and accurate, allowing scientists to explore different climate scenarios with greater confidence. ISEFlow distinguishes between high and low emissions scenarios, helping us understand how today’s choices impact future sea levels. ISEFlow supports more reliable climate predictions and helps scientists study the future of ice sheets.
James F. O'Neill, Tamsin L. Edwards, Daniel F. Martin, Courtney Shafer, Stephen L. Cornford, Hélène L. Seroussi, Sophie Nowicki, Mira Adhikari, and Lauren J. Gregoire
The Cryosphere, 19, 541–563, https://doi.org/10.5194/tc-19-541-2025, https://doi.org/10.5194/tc-19-541-2025, 2025
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We use an ice sheet model to simulate the Antarctic contribution to sea level over the 21st century under a range of future climates and varying how sensitive the ice sheet is to different processes. We find that ocean temperatures increase and more snow falls on the ice sheet under stronger warming scenarios. When the ice sheet is sensitive to ocean warming, ocean melt-driven loss exceeds snowfall-driven gains, meaning that the sea level contribution is greater with more climate warming.
Joseph P. Tulenko, Greg Balco, Michael A. Clynne, and L. J. Patrick Muffler
Geochronology, 6, 639–652, https://doi.org/10.5194/gchron-6-639-2024, https://doi.org/10.5194/gchron-6-639-2024, 2024
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Cosmogenic nuclide exposure dating is an exceptional tool for reconstructing glacier histories, but reconstructions based on common target nuclides (e.g., 10Be) can be costly and time-consuming to generate. Here, we present a cost-effective proof-of-concept 21Ne exposure age chronology from Lassen Volcanic National Park, CA, USA, that broadly agrees with nearby 10Be chronologies but at lower precision.
Beata Csatho, Tony Schenk, and Tom Neumann
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-3-2024, 83–88, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-83-2024, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-83-2024, 2024
Benjamin Reynolds, Sophie Nowicki, and Kristin Poinar
EGUsphere, https://doi.org/10.5194/egusphere-2024-2424, https://doi.org/10.5194/egusphere-2024-2424, 2024
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Stress in glaciers, ice sheets, and ice shelves causes crevasses, which are important drivers of retreat and sea level rise. We find that different assumptions found in the literature lead to significantly (up to a factor of two) different crevasse depths and recommend a calculation based on observed ice flow patterns. We find that other stress calculations likely overpredict ice shelf vulnerability to hydrofracture.
Benjamin A. Keisling, Joerg M. Schaefer, Robert M. DeConto, Jason P. Briner, Nicolás E. Young, Caleb K. Walcott, Gisela Winckler, Allie Balter-Kennedy, and Sridhar Anandakrishnan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2427, https://doi.org/10.5194/egusphere-2024-2427, 2024
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Understanding how much the Greenland ice sheet melted in response to past warmth helps better predicting future sea-level change. Here we present a framework for using numerical ice-sheet model simulations to provide constraints on how much mass the ice sheet loses before different areas become ice-free. As observations from subglacial archives become more abundant, this framework can guide subglacial sampling efforts to gain the most robust information about past ice-sheet geometries.
Karlee K. Prince, Jason P. Briner, Caleb K. Walcott, Brooke M. Chase, Andrew L. Kozlowski, Tammy M. Rittenour, and Erica P. Yang
Geochronology, 6, 409–427, https://doi.org/10.5194/gchron-6-409-2024, https://doi.org/10.5194/gchron-6-409-2024, 2024
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We fill a spatial data gap in the ice sheet retreat history of the Laurentide Ice Sheet after the Last Glacial Maximum and investigate a hypothesis that the ice sheet re-advanced into western New York, USA, at ~13 ka. With radiocarbon and optically stimulated luminescence (OSL) dating, we find that ice began retreating from its maximum extent after 20 ka, but glacial ice persisted in glacial landforms until ~15–14 ka when they finally stabilized. We find no evidence of a re-advance at ~13 ka.
