Articles | Volume 11, issue 4
https://doi.org/10.5194/gmd-11-1257-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-1257-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| Highlight paper
| 
10 Apr 2018
Model evaluation paper | Highlight paper |
| 10 Apr 2018
| 10 Apr 2018
Intercomparison of Antarctic ice-shelf, ocean, and sea-ice interactions simulated by MetROMS-iceshelf and FESOM 1.4
Kaitlin A. Naughten
CORRESPONDING AUTHOR
Climate Change Research Centre, Level 4 Mathews Building, UNSW Sydney, Sydney NSW 2052, Australia
ARC Centre of Excellence for Climate System Science, Australia
Antarctic Climate & Ecosystems Cooperative Research Centre, Private Bag 80, Hobart TAS 7001, Australia
Katrin J. Meissner
Climate Change Research Centre, Level 4 Mathews Building, UNSW Sydney, Sydney NSW 2052, Australia
ARC Centre of Excellence for Climate System Science, Australia
Benjamin K. Galton-Fenzi
Australian Antarctic Division, 203 Channel Highway, Kingston TAS 7050, Australia
Antarctic Climate & Ecosystems Cooperative Research Centre, Private Bag 80, Hobart TAS 7001, Australia
Matthew H. England
Climate Change Research Centre, Level 4 Mathews Building, UNSW Sydney, Sydney NSW 2052, Australia
ARC Centre of Excellence for Climate System Science, Australia
Ralph Timmermann
Alfred Wegener Institut, Postfach 12 01 61, 27515 Bremerhaven, Germany
Hartmut H. Hellmer
Alfred Wegener Institut, Postfach 12 01 61, 27515 Bremerhaven, Germany
Tore Hattermann
Akvaplan-niva, P.O. Box 6606, Langnes, 9296 Tromsø, Norway
Alfred Wegener Institut, Postfach 12 01 61, 27515 Bremerhaven, Germany
Jens B. Debernard
Norwegian Meteorological Institute, P.O. Box 43, Blindern, 0313 Oslo, Norway
Related authors
No articles found.
Ole Richter, Ralph Timmermann, G. Hilmar Gudmundsson, and Jan De Rydt
Geosci. Model Dev., 18, 2945–2960, https://doi.org/10.5194/gmd-18-2945-2025, https://doi.org/10.5194/gmd-18-2945-2025, 2025
Short summary
Short summary
The new coupled ice sheet–ocean model addresses challenges related to horizontal resolution through advanced mesh flexibility, enabled by the use of unstructured grids. We describe the new model, verify its functioning in an idealised setting and demonstrate its advantages in a global-ocean–Antarctic ice sheet domain. The results of this study comprise an important step towards improving predictions of the Antarctic contribution to sea level rise over centennial timescales.
Torsten Kanzow, Angelika Humbert, Thomas Mölg, Mirko Scheinert, Matthias Braun, Hans Burchard, Francesca Doglioni, Philipp Hochreuther, Martin Horwath, Oliver Huhn, Maria Kappelsberger, Jürgen Kusche, Erik Loebel, Katrina Lutz, Ben Marzeion, Rebecca McPherson, Mahdi Mohammadi-Aragh, Marco Möller, Carolyne Pickler, Markus Reinert, Monika Rhein, Martin Rückamp, Janin Schaffer, Muhammad Shafeeque, Sophie Stolzenberger, Ralph Timmermann, Jenny Turton, Claudia Wekerle, and Ole Zeising
The Cryosphere, 19, 1789–1824, https://doi.org/10.5194/tc-19-1789-2025, https://doi.org/10.5194/tc-19-1789-2025, 2025
Short summary
Short summary
The Greenland Ice Sheet represents the second-largest contributor to global sea-level rise. We quantify atmosphere, ice and ocean processes related to the mass balance of glaciers in northeast Greenland, focusing on Greenland’s largest floating ice tongue, the 79° N Glacier. We find that together, the different in situ and remote sensing observations and model simulations reveal a consistent picture of a coupled atmosphere–ice sheet–ocean system that has entered a phase of major change.
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
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
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.
Babette A.A. Hoogakker, Catherine Davis, Yi Wang, Stephanie Kusch, Katrina Nilsson-Kerr, Dalton S. Hardisty, Allison Jacobel, Dharma Reyes Macaya, Nicolaas Glock, Sha Ni, Julio Sepúlveda, Abby Ren, Alexandra Auderset, Anya V. Hess, Katrin J. Meissner, Jorge Cardich, Robert Anderson, Christine Barras, Chandranath Basak, Harold J. Bradbury, Inda Brinkmann, Alexis Castillo, Madelyn Cook, Kassandra Costa, Constance Choquel, Paula Diz, Jonas Donnenfield, Felix J. Elling, Zeynep Erdem, Helena L. Filipsson, Sebastián Garrido, Julia Gottschalk, Anjaly Govindankutty Menon, Jeroen Groeneveld, Christian Hallmann, Ingrid Hendy, Rick Hennekam, Wanyi Lu, Jean Lynch-Stieglitz, Lélia Matos, Alfredo Martínez-García, Giulia Molina, Práxedes Muñoz, Simone Moretti, Jennifer Morford, Sophie Nuber, Svetlana Radionovskaya, Morgan Reed Raven, Christopher J. Somes, Anja S. Studer, Kazuyo Tachikawa, Raúl Tapia, Martin Tetard, Tyler Vollmer, Xingchen Wang, Shuzhuang Wu, Yan Zhang, Xin-Yuan Zheng, and Yuxin Zhou
Biogeosciences, 22, 863–957, https://doi.org/10.5194/bg-22-863-2025, https://doi.org/10.5194/bg-22-863-2025, 2025
Short summary
Short summary
Paleo-oxygen proxies can extend current records, constrain pre-anthropogenic baselines, provide datasets necessary to test climate models under different boundary conditions, and ultimately understand how ocean oxygenation responds on longer timescales. Here we summarize current proxies used for the reconstruction of Cenozoic seawater oxygen levels. This includes an overview of the proxy's history, how it works, resources required, limitations, and future recommendations.
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.
Fabio Boeira Dias, Matthew H. England, Adele K. Morrison, and Benjamin Galton-Fenzi
EGUsphere, https://doi.org/10.5194/egusphere-2024-3905, https://doi.org/10.5194/egusphere-2024-3905, 2025
Short summary
Short summary
The Antarctic Ice Sheet melting dominates the sea-level projection uncertainties. Much uncertainty arises from our limited understanding of how ice shelves melt from below. Using a detailed ocean-ice shelf model, we found that East Antarctic ice shelves experience seasonal melting driven by ocean heat transport variability. In contrast, West Antarctic ice shelves show consistent melting due to a steady supply of warm, deep water, indicating potentially distinct response due to a warming climate.
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev., 17, 8243–8265, https://doi.org/10.5194/gmd-17-8243-2024, https://doi.org/10.5194/gmd-17-8243-2024, 2024
Short summary
Short summary
We introduce an accelerated forcing approach to address timescale discrepancies between the ice sheets and ocean components in coupled modelling by reducing the ocean simulation duration. The approach is evaluated using idealized coupled models, and its limitations in real-world applications are discussed. Our results suggest it can be a valuable tool for process-oriented coupled ice sheet–ocean modelling and downscaling climate simulations with such models.
Yu Wang, Chen Zhao, Rupert Gladstone, Thomas Zwinger, Benjamin K. Galton-Fenzi, and Poul Christoffersen
The Cryosphere, 18, 5117–5137, https://doi.org/10.5194/tc-18-5117-2024, https://doi.org/10.5194/tc-18-5117-2024, 2024
Short summary
Short summary
Our research delves into the future evolution of Antarctica's Wilkes Subglacial Basin (WSB) and its potential contribution to sea level rise, focusing on how basal melt is implemented at the grounding line in ice flow models. Our findings suggest that these implementation methods can significantly impact the magnitude of future ice loss projections. Under a high-emission scenario, the WSB ice sheet could undergo massive and rapid retreat between 2200 and 2300.
Vanessa Teske, Ralph Timmermann, Cara Nissen, Rolf Zentek, Tido Semmler, and Günther Heinemann
EGUsphere, https://doi.org/10.5194/egusphere-2024-2873, https://doi.org/10.5194/egusphere-2024-2873, 2024
Short summary
Short summary
We investigate the structural changes the Antarctic Slope Front in the southern Weddell Sea experiences in a warming climate by conducting two ocean simulations driven by atmospheric data of different horizontal resolution. Cross-slope currents associated with a regime shift from a cold to a warm Filchner Trough on the continental shelf temporarily disturb the structure of the slope front and reduce its depth, but the primary reason for a regime shift is the cross-slope density gradient.
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.
Bartholomé Duboc, Katrin J. Meissner, Laurie Menviel, Nicholas K. H. Yeung, Babette Hoogakker, Tilo Ziehn, and Matthew Chamberlain
EGUsphere, https://doi.org/10.5194/egusphere-2024-2675, https://doi.org/10.5194/egusphere-2024-2675, 2024
Short summary
Short summary
We use an Earth System Model to simulate ocean oxygen during two past warm periods, the Last Interglacial (~129–115 ka) and Marine Isotope Stage (MIS) 9e (~336-321 ka). The global ocean is overall less oxygenated compared to the preindustrial simulation. Large regions in the Mediterranean Sea are oxygen deprived in the Last Interglacial simulation, and to a lesser extent in the MIS 9e simulation, due to an intensification and expansion of the African Monsoon and enhanced river run-off.
Ole Zeising, Niklas Neckel, Nils Dörr, Veit Helm, Daniel Steinhage, Ralph Timmermann, and Angelika Humbert
The Cryosphere, 18, 1333–1357, https://doi.org/10.5194/tc-18-1333-2024, https://doi.org/10.5194/tc-18-1333-2024, 2024
Short summary
Short summary
The 79° North Glacier in Greenland has experienced significant changes over the last decades. Due to extreme melt rates, the ice has thinned significantly in the vicinity of the grounding line, where a large subglacial channel has formed since 2010. We attribute these changes to warm ocean currents and increased subglacial discharge from surface melt. However, basal melting has decreased since 2018, indicating colder water inflow into the cavity below the glacier.
Cara Nissen, Ralph Timmermann, Mathias van Caspel, and Claudia Wekerle
Ocean Sci., 20, 85–101, https://doi.org/10.5194/os-20-85-2024, https://doi.org/10.5194/os-20-85-2024, 2024
Short summary
Short summary
The southeastern Weddell Sea is important for global ocean circulation due to the cross-shelf-break exchange of Dense Shelf Water and Warm Deep Water, but their exact circulation pathways remain elusive. Using Lagrangian model experiments in an eddy-permitting ocean model, we show how present circulation pathways and transit times of these water masses on the continental shelf are altered by 21st-century climate change, which has implications for local ice-shelf basal melt rates and ecosystems.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
Short summary
Short summary
Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Lukrecia Stulic, Ralph Timmermann, Stephan Paul, Rolf Zentek, Günther Heinemann, and Torsten Kanzow
Ocean Sci., 19, 1791–1808, https://doi.org/10.5194/os-19-1791-2023, https://doi.org/10.5194/os-19-1791-2023, 2023
Short summary
Short summary
In the southern Weddell Sea, the strong sea ice growth in coastal polynyas drives formation of dense shelf water. By using a sea ice–ice shelf–ocean model with representation of the changing icescape based on satellite data, we find that polynya sea ice growth depends on both the regional atmospheric forcing and the icescape. Not just strength but also location of the sea ice growth in polynyas affects properties of the dense shelf water and the basal melting of the Filchner–Ronne Ice Shelf.
Sina Loriani, Yevgeny Aksenov, David Armstrong McKay, Govindasamy Bala, Andreas Born, Cristiano M. Chiessi, Henk Dijkstra, Jonathan F. Donges, Sybren Drijfhout, Matthew H. England, Alexey V. Fedorov, Laura Jackson, Kai Kornhuber, Gabriele Messori, Francesco Pausata, Stefanie Rynders, Jean-Baptiste Salée, Bablu Sinha, Steven Sherwood, Didier Swingedouw, and Thejna Tharammal
EGUsphere, https://doi.org/10.5194/egusphere-2023-2589, https://doi.org/10.5194/egusphere-2023-2589, 2023
Short summary
Short summary
In this work, we draw on paleoreords, observations and modelling studies to review tipping points in the ocean overturning circulations, monsoon systems and global atmospheric circulations. We find indications for tipping in the ocean overturning circulations and the West African monsoon, with potentially severe impacts on the Earth system and humans. Tipping in the other considered systems is considered conceivable but currently not sufficiently supported by evidence.
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.
Verena Haid, Ralph Timmermann, Özgür Gürses, and Hartmut H. Hellmer
Ocean Sci., 19, 1529–1544, https://doi.org/10.5194/os-19-1529-2023, https://doi.org/10.5194/os-19-1529-2023, 2023
Short summary
Short summary
Recently, it was found that cold-to-warm changes in Antarctic shelf sea areas are possible and lead to higher ice shelf melt rates. In modelling experiments, we found that if the highest density in front of the ice shelf becomes lower than the density of the warmer water off-shelf at the deepest access to the shelf, the off-shelf water will flow onto the shelf. Our results also indicate that this change will offer some, although not much, resistance to reversal and constitutes a tipping point.
Laurie C. Menviel, Paul Spence, Andrew E. Kiss, Matthew A. Chamberlain, Hakase Hayashida, Matthew H. England, and Darryn Waugh
Biogeosciences, 20, 4413–4431, https://doi.org/10.5194/bg-20-4413-2023, https://doi.org/10.5194/bg-20-4413-2023, 2023
Short summary
Short summary
As the ocean absorbs 25% of the anthropogenic emissions of carbon, it is important to understand the impact of climate change on the flux of carbon between the ocean and the atmosphere. Here, we use a very high-resolution ocean, sea-ice, carbon cycle model to show that the capability of the Southern Ocean to uptake CO2 has decreased over the last 40 years due to a strengthening and poleward shift of the southern hemispheric westerlies. This trend is expected to continue over the coming century.
Felicity S. McCormack, Jason L. Roberts, Bernd Kulessa, Alan Aitken, Christine F. Dow, Lawrence Bird, Benjamin K. Galton-Fenzi, Katharina Hochmuth, Richard S. Jones, Andrew N. Mackintosh, and Koi McArthur
The Cryosphere, 17, 4549–4569, https://doi.org/10.5194/tc-17-4549-2023, https://doi.org/10.5194/tc-17-4549-2023, 2023
Short summary
Short summary
Changes in Antarctic surface elevation can cause changes in ice and basal water flow, impacting how much ice enters the ocean. We find that ice and basal water flow could divert from the Totten to the Vanderford Glacier, East Antarctica, under only small changes in the surface elevation, with implications for estimates of ice loss from this region. Further studies are needed to determine when this could occur and if similar diversions could occur elsewhere in Antarctica due to climate change.
Himadri Saini, Katrin J. Meissner, Laurie Menviel, and Karin Kvale
Clim. Past, 19, 1559–1584, https://doi.org/10.5194/cp-19-1559-2023, https://doi.org/10.5194/cp-19-1559-2023, 2023
Short summary
Short summary
Understanding the changes in atmospheric CO2 during the last glacial cycle is crucial to comprehend the impact of climate change in the future. Previous research has hypothesised a key role of greater aeolian iron input into the Southern Ocean in influencing the global atmospheric CO2 levels by impacting the changes in the marine phytoplankton response. In our study, we test this iron hypothesis using climate modelling and constrain the impact of ocean iron supply on global CO2 decrease.
Andrew P. Schurer, Gabriele C. Hegerl, Hugues Goosse, Massimo A. Bollasina, Matthew H. England, Michael J. Mineter, Doug M. Smith, and Simon F. B. Tett
Clim. Past, 19, 943–957, https://doi.org/10.5194/cp-19-943-2023, https://doi.org/10.5194/cp-19-943-2023, 2023
Short summary
Short summary
We adopt an existing data assimilation technique to constrain a model simulation to follow three important modes of variability, the North Atlantic Oscillation, El Niño–Southern Oscillation and the Southern Annular Mode. How it compares to the observed climate is evaluated, with improvements over simulations without data assimilation found over many regions, particularly the tropics, the North Atlantic and Europe, and discrepancies with global cooling following volcanic eruptions are reconciled.
