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

=== 4.4.4 Response to Short-lived Climate Forcers and Volcanic Eruptions ===

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Mitigation of SLCFs affects future climate projections and could alter the time of emergence of anthropogenic climate change signals. The AR5 assessed that emission reductions aimed at decreasing local air pollution could have a near-term warming impact on climate (''high confidence'') ([[#Kirtman--2013|Kirtman et al., 2013]]). Because of their shorter lifetimes, reductions in emissions of SLCF species mainly influence near-term GSAT trends ([[#Chalmers--2012|Chalmers et al., 2012]] ; [[#Shindell--2017|Shindell et al., 2017]] ; [[#Shindell--2019|Shindell and Smith, 2019]]), but on decadal time scales the near-term response to even very large reductions in SLCFs may be difficult to detect in the presence of large internal climate variability ([[#Samset--2020|Samset et al., 2020]]). The changes in SLCF emissions during the COVID-19 pandemic has resulted in a small net radiative forcing without a discernible impact on GSAT (Cross-Chapter Box 6.1). SLCF mitigation also leads to a higher GSAT in the mid- to long-term ([[#Smith--2013|Smith and Mizrahi, 2013]] ; [[#Stohl--2015|Stohl et al., 2015]] ; [[#Hienola--2018|Hienola et al., 2018]]) and can influence peak warming during the 21st century ([[#Rogelj--2014|Rogelj et al., 2014]] ; [[#Hienola--2018|Hienola et al., 2018]]). This section focuses on the total effect of SLCF changes on GSAT projections in the SSP scenarios. A more detailed breakdown of the separate climate effects of SLCF species and precursor species can be found in Sections 6.7.2 and 6.7.3.

A model experiment based on the SSP3-7.0 scenario with aerosols, their precursors, and non-methane tropospheric ozone precursors set to SSP1-1.9 abundances (SSP3-7.0-lowSLCF-highCH4; [[#Collins--2017|Collins et al., 2017]]) shows a projected multi-model mean GSAT anomaly that is higher by 0.22°C at mid-century (2045-2054) compared to SSP3-7.0 (Figure 4.18; [[#Allen--2020|Allen et al., 2020]]), but this difference is smaller than the inter-model spread of the SSP3-7.0 projections based on the CMIP6 models. Note the SSP3-7.0-lowSLCF-highCH4 experiment does not perturb methane from SSP3-7.0 concentrations. A modified SSP3-7.0-lowSLCF-lowCH4 scenario that also includes methane mitigation shows a lower GSAT by mid-century compared to SSP3-7.0 ([[#Allen--2021|Allen et al., 2021]]).

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[[File:b69103b33e1f4d30dd6d8b7549058f46 IPCC_AR6_WGI_Figure_4_18.png]]

'''Figure 4.18 |''' '''Influence of SLCFs on projected GSAT change.''' Change is shown relative to the 1995–2014 average (left axis) and relative to the 1850–1900 average (right axis). The comparison is for CMIP6 models for the AerChemMIP ([[#Collins--2017|Collins et al., 2017]]) SSP3-7.0-lowSLCF-highCH4 experiment (red dashed; note in the original experiment protocol this is called SSP3-7.0-lowNTCF), where concentrations of short-lived species are reduced compared to reference SSP3-7.0 scenario (red solid). Black shows the historical simulation until 2014 for the same 9 models as the projections. The curves show averages over the r1 simulations contributed to the CMIP6 exercise, the shadings around the historical and SSP3-7.0 curves shows 5–95% ranges and the numbers near the top show the number of model simulations.

Building on CMIP6 results for the effects of reducing SLCF emissions from a baseline of SSP3-7.0, the overall contribution of SLCFs to GSAT changes in the marker SSPs are now quantified using a simple climate model emulator. For consistency with Section 6.7.2 and Figure 6.22, the basket of SLCF compounds considered includes aerosols, ozone, methane, black carbon on snow and hydrofluorocarbons (HFCs) with lifetimes of less than 50 years. In the five marker SSPs considered, the net effect of SLCFs contributes to a higher GSAT in the near, mid- and long term (Table 4.6 and Section 6.7.2). In the SSP1-1.9 and SSP1-2.6 scenarios, SLCFs contribute to a higher GSAT by a central estimate of around 0.3°C compared to 1995–2014 across the three-time horizons. In the long-term, the 0.3C warming due to SLCFs in SSP1-2.6 can be compared to the assessed ''very likely'' GSAT change for this period of 0.5°C–1.5°C ([[#4.3.4|Section 4.3.4]] and Table 4.5). The SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios all show a larger SLCF effect on GSAT in the long term relative to the near term. In SSP3-7.0, the long-term warming due to SLCFs by 0.7°C can be compared with the assessed ''very likely'' GSAT anomaly for this period of 2.0°C –3.7°C ([[#4.3.4|Section 4.3.4]]). In summary, it is ''very likely'' that changes in SLCFs contribute to an overall warmer GSAT over the near, mid- and long term in the five SSP scenarios considered (Table 4.6, Section 6.7.2 and Figure 6.22).