Joseph P. Tulenko, Jason P. Briner, Nicolás E. Young, and Joerg M. Schaefer
Clim. Past, 20, 625–636, https://doi.org/10.5194/cp-20-625-2024, https://doi.org/10.5194/cp-20-625-2024, 2024
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We take advantage of a site in Alaska – where climate records are limited and a former alpine glacier deposited a dense sequence of moraines spanning the full deglaciation – to construct a proxy summer temperature record. Building on age constraints for moraines in the valley, we reconstruct paleo-glacier surfaces and estimate the summer temperatures (relative to the Little Ice Age) for each moraine. The record suggests that the influence of North Atlantic climate forcing extended to Alaska.
Caleb K. Walcott, Jason P. Briner, Joseph P. Tulenko, and Stuart M. Evans
Clim. Past, 20, 91–106, https://doi.org/10.5194/cp-20-91-2024, https://doi.org/10.5194/cp-20-91-2024, 2024
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Available data suggest that Alaska was not as cold as many of the high-latitude areas of the Northern Hemisphere during the Last Ice Age. These results come from isolated climate records, climate models, and data synthesis projects. We used the extents of mountain glaciers during the Last Ice Age and Little Ice Age to show precipitation gradients across Alaska and provide temperature data from across the whole state. Our findings support a relatively warm Alaska during the Last Ice Age.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
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Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Dominik Fahrner, Donald Slater, Aman KC, Claudia Cenedese, David A. Sutherland, Ellyn Enderlin, Femke de Jong, Kristian K. Kjeldsen, Michael Wood, Peter Nienow, Sophie Nowicki, and Till Wagner
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-411, https://doi.org/10.5194/essd-2023-411, 2023
Preprint withdrawn
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Marine-terminating glaciers can lose mass through frontal ablation, which comprises submarine and surface melting, and iceberg calving. We estimate frontal ablation for 49 marine-terminating glaciers in Greenland by combining existing, satellite derived data and calculating volume change near the glacier front over time. The dataset offers exciting opportunities to study the influence of climate forcings on marine-terminating glaciers in Greenland over multi-decadal timescales.
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
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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.
Celia Trunz, Kristin Poinar, Lauren C. Andrews, Matthew D. Covington, Jessica Mejia, Jason Gulley, and Victoria Siegel
The Cryosphere, 17, 5075–5094, https://doi.org/10.5194/tc-17-5075-2023, https://doi.org/10.5194/tc-17-5075-2023, 2023
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Models simulating water pressure variations at the bottom of glaciers must use large storage parameters to produce realistic results. Whether that storage occurs englacially (in moulins) or subglacially is a matter of debate. Here, we directly simulate moulin volume to constrain the storage there. We find it is not enough. Instead, subglacial processes, including basal melt and input from upstream moulins, must be responsible for stabilizing these water pressure fluctuations.
Gifford H. Miller, Simon L. Pendleton, Alexandra Jahn, Yafang Zhong, John T. Andrews, Scott J. Lehman, Jason P. Briner, Jonathan H. Raberg, Helga Bueltmann, Martha Raynolds, Áslaug Geirsdóttir, and John R. Southon
Clim. Past, 19, 2341–2360, https://doi.org/10.5194/cp-19-2341-2023, https://doi.org/10.5194/cp-19-2341-2023, 2023
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Receding Arctic ice caps reveal moss killed by earlier ice expansions; 186 moss kill dates from 71 ice caps cluster at 250–450, 850–1000 and 1240–1500 CE and continued expanding 1500–1880 CE, as recorded by regions of sparse vegetation cover, when ice caps covered > 11 000 km2 but < 100 km2 at present. The 1880 CE state approached conditions expected during the start of an ice age; climate models suggest this was only reversed by anthropogenic alterations to the planetary energy balance.
Denis Felikson, Sophie Nowicki, Isabel Nias, Beata Csatho, Anton Schenk, Michael J. Croteau, and Bryant Loomis
The Cryosphere, 17, 4661–4673, https://doi.org/10.5194/tc-17-4661-2023, https://doi.org/10.5194/tc-17-4661-2023, 2023
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We narrow the spread in model simulations of the Greenland Ice Sheet using velocity change, dynamic thickness change, and mass change observations. We find that the type of observation chosen can lead to significantly different calibrated probability distributions. Further work is required to understand how to best calibrate ensembles of ice sheet simulations because this will improve probability distributions of projected sea-level rise, which is crucial for coastal planning and adaptation.