Xavier Crosta, Karen E. Kohfeld, Helen C. Bostock, Matthew Chadwick, Alice Du Vivier, Oliver Esper, Johan Etourneau, Jacob Jones, Amy Leventer, Juliane Müller, Rachael H. Rhodes, Claire S. Allen, Pooja Ghadi, Nele Lamping, Carina B. Lange, Kelly-Anne Lawler, David Lund, Alice Marzocchi, Katrin J. Meissner, Laurie Menviel, Abhilash Nair, Molly Patterson, Jennifer Pike, Joseph G. Prebble, Christina Riesselman, Henrik Sadatzki, Louise C. Sime, Sunil K. Shukla, Lena Thöle, Maria-Elena Vorrath, Wenshen Xiao, and Jiao Yang
Clim. Past, 18, 1729–1756, https://doi.org/10.5194/cp-18-1729-2022, https://doi.org/10.5194/cp-18-1729-2022, 2022
Short summary
Short summary
Despite its importance in the global climate, our knowledge of Antarctic sea-ice changes throughout the last glacial–interglacial cycle is extremely limited. As part of the Cycles of Sea Ice Dynamics in the Earth system (C-SIDE) Working Group, we review marine- and ice-core-based sea-ice proxies to provide insights into their applicability and limitations. By compiling published records, we provide information on Antarctic sea-ice dynamics over the past 130 000 years.
Madelaine Rosevear, Benjamin Galton-Fenzi, and Craig Stevens
Ocean Sci., 18, 1109–1130, https://doi.org/10.5194/os-18-1109-2022, https://doi.org/10.5194/os-18-1109-2022, 2022
Short summary
Short summary
Understanding ocean-driven melting of Antarctic ice shelves is critical for predicting future sea level. However, ocean observations from beneath ice shelves are scarce. Here, we present unique ocean and melting data from the Amery Ice Shelf, East Antarctica. We use our observations to evaluate common methods of representing melting in ocean–climate models (melting
parameterisations) and show that these parameterisations overestimate melting when the ocean is warm and/or currents are weak.
Chen Zhao, Rupert Gladstone, Benjamin Keith Galton-Fenzi, David Gwyther, and Tore Hattermann
Geosci. Model Dev., 15, 5421–5439, https://doi.org/10.5194/gmd-15-5421-2022, https://doi.org/10.5194/gmd-15-5421-2022, 2022
Short summary
Short summary
We use a coupled ice–ocean model to explore an oscillation feature found in several contributing models to MISOMIP1. The oscillation is closely related to the discretized grounding line retreat and likely strengthened by the buoyancy–melt feedback and/or melt–geometry feedback near the grounding line, and frequent ice–ocean coupling. Our model choices have a non-trivial impact on mean melt and ocean circulation strength, which might be interesting for the coupled ice–ocean community.
Ole Richter, David E. Gwyther, Matt A. King, and Benjamin K. Galton-Fenzi
The Cryosphere, 16, 1409–1429, https://doi.org/10.5194/tc-16-1409-2022, https://doi.org/10.5194/tc-16-1409-2022, 2022
Short summary
Short summary
Tidal currents may play an important role in Antarctic ice sheet retreat by changing the rate at which the ocean melts glaciers. Here, using a computational ocean model, we derive the first estimate of present-day tidal melting that covers all of Antarctica. Our results suggest that large-scale ocean models aiming to accurately predict ice melt rates will need to account for the effects of tides. The inclusion of tide-induced friction at the ice–ocean interface should be prioritized.
Ryan A. Green, Laurie Menviel, Katrin J. Meissner, Xavier Crosta, Deepak Chandan, Gerrit Lohmann, W. Richard Peltier, Xiaoxu Shi, and Jiang Zhu
Clim. Past, 18, 845–862, https://doi.org/10.5194/cp-18-845-2022, https://doi.org/10.5194/cp-18-845-2022, 2022
Short summary
Short summary
Climate models are used to predict future climate changes and as such, it is important to assess their performance in simulating past climate changes. We analyze seasonal sea-ice cover over the Southern Ocean simulated from numerical PMIP3, PMIP4 and LOVECLIM simulations during the Last Glacial Maximum (LGM). Comparing these simulations to proxy data, we provide improved estimates of LGM seasonal sea-ice cover. Our estimate of summer sea-ice extent is 20 %–30 % larger than previous estimates.
Yu Wang, Chen Zhao, Rupert Gladstone, Ben Galton-Fenzi, and Roland Warner
The Cryosphere, 16, 1221–1245, https://doi.org/10.5194/tc-16-1221-2022, https://doi.org/10.5194/tc-16-1221-2022, 2022
Short summary
Short summary
The thermal structure of the Amery Ice Shelf and its spatial pattern are evaluated and analysed through temperature observations from six boreholes and numerical simulations. The simulations demonstrate significant ice warming downstream along the ice flow and a great variation of the thermal structure across the ice flow. We suggest that the thermal structure of the Amery Ice Shelf is unlikely to be affected by current climate changes on decadal timescales.
Dipayan Choudhury, Laurie Menviel, Katrin J. Meissner, Nicholas K. H. Yeung, Matthew Chamberlain, and Tilo Ziehn
Clim. Past, 18, 507–523, https://doi.org/10.5194/cp-18-507-2022, https://doi.org/10.5194/cp-18-507-2022, 2022
Short summary
Short summary
We investigate the effects of a warmer climate from the Earth's paleoclimate (last interglacial) on the marine carbon cycle of the Southern Ocean using a carbon-cycle-enabled state-of-the-art climate model. We find a 150 % increase in CO2 outgassing during this period, which results from competition between higher sea surface temperatures and weaker oceanic circulation. From this we unequivocally infer that the carbon uptake by the Southern Ocean will reduce under a future warming scenario.
Ole Richter, David E. Gwyther, Benjamin K. Galton-Fenzi, and Kaitlin A. Naughten
Geosci. Model Dev., 15, 617–647, https://doi.org/10.5194/gmd-15-617-2022, https://doi.org/10.5194/gmd-15-617-2022, 2022
Short summary
Short summary
Here we present an improved model of the Antarctic continental shelf ocean and demonstrate that it is capable of reproducing present-day conditions. The improvements are fundamental and regard the inclusion of tides and ocean eddies. We conclude that the model is well suited to gain new insights into processes that are important for Antarctic ice sheet retreat and global ocean changes. Hence, the model will ultimately help to improve projections of sea level rise and climate change.
Karin Kvale, David P. Keller, Wolfgang Koeve, Katrin J. Meissner, Christopher J. Somes, Wanxuan Yao, and Andreas Oschlies
Geosci. Model Dev., 14, 7255–7285, https://doi.org/10.5194/gmd-14-7255-2021, https://doi.org/10.5194/gmd-14-7255-2021, 2021
Short summary
Short summary
We present a new model of biological marine silicate cycling for the University of Victoria Earth System Climate Model (UVic ESCM). This new model adds diatoms, which are a key aspect of the biological carbon pump, to an existing ecosystem model. Our modifications change how the model responds to warming, with net primary production declining more strongly than in previous versions. Diatoms in particular are simulated to decline with climate warming due to their high nutrient requirements.
Nicholas King-Hei Yeung, Laurie Menviel, Katrin J. Meissner, Andréa S. Taschetto, Tilo Ziehn, and Matthew Chamberlain
Clim. Past, 17, 869–885, https://doi.org/10.5194/cp-17-869-2021, https://doi.org/10.5194/cp-17-869-2021, 2021
Short summary
Short summary
The Last Interglacial period (LIG) is characterised by strong orbital forcing compared to the pre-industrial period (PI). This study compares the mean climate state of the LIG to the PI as simulated by the ACCESS-ESM1.5, with a focus on the southern hemispheric monsoons, which are shown to be consistently weakened. This is associated with cooler terrestrial conditions in austral summer due to decreased insolation, and greater pressure and subsidence over land from Hadley cell strengthening.
Shannon A. Bengtson, Laurie C. Menviel, Katrin J. Meissner, Lise Missiaen, Carlye D. Peterson, Lorraine E. Lisiecki, and Fortunat Joos
Clim. Past, 17, 507–528, https://doi.org/10.5194/cp-17-507-2021, https://doi.org/10.5194/cp-17-507-2021, 2021
Short summary
Short summary
The last interglacial was a warm period that may provide insights into future climates. Here, we compile and analyse stable carbon isotope data from the ocean during the last interglacial and compare it to the Holocene. The data show that Atlantic Ocean circulation was similar during the last interglacial and the Holocene. We also establish a difference in the mean oceanic carbon isotopic ratio between these periods, which was most likely caused by burial and weathering carbon fluxes.
Rupert Gladstone, Benjamin Galton-Fenzi, David Gwyther, Qin Zhou, Tore Hattermann, Chen Zhao, Lenneke Jong, Yuwei Xia, Xiaoran Guo, Konstantinos Petrakopoulos, Thomas Zwinger, Daniel Shapero, and John Moore
Geosci. Model Dev., 14, 889–905, https://doi.org/10.5194/gmd-14-889-2021, https://doi.org/10.5194/gmd-14-889-2021, 2021
Short summary
Short summary
Retreat of the Antarctic ice sheet, and hence its contribution to sea level rise, is highly sensitive to melting of its floating ice shelves. This melt is caused by warm ocean currents coming into contact with the ice. Computer models used for future ice sheet projections are not able to realistically evolve these melt rates. We describe a new coupling framework to enable ice sheet and ocean computer models to interact, allowing projection of the evolution of melt and its impact on sea level.
Masa Kageyama, Louise C. Sime, Marie Sicard, Maria-Vittoria Guarino, Anne de Vernal, Ruediger Stein, David Schroeder, Irene Malmierca-Vallet, Ayako Abe-Ouchi, Cecilia Bitz, Pascale Braconnot, Esther C. Brady, Jian Cao, Matthew A. Chamberlain, Danny Feltham, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina Morozova, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Ryouta O'ishi, Silvana Ramos Buarque, David Salas y Melia, Sam Sherriff-Tadano, Julienne Stroeve, Xiaoxu Shi, Bo Sun, Robert A. Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, Weipeng Zheng, and Tilo Ziehn
Clim. Past, 17, 37–62, https://doi.org/10.5194/cp-17-37-2021, https://doi.org/10.5194/cp-17-37-2021, 2021
Short summary
Short summary
The Last interglacial (ca. 127 000 years ago) is a period with increased summer insolation at high northern latitudes, resulting in a strong reduction in Arctic sea ice. The latest PMIP4-CMIP6 models all simulate this decrease, consistent with reconstructions. However, neither the models nor the reconstructions agree on the possibility of a seasonally ice-free Arctic. Work to clarify the reasons for this model divergence and the conflicting interpretations of the records will thus be needed.
Bette L. Otto-Bliesner, Esther C. Brady, Anni Zhao, Chris M. Brierley, Yarrow Axford, Emilie Capron, Aline Govin, Jeremy S. Hoffman, Elizabeth Isaacs, Masa Kageyama, Paolo Scussolini, Polychronis C. Tzedakis, Charles J. R. Williams, Eric Wolff, Ayako Abe-Ouchi, Pascale Braconnot, Silvana Ramos Buarque, Jian Cao, Anne de Vernal, Maria Vittoria Guarino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina A. Morozova, Kerim H. Nisancioglu, Ryouta O'ishi, David Salas y Mélia, Xiaoxu Shi, Marie Sicard, Louise Sime, Christian Stepanek, Robert Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 17, 63–94, https://doi.org/10.5194/cp-17-63-2021, https://doi.org/10.5194/cp-17-63-2021, 2021
Short summary
Short summary
The CMIP6–PMIP4 Tier 1 lig127k experiment was designed to address the climate responses to strong orbital forcing. We present a multi-model ensemble of 17 climate models, most of which have also completed the CMIP6 DECK experiments and are thus important for assessing future projections. The lig127ksimulations show strong summer warming over the NH continents. More than half of the models simulate a retreat of the Arctic minimum summer ice edge similar to the average for 2000–2018.
Hélène Seroussi, 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, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 14, 3033–3070, https://doi.org/10.5194/tc-14-3033-2020, https://doi.org/10.5194/tc-14-3033-2020, 2020
Short summary
Short summary
The Antarctic ice sheet has been losing mass over at least the past 3 decades in response to changes in atmospheric and oceanic conditions. This study presents an ensemble of model simulations of the Antarctic evolution over the 2015–2100 period based on various ice sheet models, climate forcings and emission scenarios. Results suggest that the West Antarctic ice sheet will continue losing a large amount of ice, while the East Antarctic ice sheet could experience increased snow accumulation.
Nadine Mengis, David P. Keller, Andrew H. MacDougall, Michael Eby, Nesha Wright, Katrin J. Meissner, Andreas Oschlies, Andreas Schmittner, Alexander J. MacIsaac, H. Damon Matthews, and Kirsten Zickfeld
Geosci. Model Dev., 13, 4183–4204, https://doi.org/10.5194/gmd-13-4183-2020, https://doi.org/10.5194/gmd-13-4183-2020, 2020
Short summary
Short summary
In this paper, we evaluate the newest version of the University of Victoria Earth System Climate Model (UVic ESCM 2.10). Combining recent model developments as a joint effort, this version is to be used in the next phase of model intercomparison and climate change studies. The UVic ESCM 2.10 is capable of reproducing changes in historical temperature and carbon fluxes well. Additionally, the model is able to reproduce the three-dimensional distribution of many ocean tracers.
Yoshihiro Nakayama, Ralph Timmermann, and Hartmut H. Hellmer
The Cryosphere, 14, 2205–2216, https://doi.org/10.5194/tc-14-2205-2020, https://doi.org/10.5194/tc-14-2205-2020, 2020
Short summary
Short summary
Previous studies have shown accelerations of West Antarctic glaciers, implying that basal melt rates of these glaciers were small and increased in the middle of the 20th century. We conduct coupled sea ice–ice shelf–ocean simulations with different levels of ice shelf melting from West Antarctic glaciers. This study reveals how far and how quickly glacial meltwater from ice shelves in the Amundsen and Bellingshausen seas propagates downstream into the Ross Sea and along the East Antarctic coast.
Andrew E. Kiss, Andrew McC. Hogg, Nicholas Hannah, Fabio Boeira Dias, Gary B. Brassington, Matthew A. Chamberlain, Christopher Chapman, Peter Dobrohotoff, Catia M. Domingues, Earl R. Duran, Matthew H. England, Russell Fiedler, Stephen M. Griffies, Aidan Heerdegen, Petra Heil, Ryan M. Holmes, Andreas Klocker, Simon J. Marsland, Adele K. Morrison, James Munroe, Maxim Nikurashin, Peter R. Oke, Gabriela S. Pilo, Océane Richet, Abhishek Savita, Paul Spence, Kial D. Stewart, Marshall L. Ward, Fanghua Wu, and Xihan Zhang
Geosci. Model Dev., 13, 401–442, https://doi.org/10.5194/gmd-13-401-2020, https://doi.org/10.5194/gmd-13-401-2020, 2020
Short summary
Short summary
We describe new computer model configurations which simulate the global ocean and sea ice at three resolutions. The coarsest resolution is suitable for multi-century climate projection experiments, whereas the finest resolution is designed for more detailed studies over time spans of decades. The paper provides technical details of the model configurations and an assessment of their performance relative to observations.
Lise S. Graff, Trond Iversen, Ingo Bethke, Jens B. Debernard, Øyvind Seland, Mats Bentsen, Alf Kirkevåg, Camille Li, and Dirk J. L. Olivié
Earth Syst. Dynam., 10, 569–598, https://doi.org/10.5194/esd-10-569-2019, https://doi.org/10.5194/esd-10-569-2019, 2019
Short summary
Short summary
Differences between a 1.5 and a 2.0 °C warmer global climate than 1850 conditions are discussed based on a suite of global atmosphere-only, fully coupled, and slab-ocean runs with the Norwegian Earth System Model. Responses, such as the Arctic amplification of global warming, are stronger with the fully coupled and slab-ocean configurations. While ice-free Arctic summers are rare under 1.5 °C warming in the slab-ocean runs, they are estimated to occur 18 % of the time under 2.0 °C warming.
Karin F. Kvale, Katherine E. Turner, Angela Landolfi, and Katrin J. Meissner
Biogeosciences, 16, 1019–1034, https://doi.org/10.5194/bg-16-1019-2019, https://doi.org/10.5194/bg-16-1019-2019, 2019
Short summary
Short summary
Drivers motivating the evolution of calcifying phytoplankton are poorly understood. We explore differences in global ocean chemistry with and without calcifiers during rapid climate changes. We find the presence of phytoplankton calcifiers stabilizes the volume of low oxygen regions and consequently stabilizes the concentration of nitrate, which is an important nutrient required for photosynthesis. By stabilizing nitrate concentrations, calcifiers improve their growth conditions.
Chad A. Greene, Duncan A. Young, David E. Gwyther, Benjamin K. Galton-Fenzi, and Donald D. Blankenship
The Cryosphere, 12, 2869–2882, https://doi.org/10.5194/tc-12-2869-2018, https://doi.org/10.5194/tc-12-2869-2018, 2018
Short summary
Short summary
We show that Totten Ice Shelf accelerates each spring in response to the breakup of seasonal landfast sea ice at the ice shelf calving front. The previously unreported seasonal flow variability may have aliased measurements in at least one previous study of Totten's response to ocean forcing on interannual timescales. The role of sea ice in buttressing the flow of the ice shelf implies that long-term changes in sea ice cover could have impacts on the mass balance of the East Antarctic Ice Sheet.
