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

=== 6.4.3 Climate Responses to SLCFs ===

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This section briefly discusses the climate response to SLCFs, in particular to changes in aerosols, and gathers complementary information and assessments from Chapters 3, 7, 8 and 10.

Warming or cooling atmospheric aerosols, such as BC and sulphate, can affect temperature and precipitation in distinct ways by modifying the shortwave and longwave radiation, the lapse rate of the troposphere, and influencing cloud microphysical properties ( [[IPCC:Wg1:Chapter:Chapter-10#10.1.4.1.4|Section 10.1.4]] , Box 8.1). An important distinction between scattering and absorbing aerosols is the opposing nature of their influences on circulation, clouds and precipitation, besides surface temperature as evident from the contrasting regional climate responses to regional aerosol emissions (e.g., [[#Lewinschal--2019|Lewinschal et al., 2019]] ; [[#Sand--2020|Sand et al., 2020]] ; also see Chapters 8 and 10).

On the global scale, as assessed in Chapter 3, anthropogenic aerosols have ''likely'' cooled GSAT since 1850–1900 driven by the negative aerosol forcing, while it is ''extremely likely'' that human-induced stratospheric ozone depletion has primarily driven stratospheric cooling between 1979 and the mid-1990s. Multiple modelling studies support the understanding that present-day emissions of SO <sub>2</sub> , a precursor for sulphate aerosols, are the dominant driver of near- surface air temperature responses in comparison to BC or OC even though, for some regions, BC forcing plays a key role (Baker et al. , 2015; Samset et al. , 2016; Stjern et al. , 2017; Zanis et al. , 2020) '''.''' Further, there is ''high confidence'' that the aerosol-driven cooling has led to detectable large-scale water-cycle changes since at least the mid-20th <sup></sup> century as assessed in Chapter 8. The overall effect of surface cooling from anthropogenic aerosols is to reduce global precipitation and alter large-scale atmospheric circulation patterns ( ''high confidence'' ), primarily driven by the cooling effects of sulphate aerosols ( [[IPCC:Wg1:Chapter:Chapter-8#8.2.1|Section 8.2.1]] ). In addition, there is ''high confidence'' that darkening of snow through the deposition of black carbon and other light-absorbing particles enhances snowmelt ( [[IPCC:Wg1:Chapter:Chapter-7#7.3.4.3|Section 7.3.4.3]] ; SROCC Chapter 3).

In AR5, there was ''low confidence'' in the overall understanding of climate response to spatially varying patterns of forcing, though there was ''medium'' to ''high confidence'' in some regional climate responses, such as the damped warming of the NH and shifting of the ITCZ from aerosols, and positive feedbacks enhancing the local response from high-latitude snow and ice albedo changes. Since AR5, the relationship between inhomogeneous forcing and climate response is better understood, providing further evidence of the climate influence of SLCFs (aerosols and ozone in particular) on global to regional scales ( [[#Collins--2013|Collins et al., 2013]] ; [[#Shindell--2015|Shindell et al., 2015]] ; [[#Aamaas--2017|Aamaas et al., 2017]] ; [[#Kasoar--2018|Kasoar et al., 2018]] ; [[#Persad--2018|Persad and Caldeira, 2018]] ; [[#Wilcox--2019|Wilcox et al., 2019]] ) which differ from the relatively homogeneous spatial influence from LLGHGs.

Large geographical variations in aerosol ERFs (Section 6.4.1) affect global and regional temperature responses ( [[#Myhre--2013|Myhre et al., 2013]] ; [[#Shindell--2015|Shindell et al., 2015]] ). Multi-model CMIP6 ensemble-mean results (Figure 6.13) show cooling over almost all areas of the globe in response to increases of aerosol and their precursor emissions from 1850 to the recent past (1995–2014). While the ERF has hotspots, the temperature response is more evenly distributed in line with the results of CMIP5 models including the temperature response to ozone changes ( [[#Shindell--2015|Shindell et al., 2015]] ). The ensemble-mean global mean surface temperature decreases by 0.66°C ± 0.51°C while decreasing by 0.97°C ± 0.54°C for the Northern Hemisphere and 0.34°C ± 0.2°C for the Southern Hemisphere. The zonal-mean temperature response is negative at all latitudes ( ''high confidence'' ) and becomes more negative with increasing latitude, with a maximum ensemble-mean decrease of around 2.7°C at northern polar latitudes. The zonal-mean response is not directly proportional to the zonal-mean forcing, especially in the Arctic where the temperature response is cooling while the local ERF is positive (Figure 6.10). This is consistent with prior studies showing that the Arctic, in particular, is highly sensitive to forcing at NH mid-latitudes (e.g., [[#Shindell--2009|Shindell and Faluvegi, 2009]] ; [[#Sand--2013a|Sand et al., 2013a]] ) and with results from CMIP5 models (more on the Arctic below; [[#Shindell--2015|Shindell et al., 2015]] ). Thus, there is ''high confidence'' that the temperature response to aerosols is more asymmetric than the response to WMGHGs and negative at all latitudes.

