Articles | Volume 16, issue 6
https://doi.org/10.5194/tc-16-2565-2022
© Author(s) 2022. 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-16-2565-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Jun 2022
Research article |
| 28 Jun 2022
| 28 Jun 2022
Sea ice floe size: its impact on pan-Arctic and local ice mass and required model complexity
Adam William Bateson
CORRESPONDING AUTHOR
Centre for Polar Observation and Modelling, Department of Meteorology, University of Reading, Reading, RG2 7PS, United Kingdom
Daniel L. Feltham
Centre for Polar Observation and Modelling, Department of Meteorology, University of Reading, Reading, RG2 7PS, United Kingdom
David Schröder
Centre for Polar Observation and Modelling, Department of Meteorology, University of Reading, Reading, RG2 7PS, United Kingdom
British Antarctic Survey, Cambridge, CB3 0ET, United Kingdom
Yanan Wang
School of Applied Sciences, University of Huddersfield, Huddersfield, United Kingdom
Byongjun Hwang
School of Applied Sciences, University of Huddersfield, Huddersfield, United Kingdom
Jeff K. Ridley
Hadley Centre for Climate Prediction and Research, Met Office, Exeter, EX1 3PB, United Kingdom
Yevgeny Aksenov
National Oceanography Centre Southampton, Southampton, SO14 3ZH,
United Kingdom
Related authors
Yanan Wang, Byongjun Hwang, Adam William Bateson, Yevgeny Aksenov, and Christopher Horvat
The Cryosphere, 17, 3575–3591, https://doi.org/10.5194/tc-17-3575-2023, https://doi.org/10.5194/tc-17-3575-2023, 2023
Short summary
Short summary
Sea ice is composed of small, discrete pieces of ice called floes, whose size distribution plays a critical role in the interactions between the sea ice, ocean and atmosphere. This study provides an assessment of sea ice models using new high-resolution floe size distribution observations, revealing considerable differences between them. These findings point not only to the limitations in models but also to the need for more high-resolution observations to validate and calibrate models.
Rebecca Caitlin Frew, Daniel Feltham, David Schroeder, and Adam William Bateson
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-91, https://doi.org/10.5194/tc-2023-91, 2023
Preprint under review for TC
Short summary
Short summary
As summer Arctic sea ice extent has retreated, the marginal ice zone (MIZ) has been widening and making up an increasing percentage of the summer sea ice. The MIZ is projected to become a larger percentage of the summer ice cover, as the Arctic transitions to ice free summers. Using a sea ice model we find that the processes and timing of sea ice loss differ in the MIZ to the rest of the sea cover.
Adam W. Bateson, Daniel L. Feltham, David Schröder, Lucia Hosekova, Jeff K. Ridley, and Yevgeny Aksenov
The Cryosphere, 14, 403–428, https://doi.org/10.5194/tc-14-403-2020, https://doi.org/10.5194/tc-14-403-2020, 2020
Short summary
Short summary
The Arctic sea ice cover has been observed to be decreasing, particularly in summer. We use numerical models to gain insight into processes controlling its seasonal and decadal evolution. Sea ice is made of pieces of ice called floes. Previous models have set these floes to be the same size, which is not supported by observations. In this study we show that accounting for variable floe size reveals the importance of sea ice regions close to the open ocean in driving seasonal retreat of sea ice.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
Short summary
Short summary
This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Viktoria Spaiser, Sirkku Juhola, Sara M. Constantino, Weisi Guo, Tabitha Watson, Jana Sillmann, Alessandro Craparo, Ashleigh Basel, John T. Bruun, Krishna Krishnamurthy, Jürgen Scheffran, Patricia Pinho, Uche T. Okpara, Jonathan F. Donges, Avit Bhowmik, Taha Yasseri, Ricardo Safra de Campos, Graeme S. Cumming, Hugues Chenet, Florian Krampe, Jesse F. Abrams, James G. Dyke, Stefanie Rynders, Yevgeny Aksenov, and Bryan M. Spears
Earth Syst. Dynam., 15, 1179–1206, https://doi.org/10.5194/esd-15-1179-2024, https://doi.org/10.5194/esd-15-1179-2024, 2024
Short summary
Short summary
In this paper, we identify potential negative social tipping points linked to Earth system destabilization and draw on related research to understand the drivers and likelihood of these negative social tipping dynamics, their potential effects on human societies and the Earth system, and the potential for cascading interactions and contribution to systemic risks.
David Storkey, Pierre Mathiot, Michael J. Bell, Dan Copsey, Catherine Guiavarc'h, Helene T. Hewitt, Jeff Ridley, and Malcolm J. Roberts
EGUsphere, https://doi.org/10.5194/egusphere-2024-1414, https://doi.org/10.5194/egusphere-2024-1414, 2024
Short summary
Short summary
The Southern Ocean is a key region of the world ocean in the context of climate change studies. We show that the HadGEM3 coupled model with intermediate ocean resolution struggles to accurately simulate the Southern Ocean. Increasing the frictional drag that the sea floor exerts on ocean currents, and introducing a representation of unresolved ocean eddies both appear to reduce the large-scale biases in this model.
Alexander T. Archibald, Bablu Sinha, Maria Russo, Emily Matthews, Freya Squires, N. Luke Abraham, Stephane Bauguitte, Thomas Bannan, Thomas Bell, David Berry, Lucy Carpenter, Hugh Coe, Andrew Coward, Peter Edwards, Daniel Feltham, Dwayne Heard, Jim Hopkins, James Keeble, Elizabeth C. Kent, Brian King, Isobel R. Lawrence, James Lee, Claire R. Macintosh, Alex Megann, Ben I. Moat, Katie Read, Chris Reed, Malcolm Roberts, Reinhard Schiemann, David Schroeder, Tim Smyth, Loren Temple, Navaneeth Thamban, Lisa Whalley, Simon Williams, Huihui Wu, and Ming-Xi Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-405, https://doi.org/10.5194/essd-2023-405, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Here we present an overview of the data generated as part of the North Atlantic Climate System Integrated Studies (ACSIS) programme which are available through dedicated repositories at the Centre for Environmental Data Analysis (CEDA, www.ceda.ac.uk) and the British Oceanographic Data Centre (BODC, bodc.ac.uk). ACSIS data cover the full North Atlantic System comprising: the North Atlantic Ocean, the atmosphere above it including its composition, Arctic Sea Ice and the Greenland Ice Sheet.
Nico Wunderling, Anna S. von der Heydt, Yevgeny Aksenov, Stephen Barker, Robbin Bastiaansen, Victor Brovkin, Maura Brunetti, Victor Couplet, Thomas Kleinen, Caroline H. Lear, Johannes Lohmann, Rosa Maria Roman-Cuesta, Sacha Sinet, Didier Swingedouw, Ricarda Winkelmann, Pallavi Anand, Jonathan Barichivich, Sebastian Bathiany, Mara Baudena, John T. Bruun, Cristiano M. Chiessi, Helen K. Coxall, David Docquier, Jonathan F. Donges, Swinda K. J. Falkena, Ann Kristin Klose, David Obura, Juan Rocha, Stefanie Rynders, Norman Julius Steinert, and Matteo Willeit
Earth Syst. Dynam., 15, 41–74, https://doi.org/10.5194/esd-15-41-2024, https://doi.org/10.5194/esd-15-41-2024, 2024
Short summary
Short summary
This paper maps out the state-of-the-art literature on interactions between tipping elements relevant for current global warming pathways. We find indications that many of the interactions between tipping elements are destabilizing. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 °C or on shorter timescales if global warming surpasses 2.0 °C.
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.
Christoph Heinze, Thorsten Blenckner, Peter Brown, Friederike Fröb, Anne Morée, Adrian L. New, Cara Nissen, Stefanie Rynders, Isabel Seguro, Yevgeny Aksenov, Yuri Artioli, Timothée Bourgeois, Friedrich Burger, Jonathan Buzan, B. B. Cael, Veli Çağlar Yumruktepe, Melissa Chierici, Christopher Danek, Ulf Dieckmann, Agneta Fransson, Thomas Frölicher, Giovanni Galli, Marion Gehlen, Aridane G. González, Melchor Gonzalez-Davila, Nicolas Gruber, Örjan Gustafsson, Judith Hauck, Mikko Heino, Stephanie Henson, Jenny Hieronymus, I. Emma Huertas, Fatma Jebri, Aurich Jeltsch-Thömmes, Fortunat Joos, Jaideep Joshi, Stephen Kelly, Nandini Menon, Precious Mongwe, Laurent Oziel, Sólveig Ólafsdottir, Julien Palmieri, Fiz F. Pérez, Rajamohanan Pillai Ranith, Juliano Ramanantsoa, Tilla Roy, Dagmara Rusiecka, J. Magdalena Santana Casiano, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Miriam Seifert, Anna Shchiptsova, Bablu Sinha, Christopher Somes, Reiner Steinfeldt, Dandan Tao, Jerry Tjiputra, Adam Ulfsbo, Christoph Völker, Tsuyoshi Wakamatsu, and Ying Ye
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-182, https://doi.org/10.5194/bg-2023-182, 2023
Preprint under review for BG
Short summary
Short summary
For assessing the consequences of human-induced climate change for the marine realm, it is necessary to not only look at gradual changes but also at abrupt changes of environmental conditions. We summarise abrupt changes in ocean warming, acidification, and oxygen concentration as the key environmental factors for ecosystems. Taking these abrupt changes into account requires greenhouse gas emissions to be reduced to a larger extent than previously thought to limit respective damage.
