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

=== 4.6.2 Climate Goals, Overshoot, and Path-Dependence ===

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Many scenarios aiming at limiting warming by 2100 to 1.5°C involve overshoot – ERF temporarily exceeds a certain level before peaking and declining again (Annex VII: Glossary). To quantify the implications of any such overshoot, this subsection assesses reversibility of climate due to temporary overshoot of GSAT levels during the 21st century, and implications for the use of carbon budgets. It also assesses differences in climate outcomes under different pathways, with a focus on comparing the SSPs used in CMIP6 with the RCPs used in CMIP5.

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==== 4.6.2.1 Climate Change Under Overshoot ====

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The SR1.5 ( [[#IPCC--2018b|IPCC, 2018b]] ) concluded with ''high confidence'' that overshoot trajectories ‘result in higher impacts and associated challenges compared to pathways that limit global warming to 1.5°C with no or limited overshoot’. The degree and duration of overshoot affects the risks and impacts likely to be experienced ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ) and the emissions pathway required to achieve it ( [[#Akimoto--2018|Akimoto et al., 2018]] ). Consequences relating to ice sheets and climatic extremes have been found to be greater at 2°C of global warming than at 1.5°C ( [[#Schleussner--2016|Schleussner et al., 2016]] ; [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ) but even on recovery to lower temperatures, these effects may not reverse. Overshoot has been found to lead to irreversible changes in thermosteric sea level ( [[#Tokarska--2015|Tokarska and Zickfeld, 2015]] ; [[#Palter--2018|Palter et al., 2018]] ; [[#Tachiiri--2019|Tachiiri et al., 2019]] ), AMOC ( [[#Palter--2018|Palter et al., 2018]] ), ice sheets, and permafrost carbon (Sections 4.7.2 and 5.4.9) and to long-lasting effects on ocean heat ( [[#Tsutsui--2006|Tsutsui et al., 2006]] ). Abrupt changes and tipping points are not well understood, but the higher the warming level and the longer the duration of overshoot, the greater the risk of unexpected changes ( [[#4.7.2|Section 4.7.2]] ). Non-reversal of the hydrological cycle has also been found in some studies with an increase in global precipitation following CO <sub>2</sub> decrease being attributed to a build-up of ocean heat ( [[#Wu--2010|Wu et al., 2010]] ), and to a fast atmospheric adjustment to CO <sub>2</sub> radiative forcing ( [[#Cao--2011|Cao et al., 2011]] ).

Global temperature is expected to remain approximately constant if emissions of CO <sub>2</sub> were to cease ( [[#4.7.1.1|Section 4.7.1.1]] ), and so reductions in GSAT are only possible in the event of net negative global CO <sub>2</sub> emissions. We assess here results from an overshoot scenario (SSP5-3.4-OS; [[#O’Neill--2016|O’Neill et al., 2016]] ), which explores the implications of a peak and decline in forcing during the 21st century. Reversibility under more extreme and idealized carbon dioxide removal (CDR) scenarios is assessed in [[#4.6.3|Section 4.6.3]] . In SSP5-3.4-OS, CO <sub>2</sub> peaks at 571 ppm in the year 2062 and reverts to 497 ppm by 2100 – approximately the same level as in 2040. SSP5-3.4-OS has strong net negative emissions of CO <sub>2</sub> , exceeding those in SSP1-2.6 and SSP1-1.9 from 2070 onwards and reaching –5.5 PgC yr <sup>–1</sup> (–20 GtCO <sub>2</sub> yr <sup>–1</sup> ) by 2100. While this causes global mean temperature to decline, changes in climate have not fully reversed by 2100 under this reversal of CO <sub>2</sub> concentration (Figure 4.34). Quantities are compared for 2081–2100 relative to a 20-year period (2034–2053) of the same average CO <sub>2</sub> . Differences between these two periods of the same CO <sub>2</sub> are: GSAT: 0.28 ± 0.30°C (mean ± standard deviation); global land precipitation: 0.026 ± 0.011 mm day <sup>–1</sup> ; September Arctic sea ice area: –0.32 ± 0.53 million km <sup>2</sup> ; thermosteric sea level: 12 ± 0.8 cm. As assessed in Section 9.3.1.1, Arctic sea ice area is linearly reversible with GSAT. Although these climate quantities are not fully reversible, the overshoot scenario results in reduced climate change compared with stabilisation or continued increase in greenhouse gases ( [[#Tsutsui--2006|Tsutsui et al., 2006]] ; [[#Palter--2018|Palter et al., 2018]] ; [[#Tachiiri--2019|Tachiiri et al., 2019]] ) ( ''high confidence'' ).