Lenneke M. Jong, Rupert M. Gladstone, Benjamin K. Galton-Fenzi, and Matt A. King
The Cryosphere, 12, 2425–2436, https://doi.org/10.5194/tc-12-2425-2018, https://doi.org/10.5194/tc-12-2425-2018, 2018
Short summary
Short summary
We used an ice sheet model to simulate temporary regrounding of a marine ice sheet retreating across a retrograde bedrock slope. We show that a sliding relation incorporating water-filled cavities and the ice overburden pressure at the base allows the temporary regrounding to occur. This suggests that choice of basal sliding relation can be important when modelling grounding line behaviour of regions where potential ice rises and pinning points are present and regrounding could occur.
Sue Cook, Jan Åström, Thomas Zwinger, Benjamin Keith Galton-Fenzi, Jamin Stevens Greenbaum, and Richard Coleman
The Cryosphere, 12, 2401–2411, https://doi.org/10.5194/tc-12-2401-2018, https://doi.org/10.5194/tc-12-2401-2018, 2018
Short summary
Short summary
The growth of fractures on Antarctic ice shelves is important because it controls the amount of ice lost as icebergs. We use a model constructed of multiple interconnected blocks to predict the locations where fractures will form on the Totten Ice Shelf in East Antarctica. The results show that iceberg calving is controlled not only by fractures forming near the front of the ice shelf but also by fractures which formed many kilometres upstream.
Rachael D. Mueller, Tore Hattermann, Susan L. Howard, and Laurie Padman
The Cryosphere, 12, 453–476, https://doi.org/10.5194/tc-12-453-2018, https://doi.org/10.5194/tc-12-453-2018, 2018
Short summary
Short summary
There is evidence that climate change in the Weddell Sea will cause warmer water to flow toward the icy continent and into the ocean cavity circulating beneath a thick (~ 1000 m) ice sheet extension that floats over the Weddell Sea, called the Filchner–Ronne Ice Shelf (FRIS). This paper addresses the impact of this potential warming on the melting of FRIS. It evaluates the previously unexplored feedbacks between ice melting, changes in cavity geometry, tides, and circulation.
Karin F. Kvale and Katrin J. Meissner
Biogeosciences, 14, 4767–4780, https://doi.org/10.5194/bg-14-4767-2017, https://doi.org/10.5194/bg-14-4767-2017, 2017
Short summary
Short summary
Climate models containing ocean biogeochemistry contain a lot of poorly constrained parameters, which makes model tuning difficult. For more than 20 years modellers have generally assumed phytoplankton light attenuation parameter value choice has an insignificant affect on model ocean primary production; thus, it is often overlooked for tuning. We show that an empirical range of light attenuation parameter values can affect primary production, with increasing sensitivity under climate change.
Ralph Timmermann and Sebastian Goeller
Ocean Sci., 13, 765–776, https://doi.org/10.5194/os-13-765-2017, https://doi.org/10.5194/os-13-765-2017, 2017
Short summary
Short summary
A coupled model has been developed to study the interaction between the ocean and the Antarctic ice sheet. Simulations for present-day climate yield realistic ice-shelf melt rates and a grounding line position close to the observed state. In a warm-water-inflow scenario, the model suggests a substantial thinning of the ice shelf and a local retreat of the grounding line. The coupled model yields a stronger increase in ice-shelf basal melt rates than a fixed-geometry control experiment.
Daniela Niemeyer, Tronje P. Kemena, Katrin J. Meissner, and Andreas Oschlies
Earth Syst. Dynam., 8, 357–367, https://doi.org/10.5194/esd-8-357-2017, https://doi.org/10.5194/esd-8-357-2017, 2017
Felicity S. Graham, Jason L. Roberts, Ben K. Galton-Fenzi, Duncan Young, Donald Blankenship, and Martin J. Siegert
Earth Syst. Sci. Data, 9, 267–279, https://doi.org/10.5194/essd-9-267-2017, https://doi.org/10.5194/essd-9-267-2017, 2017
Short summary
Short summary
Antarctic bed topography datasets are interpolated onto low-resolution grids because our observed topography data are sparsely sampled. This has implications for ice-sheet model simulations, especially in regions prone to instability, such as grounding lines, where detailed knowledge of the topography is required. Here, we constructed a high-resolution synthetic bed elevation dataset using observed covariance properties to assess the dependence of simulated ice-sheet dynamics on grid resolution.
Amelie Driemel, Eberhard Fahrbach, Gerd Rohardt, Agnieszka Beszczynska-Möller, Antje Boetius, Gereon Budéus, Boris Cisewski, Ralph Engbrodt, Steffen Gauger, Walter Geibert, Patrizia Geprägs, Dieter Gerdes, Rainer Gersonde, Arnold L. Gordon, Hannes Grobe, Hartmut H. Hellmer, Enrique Isla, Stanley S. Jacobs, Markus Janout, Wilfried Jokat, Michael Klages, Gerhard Kuhn, Jens Meincke, Sven Ober, Svein Østerhus, Ray G. Peterson, Benjamin Rabe, Bert Rudels, Ursula Schauer, Michael Schröder, Stefanie Schumacher, Rainer Sieger, Jüri Sildam, Thomas Soltwedel, Elena Stangeew, Manfred Stein, Volker H Strass, Jörn Thiede, Sandra Tippenhauer, Cornelis Veth, Wilken-Jon von Appen, Marie-France Weirig, Andreas Wisotzki, Dieter A. Wolf-Gladrow, and Torsten Kanzow
Earth Syst. Sci. Data, 9, 211–220, https://doi.org/10.5194/essd-9-211-2017, https://doi.org/10.5194/essd-9-211-2017, 2017
Short summary
Short summary
Our oceans are always in motion – huge water masses are circulated by winds and by global seawater density gradients resulting from different water temperatures and salinities. Measuring temperature and salinity of the world's oceans is crucial e.g. to understand our climate. Since 1983, the research icebreaker Polarstern has been the basis of numerous water profile measurements in the Arctic and the Antarctic. We report on a unique collection of 33 years of polar salinity and temperature data.
Christopher J. Fogwill, Erik van Sebille, Eva A. Cougnon, Chris S. M. Turney, Steve R. Rintoul, Benjamin K. Galton-Fenzi, Graeme F. Clark, E. M. Marzinelli, Eleanor B. Rainsley, and Lionel Carter
The Cryosphere, 10, 2603–2609, https://doi.org/10.5194/tc-10-2603-2016, https://doi.org/10.5194/tc-10-2603-2016, 2016
Short summary
Short summary
Here we report new data from in situ oceanographic surveys and high-resolution ocean modelling experiments in the Commonwealth Bay region of East Antarctica, where in 2010 there was a major reconfiguration of the regional icescape due to the collision of the 97 km long iceberg B09B with the Mertz Glacier tongue. Here we compare post-calving observations with high-resolution ocean modelling which suggest that this reconfiguration has led to the development of a new polynya off Commonwealth Bay.
Janin Schaffer, Ralph Timmermann, Jan Erik Arndt, Steen Savstrup Kristensen, Christoph Mayer, Mathieu Morlighem, and Daniel Steinhage
Earth Syst. Sci. Data, 8, 543–557, https://doi.org/10.5194/essd-8-543-2016, https://doi.org/10.5194/essd-8-543-2016, 2016
Short summary
Short summary
The RTopo-2 data set provides consistent maps of global ocean bathymetry and ice surface topographies for Greenland and Antarctica at 30 arcsec grid spacing. We corrected data from earlier products in the areas of Petermann, Hagen Bræ, and Helheim glaciers, incorporated original data for the floating ice tongue of Nioghalvfjerdsfjorden Glacier, and applied corrections for the geometry of Getz, Abbot, and Fimbul ice shelf cavities. The data set is available from the PANGAEA database.
Xylar S. Asay-Davis, Stephen L. Cornford, Gaël Durand, Benjamin K. Galton-Fenzi, Rupert M. Gladstone, G. Hilmar Gudmundsson, Tore Hattermann, David M. Holland, Denise Holland, Paul R. Holland, Daniel F. Martin, Pierre Mathiot, Frank Pattyn, and Hélène Seroussi
Geosci. Model Dev., 9, 2471–2497, https://doi.org/10.5194/gmd-9-2471-2016, https://doi.org/10.5194/gmd-9-2471-2016, 2016
Short summary
Short summary
Coupled ice sheet–ocean models capable of simulating moving grounding lines are just becoming available. Such models have a broad range of potential applications in studying the dynamics of ice sheets and glaciers, including assessing their contributions to sea level change. Here we describe the idealized experiments that make up three interrelated Model Intercomparison Projects (MIPs) for marine ice sheet models and regional ocean circulation models incorporating ice shelf cavities.
Willem P. Sijp and Matthew H. England
Clim. Past, 12, 543–552, https://doi.org/10.5194/cp-12-543-2016, https://doi.org/10.5194/cp-12-543-2016, 2016
Short summary
Short summary
The polar warmth of the greenhouse climates in the Earth's past represents a fundamentally different climate state to that of today, with a strongly reduced temperature difference between the Equator and the poles. It is commonly thought that this would lead to a more quiescent ocean, with much reduced ventilation of the abyss. Surprisingly, using a Cretaceous cimate model, we find that ocean overturning is not weaker under a reduced temperature gradient arising from amplified polar heat.
S. L. Cornford, D. F. Martin, A. J. Payne, E. G. Ng, A. M. Le Brocq, R. M. Gladstone, T. L. Edwards, S. R. Shannon, C. Agosta, M. R. van den Broeke, H. H. Hellmer, G. Krinner, S. R. M. Ligtenberg, R. Timmermann, and D. G. Vaughan
The Cryosphere, 9, 1579–1600, https://doi.org/10.5194/tc-9-1579-2015, https://doi.org/10.5194/tc-9-1579-2015, 2015
Short summary
Short summary
We used a high-resolution ice sheet model capable of resolving grounding line dynamics (BISICLES) to compute responses of the major West Antarctic ice streams to projections of ocean and atmospheric warming. This is computationally demanding, and although other groups have considered parts of West Antarctica, we think this is the first calculation for the whole region at the sub-kilometer resolution that we show is required.
S. Danilov, Q. Wang, R. Timmermann, N. Iakovlev, D. Sidorenko, M. Kimmritz, T. Jung, and J. Schröter
Geosci. Model Dev., 8, 1747–1761, https://doi.org/10.5194/gmd-8-1747-2015, https://doi.org/10.5194/gmd-8-1747-2015, 2015
Short summary
Short summary
Unstructured meshes allow multi-resolution modeling of ocean dynamics. Sea ice models formulated on unstructured meshes are a necessary component of ocean models intended for climate studies. This work presents a description of a finite-element sea ice model which is used as a component of a finite-element sea ice ocean circulation model. The principles underlying its design can be of interest to other groups pursuing ocean modelling on unstructured meshes.
A. Levermann, R. Winkelmann, S. Nowicki, J. L. Fastook, K. Frieler, R. Greve, H. H. Hellmer, M. A. Martin, M. Meinshausen, M. Mengel, A. J. Payne, D. Pollard, T. Sato, R. Timmermann, W. L. Wang, and R. A. Bindschadler
Earth Syst. Dynam., 5, 271–293, https://doi.org/10.5194/esd-5-271-2014, https://doi.org/10.5194/esd-5-271-2014, 2014
Q. Wang, S. Danilov, D. Sidorenko, R. Timmermann, C. Wekerle, X. Wang, T. Jung, and J. Schröter
Geosci. Model Dev., 7, 663–693, https://doi.org/10.5194/gmd-7-663-2014, https://doi.org/10.5194/gmd-7-663-2014, 2014
K. F. Kvale, K. J. Meissner, D. P. Keller, M. Eby, and A. Schmittner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-1709-2014, https://doi.org/10.5194/gmdd-7-1709-2014, 2014
Revised manuscript not accepted
D. Olbers, H. H. Hellmer, and F. F. J. H. Buck
The Cryosphere Discuss., https://doi.org/10.5194/tcd-8-919-2014, https://doi.org/10.5194/tcd-8-919-2014, 2014
Revised manuscript has not been submitted
L. Menviel, A. Timmermann, T. Friedrich, and M. H. England
Clim. Past, 10, 63–77, https://doi.org/10.5194/cp-10-63-2014, https://doi.org/10.5194/cp-10-63-2014, 2014
S. McGregor, A. Timmermann, M. H. England, O. Elison Timm, and A. T. Wittenberg
Clim. Past, 9, 2269–2284, https://doi.org/10.5194/cp-9-2269-2013, https://doi.org/10.5194/cp-9-2269-2013, 2013
Related subject area
Cryosphere
Coupling framework (1.0) for the Úa (2023b) ice sheet model and the FESOM-1.4 z-coordinate ocean model in an Antarctic domain
A gradient-boosted tree framework to model the ice thickness of the world's glaciers (IceBoost v1.1)
Towards deep-learning solutions for classification of automated snow height measurements (CleanSnow v1.0.2)
Quantitative sub-ice and marine tracing of Antarctic sediment provenance (TASP v1.0)
Tuning parameters of a sea ice model using machine learning
WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China
Clustering simulated snow profiles to form avalanche forecast regions
SnowQM 1.0: a fast R package for bias-correcting spatial fields of snow water equivalent using quantile mapping
Simulation of snow albedo and solar irradiance profile with the Two-streAm Radiative TransfEr in Snow (TARTES) v2.0 model
Computationally efficient subglacial drainage modelling using Gaussian Process emulators: GlaDS-GP v1.0
Evaluation of MITgcm-based ocean reanalyses for the Southern Ocean
Improvements in the land surface configuration to better simulate seasonal snow cover in the European Alps with the CNRM-AROME (cycle 46) convection-permitting regional climate model
A three-stage model pipeline predicting regional avalanche danger in Switzerland (RAvaFcast v1.0.0): a decision-support tool for operational avalanche forecasting
A Flexible Snow Model (FSM 2.1.0) including a forest canopy
Anisotropic metric-based mesh adaptation for ice flow modelling in Firedrake
A global–land snow scheme (GLASS) v1.0 for the GFDL Earth System Model: formulation and evaluation at instrumented sites
Design and performance of ELSA v2.0: an isochronal model for ice-sheet layer tracing
Southern Ocean Ice Prediction System version 1.0 (SOIPS v1.0): description of the system and evaluation of synoptic-scale sea ice forecasts
Lagrangian tracking of sea ice in Community Ice CodE (CICE; version 5)
openAMUNDSEN v1.0: an open-source snow-hydrological model for mountain regions
OpenFOAM-avalanche 2312: depth-integrated models beyond dense-flow avalanches
Refactoring the elastic–viscous–plastic solver from the sea ice model CICE v6.5.1 for improved performance
CMIP6 models overestimate sea ice melt, growth & conduction relative to ice mass balance buoy estimates
A new 3D full-Stokes calving algorithm within Elmer/Ice (v9.0)
The Utrecht Finite Volume Ice-Sheet Model (UFEMISM version 2.0) – part 1: description and idealised experiments
A novel numerical implementation for the surface energy budget of melting snowpacks and glaciers
SnowPappus v1.0, a blowing-snow model for large-scale applications of the Crocus snow scheme
A stochastic parameterization of ice sheet surface mass balance for the Stochastic Ice-Sheet and Sea-Level System Model (StISSM v1.0)
Graphics-processing-unit-accelerated ice flow solver for unstructured meshes using the Shallow-Shelf Approximation (FastIceFlo v1.0.1)
A finite-element framework to explore the numerical solution of the coupled problem of heat conduction, water vapor diffusion, and settlement in dry snow (IvoriFEM v0.1.0)
Description and validation of the ice sheet model Nix v1.0
AvaFrame com1DFA (v1.3): a thickness-integrated computational avalanche module – theory, numerics, and testing
Universal differential equations for glacier ice flow modelling
A new model for supraglacial hydrology evolution and drainage for the Greenland Ice Sheet (SHED v1.0)
Modeling sensitivities of thermally and hydraulically driven ice stream surge cycling
A parallel implementation of the confined–unconfined aquifer system model for subglacial hydrology: design, verification, and performance analysis (CUAS-MPI v0.1.0)
Automatic snow type classification of snow micropenetrometer profiles with machine learning algorithms
An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0
A wind-driven snow redistribution module for Alpine3D v3.3.0: adaptations designed for downscaling ice sheet surface mass balance
The CryoGrid community model (version 1.0) – a multi-physics toolbox for climate-driven simulations in the terrestrial cryosphere
Glacier Energy and Mass Balance (GEMB): a model of firn processes for cryosphere research
Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean
Introducing CRYOWRF v1.0: multiscale atmospheric flow simulations with advanced snow cover modelling
SUHMO: an adaptive mesh refinement SUbglacial Hydrology MOdel v1.0
Improving snow albedo modeling in the E3SM land model (version 2.0) and assessing its impacts on snow and surface fluxes over the Tibetan Plateau
The Multiple Snow Data Assimilation System (MuSA v1.0)
The Stochastic Ice-Sheet and Sea-Level System Model v1.0 (StISSM v1.0)
Improved representation of the contemporary Greenland ice sheet firn layer by IMAU-FDM v1.2G
Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.
