Articles | Volume 18, issue 8
https://doi.org/10.5194/tc-18-3825-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-18-3825-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Aug 2024
Research article |
| 26 Aug 2024
| 26 Aug 2024
The role of atmospheric conditions in the Antarctic sea ice extent summer minima
Bianca Mezzina
CORRESPONDING AUTHOR
Earth and Climate Research Center, Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
Hugues Goosse
Earth and Climate Research Center, Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
François Klein
Earth and Climate Research Center, Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
Antoine Barthélemy
Earth and Climate Research Center, Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
François Massonnet
Earth and Climate Research Center, Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
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Elizabeth R. Thomas, Diana O. Vladimirova, Dieter R. Tetzner, B. Daniel Emanuelsson, Nathan Chellman, Daniel A. Dixon, Hugues Goosse, Mackenzie M. Grieman, Amy C. F. King, Michael Sigl, Danielle G. Udy, Tessa R. Vance, Dominic A. Winski, V. Holly L. Winton, Nancy A. N. Bertler, Akira Hori, Chavarukonam M. Laluraj, Joseph R. McConnell, Yuko Motizuki, Kazuya Takahashi, Hideaki Motoyama, Yoichi Nakai, Franciéle Schwanck, Jefferson Cardia Simões, Filipe Gaudie Ley Lindau, Mirko Severi, Rita Traversi, Sarah Wauthy, Cunde Xiao, Jiao Yang, Ellen Mosely-Thompson, Tamara V. Khodzher, Ludmila P. Golobokova, and Alexey A. Ekaykin
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Nicolas Ghilain, Stéphane Vannitsem, Quentin Dalaiden, Hugues Goosse, Lesley De Cruz, and Wenguang Wei
Earth Syst. Sci. Data, 14, 1901–1916, https://doi.org/10.5194/essd-14-1901-2022, https://doi.org/10.5194/essd-14-1901-2022, 2022
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Modeling the climate at high resolution is crucial to represent the snowfall accumulation over the complex orography of the Antarctic coast. While ice cores provide a view constrained spatially but over centuries, climate models can give insight into its spatial distribution, either at high resolution over a short period or vice versa. We downscaled snowfall accumulation from climate model historical simulations (1850–present day) over Dronning Maud Land at 5.5 km using a statistical method.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
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The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Koffi Worou, Hugues Goosse, Thierry Fichefet, and Fred Kucharski
Earth Syst. Dynam., 13, 231–249, https://doi.org/10.5194/esd-13-231-2022, https://doi.org/10.5194/esd-13-231-2022, 2022
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Over the Guinea Coast, the increased rainfall associated with warm phases of the Atlantic Niño is reasonably well simulated by 24 climate models out of 31, for the present-day conditions. In a warmer climate, general circulation models project a gradual decrease with time of the rainfall magnitude associated with the Atlantic Niño for the 2015–2039, 2040–2069 and 2070–2099 periods. There is a higher confidence in these changes over the equatorial Atlantic than over the Guinea Coast.
Charles Pelletier, Thierry Fichefet, Hugues Goosse, Konstanze Haubner, Samuel Helsen, Pierre-Vincent Huot, Christoph Kittel, François Klein, Sébastien Le clec'h, Nicole P. M. van Lipzig, Sylvain Marchi, François Massonnet, Pierre Mathiot, Ehsan Moravveji, Eduardo Moreno-Chamarro, Pablo Ortega, Frank Pattyn, Niels Souverijns, Guillian Van Achter, Sam Vanden Broucke, Alexander Vanhulle, Deborah Verfaillie, and Lars Zipf
Geosci. Model Dev., 15, 553–594, https://doi.org/10.5194/gmd-15-553-2022, https://doi.org/10.5194/gmd-15-553-2022, 2022
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We present PARASO, a circumpolar model for simulating the Antarctic climate. PARASO features five distinct models, each covering different Earth system subcomponents (ice sheet, atmosphere, land, sea ice, ocean). In this technical article, we describe how this tool has been developed, with a focus on the
coupling interfacesrepresenting the feedbacks between the distinct models used for contribution. PARASO is stable and ready to use but is still characterized by significant biases.
Xia Lin, François Massonnet, Thierry Fichefet, and Martin Vancoppenolle
Geosci. Model Dev., 14, 6331–6354, https://doi.org/10.5194/gmd-14-6331-2021, https://doi.org/10.5194/gmd-14-6331-2021, 2021
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This study introduces a new Sea Ice Evaluation Tool (SITool) to evaluate the model skills on the bipolar sea ice simulations by providing performance metrics and diagnostics. SITool is applied to evaluate the CMIP6 OMIP simulations. By changing the atmospheric forcing from CORE-II to JRA55-do data, many aspects of sea ice simulations are improved. SITool will be useful for helping teams managing various versions of a sea ice model or tracking the time evolution of model performance.
Tian Tian, Shuting Yang, Mehdi Pasha Karami, François Massonnet, Tim Kruschke, and Torben Koenigk
Geosci. Model Dev., 14, 4283–4305, https://doi.org/10.5194/gmd-14-4283-2021, https://doi.org/10.5194/gmd-14-4283-2021, 2021
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Three decadal prediction experiments with EC-Earth3 are performed to investigate the impact of ocean, sea ice concentration and thickness initialization, respectively. We find that the persistence of perennial thick ice in the central Arctic can affect the sea ice predictability in its adjacent waters via advection process or wind, despite those regions being seasonally ice free during two recent decades. This has implications for the coming decades as the thinning of Arctic sea ice continues.
Ann Keen, Ed Blockley, David A. Bailey, Jens Boldingh Debernard, Mitchell Bushuk, Steve Delhaye, David Docquier, Daniel Feltham, François Massonnet, Siobhan O'Farrell, Leandro Ponsoni, José M. Rodriguez, David Schroeder, Neil Swart, Takahiro Toyoda, Hiroyuki Tsujino, Martin Vancoppenolle, and Klaus Wyser
The Cryosphere, 15, 951–982, https://doi.org/10.5194/tc-15-951-2021, https://doi.org/10.5194/tc-15-951-2021, 2021
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We compare the mass budget of the Arctic sea ice in a number of the latest climate models. New output has been defined that allows us to compare the processes of sea ice growth and loss in a more detailed way than has previously been possible. We find that that the models are strikingly similar in terms of the major processes causing the annual growth and loss of Arctic sea ice and that the budget terms respond in a broadly consistent way as the climate warms during the 21st century.
Hugues Goosse, Quentin Dalaiden, Marie G. P. Cavitte, and Liping Zhang
Clim. Past, 17, 111–131, https://doi.org/10.5194/cp-17-111-2021, https://doi.org/10.5194/cp-17-111-2021, 2021
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Polynyas are ice-free oceanic areas within the sea ice pack. Small polynyas are regularly observed in the Southern Ocean, but large open-ocean polynyas have been rare over the past decades. Using records from available ice cores in Antarctica, we reconstruct past polynya activity and confirm that those events have also been rare over the past centuries, but the information provided by existing data is not sufficient to precisely characterize the timing of past polynya opening.
Qian Shi, Qinghua Yang, Longjiang Mu, Jinfei Wang, François Massonnet, and Matthew R. Mazloff
The Cryosphere, 15, 31–47, https://doi.org/10.5194/tc-15-31-2021, https://doi.org/10.5194/tc-15-31-2021, 2021
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The ice thickness from four state-of-the-art reanalyses (GECCO2, SOSE, NEMO-EnKF and GIOMAS) are evaluated against that from remote sensing and in situ observations in the Weddell Sea, Antarctica. Most of the reanalyses can reproduce ice thickness in the central and eastern Weddell Sea but failed to capture the thick and deformed ice in the western Weddell Sea. These results demonstrate the possibilities and limitations of using current sea-ice reanalysis in Antarctic climate research.
Marie G. P. Cavitte, Quentin Dalaiden, Hugues Goosse, Jan T. M. Lenaerts, and Elizabeth R. Thomas
The Cryosphere, 14, 4083–4102, https://doi.org/10.5194/tc-14-4083-2020, https://doi.org/10.5194/tc-14-4083-2020, 2020
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Surface mass balance (SMB) and surface air temperature (SAT) are correlated at the regional scale for most of Antarctica, SMB and δ18O. Areas with low/no correlation are where wind processes (foehn, katabatic wind warming, and erosion) are sufficiently active to overwhelm the synoptic-scale snow accumulation. Measured in ice cores, the link between SMB, SAT, and δ18O is much weaker. Random noise can be removed by core record averaging but local processes perturb the correlation systematically.
