Articles | Volume 20, issue 2
https://doi.org/10.5194/tc-20-905-2026
https://doi.org/10.5194/tc-20-905-2026
Research article
 | 
03 Feb 2026
Research article |  | 03 Feb 2026

Enhanced neural network classification for Arctic summer sea ice

Anne Braakmann-Folgmann, Jack C. Landy, Geoffrey Dawson, and Robert Ricker

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Short summary
To calculate sea ice thickness from altimetry, returns from ice and leads need to be differentiated. During summer, melt ponds complicate this task, as they resemble leads. In this study, we improve a previously suggested neural network classifier by expanding the training dataset fivefold, tuning the network architecture and introducing an additional class for thinned floes. We show that this increases the accuracy from 77 ± 5 % to 84 ± 2 % and that more leads are found.
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