Publications associated with Climate Processes


Anthropogenic aerosol forcing – insights from multiple estimates from aerosol-climate models with reduced complexity

Atmospheric Chemistry and Physics Copernicus GmbH 19 (2019) 6821-6841

S Fiedler, S Kinne, WTK Huang, P Räisänen, D O'Donnell, N Bellouin, P Stier, J Merikanto, T van Noije, R Makkonen, U Lohmann

<jats:p>&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; This study assesses the change in anthropogenic aerosol forcing from the mid-1970s to the mid-2000s. Both decades had similar global-mean anthropogenic aerosol optical depths but substantially different global distributions. For both years, we quantify (i) the forcing spread due to model-internal variability and (ii) the forcing spread among models. Our assessment is based on new ensembles of atmosphere-only simulations with five state-of-the-art Earth system models. Four of these models will be used in the sixth Coupled Model Intercomparison Project (CMIP6; &lt;span class="cit" id="xref_altparen.1"&gt;&lt;a href="#bib1.bibx14"&gt;Eyring et al.&lt;/a&gt;, &lt;a href="#bib1.bibx14"&gt;2016&lt;/a&gt;&lt;/span&gt;). Here, the complexity of the anthropogenic aerosol has been reduced in the participating models. In all our simulations, we prescribe the same patterns of the anthropogenic aerosol optical properties and associated effects on the cloud droplet number concentration. We calculate the instantaneous radiative forcing (RF) and the effective radiative forcing (ERF). Their difference defines the net contribution from rapid adjustments. Our simulations show a model spread in ERF from &lt;span class="inline-formula"&gt;−0.4&lt;/span&gt; to &lt;span class="inline-formula"&gt;−0.9&lt;/span&gt;&amp;amp;thinsp;W&amp;amp;thinsp;m&lt;span class="inline-formula"&gt;&lt;sup&gt;−2&lt;/sup&gt;&lt;/span&gt;. The standard deviation in annual ERF is 0.3&amp;amp;thinsp;W&amp;amp;thinsp;m&lt;span class="inline-formula"&gt;&lt;sup&gt;−2&lt;/sup&gt;&lt;/span&gt;, based on 180 individual estimates from each participating model. This result implies that identifying the model spread in ERF due to systematic differences requires averaging over a sufficiently large number of years. Moreover, we find almost identical ERFs for the mid-1970s and mid-2000s for individual models, although there are major model differences in natural aerosols and clouds. The model-ensemble mean ERF is &lt;span class="inline-formula"&gt;−0.54&lt;/span&gt;&amp;amp;thinsp;W&amp;amp;thinsp;m&lt;span class="inline-formula"&gt;&lt;sup&gt;−2&lt;/sup&gt;&lt;/span&gt; for the pre-industrial era to the mid-1970s and &lt;span class="inline-formula"&gt;−0.59&lt;/span&gt;&amp;amp;thinsp;W&amp;amp;thinsp;m&lt;span class="inline-formula"&gt;&lt;sup&gt;−2&lt;/sup&gt;&lt;/span&gt; for the pre-industrial era to the mid-2000s. Our result suggests that comparing ERF changes between two observable periods rather than absolute magnitudes relative to a poorly constrained pre-industrial state might provide a better test for a model's ability to represent transient climate changes.&lt;/p&gt; </jats:p>


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