Guillian Van Achter, Leandro Ponsoni, François Massonnet, Thierry Fichefet, and Vincent Legat
The Cryosphere, 14, 3479–3486, https://doi.org/10.5194/tc-14-3479-2020, https://doi.org/10.5194/tc-14-3479-2020, 2020
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We document the spatio-temporal internal variability of Arctic sea ice thickness and its changes under anthropogenic forcing, which is key to understanding, and eventually predicting, the evolution of sea ice in response to climate change.
The patterns of sea ice thickness variability remain more or less stable during pre-industrial, historical and future periods, despite non-stationarity on short timescales. These patterns start to change once Arctic summer ice-free events occur, after 2050.
Eduardo Moreno-Chamarro, Pablo Ortega, and François Massonnet
Geosci. Model Dev., 13, 4773–4787, https://doi.org/10.5194/gmd-13-4773-2020, https://doi.org/10.5194/gmd-13-4773-2020, 2020
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Climate models need to capture sea ice complexity to represent it realistically. Here we assess how distributing sea ice in discrete thickness categories impacts how sea ice variability is simulated in the NEMO3.6–LIM3 model. Simulations and satellite observations are compared by using k-means clustering of sea ice concentration in winter and summer between 1979 and 2014 at both poles. Little improvements in the modeled sea ice lead us to recommend using the standard number of five categories.
David Parkes and Hugues Goosse
The Cryosphere, 14, 3135–3153, https://doi.org/10.5194/tc-14-3135-2020, https://doi.org/10.5194/tc-14-3135-2020, 2020
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Direct records of glacier changes rarely go back more than the last 100 years and are few and far between. We used a sophisticated glacier model to simulate glacier length changes over the last 1000 years for those glaciers that we do have long-term records of, to determine whether the model can run in a stable, realistic way over a long timescale, reproducing recent observed trends. We find that post-industrial changes are larger than other changes in this time period driven by recent warming.
Zhiqiang Lyu, Anais J. Orsi, and Hugues Goosse
Clim. Past, 16, 1411–1428, https://doi.org/10.5194/cp-16-1411-2020, https://doi.org/10.5194/cp-16-1411-2020, 2020
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This paper uses two different ways to perform model–data comparisons for the borehole temperature in Antarctica. The results suggest most models generally reproduce the long-term cooling in West Antarctica from 1000 to 1600 CE and the recent 50 years of warming in West Antarctica and Antarctic Peninsula. However, The 19th-century cooling in the Antarctic Peninsula (−0.94 °C) is not reproduced by any of the models, which tend to show warming instead.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Leandro Ponsoni, François Massonnet, David Docquier, Guillian Van Achter, and Thierry Fichefet
The Cryosphere, 14, 2409–2428, https://doi.org/10.5194/tc-14-2409-2020, https://doi.org/10.5194/tc-14-2409-2020, 2020
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The continuous melting of the Arctic sea ice observed in the last decades has a significant impact at global and regional scales. To understand the amplitude and consequences of this impact, the monitoring of the total sea ice volume is crucial. However, in situ monitoring in such a harsh environment is hard to perform and far too expensive. This study shows that four well-placed sampling locations are sufficient to explain about 70 % of the inter-annual changes in the pan-Arctic sea ice volume.
Jeanne Rezsöhazy, Hugues Goosse, Joël Guiot, Fabio Gennaretti, Etienne Boucher, Frédéric André, and Mathieu Jonard
Clim. Past, 16, 1043–1059, https://doi.org/10.5194/cp-16-1043-2020, https://doi.org/10.5194/cp-16-1043-2020, 2020
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Tree rings are the main data source for climate reconstructions over the last millennium. Statistical tree-growth models have limitations that process-based models could overcome. Here, we investigate the possibility of using a process-based ecophysiological model (MAIDEN) as a complex proxy system model for palaeoclimate applications. We show its ability to simulate tree-growth index time series that can fit robustly tree-ring width observations under certain conditions.
Quentin Dalaiden, Hugues Goosse, François Klein, Jan T. M. Lenaerts, Max Holloway, Louise Sime, and Elizabeth R. Thomas
The Cryosphere, 14, 1187–1207, https://doi.org/10.5194/tc-14-1187-2020, https://doi.org/10.5194/tc-14-1187-2020, 2020
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Large uncertainties remain in Antarctic surface temperature reconstructions over the last millennium. Here, the analysis of climate model outputs reveals that snow accumulation is a more relevant proxy for surface temperature reconstructions than δ18O. We use this finding in data assimilation experiments to compare to observed surface temperatures. We show that our continental temperature reconstruction outperforms reconstructions based on δ18O, especially for East Antarctica.
Louis de Wergifosse, Frédéric André, Nicolas Beudez, François de Coligny, Hugues Goosse, François Jonard, Quentin Ponette, Hugues Titeux, Caroline Vincke, and Mathieu Jonard
Geosci. Model Dev., 13, 1459–1498, https://doi.org/10.5194/gmd-13-1459-2020, https://doi.org/10.5194/gmd-13-1459-2020, 2020
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Given their key role in the simulation of climate impacts on tree growth, phenological and water balance processes must be integrated in models simulating forest dynamics under a changing environment. Here, we describe these processes integrated in HETEROFOR, a model accounting simultaneously for the functional, structural and spatial complexity to explore the forest response to forestry practices. The model evaluation using phenological and soil water content observations is quite promising.
François Massonnet, Martin Ménégoz, Mario Acosta, Xavier Yepes-Arbós, Eleftheria Exarchou, and Francisco J. Doblas-Reyes
Geosci. Model Dev., 13, 1165–1178, https://doi.org/10.5194/gmd-13-1165-2020, https://doi.org/10.5194/gmd-13-1165-2020, 2020
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Earth system models (ESMs) are one of the cornerstones of modern climate science. They are usually run on high-performance computers (HPCs). Whether the choice of HPC can affect the model results is a question of importance for optimizing the design of scientific studies. Here, we introduce a protocol for testing the replicability of the EC-Earth3 ESM across different HPCs. We find the simulation results to be replicable only if specific precautions are taken at the compilation stage.
François Massonnet, Antoine Barthélemy, Koffi Worou, Thierry Fichefet, Martin Vancoppenolle, Clément Rousset, and Eduardo Moreno-Chamarro
Geosci. Model Dev., 12, 3745–3758, https://doi.org/10.5194/gmd-12-3745-2019, https://doi.org/10.5194/gmd-12-3745-2019, 2019
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Sea ice thickness varies considerably on spatial scales of several meters. However, contemporary climate models cannot resolve such scales yet. This is why sea ice models used in climate models include an ice thickness distribution (ITD) to account for this unresolved variability. Here, we explore with the ocean–sea ice model NEMO3.6-LIM3 the sensitivity of simulated mean Arctic and Antarctic sea ice states to the way the ITD is discretized.
François Klein, Nerilie J. Abram, Mark A. J. Curran, Hugues Goosse, Sentia Goursaud, Valérie Masson-Delmotte, Andrew Moy, Raphael Neukom, Anaïs Orsi, Jesper Sjolte, Nathan Steiger, Barbara Stenni, and Martin Werner
Clim. Past, 15, 661–684, https://doi.org/10.5194/cp-15-661-2019, https://doi.org/10.5194/cp-15-661-2019, 2019
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Antarctic temperature changes over the past millennia have been reconstructed from isotope records in ice cores in several studies. However, the link between both variables is complex. Here, we investigate the extent to which this affects the robustness of temperature reconstructions using pseudoproxy and data assimilation experiments. We show that the reconstruction skill is limited, especially at the regional scale, due to a weak and nonstationary covariance between δ18O and temperature.
Chris S. M. Turney, Helen V. McGregor, Pierre Francus, Nerilie Abram, Michael N. Evans, Hugues Goosse, Lucien von Gunten, Darrell Kaufman, Hans Linderholm, Marie-France Loutre, and Raphael Neukom
Clim. Past, 15, 611–615, https://doi.org/10.5194/cp-15-611-2019, https://doi.org/10.5194/cp-15-611-2019, 2019
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This PAGES (Past Global Changes) 2k (climate of the past 2000 years working group) special issue of Climate of the Past brings together the latest understanding of regional change and impacts from PAGES 2k groups across a range of proxies and regions. The special issue has emerged from a need to determine the magnitude and rate of change of regional and global climate beyond the timescales accessible within the observational record.
