Preprints
https://doi.org/10.5194/egusphere-2026-742
https://doi.org/10.5194/egusphere-2026-742
23 Feb 2026
 | 23 Feb 2026
Status: this preprint is open for discussion and under review for The Cryosphere (TC).

A Reanalysis of the Arctic sea ice cover over the satellite era utilising summertime observations of SIT

Nicholas Williams, Nicholas Byrne, Daniel Feltham, Peter Jan Van Leeuwen, Ross Bannister, David Schroeder, Isobel Lawrence, Lars Nerger, Jack Landy, and Geoffrey Dawson

Abstract. Climate change has significantly affected the Arctic over the satellite era, with sea ice undergoing a substantial decline. While changes in sea ice concentration (SIC) and sea ice extent (SIE) have been widely studied, sea ice thickness (SIT) and volume (SIV) remain less well constrained due to limited observations. Quantifying SIV trends is particularly important for understanding sea ice changes in response to climate change. Here we present three reanalyses that assimilate different combinations of SIC and SIT products, including year-round SIT observations, into the CPOM-CICE sea ice model, which incorporates advanced parameterisations for melt ponds, form drag, and rheology. Assimilating NASA Team SIC together with year-round SIT substantially improves SIT estimates, and year-round SIT assimilation outperforms winter-only SIT assimilation, even at the end of winter, by better initialising the growth season. Comparison with four independent observational datasets and PIOMAS identifies the best-performing reanalysis, which we analyse for 2010–2020 to diagnose model deficiencies. The model exhibits a seasonally compensating bias cycle: excessive freeze-up and overly thick, consolidated ice in autumn and winter lead to elevated extent and thickness and a suppressed marginal ice zone in spring, while enhanced late-summer melt offsets these errors, yielding September extents close to observations but with anomalously thick ice packed against the Canadian Arctic Archipelago. This suggests that misrepresentations of ice growth, lead formation and refreezing, marginal ice zone dynamics, mechanical redistribution, and melt timing interact to obscure errors in concentration and thickness. Additionally, our best performing reanalysis also shows the thickest ice is less thick and more evenly distributed across the central Arctic in the 2010s. This reanalysis provides new insight into recent Arctic sea ice change and its underlying processes, as well as identifying key deficiencies in the sea ice model physics which can be a focus for future model development.

Competing interests: At least one of the (co-)authors is a member of the editorial board of The Cryosphere.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Nicholas Williams, Nicholas Byrne, Daniel Feltham, Peter Jan Van Leeuwen, Ross Bannister, David Schroeder, Isobel Lawrence, Lars Nerger, Jack Landy, and Geoffrey Dawson

Status: open (until 06 Apr 2026)

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Nicholas Williams, Nicholas Byrne, Daniel Feltham, Peter Jan Van Leeuwen, Ross Bannister, David Schroeder, Isobel Lawrence, Lars Nerger, Jack Landy, and Geoffrey Dawson
Nicholas Williams, Nicholas Byrne, Daniel Feltham, Peter Jan Van Leeuwen, Ross Bannister, David Schroeder, Isobel Lawrence, Lars Nerger, Jack Landy, and Geoffrey Dawson
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Latest update: 23 Feb 2026
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Short summary
In this study we present three satellite era Arctic sea ice reanalyses, each assimilating different combinations of sea ice concentration and thickness observations. Results show that using year-round thickness observations substantially improves reanalysis compared to winter-only data. The best-performing reanalysis reveals a seasonally compensating bias cycle, suggesting errors in ice growth, leads, refreezing, marginal ice zone dynamics, redistribution, and melt timing mask model errors.
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