Brandon L. Graham, Jason P. Briner, Nicolás E. Young, Allie Balter-Kennedy, Michele Koppes, Joerg M. Schaefer, Kristin Poinar, and Elizabeth K. Thomas
The Cryosphere, 17, 4535–4547, https://doi.org/10.5194/tc-17-4535-2023, https://doi.org/10.5194/tc-17-4535-2023, 2023
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Glacial erosion is a fundamental process operating on Earth's surface. Two processes of glacial erosion, abrasion and plucking, are poorly understood. We reconstructed rates of abrasion and quarrying in Greenland. We derive a total glacial erosion rate of 0.26 ± 0.16 mm per year. We also learned that erosion via these two processes is about equal. Because the site is similar to many other areas covered by continental ice sheets, these results may be applied to many places on Earth.
Whyjay Zheng, Shashank Bhushan, Maximillian Van Wyk De Vries, William Kochtitzky, David Shean, Luke Copland, Christine Dow, Renette Jones-Ivey, and Fernando Pérez
The Cryosphere, 17, 4063–4078, https://doi.org/10.5194/tc-17-4063-2023, https://doi.org/10.5194/tc-17-4063-2023, 2023
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We design and propose a method that can evaluate the quality of glacier velocity maps. The method includes two numbers that we can calculate for each velocity map. Based on statistics and ice flow physics, velocity maps with numbers close to the recommended values are considered to have good quality. We test the method using the data from Kaskawulsh Glacier, Canada, and release an open-sourced software tool called GLAcier Feature Tracking testkit (GLAFT) to help users assess their velocity maps.
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
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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.
Jason P. Briner, Caleb K. Walcott, Joerg M. Schaefer, Nicolás E. Young, Joseph A. MacGregor, Kristin Poinar, Benjamin A. Keisling, Sridhar Anandakrishnan, Mary R. Albert, Tanner Kuhl, and Grant Boeckmann
The Cryosphere, 16, 3933–3948, https://doi.org/10.5194/tc-16-3933-2022, https://doi.org/10.5194/tc-16-3933-2022, 2022
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The 7.4 m of sea level equivalent stored as Greenland ice is getting smaller every year. The uncertain trajectory of ice loss could be better understood with knowledge of the ice sheet's response to past climate change. Within the bedrock below the present-day ice sheet is an archive of past ice-sheet history. We analyze all available data from Greenland to create maps showing where on the ice sheet scientists can drill, using currently available drills, to obtain sub-ice materials.
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
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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.
Lauren C. Andrews, Kristin Poinar, and Celia Trunz
The Cryosphere, 16, 2421–2448, https://doi.org/10.5194/tc-16-2421-2022, https://doi.org/10.5194/tc-16-2421-2022, 2022
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We introduce a model for moulin geometry motivated by the wide range of sizes and shapes of explored moulins. Moulins comprise 10–14 % of the Greenland englacial–subglacial hydrologic system and act as time-varying water storage reservoirs. Moulin geometry can vary approximately 10 % daily and over 100 % seasonally. Moulin shape modulates the efficiency of the subglacial system that controls ice flow and should thus be included in hydrologic models.
Joshua K. Cuzzone, Nicolás E. Young, Mathieu Morlighem, Jason P. Briner, and Nicole-Jeanne Schlegel
The Cryosphere, 16, 2355–2372, https://doi.org/10.5194/tc-16-2355-2022, https://doi.org/10.5194/tc-16-2355-2022, 2022
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We use an ice sheet model to determine what influenced the Greenland Ice Sheet to retreat across a portion of southwestern Greenland during the Holocene (about the last 12 000 years). Our simulations, constrained by observations from geologic markers, show that atmospheric warming and ice melt primarily caused the ice sheet to retreat rapidly across this domain. We find, however, that iceberg calving at the interface where the ice meets the ocean significantly influenced ice mass change.
Caleb K. Walcott, Jason P. Briner, James F. Baichtal, Alia J. Lesnek, and Joseph M. Licciardi
Geochronology, 4, 191–211, https://doi.org/10.5194/gchron-4-191-2022, https://doi.org/10.5194/gchron-4-191-2022, 2022
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We present a record of ice retreat from the northern Alexander Archipelago, Alaska. During the last ice age (~ 26 000–19 000 years ago), these islands were covered by the Cordilleran Ice Sheet. We tested whether islands were ice-free during the last ice age for human migrants moving from Asia to the Americas. We found that these islands became ice-free between ~ 15 100 years ago and ~ 16 000 years ago, and thus these islands were not suitable for human habitation during the last ice age.
