Predicting North Atlantic Temperature Trends with the Analogue Method using the MPI CMIP6 Grand Ensemble

The analogue method is a powerful and efficient tool for climate predictions, particularly in regions like the North Atlantic, where impacts of climate change have been relatively modest. While climate projections effectively estimate global mean surface temperature trends over a century, decadal trends in the North Atlantic diverge from the global trend. Here, we leverage on the similar evolution of analogous patterns on a decadal time scale by comparing SST patterns in observed data with patterns from an existing simulation ensemble. We apply this method to ten-year SST trend reconstructions in the North Atlantic using the MPI CMIP6 grand ensemble. In addition, we assess the impact of volcanic eruptions on the quality of the SST trend reconstruction for the time period 1960-2019. We also provide a prediction for 2020–2029. We find that the analogue method delivers high correlation of SST trend reconstructions with observed trends for the MPI CMIP6 grand ensemble. Volcanic influence can be accounted for by trimming the time series to those times unaffected by volcanic eruptions, which results in a higher correlation. Our results suggest that the decadal predictions of SST trends might also be achieved without the need for new, computationally expensive simulations.