Yanan Wang, Byongjun Hwang, Adam William Bateson, Yevgeny Aksenov, and Christopher Horvat
The Cryosphere, 17, 3575–3591, https://doi.org/10.5194/tc-17-3575-2023, https://doi.org/10.5194/tc-17-3575-2023, 2023
Short summary
Short summary
Sea ice is composed of small, discrete pieces of ice called floes, whose size distribution plays a critical role in the interactions between the sea ice, ocean and atmosphere. This study provides an assessment of sea ice models using new high-resolution floe size distribution observations, revealing considerable differences between them. These findings point not only to the limitations in models but also to the need for more high-resolution observations to validate and calibrate models.
Nicholas Williams, Nicholas Byrne, Daniel Feltham, Peter Jan Van Leeuwen, Ross Bannister, David Schroeder, Andrew Ridout, and Lars Nerger
The Cryosphere, 17, 2509–2532, https://doi.org/10.5194/tc-17-2509-2023, https://doi.org/10.5194/tc-17-2509-2023, 2023
Short summary
Short summary
Observations show that the Arctic sea ice cover has reduced over the last 40 years. This study uses ensemble-based data assimilation in a stand-alone sea ice model to investigate the impacts of assimilating three different kinds of sea ice observation, including the novel assimilation of sea ice thickness distribution. We show that assimilating ice thickness distribution has a positive impact on thickness and volume estimates within the ice pack, especially for very thick ice.
Rebecca Caitlin Frew, Daniel Feltham, David Schroeder, and Adam William Bateson
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-91, https://doi.org/10.5194/tc-2023-91, 2023
Preprint under review for TC
Short summary
Short summary
As summer Arctic sea ice extent has retreated, the marginal ice zone (MIZ) has been widening and making up an increasing percentage of the summer sea ice. The MIZ is projected to become a larger percentage of the summer ice cover, as the Arctic transitions to ice free summers. Using a sea ice model we find that the processes and timing of sea ice loss differ in the MIZ to the rest of the sea cover.
Maria Vittoria Guarino, Louise C. Sime, Rachel Diamond, Jeff Ridley, and David Schroeder
Clim. Past, 19, 865–881, https://doi.org/10.5194/cp-19-865-2023, https://doi.org/10.5194/cp-19-865-2023, 2023
Short summary
Short summary
We investigate the response of the atmosphere, ocean, and ice domains to the release of a large volume of glacial meltwaters thought to have occurred during the Last Interglacial period. We show that the signal that originated in the North Atlantic travels over great distances across the globe. It modifies the ocean gyre circulation in the Northern Hemisphere as well as the belt of westerly winds in the Southern Hemisphere, with consequences for Antarctic sea ice.
Antony Siahaan, Robin S. Smith, Paul R. Holland, Adrian Jenkins, Jonathan M. Gregory, Victoria Lee, Pierre Mathiot, Antony J. Payne, Jeff K. Ridley, and Colin G. Jones
The Cryosphere, 16, 4053–4086, https://doi.org/10.5194/tc-16-4053-2022, https://doi.org/10.5194/tc-16-4053-2022, 2022
Short summary
Short summary
The UK Earth System Model is the first to fully include interactions of the atmosphere and ocean with the Antarctic Ice Sheet. Under the low-greenhouse-gas SSP1–1.9 (Shared Socioeconomic Pathway) scenario, the ice sheet remains stable over the 21st century. Under the strong-greenhouse-gas SSP5–8.5 scenario, the model predicts strong increases in melting of large ice shelves and snow accumulation on the surface. The dominance of accumulation leads to a sea level fall at the end of the century.
Rachel Diamond, Louise C. Sime, David Schroeder, and Maria-Vittoria Guarino
The Cryosphere, 15, 5099–5114, https://doi.org/10.5194/tc-15-5099-2021, https://doi.org/10.5194/tc-15-5099-2021, 2021
Short summary
Short summary
The Hadley Centre Global Environment Model version 3 (HadGEM3) is the first coupled climate model to simulate an ice-free summer Arctic during the Last Interglacial (LIG), 127 000 years ago, and yields accurate Arctic surface temperatures. We investigate the causes and impacts of this extreme simulated ice loss and, in particular, the role of melt ponds.
Amy Solomon, Céline Heuzé, Benjamin Rabe, Sheldon Bacon, Laurent Bertino, Patrick Heimbach, Jun Inoue, Doroteaciro Iovino, Ruth Mottram, Xiangdong Zhang, Yevgeny Aksenov, Ronan McAdam, An Nguyen, Roshin P. Raj, and Han Tang
Ocean Sci., 17, 1081–1102, https://doi.org/10.5194/os-17-1081-2021, https://doi.org/10.5194/os-17-1081-2021, 2021
Short summary
Short summary
Freshwater in the Arctic Ocean plays a critical role in the global climate system by impacting ocean circulations, stratification, mixing, and emergent regimes. In this review paper we assess how Arctic Ocean freshwater changed in the 2010s relative to the 2000s. Estimates from observations and reanalyses show a qualitative stabilization in the 2010s due to a compensation between a freshening of the Beaufort Gyre and a reduction in freshwater in the Amerasian and Eurasian basins.
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
Short summary
Short summary
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.
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.
Rebecca J. Rolph, Daniel L. Feltham, and David Schröder
The Cryosphere, 14, 1971–1984, https://doi.org/10.5194/tc-14-1971-2020, https://doi.org/10.5194/tc-14-1971-2020, 2020
Short summary
Short summary
It is well known that the Arctic sea ice extent is declining, and it is often assumed that the marginal ice zone (MIZ), the area of partial sea ice cover, is consequently increasing. However, we find no trend in the MIZ extent during the last 40 years from observations that is consistent with a widening of the MIZ as it moves northward. Differences of MIZ extent between different satellite retrievals are too large to provide a robust basis to verify model simulations of MIZ extent.
Adam W. Bateson, Daniel L. Feltham, David Schröder, Lucia Hosekova, Jeff K. Ridley, and Yevgeny Aksenov
The Cryosphere, 14, 403–428, https://doi.org/10.5194/tc-14-403-2020, https://doi.org/10.5194/tc-14-403-2020, 2020
Short summary
Short summary
The Arctic sea ice cover has been observed to be decreasing, particularly in summer. We use numerical models to gain insight into processes controlling its seasonal and decadal evolution. Sea ice is made of pieces of ice called floes. Previous models have set these floes to be the same size, which is not supported by observations. In this study we show that accounting for variable floe size reveals the importance of sea ice regions close to the open ocean in driving seasonal retreat of sea ice.
Maria-Vittoria Guarino, Louise C. Sime, David Schroeder, Grenville M. S. Lister, and Rosalyn Hatcher
Geosci. Model Dev., 13, 139–154, https://doi.org/10.5194/gmd-13-139-2020, https://doi.org/10.5194/gmd-13-139-2020, 2020
Short summary
Short summary
When the same weather or climate simulation is run on different high-performance computing (HPC) platforms, model outputs may not be identical for a given initial condition. Here, we investigate the behaviour of the Preindustrial simulation prepared by the UK Met Office for the forthcoming CMIP6 under different computing environments. Discrepancies between the means of key climate variables were analysed at different timescales, from decadal to centennial.
Alex West, Mat Collins, Ed Blockley, Jeff Ridley, and Alejandro Bodas-Salcedo
The Cryosphere, 13, 2001–2022, https://doi.org/10.5194/tc-13-2001-2019, https://doi.org/10.5194/tc-13-2001-2019, 2019
Short summary
Short summary
This study presents a framework for examining the causes of model errors in Arctic sea ice volume, using HadGEM2-ES as a case study. Simple models are used to estimate how much of the error in energy arriving at the ice surface is due to error in key Arctic climate variables. The method quantifies how each variable affects sea ice volume balance and shows that for HadGEM2-ES an annual mean low bias in ice thickness is likely due to errors in surface melt onset.
David Schröder, Danny L. Feltham, Michel Tsamados, Andy Ridout, and Rachel Tilling
The Cryosphere, 13, 125–139, https://doi.org/10.5194/tc-13-125-2019, https://doi.org/10.5194/tc-13-125-2019, 2019
Short summary
Short summary
This paper uses sea ice thickness data (CryoSat-2) to identify and correct shortcomings in simulating winter ice growth in the widely used sea ice model CICE. Adding a model of snow drift and using a different scheme for calculating the ice conductivity improve model results. Sensitivity studies demonstrate that atmospheric winter conditions have little impact on winter ice growth, and the fate of Arctic summer sea ice is largely controlled by atmospheric conditions during the melting season.
Sammie Buzzard, Daniel Feltham, and Daniela Flocco
The Cryosphere, 12, 3565–3575, https://doi.org/10.5194/tc-12-3565-2018, https://doi.org/10.5194/tc-12-3565-2018, 2018
Short summary
Short summary
Surface lakes on ice shelves can not only change the amount of solar energy the ice shelf receives, but may also play a pivotal role in sudden ice shelf collapse such as that of the Larsen B Ice Shelf in 2002.
Here we simulate current and future melting on Larsen C, Antarctica’s most northern ice shelf and one on which lakes have been observed. We find that should future lakes occur closer to the ice shelf front, they may contain sufficient meltwater to contribute to ice shelf instability.
Jeff K. Ridley and Edward W. Blockley
The Cryosphere, 12, 3355–3360, https://doi.org/10.5194/tc-12-3355-2018, https://doi.org/10.5194/tc-12-3355-2018, 2018
Short summary
Short summary
The climate change conference held in Paris in 2016 made a commitment to limiting global-mean warming since the pre-industrial era to well below 2 °C and to pursue efforts to limit the warming to 1.5 °C. Since global warming is already at 1 °C, the 1.5 °C can only be achieved at considerable cost. It is thus important to assess the risks associated with the higher target. This paper shows that the decline of Arctic sea ice, and associated impacts, can only be halted with the 1.5 °C target.
