Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics
NPG
Articles | Volume 33, issue 3
Articles | Volume 33, issue 3
https://doi.org/10.5194/npg-33-455-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-33-455-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 33, issue 3
Research article
 | 
27 Aug 2026
Research article |  | 27 Aug 2026

Covariations between persistent synoptic features and record low Antarctic sea ice events via unsupervised regression learning

Andrew R. Axelsen, Terence J. O'Kane, Courtney R. Quinn, and Andrew P. Bassom

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Cited articles

Axelsen, A. R.: SH-DynamicsNotebooks, Zenodo [code], https://doi.org/10.5281/zenodo.16340913, 2025. a
Axelsen, A. R., O'Kane, T. J., Quinn, C. R., and Bassom, A. P.: Hyperbolicity and Southern Hemisphere persistent synoptic events, J. Adv. Model. Earth Sy., 17, 1–25, e2024MS004834, https://doi.org/10.1029/2024MS004834, 2025. a, b, c, d, e
Boehm, C. L., Thompson, D. W. J., and Blanchard-Wrigglesworth, E.: The key role of the Southern Annular Mode during the sea-ice maximum for Antarctic sea ice and its recent loss, Commun. Earth Environ., 6, 833, 1–11, https://doi.org/10.1038/s43247-025-02792-2, 2025. a
Bromwich, D. H., Ensign, A., Wang, S.-H., and Zou, X.: Major Artifacts in ERA5 2-m air temperature trends over Antarctica prior to and dDuring the modern satellite era, Geophysical Research Letters, 51, e2024GL111907, https://doi.org/10.1029/2024GL111907, 2024. a
Chan, A. C., England, M. R., Screen, J. A., Bracegirdle, T. J., Blockley, E. W., and Holmes, C. R.: Extreme Antarctic sea ice loss facilitated by negative shift of Southern Annular Mode, Geophys. Res. Lett., 52, 1–8, e2025GL116688, https://doi.org/10.1029/2025GL116688, 2025. a
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Recent increases in the variability of Antarctic sea ice have elicited much interest and research on these changes. Here, we examine observations taken from three specific years (2016, 2021, and 2023) which either contain or precede a period of anomalously low sea ice extent. To understand the combined influence of weather systems, surface temperatures, and atmospheric pressure on sea ice formation and decay, we apply novel methods from machine learning and dynamical systems.
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