High-resolution Arctic sea ice lead variations during wintertime (2016–2023) from SAR observations

In the Arctic, sea ice leads are crucial for the exchange of energy between the ocean and the atmosphere. Leads exhibit a wide range of widths, from several meters to tens of kilometers, with narrow leads being most abundant. Therefore, high-resolution observations are essential for monitoring leads distributions and variations. Here, we used an approach based on deep learning to generate an Arctic lead record with a spatial resolution of 40 m for wintertime 2016‒2023 based on Sentinel-1Synthetic Aperture Radar (SAR) images. The results indicate that our new lead record captures the spatial distribution pattern and the temporal variations in the lead fraction well, as one would expect from atmospheric and oceanic forcings and in agreement with two alternative pan-Arctic lead datasets. Meanwhile, the monthly Arctic lead fraction variations are consistent to the variations in sea ice drift. With our product the Arctic lead width distribution can be analyzed with a comparable high spatial resolution. Our results demonstrate that Arctic lead width distributions follow a power law function with leads narrower than 1 km accounting for approximately half of the total during winter. This study enhances the understanding of the spatiotemporal variations in Arctic sea ice leads and their width distributions, supporting climate change research.

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Publication Details

Journal
Advances in Climate Change Research
Published
2025-08-27
DOI
https://doi.org/10.1016/j.accre.2025.08.006
Primary Topic
Arctic and Antarctic ice dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

High-resolution Arctic sea ice lead variations during wintertime (2016–2023) from SAR observations

Fengming Hui, Gunnar Spreen, Zhilun Zhang, Xiao Cheng et al.
Advances in Climate Change Research
Arctic and Antarctic ice dynamics
article

High-resolution Arctic sea ice lead variations during wintertime (2016–2023) from SAR observations

Fengming Hui, Gunnar Spreen, Zhilun Zhang, Xiao Cheng, Shiyi Chen
article en

Abstract

In the Arctic, sea ice leads are crucial for the exchange of energy between the ocean and the atmosphere. Leads exhibit a wide range of widths, from several meters to tens of kilometers, with narrow leads being most abundant. Therefore, high-resolution observations are essential for monitoring leads distributions and variations. Here, we used an approach based on deep learning to generate an Arctic lead record with a spatial resolution of 40 m for wintertime 2016‒2023 based on Sentinel-1Synthetic Aperture Radar (SAR) images. The results indicate that our new lead record captures the spatial distribution pattern and the temporal variations in the lead fraction well, as one would expect from atmospheric and oceanic forcings and in agreement with two alternative pan-Arctic lead datasets. Meanwhile, the monthly Arctic lead fraction variations are consistent to the variations in sea ice drift. With our product the Arctic lead width distribution can be analyzed with a comparable high spatial resolution. Our results demonstrate that Arctic lead width distributions follow a power law function with leads narrower than 1 km accounting for approximately half of the total during winter. This study enhances the understanding of the spatiotemporal variations in Arctic sea ice leads and their width distributions, supporting climate change research.

Advances in Climate Change ResearchVol. 16(5)
Sun Yat-sen University (CN), University of Bremen (DE), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN), Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (CN)
Deutsche Forschungsgemeinschaft, Ministry of Science and Technology of the People's Republic of China, National Key Research and Development Program of China
Life below water
Openalex Percentile: Top 72%
Arctic and Antarctic ice dynamics
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