Douglas P. Steen, Joseph S. Stoner, Jason P. Briner, and Darrell S. Kaufman
Geochronology Discuss., https://doi.org/10.5194/gchron-2021-19, https://doi.org/10.5194/gchron-2021-19, 2021
Publication in GChron not foreseen
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Paleomagnetic data from Cascade Lake (Brooks Range, Alaska) extend the radiometric-based age model of the sedimentary sequence extending back 21 kyr. Correlated ages based on prominent features in paleomagnetic secular variations (PSV) diverge from the radiometric ages in the upper 1.6 m, by up to about 2000 years at around 4 ka. Four late Holocene cryptotephra in this section support the PSV chronology and suggest the influence of hard water or aged organic material.
Kristin Poinar and Lauren C. Andrews
The Cryosphere, 15, 1455–1483, https://doi.org/10.5194/tc-15-1455-2021, https://doi.org/10.5194/tc-15-1455-2021, 2021
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This study addresses Greenland supraglacial lake drainages. We analyze ice deformation associated with lake drainages over 18 summers to assess whether
precursorstrain-rate events consistently precede lake drainages. We find that currently available remote sensing data products cannot resolve these events, and thus we cannot predict future lake drainages. Thus, future avenues for evaluating this hypothesis will require major field-based GPS or photogrammetry efforts.
Svend Funder, Anita H. L. Sørensen, Nicolaj K. Larsen, Anders A. Bjørk, Jason P. Briner, Jesper Olsen, Anders Schomacker, Laura B. Levy, and Kurt H. Kjær
Clim. Past, 17, 587–601, https://doi.org/10.5194/cp-17-587-2021, https://doi.org/10.5194/cp-17-587-2021, 2021
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Cosmogenic 10Be exposure dates from outlying islets along 300 km of the SW Greenland coast indicate that, although affected by inherited 10Be, the ice margin here was retreating during the Younger Dryas. These results seem to be corroborated by recent studies elsewhere in Greenland. The apparent mismatch between temperatures and ice margin behaviour may be explained by the advection of warm water to the ice margin on the shelf and by increased seasonality, both caused by a weakened AMOC.
Nicolás E. Young, Alia J. Lesnek, Josh K. Cuzzone, Jason P. Briner, Jessica A. Badgeley, Alexandra Balter-Kennedy, Brandon L. Graham, Allison Cluett, Jennifer L. Lamp, Roseanne Schwartz, Thibaut Tuna, Edouard Bard, Marc W. Caffee, Susan R. H. Zimmerman, and Joerg M. Schaefer
Clim. Past, 17, 419–450, https://doi.org/10.5194/cp-17-419-2021, https://doi.org/10.5194/cp-17-419-2021, 2021
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Retreat of the Greenland Ice Sheet (GrIS) margin is exposing a bedrock landscape that holds clues regarding the timing and extent of past ice-sheet minima. We present cosmogenic nuclide measurements from recently deglaciated bedrock surfaces (the last few decades), combined with a refined chronology of southwestern Greenland deglaciation and model simulations of GrIS change. Results suggest that inland retreat of the southwestern GrIS margin was likely minimal in the middle to late Holocene.
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
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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.
Eric Larour, Lambert Caron, Mathieu Morlighem, Surendra Adhikari, Thomas Frederikse, Nicole-Jeanne Schlegel, Erik Ivins, Benjamin Hamlington, Robert Kopp, and Sophie Nowicki
Geosci. Model Dev., 13, 4925–4941, https://doi.org/10.5194/gmd-13-4925-2020, https://doi.org/10.5194/gmd-13-4925-2020, 2020
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ISSM-SLPS is a new projection system for future sea level that increases the resolution and accuracy of current projection systems and improves the way uncertainty is treated in such projections. This will pave the way for better inclusion of state-of-the-art results from existing intercomparison efforts carried out by the scientific community, such as GlacierMIP2 or ISMIP6, into sea-level projections.