Benchmarking the vertically integrated ice-sheet model IMAU-ICE (version 2.0)
Ole Richter, Ralph Timmermann, G. Hilmar Gudmundsson, and Jan De Rydt
Geosci. Model Dev., 18, 2945–2960, https://doi.org/10.5194/gmd-18-2945-2025, https://doi.org/10.5194/gmd-18-2945-2025, 2025
Short summary
Short summary
The new coupled ice sheet–ocean model addresses challenges related to horizontal resolution through advanced mesh flexibility, enabled by the use of unstructured grids. We describe the new model, verify its functioning in an idealised setting and demonstrate its advantages in a global-ocean–Antarctic ice sheet domain. The results of this study comprise an important step towards improving predictions of the Antarctic contribution to sea level rise over centennial timescales.
Niccolò Maffezzoli, Eric Rignot, Carlo Barbante, Troels Petersen, and Sebastiano Vascon
Geosci. Model Dev., 18, 2545–2568, https://doi.org/10.5194/gmd-18-2545-2025, https://doi.org/10.5194/gmd-18-2545-2025, 2025
Short summary
Short summary
In this work we introduce IceBoost, a machine learning framework to model the ice thickness distribution of all the world's glaciers with greater accuracy than state-of-the-art methods. The model is trained on 3.7 million measurements globally available and provides skilful estimates across all regions. This advancement will help in better assessing future sea level changes and freshwater resources, with significance for both the scientific community and society at large.
Jan Svoboda, Marc Ruesch, David Liechti, Corinne Jones, Michele Volpi, Michael Zehnder, and Jürg Schweizer
Geosci. Model Dev., 18, 1829–1849, https://doi.org/10.5194/gmd-18-1829-2025, https://doi.org/10.5194/gmd-18-1829-2025, 2025
Short summary
Short summary
Accurately measuring snow height is key for modeling approaches in climate science, snow hydrology, and avalanche forecasting. Erroneous snow height measurements often occur when snow height is low or changes, for instance during snowfall in summer. We prepare a new benchmark dataset with annotated snow height data and demonstrate how to improve the measurement quality using modern deep-learning approaches. Our approach can be easily implemented in a data pipeline for snow modeling.
James W. Marschalek, Edward Gasson, Tina van de Flierdt, Claus-Dieter Hillenbrand, Martin J. Siegert, and Liam Holder
Geosci. Model Dev., 18, 1673–1708, https://doi.org/10.5194/gmd-18-1673-2025, https://doi.org/10.5194/gmd-18-1673-2025, 2025
Short summary
Short summary
Ice sheet models can help predict how Antarctica's ice sheets respond to environmental change, and such models benefit from comparison to geological data. Here, we use an ice sheet model output and other data to predict the erosion of debris and trace its transport to where it is deposited on the ocean floor. This allows the results of ice sheet modelling to be directly and quantitively compared to real-world data, helping to reduce uncertainty regarding Antarctic sea level contribution.
Anton Korosov, Yue Ying, and Einar Ólason
Geosci. Model Dev., 18, 885–904, https://doi.org/10.5194/gmd-18-885-2025, https://doi.org/10.5194/gmd-18-885-2025, 2025
Short summary
Short summary
We have developed a new method to improve the accuracy of sea ice models, which predict how ice moves and deforms due to wind and ocean currents. Traditional models use parameters that are often poorly defined. The new approach uses machine learning to fine-tune these parameters by comparing simulated ice drift with satellite data. The method identifies optimal settings for the model by analysing patterns in ice deformation. This results in more accurate simulations of sea ice drift forecasting.
Xia Wang, Tao Che, Xueyin Ruan, Shanna Yue, Jing Wang, Chun Zhao, and Lei Geng
Geosci. Model Dev., 18, 651–670, https://doi.org/10.5194/gmd-18-651-2025, https://doi.org/10.5194/gmd-18-651-2025, 2025
Short summary
Short summary
We employed the WRF-Chem model to parameterize atmospheric nitrate deposition in snow and evaluate its performance in simulating snow cover, snow depth, and concentrations of dust and nitrate using new observations from northern China. The results generally exhibit reasonable agreement with field observations in northern China, demonstrating the model's capability to simulate snow properties, including concentrations of reservoir species.
Simon Horton, Florian Herla, and Pascal Haegeli
Geosci. Model Dev., 18, 193–209, https://doi.org/10.5194/gmd-18-193-2025, https://doi.org/10.5194/gmd-18-193-2025, 2025
Short summary
Short summary
We present a method for avalanche forecasters to analyze patterns in snowpack model simulations. It uses fuzzy clustering to group small regions into larger forecast areas based on snow characteristics, locations, and temporal history. Tested in the Columbia Mountains in two winter seasons, it closely matched real forecast regions regions and identified major avalanche hazard patterns. This approach simplifies complex model outputs, helping forecasters make informed decisions.
Adrien Michel, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty
Geosci. Model Dev., 17, 8969–8988, https://doi.org/10.5194/gmd-17-8969-2024, https://doi.org/10.5194/gmd-17-8969-2024, 2024
Short summary
Short summary
We present a method to correct snow cover maps (represented in terms of snow water equivalent) to match better-quality maps. The correction can then be extended backwards and forwards in time for periods when better-quality maps are not available. The method is fast and gives good results. It is then applied to obtain a climatology of the snow cover in Switzerland over the past 60 years at a resolution of 1 d and 1 km. This is the first time that such a dataset has been produced.
Ghislain Picard and Quentin Libois
Geosci. Model Dev., 17, 8927–8953, https://doi.org/10.5194/gmd-17-8927-2024, https://doi.org/10.5194/gmd-17-8927-2024, 2024
Short summary
Short summary
The Two-streAm Radiative TransfEr in Snow (TARTES) is a radiative transfer model to compute snow albedo in the solar domain and the profiles of light and energy absorption in a multi-layered snowpack whose physical properties are user defined. It uniquely considers snow grain shape flexibly, based on recent insights showing that snow does not behave as a collection of ice spheres but instead as a random medium. TARTES is user-friendly yet performs comparably to more complex models.
Tim Hill, Derek Bingham, Gwenn E. Flowers, and Matthew J. Hoffman
EGUsphere, https://doi.org/10.22541/essoar.172736254.41350153/v2, https://doi.org/10.22541/essoar.172736254.41350153/v2, 2024
Short summary
Short summary
Subglacial drainage models represent water flow beneath glaciers and ice sheets. Here, we train fast statistical models called Gaussian Process 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.
Yoshihiro Nakayama, Alena Malyarenko, Hong Zhang, Ou Wang, Matthis Auger, Yafei Nie, Ian Fenty, Matthew Mazloff, Armin Köhl, and Dimitris Menemenlis
Geosci. Model Dev., 17, 8613–8638, https://doi.org/10.5194/gmd-17-8613-2024, https://doi.org/10.5194/gmd-17-8613-2024, 2024
Short summary
Short summary
Global- and basin-scale ocean reanalyses are becoming easily accessible. However, such ocean reanalyses are optimized for their entire model domains and their ability to simulate the Southern Ocean requires evaluation. We conduct intercomparison analyses of Massachusetts Institute of Technology General Circulation Model (MITgcm)-based ocean reanalyses. They generally perform well for the open ocean, but open-ocean temporal variability and Antarctic continental shelves require improvements.
Diego Monteiro, Cécile Caillaud, Matthieu Lafaysse, Adrien Napoly, Mathieu Fructus, Antoinette Alias, and Samuel Morin
Geosci. Model Dev., 17, 7645–7677, https://doi.org/10.5194/gmd-17-7645-2024, https://doi.org/10.5194/gmd-17-7645-2024, 2024
Short summary
Short summary
Modeling snow cover in climate and weather forecasting models is a challenge even for high-resolution models. Recent simulations with CNRM-AROME have shown difficulties when representing snow in the European Alps. Using remote sensing data and in situ observations, we evaluate modifications of the land surface configuration in order to improve it. We propose a new surface configuration, enabling a more realistic simulation of snow cover, relevant for climate and weather forecasting applications.
Alessandro Maissen, Frank Techel, and Michele Volpi
Geosci. Model Dev., 17, 7569–7593, https://doi.org/10.5194/gmd-17-7569-2024, https://doi.org/10.5194/gmd-17-7569-2024, 2024
Short summary
Short summary
By harnessing AI models, this work enables processing large amounts of data, including weather conditions, snowpack characteristics, and historical avalanche data, to predict human-like avalanche forecasts in Switzerland. Our proposed model can significantly assist avalanche forecasters in their decision-making process, thereby facilitating more efficient and accurate predictions crucial for ensuring safety in Switzerland's avalanche-prone regions.
Richard Essery, Giulia Mazzotti, Sarah Barr, Tobias Jonas, Tristan Quaife, and Nick Rutter
EGUsphere, https://doi.org/10.5194/egusphere-2024-2546, https://doi.org/10.5194/egusphere-2024-2546, 2024
Short summary
Short summary
How forests influence accumulation and melt of snow on the ground is of long-standing interest, but uncertainty remains in how best to model forest snow processes. We developed the Flexible Snow Model version 2 to quantify these uncertainties. In a first model demonstration, how unloading of intercepted snow from the forest canopy is represented is responsible for the largest uncertainty. Global mapping of forest distribution is also likely to be a large source of uncertainty in existing models.
Davor Dundovic, Joseph G. Wallwork, Stephan C. Kramer, Fabien Gillet-Chaulet, Regine Hock, and Matthew D. Piggott
EGUsphere, https://doi.org/10.5194/egusphere-2024-2649, https://doi.org/10.5194/egusphere-2024-2649, 2024
Short summary
Short summary
Accurate numerical studies of glaciers often require high-resolution simulations, which often prove too demanding even for modern computers. In this paper we develop a method that identifies whether different parts of a glacier require high or low resolution based on its physical features, such as its thickness and velocity. We show that by doing so we can achieve a more optimal simulation accuracy for the available computing resources compared to uniform resolution simulations.
Enrico Zorzetto, Sergey Malyshev, Paul Ginoux, and Elena Shevliakova
Geosci. Model Dev., 17, 7219–7244, https://doi.org/10.5194/gmd-17-7219-2024, https://doi.org/10.5194/gmd-17-7219-2024, 2024
Short summary
Short summary
We describe a new snow scheme developed for use in global climate models, which simulates the interactions of snowpack with vegetation, atmosphere, and soil. We test the new snow model over a set of sites where in situ observations are available. We find that when compared to a simpler snow model, this model improves predictions of seasonal snow and of soil temperature under the snowpack, important variables for simulating both the hydrological cycle and the global climate system.
Therese Rieckh, Andreas Born, Alexander Robinson, Robert Law, and Gerrit Gülle
Geosci. Model Dev., 17, 6987–7000, https://doi.org/10.5194/gmd-17-6987-2024, https://doi.org/10.5194/gmd-17-6987-2024, 2024
Short summary
Short summary
We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. It creates layers of snow accumulation at fixed times during the simulation, which are used to model the internal stratification of the ice sheet. Together with reconstructed isochrones from radiostratigraphy data, ELSA can be used to assess ice sheet models and to improve their parameterization. ELSA can be used coupled to an ice sheet model or forced with its output.
Fu Zhao, Xi Liang, Zhongxiang Tian, Ming Li, Na Liu, and Chengyan Liu
Geosci. Model Dev., 17, 6867–6886, https://doi.org/10.5194/gmd-17-6867-2024, https://doi.org/10.5194/gmd-17-6867-2024, 2024
Short summary
Short summary
In this work, we introduce a newly developed Antarctic sea ice forecasting system, namely the Southern Ocean Ice Prediction System (SOIPS). The system is based on a regional sea ice‒ocean‒ice shelf coupled model and can assimilate sea ice concentration observations. By assessing the system's performance in sea ice forecasts, we find that the system can provide reliable Antarctic sea ice forecasts for the next 7 d and has the potential to guide ship navigation in the Antarctic sea ice zone.
Chenhui Ning, Shiming Xu, Yan Zhang, Xuantong Wang, Zhihao Fan, and Jiping Liu
Geosci. Model Dev., 17, 6847–6866, https://doi.org/10.5194/gmd-17-6847-2024, https://doi.org/10.5194/gmd-17-6847-2024, 2024
Short summary
Short summary
Sea ice models are mainly based on non-moving structured grids, which is different from buoy measurements that follow the ice drift. To facilitate Lagrangian analysis, we introduce online tracking of sea ice in Community Ice CodE (CICE). We validate the sea ice tracking with buoys and evaluate the sea ice deformation in high-resolution simulations, which show multi-fractal characteristics. The source code is openly available and can be used in various scientific and operational applications.
Ulrich Strasser, Michael Warscher, Erwin Rottler, and Florian Hanzer
Geosci. Model Dev., 17, 6775–6797, https://doi.org/10.5194/gmd-17-6775-2024, https://doi.org/10.5194/gmd-17-6775-2024, 2024
Short summary
Short summary
openAMUNDSEN is a fully distributed open-source snow-hydrological model for mountain catchments. It includes process representations of an empirical, semi-empirical, and physical nature. It uses temperature, precipitation, humidity, radiation, and wind speed as forcing data and is computationally efficient, of a modular nature, and easily extendible. The Python code is available on GitHub (https://github.com/openamundsen/openamundsen), including documentation (https://doc.openamundsen.org).
Matthias Rauter and Julia Kowalski
Geosci. Model Dev., 17, 6545–6569, https://doi.org/10.5194/gmd-17-6545-2024, https://doi.org/10.5194/gmd-17-6545-2024, 2024
Short summary
Short summary
Snow avalanches can form large powder clouds that substantially exceed the velocity and reach of the dense core. Only a few complex models exist to simulate this phenomenon, and the respective hazard is hard to predict. This work provides a novel flow model that focuses on simple relations while still encapsulating the significant behaviour. The model is applied to reconstruct two catastrophic powder snow avalanche events in Austria.
Till Andreas Soya Rasmussen, Jacob Poulsen, Mads Hvid Ribergaard, Ruchira Sasanka, Anthony P. Craig, Elizabeth C. Hunke, and Stefan Rethmeier
Geosci. Model Dev., 17, 6529–6544, https://doi.org/10.5194/gmd-17-6529-2024, https://doi.org/10.5194/gmd-17-6529-2024, 2024
Short summary
Short summary
Earth system models (ESMs) today strive for better quality based on improved resolutions and improved physics. A limiting factor is the supercomputers at hand and how best to utilize them. This study focuses on the refactorization of one part of a sea ice model (CICE), namely the dynamics. It shows that the performance can be significantly improved, which means that one can either run the same simulations much cheaper or advance the system according to what is needed.
Alex Edward West and Edward William Blockley
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-121, https://doi.org/10.5194/gmd-2024-121, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study uses ice mass balance buoys – temperature and height-measuring devices frozen into sea ice – to find how well climate models simulate the melt & growth of, and conduction of heat through, Arctic sea ice. This may help understand why models produce varying amounts of sea ice in the present day. We find models tend to show more melt, growth or conduction for a given ice thickness than the buoys, though the difference is smaller for models with more physically realistic thermodynamics.
Iain Wheel, Douglas I. Benn, Anna J. Crawford, Joe Todd, and Thomas Zwinger
Geosci. Model Dev., 17, 5759–5777, https://doi.org/10.5194/gmd-17-5759-2024, https://doi.org/10.5194/gmd-17-5759-2024, 2024
Short summary
Short summary
Calving, the detachment of large icebergs from glaciers, is one of the largest uncertainties in future sea level rise projections. This process is poorly understood, and there is an absence of detailed models capable of simulating calving. A new 3D calving model has been developed to better understand calving at glaciers where detailed modelling was previously limited. Importantly, the new model is very flexible. By allowing for unrestricted calving geometries, it can be applied at any location.
Constantijn J. Berends, Victor Azizi, Jorge Bernales, and Roderik S. W. van de Wal
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-5, https://doi.org/10.5194/gmd-2024-5, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Ice-sheet models are computer programs that can simulate how the Greenland and Antarctic ice sheets will evolve in the future. The accuracy of these models depends on their resolution: how small the details are that the model can resolve. We have created a model with a variable resolution, which can resolve a lot of detail in areas where lots of changes happen in the ice, and less detail in areas where the ice does not move so much. This makes the model both accurate and fast.
