Articles | Volume 18, issue 6
https://doi.org/10.5194/tc-18-2917-2024
© 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-18-2917-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Jun 2024
Research article |
| 25 Jun 2024
| 25 Jun 2024
Ice-shelf freshwater triggers for the Filchner–Ronne Ice Shelf melt tipping point in a global ocean–sea-ice model
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Carolyn Branecky Begeman
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Xylar S. Asay-Davis
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Darin Comeau
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Alice Barthel
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Stephen F. Price
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Jonathan D. Wolfe
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Related authors
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.
Trevor R. Hillebrand, Matthew J. Hoffman, Holly K. Han, Mauro Perego, Alexander O. Hager, Andrew Nolan, Xylar Asay-Davis, Stephen F. Price, Jerry Watkins, and Max Carlson
EGUsphere, https://doi.org/10.5194/egusphere-2025-3942, https://doi.org/10.5194/egusphere-2025-3942, 2025
Short summary
Short summary
We present new simulations that complement our contribution to the ISMIP6-Antarctica-2300 ensemble. We find significant mass loss after 2300 under both low-emissions and present-day forcing. Thermal evolution is extremely important, with fixed temperature yielding up to twice as much mass loss as simulations with evolving temperature. External forcing uncertainty dominates the ensemble spread after 2050. Initial condition uncertainty could explain the inter-model spread in the ISMIP6 ensembles.
Tim Hill, Derek Bingham, Gwenn E. Flowers, and Matthew J. Hoffman
Geosci. Model Dev., 18, 4045–4074, https://doi.org/10.5194/gmd-18-4045-2025, https://doi.org/10.5194/gmd-18-4045-2025, 2025
Short summary
Short summary
Subglacial drainage models represent water flow beneath glaciers and ice sheets. Here, we train fast statistical models called Gaussian process (GP) emulators to accelerate subglacial drainage modelling by ~ 1000 times. We use the fast emulator predictions to show that three of the model parameters are responsible for > 90 % of the variance in model outputs. The fast GP emulators will enable future uncertainty quantification and calibration of these models.
John D. Jakeman, Mauro Perego, D. Thomas Seidl, Tucker A. Hartland, Trevor R. Hillebrand, Matthew J. Hoffman, and Stephen F. Price
Earth Syst. Dynam., 16, 513–544, https://doi.org/10.5194/esd-16-513-2025, https://doi.org/10.5194/esd-16-513-2025, 2025
Short summary
Short summary
This study investigated the computational benefits of using multiple models of varying cost and accuracy to quantify uncertainty in the mass change of Humboldt Glacier, Greenland, between 2007 and 2100 using a single climate change scenario. Despite some models being incapable of capturing the local features of the ice-flow fields, using multiple models reduced the error in the estimated statistics by over an order of magnitude when compared to an approach that only used a single accurate model.
Irena Vaňková, Xylar Asay-Davis, Carolyn Branecky Begeman, Darin Comeau, Alexander Hager, Matthew Hoffman, Stephen F. Price, and Jonathan Wolfe
The Cryosphere, 19, 507–523, https://doi.org/10.5194/tc-19-507-2025, https://doi.org/10.5194/tc-19-507-2025, 2025
Short summary
Short summary
We study the effect of subglacial discharge on basal melting for Antarctic ice shelves. We find that the results from previous studies of vertical ice fronts and two-dimensional ice tongues do not translate to the rotating ice-shelf framework. The melt rate dependence on discharge is stronger in the rotating framework. Further, there is a substantial melt-rate sensitivity to the location of the discharge along the grounding line relative to the directionality of the Coriolis force.
Sanket Jantre, Matthew J. Hoffman, Nathan M. Urban, Trevor Hillebrand, Mauro Perego, Stephen Price, and John D. Jakeman
The Cryosphere, 18, 5207–5238, https://doi.org/10.5194/tc-18-5207-2024, https://doi.org/10.5194/tc-18-5207-2024, 2024
Short summary
Short summary
We investigate potential sea-level rise from Antarctica's Lambert Glacier, once considered stable but now at risk due to projected ocean warming by 2100. Using statistical methods and limited supercomputer simulations, we calibrated our ice-sheet model using three observables. We find that, under high greenhouse gas emissions, glacier retreat could raise sea levels by 46–133 mm by 2300. This study highlights the need for better observations to reduce uncertainty in ice-sheet model projections.
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.
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.
Trevor R. Hillebrand, Matthew J. Hoffman, Mauro Perego, Stephen F. Price, and Ian M. Howat
The Cryosphere, 16, 4679–4700, https://doi.org/10.5194/tc-16-4679-2022, https://doi.org/10.5194/tc-16-4679-2022, 2022
Short summary
Short summary
We estimate that Humboldt Glacier, northern Greenland, will contribute 5.2–8.7 mm to global sea level in 2007–2100, using an ensemble of model simulations constrained by observations of glacier retreat and speedup. This is a significant fraction of the 40–140 mm from the whole Greenland Ice Sheet predicted by the recent ISMIP6 multi-model ensemble, suggesting that calibrating models against observed velocity changes could result in higher estimates of 21st century sea-level rise from Greenland.
Alexander O. Hager, Matthew J. Hoffman, Stephen F. Price, and Dustin M. Schroeder
The Cryosphere, 16, 3575–3599, https://doi.org/10.5194/tc-16-3575-2022, https://doi.org/10.5194/tc-16-3575-2022, 2022
Short summary
Short summary
The presence of water beneath glaciers is a control on glacier speed and ocean-caused melting, yet it has been unclear whether sizable volumes of water can exist beneath Antarctic glaciers or how this water may flow along the glacier bed. We use computer simulations, supported by observations, to show that enough water exists at the base of Thwaites Glacier, Antarctica, to form "rivers" beneath the glacier. These rivers likely moderate glacier speed and may influence its rate of retreat.
