Articles | Volume 19, issue 10
https://doi.org/10.5194/tc-19-4149-2025
https://doi.org/10.5194/tc-19-4149-2025
Research article
 | 
02 Oct 2025
Research article |  | 02 Oct 2025

Developing a deep learning forecasting system for short-term and high-resolution prediction of sea ice concentration

Are Frode Kvanum, Cyril Palerme, Malte Müller, Jean Rabault, and Nick Hughes

Model code and software

Project repository Are Frode Kvanum https://github.com/AreFrode/Developing_ice_chart_deep_learning_predictions

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Short summary
Recent studies have shown that machine learning models are effective at predicting sea ice concentration, yet few have explored the development of such models in an operational context. In this study, we present the development of a machine learning forecasting system which can predict sea ice concentration at 1 km resolution up to 3 d ahead using real-time operational data. The developed forecasts predict the sea ice edge position with better accuracy than physical and baseline forecasts.
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