David Storkey, Adam T. Blaker, Pierre Mathiot, Alex Megann, Yevgeny Aksenov, Edward W. Blockley, Daley Calvert, Tim Graham, Helene T. Hewitt, Patrick Hyder, Till Kuhlbrodt, Jamie G. L. Rae, and Bablu Sinha
Geosci. Model Dev., 11, 3187–3213, https://doi.org/10.5194/gmd-11-3187-2018, https://doi.org/10.5194/gmd-11-3187-2018, 2018
Short summary
Short summary
We document the latest version of the shared UK global configuration of the
NEMO ocean model. This configuration will be used as part of the climate
models for the UK contribution to the IPCC 6th Assessment Report.
30-year integrations forced with atmospheric forcing show that the new
configurations have an improved simulation in the Southern Ocean with the
near-surface temperatures and salinities and the sea ice all matching the
observations more closely.
Julienne C. Stroeve, David Schroder, Michel Tsamados, and Daniel Feltham
The Cryosphere, 12, 1791–1809, https://doi.org/10.5194/tc-12-1791-2018, https://doi.org/10.5194/tc-12-1791-2018, 2018
Short summary
Short summary
This paper looks at the impact of the warm winter and anomalously low number of total freezing degree days during winter 2016/2017 on thermodynamic ice growth and overall thickness anomalies. The approach relies on evaluation of satellite data (CryoSat-2) and model output. While there is a negative feedback between rapid ice growth for thin ice, with thermodynamic ice growth increasing over time, since 2012 that relationship is changing, in part because the freeze-up is happening later.
Fabrice Ardhuin, Yevgueny Aksenov, Alvise Benetazzo, Laurent Bertino, Peter Brandt, Eric Caubet, Bertrand Chapron, Fabrice Collard, Sophie Cravatte, Jean-Marc Delouis, Frederic Dias, Gérald Dibarboure, Lucile Gaultier, Johnny Johannessen, Anton Korosov, Georgy Manucharyan, Dimitris Menemenlis, Melisa Menendez, Goulven Monnier, Alexis Mouche, Frédéric Nouguier, George Nurser, Pierre Rampal, Ad Reniers, Ernesto Rodriguez, Justin Stopa, Céline Tison, Clément Ubelmann, Erik van Sebille, and Jiping Xie
Ocean Sci., 14, 337–354, https://doi.org/10.5194/os-14-337-2018, https://doi.org/10.5194/os-14-337-2018, 2018
Short summary
Short summary
The Sea surface KInematics Multiscale (SKIM) monitoring mission is a proposal for a future satellite that is designed to measure ocean currents and waves. Using a Doppler radar, the accurate measurement of currents requires the removal of the mean velocity due to ocean wave motions. This paper describes the main processing steps needed to produce currents and wave data from the radar measurements. With this technique, SKIM can provide unprecedented coverage and resolution, over the global ocean.
Jeff K. Ridley, Edward W. Blockley, Ann B. Keen, Jamie G. L. Rae, Alex E. West, and David Schroeder
Geosci. Model Dev., 11, 713–723, https://doi.org/10.5194/gmd-11-713-2018, https://doi.org/10.5194/gmd-11-713-2018, 2018
Short summary
Short summary
The sea ice component of the Met Office coupled climate model, HadGEM3-GC3.1, is presented and evaluated. We determine that the mean state of the sea ice is well reproduced for the Arctic; however, a warm sea surface temperature bias over the Southern Ocean results in a low Antarctic sea ice cover.
Jamie G. L. Rae, Alexander D. Todd, Edward W. Blockley, and Jeff K. Ridley
The Cryosphere, 11, 3023–3034, https://doi.org/10.5194/tc-11-3023-2017, https://doi.org/10.5194/tc-11-3023-2017, 2017
Short summary
Short summary
Several studies have highlighted links between Arctic summer storms and September sea ice extent in observations. Here we use model and reanalysis data to investigate the sensitivity of such links to the analytical methods used, in order to determine their robustness. The links were found to depend on the resolution of the model and dataset, the method used to identify storms and the time period used in the analysis. We therefore recommend caution when interpreting the results of such studies.
Alek A. Petty, Michel C. Tsamados, Nathan T. Kurtz, Sinead L. Farrell, Thomas Newman, Jeremy P. Harbeck, Daniel L. Feltham, and Jackie A. Richter-Menge
The Cryosphere, 10, 1161–1179, https://doi.org/10.5194/tc-10-1161-2016, https://doi.org/10.5194/tc-10-1161-2016, 2016
Short summary
Short summary
This study presents an analysis of Arctic sea ice topography using high-resolution, three-dimensional surface elevation data from the Airborne Topographic Mapper (ATM) laser altimeter, flown as part of NASA's Operation IceBridge mission. We describe and implement a newly developed sea ice surface feature-picking algorithm and derive novel information regarding the height, volume and geometry of surface features over the western Arctic sea ice cover.
Daniela Flocco, Daniel L. Feltham, David Schroeder, and Michel Tsamados
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-118, https://doi.org/10.5194/tc-2016-118, 2016
Preprint withdrawn
Short summary
Short summary
Melt ponds form over the sea ice cover in the Arctic and impact the surface albedo inducing a positive feedback leading to further melting.
While they refreeze, ponds delay basal sea ice growth in Autumn impacting the internal sea ice temperature and therefore its basal growth rate. By using a numerical model we estimate an inhibited basal growth of up to 228 km3, which represents 25 % of the basal sea ice growth estimated by PIOMAS during the months of September and October.
J. K. Ridley, R. A. Wood, A. B. Keen, E. Blockley, and J. A. Lowe
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-28, https://doi.org/10.5194/tc-2016-28, 2016
Revised manuscript has not been submitted
Short summary
Short summary
The internal variability in model projections of Arctic sea ice extent is high. As a consequence an ensemble of projections from a single model can show considerable scatter in the range of dates for an "ice-free" Arctic. This paper investigates if the scatter can be reduced for a variety of definitions of "ice-free". Daily GCM data reveals that only a high emissions scenario results in the optimal definition of five conservative years in with ice extent is below one million square kilometer.
C. Heuzé, J. K. Ridley, D. Calvert, D. P. Stevens, and K. J. Heywood
Geosci. Model Dev., 8, 3119–3130, https://doi.org/10.5194/gmd-8-3119-2015, https://doi.org/10.5194/gmd-8-3119-2015, 2015
Short summary
Short summary
Most ocean models, including NEMO, have unrealistic Southern Ocean deep convection. That is, through extensive areas of the Southern Ocean, they exhibit convection from the surface of the ocean to the sea floor. We find this convection to be an issue as it impacts the whole ocean circulation, notably strengthening the Antarctic Circumpolar Current. Using sensitivity experiments, we show that counter-intuitively the vertical mixing needs to be enhanced to reduce this spurious convection.
J. G. L. Rae, H. T. Hewitt, A. B. Keen, J. K. Ridley, A. E. West, C. M. Harris, E. C. Hunke, and D. N. Walters
Geosci. Model Dev., 8, 2221–2230, https://doi.org/10.5194/gmd-8-2221-2015, https://doi.org/10.5194/gmd-8-2221-2015, 2015
Short summary
Short summary
The paper presents a new sea ice configuration, GSI6.0, in the Met Office coupled atmosphere-ocean-ice model. Differences in the sea ice from a previous configuration (GSI4.0) are explained in the context of a previously published sensitivity study. In summer, Arctic sea ice is thicker and more extensive than in GSI4.0, bringing it closer to the observationally derived data sets. In winter, the Arctic ice is thicker but less extensive than in GSI4.0.
R. Marsh, V. O. Ivchenko, N. Skliris, S. Alderson, G. R. Bigg, G. Madec, A. T. Blaker, Y. Aksenov, B. Sinha, A. C. Coward, J. Le Sommer, N. Merino, and V. B. Zalesny
Geosci. Model Dev., 8, 1547–1562, https://doi.org/10.5194/gmd-8-1547-2015, https://doi.org/10.5194/gmd-8-1547-2015, 2015
Short summary
Short summary
Calved icebergs account for around 50% of total freshwater input to the ocean from the Greenland and Antarctic ice sheets. As they melt, icebergs interact with the ocean. We have developed and tested interactive icebergs in a state-of-the-art global ocean model, showing how sea ice, temperatures, and currents are disturbed by iceberg melting. With this new model capability, we are better prepared to predict how future increases in iceberg numbers might influence the oceans and climate.
