Articles | Volume 19, issue 3
https://doi.org/10.5194/tc-19-1241-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-19-1241-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Mar 2025
Research article |
| 17 Mar 2025
| 17 Mar 2025
Inferring the seasonality of sea ice floes in the Weddell Sea using ICESat-2
Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, the Netherlands
Environmental Science and Engineering, California Institute of Technology, Pasadena, CA, USA
Heather Regan
Nansen Environmental and Remote Sensing Center, Bergen, Norway
Bjerknes Centre for Climate Research, Bergen, Norway
Younghyun Koo
Department of Earth and Planetary Sciences, University of Texas at San Antonio, San Antonio, TX, USA
Sean Minhui Tashi Chua
Nansen Environmental and Remote Sensing Center, Bergen, Norway
Australian Antarctic Division, Kingston, Australia
Australian Antarctic Program Partnership, University of Tasmania, Hobart, Australia
Department of Earth and Environmental Science, University of Pennsylvania, Philadelphia, PA, USA
Petra Heil
Australian Antarctic Division, Kingston, Australia
Australian Antarctic Program Partnership, University of Tasmania, Hobart, Australia
WSL Institute for Snow and Avalanche Research, Davos, Switzerland
Related authors
No articles found.
Younghyun Koo, Gong Cheng, Mathieu Morlighem, and Maryam Rahnemoonfar
The Cryosphere, 19, 2583–2599, https://doi.org/10.5194/tc-19-2583-2025, https://doi.org/10.5194/tc-19-2583-2025, 2025
Short summary
Short summary
Calving, the breaking of ice bodies from the terminus of a glacier, plays an important role in the mass losses of Greenland ice sheets. However, calving parameters have been poorly understood because of the intensive computational demands of traditional numerical models. To address this issue and find the optimal calving parameter that best represents real observations, we develop deep-learning emulators based on graph neural network architectures.
Jennifer Veitch, Enrique Alvarez-Fanjul, Arthur Capet, Stefania Ciliberti, Mauro Cirano, Emanuela Clementi, Fraser Davidson, Ghada el Serafy, Guilherme Franz, Patrick Hogan, Sudheer Joseph, Svitlana Liubartseva, Yasumasa Miyazawa, Heather Regan, and Katerina Spanoudaki
State Planet, 5-opsr, 6, https://doi.org/10.5194/sp-5-opsr-6-2025, https://doi.org/10.5194/sp-5-opsr-6-2025, 2025
Short summary
Short summary
Ocean forecast systems provide information about a future state of the ocean. This information is provided in the form of decision support tools, or downstream applications, that can be accessed by various stakeholders to support livelihoods, coastal resilience and the good governance of the marine environment. This paper provides an overview of the various downstream applications of ocean forecast systems that are utilized around the world.
Mauro Cirano, Enrique Alvarez-Fanjul, Arthur Capet, Stefania Ciliberti, Emanuela Clementi, Boris Dewitte, Matias Dinápoli, Ghada El Serafy, Patrick Hogan, Sudheer Joseph, Yasumasa Miyazawa, Ivonne Montes, Diego A. Narvaez, Heather Regan, Claudia G. Simionato, Gregory C. Smith, Joanna Staneva, Clemente A. S. Tanajura, Pramod Thupaki, Claudia Urbano-Latorre, Jennifer Veitch, and Jorge Zavala Hidalgo
State Planet, 5-opsr, 5, https://doi.org/10.5194/sp-5-opsr-5-2025, https://doi.org/10.5194/sp-5-opsr-5-2025, 2025
Short summary
Short summary
Operational ocean forecasting systems (OOFSs) are crucial for human activities, environmental monitoring, and policymaking. An assessment across eight key regions highlights strengths and gaps, particularly in coastal and biogeochemical forecasting. AI offers improvements, but collaboration, knowledge sharing, and initiatives like the OceanPrediction Decade Collaborative Centre (DCC) are key to enhancing accuracy, accessibility, and global forecasting capabilities.
Einar Ólason, Guillaume Boutin, Timothy Williams, Anton Korosov, Heather Regan, Jonathan Rheinlænder, Pierre Rampal, Daniela Flocco, Abdoulaye Samaké, Richard Davy, Timothy Spain, and Sean Chua
EGUsphere, https://doi.org/10.5194/egusphere-2024-3521, https://doi.org/10.5194/egusphere-2024-3521, 2025
Short summary
Short summary
This paper introduces a new version of the neXtSIM sea-ice model. NeXtSIM is unique among sea-ice models in how it represents sea-ice dynamics, focusing on features such as cracks and ridges and how these impact interactions between the atmosphere and ocean where sea ice is present. The new version introduces some physical parameterisations and model options detailed and explained in the paper. Following the paper's publication, the neXtSIM code will be released publicly for the first time.
