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Abstract:
Network-based early warning signals of El Niño have been recognized for over a decade, with the potential to indicate El Niño onsets about one year in advance. However, the signal’s physical origins remain poorly understood. Before investigating the underlying mechanisms through model-based experiments, it is essential to first assess whether current climate models are capable of reproducing these signals. In this study, we evaluate simulations from both the pre-industrial control (piControl) and historical runs of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). While none of the models exhibited skill in either experiment, performance was generally better in the historical runs, suggesting that the inclusion of external forcing may improve model simulations, despite the inadequate representation of internal dynamics. Further analysis revealed that some models such as CESM2, FGOALS-g3, and MRI-ESM2-0 may provide effective early warning information for El Niño events, but their warning signals tended to emerge later than those in reanalysis data. Using a new network-based evaluation metric to assess air-sea interactions in the tropical Pacific, we found that models’ early warning performances were generally associated with their ability to simulate these interactions. This highlights the importance of improving representations of air-sea coupling in current models. For future investigations into the physical mechanisms underlying the network-based early warning signals, CESM2, FGOALS-g3, and MRI-ESM2-0 are recommended due to their relatively better performance compared to the other models considered in this work, although the causes of their delayed signal emergence warrant further exploration.