I. A. Dmitrenko, S. A. Kirillov, N. Serra, N. V. Koldunov, V. V. Ivanov, U. Schauer, I. V. Polyakov, D. Barber, M. Janout, V. S. Lien, M. Makhotin, and Y. Aksenov
Ocean Sci., 10, 719–730, https://doi.org/10.5194/os-10-719-2014, https://doi.org/10.5194/os-10-719-2014, 2014
T. Howard, A. K. Pardaens, J. L. Bamber, J. Ridley, G. Spada, R. T. W. L. Hurkmans, J. A. Lowe, and D. Vaughan
Ocean Sci., 10, 473–483, https://doi.org/10.5194/os-10-473-2014, https://doi.org/10.5194/os-10-473-2014, 2014
T. Howard, J. Ridley, A. K. Pardaens, R. T. W. L. Hurkmans, A. J. Payne, R. H. Giesen, J. A. Lowe, J. L. Bamber, T. L. Edwards, and J. Oerlemans
Ocean Sci., 10, 485–500, https://doi.org/10.5194/os-10-485-2014, https://doi.org/10.5194/os-10-485-2014, 2014
A. Megann, D. Storkey, Y. Aksenov, S. Alderson, D. Calvert, T. Graham, P. Hyder, J. Siddorn, and B. Sinha
Geosci. Model Dev., 7, 1069–1092, https://doi.org/10.5194/gmd-7-1069-2014, https://doi.org/10.5194/gmd-7-1069-2014, 2014
A. A. Petty, P. R. Holland, and D. L. Feltham
The Cryosphere, 8, 761–783, https://doi.org/10.5194/tc-8-761-2014, https://doi.org/10.5194/tc-8-761-2014, 2014
F. Wobus, G. I. Shapiro, J. M. Huthnance, M. A. M. Maqueda, and Y. Aksenov
Ocean Sci., 9, 885–899, https://doi.org/10.5194/os-9-885-2013, https://doi.org/10.5194/os-9-885-2013, 2013
Related subject area
Discipline: Sea ice | Subject: Numerical Modelling
How many parameters are needed to represent polar sea ice surface patterns and heterogeneity?
Exploring non-Gaussian sea ice characteristics via observing system simulation experiments
Past and future of the Arctic sea ice in High-Resolution Model Intercomparison Project (HighResMIP) climate models
Data-driven surrogate modeling of high-resolution sea-ice thickness in the Arctic
Using Icepack to reproduce ice mass balance buoy observations in landfast ice: improvements from the mushy-layer thermodynamics
Understanding the influence of ocean waves on Arctic sea ice simulation: a modeling study with an atmosphere–ocean–wave–sea ice coupled model
Sea ice cover in the Copernicus Arctic Regional Reanalysis
Smoothed particle hydrodynamics implementation of the standard viscous–plastic sea-ice model and validation in simple idealized experiments
Phase-field models of floe fracture in sea ice
The effect of partial dissolution on sea-ice chemical transport: a combined model–observational study using poly- and perfluoroalkylated substances (PFASs)
Deep learning subgrid-scale parametrisations for short-term forecasting of sea-ice dynamics with a Maxwell elasto-brittle rheology
Modelling ice mélange based on the viscous-plastic sea-ice rheology
Impact of atmospheric forcing uncertainties on Arctic and Antarctic sea ice simulations in CMIP6 OMIP models
Arctic sea ice mass balance in a new coupled ice–ocean model using a brittle rheology framework
Wave-triggered breakup in the marginal ice zone generates lognormal floe size distributions: a simulation study
Exploring the capabilities of electrical resistivity tomography to study subsea permafrost
A probabilistic seabed–ice keel interaction model
The effect of changing sea ice on wave climate trends along Alaska's central Beaufort Sea coast
Arctic sea ice anomalies during the MOSAiC winter 2019/20
Edge displacement scores
Toward a method for downscaling sea ice pressure for navigation purposes
The Arctic Ocean Observation Operator for 6.9 GHz (ARC3O) – Part 1: How to obtain sea ice brightness temperatures at 6.9 GHz from climate model output
The Arctic Ocean Observation Operator for 6.9 GHz (ARC3O) – Part 2: Development and evaluation
Feature-based comparison of sea ice deformation in lead-permitting sea ice simulations
Wave energy attenuation in fields of colliding ice floes – Part 1: Discrete-element modelling of dissipation due to ice–water drag
Validation of the sea ice surface albedo scheme of the regional climate model HIRHAM–NAOSIM using aircraft measurements during the ACLOUD/PASCAL campaigns
Simulating intersection angles between conjugate faults in sea ice with different viscous–plastic rheologies
IcePAC – a probabilistic tool to study sea ice spatio-temporal dynamics: application to the Hudson Bay area
New insight from CryoSat-2 sea ice thickness for sea ice modelling
Investigating future changes in the volume budget of the Arctic sea ice in a coupled climate model
Medium-range predictability of early summer sea ice thickness distribution in the East Siberian Sea based on the TOPAZ4 ice–ocean data assimilation system
Joseph Fogarty, Elie Bou-Zeid, Mitchell Bushuk, and Linette Boisvert
The Cryosphere, 18, 4335–4354, https://doi.org/10.5194/tc-18-4335-2024, https://doi.org/10.5194/tc-18-4335-2024, 2024
Short summary
Short summary
We hypothesize that using a broad set of surface characterization metrics for polar sea ice surfaces will lead to more accurate representations in general circulation models. However, the first step is to identify the minimum set of metrics required. We show via numerical simulations that sea ice surface patterns can play a crucial role in determining boundary layer structures. We then statistically analyze a set of high-resolution sea ice surface images to obtain this minimal set of parameters.
Christopher Riedel and Jeffrey Anderson
The Cryosphere, 18, 2875–2896, https://doi.org/10.5194/tc-18-2875-2024, https://doi.org/10.5194/tc-18-2875-2024, 2024
Short summary
Short summary
Accurate sea ice conditions are crucial for quality sea ice projections, which have been connected to rapid warming over the Arctic. Knowing which observations to assimilate into models will help produce more accurate sea ice conditions. We found that not assimilating sea ice concentration led to more accurate sea ice states. The methods typically used to assimilate observations in our models apply assumptions to variables that are not well suited for sea ice because they are bounded variables.
Julia Selivanova, Doroteaciro Iovino, and Francesco Cocetta
The Cryosphere, 18, 2739–2763, https://doi.org/10.5194/tc-18-2739-2024, https://doi.org/10.5194/tc-18-2739-2024, 2024
Short summary
Short summary
Climate models show differences in sea ice representation in comparison to observations. Increasing the model resolution is a recognized way to improve model realism and obtain more reliable future projections. We find no strong impact of resolution on sea ice representation; it rather depends on the analysed variable and the model used. By 2050, the marginal ice zone (MIZ) becomes a dominant feature of the Arctic ice cover, suggesting a shift to a new regime similar to that in Antarctica.
Charlotte Durand, Tobias Sebastian Finn, Alban Farchi, Marc Bocquet, Guillaume Boutin, and Einar Ólason
The Cryosphere, 18, 1791–1815, https://doi.org/10.5194/tc-18-1791-2024, https://doi.org/10.5194/tc-18-1791-2024, 2024
Short summary
Short summary
This paper focuses on predicting Arctic-wide sea-ice thickness using surrogate modeling with deep learning. The model has a predictive power of 12 h up to 6 months. For this forecast horizon, persistence and daily climatology are systematically outperformed, a result of learned thermodynamics and advection. Consequently, surrogate modeling with deep learning proves to be effective at capturing the complex behavior of sea ice.
Mathieu Plante, Jean-François Lemieux, L. Bruno Tremblay, Adrienne Tivy, Joey Angnatok, François Roy, Gregory Smith, Frédéric Dupont, and Adrian K. Turner
The Cryosphere, 18, 1685–1708, https://doi.org/10.5194/tc-18-1685-2024, https://doi.org/10.5194/tc-18-1685-2024, 2024
Short summary
Short summary
We use a sea ice model to reproduce ice growth observations from two buoys deployed on coastal sea ice and analyze the improvements brought by new physics that represent the presence of saline liquid water in the ice interior. We find that the new physics with default parameters degrade the model performance, with overly rapid ice growth and overly early snow flooding on top of the ice. The performance is largely improved by simple modifications to the ice growth and snow-flooding algorithms.
Chao-Yuan Yang, Jiping Liu, and Dake Chen
The Cryosphere, 18, 1215–1239, https://doi.org/10.5194/tc-18-1215-2024, https://doi.org/10.5194/tc-18-1215-2024, 2024
Short summary
Short summary
We present a new atmosphere–ocean–wave–sea ice coupled model to study the influences of ocean waves on Arctic sea ice simulation. Our results show (1) smaller ice-floe size with wave breaking increases ice melt, (2) the responses in the atmosphere and ocean to smaller floe size partially reduce the effect of the enhanced ice melt, (3) the limited oceanic energy is a strong constraint for ice melt enhancement, and (4) ocean waves can indirectly affect sea ice through the atmosphere and the ocean.
Yurii Batrak, Bin Cheng, and Viivi Kallio-Myers
The Cryosphere, 18, 1157–1183, https://doi.org/10.5194/tc-18-1157-2024, https://doi.org/10.5194/tc-18-1157-2024, 2024
Short summary
Short summary
Atmospheric reanalyses provide consistent series of atmospheric and surface parameters in a convenient gridded form. In this paper, we study the quality of sea ice in a recently released regional reanalysis and assess its added value compared to a global reanalysis. We show that the regional reanalysis, having a more complex sea ice model, gives an improved representation of sea ice, although there are limitations indicating potential benefits in using more advanced approaches in the future.
Oreste Marquis, Bruno Tremblay, Jean-François Lemieux, and Mohammed Islam
The Cryosphere, 18, 1013–1032, https://doi.org/10.5194/tc-18-1013-2024, https://doi.org/10.5194/tc-18-1013-2024, 2024
Short summary
Short summary
We developed a standard viscous–plastic sea-ice model based on the numerical framework called smoothed particle hydrodynamics. The model conforms to the theory within an error of 1 % in an idealized ridging experiment, and it is able to simulate stable ice arches. However, the method creates a dispersive plastic wave speed. The framework is efficient to simulate fractures and can take full advantage of parallelization, making it a good candidate to investigate sea-ice material properties.