Diana Francis, Ricardo Fonseca, Narendra Nelli, Petra Heil, Jonathan Wille, Irina Gorodetskaya, and Robert Massom
EGUsphere, https://doi.org/10.5194/egusphere-2024-3535, https://doi.org/10.5194/egusphere-2024-3535, 2025
Short summary
Short summary
This study investigates the impact of atmospheric rivers and associated atmospheric dynamics on sea-ice thickness and snow depth at a coastal site in East Antarctica during July–November 2022 using in-situ measurements and numerical modelling. The passage of an atmospheric river induced a reduction of up to 0.06 m in both fields. Precipitation occurred from the convergence of katabatic winds with advected low-latitude moist air.
Kai Liu, Hongyan Zhang, Yong Bo, Dehui Li, Long Li, Hang Li, Shudong Wang, and Xueke Li
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-129, https://doi.org/10.5194/hess-2024-129, 2024
Manuscript not accepted for further review
Short summary
Short summary
Our framework brings together remote sensing, machine learning, and numerical modeling to enhance soil moisture records. We merge outputs from various machine learning algorithms to ensure the model reliability. The ability of our approach in capturing drought dynamics is noticeable, making it invaluable in arid and semi-arid regions globally, such as northern China and the northern-central United States, where drought susceptibility is high.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
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
Short summary
Short summary
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.
Heather Regan, Pierre Rampal, Einar Ólason, Guillaume Boutin, and Anton Korosov
The Cryosphere, 17, 1873–1893, https://doi.org/10.5194/tc-17-1873-2023, https://doi.org/10.5194/tc-17-1873-2023, 2023
Short summary
Short summary
Multiyear ice (MYI), sea ice that survives the summer, is more resistant to changes than younger ice in the Arctic, so it is a good indicator of sea ice resilience. We use a model with a new way of tracking MYI to assess the contribution of different processes affecting MYI. We find two important years for MYI decline: 2007, when dynamics are important, and 2012, when melt is important. These affect MYI volume and area in different ways, which is important for the interpretation of observations.
Na Li, Ruibo Lei, Petra Heil, Bin Cheng, Minghu Ding, Zhongxiang Tian, and Bingrui Li
The Cryosphere, 17, 917–937, https://doi.org/10.5194/tc-17-917-2023, https://doi.org/10.5194/tc-17-917-2023, 2023
Short summary
Short summary
The observed annual maximum landfast ice (LFI) thickness off Zhongshan (Davis) was 1.59±0.17 m (1.64±0.08 m). Larger interannual and local spatial variabilities for the seasonality of LFI were identified at Zhongshan, with the dominant influencing factors of air temperature anomaly, snow atop, local topography and wind regime, and oceanic heat flux. The variability of LFI properties across the study domain prevailed at interannual timescales, over any trend during the recent decades.
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.
Kai Liu, Xueke Li, Shudong Wang, and Hongyan Zhang
Hydrol. Earth Syst. Sci., 27, 577–598, https://doi.org/10.5194/hess-27-577-2023, https://doi.org/10.5194/hess-27-577-2023, 2023
Short summary
Short summary
Remote sensing has opened opportunities for mapping spatiotemporally continuous soil moisture, but it is hampered by data gaps. We propose a robust gap-filling approach to reconstruct daily satellite soil moisture. The merit of our approach is to integrate satellite observations, model-driven knowledge, and spatiotemporal machine learning. We also apply the developed approach to long-term datasets. Our study provides a potential avenue for hydrological applications.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
Short summary
Short summary
Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
Short summary
Short summary
The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Joey J. Voermans, Qingxiang Liu, Aleksey Marchenko, Jean Rabault, Kirill Filchuk, Ivan Ryzhov, Petra Heil, Takuji Waseda, Takehiko Nose, Tsubasa Kodaira, Jingkai Li, and Alexander V. Babanin
The Cryosphere, 15, 5557–5575, https://doi.org/10.5194/tc-15-5557-2021, https://doi.org/10.5194/tc-15-5557-2021, 2021
Short summary
Short summary
We have shown through field experiments that the amount of wave energy dissipated in landfast ice, sea ice attached to land, is much larger than in broken ice. By comparing our measurements against predictions of contemporary wave–ice interaction models, we determined which models can explain our observations and which cannot. Our results will improve our understanding of how waves and ice interact and how we can model such interactions to better forecast waves and ice in the polar regions.
YoungHyun Koo, Hongjie Xie, Stephen F. Ackley, Alberto M. Mestas-Nuñez, Grant J. Macdonald, and Chang-Uk Hyun
The Cryosphere, 15, 4727–4744, https://doi.org/10.5194/tc-15-4727-2021, https://doi.org/10.5194/tc-15-4727-2021, 2021
Short summary
Short summary
This study demonstrates for the first time the potential of Google Earth Engine (GEE) cloud-computing platform and Sentinel-1 synthetic aperture radar (SAR) images for semi-automated tracking of area changes and movements of iceberg B43. Our novel GEE-based iceberg tracking can be used to construct a large iceberg database for a better understanding of the behavior of icebergs and their interactions with surrounding environments.
