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We employ a moist energy balance model (MEBM), representing atmospheric heat transport as the diffusion of near-surface moist static energy, to evaluate sources of uncertainty in the meridional pattern of surface warming. Given zonal mean patterns of radiative forcing, radiative feedbacks, and ocean heat uptake, the MEBM accurately predicts zonal mean warming as simulated by general circulation models under increased CO2. Over a wide range of latitudes, the MEBM captures approximately 90% of the variance in zonal mean warming across the general circulation models, with approximately 70% of the variance attributable to differences in radiative feedbacks alone. Partitioning the radiative feedbacks into individual components shows that the majority of the uncertainty in the meridional pattern of warming arises from uncertainty in cloud feedbacks. Isolating feedback uncertainty within specific regions demonstrates that tropical feedback uncertainty leads to surface warming uncertainty that is global and nearly uniform with latitude, whereas polar feedback uncertainty leads to surface warming uncertainty that is largely confined to the poles.

Plain Language Summary In response to greenhouse gas forcing, global climate modelswhich physically describe how the climate system operatespredict a range of surface warming patterns. To better understand the sources of uncertainty in predicted warming patterns, we use an idealized climate model that links regional physical processes to warming responses across latitudes by representing changes in poleward atmospheric heat transport. We find that uncertainty in the spatial pattern of warming primarily arises from uncertainty in climate feedbacks, with uncertainty in climate forcing and ocean heat uptake playing smaller roles. Cloud feedbacks, in particular, contribute the greatest source of warming uncertainty in most regions. By considering the spread of climate feedbacks within distinct geographic regions, we show that feedback uncertainty in the tropics leads to warming uncertainty at all latitudes. However, feedback uncertainty in polar regions leads to warming uncertainty that is confined near the poles. The results suggest that polar warming is particularly difficult to predict because it is influenced by both local and nonlocal feedback processes. On the other hand, improved understanding of tropical cloud feedbacks has the potential to improve warming projections at all latitudes.