Tong Zhang, Stephen F. Price, Matthew J. Hoffman, Mauro Perego, and Xylar Asay-Davis
The Cryosphere, 14, 3407–3424, https://doi.org/10.5194/tc-14-3407-2020, https://doi.org/10.5194/tc-14-3407-2020, 2020
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.
Dongyu Feng, Zeli Tan, Darren Engwirda, Jonathan D. Wolfe, Donghui Xu, Chang Liao, Gautam Bisht, James J. Benedict, Tian Zhou, Mithun Deb, Hong-Yi Li, and L. Ruby Leung
Nat. Hazards Earth Syst. Sci., 25, 3619–3639, https://doi.org/10.5194/nhess-25-3619-2025, https://doi.org/10.5194/nhess-25-3619-2025, 2025
Short summary
Short summary
Our study explores how riverine and coastal flooding during hurricanes is influenced by the interaction of atmosphere, land, river, and ocean conditions. Using an advanced Earth system model, we simulate Hurricane Irene to evaluate how meteorological and hydrological uncertainties affect flood modeling. Our findings reveal the importance of a multi-component modeling system, how hydrological conditions play critical roles in flood modeling, and greater flood risks if multiple factors are present.
Trevor R. Hillebrand, Matthew J. Hoffman, Holly K. Han, Mauro Perego, Alexander O. Hager, Andrew Nolan, Xylar Asay-Davis, Stephen F. Price, Jerry Watkins, and Max Carlson
EGUsphere, https://doi.org/10.5194/egusphere-2025-3942, https://doi.org/10.5194/egusphere-2025-3942, 2025
Short summary
Short summary
We present new simulations that complement our contribution to the ISMIP6-Antarctica-2300 ensemble. We find significant mass loss after 2300 under both low-emissions and present-day forcing. Thermal evolution is extremely important, with fixed temperature yielding up to twice as much mass loss as simulations with evolving temperature. External forcing uncertainty dominates the ensemble spread after 2050. Initial condition uncertainty could explain the inter-model spread in the ISMIP6 ensembles.
Tim Hill, Derek Bingham, Gwenn E. Flowers, and Matthew J. Hoffman
Geosci. Model Dev., 18, 4045–4074, https://doi.org/10.5194/gmd-18-4045-2025, https://doi.org/10.5194/gmd-18-4045-2025, 2025
Short summary
Short summary
Subglacial drainage models represent water flow beneath glaciers and ice sheets. Here, we train fast statistical models called Gaussian process (GP) emulators to accelerate subglacial drainage modelling by ~ 1000 times. We use the fast emulator predictions to show that three of the model parameters are responsible for > 90 % of the variance in model outputs. The fast GP emulators will enable future uncertainty quantification and calibration of these models.
Claire K. Yung, Xylar S. Asay-Davis, Alistair Adcroft, Christopher Y. S. Bull, Jan De Rydt, Michael S. Dinniman, Benjamin K. Galton-Fenzi, Daniel Goldberg, David E. Gwyther, Robert Hallberg, Matthew Harrison, Tore Hattermann, David M. Holland, Denise Holland, Paul R. Holland, James R. Jordan, Nicolas C. Jourdain, Kazuya Kusahara, Gustavo Marques, Pierre Mathiot, Dimitris Menemenlis, Adele K. Morrison, Yoshihiro Nakayama, Olga Sergienko, Robin S. Smith, Alon Stern, Ralph Timmermann, and Qin Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2025-1942, https://doi.org/10.5194/egusphere-2025-1942, 2025
Short summary
Short summary
ISOMIP+ compares 12 ocean models that simulate ice-ocean interactions in a common, idealised, static ice shelf cavity setup, aiming to assess and understand inter-model variability. Models simulate similar basal melt rate patterns, ocean profiles and circulation but differ in ice-ocean boundary layer properties and spatial distributions of melting. Ice-ocean boundary layer representation is a key area for future work, as are realistic-domain ice sheet-ocean model intercomparisons.
John D. Jakeman, Mauro Perego, D. Thomas Seidl, Tucker A. Hartland, Trevor R. Hillebrand, Matthew J. Hoffman, and Stephen F. Price
Earth Syst. Dynam., 16, 513–544, https://doi.org/10.5194/esd-16-513-2025, https://doi.org/10.5194/esd-16-513-2025, 2025
Short summary
Short summary
This study investigated the computational benefits of using multiple models of varying cost and accuracy to quantify uncertainty in the mass change of Humboldt Glacier, Greenland, between 2007 and 2100 using a single climate change scenario. Despite some models being incapable of capturing the local features of the ice-flow fields, using multiple models reduced the error in the estimated statistics by over an order of magnitude when compared to an approach that only used a single accurate model.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
Short summary
Short summary
Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Benjamin Keith Galton-Fenzi, Richard Porter-Smith, Sue Cook, Eva Cougnon, David E. Gwyther, Wilma G. C. Huneke, Madelaine G. Rosevear, Xylar Asay-Davis, Fabio Boeira Dias, Michael S. Dinniman, David Holland, Kazuya Kusahara, Kaitlin A. Naughten, Keith W. Nicholls, Charles Pelletier, Ole Richter, Helene L. Seroussi, and Ralph Timmermann
EGUsphere, https://doi.org/10.5194/egusphere-2024-4047, https://doi.org/10.5194/egusphere-2024-4047, 2025
Short summary
Short summary
Melting beneath Antarctica’s floating ice shelves is key to future sea-level rise. We compare several different ocean simulations with satellite measurements, and provide the first multi-model average estimate of melting and refreezing driven by both ocean temperature and currents beneath ice shelves. The multi-model average can provide a useful tool for better understanding the role of ice shelf melting in present-day and future ice-sheet changes and informing coastal adaptation efforts.
