On the relationship between aerosol model uncertainty and radiative forcing uncertainty
On the relationship between aerosol model uncertainty and radiative forcing uncertainty
复制标题
气溶胶模型不确定性与辐射强迫不确定性的关系
DOI：
10.1073/pnas.1507050113
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
K. Carslaw
中科院分区：
文献类型：
--
作者：
Lindsay A. Lee;C. Reddington;K. Carslaw
历史上气候辐射强迫的最大不确定性是由气溶胶与云的相互作用引起的。历史强迫不是一个可直接测量的量，因此可靠的评估取决于受观测约束的全球气溶胶和云模型的发展。然而，还没有系统的评估如何减少全球气溶胶模型的不确定性将通过在预测的强迫的不确定性。我们使用一个全球模式扰动参数合奏表明，严格的观测约束模型中的气溶胶浓度有一个相对较小的影响，气溶胶相关的不确定性，在工业化前和现在的时期之间的计算强迫。其中一个因素是，当今的气溶胶对决定工业化前气溶胶状态的自然排放物的敏感性较低。然而，弱约束的主要原因是，该模型的完整的不确定性空间产生了大量的模型变量，这些变量与当今的气溶胶观测结果相比同样可以接受。在观测约束模型中，气溶胶浓度的范围很窄，给人的印象是气溶胶模型的不确定性很低。然而，这些多重“等终”模型预测的强迫范围很广。为了取得进展，我们需要对模型的不确定性有更深入的了解，并利用观测来约束它。气溶胶模型的等效性意味着，为了实现模型与观测的一致性而调整少量模型过程可能会给人一种模型鲁棒性的误导印象。
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.
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影响因子：
5.1
作者：
Mann, G. W.;Carslaw, K. S.;Johnson, C. E.
通讯作者：
Johnson, C. E.
影响因子：
6.3
作者：
D. Spracklen;J. Jimenez;K. Carslaw;D. Worsnop;M. J. Evans;G. Mann;Q. Zhang;M. Canagaratna;
通讯作者：
D. Spracklen;J. Jimenez;K. Carslaw;D. Worsnop;M. J. Evans;G. Mann;Q. Zhang;M. Canagaratna;
影响因子：
5.2
作者：
A. Rap;C. Scott;D. Spracklen;N. Bellouin;P. Forster;K. Carslaw;A. Schmidt;G. Mann
通讯作者：
A. Rap;C. Scott;D. Spracklen;N. Bellouin;P. Forster;K. Carslaw;A. Schmidt;G. Mann
影响因子：
6.3
作者：
Lee, L. A.;Carslaw, K. S.;Spracklen, D. V.
通讯作者：
Spracklen, D. V.