In addition to effects on GSAT, SLCFs affect other aspects of the global climate system (Section 6.7.2). The additional warming at high northern latitudes associated with projected reductions in aerosol emissions over the 21st century leads to a more rapid reduction in Arctic sea ice extent in the RCP scenarios ([[#Gagné--2015|Gagné et al., 2015]]). Furthermore, mitigation of non-methane SLCFs in the SSP3-7.0-lowSLCF-highCH4 scenario causes an increase in global mean precipitation, with larger regional changes in southern and eastern Asia ([[#Allen--2020|Allen et al., 2020]]).

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'''Table''' '''4.6 |''' '''The net effect of SLCFs on GSAT change.''' Changes in 20-year averaged GSAT relative to 1995–2014 for 2021–2040, 2041–2060, and 2081–2100 for the five marker SSP scenarios. Values give the median and, in parentheses, the 5–95% range calculated from a 2237-member ensemble of the two-layer emulator that is driven with the ERF projections, including uncertainties, described in [[IPCC:Wg1:Chapter:Chapter-7|Chapter 7]] Supplementary Material 7.SM.1.4. The ensemble is constrained to assessed ranges of ECS, TCR, ocean heat content change, GSAT response, and carbon cycle metrics (Section 7.3.5; [[IPCC:Wg1:Chapter:Chapter-7|Chapter 7]] Supplementary Material 7.SM.2.2). The GSAT contribution of individual forcer responses use the difference between parallel runs of the constrained two-layer model with all anthropogenic forcing and all anthropogenic forcing with the component of interest (e.g., methane) removed ([[IPCC:Wg1:Chapter:Chapter-7|Chapter 7]] Supplementary Material 7.SM.2.3). Values are given to one decimal place.

{| class="wikitable"
|-
| '''Time Period'''

| '''SSP1-1.9 (°C)'''

| '''SSP1-2.6 (°C)'''

| '''SSP2-4.5 (°C)'''

| '''SSP3-7.0 (°C)'''

| '''SSP5-8.5 (°C)'''

|-
| Near Term (2021–2040)

| 0.2 (0.1, 0.3)

| 0.2 (0.1, 0.3)

| 0.2 (0.1, 0.3)

| 0.2 (0.1, 0.3)

| 0.3 (0.2, 0.4)

|-
| Mid-Term (2041–2060)

| 0.2 (0.0, 0.4)

| 0.2 (0.0, 0.4)

| 0.3 (0.2, 0.4)

| 0.3 (0.2, 0.4)

| 0.5 (0.3, 0.7)

|-
| Long Term (2081–2100)

| 0.1 (-0.1, 0.4)

| 0.2 (0.0, 0.4)

| 0.3 (0.1, 0.6)

| 0.5 (0.4, 0.8)

| 0.7 (0.4, 1.0)

|}

The main uncertainties in climate effects of SLCFs in the future come from: (i) the uncertainty in anthropogenic aerosol ERF (Section 7.3.3); (ii) uncertainty in the relative emissions of different SLCFs that have warming and cooling effects in the current climate (Section 6.2); and (iii) physical uncertainty including the efficacy of the climate response to SLCFs compared to long-lived GHGs ([[#Marvel--2016|Marvel et al., 2016]] ; [[#Richardson--2019|Richardson et al., 2019]]). One example of physical uncertainty is that the shortwave radiative forcing from methane was neglected in previous calculations ([[#Etminan--2016|Etminan et al., 2016]] ; [[#Collins--2018|Collins et al., 2018]]), which affects understanding of present day and future methane ERF ([[#Modak--2018|Modak et al., 2018]]). Another example of physical uncertainty is projected changes in lightning-NO <sub>x</sub> production, which contribute to future ozone radiative forcing ([[#Banerjee--2014|Banerjee et al., 2014]] , 2018; [[#Finney--2018|Finney et al., 2018]]).