Diana Francis, Kyle S. Mattingly, Stef Lhermitte, Marouane Temimi, and Petra Heil
The Cryosphere, 15, 2147–2165, https://doi.org/10.5194/tc-15-2147-2021, https://doi.org/10.5194/tc-15-2147-2021, 2021
Short summary
Short summary
The unexpected September 2019 calving event from the Amery Ice Shelf, the largest since 1963 and which occurred almost a decade earlier than expected, was triggered by atmospheric extremes. Explosive twin polar cyclones provided a deterministic role in this event by creating oceanward sea surface slope triggering the calving. The observed record-anomalous atmospheric conditions were promoted by blocking ridges and Antarctic-wide anomalous poleward transport of heat and moisture.
Joey J. Voermans, Jean Rabault, Kirill Filchuk, Ivan Ryzhov, Petra Heil, Aleksey Marchenko, Clarence O. Collins III, Mohammed Dabboor, Graig Sutherland, and Alexander V. Babanin
The Cryosphere, 14, 4265–4278, https://doi.org/10.5194/tc-14-4265-2020, https://doi.org/10.5194/tc-14-4265-2020, 2020
Short summary
Short summary
In this work we demonstrate the existence of an observational threshold which identifies when waves are most likely to break sea ice. This threshold is based on information from two recent field campaigns, supplemented with existing observations of sea ice break-up. We show that both field and laboratory observations tend to converge to a single quantitative threshold at which the wave-induced sea ice break-up takes place, which opens a promising avenue for operational forecasting models.
Andrew E. Kiss, Andrew McC. Hogg, Nicholas Hannah, Fabio Boeira Dias, Gary B. Brassington, Matthew A. Chamberlain, Christopher Chapman, Peter Dobrohotoff, Catia M. Domingues, Earl R. Duran, Matthew H. England, Russell Fiedler, Stephen M. Griffies, Aidan Heerdegen, Petra Heil, Ryan M. Holmes, Andreas Klocker, Simon J. Marsland, Adele K. Morrison, James Munroe, Maxim Nikurashin, Peter R. Oke, Gabriela S. Pilo, Océane Richet, Abhishek Savita, Paul Spence, Kial D. Stewart, Marshall L. Ward, Fanghua Wu, and Xihan Zhang
Geosci. Model Dev., 13, 401–442, https://doi.org/10.5194/gmd-13-401-2020, https://doi.org/10.5194/gmd-13-401-2020, 2020
Short summary
Short summary
We describe new computer model configurations which simulate the global ocean and sea ice at three resolutions. The coarsest resolution is suitable for multi-century climate projection experiments, whereas the finest resolution is designed for more detailed studies over time spans of decades. The paper provides technical details of the model configurations and an assessment of their performance relative to observations.
Xin Long, Xuexi Tie, Jiamao Zhou, Wenting Dai, Xueke Li, Tian Feng, Guohui Li, Junji Cao, and Zhisheng An
Atmos. Chem. Phys., 19, 11185–11197, https://doi.org/10.5194/acp-19-11185-2019, https://doi.org/10.5194/acp-19-11185-2019, 2019
Short summary
Short summary
China is undergoing ever-increasing demand for electricity, and launched the Green Light Program (GLP), which is an effective reduction of the coal consumption for power generation. The estimated potential coal saving induced by the GLP can reach a massive value of 120–323 million tons. There was a massive resultant potential emission reduction of air pollutants, which is inherently connected to the haze formation, because the NOx and SO2 are important precursors for the formation of particles.
Related subject area
Discipline: Sea ice | Subject: Antarctic
A new dataset of Southern Ocean sea-ice leads: First insights into regional lead patterns, seasonality and trends, 2003–2023
Impacts of Atmospheric Dynamics on Sea-Ice and Snow Thickness at a Coastal Site in East Antarctica
Brief communication: New perspectives on the skill of modelled sea ice trends in light of recent Antarctic sea ice loss
Quantifying the influence of snow over sea ice morphology on L-band passive microwave satellite observations in the Southern Ocean
The role of atmospheric conditions in the Antarctic sea ice extent summer minima
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
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
Umesh Dubey, Sascha Willmes, and Günther Heinemann
EGUsphere, https://doi.org/10.5194/egusphere-2025-736, https://doi.org/10.5194/egusphere-2025-736, 2025
Short summary
Short summary
Sea-ice leads facilitate the exchange of heat and moisture between the ocean and atmosphere during wintertime. We present a new dataset on monthly wintertime sea-ice leads in the Southern Ocean from 2003 to 2023. Our study reveals distinct regional patterns, seasonal variability, and small but significant trends. Here, we present initial findings on Southern Ocean lead dynamics to support future research into the complex pan-Antarctic interactions among sea ice, ocean and atmosphere.
Diana Francis, Ricardo Fonseca, Narendra Nelli, Petra Heil, Jonathan Wille, Irina Gorodetskaya, and Robert Massom
EGUsphere, https://doi.org/10.5194/egusphere-2024-3535, https://doi.org/10.5194/egusphere-2024-3535, 2025
Short summary
Short summary
This study investigates the impact of atmospheric rivers and associated atmospheric dynamics on sea-ice thickness and snow depth at a coastal site in East Antarctica during July–November 2022 using in-situ measurements and numerical modelling. The passage of an atmospheric river induced a reduction of up to 0.06 m in both fields. Precipitation occurred from the convergence of katabatic winds with advected low-latitude moist air.
