Articles | Volume 18, issue 17
Atmos. Chem. Phys., 18, 13031–13053, 2018
https://doi.org/10.5194/acp-18-13031-2018
Atmos. Chem. Phys., 18, 13031–13053, 2018
https://doi.org/10.5194/acp-18-13031-2018

Research article 11 Sep 2018

Research article | 11 Sep 2018

The importance of comprehensive parameter sampling and multiple observations for robust constraint of aerosol radiative forcing

Jill S. Johnson et al.

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Cited articles

Allen, R. J., Norris, J. R., and Wild, M.: Evaluation of multidecadal variability in CMIP5 surface solar radiation and inferred underestimation of aerosol direct effects over Europe, China, Japan, and India, J. Geophys. Res.-Atmos., 118, 6311–6336, https://doi.org/10.1002/jgrd.50426, 2013. 
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Andres, R. J. and Kasgnoc, A. D.: A time-averaged inventory of subaerial volcanic sulfur emissions, J. Geophys. Res.-Atmos., 103, 25251–25261, https://doi.org/10.1029/98JD02091, 1998. 
Andrianakis, I., Vernon, I., McCreesh, N., McKinley, T. J., Oakley, J. E., Nsubuga, R. N., Goldstein, M., and White, R. G.: History matching of a complex epidemiological model of human immunodeficiency virus transmission by using variance emulation, J. R. Stat. Soc. C-Appl., 66, 717–740, https://doi.org/10.1111/rssc.12198, 2017. 
Ban-weiss, G. A., Jin, L., Bauer, S. E., Bennartz, R., Liu, X., Zhang, K., Ming, Y., Guo, H., and Jiang, J. H.: Evaluating clouds, aerosols, and their interactions in three global climate models using satellite simulators and observations, J. Geophys. Res., 119, 10876–10901, https://doi.org/10.1002/2014JD021722, 2014. 
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Short summary
We estimate the uncertainty in an aerosol–climate model that has been tuned to match several common types of observations. We used a large set of model simulations and built emulators so that we could generate 4 million “variants” of our climate model. Even after using nine aerosol and cloud observations to constrain the model, the uncertainty remains large. We conclude that estimates of aerosol forcing from multi-model studies are likely to be more uncertain than currently estimated.
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