Editing IPCC:AR6/SR15/Chapter-2 (section)

==== Changes and uncertainties in effective radiative forcings (ERF) for one 1.5°C-consistent pathway (SSP2-19) as estimated by MAGICC and FAIR. ====

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The lines are indicative of the total effective radiative forcing from all anthropogenic sources (solid lines) and for non-CO <sub>2</sub> agents only (dashed lines), as represented by MAGICC (red) and FAIR (blue) relative to 2010, respectively. Vertical bars show the mean radiative forcing as predicted by MAGICC and FAIR of relevant non-CO <sub>2</sub> agents for year 2030, 2050 and 2100. The vertical lines give the uncertainty (1 standard deviation) of the ERFs for the represented species.

Original Creation for this Report using the SR15 scenario database

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For mitigation pathways that aim at halting and reversing radiative forcing increase during this century, the aerosol radiative forcing is a considerable source of uncertainty (Figure 2.2) (Samset et al., 2018; Smith et al., 2018) <sup>[[#fn:r46|46]]</sup> . Indeed, reductions in SO <sub>2</sub> (and NO <sub>x</sub> ) emissions largely associated with fossil-fuel burning are expected to reduce the cooling effects of both aerosol radiative interactions and aerosol cloud interactions, leading to warming (Myhre et al., 2013; Samset et al., 2018) <sup>[[#fn:r47|47]]</sup> . A multimodel analysis (Myhre et al., 2017) <sup>[[#fn:r48|48]]</sup> and a study based on observational constraints (Malavelle et al., 2017) <sup>[[#fn:r49|49]]</sup> largely support the AR5 best estimate and uncertainty range of aerosol forcing. The partitioning of total aerosol radiative forcing between aerosol precursor emissions is important (Ghan et al., 2013; Jones et al., 2018; Smith et al., 2018) <sup>[[#fn:r50|50]]</sup> as this affects the estimate of the mitigation potential from different sectors that have aerosol precursor emission sources. The total aerosol effective radiative forcing change in stringent mitigation pathways is expected to be dominated by the effects from the phase-out of SO <sub>2</sub> , although the magnitude of this aerosol-warming effect depends on how much of the present-day aerosol cooling is attributable to SO <sub>2</sub> , particularly the cooling associated with aerosol–cloud interaction (Figure 2.2). Regional differences in the linearity of aerosol–cloud interactions (Carslaw et al., 2013; Kretzschmar et al., 2017) <sup>[[#fn:r51|51]]</sup> make it difficult to separate the role of individual precursors. Precursors that are not fully mitigated will continue to affect the Earth system. If, for example, the role of nitrate aerosol cooling is at the strongest end of the assessed IPCC AR5 uncertainty range, future temperature increases may be more modest if ammonia emissions continue to rise (Hauglustaine et al., 2014) <sup>[[#fn:r52|52]]</sup> .

Figure 2.2 shows that there are substantial differences in the evolution of estimated effective radiative forcing of non-CO <sub>2</sub> forcers between MAGICC and FAIR. These forcing differences result in MAGICC simulating a larger warming trend in the near term compared to both the FAIR model and the recent observed trends of 0.2°C per decade reported in Chapter 1 (Figure 2.1, Supplementary Material 2.SM.1.1, Chapter 1, Section 1.2.1.3). The aerosol effective forcing is stronger in MAGICC compared to either FAIR or the AR5 best estimate, though it is still well within the AR5 uncertainty range (Supplementary Material 2.SM.1.1.1). A recent revision (Etminan et al., 2016) <sup>[[#fn:r53|53]]</sup> increases the methane forcing by 25%. This revision is used in the FAIR but not in the AR5 setup of MAGICC that is applied here. Other structural differences exist in how the two models relate emissions to concentrations that contribute to differences in forcing (see Supplementary Material 2.SM.1.1.1).

Non-CO <sub>2</sub> climate forcers exhibit a greater geographical variation in radiative forcings than CO <sub>2</sub> , which leads to important uncertainties in the temperature response <sub> </sub> (Myhre et al., 2013) <sup>[[#fn:r54|54]]</sup> . This uncertainty increases the relative uncertainty of the temperature pathways associated with low emission scenarios compared to high emission scenarios (Clarke et al., 2014) <sup>[[#fn:r55|55]]</sup> . It is also important to note that geographical patterns of temperature change and other climate responses, especially those related to precipitation, depend significantly on the forcing mechanism (Myhre et al., 2013; Shindell et al., 2015; Marvel et al., 2016; Samset et al., 2016) <sup>[[#fn:r56|56]]</sup> (see also Chapter 3, Section 3.6.2.2).

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