Articles | Volume 17, issue 4
https://doi.org/10.5194/tc-17-1545-2023
© Author(s) 2023. 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-17-1545-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Apr 2023
Research article |
| 11 Apr 2023
| 11 Apr 2023
A quasi-objective single-buoy approach for understanding Lagrangian coherent structures and sea ice dynamics
Nikolas O. Aksamit
CORRESPONDING AUTHOR
Department of Geography, University of Victoria, Victoria, BC V8P 5C2, Canada
School of Earth and Environment, University of Canterbury, Christchurch 8041, New Zealand
now at: Department of Mathematics and Statistics, UiT – The Arctic University of Norway, Tromsø, Norway
Randall K. Scharien
Department of Geography, University of Victoria, Victoria, BC V8P 5C2, Canada
Jennifer K. Hutchings
College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, USA
Jennifer V. Lukovich
Centre for Earth Observation Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
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The breakup and movement of sea ice can be approximated as an assemblage of interacting floes. The discrete element modeling technique holds promise in accurately representing these processes. This article describes a model, formulated to represent sea ice floes on a sphere with the objective of modeling roughly kilometer scale sea ice for periods of minutes to days. Such a model help inform more complex Earth systems models and potentially provide a navigational forecasting tool.
Scott M. Durski and Jennifer K. Hutchings
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We demonstrate the performance of a new sea ice model that can be tuned based on knowledge of the physical processes of cracking, ridging, and ice floe interactions. The sensitivity of sea ice cracking and ice floe interactions to model parameters is explored in idealized experiments and for ice jamming across a strait. The model can be used to improve understanding of how pack ice properties vary across scales.
Constanza S. Salvó, Randall K. Scharien, David Iqqaqsaq, Robert Briggs, Trevor Bell, and Saeid Homayouni
EGUsphere, https://doi.org/10.5194/egusphere-2026-4311, https://doi.org/10.5194/egusphere-2026-4311, 2026
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Julien Meloche, Melody Sandells, Henning Löwe, Nick Rutter, Ghislain Picard, Richard Essery, Randall K. Scharien, Alexandre Langlois, Matthias Jaggi, Josh King, Peter Toose, Michele Scagliola, Jerome Bouffard, Alessandro Di Bella, and Christian Haas
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Sea ice thickness is essential for climate studies. Radar altimetry has provided sea ice thickness measurements, but uncertainty arises from the interaction of the signal with the snow cover. Therefore, modelling the signal interaction with the snow is necessary to improve retrieval. A radar model was used to simulate the radar signal from the snow-covered sea ice. This work paved the way to improved physical algorithms to retrieve snow depth and sea ice thickness for radar altimeter missions.
Rasmus Tage Tonboe, Vishnu Nandan, Marcus Huntemann, Julienne Stroeve, Randall Scharien, John Yackel, Lars Kaleschke, Hoyeon Shi, and Tânia Casal
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Connor Wolfgang Dean, Randall Scharien, Ian Willis, and Kali Ann McDougall
The Cryosphere, 20, 1559–1588, https://doi.org/10.5194/tc-20-1559-2026, https://doi.org/10.5194/tc-20-1559-2026, 2026
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In this study we track winter supraglacial lake drainage on the Greenland Ice Sheet. Winter drainage is hard to observe, so we used synthetic aperture radar images to build a method that detects events across ten winter seasons. We find drainage occurs every winter, often in cascades, is most common at lower elevations, and indicates clear links to summer drainage and melt conditions. Winter drainage seldom drives seasonal changes in ice speed, though brief increases can follow cascade events.
Ferran Hernández-Macià, Marcus Huntemann, Carolina Gabarró, Gunnar Spreen, and Randall K. Scharien
EGUsphere, https://doi.org/10.5194/egusphere-2026-1336, https://doi.org/10.5194/egusphere-2026-1336, 2026
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Radiometric low-frequency microwave measurements collected in the Canadian Arctic are used to evaluate how well different models reproduce the emission of snow-covered sea ice. Standard models assume that radiation from different layers does not interfere, but the in situ observations can only be explained when interference effects are included. The results show that this coherent approach reproduces the measurements better, highlighting an effect often neglected in current approaches.