Irena Vaňková, Xylar Asay-Davis, Carolyn Branecky Begeman, Darin Comeau, Alexander Hager, Matthew Hoffman, Stephen F. Price, and Jonathan Wolfe
The Cryosphere, 19, 507–523, https://doi.org/10.5194/tc-19-507-2025, https://doi.org/10.5194/tc-19-507-2025, 2025
Short summary
Short summary
We study the effect of subglacial discharge on basal melting for Antarctic ice shelves. We find that the results from previous studies of vertical ice fronts and two-dimensional ice tongues do not translate to the rotating ice-shelf framework. The melt rate dependence on discharge is stronger in the rotating framework. Further, there is a substantial melt-rate sensitivity to the location of the discharge along the grounding line relative to the directionality of the Coriolis force.
Sanket Jantre, Matthew J. Hoffman, Nathan M. Urban, Trevor Hillebrand, Mauro Perego, Stephen Price, and John D. Jakeman
The Cryosphere, 18, 5207–5238, https://doi.org/10.5194/tc-18-5207-2024, https://doi.org/10.5194/tc-18-5207-2024, 2024
Short summary
Short summary
We investigate potential sea-level rise from Antarctica's Lambert Glacier, once considered stable but now at risk due to projected ocean warming by 2100. Using statistical methods and limited supercomputer simulations, we calibrated our ice-sheet model using three observables. We find that, under high greenhouse gas emissions, glacier retreat could raise sea levels by 46–133 mm by 2300. This study highlights the need for better observations to reduce uncertainty in ice-sheet model projections.
Jan De Rydt, Nicolas C. Jourdain, Yoshihiro Nakayama, Mathias van Caspel, Ralph Timmermann, Pierre Mathiot, Xylar S. Asay-Davis, Hélène Seroussi, Pierre Dutrieux, Ben Galton-Fenzi, David Holland, and Ronja Reese
Geosci. Model Dev., 17, 7105–7139, https://doi.org/10.5194/gmd-17-7105-2024, https://doi.org/10.5194/gmd-17-7105-2024, 2024
Short summary
Short summary
Global climate models do not reliably simulate sea-level change due to ice-sheet–ocean interactions. We propose a community modelling effort to conduct a series of well-defined experiments to compare models with observations and study how models respond to a range of perturbations in climate and ice-sheet geometry. The second Marine Ice Sheet–Ocean Model Intercomparison Project will continue to lay the groundwork for including ice-sheet–ocean interactions in global-scale IPCC-class models.
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.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
Short summary
Short summary
High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Hyein Jeong, Adrian K. Turner, Andrew F. Roberts, Milena Veneziani, Stephen F. Price, Xylar S. Asay-Davis, Luke P. Van Roekel, Wuyin Lin, Peter M. Caldwell, Hyo-Seok Park, Jonathan D. Wolfe, and Azamat Mametjanov
The Cryosphere, 17, 2681–2700, https://doi.org/10.5194/tc-17-2681-2023, https://doi.org/10.5194/tc-17-2681-2023, 2023
Short summary
Short summary
We find that E3SM-HR reproduces the main features of the Antarctic coastal polynyas. Despite the high amount of coastal sea ice production, the densest water masses are formed in the open ocean. Biases related to the lack of dense water formation are associated with overly strong atmospheric polar easterlies. Our results indicate that the large-scale polar atmospheric circulation must be accurately simulated in models to properly reproduce Antarctic dense water formation.
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.
Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
Short summary
Short summary
Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
Trevor R. Hillebrand, Matthew J. Hoffman, Mauro Perego, Stephen F. Price, and Ian M. Howat
The Cryosphere, 16, 4679–4700, https://doi.org/10.5194/tc-16-4679-2022, https://doi.org/10.5194/tc-16-4679-2022, 2022
Short summary
Short summary
We estimate that Humboldt Glacier, northern Greenland, will contribute 5.2–8.7 mm to global sea level in 2007–2100, using an ensemble of model simulations constrained by observations of glacier retreat and speedup. This is a significant fraction of the 40–140 mm from the whole Greenland Ice Sheet predicted by the recent ISMIP6 multi-model ensemble, suggesting that calibrating models against observed velocity changes could result in higher estimates of 21st century sea-level rise from Greenland.
Alexander O. Hager, Matthew J. Hoffman, Stephen F. Price, and Dustin M. Schroeder
The Cryosphere, 16, 3575–3599, https://doi.org/10.5194/tc-16-3575-2022, https://doi.org/10.5194/tc-16-3575-2022, 2022
Short summary
Short summary
The presence of water beneath glaciers is a control on glacier speed and ocean-caused melting, yet it has been unclear whether sizable volumes of water can exist beneath Antarctic glaciers or how this water may flow along the glacier bed. We use computer simulations, supported by observations, to show that enough water exists at the base of Thwaites Glacier, Antarctica, to form "rivers" beneath the glacier. These rivers likely moderate glacier speed and may influence its rate of retreat.
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.
Milena Veneziani, Wieslaw Maslowski, Younjoo J. Lee, Gennaro D'Angelo, Robert Osinski, Mark R. Petersen, Wilbert Weijer, Anthony P. Craig, John D. Wolfe, Darin Comeau, and Adrian K. Turner
Geosci. Model Dev., 15, 3133–3160, https://doi.org/10.5194/gmd-15-3133-2022, https://doi.org/10.5194/gmd-15-3133-2022, 2022
Short summary
Short summary
We present an Earth system model (ESM) simulation, E3SM-Arctic-OSI, with a refined grid to better resolve the Arctic ocean and sea-ice system and low spatial resolution elsewhere. The configuration satisfactorily represents many aspects of the Arctic system and its interactions with the sub-Arctic, while keeping computational costs at a fraction of those necessary for global high-resolution ESMs. E3SM-Arctic can thus be an efficient tool to study Arctic processes on climate-relevant timescales.