Kévin Fourteau, Julien Brondex, Fanny Brun, and Marie Dumont
Geosci. Model Dev., 17, 1903–1929, https://doi.org/10.5194/gmd-17-1903-2024, https://doi.org/10.5194/gmd-17-1903-2024, 2024
Short summary
Short summary
In this paper, we provide a novel numerical implementation for solving the energy exchanges at the surface of snow and ice. By combining the strong points of previous models, our solution leads to more accurate and robust simulations of the energy exchanges, surface temperature, and melt while preserving a reasonable computation time.
Matthieu Baron, Ange Haddjeri, Matthieu Lafaysse, Louis Le Toumelin, Vincent Vionnet, and Mathieu Fructus
Geosci. Model Dev., 17, 1297–1326, https://doi.org/10.5194/gmd-17-1297-2024, https://doi.org/10.5194/gmd-17-1297-2024, 2024
Short summary
Short summary
Increasing the spatial resolution of numerical systems simulating snowpack evolution in mountain areas requires representing small-scale processes such as wind-induced snow transport. We present SnowPappus, a simple scheme coupled with the Crocus snow model to compute blowing-snow fluxes and redistribute snow among grid points at 250 m resolution. In terms of numerical cost, it is suitable for large-scale applications. We present point-scale evaluations of fluxes and snow transport occurrence.
Lizz Ultee, Alexander A. Robel, and Stefano Castruccio
Geosci. Model Dev., 17, 1041–1057, https://doi.org/10.5194/gmd-17-1041-2024, https://doi.org/10.5194/gmd-17-1041-2024, 2024
Short summary
Short summary
The surface mass balance (SMB) of an ice sheet describes the net gain or loss of mass from ice sheets (such as those in Greenland and Antarctica) through interaction with the atmosphere. We developed a statistical method to generate a wide range of SMB fields that reflect the best understanding of SMB processes. Efficiently sampling the variability of SMB will help us understand sources of uncertainty in ice sheet model projections.
Anjali Sandip, Ludovic Räss, and Mathieu Morlighem
Geosci. Model Dev., 17, 899–909, https://doi.org/10.5194/gmd-17-899-2024, https://doi.org/10.5194/gmd-17-899-2024, 2024
Short summary
Short summary
We solve momentum balance for unstructured meshes to predict ice flow for real glaciers using a pseudo-transient method on graphics processing units (GPUs) and compare it to a standard central processing unit (CPU) implementation. We justify the GPU implementation by applying the price-to-performance metric for up to million-grid-point spatial resolutions. This study represents a first step toward leveraging GPU processing power, enabling more accurate polar ice discharge predictions.
Julien Brondex, Kévin Fourteau, Marie Dumont, Pascal Hagenmuller, Neige Calonne, François Tuzet, and Henning Löwe
Geosci. Model Dev., 16, 7075–7106, https://doi.org/10.5194/gmd-16-7075-2023, https://doi.org/10.5194/gmd-16-7075-2023, 2023
Short summary
Short summary
Vapor diffusion is one of the main processes governing snowpack evolution, and it must be accounted for in models. Recent attempts to represent vapor diffusion in numerical models have faced several difficulties regarding computational cost and mass and energy conservation. Here, we develop our own finite-element software to explore numerical approaches and enable us to overcome these difficulties. We illustrate the capability of these approaches on established numerical benchmarks.
Daniel Moreno-Parada, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
EGUsphere, https://doi.org/10.5194/egusphere-2023-2690, https://doi.org/10.5194/egusphere-2023-2690, 2023
Short summary
Short summary
We introduce Nix, an ice-sheet model designed for understanding how large masses of ice behave. Nix as a computer program that simulates the movement and temperature changes in ice sheets. Nix helps us study how ice sheets respond to changes in the atmosphere and ocean. We found that how fast ice melts under the shelves and how heat is exchanged, play a role in determining the future of ice sheets. Nix is a useful tool for learning more about how climate change affects polar ice sheets.
Matthias Tonnel, Anna Wirbel, Felix Oesterle, and Jan-Thomas Fischer
Geosci. Model Dev., 16, 7013–7035, https://doi.org/10.5194/gmd-16-7013-2023, https://doi.org/10.5194/gmd-16-7013-2023, 2023
Short summary
Short summary
Avaframe - the open avalanche framework - provides open-source tools to simulate and investigate snow avalanches. It is utilized for multiple purposes, the two main applications being hazard mapping and scientific research of snow processes. We present the theory, conversion to a computer model, and testing for one of the core modules used for simulations of a particular type of avalanche, the so-called dense-flow avalanches. Tests check and confirm the applicability of the utilized method.
Jordi Bolibar, Facundo Sapienza, Fabien Maussion, Redouane Lguensat, Bert Wouters, and Fernando Pérez
Geosci. Model Dev., 16, 6671–6687, https://doi.org/10.5194/gmd-16-6671-2023, https://doi.org/10.5194/gmd-16-6671-2023, 2023
Short summary
Short summary
We developed a new modelling framework combining numerical methods with machine learning. Using this approach, we focused on understanding how ice moves within glaciers, and we successfully learnt a prescribed law describing ice movement for 17 glaciers worldwide as a proof of concept. Our framework has the potential to discover important laws governing glacier processes, aiding our understanding of glacier physics and their contribution to water resources and sea-level rise.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
Short summary
Short summary
We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Kevin Hank, Lev Tarasov, and Elisa Mantelli
Geosci. Model Dev., 16, 5627–5652, https://doi.org/10.5194/gmd-16-5627-2023, https://doi.org/10.5194/gmd-16-5627-2023, 2023
Short summary
Short summary
Physically meaningful modeling of geophysical system instabilities is numerically challenging, given the potential effects of purely numerical artifacts. Here we explore the sensitivity of ice stream surge activation to numerical and physical model aspects. We find that surge characteristics exhibit a resolution dependency but converge at higher horizontal grid resolutions and are significantly affected by the incorporation of bed thermal and sub-glacial hydrology models.
Yannic Fischler, Thomas Kleiner, Christian Bischof, Jeremie Schmiedel, Roiy Sayag, Raban Emunds, Lennart Frederik Oestreich, and Angelika Humbert
Geosci. Model Dev., 16, 5305–5322, https://doi.org/10.5194/gmd-16-5305-2023, https://doi.org/10.5194/gmd-16-5305-2023, 2023
Short summary
Short summary
Water underneath ice sheets affects the motion of glaciers. This study presents a newly developed code, CUAS-MPI, that simulates subglacial hydrology. It is designed for supercomputers and is hence a parallelized code. We measure the performance of this code for simulations of the entire Greenland Ice Sheet and find that the code works efficiently. Moreover, we validated the code to ensure the correctness of the solution. CUAS-MPI opens new possibilities for simulations of ice sheet hydrology.
Julia Kaltenborn, Amy R. Macfarlane, Viviane Clay, and Martin Schneebeli
Geosci. Model Dev., 16, 4521–4550, https://doi.org/10.5194/gmd-16-4521-2023, https://doi.org/10.5194/gmd-16-4521-2023, 2023
Short summary
Short summary
Snow layer segmentation and snow grain classification are essential diagnostic tasks for cryospheric applications. A SnowMicroPen (SMP) can be used to that end; however, the manual classification of its profiles becomes infeasible for large datasets. Here, we evaluate how well machine learning models automate this task. Of the 14 models trained on the MOSAiC SMP dataset, the long short-term memory model performed the best. The findings presented here facilitate and accelerate SMP data analysis.
Johannes Aschauer, Adrien Michel, Tobias Jonas, and Christoph Marty
Geosci. Model Dev., 16, 4063–4081, https://doi.org/10.5194/gmd-16-4063-2023, https://doi.org/10.5194/gmd-16-4063-2023, 2023
Short summary
Short summary
Snow water equivalent is the mass of water stored in a snowpack. Based on exponential settling functions, the empirical snow density model SWE2HS is presented to convert time series of daily snow water equivalent into snow depth. The model has been calibrated with data from Switzerland and validated with independent data from the European Alps. A reference implementation of SWE2HS is available as a Python package.
Eric Keenan, Nander Wever, Jan T. M. Lenaerts, and Brooke Medley
Geosci. Model Dev., 16, 3203–3219, https://doi.org/10.5194/gmd-16-3203-2023, https://doi.org/10.5194/gmd-16-3203-2023, 2023
Short summary
Short summary
Ice sheets gain mass via snowfall. However, snowfall is redistributed by the wind, resulting in accumulation differences of up to a factor of 5 over distances as short as 5 km. These differences complicate estimates of ice sheet contribution to sea level rise. For this reason, we have developed a new model for estimating wind-driven snow redistribution on ice sheets. We show that, over Pine Island Glacier in West Antarctica, the model improves estimates of snow accumulation variability.
Sebastian Westermann, Thomas Ingeman-Nielsen, Johanna Scheer, Kristoffer Aalstad, Juditha Aga, Nitin Chaudhary, Bernd Etzelmüller, Simon Filhol, Andreas Kääb, Cas Renette, Louise Steffensen Schmidt, Thomas Vikhamar Schuler, Robin B. Zweigel, Léo Martin, Sarah Morard, Matan Ben-Asher, Michael Angelopoulos, Julia Boike, Brian Groenke, Frederieke Miesner, Jan Nitzbon, Paul Overduin, Simone M. Stuenzi, and Moritz Langer
Geosci. Model Dev., 16, 2607–2647, https://doi.org/10.5194/gmd-16-2607-2023, https://doi.org/10.5194/gmd-16-2607-2023, 2023
Short summary
Short summary
The CryoGrid community model is a new tool for simulating ground temperatures and the water and ice balance in cold regions. It is a modular design, which makes it possible to test different schemes to simulate, for example, permafrost ground in an efficient way. The model contains tools to simulate frozen and unfrozen ground, snow, glaciers, and other massive ice bodies, as well as water bodies.
Alex S. Gardner, Nicole-Jeanne Schlegel, and Eric Larour
Geosci. Model Dev., 16, 2277–2302, https://doi.org/10.5194/gmd-16-2277-2023, https://doi.org/10.5194/gmd-16-2277-2023, 2023
Short summary
Short summary
This is the first description of the open-source Glacier Energy and Mass Balance (GEMB) model. GEMB models the ice sheet and glacier surface–atmospheric energy and mass exchange, as well as the firn state. The model is evaluated against the current state of the art and in situ observations and is shown to perform well.
Yafei Nie, Chengkun Li, Martin Vancoppenolle, Bin Cheng, Fabio Boeira Dias, Xianqing Lv, and Petteri Uotila
Geosci. Model Dev., 16, 1395–1425, https://doi.org/10.5194/gmd-16-1395-2023, https://doi.org/10.5194/gmd-16-1395-2023, 2023
Short summary
Short summary
State-of-the-art Earth system models simulate the observed sea ice extent relatively well, but this is often due to errors in the dynamic and other processes in the simulated sea ice changes cancelling each other out. We assessed the sensitivity of these processes simulated by the coupled ocean–sea ice model NEMO4.0-SI3 to 18 parameters. The performance of the model in simulating sea ice change processes was ultimately improved by adjusting the three identified key parameters.
Varun Sharma, Franziska Gerber, and Michael Lehning
Geosci. Model Dev., 16, 719–749, https://doi.org/10.5194/gmd-16-719-2023, https://doi.org/10.5194/gmd-16-719-2023, 2023
Short summary
Short summary
Most current generation climate and weather models have a relatively simplistic description of snow and snow–atmosphere interaction. One reason for this is the belief that including an advanced snow model would make the simulations too computationally demanding. In this study, we bring together two state-of-the-art models for atmosphere (WRF) and snow cover (SNOWPACK) and highlight both the feasibility and necessity of such coupled models to explore underexplored phenomena in the cryosphere.
Anne M. Felden, Daniel F. Martin, and Esmond G. Ng
Geosci. Model Dev., 16, 407–425, https://doi.org/10.5194/gmd-16-407-2023, https://doi.org/10.5194/gmd-16-407-2023, 2023
Short summary
Short summary
We present and validate a novel subglacial hydrology model, SUHMO, based on an adaptive mesh refinement framework. We propose the addition of a pseudo-diffusion to recover the wall melting in channels. Computational performance analysis demonstrates the efficiency of adaptive mesh refinement on large-scale hydrologic problems. The adaptive mesh refinement approach will eventually enable better ice bed boundary conditions for ice sheet simulations at a reasonable computational cost.
Dalei Hao, Gautam Bisht, Karl Rittger, Edward Bair, Cenlin He, Huilin Huang, Cheng Dang, Timbo Stillinger, Yu Gu, Hailong Wang, Yun Qian, and L. Ruby Leung
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, https://doi.org/10.5194/gmd-16-75-2023, 2023
Short summary
Short summary
Snow with the highest albedo of land surface plays a vital role in Earth’s surface energy budget and water cycle. This study accounts for the impacts of snow grain shape and mixing state of light-absorbing particles with snow on snow albedo in the E3SM land model. The findings advance our understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offer guidance for improving snow simulations and radiative forcing estimates in Earth system models.
Esteban Alonso-González, Kristoffer Aalstad, Mohamed Wassim Baba, Jesús Revuelto, Juan Ignacio López-Moreno, Joel Fiddes, Richard Essery, and Simon Gascoin
Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, https://doi.org/10.5194/gmd-15-9127-2022, 2022
Short summary
Short summary
Snow cover plays an important role in many processes, but its monitoring is a challenging task. The alternative is usually to simulate the snowpack, and to improve these simulations one of the most promising options is to fuse simulations with available observations (data assimilation). In this paper we present MuSA, a data assimilation tool which facilitates the implementation of snow monitoring initiatives, allowing the assimilation of a wide variety of remotely sensed snow cover information.
Vincent Verjans, Alexander A. Robel, Helene Seroussi, Lizz Ultee, and Andrew F. Thompson
Geosci. Model Dev., 15, 8269–8293, https://doi.org/10.5194/gmd-15-8269-2022, https://doi.org/10.5194/gmd-15-8269-2022, 2022
Short summary
Short summary
We describe the development of the first large-scale ice sheet model that accounts for stochasticity in a range of processes. Stochasticity allows the impacts of inherently uncertain processes on ice sheets to be represented. This includes climatic uncertainty, as the climate is inherently chaotic. Furthermore, stochastic capabilities also encompass poorly constrained glaciological processes that display strong variability at fine spatiotemporal scales. We present the model and test experiments.
Max Brils, Peter Kuipers Munneke, Willem Jan van de Berg, and Michiel van den Broeke
Geosci. Model Dev., 15, 7121–7138, https://doi.org/10.5194/gmd-15-7121-2022, https://doi.org/10.5194/gmd-15-7121-2022, 2022
Short summary
Short summary
Firn covers the Greenland ice sheet (GrIS) and can temporarily prevent mass loss. Here, we present the latest version of our firn model, IMAU-FDM, with an application to the GrIS. We improved the density of fallen snow, the firn densification rate and the firn's thermal conductivity. This leads to a higher air content and 10 m temperatures. Furthermore we investigate three case studies and find that the updated model shows greater variability and an increased sensitivity in surface elevation.
Océane Hames, Mahdi Jafari, David Nicholas Wagner, Ian Raphael, David Clemens-Sewall, Chris Polashenski, Matthew D. Shupe, Martin Schneebeli, and Michael Lehning
Geosci. Model Dev., 15, 6429–6449, https://doi.org/10.5194/gmd-15-6429-2022, https://doi.org/10.5194/gmd-15-6429-2022, 2022
Short summary
Short summary
This paper presents an Eulerian–Lagrangian snow transport model implemented in the fluid dynamics software OpenFOAM, which we call snowBedFoam 1.0. We apply this model to reproduce snow deposition on a piece of ridged Arctic sea ice, which was produced during the MOSAiC expedition through scan measurements. The model appears to successfully reproduce the enhanced snow accumulation and deposition patterns, although some quantitative uncertainties were shown.
Constantijn J. Berends, Heiko Goelzer, Thomas J. Reerink, Lennert B. Stap, and Roderik S. W. van de Wal
Geosci. Model Dev., 15, 5667–5688, https://doi.org/10.5194/gmd-15-5667-2022, https://doi.org/10.5194/gmd-15-5667-2022, 2022
Short summary
Short summary
The rate at which marine ice sheets such as the West Antarctic ice sheet will retreat in a warming climate and ocean is still uncertain. Numerical ice-sheet models, which solve the physical equations that describe the way glaciers and ice sheets deform and flow, have been substantially improved in recent years. Here we present the results of several years of work on IMAU-ICE, an ice-sheet model of intermediate complexity, which can be used to study ice sheets of both the past and the future.