Cited articles
Balco, G.: Technical note: A prototype transparent-middle-layer data management and analysis infrastructure for cosmogenic-nuclide exposure dating, Geochronology, 2, 169–175, https://doi.org/10.5194/gchron-2-169-2020, 2020.
Cicero, E., Poinar, K., Jones-Ivey, R., Petty, A. A., Sperhac, J. M., Patra, A., and Briner, J. P.: Firn aquifer water discharges into crevasses across Southeast Greenland, J. Glaciol., 69, 1379–1392, https://doi.org/10.1017/jog.2023.25, 2023.
Fox-Kemper, B., Hewitt, H. T., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S. S., Edwards, T. L., Golledge, N. R., Hemer, M., Kopp, R. E., Krinner, G., Mix, A., Notz, D., Nowicki, S., Nurhati, I. S., Ruiz, L., Sallée, J.-B., Slangen, A. B. A., and Yu, Y.: Ocean, Cryosphere and Sea Level Change, in: Climate Change 2021 – The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, 1211–1362, https://doi.org/10.1017/9781009157896.011, 2023.
Goliber, S. and Christian, J. E.: Visualizing Glacier/Ocean Change Edit (Version 1), The Ghub, https://doi.org/10.5281/zenodo.11236869, 2024.
Goliber, S., Paredes, M., Fendrock, M., Tulenko, J., Jones-Ivey, R., and Talebigheshlaghi, G.: Introduction to Python for Geoscientists – Ghub, Zenodo [data set], https://doi.org/10.5281/zenodo.14873178, 2025.
Hooijer, A. and Vernimmen, R.: Global LiDAR land elevation data reveal greatest sea-level rise vulnerability in the tropics, Nat. Commun., 12, 3592, https://doi.org/10.1038/s41467-021-23810-9, 2021.
Jones-Ivey, R., Sperhac, J., Poinar, K., and Petty, A.: ATM-Based Crevasse Detection & Extraction workflow, Zenodo [data set], https://doi.org/10.5281/zenodo.14873214, 2025.
Khrulev, C., Aschwanden, A., Bueler, E., Brown, J., Maxwell, D., Albrecht, T., Reese, R., Mengel, M., Martin, M., Winkelmann, R., Zeitz, M., Levermann, A., Feldmann, J., Garbe, J., Haseloff, M., Seguinot, J., Hinck, S., Kleiner, T., Fischer, E., Damsgaard, A., Lingle, C., van Pelt, W., Ziemen, F., Shemonski, N., Mankoff, K., Kennedy, J., Blum, K., Habermann, M., DellaGiustina, D., Hock, R., Kreuzer, M., Degregori, E., and Schoell, S.: Parallel Ice Sheet Model (PISM), Zenodo [code], https://doi.org/10.5281/zenodo.10202029, 2023.
Koenig, L., Martin, S., Studinger, M., and Sonntag, J.: Polar Airborne Observations Fill Gap in Satellite Data, Eos Transactions American Geophysical Union, 91, 333–334, https://doi.org/10.1029/2010EO380002, 2010.
Leger, T. P. M., Clark, C. D., Huynh, C., Jones, S., Ely, J. C., Bradley, S. L., Diemont, C., and Hughes, A. L. C.: A Greenland-wide empirical reconstruction of paleo ice sheet retreat informed by ice extent markers: PaleoGrIS version 1.0, Clim. Past, 20, 701–755, https://doi.org/10.5194/cp-20-701-2024, 2024.
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.
Morlighem, M., Williams, C. N., Rignot, E., An, L., Arndt, J. E., Bamber, J. L., Catania, G., Chauché, N., Dowdeswell, J. A., Dorschel, B., Fenty, I., Hogan, K., Howat, I., Hubbard, A., Jakobsson, M., Jordan, T. M., Kjeldsen, K. K., Millan, R., Mayer, L., Mouginot, J., Noël, B. P. Y., O'Cofaigh, C., Palmer, S., Rysgaard, S., Seroussi, H., Siegert, M. J., Slabon, P., Straneo, F., van den Broeke, M. R., Weinrebe, W., Wood, M., and Zinglersen, K. B.: BedMachine v3: Complete Bed Topography and Ocean Bathymetry Mapping of Greenland From Multibeam Echo Sounding Combined With Mass Conservation, Geophys. Res. Lett., 44, 11051–11061, https://doi.org/10.1002/2017GL074954, 2017.