Huy Dinh, Dimitrios Giannakis, Joanna Slawinska, and Georg Stadler
The Cryosphere, 17, 3883–3893, https://doi.org/10.5194/tc-17-3883-2023, https://doi.org/10.5194/tc-17-3883-2023, 2023
Short summary
Short summary
We develop a numerical method to simulate the fracture in kilometer-sized chunks of floating ice in the ocean. Our approach uses a mathematical model that balances deformation energy against the energy required for fracture. We study the strength of ice chunks that contain random impurities due to prior damage or refreezing and what types of fractures are likely to occur. Our model shows that crack direction critically depends on the orientation of impurities relative to surrounding forces.
Max Thomas, Briana Cate, Jack Garnett, Inga J. Smith, Martin Vancoppenolle, and Crispin Halsall
The Cryosphere, 17, 3193–3201, https://doi.org/10.5194/tc-17-3193-2023, https://doi.org/10.5194/tc-17-3193-2023, 2023
Short summary
Short summary
A recent study showed that pollutants can be enriched in growing sea ice beyond what we would expect from a perfectly dissolved chemical. We hypothesise that this effect is caused by the specific properties of the pollutants working in combination with fluid moving through the sea ice. To test our hypothesis, we replicate this behaviour in a sea-ice model and show that this type of modelling can be applied to predicting the transport of chemicals with complex behaviour in sea ice.
Tobias Sebastian Finn, Charlotte Durand, Alban Farchi, Marc Bocquet, Yumeng Chen, Alberto Carrassi, and Véronique Dansereau
The Cryosphere, 17, 2965–2991, https://doi.org/10.5194/tc-17-2965-2023, https://doi.org/10.5194/tc-17-2965-2023, 2023
Short summary
Short summary
We combine deep learning with a regional sea-ice model to correct model errors in the sea-ice dynamics of low-resolution forecasts towards high-resolution simulations. The combined model improves the forecast by up to 75 % and thereby surpasses the performance of persistence. As the error connection can additionally be used to analyse the shortcomings of the forecasts, this study highlights the potential of combined modelling for short-term sea-ice forecasting.
Saskia Kahl, Carolin Mehlmann, and Dirk Notz
EGUsphere, https://doi.org/10.5194/egusphere-2023-982, https://doi.org/10.5194/egusphere-2023-982, 2023
Short summary
Short summary
Ice mélange is a mixture of sea ice and icebergs, which can have a strong influence on the sea-ice-ocean interaction. So far, ice mélange is not represented in climate models. We include icebergs into the most used sea-ice model by modifying the mathematical equations that describe the material law of sea ice. We show with three test cases that the modification is necessary to represent icebergs. Furthermore we suggest a numerical method to solve the ice mélange equations computational efficient.
Xia Lin, François Massonnet, Thierry Fichefet, and Martin Vancoppenolle
The Cryosphere, 17, 1935–1965, https://doi.org/10.5194/tc-17-1935-2023, https://doi.org/10.5194/tc-17-1935-2023, 2023
Short summary
Short summary
This study provides clues on how improved atmospheric reanalysis products influence sea ice simulations in ocean–sea ice models. The summer ice concentration simulation in both hemispheres can be improved with changed surface heat fluxes. The winter Antarctic ice concentration and the Arctic drift speed near the ice edge and the ice velocity direction simulations are improved with changed wind stress. The radiation fluxes and winds in atmospheric reanalyses are crucial for sea ice simulations.
Guillaume Boutin, Einar Ólason, Pierre Rampal, Heather Regan, Camille Lique, Claude Talandier, Laurent Brodeau, and Robert Ricker
The Cryosphere, 17, 617–638, https://doi.org/10.5194/tc-17-617-2023, https://doi.org/10.5194/tc-17-617-2023, 2023
Short summary
Short summary
Sea ice cover in the Arctic is full of cracks, which we call leads. We suspect that these leads play a role for atmosphere–ocean interactions in polar regions, but their importance remains challenging to estimate. We use a new ocean–sea ice model with an original way of representing sea ice dynamics to estimate their impact on winter sea ice production. This model successfully represents sea ice evolution from 2000 to 2018, and we find that about 30 % of ice production takes place in leads.
Nicolas Guillaume Alexandre Mokus and Fabien Montiel
The Cryosphere, 16, 4447–4472, https://doi.org/10.5194/tc-16-4447-2022, https://doi.org/10.5194/tc-16-4447-2022, 2022
Short summary
Short summary
On the fringes of polar oceans, sea ice is easily broken by waves. As small pieces of ice, or floes, are more easily melted by the warming waters than a continuous ice cover, it is important to incorporate these floe sizes in climate models. These models simulate climate evolution at the century scale and are built by combining specialised modules. We study the statistical distribution of floe sizes under the impact of waves to better understand how to connect sea ice modules to wave modules.
Mauricio Arboleda-Zapata, Michael Angelopoulos, Pier Paul Overduin, Guido Grosse, Benjamin M. Jones, and Jens Tronicke
The Cryosphere, 16, 4423–4445, https://doi.org/10.5194/tc-16-4423-2022, https://doi.org/10.5194/tc-16-4423-2022, 2022
Short summary
Short summary
We demonstrate how we can reliably estimate the thawed–frozen permafrost interface with its associated uncertainties in subsea permafrost environments using 2D electrical resistivity tomography (ERT) data. In addition, we show how further analyses considering 1D inversion and sensitivity assessments can help quantify and better understand 2D ERT inversion results. Our results illustrate the capabilities of the ERT method to get insights into the development of the subsea permafrost.
Frédéric Dupont, Dany Dumont, Jean-François Lemieux, Elie Dumas-Lefebvre, and Alain Caya
The Cryosphere, 16, 1963–1977, https://doi.org/10.5194/tc-16-1963-2022, https://doi.org/10.5194/tc-16-1963-2022, 2022
Short summary
Short summary
In some shallow seas, grounded ice ridges contribute to stabilizing and maintaining a landfast ice cover. A scheme has already proposed where the keel thickness varies linearly with the mean thickness. Here, we extend the approach by taking into account the ice thickness and bathymetry distributions. The probabilistic approach shows a reasonably good agreement with observations and previous grounding scheme while potentially offering more physical insights into the formation of landfast ice.
Kees Nederhoff, Li Erikson, Anita Engelstad, Peter Bieniek, and Jeremy Kasper
The Cryosphere, 16, 1609–1629, https://doi.org/10.5194/tc-16-1609-2022, https://doi.org/10.5194/tc-16-1609-2022, 2022
Short summary
Short summary
Diminishing sea ice is impacting waves across the Arctic region. Recent work shows the effect of the sea ice on offshore waves; however, effects within the nearshore are less known. This study characterizes the wave climate in the central Beaufort Sea coast of Alaska. We show that the reduction of sea ice correlates strongly with increases in the average and extreme waves. However, found trends deviate from offshore, since part of the increase in energy is dissipated before reaching the shore.
Klaus Dethloff, Wieslaw Maslowski, Stefan Hendricks, Younjoo J. Lee, Helge F. Goessling, Thomas Krumpen, Christian Haas, Dörthe Handorf, Robert Ricker, Vladimir Bessonov, John J. Cassano, Jaclyn Clement Kinney, Robert Osinski, Markus Rex, Annette Rinke, Julia Sokolova, and Anja Sommerfeld
The Cryosphere, 16, 981–1005, https://doi.org/10.5194/tc-16-981-2022, https://doi.org/10.5194/tc-16-981-2022, 2022
Short summary
Short summary
Sea ice thickness anomalies during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) winter in January, February and March 2020 were simulated with the coupled Regional Arctic climate System Model (RASM) and compared with CryoSat-2/SMOS satellite data. Hindcast and ensemble simulations indicate that the sea ice anomalies are driven by nonlinear interactions between ice growth processes and wind-driven sea-ice transports, with dynamics playing a dominant role.
Arne Melsom
The Cryosphere, 15, 3785–3796, https://doi.org/10.5194/tc-15-3785-2021, https://doi.org/10.5194/tc-15-3785-2021, 2021
Short summary
Short summary
This study presents new methods to assess how well observations of sea ice expansion are reproduced by results from models. The aim is to provide information about the quality of forecasts for changes in the sea ice extent to operators in or near ice-infested waters. A test using 2 years of model results demonstrates the practical applicability and usefulness of the methods that are presented.
Jean-François Lemieux, L. Bruno Tremblay, and Mathieu Plante
The Cryosphere, 14, 3465–3478, https://doi.org/10.5194/tc-14-3465-2020, https://doi.org/10.5194/tc-14-3465-2020, 2020
Short summary
Short summary
Sea ice pressure poses great risk for navigation; it can lead to ship besetting and damages. Sea ice forecasting systems can predict the evolution of pressure. However, these systems have low spatial resolution (a few km) compared to the dimensions of ships. We study the downscaling of pressure from the km-scale to scales relevant for navigation. We find that the pressure applied on a ship beset in heavy ice conditions can be markedly larger than the pressure predicted by the forecasting system.
Clara Burgard, Dirk Notz, Leif T. Pedersen, and Rasmus T. Tonboe
The Cryosphere, 14, 2369–2386, https://doi.org/10.5194/tc-14-2369-2020, https://doi.org/10.5194/tc-14-2369-2020, 2020
Short summary
Short summary
The high disagreement between observations of Arctic sea ice makes it difficult to evaluate climate models with observations. We investigate the possibility of translating the model state into what a satellite could observe. We find that we do not need complex information about the vertical distribution of temperature and salinity inside the ice but instead are able to assume simplified distributions to reasonably translate the simulated sea ice into satellite
language.