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[[File:06b25de61a738d01818e9556b9bc6b0b IPCC_AR6_WGI_Figure_6_13.png]]

'''Figure 6.13 |''' '''Multi-model mean surface air temperature response over the recent past (1995–2014) induced by aerosol changes since 1850.''' Calculation is based on the difference between CMIP6 ‘historical’ and AerChemMIP ‘hist-piAer’ experiments averaged over 1995–2014, where '''(a)''' is the spatial pattern of the annual mean surface air temperature response, and '''(b)''' is the mean zonally averaged response. Model means are derived from the years 1995–2014. Uncertainty is represented using the advanced approach: No overlay indicates regions with robust signal, where ≥66% of models show change greater than variability threshold and ≥80% of all models agree on sign of change; diagonal lines indicate regions with no change or no robust signal, where &lt;66% of models show a change greater than the variability threshold; crossed lines indicate regions with conflicting signal, where ≥66% of models show change greater than variability threshold and &lt;80% of all models agree on sign of change. For more information on the advanced approach, please refer to the Cross-Chapter Box Atlas.1. AerChemMIP models MIROC6, MRI-ESM2-0, NorESM2-LM, GFDL-ESM4, GISS-E2-1-G and UKESM1-0-LL are used in the analysis. Further details on data sources and processing are available in the chapter data table (Table 6.SM.3).

The asymmetric aerosol and greenhouse gas forcing on regional-scale climate responses have also been assessed to lead to contrasting effects on precipitation in Chapter 8. The asymmetric historical radiative forcing due to aerosols led to a southward shift in the tropical rain belt ( ''high confidence'' ) and contributed to the Sahel drought from the 1970s to the 1980s ( ''high confidence'' ). Furthermore, the asymmetry of the forcing led to contrasting effects in monsoon precipitation changes over West Africa, Southern Asia and Eastern Asia over much of the mid-20th <sup></sup> century due to GHG-induced precipitation increases counteracted by anthropogenic aerosol-induced decreases ( ''high confidence'' ) (see [[IPCC:Wg1:Chapter:Chapter-8#8.3|Section 8.3]] and Box 8.1).

The Arctic region is warming considerably faster than the rest of the globe ( [[IPCC:Wg1:Chapter:Atlas|Atlas]] 11.2.2) and, generally, studies indicate that this amplification of the temperature response toward the Arctic has an important contribution from local and remote aerosol forcing ( [[#Stjern--2017|Stjern et al., 2017]] ; [[#Westervelt--2018|Westervelt et al., 2018]] ). Several studies indicate that changes in long-range transport of sulphate and BC from northern mid-latitudes can potentially explain a significant fraction of Arctic warming since the 1980s (e.g., Navarro et al. , 2016; Breider et al. , 2017; Ren et al. , 2020) . Modelling studies show that changes in mid-latitude aerosols have influenced Arctic climate by changing the radiative balance through aerosol–radiation and aerosol–cloud interactions, and enhancing poleward heat transport ( [[#Navarro--2016|Navarro et al., 2016]] ; [[#Ren--2020|Ren et al., 2020]] ). Idealized aerosol-perturbation studies have shed further light on the sensitivity of Arctic temperature response to individual aerosol species. Studies show relatively large responses in the Arctic to BC perturbations and reveal the importance of remote BC forcing by rapid adjustments (Sand et al. , 2013b; Stjern et al. , 2017; L. Liu et al. , 2018; Yang et al. , 2019b) . Perturbations in SO <sub>2</sub> emissions over major emitting regions in the Northern Hemisphere have been shown to produce the largest Arctic temperature responses ( [[#Kasoar--2018|Kasoar et al., 2018]] ; [[#Lewinschal--2019|Lewinschal et al., 2019]] ).

The effects of changes in aerosols on local and remote changes in temperature, circulation and precipitation are sensitive to a number of model uncertainties affecting aerosol sources, transformation and resulting radiative efficacy. Therefore, regional climate effects in global model studies must be interpreted with caution. When investigating the climate response to regional aerosol emissions, such uncertainties are likely to be confounded even further by the variability between models in regional climate and circulation patterns, leading to greater inter-model spread at regional scales than at a global scale ( [[#Baker--2015|Baker et al., 2015]] ; [[#Kasoar--2016|Kasoar et al., 2016]] ).

In summary, over the historical period, changes in aerosols and their ERF have primarily contributed to cooling, partly masking the human-induced warming ( ''high confidence'' ). Radiative forcings induced by aerosol changes lead to both local and remote changes in temperature ( ''high confidence'' ). The temperature response preserves hemispheric asymmetry of the ERF but is more latitudinally uniform with strong amplification of the temperature response towards the Arctic ( ''medium confidence'' ).

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