Editing IPCC:AR6/SR15/Chapter-4 (section)

== Cross-Chapter Box 10: Solar Radiation Modification in the Context of 1.5°C Mitigation Pathways ==

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====== Lead Authors ======

* Anastasia Revokatova (Russia)
* Heleen de Coninck (Netherlands)
* Piers Forster (United Kingdom)
* Veronika Ginzburg (Russia)
* Jatin Kala (Australia)
* Diana Liverman (United States)
* Maxime Plazzotta (France)
* Roland Séférian (France)
* Sonia I. Seneviratne (Switzerland)
* Jana Sillmann (Germany, Norway)

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Solar radiation modification (SRM) refers to a range of radiation modification measures not related to greenhouse gas (GHG) mitigation that seek to limit global warming (see Chapter 1, Section 1.4.1). Most methods involve reducing the amount of incoming solar radiation reaching the surface, but others also act on the longwave radiation budget by reducing optical thickness and cloud lifetime (see Table 4.7). In the context of this report, SRM is assessed in terms of its potential to limit warming below 1.5°C in temporary overshoot scenarios as a way to reduce elevated temperatures and associated impacts (Irvine et al., 2016; Keith and Irvine, 2016; Chen and Xin, 2017; Sugiyama et al., 2017a; Visioni et al., 2017a; MacMartin et al., 2018) <sup>[[#fn:r782|782]]</sup> . The inherent variability of the climate system would make it difficult to detect the efficacy or side-effects of SRM intervention when deployed in such a temporary scenario (Jackson et al., 2015) <sup>[[#fn:r783|783]]</sup> .

'''A. Potential SRM timing and magnitude'''

Published SRM approaches are summarized in Table 4.7. The timing and magnitude of potential SRM deployment depends on the temperature overshoot associated with mitigation pathways. All overshooting pathways make use of carbon dioxide removal. Therefore, if considered, SRM would only be deployed as a supplemental measure to large-scale carbon dioxide removal (Chapter 2, Section 2.3).

Cross-Chapter Box 10, Figure 1 below illustrates an example of how a hypothetical SRM deployment based on stratospheric aerosols injection (SAI) could be used to limit warming below 1.5°C using an ‘adaptive SRM’ approach (e.g., Kravitz et al., 2011; Tilmes et al., 2016) <sup>[[#fn:r784|784]]</sup> , where global mean temperature rise  exceeds 1.5°C compared to pre-industrial level by mid-century and returns below 1.5°C before 2100 with a 66% likelihood (see Chapter 2). In all such limited adaptive deployment scenarios, deployment of SRM only commences under conditions in which CO <sub>2</sub> emissions have already fallen substantially below their peak level and are continuing to fall. In order to hold warming to 1.5°C, a hypothetical SRM deployment could span from one to several decades, with the earliest possible threshold exceedance occurring before mid-century. Over this duration, SRM has to compensate for warming that exceeds 1.5°C (displayed with hatching on panel a) with a decrease in radiative forcing (panel b) which could be achieved with a rate of SAI varying between 0–5.9 MtSO <sub>2</sub> yr <sup>−</sup> <sup>1</sup> (panel c) (Robock et al., 2008; Heckendorn et al., 2009) <sup>[[#fn:r785|785]]</sup> .

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'''Cross-Chapter Box 10. Figure 1'''

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'''Evolution of hypothetical SRM deployment (based on stratospheric aerosols injection, or SAI) in the context of 1.5°C-consistent pathways.'''
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[[File:0562b84f76feea7ec004a3b76b3a4b5d Cross-Chapter-Box-10-Figure-1-1-1024x854.jpg]]

(a) Range of median temperature outcomes as simulated by MAGICC (see in Chapter 2, Section 2.2) given the range of CO <sub>2</sub> emissions and (b) other climate forcers for mitigation pathways exceeding 1.5°C at mid-century and returning below by 2100 with a 66% likelihood. Geophysical characteristics are represented by (c) the magnitude of radiative forcing and (d) the amount of stratospheric SO <sub>2</sub> injection that are required to keep the global median temperature below 1.5°C during the temperature overshoot (given by the blue hatching on panel a). SRM surface radiative forcing has been diagnosed using a mean cooling efficiency of 0.3°C (W− m2) of Plazzotta et al. (2018) <sup>[[#fn:r786|786]]</sup> . Magnitude and timing of SO <sub>2</sub> injection have been derived from published estimates of Heckendorn et al. (2009) <sup>[[#fn:r787|787]]</sup> and Robock et al. (2008) <sup>[[#fn:r788|788]]</sup> .

