Feedbacks, Pattern Effects, and Efficacies in a Large Ensemble of HadGEM3‐GC3.1‐LL Historical Simulations

Climate feedbacks over the historical period (here defined as 1850–2014) have been investigated in large ensembles of historical and single forcing experiments (hist‐ghg, hist‐aer, and hist‐nat), with 47 members for each experiment. Across the historical ensemble with all forcings, a range in estimated Effective Climate Sensitivity (EffCS) between approximately 3–6 K is found, a considerable spread stemming solely from initial condition uncertainty. The spread in EffCS is associated with varying Sea Surface Temperature (SST) patterns seen across the ensemble due to their influence on different feedback processes. For example, the level of polar amplification is strongly correlated with the amount of sea ice melt per degree of global warming. This mechanism is related to the large spread in shortwave clear‐sky feedbacks and is the main contributor to the different forcing efficacies seen across the different forcing agents, although in HadGEM3‐GC3.1‐LL these differences in forcing efficacy are shown to be small. The spread in other feedbacks is also investigated, with the level of tropical SST warming strongly correlated with the longwave clear‐sky feedbacks, and the local surface‐air‐temperatures well correlated with the spread in cloud radiative effect feedbacks. The metrics used to understand the spread in feedbacks can also help to explain the disparity between feedbacks seen in the historical experiment simulations and modeled estimate of the feedbacks seen in the real world derived from an atmosphere‐only experiment prescribed with observed SSTs (termed amip‐piForcing). Plain Language Summary Understanding how the Earth's climate responds to an imposed forcing such as an increase in greenhouse gases or aerosols is an important issue relevant to climate mitigation and adaptation policies on the global scale. One way we can understand this is by analysing the historical period (1850–2014), a period over which the climate has already changed substantially due to human induced forcings, and also a period over which observations allow us to compare modeled changes in climate with the changes seen in the real world. Here, we use a large ensemble of climate model simulations of the historical period where we aim to understand (a) how natural variability causes differences in the global temperature response to the same imposed forcing, (b) what causes different forcing agents (e.g., greenhouse gases or aerosols) to be more or less effective at warming or cool