Climate projections made using ensembles of model simulations typically present spatial information using ensemble-average changes. However, quantifying and understanding spread in model projections is critical for meeting decision-makers’ needs. Here we explore projected ensemble ranges in mean and extreme temperature and precipitation metrics, and their relationships, using CMIP6 simulations. The range is characterised by ensemble minimums and maximums, and intermediate percentiles. Heatmaps then display the contribution of individual models to the overall global pattern of changes at these points in the range. Furthermore, we examine if framing changes, both in terms of a future time slice (2070-2099) and a future global warming level (3 degrees), relative to a historical period (1850-1900), affects interpretation of results. The 2070-2099 time slice exhibits known patterns of change such as Arctic warming, and drying and wetting regions, exacerbated according to the ensemble percentile considered. For extreme temperatures, while 25^th, median, and 75^th percentile changes are relatively evenly contributed to by all models, ensemble-minimum and -maximum changes are instead dominated by one or two models. In particular, the CanESM5 dominates ensemble-maximum changes. Furthermore, the NorESM2-LM dominates ensemble-minimum changes for the coldest night of the year and contributes largely to ensemble-maximum changes for the warmest day of the year – which are opposite ends of the most extreme measures we consider. Moreover, for the 3-degrees global warming level, the CanESM5 domination ceases yet the NorESM2-LM domination persists. This has implications for the expression of ensemble ranges in multi-model projections, depending on the framing of the future period, and for the interpretation of what constitutes an outlier model. Thus, we encourage multi-model studies to visualize, understand, and communicate ensemble spread in their climate projections. 

cmip6,ETCCDI,extremes,ensemble ranges