A collection on artificial intelligence and the complexity of the geosciences
To push the frontiers of geosciences forward, Nonlinear Processes in Geophysics has collated a collection of papers on artificial intelligence and the complexity of the geosciences. These articles explore a broad range of topics from original applications to methodological questions and disruptive concepts. This collection will highlight the diversity of techniques and approaches as well as the key trends.
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.