Leandro Ponsoni, François Massonnet, Thierry Fichefet, Matthieu Chevallier, and David Docquier
The Cryosphere, 13, 521–543, https://doi.org/10.5194/tc-13-521-2019, https://doi.org/10.5194/tc-13-521-2019, 2019
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The Arctic is a main component of the Earth's climate system. It is fundamental to understand the behavior of Arctic sea ice coverage over time and in space due to many factors, e.g., shipping lanes, the travel and tourism industry, hunting and fishing activities, mineral resource extraction, and the potential impact on the weather in midlatitude regions. In this work we use observations and results from models to understand how variations in the sea ice thickness change over time and in space.
Marion Lebrun, Martin Vancoppenolle, Gurvan Madec, and François Massonnet
The Cryosphere, 13, 79–96, https://doi.org/10.5194/tc-13-79-2019, https://doi.org/10.5194/tc-13-79-2019, 2019
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The present analysis shows that the increase in the Arctic ice-free season duration will be asymmetrical, with later autumn freeze-up contributing about twice as much as earlier spring retreat. This feature is robustly found in a hierarchy of climate models and is consistent with a simple mechanism: solar energy is absorbed more efficiently than it can be released in non-solar form and should emerge out of variability within the next few decades.
Hugues Goosse, Pierre-Yves Barriat, Quentin Dalaiden, François Klein, Ben Marzeion, Fabien Maussion, Paolo Pelucchi, and Anouk Vlug
Clim. Past, 14, 1119–1133, https://doi.org/10.5194/cp-14-1119-2018, https://doi.org/10.5194/cp-14-1119-2018, 2018
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Glaciers provide iconic illustrations of past climate change, but records of glacier length fluctuations have not been used systematically to test the ability of models to reproduce past changes. One reason is that glacier length depends on several complex factors and so cannot be simply linked to the climate simulated by models. This is done here, and it is shown that the observed glacier length fluctuations are generally well within the range of the simulations.
Feng Shi, Sen Zhao, Zhengtang Guo, Hugues Goosse, and Qiuzhen Yin
Clim. Past, 13, 1919–1938, https://doi.org/10.5194/cp-13-1919-2017, https://doi.org/10.5194/cp-13-1919-2017, 2017
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We reconstructed the multi-proxy precipitation field for China over the past 500 years, which includes three leading modes (a monopole, a dipole, and a triple) of precipitation variability. The dipole mode may be controlled by the El Niño–Southern Oscillation variability. Such reconstruction is an essential source of information to document the climate variability over decadal to centennial timescales and can be used to assess the ability of climate models to simulate past climate change.
Kristina Seftigen, Hugues Goosse, Francois Klein, and Deliang Chen
Clim. Past, 13, 1831–1850, https://doi.org/10.5194/cp-13-1831-2017, https://doi.org/10.5194/cp-13-1831-2017, 2017
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Comparisons of proxy data to GCM-simulated hydroclimate are still limited and inter-model variability remains poorly characterized. In this study, we bring together tree-ring paleoclimate evidence and CMIP5–PMIP3 model simulations of the last millennium hydroclimate variability across Scandinavia. We explore the consistency between the datasets and the role of external forcing versus internal variability in driving the hydroclimate changes regionally.
David Docquier, François Massonnet, Antoine Barthélemy, Neil F. Tandon, Olivier Lecomte, and Thierry Fichefet
The Cryosphere, 11, 2829–2846, https://doi.org/10.5194/tc-11-2829-2017, https://doi.org/10.5194/tc-11-2829-2017, 2017
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Our study provides a new way to evaluate the performance of a climate model regarding the interplay between sea ice motion, area and thickness in the Arctic against different observation datasets. We show that the NEMO-LIM model is good in that respect and that the relationships between the different sea ice variables are complex. The metrics we developed can be used in the framework of the Coupled Model Intercomparison Project 6 (CMIP6), which will feed the next IPCC report.
Barbara Stenni, Mark A. J. Curran, Nerilie J. Abram, Anais Orsi, Sentia Goursaud, Valerie Masson-Delmotte, Raphael Neukom, Hugues Goosse, Dmitry Divine, Tas van Ommen, Eric J. Steig, Daniel A. Dixon, Elizabeth R. Thomas, Nancy A. N. Bertler, Elisabeth Isaksson, Alexey Ekaykin, Martin Werner, and Massimo Frezzotti
Clim. Past, 13, 1609–1634, https://doi.org/10.5194/cp-13-1609-2017, https://doi.org/10.5194/cp-13-1609-2017, 2017
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Within PAGES Antarctica2k, we build an enlarged database of ice core water stable isotope records. We produce isotopic composites and temperature reconstructions since 0 CE for seven distinct Antarctic regions. We find a significant cooling trend from 0 to 1900 CE across all regions. Since 1900 CE, significant warming trends are identified for three regions. Only for the Antarctic Peninsula is this most recent century-scale trend unusual in the context of last-2000-year natural variability.
Johann H. Jungclaus, Edouard Bard, Mélanie Baroni, Pascale Braconnot, Jian Cao, Louise P. Chini, Tania Egorova, Michael Evans, J. Fidel González-Rouco, Hugues Goosse, George C. Hurtt, Fortunat Joos, Jed O. Kaplan, Myriam Khodri, Kees Klein Goldewijk, Natalie Krivova, Allegra N. LeGrande, Stephan J. Lorenz, Jürg Luterbacher, Wenmin Man, Amanda C. Maycock, Malte Meinshausen, Anders Moberg, Raimund Muscheler, Christoph Nehrbass-Ahles, Bette I. Otto-Bliesner, Steven J. Phipps, Julia Pongratz, Eugene Rozanov, Gavin A. Schmidt, Hauke Schmidt, Werner Schmutz, Andrew Schurer, Alexander I. Shapiro, Michael Sigl, Jason E. Smerdon, Sami K. Solanki, Claudia Timmreck, Matthew Toohey, Ilya G. Usoskin, Sebastian Wagner, Chi-Ju Wu, Kok Leng Yeo, Davide Zanchettin, Qiong Zhang, and Eduardo Zorita
Geosci. Model Dev., 10, 4005–4033, https://doi.org/10.5194/gmd-10-4005-2017, https://doi.org/10.5194/gmd-10-4005-2017, 2017
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Climate model simulations covering the last millennium provide context for the evolution of the modern climate and for the expected changes during the coming centuries. They can help identify plausible mechanisms underlying palaeoclimatic reconstructions. Here, we describe the forcing boundary conditions and the experimental protocol for simulations covering the pre-industrial millennium. We describe the PMIP4 past1000 simulations as contributions to CMIP6 and additional sensitivity experiments.
Chris S.~M. Turney, Andrew Klekociuk, Christopher J. Fogwill, Violette Zunz, Hugues Goosse, Claire L. Parkinson, Gilbert Compo, Matthew Lazzara, Linda Keller, Rob Allan, Jonathan G. Palmer, Graeme Clark, and Ezequiel Marzinelli
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-51, https://doi.org/10.5194/tc-2017-51, 2017
Revised manuscript not accepted
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We demonstrate that a mid-twentieth century decrease in geopotential height in the southwest Pacific marks a Rossby wave response to equatorial Pacific warming, leading to enhanced easterly airflow off George V Land. Our results suggest that in contrast to ozone hole-driven changes in the Amundsen Sea, the 1979–2015 increase in sea ice extent off George V Land may be in response to reduced northward Ekman drift and enhanced (near-coast) production as a consequence of low latitude forcing.
