Editing IPCC:AR6/WGI/Chapter-7 (section)

===== 7.3.3.2.2 Model-based evidence =====

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As in AR5, the representation of aerosol–cloud interactions in ESMs remains a challenge, due to the limited representation of important sub-gridscale processes, from the emissions of aerosols and their precursors to precipitation formation. ESMs that simulate ERFaci typically include aerosol–cloud interactions in liquid stratiform clouds only, while very few include aerosol interactions with mixed-phase, convective and ice clouds. Adding to the spread in model-derived estimates of ERFaci is the fact that model configurations and assumptions vary across studies, for example when it comes to the treatment of oxidants, which influence aerosol formation, and their changes through time ( [[#Karset--2018|Karset et al., 2018]] ).

In AR5, ERFaci was assessed as the residual of the total aerosol ERF and ERFari, as the total aerosol ERF was easier to calculate based on available model simulations ( [[#Boucher--2013|Boucher et al., 2013]] ). The central estimates of total aerosol ERF and ERFari in AR5 were –0.9 W m <sup>–2</sup> and –0.45 W m <sup>–2</sup> , respectively, yielding an ERFaci estimate of –0.45 W m <sup>–2</sup> . This value is much less negative than the bottom-up estimate of ERFaci from ESMs presented in AR5 (–1.4 W m <sup>–2</sup> ) and efforts have been made since to reconcile this difference. [[#Zelinka--2014|Zelinka et al. (2014)]] estimated ERFaci to be –0.96 ± 0.55 W m <sup>–2</sup> (including semi-direct effects, and with land-surface cooling effect applied), based on nine CMIP5 models (Table 7.6). The corresponding ERFaci estimate based on 17 RFMIP models from CMIP6 is slightly less negative at –0.86 ± 0.57 W m <sup>–2</sup> (Table 7.6). Other post-AR5 estimates of ERFaci based on single-model studies are either in agreement with or slightly larger in magnitude than the CMIP6 estimate ( [[#Gordon--2016|Gordon et al., 2016]] ; [[#Fiedler--2017|Fiedler et al., 2017]] , 2019; [[#Neubauer--2017|Neubauer et al., 2017]] ; [[#Karset--2018|Karset et al., 2018]] ; [[#Regayre--2018|Regayre et al., 2018]] ; [[#Zhou--2018b|Zhou et al., 2018b]] ; [[#Golaz--2019|Golaz et al., 2019]] ; [[#Diamond--2020|Diamond et al., 2020]] ).

The adjustment contribution to the CMIP6 ensemble mean ERFaci is –0.20 W m <sup>–2</sup> , though with considerable differences between the models ( [[#Smith--2020b|Smith et al., 2020b]] ). Generally, this adjustment in ESMs arises mainly from LWP changes (e.g., [[#Ghan--2016|Ghan et al., 2016]] ), while satellite observations suggest that cloud cover adjustments dominate and that aerosol effects on LWP are overestimated in ESMs ( [[#Bender--2019|Bender et al., 2019]] ). Large-eddy-simulations also tend to suggest an overestimated aerosol effect on cloud lifetime in ESMs, but some report an aerosol-induced decrease in cloud cover that is at odds with satellite observations ( [[#Seifert--2015|Seifert et al., 2015]] ). Despite this potential disagreement when it comes to the dominant adjustment mechanism, a substantial negative contribution to ERFaci from adjustments is supported both by observational and modelling studies.

Contributions to ERFaci from anthropogenic aerosols acting as INPs are generally not included in CMIP6 models. Two global modelling studies incorporating parametrizations based on recent laboratory studies both found a negative contribution to ERFaci ( [[#Penner--2018|Penner et al., 2018]] ; [[#McGraw--2020|McGraw et al., 2020]] ), with central estimates of –0.3 and –0.13 W m <sup>–2</sup> , respectively. However, previous studies have produced model estimates of opposing signs ( [[#Storelvmo--2017|Storelvmo, 2017]] ). There is thus ''limited evidenc'' e and ''medium agreement'' for a small negative contribution to ERFaci from anthropogenic INP-induced cirrus modifications ( ''low confidence'' ).

Similarly, aerosol effects on deep convective clouds are typically not incorporated in ESMs. However, cloud-resolving modelling studies support non-negligible aerosol effects on the radiative properties of convective clouds and associated detrained cloud anvils ( [[#Tao--2012|Tao et al., 2012]] ). While global ERF estimates are currently not available for these effects, the fact that they are missing in most ESMs adds to the uncertainty range for the model-based ERFaci.

From model-based evidence, ERFaci is assessed to –1.0 ± 0.8 W m <sup>–2</sup> ( ''medium confidence'' ). This assessment uses the mean ERFaci in Table 7.6 as a starting point, but further allows for a small negative ERF contribution from cirrus clouds. The uncertainty range is based on those reported in Table 7.6, but widened to account for uncertain but ''likely'' non-negligible processes currently unaccounted for in ESMs.

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