Caroline R. Holmes, Thomas J. Bracegirdle, Paul R. Holland, Julienne Stroeve, and Jeremy Wilkinson
The Cryosphere, 18, 5641–5652, https://doi.org/10.5194/tc-18-5641-2024, https://doi.org/10.5194/tc-18-5641-2024, 2024
Short summary
Short summary
Until recently, satellite data showed an increase in Antarctic sea ice area since 1979, but climate models simulated a decrease over this period. This mismatch was one reason for low confidence in model projections of 21st-century sea ice loss. We show that following low Antarctic sea ice in 2022 and 2023, we can no longer conclude that modelled and observed trends differ. However, differences in the manner of the decline mean that model sea ice projections should still be viewed with caution.
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
Short summary
Short summary
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.
Bianca Mezzina, Hugues Goosse, François Klein, Antoine Barthélemy, and François Massonnet
The Cryosphere, 18, 3825–3839, https://doi.org/10.5194/tc-18-3825-2024, https://doi.org/10.5194/tc-18-3825-2024, 2024
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
We find that E3SM-HR reproduces the main features of the Antarctic coastal polynyas. Despite the high amount of coastal sea ice production, the densest water masses are formed in the open ocean. Biases related to the lack of dense water formation are associated with overly strong atmospheric polar easterlies. Our results indicate that the large-scale polar atmospheric circulation must be accurately simulated in models to properly reproduce Antarctic dense water formation.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Ackley, S. F., Perovich, D. K., Maksym, T., Weissling, B., and Xie, H.: Surface flooding of Antarctic summer sea ice, Ann. Glaciol., 61, 117–126, https://doi.org/10.1017/aog.2020.22, 2020. a, b
Arndt, S.: Sensitivity of sea ice growth to snow properties in opposing regions of the Weddell Sea in late summer, Geophys. Res. Lett., 49, e2022GL099653, https://doi.org/10.1029/2022GL099653, 2022. a
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. a, b
Brenner, S., Horvat, C., Hall, P., Lo Piccolo, A., Fox-Kemper, B., Labbé, S., and Dansereau, V.: Scale-dependent air-sea exchange in the polar oceans: floe-floe and floe-flow coupling in the generation of ice-ocean boundary layer turbulence, Geophys. Res. Lett., 50, e2023GL105703, https://doi.org/10.1029/2023GL105703, 2023. a
Bushuk, M., Winton, M., Haumann, F. A., Delworth, T., Lu, F., Zhang, Y., Jia, L., Zhang, L., Cooke, W., Harrison, M., Hurlin, B., Johnson, N. C., Kapnick, S. B., McHugh, C., Murakami, H., Rosati, A., Tseng, K.-C., Wittenberg, A. T., Yang, X., and Zeng, F.: Seasonal prediction and predictability of regional Antarctic sea ice, J. Climate, 34, 6207–6233, https://doi.org/10.1175/JCLI-D-20-0965.1, 2021. a
Denton, A. A. and Timmermans, M.-L.: Characterizing the sea-ice floe size distribution in the Canada Basin from high-resolution optical satellite imagery, The Cryosphere, 16, 1563–1578, https://doi.org/10.5194/tc-16-1563-2022, 2022. a
Eicken, H.: The role of sea ice in structuring Antarctic ecosystems, Polar Biol., 12, 3–13, https://doi.org/10.1007/BF00239960, 1992. a
England, M. R., Polvani, L. M., Sun, L., and Deser, C.: Tropical climate responses to projected Arctic and Antarctic sea-ice loss, Nat. Geosci., 13, 275–281, https://doi.org/10.1038/s41561-020-0546-9, 2020. a
Farrell, S. L., Duncan, K., Buckley, E. M., Richter-Menge, J., and Li, R.: Mapping sea ice surface topography in high fidelity with ICESat-2, Geophys. Res. Lett., 47, e2020GL090708, https://doi.org/10.1029/2020GL090708, 2020. a, b, c, d
Fiedler, E. K., Martin, M. J., Blockley, E., Mignac, D., Fournier, N., Ridout, A., Shepherd, A., and Tilling, R.: Assimilation of sea ice thickness derived from CryoSat-2 along-track freeboard measurements into the Met Office's Forecast Ocean Assimilation Model (FOAM), The Cryosphere, 16, 61–85, https://doi.org/10.5194/tc-16-61-2022, 2022. a
Fretwell, P. T., Boutet, A., and Ratcliffe, N.: Record low 2022 Antarctic sea ice led to catastrophic breeding failure of emperor penguins, Nature Communications Earth and Environment, 4, 273, https://doi.org/10.1038/s43247-023-00927-x, 2023. a