Carolyn Branecky Begeman, Xylar Asay-Davis, and Luke Van Roekel
The Cryosphere, 16, 277–295, https://doi.org/10.5194/tc-16-277-2022, https://doi.org/10.5194/tc-16-277-2022, 2022
Short summary
Short summary
This study uses ocean modeling at ultra-high resolution to study the small-scale ocean mixing that controls ice-shelf melting. It offers some insights into the relationship between ice-shelf melting and ocean temperature far from the ice base, which may help us project how fast ice will melt when ocean waters entering the cavity warm. This study adds to a growing body of research that indicates we need a more sophisticated treatment of ice-shelf melting in coarse-resolution ocean models.
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.
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.
Qiang Sun, Christopher M. Little, Alice M. Barthel, and Laurie Padman
Ocean Sci., 17, 131–145, https://doi.org/10.5194/os-17-131-2021, https://doi.org/10.5194/os-17-131-2021, 2021
Tong Zhang, Stephen F. Price, Matthew J. Hoffman, Mauro Perego, and Xylar Asay-Davis
The Cryosphere, 14, 3407–3424, https://doi.org/10.5194/tc-14-3407-2020, https://doi.org/10.5194/tc-14-3407-2020, 2020
Cited articles
Adcroft, A. and Campin, J.-M.: Rescaled height coordinates for accurate representation of free-surface flows in ocean circulation models, Ocean Model., 7, 269–284, https://doi.org/10.1016/j.ocemod.2003.09.003, 2004. a
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. a, b, c, d
Asay-Davis, X.: MPAS-Dev/MPAS-Analysis: v1.4.0 (1.4.0), Zenodo [code], https://doi.org/10.5281/zenodo.5109439, 2021. a
Barthel, A., Agosta, C., Little, C. M., Hattermann, T., Jourdain, N. C., Goelzer, H., Nowicki, S., Seroussi, H., Straneo, F., and Bracegirdle, T. J.: CMIP5 model selection for ISMIP6 ice sheet model forcing: Greenland and Antarctica, The Cryosphere, 14, 855–879, https://doi.org/10.5194/tc-14-855-2020, 2020. a, b, c, d
Bisht, G., Riley, W. J., Hammond, G. E., and Lorenzetti, D. M.: Development and evaluation of a variably saturated flow model in the global E3SM Land Model (ELM) version 1.0, Geosci. Model Dev., 11, 4085–4102, https://doi.org/10.5194/gmd-11-4085-2018, 2018. a
Bronselaer, B., Winton, M., Griffies, S. M., Hurlin, W. J., Rodgers, K. B., Sergienko, O. V., Stouffer, R. J., and Russell, J. L.: Change in future climate due to Antarctic meltwater, Nature, 564, 53–58, https://doi.org/10.1038/s41586-018-0712-z, 2018. a, b
Bull, C. Y. S., Jenkins, A., Jourdain, N. C., Vǎková, I., Holland, P. R., Mathiot, P., Hausmann, U., and Sallée, J.: Remote Control of Filchner-Ronne Ice Shelf Melt Rates by the Antarctic Slope Current, J. Geophys. Res.-Oceans, 126, e2020JC016550, https://doi.org/10.1029/2020JC016550, 2021. a, b, c, d, e
Burrows, S. M., Maltrud, M., Yang, X., Zhu, Q., Jeffery, N., Shi, X., Ricciuto, D., Wang, S., Bisht, G., Tang, J., Wolfe, J., Harrop, B. E., Singh, B., Brent, L., Baldwin, S., Zhou, T., Cameron-Smith, P., Keen, N., Collier, N., Xu, M., Hunke, E. C., Elliott, S. M., Turner, A. K., Li, H., Wang, H., Golaz, J. C., Bond-Lamberty, B., Hoffman, F. M., Riley, W. J., Thornton, P. E., Calvin, K., and Leung, L. R.: The DOE E3SM v1.1 Biogeochemistry Configuration: Description and Simulated Ecosystem-Climate Responses to Historical Changes in Forcing, J. Adv. Model. Earth Sy., 12, 1–59, https://doi.org/10.1029/2019MS001766, 2020. a
Church, J., Clark, P., Cazenave, A., Gregory, J., Jevrejeva, S., Levermann, A., Merrifield, M., Milne, G., Nerem, R., Nunn, P., Payne, A., Pfeffer, W., Stammer, D., and Unnikrishnan, A.: Sea Level Change, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T., Qin, D., Plattner, G.-K., Tignor, M., Allen, S., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1137–1216, 2013. a
Comeau, D.: CGM-DIB simulation data, Earth System Grid Federation [data set], https://aims2.llnl.gov/search/E3SM?project=E3SM&activeFacets =% 7B% 22campaign% 22% 3A% 22Cryosphere-v1% 22% 2C% 22experiment% 22% 3A% 22G-IAF-DIB-ISMF% 22% 7D (last access: 9 March 2024), 2021a. a
Comeau, D.: CGM-VIB simulation data, Earth System Grid Federation [data set], https://aims2.llnl.gov/search/E3SM?project=E3SM&activeFacets =% % 22campaign% 22% 3A% 22Cryosphere-v1% 22% 2C% 22experiment% 22% 3A% 22G-IAF-DIB-ISMF-3dGM% 22% 7D (last access: 9 March 2024), 2021b. a
Comeau, D., Asay-Davis, X. S., Begeman, C. B., Hoffman, M. J., Lin, W., Petersen, M. R., Price, S. F., Roberts, A. F., Van Roekel, L. P., Veneziani, M., Wolfe, J. D., Fyke, J. G., Ringler, T. D., and Turner, A. K.: The DOE E3SM v1.2 Cryosphere Configuration: Description and Simulated Antarctic Ice-Shelf Basal Melting, J. Adv. Model. Earth Sy., 14, e2021MS002468, https://doi.org/10.1029/2021MS002468, 2022. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p
