Arctic clouds play a key role in Arctic climate variability and change; however, contemporary climate models struggle to simulate cloud properties accurately. Model-simulated cloud properties are determined by the physical parameterizations and their interactions within the model configuration. Quantifying effects of individual parameterization changes on model-simulated clouds informs efforts to improve cloud properties in models and provides insights on climate system behavior. This study quantities the influence of individual parameterization schemes on Arctic low cloud properties within the Hadley Centre Global Environmental Model 3 atmospheric model using a suite of experiments where individual parameterization packages are changed one-at-a-time between two configurations: GA6 and GA7.1. The results indicate that individual parameterization changes explain most of the cloud property differences, whereas multiple parameterizations, including non-cloud schemes, contribute to cloud radiative effect differences. The influence of a parameterization change on cloud properties is found to vary by meteorological regime. We employ a three-term decomposition to quantify contributions from (1) regime independent, (2) regime dependent, and (3) the regime frequency of occurrence changes. Decomposition results indicate that each term contributes differently to each cloud property change and that non-cloud parameterization changes make a substantial contribution to the LW and SW cloud radiative effects by modifying clear-sky fluxes differently across regimes. The analysis provides insights on the role of non-cloud parameterizations for setting cloud radiative effects, a model pathway for cloud-atmosphere circulation interactions, and raises questions on the most useful observational approaches for improving models.

We compare the radiative feedbacks resulting from a uniform warming and cooling of sea surface temperatures by 4 K in an ensemble of global climate models. The global-mean net feedback is less stabilising in response to warming in all nine models. This is primarily due to a stronger tropical water vapour feedback, with a smaller contribution from the shortwave cloud feedback. The zonal-mean feedbacks are similarly robust across the ensemble. In the extra-tropics, more positive shortwave cloud feedback under warming is associated with further poleward migration of the mean Southern Hemisphere jet latitude in some models. However, additional experiments with an aquaplanet version of the HadGEM3 model suggest that the asymmetry of the jet shift is not driving that in the cloud feedbacks at these latitudes. In the tropics, stronger water vapour feedback under warming is offset by a weaker shortwave cloud feedback. The result is that the ensemble spread in the differences between the global feedbacks under warming and cooling is mainly determined by their differences in the tropics. The spatial distribution of the feedbacks largely reflects the zonal mean behaviour, although there is considerable intermodel variation in the regional cloud feedbacks, particularly in the tropical shortwave cloud feedback. Comparison with CO2- and solar-forced coupled experiments suggests that the global-mean longwave cloud feedback is nearly invariant to warming and cooling, regardless of the nature of the forcing. The shortwave cloud feedback is generally more positive under warming in the coupled models, consistent with the uniform SST perturbation experiments.

We investigate the dependence of radiative feedback on the pattern of sea-surface temperature (SST) change in fourteen Atmospheric General Circulation Models (AGCMs) forced with observed variations in SST and sea-ice over the historical record from 1871 to near-present. We find that over 1871-1980, the Earth warmed with feedbacks largely consistent and strongly correlated with long-term climate sensitivity feedbacks (diagnosed from corresponding atmosphere-ocean GCM abrupt-4xCO2 simulations). Post 1980 however, the Earth warmed with unusual trends in tropical Pacific SSTs (enhanced warming in the west, cooling in the east) that drove climate feedback to be uncorrelated with – and indicating much lower climate sensitivity than – that expected for long-term CO2 increase. We show that these conclusions are not strongly dependent on the AMIP II SST dataset used to force the AGCMs, though the magnitude of feedback post 1980 is generally smaller in eight AGCMs forced with alternative HadISST1 SST boundary conditions. We quantify a ‘pattern effect’ (defined as the difference between historical and long-term CO2 feedback) equal to 0.44 ± 0.47 [5-95%] W m-2 K-1 for the time-period 1871-2010, which increases by 0.05 ± 0.04 W m-2 K-1 if calculated over 1871-2014. Assessed changes in the Earth’s historical energy budget are in agreement with the AGCM feedback estimates. Furthermore satellite observations of changes in top-of-atmosphere radiative fluxes since 1985 suggest that the pattern effect was particularly strong over recent decades, though this may be waning post 2014 due to a warming of the eastern Pacific.