Geise, G. R., Barton, C. C., and Tebbens, S. F.: Power scaling and seasonal changes of floe areas in the Arctic East Siberian Sea, Pure Appl. Geophys., 174, 387–396, https://doi.org/10.1007/s00024-016-1364-2, 2017. a
Giles, K. A., Laxon, S. W., and Worby, A. P.: Antarctic sea ice elevation from satellite radar altimetry, Geophys. Res. Lett., 35, L03503, https://doi.org/10.1029/2007GL031572, 2008. a
Gill, A.: Circulation and bottom water production in the Weddell Sea, Deep Sea Research and Oceanographic Abstracts, 20, 111–140, https://doi.org/10.1016/0011-7471(73)90048-X, 1973. a
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. a
Gupta, M. and Thompson, A. F.: Regimes of sea-ice floe melt: ice-ocean coupling at the submesoscales, J. Geophys. Res.-Oceans, 127, e2022JC018894, https://doi.org/10.1029/2022JC018894, 2022. a, b
Gupta, M., Follows, M. J., and Lauderdale, J. M.: The effect of Antarctic sea ice on southern ocean carbon outgassing: Capping Versus Light Attenuation, Global Biogeochem. Cy., 34, e2019GB006489, https://doi.org/10.1029/2019GB006489, 2020. a
Haas, C., Nicolaus, M., Willmes, S., Worby, A., and Flinspach, D.: Sea ice and snow thickness and physical properties of an ice floe in the western Weddell Sea and their changes during spring warming, Deep-Sea Res. Pt. II, 55, 963–974, https://doi.org/10.1016/j.dsr2.2007.12.020, 2008. a, b
Herman, A.: Influence of ice concentration and floe-size distribution on cluster formation in sea-ice floes, Open Phys., 10, 715–722, https://doi.org/10.2478/s11534-012-0071-6, 2012. a
Herman, A.: Discrete-Element bonded-particle Sea Ice model DESIgn, version 1.3a – model description and implementation, Geosci. Model Dev., 9, 1219–1241, https://doi.org/10.5194/gmd-9-1219-2016, 2016. a
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, 655977, https://doi.org/10.3389/feart.2021.655977, 2021. a, b
Hopkins, M. A.: Four stages of pressure ridging, J. Geophys. Res.-Oceans, 103, 21883–21891, https://doi.org/10.1029/98JC01257, 1998. a
Horvat, C., Tziperman, E., and Campin, J.-M.: Interaction of sea ice floe size, ocean eddies, and sea ice melting, Geophys. Res. Lett., 43, 8083–8090, https://doi.org/10.1002/2016GL069742, 2016. a, b
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. a, b, c
Hutchings, J. K., Heil, P., Steer, A., and Hibler III, W. D.: Subsynoptic scale spatial variability of sea ice deformation in the western Weddell Sea during early summer, J. Geophys. Res.-Oceans, 117, C01002, https://doi.org/10.1029/2011JC006961, 2012. a, b
Hwang, B. and Wang, Y.: Multi-scale satellite observations of Arctic sea ice: new insight into the life cycle of the floe size distribution, Philos. T. Roy. Soc. A, 380, 20210259, https://doi.org/10.1098/rsta.2021.0259, 2022. a
Hwang, B., Wilkinson, J., Maksym, T., 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, Elementa: Science of the Anthropocene, 5, 40, https://doi.org/10.1525/elementa.232, 2017. a
Kohlbach, D., Graeve, M., Lange, B. A., David, C., Schaafsma, F. L., van Franeker, J. A., Vortkamp, M., Brandt, A., and Flores, H.: Dependency of Antarctic zooplankton species on ice algae-produced carbon suggests a sea ice-driven pelagic ecosystem during winter, Glob. Change Biol., 24, 4667–4681, https://doi.org/10.1111/gcb.14392, 2018. a
Koo, Y., Xie, H., Kurtz, N. T., Ackley, S. F., and Wang, W.: Sea ice surface type classification of ICESat-2 ATL07 data by using data-driven machine learning model: Ross Sea, Antarctic as an example, Remote Sens. Environ., 296, 113726, https://doi.org/10.1016/j.rse.2023.113726, 2023. a, b, c, d
Kurtz, N. T. and Markus, T.: Satellite observations of Antarctic sea ice thickness and volume, J. Geophys. Res.-Oceans, 117, C08025, https://doi.org/10.1029/2012JC008141, 2012. a, b
Kwok, R., Cunningham, G. F., Wensnahan, M., Rigor, I., Zwally, H. J., and Yi, D.: Thinning and volume loss of the Arctic Ocean sea ice cover: 2003–2008, J. Geophys. Res.-Oceans, 114, C07005, https://doi.org/10.1029/2009JC005312, 2009. a, b
Kwok, R., Markus, T., Kurtz, N. T., Petty, A. A., Neumann, T. A., Farrell, S. L., Cunningham, G. F., Hancock, D. W., Ivanoff, A., and Wimert, J. T.: Surface height and sea ice freeboard of the Arctic Ocean from ICESat-2: characteristics and early results, J. Geophys. Res.-Oceans, 124, 6942–6959, https://doi.org/10.1029/2019JC015486, 2019. a, b