Cited articles
Arakawa, A. and Lamb, V. R.: Computational design of the basic dynamical
processes of the UCLA general circulation model, Methods in Computational
Physics: Advances in Research and Applications, 17, 173–265, 1977. a
Asay-Davis, X. S., Cornford, S. L., Durand, G., Galton-Fenzi, B. K.,
Gladstone, R. M., Gudmundsson, G. H., Hattermann, T., Holland, D. M.,
Holland, D., Holland, P. R., Martin, D. F., Mathiot, P., Pattyn, F., and
Seroussi, H.: Experimental design for three interrelated marine ice sheet and
ocean model intercomparison projects: MISMIP v. 3 (MISMIP +), ISOMIP v. 2
(ISOMIP +) and MISOMIP v. 1 (MISOMIP1), Geosci. Model Dev., 9, 2471–2497,
https://doi.org/10.5194/gmd-9-2471-2016, 2016. a, b
AVISO: AVISO Level 4 Absolute Dynamic Topography for Climate Model
Comparison, Version 1, https://doi.org/10.5067/DYNTO-1D1M1, 2011. a
Bodas-Salcedo, A., Andrews, T., Karmalkar, A. V., and Ringer, M. A.: Cloud
liquid water path and radiative feedbacks over the Southern Ocean, Geophys.
Res. Lett., 43, 10938–10946, https://doi.org/10.1002/2016GL070770, 2016. a
Bouillon, S., Fichefet, T., Legat, V., and Madec, G.: The
elastic-viscous-plastic method revisited, Ocean Model., 71, 2–12,
https://doi.org/10.1016/j.ocemod.2013.05.013, 2013. a
Briegleb, B. P. and Light, B.: A Delta-Eddington multiple scattering
parameterization for solar radiation in the sea ice component of the
Community Climate System Model: NCAR Tech. Note NCAR/TN-472+STR, Tech. rep.,
National Center for Atmospheric Research, 2007. a
Chapman, D. C.: Numerical Treatment of Cross-Shelf Open Boundaries in a
Barotropic Coastal Ocean Model, J. Phys. Oceanogr., 15, 1060–1075,
https://doi.org/10.1175/1520-0485(1985)015<1060:NTOCSO>2.0.CO;2, 1985. a
Cook, C. P., van de Flierdt, T., Williams, T., Hemming, S. R., Iwai, M.,
Kobayashi, M., Jimenez-Espejo, F. J., Escutia, C., González, J. J.,
Khim, B.-K., McKay, R. M., Passchier, S., Bohaty, S. M., Riesselman, C. R.,
Tauxe, L., Sugisaki, S., Galindo, A. L., Patterson, M. O., Sangiorgi, F.,
Pierce, E. L., Brinkhuis, H., Klaus, A., Fehr, A., Bendle, J. A. P., Bijl,
P. K., Carr, S. A., Dunbar, R. B., Flores, J. A., Hayden, T. G., Katsuki, K.,
Kong, G. S., Nakai, M., Olney, M. P., Pekar, S. F., Pross, J., Röhl,
U., Sakai, T., Shrivastava, P. K., Stickley, C. E., Tuo, S., Welsh, K., and
Yamane, M.: Dynamic behaviour of the East Antarctic ice sheet during
Pliocene warmth, Nat. Geosci., 6, 765–769, https://doi.org/10.1038/ngeo1889, 2013. a
Cougnon, E. A., Galton-Fenzi, B. K., Meijers, A. J. S., and Legrésy,
B.: Modeling interannual dense shelf water export in the region of the Mertz
Glacier Tongue (1992–2007), J. Geophys. Res.-Oceans, 118, 5858–5872,
https://doi.org/10.1002/2013JC008790, 2013. a
Cunningham, S. A., Alderson, S. G., King, B. A., and Brandon, M. A.:
Transport and variability of the Antarctic Circumpolar Current in Drake
Passage, J. Geophys. Res., 108, 8084, https://doi.org/10.1029/2001JC001147, 2003. a
Debernard, J. B., Kristensen, N. M., Maartensson, S., Wang, K., and Waagbo,
G. A.: metno/metroms: Intermediate release, https://doi.org/10.5281/zenodo.290667,
2017. a
Deconto, R. M. and Pollard, D.: Contribution of Antarctica to past and
future sea-level rise, Nature, 531, 591–597, https://doi.org/10.1038/nature17145,
2016. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P.,
Bechtold, P., Beljaars, A. C. M., van de Berg, I., Biblot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Greer, A. J., Haimberger, L., Healy, S.
B., Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Kohler, M.,
Matricardi, M., McNally, A. P., Mong-Sanz, B. M., Morcette, J.-J., Park,
B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitart,
F.: The ERA-Interim reanalysis: Configuration and performance of the data
assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597,
doi:10.1002/qj.828, 2011. a
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, b, c
Dinniman, M. S., Klinck, J. M., and Smith, W. O.: A model study of
Circumpolar Deep Water on the West Antarctic Peninsula and Ross Sea
continental shelves, Deep-Sea Res. Pt. II, 58, 1508–1523,
https://doi.org/10.1016/j.dsr2.2010.11.013, 2011. a
Dinniman, M. S., Asay-Davis, X. S., Galton-Fenzi, B. K., Holland, P. R., and
Jenkins, A.: Modeling Ice Shelf/Ocean Interaction in Antarctica: a review,
Oceanography, 29, 144–153, https://doi.org/10.5670/oceanog.2016.106, 2016. a
Donohue, K. A., Tracey, K. L., Watts, D. R., Chidichimo, M. P., and
Chereskin, T. K.: Mean Antarctic Circumpolar Current transport measured in
Drake Passage, Geophys. Res. Lett., 43, 11,760–11,767,
https://doi.org/10.1002/2016GL070319, 2016. a, b
Dupont, T. K.: Assessment of the importance of ice-shelf buttressing to
ice-sheet flow, Geophys. Res. Letters, 32, L04503,
https://doi.org/10.1029/2004GL022024, 2005. a
Dutrieux, P., De Rydt, J., Jenkins, A., Holland, P. R., Ha, H. K., Lee,
S. H., Steig, E. J., Ding, Q., Abrahamsen, E. P., and Schröder, M.:
Strong sensitivity of Pine Island ice-shelf melting to climatic
variability, Science, 343, 174–178, https://doi.org/10.1126/science.1244341, 2014. a, b
Dutton, A., Carlson, A. E., Long, A. J., Milne, G. A., Clark, P. U., Deconto,
R. M., Horton, B. P., Rahmstorf, S., and Raymo, M. E.: Sea-level rise due to
polar ice-sheet mass loss during past warm periods, Science, 349, aaa4019,
https://doi.org/10.1126/science.aaa4019, 2015. a
England, M. H.: Representing the Global-Scale Water Masses in Ocean General
Circulation Models, J. Phys. Oceanogr., 23, 1523–1552,
https://doi.org/10.1175/1520-0485(1993)023<1523:RTGSWM>2.0.CO;2, 1993. a
England, M. H., Godfrey, J. S., Hirst, A. C., and Tomczak, M.: The Mechanism
for Antarctic Intermediate Water Renewal in a World Ocean Model, J. Phys.
Oceanogr., 23, 1553–1560,
https://doi.org/10.1175/1520-0485(1993)023<1553:TMFAIW>2.0.CO;2, 1993. a
Engwirda, D., Kelley, M., and Marshall, J.: High-order accurate
finite-volume formulations for the pressure gradient force in layered ocean
models, Ocean Model., 116, 1–15, https://doi.org/10.1016/j.ocemod.2017.05.003, 2017. a
Fairall, C. W., Bradley, E. F., Rogers, D. P., Edson, J. B., and Young,
G. S.: Bulk parameterization of air-sea fluxes for Tropical Ocean-Global
Atmosphere Coupled-Ocean Atmosphere Response Experiment, J. Geophys.
Res.-Oceans, 101, 3747–3764, https://doi.org/10.1029/95JC03205, 1996. a
Fetterrer, F., Knowles, K., Meier, W., and Savoie, M.: Sea Ice Index,
Version 2, National Snow & Ice Data Center, https://doi.org/10.7265/N5736NV7, 2016. a, b
Flather, R.: A tidal model of the northwest European continental shelf,
Memoires de la Societe Royale de Sciences de Liege, 6, 141–164, 1976. a
Foldvik, A., Middleton, J. H., and Foster, T. D.: The tides of the southern
Weddell Sea, Deep-Sea Res. Pt. I, 37, 1345–1362,
https://doi.org/10.1016/0198-0149(90)90047-Y, 1990. a
Foldvik, A., Gammelsrød, T., Østerhus, S., Fahrbach, E., Rohart, G.,
Schröder, M., Nicholls, K. W., Padman, L., and Woodgate, R. A.: Ice
shelf water overflow and bottom water formation in the southern Weddell Sea,
J. Geophys. Res., 109, C02015, https://doi.org/10.1029/2003JC002008, 2004. a
Fraser, A. D., Massom, R. A., Michael, K. J., Galton-Fenzi, B. K., and
Lieser, J. L.: East Antarctic Landfast Sea Ice Distribution and Variability,
2000-08, J. Climate, 25, 1137–1156, https://doi.org/10.1175/JCLI-D-10-05032.1, 2012. a
Fretwell, P., Pritchard, H. D., Vaughan, D. G., Bamber, J. L., Barrand, N.
E., Bell, R., Bianchi, C., Bingham, R. G., Blankenship, D. D., Casassa, G.,
Catania, G., Callens, D., Conway, H., Cook, A. J., Corr, H. F. J., Damaske,
D., Damm, V., Ferraccioli, F., Forsberg, R., Fujita, S., Gim, Y., Gogineni,
P., Griggs, J. A., Hindmarsh, R. C. A., Holmlund, P., Holt, J. W., Jacobel,
R. W., Jenkins, A., Jokat, W., Jordan, T., King, E. C., Kohler, J., Krabill,
W., Riger-Kusk, M., Langley, K. A., Leitchenkov, G., Leuschen, C., Luyendyk,
B. P., Matsuoka, K., Mouginot, J., Nitsche, F. O., Nogi, Y., Nost, O. A.,
Popov, S. V., Rignot, E., Rippin, D. M., Rivera, A., Roberts, J., Ross, N.,
Siegert, M. J., Smith, A. M., Steinhage, D., Studinger, M., Sun, B., Tinto,
B. K., Welch, B. C., Wilson, D., Young, D. A., Xiangbin, C., and Zirizzotti,
A.: Bedmap2: improved ice bed, surface and thickness datasets for Antarctica,
The Cryosphere, 7, 375–393, https://doi.org/10.5194/tc-7-375-2013, 2013. a
Gade, H. G.: Melting of Ice in Sea Water: A Primitive Model with Application
to the Antarctic Ice Shelf and Icebergs, J. Phys. Oceanogr., 9, 189–198,
https://doi.org/10.1175/1520-0485(1979)009<0189:MOIISW>2.0.CO;2, 1979. a
Galton-Fenzi, B. K.: Modelling Ice-Shelf/Ocean Interaction, PhD thesis,
University of Tasmania, 2009. a
Galton-Fenzi, B. K., Maraldi, C., Coleman, R., and Hunter, J. R.: The cavity
under the Amery Ice Shelf, East Antarctica, J. Glaciol., 54, 881–887,
https://doi.org/10.3189/002214308787779898, 2008. a
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
Gent, P. R., Willebrand, J., McDougall, T. J., and McWilliams, J. C.:
Parameterizing Eddy-Induced Tracer Transports in Ocean Circulation Models,
J. Phys. Oceanogr., 25, 463–474,
https://doi.org/10.1175/1520-0485(1995)025<0463:PEITTI>2.0.CO;2, 1995. a
Gladstone, R. M., Jong, L., Galton-Fenzi, B. K., Gwyther, D. E., and Moore,
J. C.: Simulating the interactions between marine ice sheets and their
surrounding oceans, in: Forum for Research into Ice Shelf Processes, Bergen,
Norway, 2017. a
Golledge, N. R., Kowalewski, D. E., Naish, T. R., Levy, R. H., Fogwill,
C. J., and Gasson, E. G. W.: The multi-millennial Antarctic commitment to
future sea-level rise, Nature, 526, 421–425, https://doi.org/10.1038/nature15706,
2015. a
Golledge, N. R., Levy, R. H., McKay, R. M., and Naish, T. R.: East Antarctic
ice sheet most vulnerable to Weddell Sea warming, Geophys. Res. Lett., 44,
1–9, https://doi.org/10.1002/2016GL072422, 2017. a
Goosse, H. and Fichefet, T.: Open-ocean convection and polynya formation in
a large-scale ice-ocean model, Tellus A, 53, 94–111,
https://doi.org/10.1034/j.1600-0870.2001.01061.x, 2001. a
Gordon, A. L., Huber, B. A., and Busecke, J.: Bottom water export from the
western Ross Sea, 2007 through 2010, Geophys. Res. Lett., 42, 5387–5394,
https://doi.org/10.1002/2015GL064457, 2015. a
Graham, J. A., Dinniman, M. S., and Klinck, J. M.: Impact of model
resolution for on-shelf heat transport along the West Antarctic Peninsula,
J. Geophys. Res.-Oceans, 121, 7880–7897, https://doi.org/10.1002/2016JC011875, 2016. a
Greenbaum, J. S., Blankenship, D. D., Young, D. A., Richter, T. G., Roberts,
J. L., Aitken, A. R. A., Legrésy, B., Schroeder, D. M., Warner, R. C.,
van Ommen, T. D., and Siegert, M. J.: Ocean access to a cavity beneath
Totten Glacier in East Antarctica, Nat. Geosci., 8, 294–298,
https://doi.org/10.1038/NGEO2388, 2015. a, b
Griffies, S. M., Böning, C., Bryan, F. O., Chassignet, E. P., Gerdes,
R., Hasumi, H., Hirst, A. C., Treguier, A.-M., and Webb, D.: Developments in
ocean climate modelling, J. Comput. Phys., 2, 123–192,
https://doi.org/10.1016/S1463-5003(00)00014-7, 2000. a
Griffies, S. M., Biastoch, A., Böning, C., Bryan, F. O., Danabasoglu,
G., Chassignet, E. P., England, M. H., Gerdes, R., Haak, H., Hallberg, R. W.,
Hazeleger, W., Jungclaus, J. H., Large, W. G., Madec, G., Pirani, A.,
Samuels, B. L., Scheinert, M., Gupta, A. S., Severijns, C. A., Simmons,
H. L., Treguier, A.-M., Winton, M., Yeager, S. G., and Yin, J.: Coordinated
Ocean-ice Reference Experiments (COREs), Ocean Model., 26, 1–46,
https://doi.org/10.1016/j.ocemod.2008.08.007, 2009. a
Gwyther, D. E.: Modelling regional ice shelf/ocean interaction with ROMS,
in: ROMS Asia-Pacific Workshop, Hobart, Australia, 2016. a
Gwyther, D. E., Galton-Fenzi, B. K., Dinniman, M. S., Roberts, J. L., and
Hunter, J. R.: The effect of basal friction on melting and freezing in ice
shelf-ocean models, Ocean Model., 95, 38–52,
https://doi.org/10.1016/j.ocemod.2015.09.004, 2015. a
Gwyther, D. E., Cougnon, E. A., Galton-Fenzi, B. K., Roberts, J. L., Hunter,
J. R., and Dinniman, M. S.: Modelling the response of ice shelf basal
melting to different ocean cavity environmental regimes, Ann. Glaciol., 57,
131–141, https://doi.org/10.1017/aog.2016.31, 2016. a, b
Haas, C., Nicolaus, M., Willmes, S., Worby, A., and Flinspach, D.: Sea ice
and snow thickness and physical properties of an ice floe in the western
Weddell Sea and their changes during spring warming, Deep-Sea Res. Pt. II,
55, 963–974, https://doi.org/10.1016/j.dsr2.2007.12.020, 2008. a
Haidvogel, D. B. and Beckmann, A.: Numerical Ocean Circulation Modeling,
Imperial College Press, London, 1999. a
Haney, R. L.: On the Pressure Gradient Force over Steep Topography in Sigma
Coordinate Ocean Models, J. Phys. Oceanogr., 21, 610–619,
https://doi.org/10.1175/1520-0485(1991)021<0610:OTPGFO>2.0.CO;2, 1991. a, b, c
Hattermann, T., Nøst, O. A., Lilly, J. M., and Smedsrud, L. H.: Two years
of oceanic observations below the Fimbul Ice Shelf, Antarctica, Geophys.
Res. Lett., 39, L12605, https://doi.org/10.1029/2012GL051012, 2012. a, b
Hellmer, H. H. and Olbers, D. J.: 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., Jacobs, S. S., and Jenkins, A.: Oceanic erosion of a
floating Antarctic glacier in the Amundsen Sea, in: Ocean, Ice, and
Atmosphere: Interactions at the Antarctic Continental Margin, edited by:
Jacobs, S. S. and Weiss, R. F., American Geophysical Union, Washington, DC,
319–339, https://doi.org/10.1029/AR075p0341, 1998. 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, 225–228,
https://doi.org/10.1038/nature11064, 2012. a
Hellmer, H. H., Kauker, F., Timmermann, R., and Hattermann, T.: The fate of
the southern Weddell Sea continental shelf in a warming climate, J. Climate,
30, 4337–4350, https://doi.org/10.1175/JCLI-D-16-0420.1, 2017. a
Herraiz-Borreguero, L., Church, J. A., Allison, I., Pena-Molino, B., Coleman,
R., Tomczak, M., and Craven, M.: Basal melt, seasonal water mass
transformation, ocean current variability, and deep convection processes
along the Amery Ice Shelf, J. Geophys. Res.-Oceans, 121, 4946–4965,
https://doi.org/10.1002/2013JC008846, 2016. a
Heuzé, C., Ridley, J. K., Calvert, D., Stevens, D. P., and Heywood, K.
