Editing IPCC:AR6/WGI/Chapter-6 (section)

=== 6.4.6 ERF by Aerosols in Proposed Solar Radiation Modification ===

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Solar radiation modification (SRM; Sections 4.6.3.3 and 8.6.3) has the potential to exert a significant ERF on the climate, mainly by affecting the SW component of the radiation budget (e.g., [[#Caldeira--2013|Caldeira et al., 2013]] ; [[#NRC--2015|NRC, 2015]] ; [[#Lawrence--2018|Lawrence et al., 2018]] ). The possible ways and the extent to which the most commonly discussed options may affect radiative forcing is addressed in this section. Side effects of SRM on stratospheric ozone and changes in atmospheric transport due to radiative heating of the lower stratosphere are discussed in [[IPCC:Wg1:Chapter:Chapter-4#4.6.3.3|Section 4.6.3.3]] .

Stratospheric aerosol injections (SAI) have the potential to achieve a high negative global ERF, with maximum ERFs ranging from –5 to –2 W m <sup>–2</sup> ( [[#Niemeier--2015|Niemeier and Timmreck, 2015]] ; [[#Weisenstein--2015|Weisenstein et al., 2015]] ; [[#Niemeier--2017|Niemeier and Schmidt, 2017]] ; [[#Kleinschmitt--2018|Kleinschmitt et al., 2018]] ). The magnitude of the maximum achievable ERF depends on the chosen aerosol type and mixture, internal structure and size, or precursor gas (e.g., SO <sub>2</sub> ), as well as the injection strategy (latitude, altitude, magnitude and season of injections), plume dispersal, model representation of aerosol microphysics, and ambient aerosol concentrations (Rasch et al. , 2008; Robock et al. , 2008; Pierce et al. , 2010; Weisenstein et al. , 2015; Laakso et al. , 2017; MacMartin et al. , 2017; Dai et al. , 2018; Kleinschmitt et al. , 2018; Vattioni et al. , 2019; Visioni et al. , 2019) . For sulphur, the radiative forcing efficiency is of around –0.1 to –0.4 W m <sup>–2</sup> /(TgS yr <sup>–1</sup> <sup>)</sup> ( [[#Niemeier--2015|Niemeier and Timmreck, 2015]] ; [[#Weisenstein--2015|Weisenstein et al., 2015]] ; [[#Niemeier--2017|Niemeier and Schmidt, 2017]] ). Different manufactured aerosols, such as ZrO <sub>2</sub> , TiO <sub>2</sub> and Al <sub>2</sub> O <sub>3</sub> , have different ERF efficiencies compared to sulphate (Ferraro et al. , 2011; Weisenstein et al. , 2015; Dykema et al. , 2016; Jones et al. , 2016) . The aerosol size distribution influences the optical properties of an aerosol layer, and hence the ERF efficiency, which also depends on the dispersion, transport, and residence time of the aerosols.

For marine cloud brightening (MCB), seeded aerosols may affect both cloud microphysical and macrophysical properties ( [[IPCC:Wg1:Chapter:Chapter-7#7.3.3.2|Section 7.3.3.2]] ). By principle, MCB relies on ERFaci through the so-called Twomey effect ( [[#Twomey--1977|Twomey, 1977]] ), but ERFari may be of equal magnitude as shown in studies that consider spraying of sea salt outside tropical marine cloud areas ( [[#Jones--2012|Jones and Haywood, 2012]] ; [[#Partanen--2012|Partanen et al., 2012]] ; [[#Alterskjaer--2013|Alterskjaer and Kristjánsson, 2013]] ; [[#Ahlm--2017|Ahlm et al., 2017]] ). The maximum negative ERF estimated from modelling is within the range of –5.4 to –0.8 W m <sup>–2</sup> (Latham et al. , 2008; Rasch et al. , 2009; Jones et al. , 2011; Partanen et al. , 2012; [[#Alterskjaer--2013|Alterskjaer and Kristjánsson, 2013]] ) . For dry sea salt, the ERF efficiency is estimated to be within the range of –3 to –10 W m <sup>–2</sup> /(Pg yr <sup>–1</sup> ), when emitted over tropical oceans in ESMs in the Geoengineering Intercomparison Project (GeoMIP; [[#Ahlm--2017|Ahlm et al., 2017]] ). Cloud-resolving models reveal the complex behaviour and response of stratocumulus clouds to seeding, in that the ERF efficiency depends on meteorological conditions, and the ambient aerosol composition, where lower background particle concentrations may increase the ERFaci efficiency ( [[#Wang--2011|Wang et al., 2011]] ). Seeding could suppress precipitation formation and drizzle, and hence increase the lifetime of clouds, preserving their cooling effect ( [[#Ferek--2000|Ferek et al., 2000]] ). In contrast, cloud lifetime could be decreased by making the smaller droplets more susceptible to evaporation. Modelling studies have shown that a positive ERFaci <sub></sub> (warming) could also result from seeding clouds with too large aerosols ( [[#Pringle--2012|Pringle et al., 2012]] ; [[#Alterskjaer--2013|Alterskjaer and Kristjánsson, 2013]] ). These individual and combined processes are not well understood, and may have a limited representation in models, or counteracting errors ( [[#Mülmenstädt--2018|Mülmenstädt and Feingold, 2018]] ), lending ''low'' to ''medium confidence'' to the ERF estimates.

Modelled ERFaci associated with cirrus cloud thinning (CCT) cover a wide range in the literature, and the maximum are of the order of –0.8 to –3.5 W m <sup>–2</sup> , though they are of ''low confidence'' , with some studies using more simplified representations ( [[#Mitchell--2009|Mitchell and Finnegan, 2009]] ; [[#Storelvmo--2013|Storelvmo et al., 2013]] ; [[#Kristjánsson--2015|Kristjánsson et al., 2015]] ; [[#Jackson--2016|Jackson et al., 2016]] ; [[#Muri--2018|Muri et al., 2018]] ; [[#Gasparini--2020|Gasparini et al., 2020]] ). ERFaci for CCT is mainly affected by particle seeding concentrations, with an optimum around 20 L <sup>–1</sup> , according to limited evidence from models ( [[#Storelvmo--2013|Storelvmo et al., 2013]] ). Seeding leading to higher particle concentrations could lead to a warming ( [[#Storelvmo--2013|Storelvmo et al., 2013]] ; [[#Penner--2015|Penner et al., 2015]] ; [[#Gasparini--2016|Gasparini and Lohmann, 2016]] ). The lack of representation of processes related to, for example, heterogeneous and homogeneous freezing and their prevalence, is a dominant source of uncertainty in ERF estimates, in addition to less research activity.

In summary, the aerosol and cloud microphysics involved with SRM are not well understood, notably due to insufficient (and varying degrees of) representation of relevant processes in models. ERF of up to several W m <sup>–2</sup> is reported in the literature, with SAI at the higher end and CCT with lower potentials, though it remains a challenge to establish ERF potentials and efficacies with confidence. Modelling studies have been published with more sophisticated treatment of SRM since AR5, but the uncertainties, such as cloud–aerosol radiation interactions, remain large ( ''high confidence'' ).

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