Chris S. M. Turney, Christopher J. Fogwill, Jonathan G. Palmer, Erik van Sebille, Zoë Thomas, Matt McGlone, Sarah Richardson, Janet M. Wilmshurst, Pavla Fenwick, Violette Zunz, Hugues Goosse, Kerry-Jayne Wilson, Lionel Carter, Mathew Lipson, Richard T. Jones, Melanie Harsch, Graeme Clark, Ezequiel Marzinelli, Tracey Rogers, Eleanor Rainsley, Laura Ciasto, Stephanie Waterman, Elizabeth R. Thomas, and Martin Visbeck
Clim. Past, 13, 231–248, https://doi.org/10.5194/cp-13-231-2017, https://doi.org/10.5194/cp-13-231-2017, 2017
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The Southern Ocean plays a fundamental role in global climate but suffers from a dearth of observational data. As the Australasian Antarctic Expedition 2013–2014 we have developed the first annually resolved temperature record using trees from subantarctic southwest Pacific (52–54˚S) to extend the climate record back to 1870. With modelling we show today's high climate variability became established in the ~1940s and likely driven by a Rossby wave response originating from the tropical Pacific.
Dirk Notz, Alexandra Jahn, Marika Holland, Elizabeth Hunke, François Massonnet, Julienne Stroeve, Bruno Tremblay, and Martin Vancoppenolle
Geosci. Model Dev., 9, 3427–3446, https://doi.org/10.5194/gmd-9-3427-2016, https://doi.org/10.5194/gmd-9-3427-2016, 2016
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The large-scale evolution of sea ice is both an indicator and a driver of climate changes. Hence, a realistic simulation of sea ice is key for a realistic simulation of the climate system of our planet. To assess and to improve the realism of sea-ice simulations, we present here a new protocol for climate-model output that allows for an in-depth analysis of the simulated evolution of sea ice.
François Klein, Hugues Goosse, Nicholas E. Graham, and Dirk Verschuren
Clim. Past, 12, 1499–1518, https://doi.org/10.5194/cp-12-1499-2016, https://doi.org/10.5194/cp-12-1499-2016, 2016
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This paper analyses global climate model simulations of long-term East African hydroclimate changes relative to proxy-based reconstructions over the last millennium. No common signal is found between model results and reconstructions as well as among the model time series, which suggests that simulated hydroclimate is mostly driven by internal variability rather than by common external forcing.
C. Rousset, M. Vancoppenolle, G. Madec, T. Fichefet, S. Flavoni, A. Barthélemy, R. Benshila, J. Chanut, C. Levy, S. Masson, and F. Vivier
Geosci. Model Dev., 8, 2991–3005, https://doi.org/10.5194/gmd-8-2991-2015, https://doi.org/10.5194/gmd-8-2991-2015, 2015
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LIM3.6 presented in this paper is the last release of the Louvain-la-Neuve sea ice model, and will be used for the next climate model intercomparison project (CMIP6). The model's robustness, versatility and sophistication have been improved.
V. Zunz and H. Goosse
The Cryosphere, 9, 541–556, https://doi.org/10.5194/tc-9-541-2015, https://doi.org/10.5194/tc-9-541-2015, 2015
M. F. Loutre, T. Fichefet, H. Goosse, P. Huybrechts, H. Goelzer, and E. Capron
Clim. Past, 10, 1541–1565, https://doi.org/10.5194/cp-10-1541-2014, https://doi.org/10.5194/cp-10-1541-2014, 2014
P. J. Hezel, T. Fichefet, and F. Massonnet
The Cryosphere, 8, 1195–1204, https://doi.org/10.5194/tc-8-1195-2014, https://doi.org/10.5194/tc-8-1195-2014, 2014
F. Klein, H. Goosse, A. Mairesse, and A. de Vernal
Clim. Past, 10, 1145–1163, https://doi.org/10.5194/cp-10-1145-2014, https://doi.org/10.5194/cp-10-1145-2014, 2014
H. Goosse and V. Zunz
The Cryosphere, 8, 453–470, https://doi.org/10.5194/tc-8-453-2014, https://doi.org/10.5194/tc-8-453-2014, 2014
A. Mairesse, H. Goosse, P. Mathiot, H. Wanner, and S. Dubinkina
Clim. Past, 9, 2741–2757, https://doi.org/10.5194/cp-9-2741-2013, https://doi.org/10.5194/cp-9-2741-2013, 2013
S. Dubinkina and H. Goosse
Clim. Past, 9, 1141–1152, https://doi.org/10.5194/cp-9-1141-2013, https://doi.org/10.5194/cp-9-1141-2013, 2013
M. Eby, A. J. Weaver, K. Alexander, K. Zickfeld, A. Abe-Ouchi, A. A. Cimatoribus, E. Crespin, S. S. Drijfhout, N. R. Edwards, A. V. Eliseev, G. Feulner, T. Fichefet, C. E. Forest, H. Goosse, P. B. Holden, F. Joos, M. Kawamiya, D. Kicklighter, H. Kienert, K. Matsumoto, I. I. Mokhov, E. Monier, S. M. Olsen, J. O. P. Pedersen, M. Perrette, G. Philippon-Berthier, A. Ridgwell, A. Schlosser, T. Schneider von Deimling, G. Shaffer, R. S. Smith, R. Spahni, A. P. Sokolov, M. Steinacher, K. Tachiiri, K. Tokos, M. Yoshimori, N. Zeng, and F. Zhao
Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, https://doi.org/10.5194/cp-9-1111-2013, 2013
P. Mathiot, H. Goosse, X. Crosta, B. Stenni, M. Braida, H. Renssen, C. J. Van Meerbeeck, V. Masson-Delmotte, A. Mairesse, and S. Dubinkina
Clim. Past, 9, 887–901, https://doi.org/10.5194/cp-9-887-2013, https://doi.org/10.5194/cp-9-887-2013, 2013
V. Zunz, H. Goosse, and F. Massonnet
The Cryosphere, 7, 451–468, https://doi.org/10.5194/tc-7-451-2013, https://doi.org/10.5194/tc-7-451-2013, 2013
Related subject area
Discipline: Sea ice | Subject: Antarctic
Quantifying the influence of snow over sea ice morphology on L-band passive microwave satellite observations in the Southern Ocean
Sources of low-frequency variability in observed Antarctic sea ice
A contrast in sea ice drift and deformation between winter and spring of 2019 in the Antarctic marginal ice zone
Brief Communication: Antarctic sea ice loss brings observed trends into agreement with climate models
Multidecadal variability and predictability of Antarctic sea ice in the GFDL SPEAR_LO model
Signature of the stratosphere–troposphere coupling on recent record-breaking Antarctic sea-ice anomalies
Southern Ocean polynyas and dense water formation in a high-resolution, coupled Earth system model
A decade-plus of Antarctic sea ice thickness and volume estimates from CryoSat-2 using a physical model and waveform fitting
Annual evolution of the ice–ocean interaction beneath landfast ice in Prydz Bay, East Antarctica
The response of sea ice and high-salinity shelf water in the Ross Ice Shelf Polynya to cyclonic atmosphere circulations
Antarctic sea ice regime shift associated with decreasing zonal symmetry in the Southern Annular Mode
Evolution of the dynamics, area, and ice production of the Amundsen Sea Polynya, Antarctica, 2016–2021
Modulation of the seasonal cycle of the Antarctic sea ice extent by sea ice processes and feedbacks with the ocean and the atmosphere
Ice Sheet and Sea Ice Ultrawideband Microwave radiometric Airborne eXperiment (ISSIUMAX) in Antarctica: first results from Terra Nova Bay
Influence of fast ice on future ice shelf melting in the Totten Glacier area, East Antarctica
A comparison between Envisat and ICESat sea ice thickness in the Southern Ocean
An indicator of sea ice variability for the Antarctic marginal ice zone
Physical and mechanical properties of winter first-year ice in the Antarctic marginal ice zone along the Good Hope Line
Altimetric observation of wave attenuation through the Antarctic marginal ice zone using ICESat-2
Flexural and compressive strength of the landfast sea ice in the Prydz Bay, East Antarctic
The sensitivity of landfast sea ice to atmospheric forcing in single-column model simulations: a case study at Zhongshan Station, Antarctica
An evaluation of Antarctic sea-ice thickness from the Global Ice-Ocean Modeling and Assimilation System based on in situ and satellite observations
Rectification and validation of a daily satellite-derived Antarctic sea ice velocity product
Weddell Sea polynya analysis using SMOS–SMAP apparent sea ice thickness retrieval
Eighteen-year record of circum-Antarctic landfast-sea-ice distribution allows detailed baseline characterisation and reveals trends and variability
Brief communication: The anomalous winter 2019 sea-ice conditions in McMurdo Sound, Antarctica
Southern Ocean polynyas in CMIP6 models
Airborne mapping of the sub-ice platelet layer under fast ice in McMurdo Sound, Antarctica
Evaluation of sea-ice thickness from four reanalyses in the Antarctic Weddell Sea
The Antarctic sea ice cover from ICESat-2 and CryoSat-2: freeboard, snow depth, and ice thickness
Seasonal and interannual variability of landfast sea ice in Atka Bay, Weddell Sea, Antarctica
Influence of sea-ice anomalies on Antarctic precipitation using source attribution in the Community Earth System Model
Retrieval of snow freeboard of Antarctic sea ice using waveform fitting of CryoSat-2 returns
Three years of sea ice freeboard, snow depth, and ice thickness of the Weddell Sea from Operation IceBridge and CryoSat-2
Lu Zhou, Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Shiming Xu, Weixin Zhu, Sahra Kacimi, Stefanie Arndt, and Zifan Yang
The Cryosphere, 18, 4399–4434, https://doi.org/10.5194/tc-18-4399-2024, https://doi.org/10.5194/tc-18-4399-2024, 2024
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Snow over Antarctic sea ice, influenced by highly variable meteorological conditions and heavy snowfall, has a complex stratigraphy and profound impact on the microwave signature. We employ advanced radiation transfer models to analyse the effects of complex snow properties on brightness temperatures over the sea ice in the Southern Ocean. Great potential lies in the understanding of snow processes and the application to satellite retrievals.