J.: Increasing vertical mixing to reduce Southern Ocean deep convection in
NEMO3.4, Geosci. Model Dev., 8, 3119–3130,
https://doi.org/10.5194/gmd-8-3119-2015, 2015. a
Hogg, A. E. and Gudmundsson, G. H.: Impacts of the Larsen-C Ice Shelf
calving event, Nat. Clim. Change, 7, 540–542, https://doi.org/10.1038/nclimate3359,
2017. a
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
Holland, P. R., Corr, H. F. J., Vaughan, D. G., Jenkins, A., and Skvarca, P.:
Marine ice in Larsen Ice Shelf, Geophys. Res. Lett., 36, 1–6,
https://doi.org/10.1029/2009GL038162, 2009. a, b
Holland, P. R., Bruneau, N., Enright, C., Losch, M., Kurtz, N. T., and Kwok,
R.: Modeled trends in Antarctic Sea Ice Thickness, J. Climate, 27,
3784–3801, https://doi.org/10.1175/JCLI-D-13-00301.1, 2014. a, b
Hunke, E. C., Hebert, D. A., and Lecomte, O.: Level-ice melt ponds in the
Los Alamos sea ice model, CICE, Ocean Model., 71, 26–42,
https://doi.org/10.1016/j.ocemod.2012.11.008, 2013. a
Hunter, J. R.: Specification for Test Models of Ice Shelf Cavities, Tech.
rep., Antarctic Climate & Ecosystems Cooperative Research Centre, 2006. a
Jacob, R., Larson, J., and Ong, E.: M × N Communication and
Parallel Interpolation in Community Climate System Model Version 3 Using the
Model Coupling Toolkit, Int. J. High Perform. C, 19, 293–307,
https://doi.org/10.1177/1094342005056116, 2005. a, b
Jacobs, S. S. and Comiso, J. C.: Sea ice and oceanic processes on the Ross
Sea continental shelf, J. Geophys. Res., 94, 18195–18211,
https://doi.org/10.1029/JC094iC12p18195, 1989. a
Jacobs, S. S., Gordon, A. L., and Ardai, J. L.: Circulation and melting
beneath the Ross Ice Shelf, Science, 203, 439–443,
https://doi.org/10.1126/science.203.4379.439, 1979. a
Jacobs, S. S., Hellmer, H. 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/10.1038/228047a0, 1992. a, b
Jacobs, S. S., Jenkins, A., Giulivi, C. F., and Dutrieux, P.: Stronger ocean
circulation and increased melting under Pine Island Glacier ice shelf, Nat.
Geosci., 4, 519–523, https://doi.org/10.1038/ngeo1188, 2011. a, b
Jenkins, A.: A One-Dimensional Model of Ice Shelf-Ocean Interaction, J.
Geophys. Res.-Oceans, 96, 20671–20677, https://doi.org/10.1029/91JC01842, 1991. a
Jenkins, A.: Convection-Driven Melting near the Grounding Lines of Ice
Shelves and Tidewater Glaciers, J. Phys. Oceanogr., 41, 2279–2294,
https://doi.org/10.1175/JPO-D-11-03.1, 2011. a
Jenkins, A.: A Simple Model of the Ice Shelf–Ocean Boundary Layer and
Current, J. Phys. Oceanogr., 46, 1785–1803, https://doi.org/10.1175/JPO-D-15-0194.1,
2016. a
Jenkins, A. and Jacobs, S. S.: Circulation and melting beneath George VI Ice
Shelf, Antarctica, J. Geophys. Res., 113, 1–18, https://doi.org/10.1029/2007JC004449,
2008. a, b, c
Jenkins, A., Dutrieux, P., Jacobs, S. S., McPhail, S. D., Perrett, J. R.,
Webb, A. T., and White, D.: Observations beneath Pine Island Glacier in West
Antarctica and implications for its retreat, Nat. Geosci., 3, 468–472,
https://doi.org/10.1038/ngeo890, 2010. a, b
Joughin, I. and Alley, R. B.: Stability of the West Antarctic ice sheet in a
warming world, Nat. Geosci., 4, 506–513, https://doi.org/10.1038/ngeo1194, 2011. a
Joughin, I. and Padman, L.: Melting and freezing beneath Filchner-Ronne Ice
Shelf, Antarctica, Geophys. Res. Lett., 30, 1477,
https://doi.org/10.1029/2003GL016941, 2003. a, b, c, d
Khazendar, A., Schodlok, M. P., Fenty, I. G., Ligtenberg, S. R. M., Rignot,
E. J., and van den Broeke, M. R.: Observed thinning of Totten Glacier is
linked to coastal polynya variability, Nat. Commun., 4, 2857,
https://doi.org/10.1038/ncomms3857, 2013. a
Kjellsson, J., Holland, P. R., Marshall, G. J., Mathiot, P., Aksenov, Y.,
Coward, A. C., Bacon, S., Megann, A. P., and Ridley, J. K.: Model
sensitivity of the Weddell and Ross seas, Antarctica, to vertical mixing and
freshwater forcing, Ocean Model., 94, 141–152,
https://doi.org/10.1016/j.ocemod.2015.08.003, 2015. a, b, c
Koltermann, K. P., Gouretski, V. V., and Jancke, K.: Hydrographic Atlas of
the World Ocean Circulation Experiment (WOCE), vol. 3, in: Atlantic Ocean
edited by: Sparrow, M., Chapman, P., and Gould, J., Tech. rep., International
WOCE Project Office, Southampton, UK, 2011. a
Kurtz, N. T. and Markus, T.: Satellite observations of Antarctic sea ice
thickness and volume, J. Geophys. Res.-Oceans, 117, 1–9,
https://doi.org/10.1029/2012JC008141, 2012. a
Kusahara, K., Hasumi, H., and Tamura, T.: Modeling sea ice production and
dense shelf water formation in coastal polynyas around East Antarctica, J.
Geophys. Res.-Oceans, 115, C10006, https://doi.org/10.1029/2010JC006133, 2010. a
Kusahara, K., Williams, G. D., Massom, R., Reid, P., and Hasumi, H.: Roles
of wind stress and thermodynamic forcing in recent trends in Antarctic sea
ice and Southern Ocean SST: An ocean-sea ice model study, Global Planet.
Change, 158, 103–118, https://doi.org/10.1016/j.gloplacha.2017.09.012, 2017. a
Kwok, R. and Cunningham, G. F.: ICESat over Arctic sea ice: Estimation of
snow depth and ice thickness, J. Geophys. Res.-Oceans, 113, 1–17,
https://doi.org/10.1029/2008JC004753, 2008. a
Langhorne, P. J., Hughes, K. G., Gough, A. J., Smith, I. J., Williams, M.
J. M., Robinson, N. J., Stevens, C. L., Rack, W., Price, D., Leonard, G. H.,
Mahoney, A. R., Haas, C., and Haskell, T. G.: Observed platelet ice
distributions in Antarctic sea ice: An index for ocean-ice shelf heat flux,
Geophys. Res. Lett., 42, 5442–5451, https://doi.org/10.1002/2015GL064508, 2015. a
Langley, K. A., Kohler, J., Sinisalo, A., Øyan, M. J., Hamran, S. E.,
Hattermann, T., Matsuoka, K., Nøst, O. A., and Isaksson, E.: Low melt
rates with seasonal variability at the base of Fimbul Ice Shelf, East
Antarctica, revealed by in situ interferometric radar measurements, Geophys.
Res. Lett., 41, 8138–8146, https://doi.org/10.1002/2014GL061782, 2014. a
Large, W. G., McWilliams, J. C., and Doney, S. C.: Oceanic Vertical Mixing
– a Review and a Model with a Nonlocal Boundary-Layer Parameterization,
Rev. Geophys., 32, 363–403, https://doi.org/10.1029/94rg01872, 1994. a
Larson, J., Jacob, R., and Ong, E.: The Model Coupling Toolkit: A New
Fortran90 Toolkit for Building Multiphysics Parallel Coupled Models, Int. J.
High Perform. C., 19, 277–292, https://doi.org/10.1177/1094342005056115, 2005. a, b
Lemarié, F., Kurian, J., Shchepetkin, A. F., Jeroen Molemaker, M.,
Colas, F., and McWilliams, J. C.: Are there inescapable issues prohibiting
the use of terrain-following coordinates in climate models?, Ocean Model.,
42, 57–79, https://doi.org/10.1016/j.ocemod.2011.11.007, 2012. a, b, c
Lenaerts, J. T. M., van den Broeke, M. R., van de Berg, W. J., van Meijgaard,
E., and Munneke, P. K.: A new, high-resolution surface mass balance map of
Antarctica (1979–2010) based on regional atmospheric climate modeling,
Geophys. Res. Lett., 39, 1–5, https://doi.org/10.1029/2011GL050713, 2012. a
Lewis, E. L. and Perkin, R. G.: Ice pumps and their rates, J. Geophys.
Res., 91, 11756–11762 , https://doi.org/10.1029/JC091iC10p11756, 1986. a
Lipscomb, W. H. and Hunke, E. C.: Modeling Sea Ice Transport Using
Incremental Remapping, Mon. Weather Rev., 132, 1341–1354,
https://doi.org/10.1175/1520-0493(2004)132<1341:MSITUI>2.0.CO;2, 2004. a
Lipscomb, W. H., Hunke, E. C., Maslowski, W., and Jakacki, J.: Ridging,
strength, and stability in high-resolution sea ice models, J. Geophys.
Res.-Oceans, 112, 1–18, https://doi.org/10.1029/2005JC003355, 2007. a
Makinson, K., Holland, P. R., Jenkins, A., Nicholls, K. W., and Holland,
D. M.: Influence of tides on melting and freezing beneath Filchner-Ronne Ice
Shelf, Antarctica, Geophys. Res. Lett., 38, L06601,
https://doi.org/10.1029/2010GL046462, 2011. a, b
Marchesiello, P., McWilliams, J. C., and Shchepetkin, A. F.: Open boundary
conditions for long-term integration of regional oceanic models, Ocean
Model., 3, 1–20, https://doi.org/10.1016/S1463-5003(00)00013-5, 2001. a
Marchesiello, P., Debreu, L., and Couvelard, X.: Spurious diapycnal mixing
in terrain-following coordinate models: The problem and a solution, Ocean
Model., 26, 156–169, https://doi.org/10.1016/j.ocemod.2008.09.004, 2009. a, b, c
Martin, T. and Adcroft, A.: Parameterizing the fresh-water flux from land
ice to ocean with interactive icebergs in a coupled climate model, Ocean
Model., 34, 111–124, https://doi.org/10.1016/j.ocemod.2010.05.001, 2010. a, b
Martinson, D. G. and McKee, D. C.: Transport of warm Upper Circumpolar Deep
Water onto the western Antarctic Peninsula continental shelf, Ocean Sci., 8,
433–442, https://doi.org/10.5194/os-8-433-2012, 2012. a
McPhail, S. D., Furlong, M. E., Pebody, M., Perrett, J. R., Stevenson, P.,
Webb, A., and White, D.: Exploring beneath the PIG Ice Shelf with the
Autosub3 AUV, in: OCEANS '09 IEEE Bremen: Balancing Technology with Future
Needs, Piscataway, USA, p. 6, https://doi.org/10.1109/OCEANSE.2009.5278170, 2009. a
McPhee, M. G., Maykut, G. A., and Morison, J. H.: Dynamics and
thermodynamics of the ice/upper ocean system in the marginal ice zone of the
Greenland Sea, J. Geophys. Res.-Oceans, 92, 7017–7031,
https://doi.org/10.1029/JC092iC07p07017, 1987. a
Meehl, G. A., Boer, G. J., Covey, C., Latif, M., and Stouffer, R. J.: The
Coupled Model Intercomparison Project (CMIP), B. Am. Meteorol. Soc., 81,
313–318, https://doi.org/10.1175/1520-0477(2000)081<0313:TCMIPC>2.3.CO;2, 2000. a
Meier, W., Fetterrer, F., Savoie, M., Mallory, S., Duerr, R., and Stroeve,
J.: NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice
Concentration, Version 2, https://doi.org/10.7265/N55M63M1, 2013. a, b, c
Mengel, M. and Levermann, A.: Ice plug prevents irreversible discharge from
East Antarctica, Nat. Clim. Change, 4, 451–455, https://doi.org/10.1038/nclimate2226,
2014. a
Miller, K. G., Wright, J. D., Browning, J. V., Kulpecz, A., Kominz, M.,
Naish, T. R., Cramer, B. S., Rosenthal, Y., Peltier, W. R., and Sosdian, S.:
High tide of the warm Pliocene: Implications of global sea level for
Antarctic deglaciation, Geology, 40, 407–410, https://doi.org/10.1130/G32869.1, 2012. a
Moffat, C., Owens, B., and Beardsley, R. C.: On the characteristics of
Circumpolar Deep Water intrusions to the west Antarctic Peninsula Continental
Shelf, J. Geophys. Res.-Oceans, 114, C05017, https://doi.org/10.1029/2008JC004955,
2009. a
Mueller, R. D., Padman, L., Dinniman, M. S., Erofeeva, S. Y., Fricker, H. A.,
and King, M. A.: Impact of tide-topography interactions on basal melting of
Larsen C Ice Shelf, Antarctica, J. Geophys. Res.-Oceans, 117, C05005,
https://doi.org/10.1029/2011JC007263, 2012. a
Müller, M., Haak, H., Jungclaus, J. H., Sündermann, J., and
Thomas, M.: The effect of ocean tides on a climate model simulation, Ocean
Model., 35, 304–313, https://doi.org/10.1016/j.ocemod.2010.09.001, 2010. a
Naud, C. M., Booth, J. F., and Del Genio, A. D.: Evaluation of ERA-Interim
and MERRA cloudiness in the Southern Ocean, J. Climate, 27, 2109–2124,
https://doi.org/10.1175/JCLI-D-13-00432.1, 2014. a
Naughten, K. A., Galton-Fenzi, B. K., Meissner, K. J., England, M. H.,
Brassington, G. B., Colberg, F., Hattermann, T., and Debernard, J. B.:
Spurious sea ice formation caused by oscillatory ocean tracer advection
schemes, Ocean Model., 116, 108–117, https://doi.org/10.1016/j.ocemod.2017.06.010,
2017. a, b, c, d, e
Naughten, K. A., Meissner, K. J., Galton-Fenzi, B. K., England, M. H., Timmermann, R., and Hellmer, H. H.: MetROMS-iceshelf, https://doi.org/10.5281/zenodo.1157230, 2018a.
Naughten, K. A., Meissner, K. J., Galton-Fenzi, B. K., England, M. H., Timmermann, R., and Hellmer, H. H.: Finite Element Sea-ice/ice-shelf Ocean Model (FESOM) 1.4, https://doi.org/10.5281/zenodo.1157228, 2018b.
Nicholls, K. W. and Johnson, M. R.: Oceanographic conditions south of
Berkner Island, beneath Filchner-Ronne Ice Shelf, Antarctica, J. Geophys.
Res., 106, 11481–11492, https://doi.org/10.1029/2000JC000350, 2001. a, b
Nicholls, K. W. and Østerhus, S.: Interannual variability and ventilation
timescales in the ocean cavity beneath Filchner-Ronne Ice Shelf, Antarctica,
J. Geophys. Res.-Oceans, 109, 1–9, https://doi.org/10.1029/2003JC002149, 2004. a
Nicholls, K. W., Makinson, K., and Østerhus, S.: Circulation and water
masses beneath the northern Ronne Ice Shelf, Antarctica, J. Geophys.
Res.-Oceans, 109, 1–11, https://doi.org/10.1029/2004JC002302, 2004. a
Nicholls, K. W., Abrahamsen, E. P., Buck, J. J. H., Dodd, P. A., Goldblatt,
C., Griffiths, G., Heywood, K. J., Hughes, N. E., Kaletzky, A., Lane-Serff,
G. F., McPhail, S. D., Millard, N. W., Oliver, K. I. C., Perrett, J., Price,
M. R., Pudsey, C. J., Saw, K., Stansfield, K., Stott, M. J., Wadhams, P.,
Webb, A. T., and Wilkinson, J. P.: Measurements beneath an Antarctic ice
shelf using an autonomous underwater vehicle, Geophys. Res. Lett., 33, 2–5,
https://doi.org/10.1029/2006GL025998, 2006. 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
O'Leary, M. J., Hearty, P. J., Thompson, W. G., Raymo, M. E., Mitrovica,
J. X., Webster, J. M., and O'Leary, M. J.: Ice sheet collapse following a
prolonged period of stable sea level during the last interglacial, Nat.