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SAI is the most-researched SRM method, with ''high agreement'' that it could limit warming to below 1.5°C (Tilmes et al., 2016; Jones et al., 2018) <sup>[[#fn:r789|789]]</sup> . The response of global temperature to SO <sub>2 </sub> injection, however, is uncertain and varies depending on the model parametrization and emission scenarios (Jones et al., 2011; Kravitz et al., 2011; Izrael et al., 2014; Crook et al., 2015; Niemeier and Timmreck, 2015; Tilmes et al., 2016; Kashimura et al., 2017) <sup>[[#fn:r790|790]]</sup> . Uncertainty also arises due to the nature and the optical properties of injected aerosols.

Other approaches are less well researched, but the literature suggests that ground-based albedo modification (GBAM), marine cloud brightening (MCB) or cirrus cloud thinning (CCT) are not assessed to be able to substantially reduce overall global temperature (Irvine et al., 2011; Seneviratne et al., 2018) <sup>[[#fn:r791|791]]</sup> . However, these SRM approaches are known to create spatially heterogeneous forcing and potentially more spatially heterogeneous climate effects, which may be used to mitigate regional climate impacts. This may be of most relevance in the case of GBAM when applied to crop and urban areas (Seneviratne et al., 2018) <sup>[[#fn:r792|792]]</sup> . Most of the literature on regional mitigation has focused on GBAM in relationship with land-use and land-cover change scenarios. Both models and observations suggest that there is a ''high agreement'' that GBAM would result in cooling over the region of changed albedo, and in particular would reduce hot extremes (Irvine et al., 2011; Akbari et al., 2012; Jacobson and Ten Hoeve, 2012; Davin et al., 2014; Crook et al., 2015, 2016; Alkama and Cescatti, 2016; Seneviratne et al., 2018) <sup>[[#fn:r793|793]]</sup> . In comparison, there is a ''limited evidence'' on the ability of MCB or CCT to mitigate regional climate impacts of 1.5°C warming because the magnitude of the climate response to MCB or CCT remains uncertain and the processes are not fully understood (Lohmann and Gasparini, 2017) <sup>[[#fn:r794|794]]</sup> .

'''B. General consequences and impacts of solar radiation modification'''

It has been proposed that deploying SRM as a supplement to mitigation may reduce increases in global temperature-related extremes and rainfall intensity, and lessen the loss of coral reefs from increasing sea-surface temperatures (Keith and Irvine, 2016) <sup>[[#fn:r795|795]]</sup> , but it would not address, or could even worsen (Tjiputra et al., 2016) <sup>[[#fn:r796|796]]</sup> , negative effects from continued ocean acidification.

Another concern with SRM is the risk of  a ‘termination shock’ or ‘termination effect’ when suddenly stopping SRM, which might cause rapid temperature rise and associated impacts (Jones et al., 2013; Izrael et al., 2014; McCusker et al., 2014) <sup>[[#fn:r797|797]]</sup> , most noticeably biodiversity loss (Trisos et al., 2018) <sup>[[#fn:r798|798]]</sup> . The severity of the termination effect has recently been debated (Parker and Irvine, 2018) <sup>[[#fn:r799|799]]</sup> and depends on the degree of SRM cooling. This report only considers limited SRM in the context of mitigation pathways to 1.5°C. Other risks of SRM deployment could be associated with the lack of testing of the proposed deployment schemes (e.g., Schäfer et al., 2013) <sup>[[#fn:r800|800]]</sup> . Ethical aspects and issues related to the governance and economics are discussed in Section 4.3.8.