David B. Bonan, Jakob Dörr, Robert C. J. Wills, Andrew F. Thompson, and Marius Årthun
The Cryosphere, 18, 2141–2159, https://doi.org/10.5194/tc-18-2141-2024, https://doi.org/10.5194/tc-18-2141-2024, 2024
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Antarctic sea ice has exhibited variability over satellite records, including a period of gradual expansion and a period of sudden decline. We use a novel statistical method to identify sources of variability in observed Antarctic sea ice changes. We find that the gradual increase in sea ice is likely related to large-scale temperature trends, and periods of abrupt sea ice decline are related to specific flavors of equatorial tropical variability known as the El Niño–Southern Oscillation.
Ashleigh Womack, Alberto Alberello, Marc de Vos, Alessandro Toffoli, Robyn Verrinder, and Marcello Vichi
The Cryosphere, 18, 205–229, https://doi.org/10.5194/tc-18-205-2024, https://doi.org/10.5194/tc-18-205-2024, 2024
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Synoptic events have a significant influence on the evolution of Antarctic sea ice. Our current understanding of the interactions between cyclones and sea ice remains limited. Using two ensembles of buoys, deployed in the north-eastern Weddell Sea region during winter and spring of 2019, we show how the evolution and spatial pattern of sea ice drift and deformation in the Antarctic marginal ice zone were affected by the balance between atmospheric and oceanic forcing and the local ice.
Caroline R. Holmes, Thomas J. Bracegirdle, Paul R. Holland, Julienne Stroeve, and Jeremy Wilkinson
EGUsphere, https://doi.org/10.5194/egusphere-2023-2881, https://doi.org/10.5194/egusphere-2023-2881, 2023
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Until recently, observed Antarctic sea ice was increasing, while in contrast numerical climate models simulated a decrease over the same period (1979–2014). This apparent mismatch was one reason for low confidence in model projections of large 21st century sea ice loss and related aspects of Southern Hemisphere climate. Here we show that, with the inclusion of several low Antarctic sea ice years (notably 2017, 2022 and 2023), we can no longer conclude that modelled and observed trends differ.
Yushi Morioka, Liping Zhang, Thomas L. Delworth, Xiaosong Yang, Fanrong Zeng, Masami Nonaka, and Swadhin K. Behera
The Cryosphere, 17, 5219–5240, https://doi.org/10.5194/tc-17-5219-2023, https://doi.org/10.5194/tc-17-5219-2023, 2023
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Antarctic sea ice extent shows multidecadal variations with its decrease in the 1980s and increase after the 2000s until 2015. Here we show that our climate model can predict the sea ice decrease by deep convection in the Southern Ocean and the sea ice increase by the surface wind variability. These results suggest that accurate simulation and prediction of subsurface ocean and atmosphere conditions are important for those of Antarctic sea ice variability on a multidecadal timescale.
Raúl R. Cordero, Sarah Feron, Alessandro Damiani, Pedro J. Llanillo, Jorge Carrasco, Alia L. Khan, Richard Bintanja, Zutao Ouyang, and Gino Casassa
The Cryosphere, 17, 4995–5006, https://doi.org/10.5194/tc-17-4995-2023, https://doi.org/10.5194/tc-17-4995-2023, 2023
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We investigate the response of Antarctic sea ice to year-to-year changes in the tropospheric–stratospheric dynamics. Our findings suggest that, by affecting the tropospheric westerlies, the strength of the stratospheric polar vortex has played a major role in recent record-breaking anomalies in Antarctic sea ice.
Hyein Jeong, Adrian K. Turner, Andrew F. Roberts, Milena Veneziani, Stephen F. Price, Xylar S. Asay-Davis, Luke P. Van Roekel, Wuyin Lin, Peter M. Caldwell, Hyo-Seok Park, Jonathan D. Wolfe, and Azamat Mametjanov
The Cryosphere, 17, 2681–2700, https://doi.org/10.5194/tc-17-2681-2023, https://doi.org/10.5194/tc-17-2681-2023, 2023
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We find that E3SM-HR reproduces the main features of the Antarctic coastal polynyas. Despite the high amount of coastal sea ice production, the densest water masses are formed in the open ocean. Biases related to the lack of dense water formation are associated with overly strong atmospheric polar easterlies. Our results indicate that the large-scale polar atmospheric circulation must be accurately simulated in models to properly reproduce Antarctic dense water formation.
Steven Fons, Nathan Kurtz, and Marco Bagnardi
The Cryosphere, 17, 2487–2508, https://doi.org/10.5194/tc-17-2487-2023, https://doi.org/10.5194/tc-17-2487-2023, 2023
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Antarctic sea ice thickness is an important quantity in the Earth system. Due to the thick and complex snow cover on Antarctic sea ice, estimating the thickness of the ice pack is difficult using traditional methods in radar altimetry. In this work, we use a waveform model to estimate the freeboard and snow depth of Antarctic sea ice from CryoSat-2 and use these values to calculate sea ice thickness and volume between 2010 and 2021 and showcase how the sea ice pack has changed over this time.
Haihan Hu, Jiechen Zhao, Petra Heil, Zhiliang Qin, Jingkai Ma, Fengming Hui, and Xiao Cheng
The Cryosphere, 17, 2231–2244, https://doi.org/10.5194/tc-17-2231-2023, https://doi.org/10.5194/tc-17-2231-2023, 2023
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The oceanic characteristics beneath sea ice significantly affect ice growth and melting. The high-frequency and long-term observations of oceanic variables allow us to deeply investigate their diurnal and seasonal variation and evaluate their influences on sea ice evolution. The large-scale sea ice distribution and ocean circulation contributed to the seasonal variation of ocean variables, revealing the important relationship between large-scale and local phenomena.
Xiaoqiao Wang, Zhaoru Zhang, Michael S. Dinniman, Petteri Uotila, Xichen Li, and Meng Zhou
The Cryosphere, 17, 1107–1126, https://doi.org/10.5194/tc-17-1107-2023, https://doi.org/10.5194/tc-17-1107-2023, 2023
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The bottom water of the global ocean originates from high-salinity water formed in polynyas in the Southern Ocean where sea ice coverage is low. This study reveals the impacts of cyclones on sea ice and water mass formation in the Ross Ice Shelf Polynya using numerical simulations. Sea ice production is rapidly increased caused by enhancement in offshore wind, promoting high-salinity water formation in the polynya. Cyclones also modulate the transport of this water mass by wind-driven currents.
Serena Schroeter, Terence J. O'Kane, and Paul A. Sandery
The Cryosphere, 17, 701–717, https://doi.org/10.5194/tc-17-701-2023, https://doi.org/10.5194/tc-17-701-2023, 2023
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Antarctic sea ice has increased over much of the satellite record, but we show that the early, strongly opposing regional trends diminish and reverse over time, leading to overall negative trends in recent decades. The dominant pattern of atmospheric flow has changed from strongly east–west to more wave-like with enhanced north–south winds. Sea surface temperatures have also changed from circumpolar cooling to regional warming, suggesting recent record low sea ice will not rapidly recover.