Daae, K., Hattermann, T., Darelius, E., Mueller, R. D., Naughten, K. A., Timmermann, R., and Hellmer, H. H.: Necessary Conditions for Warm Inflow Toward the Filchner Ice Shelf, Weddell Sea, Geophys. Res. Lett., 47, e2020GL089237, https://doi.org/10.1029/2020GL089237, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p
Danabasoglu, G. and Marshall, J.: Effects of vertical variations of thickness diffusivity in an ocean general circulation model, Ocean Model., 18, 122–141, https://doi.org/10.1016/j.ocemod.2007.03.006, 2007. a
Dawson, H. R. S., Morrison, A. K., England, M. H., and Tamsitt, V.: Pathways and Timescales of Connectivity Around the Antarctic Continental Shelf, J. Geophys. Res.-Oceans, 128, e2022JC018962, https://doi.org/10.1029/2022JC018962, 2023. a, b
Depoorter, M. A., Bamber, J. L., Griggs, J. A., Lenaerts, J. T. M., Ligtenberg, S. R. M., van den Broeke, M. R., and Moholdt, G.: Calving fluxes and basal melt rates of Antarctic ice shelves, Nature, 502, 89–92, https://doi.org/10.1038/nature12567, 2013. a
Dinniman, M. S., Asay-Davis, X. S., Galton-Fenzi, B. K., Holland, P. R., Jenkins, A., and Timmermann, R.: Modeling ice shelf/ocean interaction in Antarctica: A review, Oceanography, 29, 144–153, https://doi.org/10.5670/oceanog.2016.106, 2016. a
Dorschel, B., Hehemann, L., Viquerat, S., Warnke, F., Dreutter, S., Schulze Tenberge, Y., Accettella, D., An, L., Barrios, F., Bazhenova, E. A., Black, J., Bohoyo, F., Davey, C., de Santis, L., Escutia Dotti, C., Fremand, A. C., Fretwell, P. T., Gales, J. A., Gao, J., Gasperini, L., Greenbaum, J. S., Henderson Jencks, J., Hogan, K. A., Hong, J. K., Jakobsson, M., Jensen, L., Kool, J., Larin, S., Larter, R. D., Leitchenkov, G. L., Loubrieu, B., Mackay, K., Mayer, L., Millan, R., Morlighem, M., Navidad, F., Nitsche, F.-O., Nogi, Y., Pertuisot, C., Post, A. L., Pritchard, H. D., Purser, A., Rebesco, M., Rignot, E., Roberts, J. L., Rovere, M., Ryzhov, I., Sauli, C., Schmitt, T., Silvano, A., Smith, J. E., Snaith, H., Tate, A. J., Tinto, K., Vandenbossche, P., Weatherall, P., Wintersteller, P., Yang, C., Zhang, T., and Arndt, J. E.: The International Bathymetric Chart of the Southern Ocean version 2 (IBCSO v2), PANGAEA [data set], https://doi.org/10.1594/PANGAEA.937574, 2022. a
E3SM: Running E3SM, E3SM [data set], https://e3sm.org/model/running-e3sm (last access: 28 May 2024), 2024. a
E3SM Project: Energy Exascale Earth System Model v1.2.1, E3SM Project, DOE [code], https://doi.org/10.11578/E3SM/dc.20210309.1, 2020. a
Fogwill, C. J., Phipps, S. J., Turney, C. S. M., and Golledge, N. R.: Sensitivity of the Southern Ocean to enhanced regional Antarctic ice sheet meltwater input, Earths Future, 3, 317–329, https://doi.org/10.1002/2015EF000306, 2015. a, b
Gent, P. R. and Mcwilliams, J. C.: Isopycnal Mixing in Ocean Circulation Models, J. Phys. Oceanogr., 20, 150–155, https://doi.org/10.1175/1520-0485(1990)020<0150:IMIOCM>2.0.CO;2, 1990. a
Gille, S. T., McKee, D. C., and Martinson, D. G.: Temporal changes in the Antarctic Circumpolar Current: Implications for the Antarctic continental shelves, Oceanography, 29, 96–105, https://doi.org/10.5670/oceanog.2016.102, 2016. a
Golaz, J. C., Caldwell, P. M., Van Roekel, L. P., Petersen, M. R., Tang, Q., Wolfe, J. D., Abeshu, G., Anantharaj, V., Asay-Davis, X. S., Bader, D. C., Baldwin, S. A., Bisht, G., Bogenschutz, P. A., Branstetter, M., Brunke, M. A., Brus, S. R., Burrows, S. M., Cameron-Smith, P. J., Donahue, A. S., Deakin, M., Easter, R. C., Evans, K. J., Feng, Y., Flanner, M., Foucar, J. G., Fyke, J. G., Griffin, B. M., Hannay, C., Harrop, B. E., Hoffman, M. J., Hunke, E. C., Jacob, R. L., Jacobsen, D. W., Jeffery, N., Jones, P. W., Keen, N. D., Klein, S. A., Larson, V. E., Leung, L. R., Li, H. Y., Lin, W., Lipscomb, W. H., Ma, P. L., Mahajan, S., Maltrud, M. E., Mametjanov, A., McClean, J. L., McCoy, R. B., Neale, R. B., Price, S. F., Qian, Y., Rasch, P. J., Reeves Eyre, J. E., Riley, W. J., Ringler, T. D., Roberts, A. F., Roesler, E. L., Salinger, A. G., Shaheen, Z., Shi, X., Singh, B., Tang, J., Taylor, M. A., Thornton, P. E., Turner, A. K., Veneziani, M., Wan, H., Wang, H., Wang, S., Williams, D. N., Wolfram, P. J., Worley, P. H., Xie, S., Yang, Y., Yoon, J. H., Zelinka, M. D., Zender, C. S., Zeng, X., Zhang, C., Zhang, K., Zhang, Y., Zheng, X., Zhou, T., and Zhu, Q.: The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution, J. Adv. Model. Earth Sy., 11, 2089–2129, https://doi.org/10.1029/2018MS001603, 2019. a, b, c