Another factor that could substantially alter projections in the near-term would be the occurrence of a large explosive volcanic eruption, or even a decadal to multi-decadal sequence of small-to-moderate volcanic eruptions as witnessed over the early 21st century ([[#cross-chapter-box-4.1|Cross-Chapter Box 4.1]] ; [[#Santer--2014|Santer et al., 2014]]). An eruption similar to the last large tropical eruption, Mount Pinatubo in the Philippines in June 1991, is expected to cause substantial Northern Hemisphere (NH) cooling, peaking between 0.09°C and 0.38°C and lasting for three to five years, as indicated by climate model simulations over the past millennium (e.g., [[#Jungclaus--2010|Jungclaus et al., 2010]]). Phase 3 of Paleoclimate Modelling Intercomparison Project (PMIP3) simulated a significant NH cooling in response to individual volcanic events (peaks between 0.1°C and 0.5°C, depending on model, during the first year after the eruption) that lasts for three to five years. On a regional scale, the double volcanic events that occurred in 536 and 540 CE resulted in a cooling of 2°C ([[#Buntgen--2016|Büntgen et al., 2016]] ; [[#Toohey--2016|Toohey et al., 2016]]).

Since AR5, there has been growing progress in understanding the climate impacts of volcanic eruptions. Volcanic forcing is regarded as the dominant driver of forced variability in preindustrial surface air temperature ([[#Schurer--2013|Schurer et al., 2013]] , 2014). Large eruptions in the tropics and high latitudes were primary drivers of interannual-to-decadal temperature variability in the Northern Hemisphere during the past 2,500 years, with cooling persisting for up to ten years after some of the largest eruptive episodes ([[#Sigl--2015|Sigl et al., 2015]]). Repeated clusters of volcanic eruptions can induce a net negative radiative forcing that results in a centennial- and global-scale cooling trend via a decline in mixed-layer oceanic heat content ([[#McGregor--2015|McGregor et al., 2015]]). The response to multi-decadal changes in volcanic forcing (representing clusters of eruptions) shows similar cooling in both simulations and reconstructions of NH temperature. Volcanic eruptions generally result in decreased global precipitation for up to a few years following the eruption ([[#Iles--2014|Iles and Hegerl, 2014]] , 2015; [[#Man--2014|Man et al., 2014]]), with climatologically wet regions drying and climatologically dry regions wetting (''medium confidence''), which is opposite to the response under global warming ([[#Held--2006|Held and Soden, 2006]] ; [[#Iles--2013|Iles et al., 2013]] ; [[#Zuo--2019a|Zuo et al., 2019a]] , b). El Niño-like warming appears after large volcanic eruptions, as seen in both observations ([[#Adams--2003|Adams et al., 2003]] ; [[#McGregor--2010|McGregor et al., 2010]] ; [[#Khodri--2017|Khodri et al., 2017]]) and climate model simulations ([[#Ohba--2013|Ohba et al., 2013]] ; [[#Pausata--2015|Pausata et al., 2015]] ; [[#Colose--2016|Colose et al., 2016]] ; [[#Stevenson--2016|Stevenson et al., 2016]] ; [[#Khodri--2017|Khodri et al., 2017]] ; [[#Predybaylo--2017|Predybaylo et al., 2017]] ; [[#Zuo--2018|Zuo et al., 2018]]). The large tropical eruptions are coincident with positive Indian Ocean dipole events ([[#Maher--2015|Maher et al., 2015]]).

In AR5, uncertainty due to future volcanic activity was not considered in the assessment of the CMIP5 21st century climate projections ([[#Taylor--2012|Taylor et al., 2012]] ; [[#O’Neill--2016|O’Neill et al., 2016]]). Since AR5, there has been considerable progress in quantifying the impacts of volcanic eruptions on decadal climate prediction and longer-term climate projections ([[#Meehl--2015|Meehl et al., 2015]] ; [[#Swingedouw--2015|Swingedouw et al., 2015]] , 2017; [[#Timmreck--2016|Timmreck et al., 2016]] ; [[#Bethke--2017|Bethke et al., 2017]] ; [[#Illing--2018|Illing et al., 2018]]). By exploring 60 possible volcanic futures under RCP4.5, it has been demonstrated that the inclusion of time-varying volcanic forcing may enhance climate variability on annual-to-decadal time scales ([[#Bethke--2017|Bethke et al., 2017]]). Consistent with a tropospheric cooling response, the change in ensemble spread in the volcanic cases is skewed towards lower GSAT relative to the non-volcanic cases ([[#cross-chapter-box-4.1|Cross-Chapter Box 4.1]] , Figure 1). In these simulations with multiple volcanic forcing futures there is: (i) an increase in the frequency of extremely cold individual years; (ii) an increased likelihood of decades with negative GSAT trend (decades with negative GSAT trends become 50% more commonplace); (iii) later anthropogenic signal emergence (the mean time at which the signal of global warming emerges from the noise of natural climate variability is delayed almost everywhere) (''high confidence''); and (iv) a 10% overall reduction in global land monsoon precipitation and a 20% overall increase in the ensemble spread ([[#Man--2021|Man et al., 2021]]).

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