Kwok, R., Petty, A. A., Bagnardi, M., Kurtz, N. T., Cunningham, G. F., Ivanoff, A., and Kacimi, S.: Refining the sea surface identification approach for determining freeboards in the ICESat-2 sea ice products, The Cryosphere, 15, 821–833, https://doi.org/10.5194/tc-15-821-2021, 2021. a
Kwok, R., Petty, A., Bagnardi, M., Wimert, J. T., Cunningham, G. F., Hancock, D. W., Ivanoff, A., and Kurtz, N.: Ice, Cloud, and Land Elevation Satellite (ICESat-2) Project Algorithm Theoretical Basis Document (ATBD) for Sea Ice Products, Version 6, National Snow and Ice Data Center, https://doi.org/10.5067/9VT7NJWOTV3I, 2022. a, b
Kwok, R., Petty, A. A., Cunningham, G., Markus, T., Hancock, D., Ivanoff, A., Wimert, J., Bagnardi, M., Kurtz, N., and the ICESat-2 Science Team: ATLAS/ICESat-2 L3A Sea Ice Height, Version 6, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/ATLAS/ATL07.006, 2023. a, b
Lange, M. A. and Eicken, H.: The sea ice thickness distribution in the northwestern Weddell Sea, J. Geophys. Res.-Oceans, 96, 4821–4837, https://doi.org/10.1029/90JC02441, 1991. a
Laxon, S. W., Giles, K. A., Ridout, A. L., Wingham, D. J., Willatt, R., Cullen, R., Kwok, R., Schweiger, A., Zhang, J., Haas, C., Hendricks, S., Krishfield, R., Kurtz, N., Farrell, S., and Davidson, M.: CryoSat-2 estimates of Arctic sea ice thickness and volume, Geophys. Res. Lett., 40, 732–737, https://doi.org/10.1002/grl.50193, 2013. a
Leonard, K. C. and Maksym, T.: The importance of wind-blown snow redistribution to snow accumulation on Bellingshausen Sea ice, Ann. Glaciol., 52, 271–278, https://doi.org/10.3189/172756411795931651, 2011. a, b
Mallett, R. D. C., Stroeve, J. C., Cornish, S. B., Crawford, A. D., Lukovich, J. V., Serreze, M. C., Barrett, A. P., Meier, W. N., Heorton, H. D. B. S., and Tsamados, M.: Record winter winds in 2020/21 drove exceptional Arctic sea ice transport, Communications Earth and Environment, 2, 149, https://doi.org/10.1038/s43247-021-00221-8, 2021. a
Manucharyan, G. E. and Montemuro, B. P.: SubZero: a sea ice model with an explicit representation of the floe life cycle, J. Adv. Model. Earth Sy., 14, e2022MS003247, https://doi.org/10.1029/2022MS003247, 2022. a
Markus, T., Neumann, T., Martino, A., Abdalati, W., Brunt, K., Csatho, B., Farrell, S., Fricker, H., Gardner, A., Harding, D., Jasinski, M., Kwok, R., Magruder, L., Lubin, D., Luthcke, S., Morison, J., Nelson, R., Neuenschwander, A., Palm, S., Popescu, S., Shum, C., Schutz, B. E., Smith, B., Yang, Y., and Zwally, J.: The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): science requirements, concept, and implementation, Remote Sens. Environ., 190, 260–273, https://doi.org/10.1016/j.rse.2016.12.029, 2017. a
Maykut, G. A. and Perovich, D. K.: The role of shortwave radiation in the summer decay of a sea ice cover, J. Geophys. Res.-Oceans, 92, 7032–7044, https://doi.org/10.1029/jc092ic07p07032, 1987. a
Melsheimer, C., Spreen, G., Ye, Y., and Shokr, M.: Multiyear Ice Concentration, Antarctic, 12.5 km grid, cold seasons 2013–2018 (from satellite), PANGAEA [data set], https://doi.org/10.1594/PANGAEA.909054, 2019. a
Moncada, R., Gupta, M., Thompson, A., and Andrade, J. E.: Level set discrete element method for modeling sea ice floes, Comput. Method. Appl. M., 406, 115891, https://doi.org/10.1016/j.cma.2023.115891, 2023. a
Montiel, F. and Mokus, N.: Theoretical framework for the emergent floe size distribution in the marginal ice zone: the case for log-normality, Philos. T. Roy. Soc. A, 380, 20210257, https://doi.org/10.1098/rsta.2021.0257, 2022. a, b
Moon, W., Nandan, V., Scharien, R. K., Wilkinson, J., Yackel, J. J., Barrett, A., Lawrence, I., Segal, R. A., Stroeve, J., Mahmud, M., Duke, P. J., and Else, B.: Physical length scales of wind-blown snow redistribution and accumulation on relatively smooth Arctic first-year sea ice, Environ. Res. Lett., 14, 104003, https://doi.org/10.1088/1748-9326/ab3b8d, 2019. a, b
Muchow, M., Schmitt, A. U., and Kaleschke, L.: A lead-width distribution for Antarctic sea ice: a case study for the Weddell Sea with high-resolution Sentinel-2 images, The Cryosphere, 15, 4527–4537, https://doi.org/10.5194/tc-15-4527-2021, 2021. a