Geosci., 6, 796–800, https://doi.org/10.1038/ngeo1890, 2013. a
Pacanowski, R. C. and Philander, S. G. H.: Parameterization of Vertical
Mixing in Numerical Models of Tropical Oceans, J. Phys. Oceanogr., 11,
1443–1451, https://doi.org/10.1175/1520-0485(1981)011<1443:POVMIN>2.0.CO;2, 1981. a
Padman, L., Howard, S. L., Orsi, A. H., and Muench, R. D.: Tides of the
northwestern Ross Sea and their impact on dense outflows of Antarctic Bottom
Water, Deep-Sea Res. Pt. II, 56, 818–834, https://doi.org/10.1016/j.dsr2.2008.10.026,
2009. a
Paolo, F. S., Fricker, H. A., and Padman, L.: Volume loss from Antarctic ice
shelves is accelerating, Science, 348, 327–331,
https://doi.org/10.1126/science.aaa0940, 2015. a
Parkinson, C. L. and Washington, W. M.: A large-scale numerical model of sea
ice, J. Geophys. Res., 84, 311–337, https://doi.org/10.1029/JC084iC01p00311, 1979. a
Pellichero, V., Sallée, J.-B., Schmidtko, S., Roquet, F., and
Charrassin, J.-B.: The ocean mixed layer under Southern Ocean sea-ice:
Seasonal cycle and forcing, J. Geophys. Res.-Oceans, 122, 1608–1633,
https://doi.org/10.1002/2016JC011970, 2017. a, b
Petty, A. A., Feltham, D. L., and Holland, P. R.: Impact of Atmospheric
Forcing on Antarctic Continental Shelf Water Masses, J. Phys. Oceanogr., 43,
920–940, https://doi.org/10.1175/JPO-D-12-0172.1, 2013. a, b
Pritchard, H. D., Ligtenberg, S. R. M., Fricker, H. A., Vaughan, D. G.,
van den Broeke, M. R., and Padman, L.: Antarctic ice-sheet loss driven by
basal melting of ice shelves, Nature, 484, 502–505,
https://doi.org/10.1038/nature10968, 2012. a
Rack, W. and Rott, H.: Pattern of retreat and disintegration of the Larsen B
Ice Shelf, Ann. Glaciol., 39, 505–510, https://doi.org/10.3189/172756404781814005,
2004. a
Raymo, M. E. and Mitrovica, J. X.: Collapse of polar ice sheets during the
stage 11 interglacial, Nature, 483, 453–456, https://doi.org/10.1038/nature10891,
2012. a
Reddy, T. E., Holland, D. M., and Arrigo, K. R.: Ross ice shelf cavity
circulation, residence time, and melting: Results from a model of oceanic
chlorofluorocarbons, Cont. Shelf Res., 30, 733–742,
https://doi.org/10.1016/j.csr.2010.01.007, 2010. a, b
Rignot, E. J., Velicogna, I., van den Broeke, M. R., Monaghan, A., and
Lenaerts, J. T. M.: Acceleration of the contribution of the Greenland and
Antarctic ice sheets to sea level rise, Geophys. Res. Lett., 38, 1–5,
https://doi.org/10.1029/2011GL046583, 2011. a
Rignot, E. J., Mouginot, J., Morlighem, M., Seroussi, H., and Scheuchl, B.:
Widespread, rapid grounding line retreat of Pine Island, Thwaites, Smith,
and Kohler glaciers, West Antarctica, from 1992 to 2011, Geophys. Res.
Lett., 41, 3502–3509, https://doi.org/10.1002/2014GL060140, 2014. a, b
Rintoul, S. R., Speer, K., Sparrow, M., Meredith, M., Hofmann, E., Fahrbach,
E., Summerhayes, C., Worby, A., England, M., Bellerby, R. G., Speich, S.,
Costa, D., Hall, J., Hindell, M., Hosie, G., Stansfield, K., Fukamachi, Y.,
de Bruin, T., Naveira Garabato, A., Alverson, K., Ryabinin, V., Shin,
H. C., and Gladyshev, S.: Southern Ocean Observing System (SOOS): Rationale
and strategy for sustained observations of the Southern Ocean, in:
Proceedings of OceanObs'09: Sustained Ocean Observations and Information for
Society, edited by: Hall, J., Harrison, D. E., and Stammer, D., vol. 2, ESA
Publication WPP-306, Venice, https://doi.org/10.5270/OceanObs09.cwp.74, 2010. a
Rintoul, S. R., Silvano, A., Pena-Molino, B., van Wijk, E., Rosenberg, M.,
Greenbaum, J. S., and Blankenship, D. D.: Ocean heat drives rapid basal melt
of the Totten Ice Shelf, Sci. Adv., 2, 1–6, https://doi.org/10.1126/sciadv.1601610,
2016. a
Robertson, R., Padman, L., and Egbert, G. D.: Tides in the Weddell Sea, in:
Ocean, Ice, and Atmosphere: Interactions at the Antarctic Continental Margin,
edited by: Jacobs, S. S. and Weiss, R. F., American Geophysical Union,
Washington, DC, 341–369, https://doi.org/10.1029/AR075p0341, 1998. a
Rothrock, D. A.: The Energetics of the Plastic Deformation of Pack Ice by
Ridging, J. Geophys. Res., 80, 4514–4519, 1975. a
Rott, H., Skvarca, P., and Nagler, T.: Rapid Collapse of Northern Larsen Ice
Shelf, Antarctica, Science, 271, 788–792,
https://doi.org/10.1126/science.271.5250.788, 1996. a
Sallée, J.-B., Shuckburgh, E., Bruneau, N., Meijers, A. J. S.,
Bracegirdle, T. J., and Wang, Z.: Assessment of Southern Ocean mixed-layer
depths in CMIP5 models: Historical bias and forcing response, J. Geophys.
Res.-Oceans, 118, 1845–1862, https://doi.org/10.1002/jgrc.20157, 2013. a, b
Schmidtko, S., Heywood, K. J., Thompson, A. F., and Aoki, S.: Multidecadal
warming of Antarctic waters, Science, 346, 1227–1232,
https://doi.org/10.1126/science.1256117, 2014. a, b
Semtner, A. J.: A Model for the Thermodynamic Growth of Sea Ice in Numerical
Investigations of Climate, J. Phys. Oceanogr., 6, 379–389,
https://doi.org/10.1175/1520-0485(1976)006<0379:AMFTTG>2.0.CO;2, 1976. a
Shchepetkin, A. F.: A method for computing horizontal pressure-gradient
force in an oceanic model with a nonaligned vertical coordinate, J. Geophys.
Res., 108, 3090, https://doi.org/10.1029/2001JC001047, 2003. a
Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling
system (ROMS): A split-explicit, free-surface,
topography-following-coordinate oceanic model, Ocean Model., 9, 347–404,
https://doi.org/10.1016/j.ocemod.2004.08.002, 2005. a, b, c
Shepherd, A. P., Ivins, E. R., Geruo, A., Barletta, V. R., Bentley, M. J.,
Bettadpur, S., Briggs, K. H., Bromwich, D. H., Forsberg, R., Galin, N.,
Horwath, M., Jacobs, S. S., Joughin, I., King, M. A., Lenaerts, J. T. M., Li,
J., Ligtenberg, S. R. M., Luckman, A., Luthcke, S. B., McMillan, M., Meister,
R., Milne, G. A., Mouginot, J., Muir, A., Nicolas, J. P., Paden, J., Payne,
A. J., Pritchard, H. D., Rignot, E. J., Rott, H., Sandberg Sørensen, L.,
Scambos, T. A., Scheuchl, B., Schrama, E. J. O., Smith, B., Sundal, A. V.,
van Angelen, J. H., van de Berg, W. J., van den Broeke, M. R., Vaughan,
D. G., Velicogna, I., Wahr, J., Whitehouse, P. L., Wingham, D. J., Yi, D.,
Young, D. A., and Zwally, H. J.: A Reconciled Estimate of Ice-Sheet Mass
Balance, Science, 338, 1183–1189, https://doi.org/10.1126/science.1228102, 2012. a
Silvano, A., Rintoul, S. R., Pena-Molino, B., and Williams, G. D.:
Distribution of water masses and meltwater on the continental shelf near the
Totten and Moscow University ice shelves, J. Geophys. Res.-Oceans, 122,
2050–2068, https://doi.org/10.1002/2016JC012115, 2017. a
Smagorinsky, J.: General Circulation Experiments With the Primitive
Equations I. The Basic Experiment, Mon. Weather Rev., 91, 99–164,
https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2, 1963. a
Smagorinsky, J.: Some historical remarks on the use of non-linear
viscosities, in: Large Eddy Simulation of Complex Engineering and
Geophysical Flows, edited by: Galperin, B. and Orszag, S., Cambridge
University Press, Cambridge, 3–36, 1993. a
Smedsrud, L. H. and Jenkins, A.: Frazil ice formation in an ice shelf water
plume, J. Geophys. Res., 109, C03025, https://doi.org/10.1029/2003JC001851, 2004. a, b
Spence, P., Griffies, S. M., England, M. H., Hogg, A. M., Saenko, O. A., and
Jourdain, N. C.: Rapid subsurface warming and circulation changes of
Antarctic coastal waters by poleward shifting winds, Geophys. Res. Lett.,
41, 4601–4610, https://doi.org/10.1002/2014GL060613, 2014. a
Spence, P., Holmes, R. M., Hogg, A. M., Griffies, S. M., Stewart, K. D., and
England, M. H.: Localized rapid warming of West Antarctic subsurface waters
by remote winds, Nat. Clim. Change, 7, 595–603, https://doi.org/10.1038/nclimate3335,
2017. a
St-Laurent, P., Klinck, J. M., and Dinniman, M. S.: On the Role of Coastal
Troughs in the Circulation of Warm Circumpolar Deep Water on Antarctic
Shelves, J. Phys. Oceanogr., 43, 51–64, https://doi.org/10.1175/JPO-D-11-0237.1,
2013. a, b
Stewart, A. L. and Thompson, A. F.: Eddy-mediated transport of warm
Circumpolar Deep Water across the Antarctic Shelf Break, Geophys. Res.
Lett., 42, 432–440, https://doi.org/10.1002/2014GL062281, 2015. a
Talley, L. D.: Hydrographic Atlas of the World Ocean Circulation Experiment
(WOCE), Vol. 2, in: Pacific Ocean, edited by: Sparrow, M., Chapman, P., and
Gould, J., Tech. rep., International WOCE Project Office, Southampton, UK,
2007. a
Tamura, T. and Ohshima, K. I.: Mapping of sea ice production for Antarctic
coastal polynyas, J. Geophys. Res.-Oceans, 116, 1–5,
https://doi.org/10.1029/2010JC006586, 2008. a
Thomas, M., Sündermann, J., and Maier-Reimer, E.: Consideration of
ocean tides in an OGCM and impacts on subseasonal to decadal polar motion
excitation, Geophys. Res. Lett., 28, 2457–2460, https://doi.org/10.1029/2000GL012234,
2001. a
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
Timmermann, R., Danilov, S., Schröter, J., Böning, C., Sidorenko,
D., and Rollenhagen, K.: Ocean circulation and sea ice distribution in a
finite element global sea ice-ocean model, Ocean Model., 27, 114–129,
https://doi.org/10.1016/j.ocemod.2008.10.009, 2009. a, b, c
Timmermann, R., Le Brocq, A., Deen, T., Domack, E., Dutrieux, P.,
Galton-Fenzi, B., Hellmer, H., Humbert, A., Jansen, D., Jenkins, A.,
Lambrecht, A., Makinson, K., Niederjasper, F., Nitsche, F., Nøst, O. A.,
Smedsrud, L. H., and Smith, W. H. F.: A consistent data set of Antarctic ice
sheet topography, cavity geometry, and global bathymetry, Earth Syst. Sci.
Data, 2, 261–273, https://doi.org/10.5194/essd-2-261-2010, 2010. a
Trenberth, K. E. and Fasullo, J. T.: Simulation of present-day and
twenty-first-century energy budgets of the southern oceans, J. Climate, 23,
440–454, https://doi.org/10.1175/2009JCLI3152.1, 2010. a
Tsamados, M., Feltham, D. L., and Wilchinsky, A. V.: Impact of a new
anisotropic rheology on simulations of Arctic Sea ice, J. Geophys.
Res.-Oceans, 118, 91–107, https://doi.org/10.1029/2012JC007990, 2013. 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, 2013a. a
Turner, J., Bracegirdle, T. J., Phillips, T., Marshall, G. J., and Hosking,
J. S.: An initial assessment of Antarctic sea ice extent in the CMIP5
models, J. Climate, 26, 1473–1484, https://doi.org/10.1175/JCLI-D-12-00068.1,
2013b.
a, b
Venables, H. J. and Meredith, M. P.: Feedbacks between ice cover, ocean
stratification, and heat content in Ryder Bay, western Antarctic Peninsula,
J. Geophys. Res.-Oceans, 119, 5323–5336, https://doi.org/10.1002/2013JC009669, 2014. a
Wåhlin, A. K., Yuan, X., Björk, G., and Nohr, C.: Inflow of Warm
Circumpolar Deep Water in the Central Amundsen Shelf, J. Phys. Oceanogr.,
40, 1427–1434, https://doi.org/10.1175/2010JPO4431.1, 2010. a
Wang, Q., Danilov, S., and Schröter, J.: Finite element ocean
circulation model based on triangular prismatic elements, with application in
studying the effect of topography representation, J. Geophys. Res., 113,
C05015, https://doi.org/10.1029/2007JC004482, 2008. a, b
Wang, Q., Danilov, S., Hellmer, H. H., Sidorenko, D., Schröter, J., and
Jung, T.: Enhanced cross-shelf exchange by tides in the western Ross Sea,
Geophys. Res. Lett., 40, 5735–5739, https://doi.org/10.1002/2013GL058207, 2013. a
Wang, Q., Danilov, S., Sidorenko, D., Timmermann, R., Wekerle, C., Wang, X.,
Jung, T., and Schröter, J.: The Finite Element Sea Ice-Ocean Model
(FESOM) v.1.4: formulation of an ocean general circulation model, Geosci.
Model Dev., 7, 663–693, https://doi.org/10.5194/gmd-7-663-2014, 2014. a, b, c, d, e
Wen, J., Wang, Y., Wang, W., Jezek, K. C., Liu, H., and Allison, I.: Basal
melting and freezing under the Amery Ice Shelf, East Antarctica, J.
Glaciol., 56, 81–90, https://doi.org/10.3189/002214310791190820, 2010. a
Williams, K. D., Bodas-Salcedo, A., Déqué, M., Fermepin, S.,
Medeiros, B., Watanabe, M., Jakob, C., Klein, S. A., Senior, C. A., and
Williamson, D. L.: The transpose-AMIP II experiment and its application to
the understanding of southern ocean cloud biases in climate models, J.
Climate, 26, 3258–3274, https://doi.org/10.1175/JCLI-D-12-00429.1, 2013. a
Worby, A. P., Geiger, C. A., Paget, M. J., van Woert, M. L., Ackley, S. F.,
and DeLiberty, T. L.: Thickness distribution of Antarctic sea ice, J.
Geophys. Res.-Oceans, 113, 1–14, https://doi.org/10.1029/2007JC004254, 2008. a
Wunsch, C., Heimbach, P., Ponte, R., and Fukumori, I.: The Global General
Circulation of the Ocean Estimated by the ECCO-Consortium, Oceanography, 22,
88–103, https://doi.org/10.5670/oceanog.2009.41, 2009. a, b, c
Zwally, H. J. and Giovinetto, M. B.: Overview and Assessment of Antarctic
Ice-Sheet Mass Balance Estimates: 1992-2009, Surv. Geophys., 32, 351–376,
https://doi.org/10.1007/s10712-011-9123-5, 2011. a
Zweng, M. M., Reagan, J. R., Antonov, J. I., Mishonov, A. V., Boyer, T. P.,
Garcia, H. E., Baranova, O. K., Johnson, D. R., Seidov, D., and Bidlle,
M. M.: World Ocean Atlas 2013, vol. 2, Salinity, NOAA Atlas NESDIS, 2,
39 pp., 2013. a
Short summary
MetROMS and FESOM are two ocean/sea-ice models which resolve Antarctic ice-shelf cavities and consider thermodynamics at the ice-shelf base. We simulate the period 1992–2016 with both models, and with two options for resolution in FESOM, and compare output from the three simulations. Ice-shelf melt rates, sub-ice-shelf circulation, continental shelf water masses, and sea-ice processes are compared and evaluated against available observations.
MetROMS and FESOM are two ocean/sea-ice models which resolve Antarctic ice-shelf cavities and...
