Surprising similarities in model and observational aerosol radiative forcing estimates

Atmospheric Chemistry and Physics Copernicus GmbH 20:1 (2020) 613-623

Authors:

Edward Gryspeerdt, Johannes Mülmenstädt, Andrew Gettelman, Florent F Malavelle, Hugh Morrison, David Neubauer, Daniel G Partridge, Philip Stier, Toshihiko Takemura, Hailong Wang, Minghuai Wang, Kai Zhang

Abstract:

Abstract. The radiative forcing from aerosols (particularly through their interaction with clouds) remains one of the most uncertain components of the human forcing of the climate. Observation-based studies have typically found a smaller aerosol effective radiative forcing than in model simulations and were given preferential weighting in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). With their own sources of uncertainty, it is not clear that observation-based estimates are more reliable. Understanding the source of the model and observational differences is thus vital to reduce uncertainty in the impact of aerosols on the climate. These reported discrepancies arise from the different methods of separating the components of aerosol forcing used in model and observational studies. Applying the observational decomposition to global climate model (GCM) output, the two different lines of evidence are surprisingly similar, with a much better agreement on the magnitude of aerosol impacts on cloud properties. Cloud adjustments remain a significant source of uncertainty, particularly for ice clouds. However, they are consistent with the uncertainty from observation-based methods, with the liquid water path adjustment usually enhancing the Twomey effect by less than 50 %. Depending on different sets of assumptions, this work suggests that model and observation-based estimates could be more equally weighted in future synthesis studies.

Aerosols enhance cloud lifetime and brightness along the stratus-to-cumulus transition

Proceedings of the National Academy of Sciences National Acad Sciences 117 (2020) 30

Authors:

Matthew W Christensen, William K Jones, Philip Stier

Revisiting the 1888 Centennial Drought

Proceedings of the Royal Society of Victoria CSIRO Publishing 132:2 (2020) 49-64

Authors:

Mathilde EH Ritman, Linden C Ashcroft

Detecting anthropogenic cloud perturbations with deep learning

(2019)

Authors:

Duncan Watson-Parris, Samuel Sutherland, Matthew Christensen, Anthony Caterini, Dino Sejdinovic, Philip Stier

Efficacy of climate forcings in PDRMIP models

Journal of Geophysical Research: Atmospheres American Geophysical Union 124:23 (2019) 12824-12844

Authors:

TB Richardson, PM Forster, CJ Smith, AC Maycock, T Wood, T Andrews, O Boucher, G Faluvegi, D Flaeschner, O Hodnebrog, M Kasoar, A Kirkevåg, J-F Lamarque, J Mülmenstädt, G Myhre, D Olivié, RW Portmann, BH Samset, D Shawki, D Shindell, Philip Stier, T Takemura, A Voulgarakis, D Watson-Parris

Abstract:

Quantifying the efficacy of different climate forcings is important for understanding the real‐world climate sensitivity. This study presents a systematic multi‐model analysis of different climate driver efficacies using simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). Efficacies calculated from instantaneous radiative forcing deviate considerably from unity across forcing agents and models. Effective radiative forcing (ERF) is a better predictor of global mean near‐surface air temperature (GSAT) change. Efficacies are closest to one when ERF is computed using fixed sea surface temperature experiments and adjusted for land surface temperature changes using radiative kernels. Multi‐model mean efficacies based on ERF are close to one for global perturbations of methane, sulphate, black carbon and insolation, but there is notable inter‐model spread. We do not find robust evidence that the geographic location of sulphate aerosol affects its efficacy. GSAT is found to respond more slowly to aerosol forcing than CO2 in the early stages of simulations. Despite these differences, we find that there is no evidence for an efficacy effect on historical GSAT trend estimates based on simulations with an impulse response model, nor on the resulting estimates of climate sensitivity derived from the historical period. However, the considerable intermodel spread in the computed efficacies means that we cannot rule out an efficacy‐induced bias of ±0.4 K in equilibrium climate sensitivity to CO2 doubling (ECS) when estimated using the historical GSAT trend.