WCD-16. What do SMILEs tell us about ENSO projections?
Single model initial-condition large ensembles (SMILEs) are a valuable tool used to isolate forced changes in ENSO from its high variability. In this study, we leverage 14 SMILEs to determine how ENSO is projected to change. Future projections of ENSO variability are found to be non-linear with time. Additionally, the pattern of sea surface temperatures associated with ENSO in the tropical Pacific changes under a strong warming scenario, but these pattern changes are not consistent across models. Finally, we investigate the relationship between ENSO variability and mean-state projections in each SMILE. In many models, ENSO variability increases along with a weak El Niño-like mean-state warming pattern. This is followed by a plateau in ENSO variability concurrent with strong El Niño-like warming. Last, in some models, ENSO amplitude begins to decrease again. These results highlight the advantages of SMILEs, particularly in isolating the forced response from internal variability and investigating the time evolution of highly variable quantities such as ENSO.