Articles | Volume 23, issue 15
https://doi.org/10.5194/acp-23-8879-2023
https://doi.org/10.5194/acp-23-8879-2023
Research article
 | 
09 Aug 2023
Research article |  | 09 Aug 2023

Comparison of methods to estimate aerosol effective radiative forcings in climate models

Mark D. Zelinka, Christopher J. Smith, Yi Qin, and Karl E. Taylor

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Cited articles

Armour, K. C. and Roe, G. H.: Climate commitment in an uncertain world, Geophys. Res. Lett., 38, L01707, https://doi.org/10.1029/2010GL045850, 2011. a
Dvorak, M. T., Armour, K. C., Frierson, D. M. W., Proistosescu, C., Baker, M. B., and Smith, C. J.: Estimating the timing of geophysical commitment to 1.5 and 2.0 C of global warming, Nat. Clim. Change, 12, 547–552, https://doi.org/10.1038/s41558-022-01372-y, 2022. a
Forster, P., Storelvmo, T., Armour, K., Collins, W., Dufresne, J.-L., Frame, D., Lunt, D. J., Mauritsen, T., Palmer, M. D., Watanabe, M., Wild, M., and Zhang, X.: The Earth's energy budget, climate feedbacks, and climate sensitivity, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, https://doi.org/10.1017/9781009157896.009, 2021. a, b, c
Ghan, S. J.: Technical Note: Estimating aerosol effects on cloud radiative forcing, Atmos. Chem. Phys., 13, 9971–9974, https://doi.org/10.5194/acp-13-9971-2013, 2013. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t
Gryspeerdt, E., Mülmenstädt, J., Gettelman, A., Malavelle, F. F., Morrison, H., Neubauer, D., Partridge, D. G., Stier, P., Takemura, T., Wang, H., Wang, M., and Zhang, K.: Surprising similarities in model and observational aerosol radiative forcing estimates, Atmos. Chem. Phys., 20, 613–623, https://doi.org/10.5194/acp-20-613-2020, 2020. a
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The primary uncertainty in how strongly Earth's climate has been perturbed by human activities comes from the unknown radiative impact of aerosol changes. Accurately quantifying these forcings – and their sub-components – in climate models is crucial for understanding the past and future simulated climate. In this study we describe biases in previously published estimates of aerosol radiative forcing in climate models and provide corrected estimates along with code for users to compute them.
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