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[[File:61bb4e57a44ee1dcc8c841ad587e826e IPCC_AR6_WGI_Figure_4_34.png]]

'''Figure 4.34''' '''|''' '''Simulated changes in climate indices for SSP5-3.4-OS plotted against atmospheric CO''' <sub>2</sub> '''concentration (ppm) from 480 up to 571 and back to 496 by 2100. (a)''' Global surface air temperature change; '''(b)''' Global land precipitation change; '''(c)''' September Arctic sea ice area change; '''(d)''' Global thermosteric sea level change. Plotted changes are relative to the 2034–2053 mean which has same CO <sub>2</sub> as 2081–2100 mean (shaded grey bar). Red lines denote changes during the period up to 2062 when CO <sub>2</sub> is rising, blue lines denote changes after 2062 when CO <sub>2</sub> is decreasing again. Thick line is multi-model mean; thin lines and shading show individual models and complete model range. Numbers in square brackets indicate number of models used in each panel. Further details on data sources and processing are available in the chapter data table (Table 4.SM.1).

The transient climate response to cumulative CO <sub>2</sub> emissions, TCRE, allows climate policy goals to be associated with remaining carbon budgets as global temperature increase is near-linear with cumulative emissions (Section 5.5). Research since AR5 has shown that the concept of near-linearity of climate change to cumulative carbon emissions holds for measures other than just GSAT, such as regional climate ( [[#Leduc--2016|Leduc et al., 2016]] ) or extremes ( [[#Harrington--2016|Harrington et al., 2016]] ; [[#Seneviratne--2016|Seneviratne et al., 2016]] ). However, ocean heat and carbon uptake do exhibit path dependence, leading to deviation from the TCRE relationship for levels of overshoot above 300 PgC ( [[#Zickfeld--2016|Zickfeld et al., 2016]] ; [[#Tokarska--2019|Tokarska et al., 2019]] ). Sea level rise, loss of ice sheets, and permafrost carbon release may not reverse under overshoot and recovery of GSAT and cumulative emissions ( [[#4.7|Section 4.7]] ). TCRE remains a valuable concept to assess climate policy goals and how to achieve them but given the non-reversibility of different climate metrics with CO <sub>2</sub> and GSAT reductions, it has limitations associated with evaluating the climate response under overshoot scenarios and CO <sub>2</sub> removal ( ''medium confidence'' ).

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==== 4.6.2.2 Consistency Between Shared Socio-economic Pathways and Representative Concentration Pathways ====

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As CMIP5 and CMIP6 employed different scenario sets (RCPs and SSPs, respectively; see [[IPCC:Wg1:Chapter:Chapter-1#1.6.1.1|Section 1.6.1.1]] and Cross-Chapter Box 1.4), we assess how much of the differences in projections are due to the scenario change and how much due to model changes. The CMIP6-simulated GSAT increases tend to be larger than in CMIP5, for nominally comparable scenarios ( [[#4.3.1|Section 4.3.1]] ; [[#Tebaldi--2021|Tebaldi et al., 2021]] ).

