Arctic regional changes revealed by clustering of sea-ice observations

Abstract. Understanding the evolution of Arctic sea-ice is crucial due to its climatic and socio-economic impacts. Usual descriptors (e.g., sea-ice extent, Marginal Ice Zone, sea-ice age, and ice-free duration) quantify changes but do not account for the full seasonal cycle. Here, using satellite observations of sea-ice concentration (SIC) over 1979–2023, we perform a k-means clustering of the Arctic sea-ice seasonal cycle, initializing with equal quantile separation and using Mahalanobis distance. Without providing prior information, this data-driven method shows that the Arctic is best described by four types of seasonal cycles: open-ocean (no ice year-round), permanent sea-ice (full coverage with a minimum of 70 % SIC), and two clusters showing ice-free conditions (SIC <0.15), namely partial and full winter freezing. The latter has larger SIC in winter, more abrupt melting and freezing periods, and a shorter ice-free season than the former. This reduction of dimension in the data suggests that the first date of retreat is a good indicator for ice-free conditions the following summer and the first date of advance a good indicator for fully ice cover conditions the following winter. We introduce the probability to belong to each four seasonal cycles as a descriptor to monitor Arctic sea-ice changes. The pan-Arctic probability to belong to the permanent sea-ice seasonal cycle has decreased by 3.1 % per decade which is compensated with an increase of probability to belong to the open-ocean cluster (1.6 % per decade), the full winter freezing cluster (1.1 % per decade) and the partial winter-freezing cluster (0.5 % per decade). Regionally, the permanent sea-ice retraction from the Pacific side is compensated by the full winter-freezing cluster while the open-ocean cluster expansion in the Atlantic side is lost by the partial winter-freezing cluster. The new classes of partial and full winter freezing are helpful for sea ice process understanding as it refines the classical MIZ category into two distinct sea-ice clusters. The trend is primarily controlled by the tendency of the more abrupt melting and growth seasonal cycle (full winter-freezing cluster) compared to the trend of the quasi-sinusoidal sea-ice seasonal cycle (partial winter-freezing cluster). Also, from the Beaufort to the Kara Seas, the southern parts have stabilized (experiencing a new typical seasonal cycle, corresponding to the full winter-freezing cluster) and the northern part have destabilized (losing their typical permanent sea-ice seasonal cycle). Therefore, this work provides a new way to describe Arctic regional changes using a statistical framework based on physical behaviours of sea-ice. Our study calls for a more latitudinal vision of the Arctic regions.

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Publication Details

Journal
˜The œcryosphere
Published
2025-12-08
DOI
https://doi.org/10.5194/tc-19-6639-2025
Primary Topic
Arctic and Antarctic ice dynamics
Type
article
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article

Arctic regional changes revealed by clustering of sea-ice observations

Amélie Simon, Pierre Tandeo, Camille Lique, Florian Sévellec
˜The œcryosphere
Arctic and Antarctic ice dynamics
article

Arctic regional changes revealed by clustering of sea-ice observations

Amélie Simon, Pierre Tandeo, Camille Lique, Florian Sévellec
article en

Abstract

Abstract. Understanding the evolution of Arctic sea-ice is crucial due to its climatic and socio-economic impacts. Usual descriptors (e.g., sea-ice extent, Marginal Ice Zone, sea-ice age, and ice-free duration) quantify changes but do not account for the full seasonal cycle. Here, using satellite observations of sea-ice concentration (SIC) over 1979–2023, we perform a k-means clustering of the Arctic sea-ice seasonal cycle, initializing with equal quantile separation and using Mahalanobis distance. Without providing prior information, this data-driven method shows that the Arctic is best described by four types of seasonal cycles: open-ocean (no ice year-round), permanent sea-ice (full coverage with a minimum of 70 % SIC), and two clusters showing ice-free conditions (SIC <0.15), namely partial and full winter freezing. The latter has larger SIC in winter, more abrupt melting and freezing periods, and a shorter ice-free season than the former. This reduction of dimension in the data suggests that the first date of retreat is a good indicator for ice-free conditions the following summer and the first date of advance a good indicator for fully ice cover conditions the following winter. We introduce the probability to belong to each four seasonal cycles as a descriptor to monitor Arctic sea-ice changes. The pan-Arctic probability to belong to the permanent sea-ice seasonal cycle has decreased by 3.1 % per decade which is compensated with an increase of probability to belong to the open-ocean cluster (1.6 % per decade), the full winter freezing cluster (1.1 % per decade) and the partial winter-freezing cluster (0.5 % per decade). Regionally, the permanent sea-ice retraction from the Pacific side is compensated by the full winter-freezing cluster while the open-ocean cluster expansion in the Atlantic side is lost by the partial winter-freezing cluster. The new classes of partial and full winter freezing are helpful for sea ice process understanding as it refines the classical MIZ category into two distinct sea-ice clusters. The trend is primarily controlled by the tendency of the more abrupt melting and growth seasonal cycle (full winter-freezing cluster) compared to the trend of the quasi-sinusoidal sea-ice seasonal cycle (partial winter-freezing cluster). Also, from the Beaufort to the Kara Seas, the southern parts have stabilized (experiencing a new typical seasonal cycle, corresponding to the full winter-freezing cluster) and the northern part have destabilized (losing their typical permanent sea-ice seasonal cycle). Therefore, this work provides a new way to describe Arctic regional changes using a statistical framework based on physical behaviours of sea-ice. Our study calls for a more latitudinal vision of the Arctic regions.

˜The œcryosphereVol. 19(12)
Centre National de la Recherche Scientifique (FR), Institut national de recherche en sciences et technologies du numérique (FR), Ifremer (FR), Université de Bretagne Occidentale (FR), Laboratoire des Sciences et Techniques de l’Information de la Communication et de la Connaissance (FR), IMT Atlantique (FR), Laboratory for Ocean Physics and Satellite Remote Sensing (FR), Institut de Recherche pour le Développement (FR)
Openalex Percentile: Top 57%
Arctic and Antarctic ice dynamics
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