'''C. Consequences and impacts of SRM on the carbon budget'''

Because of its effects on surface temperature, precipitation and surface shortwave radiation, SRM would also alter the carbon budget pathways to 1.5°C or 2°C (Eliseev, 2012; Keller et al., 2014; Keith et al., 2017; Lauvset et al., 2017) <sup>[[#fn:r801|801]]</sup> .

Despite the large uncertainties in the simulated climate response to SRM, current model simulations suggest that SRM would lead to altered carbon budgets compatible with 1.5°C or 2°C. The 6 CMIP5 models investigated simulated an increase of natural carbon uptake by land biosphere and, to a smaller extent, by the oceans ( ''high agreement'' ). The multimodel mean of this response suggests an increase of the RCP4.5 carbon budget of about 150 GtCO <sub>2</sub> after 50 years of SO <sub>2</sub> injection with a rate of 4 TgS yr <sup>−</sup> <sup>1</sup> , which represents about 4 years of CO <sub>2</sub> emissions at the current rate (36 GtCO <sub>2</sub> yr <sup>−</sup> <sup>1</sup> ). However, there is uncertainty around quantitative determination of the effects that SRM or its cessation has on the carbon budget due to a lack of understanding of the radiative processes driving the global carbon cycle response to SRM (Ramachandran et al., 2000; Mercado et al., 2009; Eliseev, 2012; Xia et al., 2016) <sup>[[#fn:r802|802]]</sup> , uncertainties about how the carbon cycle will respond to termination effects of SRM, and uncertainties in climate–carbon cycle feedbacks (Friedlingstein et al., 2014) <sup>[[#fn:r803|803]]</sup> .

''' D. ''' '''Sustainable development and SRM'''

There are few studies investigating potential implications of SRM for sustainable development. These are based on a limited number of scenarios and hypothetical considerations, mainly referring to benefits from lower temperatures (Irvine et al., 2011; Nicholson, 2013; Anshelm and Hansson, 2014; Harding and Moreno-Cruz, 2016) <sup>[[#fn:r804|804]]</sup> . Other studies suggest negative impacts from SRM implementation concerning issues related to regional disparities (Heyen et al., 2015) <sup>[[#fn:r805|805]]</sup> , equity (Buck, 2012) <sup>[[#fn:r806|806]]</sup> , fisheries, ecosystems, agriculture, and termination effects (Robock, 2012; Morrow, 2014; Wong, 2014) <sup>[[#fn:r807|807]]</sup> . If SRM is initiated by the richer nations, there might be issues with local agency, and possibly worsening conditions for those suffering most under climate change (Buck et al., 2014) <sup>[[#fn:r808|808]]</sup> . In addition, ethical issues related to testing SRM have been raised (e.g., Lenferna et al., 2017) <sup>[[#fn:r809|809]]</sup> . Overall, there is ''high agreement'' that SRM would affect many development issues but ''limited evidence'' on the degree of influence, and how it manifests itself across regions and different levels of society.

'''E. Overall feasibility of SRM'''

If mitigation efforts do not keep global mean temperature below 1.5°C, SRM can potentially reduce the climate impacts of a temporary temperature overshoot, in particular extreme temperatures, rate of sea level rise and intensity of tropical cyclones, alongside intense mitigation and adaptation efforts. While theoretical developments show that SRM is technically feasible (see Section 4.3.8.2), global field experiments have not been conducted and most of the knowledge about SRM is based on imperfect model simulations and some natural analogues. There are also considerable challenges to the implementation of SRM associated with disagreements over the governance, ethics, public perception, and distributional development impacts (see Section 4.3.8) (Boyd, 2016; Preston, 2016; Asayama et al., 2017; Sugiyama et al., 2017b; Svoboda, 2017; McKinnon, 2018; Talberg et al., 2018) <sup>[[#fn:r810|810]]</sup> . Overall, the combined uncertainties surrounding the various SRM approaches, including technological maturity, physical understanding, potential impacts, and challenges of governance, constrain the ability to implement SRM in the near future.

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