Gudmundsson, G. H.: Ice-shelf buttressing and the stability of marine ice sheets, The Cryosphere, 7, 647–655, https://doi.org/10.5194/tc-7-647-2013, 2013. a
Gudmundsson, G. H., Paolo, F. S., Adusumilli, S., and Fricker, H. A.: Instantaneous Antarctic ice sheet mass loss driven by thinning ice shelves, Geophys. Res. Lett., 46, 13903–13909, https://doi.org/10.1029/2019GL085027, 2019. a
Hellmer, H. and Olbers, D.: A two-dimensional model for the thermohaline circulation under an ice shelf, Antarct. Sci., 1, 325–336, https://doi.org/10.1017/S0954102089000490, 1989. a
Hellmer, H. H., Kauker, F., Timmermann, R., Determann, J., and Rae, J.: Twenty-first-century warming of a large Antarctic ice-shelf cavity by a redirected coastal current., Nature, 485, 225–8, https://doi.org/10.1038/nature11064, 2012. a, b, c, d
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. a, b
Holland, D. M. and Jenkins, A.: Modeling Thermodynamic Ice–Ocean Interactions at the Base of an Ice Shelf, J. Phys. Oceanogr., 29, 1787–1800, https://doi.org/10.1175/1520-0485(1999)029<1787:MTIOIA>2.0.CO;2, 1999. a
Hunke, E. C. and Dukowicz, J. K.: An Elastic–Viscous–Plastic Model for Sea Ice Dynamics, J. Phys. Oceanogr., 27, 1849–1867, https://doi.org/10.1175/1520-0485(1997)027<1849:AEVPMF>2.0.CO;2, 1997. a
Jacobs, S., Helmer, H., Doake, C. S. M., Jenkins, A., and Frolich, R. M.: Melting of ice shelves and the mass balance of Antarctica, J. Glaciol., 38, 375–387, https://doi.org/10.3189/s0022143000002252, 1992. a
Jenkins, A., Dutrieux, P., Jacobs, S., Steig, E. J., Gudmundsson, G. H., Smith, J., and Heywood, K. J.: Decadal ocean forcing and Antarctic Ice Sheet response: Lessons from the Amundsen Sea, Oceanography, 29, 106–117, https://doi.org/10.5670/oceanog.2016.103, 2016. a
Jeong, H., Asay-Davis, X. S., Turner, A. K., Comeau, D. S., Price, S. F., Abernathey, R. P., Veneziani, M., Petersen, M. R., Hoffman, M. J., Mazloff, M. R., and Ringler, T. D.: Impacts of ice-shelf melting on water mass transformation in the Southern Ocean from E3SM simulations, J. Climate, 33, 5787–5808, https://doi.org/10.1175/jcli-d-19-0683.1, 2020. a, b
Joughin, I., Alley, R., and Holland, D.: Ice-sheet response to oceanic forcing, Science, 338, 1172–1176, https://doi.org/10.1126/science.1226481, 2012. a
Jourdain, N. C., Asay-Davis, X., Hattermann, T., Straneo, F., Seroussi, H., Little, C. M., and Nowicki, S.: A protocol for calculating basal melt rates in the ISMIP6 Antarctic ice sheet projections, The Cryosphere, 14, 3111–3134, https://doi.org/10.5194/tc-14-3111-2020, 2020. a
Kerr, R., Dotto, T. S., Mata, M. M., and Hellmer, H. H.: Three decades of deep water mass investigation in the Weddell Sea (1984–2014): Temporal variability and changes, Deep-Sea Res. Pt. II, 149, 70–83, https://doi.org/10.1016/j.dsr2.2017.12.002, 2018. a
Kusahara, K. and Hasumi, H.: Modeling Antarctic Ice Shelf Responses to Future Climate Changes and Impacts on the Ocean, J. Geophys. Res.-Oceans, 118, 2454–2475, https://doi.org/10.1002/jgrc.20166, 2013. a
Large, W. G. and Yeager, S. G.: The global climatology of an interannually varying air–sea flux data set, Clim. Dynam., 33, 341–364, https://doi.org/10.1007/s00382-008-0441-3, 2008. a, b
Lauber, J., Hattermann, T., de Steur, L., Darelius, E., Auger, M., Nøst, O. A., and Moholdt, G.: Warming beneath an East Antarctic Ice Shelf Due to Increased Subpolar Westerlies and Reduced Sea Ice, Nat. Geosci., 16, 877–885, https://doi.org/10.1038/s41561-023-01273-5, 2023. a
Leung, L. R., Bader, D. C., Taylor, M. A., and McCoy, R. B.: An Introduction to the E3SM Special Collection: Goals, Science Drivers, Development, and Analysis, J. Adv. Model. Earth Sy., 12, e2019MS001821, https://doi.org/10.1029/2019MS001821, 2020. a, b
Li, H. Y., Leung, L. R., Getirana, A., Huang, M., Wu, H., Xu, Y., Guo, J., and Voisin, N.: Evaluating global streamflow simulations by a physically based routing model coupled with the community land model, J. Hydrometeorol., 16, 948–971, https://doi.org/10.1175/JHM-D-14-0079.1, 2015. a
Locarnini, R. A., Mishonov, A. V., Baranova, O. K., Boyer, T. P., Zweng, M. M., Garcia, H. E., Reagan, J. R., Seidov, D., Weathers, K. W., Paver, C. R., and Smolyar, I. V.: World Ocean Atlas 2018, Volume 1: Temperature, Tech. Rep. Atlas NESDIS 81, NOAA, https://data.nodc.noaa.gov/woa/WOA18/DOC/woa18_vol1.pdf (last access: 28 May 2024), 2019. a
Marshall, J. and Radko, T.: Residual-Mean Solutions for the Antarctic Circumpolar Current and Its Associated Overturning Circulation, J. Phys. Oceanogr., 33, 2341–2354, https://doi.org/10.1175/1520-0485(2003)033<2341:RSFTAC>2.0.CO;2, 2003. a