Grant J. Macdonald, Stephen F. Ackley, Alberto M. Mestas-Nuñez, and Adrià Blanco-Cabanillas
The Cryosphere, 17, 457–476, https://doi.org/10.5194/tc-17-457-2023, https://doi.org/10.5194/tc-17-457-2023, 2023
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Polynyas are key sites of sea ice production, biological activity, and carbon sequestration. The Amundsen Sea Polynya is of particular interest due to its size and location. By analyzing radar imagery and climate and sea ice data products, we evaluate variations in the dynamics, area, and ice production of the Amundsen Sea Polynya. In particular, we find the local seafloor topography and associated grounded icebergs play an important role in the polynya dynamics, influencing ice production.
Hugues Goosse, Sofia Allende Contador, Cecilia M. Bitz, Edward Blanchard-Wrigglesworth, Clare Eayrs, Thierry Fichefet, Kenza Himmich, Pierre-Vincent Huot, François Klein, Sylvain Marchi, François Massonnet, Bianca Mezzina, Charles Pelletier, Lettie Roach, Martin Vancoppenolle, and Nicole P. M. van Lipzig
The Cryosphere, 17, 407–425, https://doi.org/10.5194/tc-17-407-2023, https://doi.org/10.5194/tc-17-407-2023, 2023
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Using idealized sensitivity experiments with a regional atmosphere–ocean–sea ice model, we show that sea ice advance is constrained by initial conditions in March and the retreat season is influenced by the magnitude of several physical processes, in particular by the ice–albedo feedback and ice transport. Atmospheric feedbacks amplify the response of the winter ice extent to perturbations, while some negative feedbacks related to heat conduction fluxes act on the ice volume.
Marco Brogioni, Mark J. Andrews, Stefano Urbini, Kenneth C. Jezek, Joel T. Johnson, Marion Leduc-Leballeur, Giovanni Macelloni, Stephen F. Ackley, Alexandra Bringer, Ludovic Brucker, Oguz Demir, Giacomo Fontanelli, Caglar Yardim, Lars Kaleschke, Francesco Montomoli, Leung Tsang, Silvia Becagli, and Massimo Frezzotti
The Cryosphere, 17, 255–278, https://doi.org/10.5194/tc-17-255-2023, https://doi.org/10.5194/tc-17-255-2023, 2023
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In 2018 the first Antarctic campaign of UWBRAD was carried out. UWBRAD is a new radiometer able to collect microwave spectral signatures over 0.5–2 GHz, thus outperforming existing similar sensors. It allows us to probe thicker sea ice and ice sheet down to the bedrock. In this work we tried to assess the UWBRAD potentials for sea ice, glaciers, ice shelves and buried lakes. We also highlighted the wider range of information the spectral signature can provide to glaciological studies.
Guillian Van Achter, Thierry Fichefet, Hugues Goosse, and Eduardo Moreno-Chamarro
The Cryosphere, 16, 4745–4761, https://doi.org/10.5194/tc-16-4745-2022, https://doi.org/10.5194/tc-16-4745-2022, 2022
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We investigate the changes in ocean–ice interactions in the Totten Glacier area between the last decades (1995–2014) and the end of the 21st century (2081–2100) under warmer climate conditions. By the end of the 21st century, the sea ice is strongly reduced, and the ocean circulation close to the coast is accelerated. Our research highlights the importance of including representations of fast ice to simulate realistic ice shelf melt rate increase in East Antarctica under warming conditions.
Jinfei Wang, Chao Min, Robert Ricker, Qian Shi, Bo Han, Stefan Hendricks, Renhao Wu, and Qinghua Yang
The Cryosphere, 16, 4473–4490, https://doi.org/10.5194/tc-16-4473-2022, https://doi.org/10.5194/tc-16-4473-2022, 2022
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The differences between Envisat and ICESat sea ice thickness (SIT) reveal significant temporal and spatial variations. Our findings suggest that both overestimation of Envisat sea ice freeboard, potentially caused by radar backscatter originating from inside the snow layer, and the AMSR-E snow depth biases and sea ice density uncertainties can possibly account for the differences between Envisat and ICESat SIT.
Marcello Vichi
The Cryosphere, 16, 4087–4106, https://doi.org/10.5194/tc-16-4087-2022, https://doi.org/10.5194/tc-16-4087-2022, 2022
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The marginal ice zone (MIZ) in the Antarctic is the largest in the world ocean. Antarctic sea ice has large year-to-year changes, and the MIZ represents its most variable component. Processes typical of the MIZ have also been observed in fully ice-covered ocean and are not captured by existing diagnostics. A new statistical method has been shown to address previous limitations in assessing the seasonal cycle of MIZ extent and to provide a probability map of sea ice state in the Southern Ocean.
Sebastian Skatulla, Riesna R. Audh, Andrea Cook, Ehlke Hepworth, Siobhan Johnson, Doru C. Lupascu, Keith MacHutchon, Rutger Marquart, Tommy Mielke, Emmanuel Omatuku, Felix Paul, Tokoloho Rampai, Jörg Schröder, Carina Schwarz, and Marcello Vichi
The Cryosphere, 16, 2899–2925, https://doi.org/10.5194/tc-16-2899-2022, https://doi.org/10.5194/tc-16-2899-2022, 2022
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First-year sea ice has been sampled at the advancing outer edge of the Antarctic marginal ice zone (MIZ) along the Good Hope Line. Ice cores were extracted from five pancake ice floes and subsequently analysed for their physical and mechanical properties. Of particular interest was elucidating the transition of ice composition within the MIZ in terms of differences in mechanical stiffness and strength properties as linked to physical and textural characteristics at early-stage ice formation.
Jill Brouwer, Alexander D. Fraser, Damian J. Murphy, Pat Wongpan, Alberto Alberello, Alison Kohout, Christopher Horvat, Simon Wotherspoon, Robert A. Massom, Jessica Cartwright, and Guy D. Williams
The Cryosphere, 16, 2325–2353, https://doi.org/10.5194/tc-16-2325-2022, https://doi.org/10.5194/tc-16-2325-2022, 2022
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The marginal ice zone is the region where ocean waves interact with sea ice. Although this important region influences many sea ice, ocean and biological processes, it has been difficult to accurately measure on a large scale from satellite instruments. We present new techniques for measuring wave attenuation using the NASA ICESat-2 laser altimeter. By measuring how waves attenuate within the sea ice, we show that the marginal ice zone may be far wider than previously realised.
Qingkai Wang, Zhaoquan Li, Peng Lu, Yigang Xu, and Zhijun Li
The Cryosphere, 16, 1941–1961, https://doi.org/10.5194/tc-16-1941-2022, https://doi.org/10.5194/tc-16-1941-2022, 2022
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A large area of landfast sea ice exists in the Prydz Bay, and it is always a safety concern to transport cargos on ice to the research stations. Knowing the mechanical properties of sea ice is helpful to solve the issue; however, these data are rarely reported in this region. We explore the effects of sea ice physical properties on the flexural strength, effective elastic modulus, and uniaxial compressive strength, which gives new insights into assessing the bearing capacity of landfast sea ice.
Fengguan Gu, Qinghua Yang, Frank Kauker, Changwei Liu, Guanghua Hao, Chao-Yuan Yang, Jiping Liu, Petra Heil, Xuewei Li, and Bo Han
The Cryosphere, 16, 1873–1887, https://doi.org/10.5194/tc-16-1873-2022, https://doi.org/10.5194/tc-16-1873-2022, 2022
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The sea ice thickness was simulated by a single-column model and compared with in situ observations obtained off Zhongshan Station in the Antarctic. It is shown that the unrealistic precipitation in the atmospheric forcing data leads to the largest bias in sea ice thickness and snow depth modeling. In addition, the increasing snow depth gradually inhibits the growth of sea ice associated with thermal blanketing by the snow.
Sutao Liao, Hao Luo, Jinfei Wang, Qian Shi, Jinlun Zhang, and Qinghua Yang
The Cryosphere, 16, 1807–1819, https://doi.org/10.5194/tc-16-1807-2022, https://doi.org/10.5194/tc-16-1807-2022, 2022
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The Global Ice-Ocean Modeling and Assimilation System (GIOMAS) can basically reproduce the observed variability in Antarctic sea-ice volume and its changes in the trend before and after 2013, and it underestimates Antarctic sea-ice thickness (SIT) especially in deformed ice zones. Assimilating additional sea-ice observations with advanced assimilation methods may result in a more accurate estimation of Antarctic SIT.