Clara Burgard, Dirk Notz, Leif T. Pedersen, and Rasmus T. Tonboe
The Cryosphere, 14, 2387–2407, https://doi.org/10.5194/tc-14-2387-2020, https://doi.org/10.5194/tc-14-2387-2020, 2020
Short summary
Short summary
The high disagreement between observations of Arctic sea ice inhibits the evaluation of climate models with observations. We develop a tool that translates the simulated Arctic Ocean state into what a satellite could observe from space in the form of brightness temperatures, a measure for the radiation emitted by the surface. We find that the simulated brightness temperatures compare well with the observed brightness temperatures. This tool brings a new perspective for climate model evaluation.
Nils Hutter and Martin Losch
The Cryosphere, 14, 93–113, https://doi.org/10.5194/tc-14-93-2020, https://doi.org/10.5194/tc-14-93-2020, 2020
Short summary
Short summary
Sea ice is composed of a multitude of floes that constantly deform due to wind and ocean currents and thereby form leads and pressure ridges. These features are visible in the ice as stripes of open-ocean or high-piled ice. High-resolution sea ice models start to resolve these deformation features. In this paper we present two simulations that agree with satellite data according to a new evaluation metric that detects deformation features and compares their spatial and temporal characteristics.
Agnieszka Herman, Sukun Cheng, and Hayley H. Shen
The Cryosphere, 13, 2887–2900, https://doi.org/10.5194/tc-13-2887-2019, https://doi.org/10.5194/tc-13-2887-2019, 2019
Short summary
Short summary
Sea ice interactions with waves are extensively studied in recent years, but mechanisms leading to wave energy attenuation in sea ice remain poorly understood. Close to the ice edge, processes contributing to dissipation include collisions between ice floes and turbulence generated under the ice due to velocity differences between ice and water. This paper analyses details of those processes both theoretically and by means of a numerical model.
Evelyn Jäkel, Johannes Stapf, Manfred Wendisch, Marcel Nicolaus, Wolfgang Dorn, and Annette Rinke
The Cryosphere, 13, 1695–1708, https://doi.org/10.5194/tc-13-1695-2019, https://doi.org/10.5194/tc-13-1695-2019, 2019
Short summary
Short summary
The sea ice surface albedo parameterization of a coupled regional climate model was validated against aircraft measurements performed in May–June 2017 north of Svalbard. The albedo parameterization was run offline from the model using the measured parameters surface temperature and snow depth to calculate the surface albedo and the individual fractions of the ice surface subtypes. An adjustment of the variables and additionally accounting for cloud cover reduced the root-mean-squared error.
Damien Ringeisen, Martin Losch, L. Bruno Tremblay, and Nils Hutter
The Cryosphere, 13, 1167–1186, https://doi.org/10.5194/tc-13-1167-2019, https://doi.org/10.5194/tc-13-1167-2019, 2019
Short summary
Short summary
We study the creation of fracture in sea ice plastic models. To do this, we compress an ideal piece of ice of 8 km by 25 km. We use two different mathematical expressions defining the resistance of ice. We find that the most common one is unable to model the fracture correctly, while the other gives better results but brings instabilities. The results are often in opposition with ice granular nature (e.g., sand) and call for changes in ice modeling.
Charles Gignac, Monique Bernier, and Karem Chokmani
The Cryosphere, 13, 451–468, https://doi.org/10.5194/tc-13-451-2019, https://doi.org/10.5194/tc-13-451-2019, 2019
Short summary
Short summary
The IcePAC tool is made to estimate the probabilities of specific sea ice conditions based on historical sea ice concentration time series from the EUMETSAT OSI-409 product (12.5 km grid), modelled using the beta distribution and used to build event probability maps, which have been unavailable until now. Compared to the Canadian ice service atlas, IcePAC showed promising results in the Hudson Bay, paving the way for its usage in other regions of the cryosphere to inform stakeholders' decisions.
David Schröder, Danny L. Feltham, Michel Tsamados, Andy Ridout, and Rachel Tilling
The Cryosphere, 13, 125–139, https://doi.org/10.5194/tc-13-125-2019, https://doi.org/10.5194/tc-13-125-2019, 2019
Short summary
Short summary
This paper uses sea ice thickness data (CryoSat-2) to identify and correct shortcomings in simulating winter ice growth in the widely used sea ice model CICE. Adding a model of snow drift and using a different scheme for calculating the ice conductivity improve model results. Sensitivity studies demonstrate that atmospheric winter conditions have little impact on winter ice growth, and the fate of Arctic summer sea ice is largely controlled by atmospheric conditions during the melting season.
Ann Keen and Ed Blockley
The Cryosphere, 12, 2855–2868, https://doi.org/10.5194/tc-12-2855-2018, https://doi.org/10.5194/tc-12-2855-2018, 2018
Short summary
Short summary
As the climate warms during the 21st century, our model shows extra melting at the top and the base of the Arctic sea ice. The reducing ice cover affects the impact these processes have on the sea ice volume budget, where the largest individual change is a reduction in the amount of growth at the base of existing ice. Using different forcing scenarios we show that, for this model, changes in the volume budget depend on the evolving ice area but not on the speed at which the ice area declines.
Takuya Nakanowatari, Jun Inoue, Kazutoshi Sato, Laurent Bertino, Jiping Xie, Mio Matsueda, Akio Yamagami, Takeshi Sugimura, Hironori Yabuki, and Natsuhiko Otsuka
The Cryosphere, 12, 2005–2020, https://doi.org/10.5194/tc-12-2005-2018, https://doi.org/10.5194/tc-12-2005-2018, 2018
Short summary
Short summary
Medium-range predictability of early summer sea ice thickness in the East Siberian Sea was examined, based on TOPAZ4 forecast data. Statistical examination indicates that the estimate drops abruptly at 4 days, which is related to dynamical process controlled by synoptic-scale atmospheric fluctuations such as an Arctic cyclone. For longer lead times (> 4 days), the thermodynamic melting process takes over, which represents most of the remaining prediction.
Cited articles
Aksenov, Y., Popova, E. E., Yool, A., Nurser, A. J. G., Williams, T. D.,
Bertino, L., and Bergh, J.: On the future navigability of Arctic sea routes:
High-resolution projections of the Arctic Ocean and sea ice, Mar. Policy,
75, 300–317, https://doi.org/10.1016/j.marpol.2015.12.027, 2017.
Alberello, A., Onorato, M., Bennetts, L., Vichi, M., Eayrs, C., MacHutchon, K., and Toffoli, A.: Brief communication: Pancake ice floe size distribution during the winter expansion of the Antarctic marginal ice zone, The Cryosphere, 13, 41–48, https://doi.org/10.5194/tc-13-41-2019, 2019.
Arntsen, A. E., Song, A. J., Perovich, D. K., and Richter-Menge, J. A.:
Observations of the summer breakup of an Arctic sea ice cover, Geophys. Res.
Lett., 42, 8057–8063, https://doi.org/10.1002/2015GL065224, 2015.
Åstrom, J. A., Ouchterlony, F., Linna, R. P., and Timonen, J.: Universal
dynamic fragmentation in D dimensions, Phys. Rev. Lett., 92, 245506,
https://doi.org/10.1103/PhysRevLett.92.245506, 2004.
Bateson, A. W.: Fragmentation and melting of the seasonal sea ice cover,
PhD thesis, Department of Meteorology, University of Reading, United
Kingdom, 293 pp., https://doi.org/10.48683/1926.00098821, 2021a.
Bateson, A. W.: Simulations of the Arctic sea ice comparing different
approaches to modelling the floe size distribution and their respective
impacts on the sea ice cover, University of Reading [data set],
https://doi.org/10.17864/1947.300, 2021b.
Bateson, A. W., Feltham, D. L., Schröder, D., Hosekova, L., Ridley, J. K., and Aksenov, Y.: Impact of sea ice floe size distribution on seasonal fragmentation and melt of Arctic sea ice, The Cryosphere, 14, 403–428, https://doi.org/10.5194/tc-14-403-2020, 2020.
Bennetts, L. G., O'Farrell, S., and Uotila, P.: Brief communication: Impacts of ocean-wave-induced breakup of Antarctic sea ice via thermodynamics in a stand-alone version of the CICE sea-ice model, The Cryosphere, 11, 1035–1040, https://doi.org/10.5194/tc-11-1035-2017, 2017.
Boutin, G., Lique, C., Ardhuin, F., Rousset, C., Talandier, C., Accensi, M., and Girard-Ardhuin, F.: Towards a coupled model to investigate wave–sea ice interactions in the Arctic marginal ice zone, The Cryosphere, 14, 709–735, https://doi.org/10.5194/tc-14-709-2020, 2020.
Boutin, G., Williams, T., Rampal, P., Olason, E., and Lique, C.: Wave–sea-ice interactions in a brittle rheological framework, The Cryosphere, 15, 431–457, https://doi.org/10.5194/tc-15-431-2021, 2021.
Cavalieri, D. J., Parkinson, C. L., Gloersen, P., and Zwally, H. J.: Sea Ice
Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave
Data, Version 1, Natl. Snow and Ice Data Cent., Boulder, CO [data set], http://nsidc.org/data/NSIDC-0051/versions/1.html (last access: 31 December
2016), 1996.
Comiso, J. C.: Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS, Version 3, NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, Colorado USA [data set], https://doi.org/10.5067/7Q8HCCWS4I0R, 2017.
Dansereau, V., Weiss, J., Saramito, P., and Lattes, P.: A Maxwell elasto-brittle rheology for sea ice modelling, The Cryosphere, 10, 1339–1359, https://doi.org/10.5194/tc-10-1339-2016, 2016.
de Boer, G., Shupe, M. D., Caldwell, P. M., Bauer, S. E., Persson, O., Boyle, J. S., Kelley, M., Klein, S. A., and Tjernström, M.: Near-surface meteorology during the Arctic Summer Cloud Ocean Study (ASCOS): evaluation of reanalyses and global climate models, Atmos. Chem. Phys., 14, 427–445, https://doi.org/10.5194/acp-14-427-2014, 2014.