Mathiot, P. and Jourdain, N. C.: Southern Ocean warming and Antarctic ice shelf melting in conditions plausible by late 23rd century in a high-end scenario, Ocean Sci., 19, 1595–1615, https://doi.org/10.5194/os-19-1595-2023, 2023. a, b, c
Matsuoka, K., Skoglund, A., and Roth, G.: Quantarctica, Norwegian Polar Institute [data set], https://doi.org/10.21334/npolar.2018.8516e961, 2018. a
Moorman, R., Morrison, A. K., and Hogg, A. M. C.: Thermal Responses to Antarctic Ice Shelf Melt in an Eddy-Rich Global Ocean–Sea Ice Model, J. Climate, 33, 6599–6620, https://doi.org/10.1175/JCLI-D-19-0846.1, 2020. a, b
Nakayama, Y., Timmermann, R., Rodehacke, C. B., Schröder, M., and Hellmer, H. H.: Modeling the spreading of glacial meltwater from the Amundsen and Bellingshausen Seas, Geophys. Res. Lett., 41, 7942–7949, https://doi.org/10.1002/2014GL061600, 2014. a, b, c
Nakayama, Y., Timmermann, R., and H. Hellmer, H.: Impact of West Antarctic ice shelf melting on Southern Ocean hydrography, The Cryosphere, 14, 2205–2216, https://doi.org/10.5194/tc-14-2205-2020, 2020. a, b, c, d
Naughten, K. A., Meissner, K. J., Galton-Fenzi, B. K., England, M. H., Timmermann, R., and Hellmer, H. H.: Future Projections of Antarctic Ice Shelf Melting Based on CMIP5 Scenarios, J. Climate, 31, 5243–5261, https://doi.org/10.1175/JCLI-D-17-0854.1, 2018. a, b, c
Naughten, K. A., De Rydt, J., Rosier, S. H. R., Jenkins, A., Holland, P. R., and Ridley, J. K.: Two-timescale response of a large Antarctic ice shelf to climate change, Nat. Commun., 12, 1991, https://doi.org/10.1038/s41467-021-22259-0, 2021. a
Nicholls, K. W., Østerhus, S., Makinson, K., Gammelsrød, T., and Fahrbach, E.: Ice-ocean processes over the continental shelf of the Southern Weddell Sea, Antarctica: A review, Rev. Geophys., 47, 1–23, https://doi.org/10.1029/2007RG000250, 2009. a
Pauling, A. G., Bitz, C. M., Smith, I. J., and Langhorne, P. J.: The Response of the Southern Ocean and Antarctic Sea Ice to Freshwater from Ice Shelves in an Earth System Model, J. Climate, 29, 1655–1672, https://doi.org/10.1175/JCLI-D-15-0501.1, 2016. a
Pauling, A. G., Smith, I. J., Langhorne, P. J., and Bitz, C. M.: Time-Dependent Freshwater Input From Ice Shelves: Impacts on Antarctic Sea Ice and the Southern Ocean in an Earth System Model, Geophys. Res. Lett., 44, 10454–10461, https://doi.org/10.1002/2017GL075017, 2017. a
Petersen, M. R., Jacobsen, D. W., Ringler, T. D., Hecht, M. W., and Maltrud, M. E.: Evaluation of the arbitrary Lagrangian-Eulerian vertical coordinate method in the MPAS-Ocean model, Ocean Model., 86, 93–113, https://doi.org/10.1016/j.ocemod.2014.12.004, 2015. a
Petersen, M. R., Asay-Davis, X. S., Berres, A. S., Chen, Q., Feige, N., Hoffman, M. J., Jacobsen, D. W., Jones, P. W., Maltrud, M. E., Price, S. F., Ringler, T. D., Streletz, G. J., Turner, A. K., Van Roekel, L. P., Veneziani, M., Wolfe, J. D., Wolfram, P. J., and Woodring, J. L.: An Evaluation of the Ocean and Sea Ice Climate of E3SM Using MPAS and Interannual CORE-II Forcing, J. Adv. Model. Earth Sy., 11, 1438–1458, https://doi.org/10.1029/2018MS001373, 2019. a, b, c, d, e, f, g
Phipps, S. J., Fogwill, C. J., and Turney, C. S. M.: Impacts of marine instability across the East Antarctic Ice Sheet on Southern Ocean dynamics, The Cryosphere, 10, 2317–2328, https://doi.org/10.5194/tc-10-2317-2016, 2016. a, b
Rasch, P. J., Xie, S., Ma, P., Lin, W., Wang, H., Tang, Q., Burrows, S. M., Caldwell, P., Zhang, K., Easter, R. C., Cameron-Smith, P., Singh, B., Wan, H., Golaz, J., Harrop, B. E., Roesler, E., Bacmeister, J., Larson, V. E., Evans, K. J., Qian, Y., Taylor, M., Leung, L. R., Zhang, Y., Brent, L., Branstetter, M., Hannay, C., Mahajan, S., Mametjanov, A., Neale, R., Richter, J. H., Yoon, J., Zender, C. S., Bader, D., Flanner, M., Foucar, J. G., Jacob, R., Keen, N., Klein, S. A., Liu, X., Salinger, A., Shrivastava, M., and Yang, Y.: An Overview of the Atmospheric Component of the Energy Exascale Earth System Model, J. Adv. Model. Earth Sy., 11, 2377–2411, https://doi.org/10.1029/2019MS001629, 2019. a
Reese, R., Gudmundsson, G. H., Levermann, A., and Winkelmann, R.: The far reach of ice-shelf thinning in Antarctica, Nat. Clim. Change, 8, 53–57, https://doi.org/10.1038/s41558-017-0020-x, 2018. a
Ringler, T., Petersen, M., Higdon, R. L., Jacobsen, D., Jones, P. W., and Maltrud, M.: A multi-resolution approach to global ocean modeling, Ocean Model., 69, 211–232, https://doi.org/10.1016/j.ocemod.2013.04.010, 2013. a
Ryan, S., Hattermann, T., Darelius, E., and Schröder, M.: Seasonal cycle of hydrography on the eastern shelf of the Filchner Trough, Weddell Sea, Antarctica, J. Geophys. Res.-Oceans, 122, 6437–6453, https://doi.org/10.1002/2017JC012916, 2017. a, b, c
