Lee Lindsay A, Reddington Carly L, Carslaw Kenneth S
School of Earth and Environment, University of Leeds, Leeds LS2 9JT, United Kingdom.
School of Earth and Environment, University of Leeds, Leeds LS2 9JT, United Kingdom
Proc Natl Acad Sci U S A. 2016 May 24;113(21):5820-7. doi: 10.1073/pnas.1507050113. Epub 2016 Feb 4.
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.
气候历史辐射强迫中最大的不确定性是由气溶胶与云的相互作用造成的。历史强迫不是一个可直接测量的量，因此可靠的评估依赖于受观测良好约束的全球气溶胶和云模型的发展。然而，对于全球气溶胶模型不确定性的降低将如何影响预测强迫的不确定性，尚未有系统的评估。我们使用一个全球模型扰动参数集合来表明，模型中气溶胶浓度的严格观测约束对工业化前和当今时期计算强迫中与气溶胶相关的不确定性影响相对较小。一个因素是当今气溶胶对决定工业化前气溶胶状态的自然排放的敏感性较低。然而，约束较弱的主要原因是模型的整个不确定性空间产生了大量与当今气溶胶观测相比同样可接受的模型变体。在受观测约束的模型中气溶胶浓度范围较窄，给人气溶胶模型不确定性较低的印象。然而，这些多个“等效”模型预测的强迫范围很广。为取得进展，我们需要更深入地理解模型不确定性以及利用观测来约束它的方法。气溶胶模型中的等效性意味着，对少数模型过程进行调整以实现模型与观测的一致，可能会给人模型稳健性的误导性印象。