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, L., Bidlot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S.
B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P.,
Köhler, M., Matricardi, M., Mcnally, A. P., Monge-Sanz, B. M.,
Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C.,
Thépaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: Configuration
and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597,
https://doi.org/10.1002/qj.828, 2011.
Feltham, D. L.: Granular flow in the marginal ice zone, Philos. Trans. R.
Soc. A, 363, 1677–1700,
https://doi.org/10.1098/rsta.2005.1601, 2005.
Ferry, N., Masina, S., Storto, A., Haines, K., Valdivieso, M., Barnier, B.,
and Molines, J.-M.: Product user manual global-reanalysis-phys-001-004-a and
b, MyOcean, Eur. Comm., Brussels, https://catalogue.marine.copernicus.eu/documents/PUM/CMEMS-GLO-PUM-001-004-009-010-011-017.pdf
(last access: 9 June 2022), 2011.
Frew, R. C., Feltham, D. L., Holland, P. R., and Petty, A. A.: Sea ice –
Ocean Feedbacks in the Antarctic Shelf Seas, J. Phys. Oceanogr., 49,
2423–2446, https://doi.org/10.1175/JPO-D-18-0229.1, 2019.
Gherardi, M. and Lagomarsino, M. C.: Characterizing the size and shape of
sea ice floes, Sci. Rep., 5,
10226, https://doi.org/10.1038/srep10226, 2015.
Herman, A.: Sea-ice floe-size distribution in the context of spontaneous
scaling emergence in stochastic systems, Phys. Rev. E, 81, 066123, https://doi.org/10.1103/PhysRevE.81.066123, 2010.
Herman, A.: Influence of ice concentration and floe-size distribution on
cluster formation in sea-ice floes, Cent. Eur. J. Phys., 10, 715–722,
https://doi.org/10.2478/s11534-012-0071-6, 2012.
Herman, A., Wenta, M., and Cheng, S.: Sizes and Shapes of Sea Ice Floes
Broken by Waves – A Case Study From the East Antarctic Coast, Front. Earth
Sci., 9, https://doi.org/10.3389/feart.2021.655977, 2021.
Horvat, C. and Roach, L. A.: WIFF1.0: a hybrid machine-learning-based parameterization of wave-induced sea ice floe fracture, Geosci. Model Dev., 15, 803–814, https://doi.org/10.5194/gmd-15-803-2022, 2022.
Horvat, C. and Tziperman, E.: A prognostic model of the sea-ice floe size and thickness distribution, The Cryosphere, 9, 2119–2134, https://doi.org/10.5194/tc-9-2119-2015, 2015.
Horvat, C., Roach, L. A., Tilling, R., Bitz, C. M., Fox-Kemper, B., Guider, C., Hill, K., Ridout, A., and Shepherd, A.: Estimating the sea ice floe size distribution using satellite altimetry: theory, climatology, and model comparison, The Cryosphere, 13, 2869–2885, https://doi.org/10.5194/tc-13-2869-2019, 2019.
Horvat, C., Blanchard-Wrigglesworth, E., and Petty, A.: Observing Waves in
Sea Ice With ICESat-2, Geophys. Res. Lett., 47,
https://doi.org/10.1029/2020GL087629, 2020.
Hunke, E. C., Lipscomb, W. H., Turner, A. K., Jeffery, N., and Elliott, S.:
CICE: the Los Alamos Sea Ice Model Documentation and Software User's Manual
LA-CC-06-012, http://www.ccpo.odu.edu/~klinck/Reprints/PDF/cicedoc2015.pdf
(last access: 9 June 2022), 2015.
Hutchings, J., Roberts, A., Geiger, C., and Richter-Menge, J.: Spatial and
temporal characterization of sea-ice deformation, Ann. Glaciol., 52,
360–368, 2011.
Hwang, B., Wilkinson, J., Maksym, E., Graber, H. C., Schweiger, A., Horvat,
C., Perovich, D. K., Arntsen, A. E., Stanton, T. P., Ren, J., and Wadhams,
P.: Winter-to summer transition of Arctic sea ice breakup and floe size
distribution in the Beaufort Sea, Elem. Sci. Anth., 5, 40, https://doi.org/10.1525/elementa.232, 2017.
Ivanova, D. P., Gleckler, P. J., Taylor, K. E., Durack, P. J., and Marvel, K.
D.: Moving beyond the total sea ice extent in gauging model biases, J.
Climate, 29, 8965–8987, https://doi.org/10.1175/JCLI-D-16-0026.1, 2016.
Jakobson, E., Vihma, T., Palo, T., Jakobson, L., Keernik, H., and Jaagus,
J.: Validation of atmospheric reanalyses over the central arctic ocean,
Geophys. Res. Lett., 39, L10802, https://doi.org/10.1029/2012gl051591, 2012.
Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S. K., Hnilo, J. J.,
Fiorino, M., and Potter, G. L.: NCEP-DOE AMIP-II reanalysis (R-2), B. Am.
Meteorol. Soc., 83, 1631–1644,
https://doi.org/10.1175/BAMS-83-11-1631,
2002.
Keen, A., Blockley, E., Bailey, D. A., Boldingh Debernard, J., Bushuk, M., Delhaye, S., Docquier, D., Feltham, D., Massonnet, F., O'Farrell, S., Ponsoni, L., Rodriguez, J. M., Schroeder, D., Swart, N., Toyoda, T., Tsujino, H., Vancoppenolle, M., and Wyser, K.: An inter-comparison of the mass budget of the Arctic sea ice in CMIP6 models, The Cryosphere, 15, 951–982, https://doi.org/10.5194/tc-15-951-2021, 2021.
Kekäläinen, P., Aström, J. A., and Timonen, J.: Solution for the
fragment-size distribution in a crack-branching model of fragmentation,
Phys. Rev. E, 76, 026112,
https://doi.org/10.1103/PhysRevE.76.026112, 2007.
Kohout, A. L., Williams, M. J. M., Dean, S. M., and Meylan, M. H.:
Storm-induced sea-ice breakup and the implications for ice extent, Nature,
509, 604–607, https://doi.org/10.1038/nature13262, 2014.
Kwok, R.: IUTAM Symposium on Scaling Laws in Ice Mechanics and Ice Dynamics,
in: Proceedings of the IUTAM Symposium held in Fairbanks, Alaska, U.S.A., 13–16 June 2000,
315–322, https://doi.org/10.1007/978-94-015-9735-7, 2001.
Kwok, R. and Untersteiner, N.: New high-resolution images of summer arctic
Sea ice, Eos, 92, 53–54, https://doi.org/10.1029/2011EO070002,
2011.
Lecomte, O., Fichefet, T., Flocco, D., Schroeder, D., and Vancoppenolle, M.:
Interactions between wind-blown snow redistribution and melt ponds in a
coupled ocean-sea ice model, Ocean Model., 87, 67–80,
https://doi.org/10.1016/j.ocemod.2014.12.003, 2015.
Lipscomb, W. H.: Remapping the thickness distribution in sea ice models, J.
Geophys. Res.-Oceans, 106, 13989–14000, 2001.
Lüpkes, C., Gryanik, V. M., Hartmann, J., and Andreas, E. L.: A
parametrization, based on sea ice morphology, of the neutral atmospheric
drag coefficients for weather prediction and climate models, J. Geophys.
Res.-Atmos., 117, D13112, https://doi.org/10.1029/2012JD017630, 2012.
Massonnet, F., Fichefet, T., Goosse, H., Bitz, C. M., Philippon-Berthier, G., Holland, M. M., and Barriat, P.-Y.: Constraining projections of summer Arctic sea ice, The Cryosphere, 6, 1383–1394, https://doi.org/10.5194/tc-6-1383-2012, 2012.
Meier, W. and Notz, D.: A note
on the accuracy and reliability of satellite-derived passive microwave
estimates of sea-ice extent, Climate and Cryosphere Sea Ice Working Group
Consensus Document, World Climate Research Program,
http://www.arcus.org/files/page/documents/1707/GCW_CliC_Sea_ice_Reliability.pdf (last access: 9 June 2022),
2010.
Perovich, D. K. and Jones, K. F.: The seasonal evolution of sea ice floe
size distribution, J. Geophys. Res.-Oceans, 119, 8767–8777,
https://doi.org/10.1002/2014JC010136, 2014.
Perovich, D. K., Richter-Menge, J. A., and Tucker, W. B.: Seasonal changes in
Arctic sea-ice morphology, Ann. Glaciol., 33, 171–176,
https://doi.org/10.3189/172756401781818716, 2001.
Petty, A. A., Holland, P. R., and Feltham, D. L.: Sea ice and the ocean mixed layer over the Antarctic shelf seas, The Cryosphere, 8, 761–783, https://doi.org/10.5194/tc-8-761-2014, 2014.
Pringle, D. J., Eicken, H., Trodahl, H. J., and Backstrom, L. G. E.: Thermal
conductivity of landfast Antarctic and Arctic sea ice, J. Geophys. Res.-Oceans, 112, C04017, https://doi.org/10.1029/2006JC003641, 2007.
Rampal, P., Dansereau, V., Olason, E., Bouillon, S., Williams, T., Korosov, A., and Samaké, A.: On the multi-fractal scaling properties of sea ice deformation, The Cryosphere, 13, 2457–2474, https://doi.org/10.5194/tc-13-2457-2019, 2019.