Tian R. Tian, Alexander D. Fraser, Noriaki Kimura, Chen Zhao, and Petra Heil
The Cryosphere, 16, 1299–1314, https://doi.org/10.5194/tc-16-1299-2022, https://doi.org/10.5194/tc-16-1299-2022, 2022
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This study presents a comprehensive validation of a satellite observational sea ice motion product in Antarctica by using drifting buoys. Two problems existing in this sea ice motion product have been noticed. After rectifying problems, we use it to investigate the impacts of satellite observational configuration and timescale on Antarctic sea ice kinematics and suggest the future improvement of satellite missions specifically designed for retrieval of sea ice motion.
Alexander Mchedlishvili, Gunnar Spreen, Christian Melsheimer, and Marcus Huntemann
The Cryosphere, 16, 471–487, https://doi.org/10.5194/tc-16-471-2022, https://doi.org/10.5194/tc-16-471-2022, 2022
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In this paper we show that the activity leading to the open-ocean polynyas near the Maud Rise seamount that have occurred repeatedly from 1974–1976 as well as 2016–2017 does not simply stop for polynya-free years. Using apparent sea ice thickness retrieval, we have identified anomalies where there is thinning of sea ice on a scale that is comparable to that of the polynya events of 2016–2017. These anomalies took place in 2010, 2013, 2014 and 2018.
Alexander D. Fraser, Robert A. Massom, Mark S. Handcock, Phillip Reid, Kay I. Ohshima, Marilyn N. Raphael, Jessica Cartwright, Andrew R. Klekociuk, Zhaohui Wang, and Richard Porter-Smith
The Cryosphere, 15, 5061–5077, https://doi.org/10.5194/tc-15-5061-2021, https://doi.org/10.5194/tc-15-5061-2021, 2021
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Landfast ice is sea ice that remains stationary by attaching to Antarctica's coastline and grounded icebergs. Although a variable feature, landfast ice exerts influence on key coastal processes involving pack ice, the ice sheet, ocean, and atmosphere and is of ecological importance. We present a first analysis of change in landfast ice over an 18-year period and quantify trends (−0.19 ± 0.18 % yr−1). This analysis forms a reference of landfast-ice extent and variability for use in other studies.
Greg H. Leonard, Kate E. Turner, Maren E. Richter, Maddy S. Whittaker, and Inga J. Smith
The Cryosphere, 15, 4999–5006, https://doi.org/10.5194/tc-15-4999-2021, https://doi.org/10.5194/tc-15-4999-2021, 2021
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McMurdo Sound sea ice can generally be partitioned into two regimes: a stable fast-ice cover forming south of approximately 77.6° S and a more dynamic region north of 77.6° S that is regularly impacted by polynyas. In 2019, a stable fast-ice cover formed unusually late due to repeated break-out events. This subsequently affected sea-ice operations in the 2019/20 field season. We analysed the 2019 sea-ice conditions and found a strong correlation with unusually large southerly wind events.
Martin Mohrmann, Céline Heuzé, and Sebastiaan Swart
The Cryosphere, 15, 4281–4313, https://doi.org/10.5194/tc-15-4281-2021, https://doi.org/10.5194/tc-15-4281-2021, 2021
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Polynyas are large open-water areas within the sea ice. We developed a method to estimate their area, distribution and frequency for the Southern Ocean in climate models and observations. All models have polynyas along the coast but few do so in the open ocean, in contrast to observations. We examine potential atmospheric and oceanic drivers of open-water polynyas and discuss recently implemented schemes that may have improved some models' polynya representation.
Christian Haas, Patricia J. Langhorne, Wolfgang Rack, Greg H. Leonard, Gemma M. Brett, Daniel Price, Justin F. Beckers, and Alex J. Gough
The Cryosphere, 15, 247–264, https://doi.org/10.5194/tc-15-247-2021, https://doi.org/10.5194/tc-15-247-2021, 2021
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We developed a method to remotely detect proxy signals of Antarctic ice shelf melt under adjacent sea ice. It is based on aircraft surveys with electromagnetic induction sounding. We found year-to-year variability of the ice shelf melt proxy in McMurdo Sound and spatial fine structure that support assumptions about the melt of the McMurdo Ice Shelf. With this method it will be possible to map and detect locations of intense ice shelf melt along the coast of Antarctica.
Qian Shi, Qinghua Yang, Longjiang Mu, Jinfei Wang, François Massonnet, and Matthew R. Mazloff
The Cryosphere, 15, 31–47, https://doi.org/10.5194/tc-15-31-2021, https://doi.org/10.5194/tc-15-31-2021, 2021
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The ice thickness from four state-of-the-art reanalyses (GECCO2, SOSE, NEMO-EnKF and GIOMAS) are evaluated against that from remote sensing and in situ observations in the Weddell Sea, Antarctica. Most of the reanalyses can reproduce ice thickness in the central and eastern Weddell Sea but failed to capture the thick and deformed ice in the western Weddell Sea. These results demonstrate the possibilities and limitations of using current sea-ice reanalysis in Antarctic climate research.
Sahra Kacimi and Ron Kwok
The Cryosphere, 14, 4453–4474, https://doi.org/10.5194/tc-14-4453-2020, https://doi.org/10.5194/tc-14-4453-2020, 2020
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Our current understanding of Antarctic ice cover is largely informed by ice extent measurements from passive microwave sensors. These records, while useful, provide a limited picture of how the ice is responding to climate change. In this paper, we combine measurements from ICESat-2 and CryoSat-2 missions to assess snow depth and ice thickness of the Antarctic ice cover over an 8-month period (April through November 2019). The potential impact of salinity in the snow layer is discussed.
Stefanie Arndt, Mario Hoppmann, Holger Schmithüsen, Alexander D. Fraser, and Marcel Nicolaus
The Cryosphere, 14, 2775–2793, https://doi.org/10.5194/tc-14-2775-2020, https://doi.org/10.5194/tc-14-2775-2020, 2020
Hailong Wang, Jeremy G. Fyke, Jan T. M. Lenaerts, Jesse M. Nusbaumer, Hansi Singh, David Noone, Philip J. Rasch, and Rudong Zhang
The Cryosphere, 14, 429–444, https://doi.org/10.5194/tc-14-429-2020, https://doi.org/10.5194/tc-14-429-2020, 2020
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Using a climate model with unique water source tagging, we found that sea-ice anomalies in the Southern Ocean and accompanying SST changes have a significant influence on Antarctic precipitation and its source attribution through their direct impact on moisture sources and indirect impact on moisture transport. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies on regional Antarctic precipitation.
Steven W. Fons and Nathan T. Kurtz
The Cryosphere, 13, 861–878, https://doi.org/10.5194/tc-13-861-2019, https://doi.org/10.5194/tc-13-861-2019, 2019
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A method to measure the snow freeboard of Antarctic sea ice from CryoSat-2 data is developed. Through comparisons with data from airborne campaigns and another satellite mission, we find that this method can reasonably retrieve snow freeboard across the Antarctic and shows promise in retrieving snow depth in certain locations. Snow freeboard data from CryoSat-2 are important because they enable the calculation of sea ice thickness and help to better understand snow depth on Antarctic sea ice.
Ron Kwok and Sahra Kacimi
The Cryosphere, 12, 2789–2801, https://doi.org/10.5194/tc-12-2789-2018, https://doi.org/10.5194/tc-12-2789-2018, 2018
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The variability of snow depth and ice thickness in three years of repeat surveys of an IceBridge (OIB) transect across the Weddell Sea is examined. Retrieved thicknesses suggest a highly variable but broadly thicker ice cover compared to that inferred from drilling and ship-based measurements. The use of lidar and radar altimeters to estimate snow depth for thickness calculations is analyzed, and the need for better characterization of biases due to radar penetration effects is highlighted.
Cited articles
Barthélemy, A., Goosse, H., Fichefet, T., and Lecomte, O.: On the sensitivity of Antarctic sea ice model biases to atmospheric forcing uncertainties, Clim. Dynam., 51, 1585–1603, https://doi.org/10.1007/s00382-017-3972-7, 2018.
