Articles | Volume 16, issue 5
https://doi.org/10.5194/tc-16-1563-2022
© 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-16-1563-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 May 2022
Research article |
| 04 May 2022
| 04 May 2022
Characterizing the sea-ice floe size distribution in the Canada Basin from high-resolution optical satellite imagery
Alexis Anne Denton
CORRESPONDING AUTHOR
Department of Earth and Planetary Sciences, Yale University, New
Haven, 06511, USA
Mary-Louise Timmermans
Department of Earth and Planetary Sciences, Yale University, New
Haven, 06511, USA
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Cited
19 citations as recorded by crossref.
- Integrating a data-driven classifier and shape-modulated segmentation for sea-ice floe extraction A. Wang et al. https://doi.org/10.1016/j.jag.2024.103726
- High-resolution maps of Arctic surface skin temperature and type retrieved from airborne thermal infrared imagery collected during the HALO–(𝒜 𝒞)3 campaign J. Müller et al. https://doi.org/10.5194/amt-18-4695-2025
- Seasonal evolution of the sea ice floe size distribution in the Beaufort Sea from 2 decades of MODIS data E. Buckley et al. https://doi.org/10.5194/tc-18-5031-2024
- Multi-scale satellite observations of Arctic sea ice: new insight into the life cycle of the floe size distribution B. Hwang & Y. Wang https://doi.org/10.1098/rsta.2021.0259
- A Fully Focused SAR Omega-K Closed-Form Algorithm for the Sentinel-6 Radar Altimeter: Methodology and Applications S. Hernández-Burgos et al. https://doi.org/10.1109/TGRS.2024.3367544
- Regimes of Sea‐Ice Floe Melt: Ice‐Ocean Coupling at the Submesoscales M. Gupta & A. Thompson https://doi.org/10.1029/2022JC018894
- Non-Newtonian viscous fluid models with learned rheology accurately reproduce Lagrangian sea ice simulations G. de Diego & G. Stadler https://doi.org/10.1103/j4qf-s1th
- Ice floe segmentation and floe size distribution in airborne and high-resolution optical satellite images: towards an automated labelling deep learning approach Q. Zhang & N. Hughes https://doi.org/10.5194/tc-17-5519-2023
- Co-located OLCI optical imagery and SAR altimetry from Sentinel-3 for enhanced Arctic spring sea ice surface classification W. Chen et al. https://doi.org/10.3389/frsen.2024.1401653
- Detecting Sea Ice Leads and Floes in the Northwest Passage Using CryoSat-2 A. Swiggs et al. https://doi.org/10.1109/JSTARS.2024.3503286
- Evolution of the Floe Size Distribution in Arctic Summer Based on High-Resolution Satellite Imagery Z. Li et al. https://doi.org/10.3390/rs16142545
- A large-scale high-resolution numerical model for sea-ice fragmentation dynamics J. Åström et al. https://doi.org/10.5194/tc-18-2429-2024
- Summer sea ice floe perimeter density in the Arctic: high-resolution optical satellite imagery and model evaluation Y. Wang et al. https://doi.org/10.5194/tc-17-3575-2023
- A novel sea ice floe fragmentation index using Sentinel-2 and AMSR2 satellite data based on machine learning W. Kim et al. https://doi.org/10.1016/j.jag.2025.104911
- Size distribution and shape properties of brash ice in icebreaking channel of level ice C. Zhao et al. https://doi.org/10.1016/j.coldregions.2025.104577
- Floes, the marginal ice zone and coupled wave-sea-ice feedbacks C. Horvat https://doi.org/10.1098/rsta.2021.0252
- Particle-Continuum Multiscale Modeling of Sea Ice Floes Q. Deng et al. https://doi.org/10.1137/23M155904X
- Inferring the seasonality of sea ice floes in the Weddell Sea using ICESat-2 M. Gupta et al. https://doi.org/10.5194/tc-19-1241-2025
- Real-time monitoring of sea ice floes using shipborne marine radar during the FACE2024 arctic expedition B. Li et al. https://doi.org/10.1080/15481603.2026.2640271
19 citations as recorded by crossref.
