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Anthropogenic aerosols and their interactions with clouds play a crucial role in regulating the Earth's radiation balance and introduce significant uncertainties in climate change projection. The effective radiative forcing due to aerosol-cloud interactions (ERFaci) is particularly difficult to quantify, leading to uncertainties in model projections of cloud feedback and climate sensitivity. Analysis of CMIP6 model simulations indicate that models with a strongly-positive cloud feedback tend to be offset with strongly negative ACI, leading to similar projections of global mean temperatures during the historical period. However, because anthropogenic aerosol primarily occur in the Northern Hemisphere, the hemispheric asymmetry in warming (NH-SH) differs significantly between low and high ACI models, with observed trends being more consistent with low ACI (weak cloud feedback) models. However, recent satellite estimates of ERFaci based on cloud controlling factors (CCF) is more consistent with high ACI models. We evaluate the CCF approach using a series of perfect model experiments. The magnitude of ERFaci depends on two factors: the amount of aerosol loading between the pre-industrial and present day, and the susceptibility of cloud albedo and cloud lifetime to that aerosol loading. By comparing observationally-constrained estimates of ERFaci with CMIP6 model simulations, we quantify the contributions of aerosol loading differences and cloud susceptibility to the inter-model spread. We find that explicitly accounting for the role of aerosol activation on cloud droplet formation is essential to obtaining accurate estimates of ERFaci, and when this is done, the satellite constrained estimates of ERFaci are more consistent with low ACI models.
Soden et al. (Fri,) studied this question.