Articles | Volume 32, issue 2
https://doi.org/10.5194/npg-32-201-2025
https://doi.org/10.5194/npg-32-201-2025
Research article
 | 
01 Jul 2025
Research article |  | 01 Jul 2025

Explaining the high skill of reservoir computing methods in El Niño prediction

Francesco Guardamagna, Claudia Wieners, and Henk A. Dijkstra

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Latest update: 09 Sep 2025
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Short summary
Artificial intelligence (AI) has recently shown promising results in ENSO (El Niño–Southern Oscillation) forecasting, outperforming traditional models. Yet AI models deliver accurate predictions without showing the underlying mechanisms. Our study examines a specific AI model, the reservoir computer (RC). Our results show that the RC is less sensitive to initial perturbations than the traditional Zebiak–Cane (ZC) model. This reduced sensitivity can explain the RC's superior skills.
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