Ryan, S., Hellmer, H. H., Janout, M., Darelius, E., Vignes, L., and Schröder, M.: Exceptionally Warm and Prolonged Flow of Warm Deep Water Toward the Filchner-Ronne Ice Shelf in 2017, Geophys. Res. Lett., 47, e2020GL088119, https://doi.org/10.1029/2020GL088119, 2020. a
Si, Y., Stewart, A. L., and Eisenman, I.: Heat transport across the Antarctic Slope Front controlled by cross-slope salinity gradients, Science Advances, 9, eadd7049, https://doi.org/10.1126/sciadv.add7049, 2023. a
Siahaan, A., Smith, R. S., Holland, P. R., Jenkins, A., Gregory, J. M., Lee, V., Mathiot, P., Payne, A. J., Ridley, J. K., and Jones, C. G.: The Antarctic contribution to 21st-century sea-level rise predicted by the UK Earth System Model with an interactive ice sheet, The Cryosphere, 16, 4053–4086, https://doi.org/10.5194/tc-16-4053-2022, 2022. a
Silvano, A., Rintoul, S. R., Peña-Molino, B., Hobbs, W. R., Van Wijk, E., Aoki, S., Tamura, T., and Williams, G. D.: Freshening by glacial meltwater enhances melting of ice shelves and reduces formation of Antarctic Bottom Water, Science Advances, 4, 1–12, https://doi.org/10.1126/sciadv.aap9467, 2018. a
Steele, M., Morley, R., and Ermold, W.: PHC: A Global Ocean Hydrography with a High-Quality Arctic Ocean, J. Climate, 14, 2079–2087, https://doi.org/10.1175/1520-0442(2001)014<2079:PAGOHW>2.0.CO;2, 2001. a
Thoma, M., Grosfeld, K., Makinson, K., and Lange, M. A.: Modelling the Impact of Ocean Warming on Melting and Water Masses of Ice Shelves in the Eastern Weddell Sea, Ocean Dynam., 60, 479–489, https://doi.org/10.1007/s10236-010-0262-x, 2010. a, b
Thoma, M., Determann, J., Grosfeld, K., Goeller, S., and Hellmer, H. H.: Future sea-level rise due to projected ocean warming beneath the Filchner Ronne Ice Shelf: A coupled model study, Earth Planet. Sc. Lett., 431, 217–224, https://doi.org/10.1016/j.epsl.2015.09.013, 2015. a
Thompson, A. F., Stewart, A. L., Spence, P., and Heywood, K. J.: The Antarctic Slope Current in a Changing Climate, Rev. Geophys., 56, 741–770, https://doi.org/10.1029/2018RG000624, 2018. a, b
Timmermann, R. and Hellmer, H. H.: Southern Ocean warming and increased ice shelf basal melting in the twenty-first and twenty-second centuries based on coupled ice-ocean finite-element modelling, Ocean Dynam., 63, 1011–1026, https://doi.org/10.1007/s10236-013-0642-0, 2013. a, b
Turner, A. K. and Hunke, E. C.: Impacts of a mushy-layer thermodynamic approach in global sea-ice simulations using the CICE sea-ice model, J. Geophys. Res.-Oceans, 120, 1253–1275, https://doi.org/10.1002/2014JC010358, 2015. a
Turner, A. K., Hunke, E. C., and Bitz, C. M.: Two modes of sea-ice gravity drainage: A parameterization for large-scale modeling, J. Geophys. Res.-Oceans, 118, 2279–2294, https://doi.org/10.1002/jgrc.20171, 2013. a
Turner, A. K., Lipscomb, W. H., Hunke, E. C., Jacobsen, D. W., Jeffery, N., Engwirda, D., Ringler, T. D., and Wolfe, J. D.: MPAS-Seaice (v1.0.0): sea-ice dynamics on unstructured Voronoi meshes, Geosci. Model Dev., 15, 3721–3751, https://doi.org/10.5194/gmd-15-3721-2022, 2022. a, b, c
Wang, Q., Danilov, S., Fahrbach, E., Schröter, J., and Jung, T.: On the impact of wind forcing on the seasonal variability of Weddell Sea Bottom Water transport, Geophys. Res. Lett., 39, L06603, https://doi.org/10.1029/2012GL051198, 2012. a, b
Zhang, T., Price, S. F., Hoffman, M. J., Perego, M., and Asay-Davis, X.: Diagnosing the sensitivity of grounding-line flux to changes in sub-ice-shelf melting, The Cryosphere, 14, 3407–3424, https://doi.org/10.5194/tc-14-3407-2020, 2020. a
Zweng, M. M., Reagan, J. R., Seidov, D., Boyer, T. P., Locarnini, R., Garcia, H. E., Mishonov, A. V., Baranova, O. K., Weathers, K. W., Paver, C. R., and Smolyar, I. V.: World Ocean Atlas 2018, Volume 2: Salinity, Tech. Rep. Atlas NESDIS 82, NOAA, https://data.nodc.noaa.gov/woa/WOA18/DOC/woa18_vol2.pdf (last access: 28 May 2024), 2019. a
Short summary
The Filchner–Ronne Ice Shelf in Antarctica is susceptible to the intrusion of deep, warm ocean water that could increase the melting at the ice-shelf base by a factor of 10. We show that representing this potential melt regime switch in a low-resolution climate model requires careful treatment of iceberg melting and ocean mixing. We also demonstrate a possible ice-shelf melt domino effect where increased melting of nearby ice shelves can lead to the melt regime switch at Filchner–Ronne.
The Filchner–Ronne Ice Shelf in Antarctica is susceptible to the intrusion of deep, warm ocean...
