Published September 22, 2023 | Published
Journal Article Open

Forced and internal components of observed Arctic sea-ice changes

  • 1. ROR icon University of Bergen
  • 2. ROR icon California Institute of Technology
  • 3. ROR icon University of Washington
  • 4. ROR icon ETH Zurich

Abstract

The Arctic sea-ice cover is strongly influenced by internal variability on decadal timescales, affecting both short-term trends and the timing of the first ice-free summer. Several mechanisms of variability have been proposed, but how these mechanisms manifest both spatially and temporally remains unclear. The relative contribution of internal variability to observed Arctic sea-ice changes also remains poorly quantified. Here, we use a novel technique called low-frequency component analysis to identify the dominant patterns of winter and summer decadal Arctic sea-ice variability in the satellite record. The identified patterns account for most of the observed regional sea-ice variability and trends, and they thus help to disentangle the role of forced and internal sea-ice changes over the satellite record. In particular, we identify a mode of decadal ocean–atmosphere–sea-ice variability, characterized by an anomalous atmospheric circulation over the central Arctic, that accounts for approximately 30 % of the accelerated decline in pan-Arctic summer sea-ice area between 2000 and 2012 but accounts for at most 10 % of the decline since 1979. For winter sea ice, we find that internal variability has dominated decadal trends in the Bering Sea but has contributed less to trends in the Barents and Kara seas. These results, which detail the first purely observation-based estimate of the contribution of internal variability to Arctic sea-ice trends, suggest a lower estimate of the contribution from internal variability than most model-based assessments.

Copyright and License

© Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License.

Published by Copernicus Publications on behalf of the European Geosciences Union.

Acknowledgement

This study was funded by the Research Council of Norway projects Nansen Legacy (grant 276730) and the Trond Mohn Foundation (grant BFS2018TMT01). We thank Andrew Thompson for helpful discussions and comments. Furthermore, we thank Qinghua Ding and one anonymous reviewer for providing helpful comments that improved the quality of this study.

Funding

This research has been supported by the Norges Forskningsråd (grant no. 276730) and the Trond Mohn Foundation (grant no. BFS2018TMT01). David B. Bonan was supported by the National Science Foundation Graduate Research Fellowship Program (NSF grant DGE-1745301). Robert C. J. Wills was supported by the National Science Foundation (NSF grant AGS-2203543).

Contributions

JD, MÅ, DBB and RCJW conceived the study. All authors interpreted the results and were involved in reviewing and editing the text. JD performed the analysis, wrote the text and created the figures. RCJW helped with applying the method to sea ice.

Data Availability

All data used in this study are freely available. OSI SAF gridded sea-ice concentration data are available at https://doi.org/10.15770/EUM_SAF_OSI_0008 (OSI SAF2017) and https://doi.org/10.15770/EUM_SAF_OSI_NRT_2008 (OSI SAF2020). The output from ERA5 is available through the Copernicus Climate Change Service: https://doi.org/10.24381/cds.f17050d7 (Hersbach et al.2023). Monthly climate indices for the Pacific Decadal Oscillation, Arctic Oscillation and North Atlantic Oscillation can be downloaded from (NOAA2022abc), respectively. The monthly mean North Pacific Gyre Oscillation index data can be downloaded from Di Lorenzo (2022). Output from CESM-LE is available from Climate Data Gateway (2021). Python scripts to run LFCA on OSI SAF sea-ice concentration data and produce Fig. 2 can be found at https://doi.org/10.5281/zenodo.7915287 (Dörr2023). LFCA is available as Python or MATLAB code under https://doi.org/10.5281/zenodo.7940013 (Wills and Shen2023).

Additional Information

This paper was edited by Bin Cheng and reviewed by two anonymous referees.

 

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Created:
April 4, 2025
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April 4, 2025