On the relationship between aerosol model uncertainty and radiative forcing uncertainty

LEE, Lindsay, REDDINGTON, C.L. and CARSLAW, K.S. (2016). On the relationship between aerosol model uncertainty and radiative forcing uncertainty. Proceedings of the National Academy of Sciences of the United States of America, 113 (21), 5820-5827.

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Abstract

The largest uncertainty in the historical radiative forcing of climate is caused by the interaction of aerosols with clouds. Historical forcing is not a directly measurable quantity, so reliable assessments depend on the development of global models of aerosols and clouds that are well constrained by observations. However, there has been no systematic assessment of how reduction in the uncertainty of global aerosol models will feed through to the uncertainty in the predicted forcing. We use a global model perturbed parameter ensemble to show that tight observational constraint of aerosol concentrations in the model has a relatively small effect on the aerosol-related uncertainty in the calculated forcing between preindustrial and present-day periods. One factor is the low sensitivity of present-day aerosol to natural emissions that determine the preindustrial aerosol state. However, the major cause of the weak constraint is that the full uncertainty space of the model generates a large number of model variants that are equally acceptable compared to present-day aerosol observations. The narrow range of aerosol concentrations in the observationally constrained model gives the impression of low aerosol model uncertainty. However, these multiple "equifinal" models predict a wide range of forcings. To make progress, we need to develop a much deeper understanding of model uncertainty and ways to use observations to constrain it. Equifinality in the aerosol model means that tuning of a small number of model processes to achieve model-observation agreement could give a misleading impression of model robustness.

Item Type:	Article
Uncontrolled Keywords:	aerosol−cloud interaction; model constraint; uncertainty analysis
Identification Number:	https://doi.org/10.1073/pnas.1507050113
Page Range:	5820-5827
SWORD Depositor:	Symplectic Elements
Depositing User:	Symplectic Elements
Date Deposited:	11 May 2021 15:14
Last Modified:	11 May 2021 15:15
URI:	https://shura.shu.ac.uk/id/eprint/26698

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