Narkevic, A., Parmuzin, I., Csatho, B. M., and Babonis, G.: IceBridge ATM L2 Icessn Elevation, Slope, and Roughness, The Ghub [data set], https://theghub.org/resources/4734 (last access: 12 March 2025), 2021.
Nowicki, S., Simon, E., and ISMIP6 team: ISMIP6 21st Century Greenland Projections, The Ghub [data set], https://doi.org/10.5281/zenodo.11176023, 2024.
Nowicki, S. M. J., Payne, A., Larour, E., Seroussi, H., Goelzer, H., Lipscomb, W., Gregory, J., Abe-Ouchi, A., and Shepherd, A.: Ice Sheet Model Intercomparison Project (ISMIP6) contribution to CMIP6, Geosci. Model Dev., 9, 4521–4545, https://doi.org/10.5194/gmd-9-4521-2016, 2016.
Seroussi, H., Pelle, T., Lipscomb, W. H., Abe-Ouchi, A., Albrecht, T., Alvarez-Solas, J., Asay-Davis, X., Barre, J.-B., Berends, C. J., Bernales, J., Blasco, J., Caillet, J., Chandler, D. M., Coulon, V., Cullather, R., Dumas, C., Galton-Fenzi, B. K., Garbe, J., Gillet-Chaulet, F., Gladstone, R., Goelzer, H., Golledge, N., Greve, R., Gudmundsson, G. H., Han, H. K., Hillebrand, T. R., Hoffman, M. J., Huybrechts, P., Jourdain, N. C., Klose, A. K., Langebroek, P. M., Leguy, G. R., Lowry, D. P., Mathiot, P., Montoya, M., Morlighem, M., Nowicki, S., Pattyn, F., Payne, A. J., Quiquet, A., Reese, R., Robinson, A., Saraste, L., Simon, E. G., Sun, S., Twarog, J. P., Trusel, L. D., Urruty, B., Van Breedam, J., van de Wal, R. S. W., Wang, Y., Zhao, C., and Zwinger, T.: Evolution of the Antarctic Ice Sheet Over the Next Three Centuries From an ISMIP6 Model Ensemble, Earths Future, 12, e2024EF004561, https://doi.org/10.1029/2024EF004561, 2024.
Smith, B., Adusumilli, S., Csathó, B. M., Felikson, D., Fricker, H. A., Gardner, A. S., Holschuh, N., Lee, J., Nilsson, J., Paolo, F., Siegfried, M. R., Sutterley, T., and the ICESat-2 Science Team: ATLAS/ICESat-2 L3A Land Ice Height (ATL06, Version 6), Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/ATLAS/ATL06.006, 2023.
Snow, T., Millstein, J., Scheick, J., Sauthoff, W., Leong, W. J., Colliander, J., Pérez, F., Munroe, J., Felikson, D., Sutterley, T., and Siegfried, M.: CryoCloud JupyterBook, Zenodo [code], https://doi.org/10.5281/zenodo.7576602, 2023.
Sperhac, J. M., Poinar, K., Jones-Ivey, R., Briner, J., Csatho, B., Nowicki, S., Simon, E., Larour, E., Quinn, J., and Patra, A.: GHub: Building a glaciology gateway to unify a community, Concurrency and Computation: Practice and Experience, 33, e6130, https://doi.org/10.1002/cpe.6130, 2021.
Tulenko, J., Balco, G., Briner, J., and Goliber, S.: AskICE-D: A querying tool for the ICE-D project, Zenodo [code], https://doi.org/10.5281/zenodo.10659601, 2024.
Short summary
Ghub is an online platform that hosts tools, datasets, and educational resources related to ice sheet science. These resources are provided by ice sheet researchers and allow other researchers, students, educators, and interested members of the general public to analyze, visualize, and download datasets that researchers use to study past and present ice sheet behavior. We describe how users can interact with Ghub, showcase some available resources, and describe the future of the Ghub project.
Ghub is an online platform that hosts tools, datasets, and educational resources related to ice...
