Articles | Volume 16, issue 7
https://doi.org/10.5194/tc-16-2927-2022
https://doi.org/10.5194/tc-16-2927-2022
Research article
 | 
20 Jul 2022
Research article |  | 20 Jul 2022

Predictability of Arctic sea ice drift in coupled climate models

Simon Felix Reifenberg and Helge Friedrich Goessling

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Cited articles

Andersson, T. R., Hosking, J. S., Pérez-Ortiz, M., Paige, B., Elliott, A., Russell, C., Law, S., Jones, D. C., Wilkinson, J., Phillips, T., Byrne, J., Tietsche, S., Sarojini, B. B., Blanchard-Wrigglesworth, E., Aksenov, Y., Downie, R., and Shuckburgh, E.: Seasonal Arctic sea ice forecasting with probabilistic deep learning, Nat. Commun., 12, 5124, https://doi.org/10.1038/s41467-021-25257-4, 2021. a
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Short summary
Using model simulations, we analyze the impact of chaotic error growth on Arctic sea ice drift predictions. Regarding forecast uncertainty, our results suggest that it matters in which season and where ice drift forecasts are initialized and that both factors vary with the model in use. We find ice velocities to be slightly more predictable than near-surface wind, a main driver of ice drift. This is relevant for future developments of ice drift forecasting systems.
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