Neumann, T. A., Martino, A. J., Markus, T., Bae, S., Bock, M. R., Brenner, A. C., Brunt, K. M., Cavanaugh, J., Fernandes, S. T., Hancock, D. W., Harbeck, K., Lee, J., Kurtz, N. T., Luers, P. J., Luthcke, S. B., Magruder, L., Pennington, T. A., Ramos-Izquierdo, L., Rebold, T., Skoog, J., and Thomas, T. C.: The Ice, Cloud, and Land Elevation Satellite – 2 mission: a global geolocated photon product derived from the Advanced Topographic Laser Altimeter System, Remote Sens. Environ., 233, 111325, https://doi.org/10.1016/j.rse.2019.111325, 2019. a
Nicholls, K. W., Østerhus, S., Makinson, K., Gammelsrød, T., and Fahrbach, E.: Ice-ocean processes over the continental shelf of the southern Weddell Sea, Antarctica: a review, Rev. Geophys., 47, RG3003, https://doi.org/10.1029/2007RG000250, 2009. a
Notz, D. and Stroeve, J.: Observed Arctic sea-ice loss directly follows anthropogenic CO2 emission, Science, 354, 747–750, https://doi.org/10.1126/science.aag2345, 2016. a
Parkinson, C. L.: A 40-y record reveals gradual Antarctic sea ice increases followed by decreases at rates far exceeding the rates seen in the Arctic, P. Natl. Acad. Sci. USA, 116, 14414–14423, https://doi.org/10.1073/pnas.1906556116, 2019. a
Parkinson, C. L. and Cavalieri, D. J.: Antarctic sea ice variability and trends, 1979–2010, The Cryosphere, 6, 871–880, https://doi.org/10.5194/tc-6-871-2012, 2012. a
Petty, A. A., Kwok, R., Bagnardi, M., Ivanoff, A., Kurtz, N., Lee, J., Wimert, J., and Hancock, D.: ATLAS/ICESat-2 L3B Daily and Monthly Gridded Sea Ice Freeboard, Version 1, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/ATLAS/ATL20.001, 2020. a
Petty, A. A., Bagnardi, M., Kurtz, N. T., Tilling, R., Fons, S., Armitage, T., Horvat, C., and Kwok, R.: Assessment of ICESat-2 sea ice surface classification with Sentinel-2 imagery: implications for freeboard and new estimates of lead and floe geometry, Earth and Space Science, 8, e2020EA001491, https://doi.org/10.1029/2020EA001491, 2021. a, b, c, d, e
Purich, A. and Doddridge, E. W.: Record low Antarctic sea ice coverage indicates a new sea ice state, Communications Earth and Environment, 4, 314, https://doi.org/10.1038/s43247-023-00961-9, 2023. a, b
Rampal, P., Weiss, J., and Marsan, D.: Positive trend in the mean speed and deformation rate of Arctic sea ice, 1979–2007, J. Geophys. Res.-Oceans, 114, C05013, https://doi.org/10.1029/2008JC005066, 2009. a, b
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. a, b
Roach, L. A., Eisenman, I., Wagner, T. J. W., Blanchard-Wrigglesworth, E., and Bitz, C. M.: Asymmetry in the seasonal cycle of Antarctic sea ice driven by insolation, Nat. Geosci., 15, 277–281, https://doi.org/10.1038/s41561-022-00913-6, 2022. a
Rothrock, D. A. and Thorndike, A. S.: Measuring the sea ice floe size distribution, J. Geophys. Res.-Oceans, 89, 6477–6486, https://doi.org/10.1029/JC089iC04p06477, 1984. a
Shokr, M., Lambe, A., and Agnew, T.: A new algorithm (ECICE) to estimate ice concentration from remote sensing observations: an application to 85-GHz passive microwave data, IEEE T. Geosci. Remote, 46, 4104–4121, https://doi.org/10.1109/TGRS.2008.2000624, 2008. a, b
Sievers, I., Rasmussen, T. A. S., and Stenseng, L.: Assimilating CryoSat-2 freeboard to improve Arctic sea ice thickness estimates, The Cryosphere, 17, 3721–3738, https://doi.org/10.5194/tc-17-3721-2023, 2023. a
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. a
Steer, A., Worby, A., and Heil, P.: Observed changes in sea-ice floe size distribution during early summer in the western Weddell Sea, Deep-Sea Res. Pt. II, 55, 933–942, https://doi.org/10.1016/j.dsr2.2007.12.016, 2008. a
Stephens, B. B. and Keeling, R. F.: The influence of Antarctic sea ice on glacial–interglacial CO2 variations, Nature, 404, 171–174, https://doi.org/10.1038/35004556, 2000. a
Stern, H. L., Schweiger, A. J., Zhang, J., and Steele, M.: On reconciling disparate studies of the sea-ice floe size distribution, Elementa: Science of the Anthropocene, 6, 49, https://doi.org/10.1525/elementa.304, 2018. a
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. a
Timco, G. and Burden, R.: An analysis of the shapes of sea ice ridges, Cold Reg. Sci. Technol., 25, 65–77, https://doi.org/10.1016/S0165-232X(96)00017-1, 1997. a
