Aerosol Radiative Forcing of Climate
Haerter, J.O., Roeckner, E., Tomassini, L. and von Storch, J.-S. 2009. Parametric uncertainty effects on aerosol radiative forcing. Geophysical Research Letters 36: 10.1029/2009GL039050.
To get a better idea of the magnitude of uncertainty associated with this conundrum, Haerter et al. used the ECHAM5 atmospheric general circulation model (GCM), which includes parameterizations of direct and first indirect aerosol effects, to see what degree of variability in F results from reasonable uncertainties associated with seven different cloud parameters: the entrainment rate for shallow convection, the entrainment rate for penetrative convection, the cloud mass flux above the non-buoyancy level, the correction to asymmetry parameter for ice clouds, the inhomogeneity parameter for liquid clouds, the inhomogeneity parameter for ice clouds, and the conversion efficiency from cloud water to precipitation.
The four researchers report that "the uncertainty due to a single one of these parameters can be as large as 0.5 W/m2," and that "the uncertainty due to combinations of these parameters can reach more than 1 W/m2." As for their significance, they say that "these numbers should be compared with the sulfate aerosol forcing of -1.9 W/m2 for the year 2000, obtained using the default values of the parameters."
With respect to these parametric uncertainties, we apparently do not know the mean sulfate aerosol forcing component of earth's top-of-the-atmosphere radiative budget to within anything better than ± 50%. In addition, Haerter et al. note that structural uncertainties, such as "uncertainties in aerosol sources, representation of aerosols in models, parameterizations that relate aerosols and cloud droplets to simulate the indirect aerosol effect, and in cloud schemes" lead to an overall uncertainty in F of approximately ± 43%, as per the most recent IPCC estimates. In reality, therefore, we probably do not know the current atmosphere's aerosol radiative forcing to anything better that ± 100%, which does not engender confidence in our ability to simulate earth's climate very far into the future with state-of-the-art climate models.