- Integrating a data-driven classifier and shape-modulated segmentation for sea-ice floe extraction A. Wang et al. https://doi.org/10.1016/j.jag.2024.103726
- High-resolution maps of Arctic surface skin temperature and type retrieved from airborne thermal infrared imagery collected during the HALO–(𝒜 𝒞)3 campaign J. Müller et al. https://doi.org/10.5194/amt-18-4695-2025
- Seasonal evolution of the sea ice floe size distribution in the Beaufort Sea from 2 decades of MODIS data E. Buckley et al. https://doi.org/10.5194/tc-18-5031-2024
- Multi-scale satellite observations of Arctic sea ice: new insight into the life cycle of the floe size distribution B. Hwang & Y. Wang https://doi.org/10.1098/rsta.2021.0259
- A Fully Focused SAR Omega-K Closed-Form Algorithm for the Sentinel-6 Radar Altimeter: Methodology and Applications S. Hernández-Burgos et al. https://doi.org/10.1109/TGRS.2024.3367544
- Regimes of Sea‐Ice Floe Melt: Ice‐Ocean Coupling at the Submesoscales M. Gupta & A. Thompson https://doi.org/10.1029/2022JC018894
- Non-Newtonian viscous fluid models with learned rheology accurately reproduce Lagrangian sea ice simulations G. de Diego & G. Stadler https://doi.org/10.1103/j4qf-s1th
- Ice floe segmentation and floe size distribution in airborne and high-resolution optical satellite images: towards an automated labelling deep learning approach Q. Zhang & N. Hughes https://doi.org/10.5194/tc-17-5519-2023
- Co-located OLCI optical imagery and SAR altimetry from Sentinel-3 for enhanced Arctic spring sea ice surface classification W. Chen et al. https://doi.org/10.3389/frsen.2024.1401653
- Detecting Sea Ice Leads and Floes in the Northwest Passage Using CryoSat-2 A. Swiggs et al. https://doi.org/10.1109/JSTARS.2024.3503286
- Evolution of the Floe Size Distribution in Arctic Summer Based on High-Resolution Satellite Imagery Z. Li et al. https://doi.org/10.3390/rs16142545
- A large-scale high-resolution numerical model for sea-ice fragmentation dynamics J. Åström et al. https://doi.org/10.5194/tc-18-2429-2024
- Summer sea ice floe perimeter density in the Arctic: high-resolution optical satellite imagery and model evaluation Y. Wang et al. https://doi.org/10.5194/tc-17-3575-2023
- A novel sea ice floe fragmentation index using Sentinel-2 and AMSR2 satellite data based on machine learning W. Kim et al. https://doi.org/10.1016/j.jag.2025.104911
- Size distribution and shape properties of brash ice in icebreaking channel of level ice C. Zhao et al. https://doi.org/10.1016/j.coldregions.2025.104577
- Floes, the marginal ice zone and coupled wave-sea-ice feedbacks C. Horvat https://doi.org/10.1098/rsta.2021.0252
- Particle-Continuum Multiscale Modeling of Sea Ice Floes Q. Deng et al. https://doi.org/10.1137/23M155904X
- Inferring the seasonality of sea ice floes in the Weddell Sea using ICESat-2 M. Gupta et al. https://doi.org/10.5194/tc-19-1241-2025
- Real-time monitoring of sea ice floes using shipborne marine radar during the FACE2024 arctic expedition B. Li et al. https://doi.org/10.1080/15481603.2026.2640271
Saved (final revised paper)
Latest update: 09 Jun 2026
Short summary
Arctic sea ice has a distribution of ice sizes that provides insight into the physics of the ice. We examine this distribution from satellite imagery from 1999 to 2014 in the Canada Basin. We find that it appears as a power law whose power becomes less negative with increasing ice concentrations and has a seasonality tied to that of ice concentration. Results suggest ice concentration be considered in models of this distribution and are important for understanding sea ice in a warming Arctic.
Arctic sea ice has a distribution of ice sizes that provides insight into the physics of the...