The radiative forcing labels on SSP and RCP scenarios is approximate and enables the multiple climate forcings within the scenario to be characterized by a single number. While the scenarios are similar in terms of the stratospheric adjusted radiative forcing ( [[#Tebaldi--2021|Tebaldi et al., 2021]] ), they differ more in their effective radiative forcing (ERF). The combination of component forcings (CO <sub>2</sub> , non-CO <sub>2</sub> greenhouse gases, aerosols) within the scenario also differ ( [[#Meinshausen--2020|Meinshausen et al., 2020]] ). The ERF levels in the RCP and SSP scenarios have been calculated by sampling uncertainty in forcing from a range of different GHG species and aerosols (see 7.SM.1.4 for details). Figure 4.35 shows the time evolution and 2081–2100 mean across the families of scenarios and how this affects projections of GSAT. That the ERFs differ between corresponding SSP and RCP scenarios makes a comparison between CMIP6 and CMIP5 projections challenging ( [[#Tebaldi--2021|Tebaldi et al., 2021]] ). [[#Wyser--2020|Wyser et al. (2020)]] find the EC-Earth3-Veg model exhibits stronger radiative forcing and substantially greater warming under SSP5-8.5 than RCP8.5, and similar, but smaller additional warmings for SSP2-4.5and SSP1-2.6 compared with RCP4.5 and RCP2.6, respectively. In addition to the global response, climate can vary regionally due to non-CO <sub>2</sub> components of forcing ( [[#Samset--2016|Samset et al., 2016]] ; [[#Richardson--2018a|Richardson et al., 2018a]] , b).

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[[File:68e2a399ae3deaecc5953de3fef12860 IPCC_AR6_WGI_Figure_4_35.png]]

'''Figure''' '''4.35 |''' '''Comparison of RCPs and SSPs run by a single emulator to estimate scenario differences.''' Time series with 5–95% ranges and medians of '''(a)''' effective radiative forcings, calculated as described in Annex 7.A.1; and '''(b)''' global surface air temperature projections relative to 1850–1900 for the RCP and SSP scenarios from MAGICC 7.5. Note that the nameplate radiative forcing level refers to stratospheric adjusted radiative forcings in AR5-consistent settings ( [[#Tebaldi--2021|Tebaldi et al., 2021]] ) while ERFs may differ. MAGICC7.5 is here run in the recommended setup for WGIII, prescribing observed GHG concentrations for the historical period and switching to emissions-driven runs in 2015. Further details on data sources and processing are available in the chapter data table (Table 4.SM.1).

Emulators ( [[#cross-chapter-box-7.1|Cross-Chapter Box 7.1]] ) can be used to aid understanding of differences between generations of scenarios. The AR5 ( [[#Collins--2013|Collins et al., 2013]] ) explored the differences between CMIP3 and CMIP5 (their Figure 12.40). Here we use an emulator calibrated to AR6 assessed GSAT ranges, thus eliminating the effect of differences in the model ensembles, to analyse the differences between SSP and RCP scenarios. MAGICC7.5 in its WGIII-calibrated setup (see [[#cross-chapter-box-7.1|Cross-Chapter Box 7.1]] ) projects differences in 2081–2100 mean warming between the RCP2.6 and SSP1-2.6 scenarios of around 0.2°C, between RCP4.5 and SSP2-4.5 ofaround 0.3°C and between RCP8.5 and SSP5-8.5 of around 0.3°C (Figure 4.35b). The SSP scenarios also have a wider 5–95% range simulated by MAGICC7.5 explaining about half of the increased range seen when comparing CMIP5 and CMIP6 models. Higher climate sensitivity is, though, the primary reason behind the upper end of the warming for SSP5-8.5 reaching 1.5°C higher than the CMIP5 results. Compared with the differences between the CMIP5 and CMIP6 multi-model ensembles for the same scenario pairs (Table A6 in [[#Tebaldi--2021|Tebaldi et al., 2021]] ), the higher ERFs of the SSP scenarios contribute approximately half of the warmer CMIP6 SSP outcomes ( ''medium confidence'' ).

In summary, there is ''medium confidence'' that about half of the warming increase in CMIP6 compared to CMIP5 is due to higher climate sensitivity in CMIP6 models; the other half arises from higher ERF in nominally comparable scenarios (e.g., RCP8.5 and SSP5-8.5).

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