Ara Lee, Jenny Hutchings, Chris Horvat, Aikaterini Tavri, and Brodie Pearson
EGUsphere, https://doi.org/10.5194/egusphere-2025-4239, https://doi.org/10.5194/egusphere-2025-4239, 2025
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MacKenzie E. Jewell, Jennifer K. Hutchings, and Angela C. Bliss
The Cryosphere, 19, 1413–1430, https://doi.org/10.5194/tc-19-1413-2025, https://doi.org/10.5194/tc-19-1413-2025, 2025
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We quantify the contribution of sea ice drift during coastal-lead events to seasonal ice transport in the Beaufort Sea. Data from GPS tracker buoys deployed as part of the Sea Ice Dynamic Experiment (SIDEx) in spring 2021 show that sea ice in the southern Beaufort Sea became more responsive to wind forcing during fracturing events detected from satellite observations. Nearly all the spring 2021 sea ice transport occurred during these events, highlighting their importance at seasonal timescales.
Julien Meloche, Melody Sandells, Henning Löwe, Nick Rutter, Richard Essery, Ghislain Picard, Randall K. Scharien, Alexandre Langlois, Matthias Jaggi, Josh King, Peter Toose, Jérôme Bouffard, Alessandro Di Bella, and Michele Scagliola
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Preprint archived
Short summary
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Sea ice thickness is essential for climate studies. Radar altimetry has provided sea ice thickness measurement, but uncertainty arises from interaction of the signal with the snow cover. Therefore, modelling the signal interaction with the snow is necessary to improve retrieval. A radar model was used to simulate the radar signal from the snow-covered sea ice. This work paved the way to improved physical algorithm to retrieve snow depth and sea ice thickness for radar altimeter missions.
MacKenzie E. Jewell, Jennifer K. Hutchings, and Cathleen A. Geiger
The Cryosphere, 17, 3229–3250, https://doi.org/10.5194/tc-17-3229-2023, https://doi.org/10.5194/tc-17-3229-2023, 2023
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Sea ice repeatedly fractures near a prominent Alaskan headland as winds move ice along the coast, challenging predictions of sea ice drift. We find winds from high-pressure systems drive these fracturing events, and the Alaskan coastal boundary modifies the resultant ice drift. This observational study shows how wind patterns influence sea ice motion near coasts in winter. Identified relations between winds, ice drift, and fracturing provide effective test cases for dynamic sea ice models.
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
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We show that wind redistributes snow on Arctic sea ice, and Ka- and Ku-band radar measurements detect both newly deposited snow and buried snow layers that can affect the accuracy of snow depth estimates on sea ice. Radar, laser, meteorological, and snow data were collected during the MOSAiC expedition. With frequent occurrence of storms in the Arctic, our results show that
wind-redistributed snow needs to be accounted for to improve snow depth estimates on sea ice from satellite radars.
Brent G. T. Else, Araleigh Cranch, Richard P. Sims, Samantha Jones, Laura A. Dalman, Christopher J. Mundy, Rebecca A. Segal, Randall K. Scharien, and Tania Guha
The Cryosphere, 16, 3685–3701, https://doi.org/10.5194/tc-16-3685-2022, https://doi.org/10.5194/tc-16-3685-2022, 2022
Short summary
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Sea ice helps control how much carbon dioxide polar oceans absorb. We compared ice cores from two sites to look for differences in carbon chemistry: one site had thin ice due to strong ocean currents and thick snow; the other site had thick ice, thin snow, and weak currents. We did find some differences in small layers near the top and the bottom of the cores, but for most of the ice volume the chemistry was the same. This result will help build better models of the carbon sink in polar oceans.
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Short summary
Coherent flow patterns in sea ice have a significant influence on sea ice fracture and refreezing. We can better understand the state of sea ice, and its influence on the atmosphere and ocean, if we understand these structures. By adapting recent developments in chaotic dynamical systems, we are able to approximate ice stretching surrounding individual ice buoys. This illuminates the state of sea ice at much higher resolution and allows us to see previously invisible ice deformation patterns.
Coherent flow patterns in sea ice have a significant influence on sea ice fracture and...
