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Two large ensembles are used to quantify the extent to which internal variability can contribute to long-term changes in El Nino-Southern Oscillation (ENSO) characteristics. We diagnose changes that are externally forced and distinguish between multi-model simulation results that differ by chance and those that differ due to different model physics. The range of simulated ENSO amplitude changes in the large ensemble historical simulations encompasses 90% of the Coupled Model Intercomparison Project 5 historical simulations and 80% of moderate (RCP4.5) and strong (RCP8.5) warming scenarios. When considering projected ENSO pattern changes, model differences are also important. We find that ENSO has high internal variability and that single realizations of a model can produce very different results to the ensemble mean response. Due to this variability, 30-40 ensemble members of a single model are needed to robustly compute absolute ENSO variance to a 10% error when 30-year analysis periods are used.

Plain Language Summary The El Nino-Southern Oscillation (ENSO) is the dominant driver of interannual variability globally, with effects that are felt all over the world. As such it is important to understand whether ENSO might change in the future or has already changed in the recent past due to anthropogenic emissions. We show that ENSO strength is highly variable between simulations from a single model, independent of external forcing. This variability is known as internal variability and occurs due to the chaotic nature of the climate system. Such variability can cloud our projections of the future when we have limited model simulations. Here, we demonstrate that < 30 simulations of the same model are needed to robustly estimate ENSO variability. Using the 100 possible futures simulated in the Max Planck Institute Grand Ensemble (MPI-GE) and 40 possible futures from the Community Earth System Large and Medium Ensemble Projects (CESM-LE/CESM-ME) we find that ENSO variability is large. Here, this strong variability will likely mask any possible observed changes, meaning that we are unlikely to be able attribute ENSO changes the near future to anthropogenic forcing.