Articles | Volume 19, issue 12
https://doi.org/10.5194/tc-19-6381-2025
https://doi.org/10.5194/tc-19-6381-2025
Research article
 | 
01 Dec 2025
Research article |  | 01 Dec 2025

Extended seasonal prediction of Antarctic sea ice concentration using ANTSIC-UNet

Ziying Yang, Jiping Liu, Mirong Song, Yongyun Hu, Qinghua Yang, Ke Fan, Rune Grand Graversen, and Lu Zhou

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Cited articles

Abernathey, R. P., Cerovecki, I., Holland, P. R., Newsom, E., Mazloff, M., and Talley, L. D.: Water-mass transformation by sea ice in the upper branch of the Southern Ocean overturning, Nat. Geosci., 9, 596–601, https://doi.org/10.1038/ngeo2749, 2016. 
Bianco, E., Iovino, D., Masina, S., Materia, S., and Ruggieri, P.: The role of upper-ocean heat content in the regional variability of Arctic sea ice at sub-seasonal timescales, The Cryosphere, 18, 2357–2379, https://doi.org/10.5194/tc-18-2357-2024, 2024. 
Bintanja, R., van Oldenborgh, G. J., Drijfhout, S. S., Wouters, B., and Katsman, C. A.: Important role for ocean warming and increased ice-shelf melt in Antarctic sea-ice expansion, Nat. Geosci., 6, 376–379, https://doi.org/10.1038/ngeo1767, 2013. 
Bourassa, M. A., Gille, S. T., Bitz, C., Carlson, D., Cerovecki, I., Clayson, C. A., Cronin, M. F., Drennan, W. M., Fairall, C. W., Hoffman, R. N., Magnusdottir, G., Pinker, R. T., Renfrew, I. A., Serreze, M., Speer, K., Talley, L. D., and Wick, G. A.: High-Latitude Ocean and Sea Ice Surface Fluxes: Challenges for Climate Research, Bulletin of the American Meteorological Society, 94, 403–423, https://doi.org/10.1175/BAMS-D-11-00244.1, 2013. 
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Short summary
Antarctic sea ice has changed rapidly in recent years. Here we developed a deep learning model trained by multiple climate variables for extended seasonal Antarctic sea ice prediction. Our model shows high predictive skills up to 6 months in advance, particularly in predicting extreme events. It also shows skillful predictions at the sea ice edge and year-to-year sea ice changes. Variable importance analyses suggest what variables are more important for prediction at different lead times.
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