Comiso, J. C., Gersten, R. A., Stock, L. V., Turner, J., Perez, G. J., and Cho, K.: Positive Trend in the Antarctic Sea Ice Cover and Associated Changes in Surface Temperature, J. Climate, 30, 2251–2267, https://doi.org/10.1175/JCLI-D-16-0408.1, 2017.
Goosse, H., Allende Contador, S., Bitz, C. M., Blanchard-Wrigglesworth, E., Eayrs, C., Fichefet, T., Himmich, K., Huot, P.-V., Klein, F., Marchi, S., Massonnet, F., Mezzina, B., Pelletier, C., Roach, L., Vancoppenolle, M., and van Lipzig, N. P. M.: Modulation of the seasonal cycle of the Antarctic sea ice extent by sea ice processes and feedbacks with the ocean and the atmosphere, The Cryosphere, 17, 407–425, https://doi.org/10.5194/tc-17-407-2023, 2023.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.f17050d7, 2023.
Hobbs, W. R., Massom, R., Stammerjohn, S., Reid, P., Williams, G., and Meier, W.: A review of recent changes in Southern Ocean sea ice, their drivers and forcings, Global Planet. Change, 143, 228–250, https://doi.org/10.1016/j.gloplacha.2016.06.008, 2016.
Holland, M. M., Blanchard-Wrigglesworth, E., Kay, J., and Vavrus, S: Initial-value predictability of Antarctic sea ice in the Community Climate System Model 3. Geophys. Res. Lett., 40, 2121–2124, https://doi.org/10.1002/grl.50410, 2013.
Holland, M. M., Landrum, L., Raphael, M., and Stammerjohn, S.: Springtime winds drive Ross Sea ice variability and change in the following autumn, Nat. Commun., 8, 731, https://doi.org/10.1038/s41467-017-00820-0, 2017.
Holland, M. M., Landrum, L., Raphael, M. N., and Kwok, R.: The regional, seasonal, and lagged influence of the Amundsen Sea Lowon Antarctic sea ice, Geophys. Res. Lett., 45, 11227–11234, https://doi.org/10.1029/2018gl080140, 2018.
Holland, P. R. and Kwok, R.: Wind-driven trends in Antarctic sea-ice drift, Nat. Geosci., 5, 872–875, https://doi.org/10.1038/ngeo1627, 2012.
Holmes, C. R., Holland, P. R., and Bracegirdle, T. J.: Compensating biases and a noteworthy success in the CMIP5 representation of Antarctic sea ice processes. Geophys. Res. Lett., 46, 4299–4307, https://doi.org/10.1029/2018GL081796, 2019.
Jena, B., Bajish, C. C., Turner, J., Ravichandran, M., Anilkumar, N., and Kshitija, S.: Record low sea ice extent in the Weddell Sea, Antarctica in April/May 2019 driven by intense and explosive polar cyclones, npj Clim. Atmos. Sci., 5, 19, https://doi.org/10.1038/s41612-022-00243-9, 2022.
Kusahara, K., Reid, P., Williams, G. D., Massom, R., and Hasumi, H.: An ocean-sea ice model study of the unprecedented Antarctic sea ice minimum in 2016, Environ. Res. Lett., 13, 84020, https://doi.org/10.1088/1748-9326/aad624, 2018.
Kusahara, K., Williams, G. D., Massom, R., Reid, P., and Hasumi, H.: Spatiotemporal dependence of Antarctic sea ice variability to dynamic and thermodynamic forcing: a coupled ocean–sea ice model study, Clim. Dynam., 52, 3791–3807, https://doi.org/10.1007/s00382-018-4348-3, 2019.
Lavergne, T., Sørensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjær, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., and Pedersen, L. T.: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49–78, https://doi.org/10.5194/tc-13-49-2019, 2019.
Lecomte, O., Goosse, H., Fichefet, T., Holland, P. R., Uotila, P., Zunz, V., and Kimura, N.: Impact of surface wind biases on the Antarctic sea ice concentration budget in climate models, Ocean Model., 105, 60–70, https://doi.org/10.1016/j.ocemod.2016.08.001, 2016.
Lee, H.-J. and Jin, E. K.: Understanding the delayed Amundsen Sea low response to ENSO, Front. Earth Sci., 11, https://doi.org/10.3389/feart.2023.1136025, 2023.
Li, X., Cai, W., Meehl, G. A., Chen, D., Yuan, X., Raphael, M., Holland, D. M., Ding, Q., Fogt, R. L., Markle, B. R., Wang, G., Bromwich, D. H., Turner, J., Xie, S.-P., Steig, E. J., Gille, S. T., Xiao, C., Wu, B., Lazzara, M. A., Chen, X., Stammerjohn, S., Holland, P. R., Holland, M. M., Cheng, X., Price, S. F., Wang, Z., Bitz, C. M., Shi, J., Gerber, E. P., Liang, X., Goosse, H., Yoo, C., Ding, M., Geng, L., Xin, M., Li, C., Dou, T., Liu, C., Sun, W., Wang, X., and Song, C.: Tropical teleconnection impacts on Antarctic climate changes, Nat. Rev. Earth Environ., 2, 680–698, https://doi.org/10.1038/s43017-021-00204-5, 2021.
Libera, S., Hobbs, W., Klocker, A., Meyer, A., and Matear, R.: Ocean-Sea Ice Processes and Their Role in Multi-Month Predictability of Antarctic Sea Ice, Geophys. Res. Lett., 49, e2021GL097047, https://doi.org/10.1029/2021gl097047, 2022.
Liu, J., Zhu, Z., and Chen, D.: Lowest Antarctic Sea Ice Record Broken for the Second Year in a Row, Ocean-Land-Atmos. Res., 3, 0007, https://doi.org/10.34133/olar.0007, 2023.
Madec, G., Bourdallé-Badie, R., Bouttier, P.-A., Bricaud, C., Bruciaferri, D., Calvert, D., Chanut, J., Clementi, E., Coward, A., Delrosso, D., Ethé, C., Flavoni, S., Graham, T., Harle, J., Iovino, D., Lea, D., Lévy, C., Lovato, T., Martin, N., Masson, S., Mocavero, S., Paul, J., Rousset, C., Storkey, D., Storto, A., and Vancoppenolle, M.: NEMO ocean engine, Tech. rep., Insitut Pierre-Simon Laplace, Zenodo [code], https://doi.org/10.5281/zenodo.3248739, 2017.
Marchi, S., Fichefet, T., Goosse, H., Zunz, V., Tietsche, S., Day, J. J., and Hawkins, E.: Reemergence of Antarctic sea ice predictability and its link to deep ocean mixing in global climate models, Clim. Dynam., 52, 1–23, https://doi.org/10.1007/s00382-018-4292-2, 2018.
Massonnet, F., Guemas, V., Fuckar, N. S., and Doblas-Reyes, F. J.: The 2014 high record of Antarctic sea ice extent, in: Explaining extreme events of 2014 from a climate perspective, edited by: Herring, S. C., Hoerling, M. P., Kossin, J. P., Peterson, T. C., and Stott, P. A., B. Am. Meteorol. Soc., 96, 163–167, https://doi.org/10.1175/BAMS-D-15-00093.1, 2015.
Mathiot, P. and Storkey, D.: NEMO model code, MetOffice (UK) branch dev_isf_remapping_UKESM_GO6package_r9314, revision 11248, MetOffice [code], https://forge.ipsl.jussieu.fr/nemo/browser/branches/UKMO/dev_isf_remapping_UKESM_GO6package_r9314?rev=15667 (last access: 21 January 2022), 2018.
Meehl, G. A., Arblaster, J. M., Chung, C. T. Y., Holland, M. M., DuVivier, A., Thompson, L. A., Yang, D., and Bitz, C. M.: Sustained ocean changes contributed to sudden Antarctic sea ice retreat in late 2016, Nat. Commun., 10, 14, https://doi.org/10.1038/s41467-018-07865-9, 2019.
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Short summary
We analyze years with extraordinarily low sea ice extent in Antarctica during summer, until the striking record in 2022. We highlight common aspects among these events, such as the fact that the exceptional melting usually occurs in two key regions and that it is related to winds with a similar direction. We also investigate whether the summer conditions are preceded by an unusual state of the sea ice during the previous winter, as well as the physical processes involved.
We analyze years with extraordinarily low sea ice extent in Antarctica during summer, until the...
