The Fall and Rise (?) of the Global Model

General circulation models (GCMs) estimate stronger effective radiative forcing by aerosol–cloud interactions (ERFaci) than other lines of evidence. The discrepancy is thought to stem in part from GCMs' inability to represent the turbulence–microphysics interactions in cloud-top entrainment that lead to a reduction in liquid water in stratocumulus-type clouds in response to an anthropogenic increase in aerosols. In the real atmosphere, precipitation suppression at low droplet number and enhanced cloud-top entrainment at high droplet number compete with each other, leading to an 'inverted v' shape of liquid water path plotted against droplet number. Enhanced entrainment is thought to be the dominant adjustment mechanism for liquid water path in the real atmosphere, weakening the overall ERFaci.

We show that the latest generation of GCMs includes models that produce a negative correlation between present-day cloud droplet number and liquid water path, a key piece of observational evidence supporting liquid water path reduction by anthropogenic aerosols and one that earlier-generation GCMs could not reproduce. However, even in the GCMs with a negative correlation, the increase in anthropogenic aerosols from preindustrial to present-day values still leads to an increase in liquid water path. This adds to the evidence that correlations in the present-day climate are not necessarily causal. Sources of confounding are investigated to explain the noncausal correlation between liquid water path and droplet number. These results are a reminder that assessments of climate parameters based on multiple lines of evidence must carefully consider the complementary strengths of different lines when the lines are in disagreement. To conclude the presentation, I will try to get the different lines of evidence to engage in Hegelian dialectic to disentangle what this means for climate projections and to imagine a world where global models (not necessarily only GCMs) contribute to physical understanding on an even footing with process modeling and observations.