Ridley, J. K., Blockley, E. W., Keen, A. B., Rae, J. G. L., West, A. E., and Schroeder, D.: The sea ice model component of HadGEM3-GC3.1, Geosci. Model Dev., 11, 713–723, https://doi.org/10.5194/gmd-11-713-2018, 2018.
Roach, L. A., Horvat, C., Dean, S. M., and Bitz, C. M.: An Emergent Sea Ice
Floe Size Distribution in a Global Coupled Ocean-Sea Ice Model, J. Geophys.
Res.-Oceans, 123, 4322–4337, https://doi.org/10.1029/2017JC013692, 2018.
Roach, L. A., Bitz, C. M., Horvat, C., and Dean, S. M.: Advances in Modeling
Interactions Between Sea Ice and Ocean Surface Waves, J. Adv. Model. Earth
Syst., 11, 4167–4181, https://doi.org/10.1029/2019MS001836, 2019.
Rösel, A., Kaleschke, L., and Birnbaum, G.: Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network, The Cryosphere, 6, 431–446, https://doi.org/10.5194/tc-6-431-2012, 2012.
Rothrock, D. A. and Thorndike, A. S.: Measuring the sea ice floe size
distribution, J. Geophys. Res., 89, 6477–6486,
https://doi.org/10.1029/JC089iC04p06477, 1984.
Rynders, S.: Impact of surface waves on sea ice and ocean in
the polar regions, PhD thesis, 205 pp., University of Southampton, United Kingdom, http://eprints.soton.ac.uk/id/eprint/428655 (last access: 9 June 2022), 2017.
Rynders, S., Aksenov, Y., Feltham, D. L., Nurser, A. J. G., and Madec, G.:
Impact of granular behaviour of fragmented sea ice on marginal ice zone
dynamics, in: IUTAM Symposium on Physics and Mechanics of Sea Ice, edited
by: Tuhkuri, J. and Polojärvi, A., Springer, Cham, 261–274,
https://doi.org/10.1007/978-3-030-80439-8_13, 2022.
Schröder, D., Feltham, D. L., Tsamados, M., Ridout, A., and Tilling, R.: New insight from CryoSat-2 sea ice thickness for sea ice modelling, The Cryosphere, 13, 125–139, https://doi.org/10.5194/tc-13-125-2019, 2019.
Schulson, E. M.: Brittle failure of ice, Eng. Fract. Mech., 68, 1839–1887,
https://doi.org/10.1016/S0013-7944(01)00037-6, 2001.
Schulson, E. M.: Compressive shear faults within arctic sea ice: Fracture on
scales large and small, J. Geophys. Res.-Oceans, 109,
C07016, https://doi.org/10.1029/2003JC002108,
2004.
Schweiger, A., Lindsay, R., Zhang, J., Steele, M., Stern, H., and Kwok, R.:
Uncertainty in modeled Arctic sea ice volume, J. Geophys. Res., 116, C00D06,
https://doi.org/10.1029/2011JC007084, 2011.
Shen, H., Hibler, W., and Leppäranta, M.: On applying granular flow
theory to a deforming broken ice field, Acta Mech., 63, 143–160, https://doi.org/10.1007/BF01182545, 1986.
Smith, M. M., Holland, M., and Light, B.: Arctic sea ice sensitivity to lateral melting representation in a coupled climate model, The Cryosphere, 16, 419–434, https://doi.org/10.5194/tc-16-419-2022, 2022.
Steele, M.: Sea ice melting and floe geometry in a simple ice-ocean model,
J. Geophys. Res.-Oceans, 97, 17729–17738, https://doi.org/10.1029/92JC01755, 1992.
Stern, H. L., Schweiger, A. J., Zhang, J., and Steele, M.: On reconciling
disparate studies of the sea-ice floe size distribution, Elem. Sci. Anth.,
6, 49, https://doi.org/10.1525/elementa.304, 2018a.
Stern, H. L., Schweiger, A. J., Stark, M., Zhang, J., Steele, M., and Hwang,
B.: Seasonal evolution of the sea-ice floe size distribution in the Beaufort
and Chukchi seas, Elem. Sci. Anth., 6, 48, https://doi.org/10.1525/elementa.305, 2018b.
Stroeve, J. C., Kattsov, V., Barrett, A., Serreze, M., Pavlova, T., Holland,
M., and Meier, W. N.: Trends in Arctic sea ice extent from CMIP5, CMIP3 and
observations, Geophys. Res. Lett., 39, L16502,
https://doi.org/10.1029/2012GL052676, 2012.
Strong, C., Foster, D., Cherkaev, E., Eisenman, I., and Golden, K. M.: On
the definition of marginal ice zone width, J. Atmos. Ocean. Tech., 34,
1565–1584, https://doi.org/10.1175/JTECH-D-16-0171.1, 2017.
Tilling, R. L., Ridout, A., and Shepherd, A.: Estimating Arctic sea ice
thickness and volume using CryoSat-2 radar altimeter data, Adv. Space Res.,
62, 1203–1225, https://doi.org/10.1016/j.asr.2017.10.051, 2018.
Toyota, T., Takatsuji, S., and Nakayama, M.: Characteristics of sea ice floe
size distribution in the seasonal ice zone, Geophys. Res. Lett., 33, L02616,
https://doi.org/10.1029/2005GL024556, 2006.
Tsamados, M., Feltham, D. L., Schroeder, D., Flocco, D., Farrell, S. L.,
Kurtz, N., Laxon, S. W., and Bacon, S.: Impact of Variable Atmospheric and
Oceanic Form Drag on Simulations of Arctic Sea Ice, J. Phys. Oceanogr.,
44, 1329–1353, https://doi.org/10.1175/JPO-D-13-0215.1, 2014.
Tsamados, M., Feltham, D., Petty, A., Schroder, D., and Flocco, D.: Processes
controlling surface, bottom and lateral melt of Arctic sea ice in a state of
the art sea ice model, Philos. T. Roy. Soc. A, 17, 10302,
https://doi.org/10.1098/rsta.2014.0167, 2015.
Virkar, Y. and Clauset, A.: Power-law distributions in binned empirical data, Ann. Appl. Stat., 8, 89–119, https://doi.org/10.1214/13-AOAS710, 2014.
Weiss, J.: Fracture and fragmentation of ice: A fractal analysis of scale
invariance, Eng. Fract. Mech., 68,
1975–2012, https://doi.org/10.1016/S0013-7944(01)00034-0, 2001.
Weiss, J. and Dansereau, V.: Linking scales in sea ice mechanics, Philos.
Trans. Roy. Soc. A, 375, 20150352, https://doi.org/10.1098/rsta.2015.0352,
2017.
Weiss, J. and Schulson, E. M.: Coulombic faulting from the grain scale to
the geophysical scale: Lessons from ice, J. Phys. D. Appl. Phys., 42,
214017,
https://doi.org/10.1088/0022-3727/42/21/214017, 2009.
Wenta, M. and Herman, A.: Area-averaged surface moisture flux over
fragmented Sea Ice: Floe size distribution effects and the associated
convection structure within the atmospheric boundary layer, Atmosphere
(Basel), 10, 654, https://doi.org/10.3390/atmos10110654, 2019.
Wilchinsky, A. V. and Feltham, D. L.: Modelling the rheology of sea ice as a
collection of diamond-shaped floes, J. Nonnewton. Fluid Mech., 138,
22–32, https://doi.org/10.1016/j.jnnfm.2006.05.001, 2006.
Wilchinsky, A. V., Feltham, D. L., and Hopkins, M. A.: Effect of shear
rupture on aggregate scale formation in sea ice, J. Geophys. Res.-Oceans,
115, C10002, https://doi.org/10.1029/2009JC006043, 2010.
Williams, T. D., Bennetts, L. G., Squire, V. A., Dumont, D., and Bertino, L.:
Wave-ice interactions in the marginal ice zone. Part 1: Theoretical
foundations, Ocean Model., 71, 81–91, https://doi.org/10.1016/j.ocemod.2013.05.010,
2013a.
Williams, T. D., Bennetts, L. G., Squire, V. A., Dumont, D., and Bertino, L.:
Wave-ice interactions in the marginal ice zone. Part 2: Numerical
implementation and sensitivity studies along 1D transects of the ocean
surface, Ocean Model., 71, 92–101, https://doi.org/10.1016/j.ocemod.2013.05.011, 2013b.
WMO: WMO Sea-Ice Nomenclature, Tech. Rep. 259, The Joint Technical
Commission for Oceanography and Marine Meteorology (JCOMM), https://library.wmo.int/doc_num.php?explnum_id=4651 (last access: 9 June 2022), 2014.
Zhang, J., Stern, H., Hwang, B., Schweiger, A., Steele, M., Stark, M., and
Graber, H. C.: Modeling the seasonal evolution of the Arctic sea ice floe
size distribution, Elem. Sci. Anthr., 4, 000126,
https://doi.org/10.12952/journal.elementa.000126, 2016.
Zhang, J. L. and Rothrock, D. A.: Modelling global sea ice with a thickness
and enthalpy distribution model in generalized curvilinear coordinates, Mon.
Weather Rev., 131, 845–861,
https://doi.org/10.1175/1520-0493(2003)131<0845:MGSIWA>2.0.CO;2, 2003.
Short summary
Numerical models are used to understand the mechanisms that drive the evolution of the Arctic sea ice cover. The sea ice cover is formed of pieces of ice called floes. Several recent studies have proposed variable floe size models to replace the standard model assumption of a fixed floe size. In this study we show the need to include floe fragmentation processes in these variable floe size models and demonstrate that model design can determine the impact of floe size on size ice evolution.
Numerical models are used to understand the mechanisms that drive the evolution of the Arctic...