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. a
Trathan, P. N., Wienecke, B., Barbraud, C., Jenouvrier, S., Kooyman, G., Le Bohec, C., Ainley, D. G., Ancel, A., Zitterbart, D. P., Chown, S. L., LaRue, M., Cristofari, R., Younger, J., Clucas, G., Bost, C.-A., Brown, J. A., Gillett, H. J., and Fretwell, P. T.: The emperor penguin – vulnerable to projected rates of warming and sea ice loss, Biol. Conserv., 241, 108216, https://doi.org/10.1016/j.biocon.2019.108216, 2020. a
Tschudi, M., Meier, W. N., Stewart, J. S., Fowler, C., and Maslanik, J.: Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors, Version 4, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/INAWUWO7QH7B, 2019. a, b
Turner, J., Holmes, C., Caton Harrison, T., Phillips, T., Jena, B., Reeves-Francois, T., Fogt, R., Thomas, E. R., and Bajish, C. C.: Record low Antarctic sea ice cover in February 2022, Geophys. Res. Lett., 49, e2022GL098904, https://doi.org/10.1029/2022GL098904, 2022. a, b
Vella, D. and Wettlaufer, J. S.: Finger rafting: a generic instability of floating elastic sheets, Phys. Rev. Lett., 98, 088303, https://doi.org/10.1103/PhysRevLett.98.088303, 2007. a
Vernet, M., Geibert, W., Hoppema, M., Brown, P. J., Haas, C., Hellmer, H. H., Jokat, W., Jullion, L., Mazloff, M., Bakker, D. C. E., Brearley, J. A., Croot, P., Hattermann, T., Hauck, J., Hillenbrand, C.-D., Hoppe, C. J. M., Huhn, O., Koch, B. P., Lechtenfeld, O. J., Meredith, M. P., Naveira Garabato, A. C., Nöthig, E.-M., Peeken, I., Rutgers van der Loeff, M. M., Schmidtko, S., Schröder, M., Strass, V. H., Torres-Valdés, S., and Verdy, A.: The Weddell Gyre, Southern Ocean: present knowledge and future challenges, Rev. Geophys., 57, 623–708, https://doi.org/10.1029/2018RG000604, 2019. a
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. a
Williams, N., Byrne, N., Feltham, D., Van Leeuwen, P. J., Bannister, R., Schroeder, D., Ridout, A., and Nerger, L.: The effects of assimilating a sub-grid-scale sea ice thickness distribution in a new Arctic sea ice data assimilation system, The Cryosphere, 17, 2509–2532, https://doi.org/10.5194/tc-17-2509-2023, 2023. a
Worby, A. P., Geiger, C. A., Paget, M. J., Van Woert, M. L., Ackley, S. F., and DeLiberty, T. L.: Thickness distribution of Antarctic sea ice, J. Geophys. Res., 113, C05S92, https://doi.org/10.1029/2007JC004254, 2008. a
Xie, H., Ackley, S., Yi, D., Zwally, H., Wagner, P., Weissling, B., Lewis, M., and Ye, K.: Sea-ice thickness distribution of the Bellingshausen Sea from surface measurements and ICESat altimetry, Deep-Sea Res. Pt. II, 58, 1039–1051, https://doi.org/10.1016/j.dsr2.2010.10.038, antarctic Sea Ice Research during the International Polar Year 2007–2009, 2011. a
Ye, Y., Heygster, G., and Shokr, M.: Improving multiyear ice concentration estimates with reanalysis air temperatures, IEEE T. Geosci. Remote, 54, 2602–2614, https://doi.org/10.1109/TGRS.2015.2503884, 2016a. a
Ye, Y., Shokr, M., Heygster, G., and Spreen, G.: Improving multiyear sea ice concentration estimates with sea ice drift, Remote Sens.-Basel, 8, 397, https://doi.org/10.3390/rs8050397, 2016b. a
Yi, D., Zwally, H. J., and Robbins, J. W.: ICESat observations of seasonal and interannual variations of sea-ice freeboard and estimated thickness in the Weddell Sea, Antarctica (2003–2009), Ann. Glaciol., 52, 43–51, https://doi.org/10.3189/172756411795931480, 2011. a, b
Zhu, Z., Liu, J., Song, M., Wang, S., and Hu, Y.: Impacts of Antarctic Sea ice, AMV and IPO on extratropical southern hemisphere climate: a modeling study, Front. Earth Sci., 9, 757475, https://doi.org/10.3389/feart.2021.757475, 2021. a
Short summary
The sea ice cover is composed of floes, whose shapes set the material properties of the pack. Here, we use a satellite product (ICESat-2) to investigate these floe shapes within the Weddell Sea in Antarctica. We find that floes tend to become smaller during the melt season, while their thickness distribution exhibits different behavior between the western and southern regions of the pack. These metrics will help calibrate models and improve our understanding of sea ice physics across scales.
The sea ice cover is composed of floes, whose shapes set the material properties of the pack....
