Editing IPCC:Wg1:Chapter:Chapter-1-comments (section)

==== 1.6.1.4 The Likelihood of Reference Scenarios, Scenario Uncertainty and Storylines ====

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In general, no likelihood is attached to the scenarios assessed in this Report. The use of different scenarios for climate change projections allows the exploration of ‘scenario uncertainty’ ( [[#1.4.4|Section 1.4.4]] ; SR1.5; [[#Collins--2013|Collins et al., 2013]] ). Scenario uncertainty is fundamentally different from geophysical uncertainties, which result from limitations in the understanding and predictability of the climate system ( [[#Smith--2011|Smith and Stern, 2011]] ). In scenarios, by contrast, future emissions depend to a large extent on the collective outcome of choices and processes related to population dynamics and economic activity, or on choices that affect a given activity’s energy and emissions intensity ( [[#Jones--2000|Jones, 2000]] ; [[#Knutti--2008|Knutti et al., 2008]] ; [[#Kriegler--2012|Kriegler et al., 2012]] ; [[#van%20Vuuren--2014|van Vuuren et al., 2014]] ). Even if identical socio-economic futures are assumed, the associated future emissions still face uncertainties, since different experts and model frameworks diverge in their estimates of future emissions ranges ( [[#Ho--2019|Ho et al., 2019]] ).

When exploring various climate futures, scenarios with no, or no additional, climate policies are often referred to as ‘baseline’ or ‘reference scenarios’ ( [[#1.6.1.1|Section 1.6.1.1]] and Glossary). Among the five core scenarios used most in this report, SSP3-7.0 and SSP5-8.5 are explicit ‘no-climate-policy’ scenarios (Cross-Chapter Box 1.4, Table 1; [[#Gidden--2019|Gidden et al., 2019]] ), assuming a carbon price of zero. These future ‘baseline’ scenarios are hence counterfactuals that include fewer climate policies compared to ‘business-as-usual’ scenarios – given that ‘business-as-usual’ scenarios could be understood to imply a continuation of existing climate policies. Generally, future scenarios are meant to cover a broad range of plausible futures, due, for example to unforeseen discontinuities in development pathways ( [[#Raskin--2020|Raskin and Swart, 2020]] ), or to large uncertainties in underlying long-term projections of economic drivers ( [[#Christensen--2018|Christensen et al., 2018]] ). However, the likelihood of high-emissions scenarios such as RCP8.5 or SSP5-8.5 is considered low in light of recent developments in the energy sector ( [[#Hausfather--2020a|Hausfather and Peters, 2020a]] , b). Studies that consider possible future emissions trends in the absence of additional climate policies, such as the recent IEA 2020 World Energy Outlook ‘stated policy’ scenario ( [[#IEA--2020|IEA, 2020]] ), project approximately constant fossil fuel and industrial CO <sub>2</sub> emissions out to 2070, approximately in line with the intermediate RCP4.5, RCP6.0 and SSP2-4.5 scenarios ( [[#Hausfather--2020b|Hausfather and Peters, 2020b]] ) and the 2030 global emissions levels that are pledged as part of the Nationally Determined Contributions (NDCs) under the Paris Agreement ( [[#1.2.2|Section 1.2.2]] ; [[#Fawcett--2015|Fawcett et al., 2015]] ; [[#Rogelj--2016|Rogelj et al., 2016]] ; [[#UNFCCC--2016|UNFCCC, 2016]] ; [[#IPCC--2018|IPCC, 2018]] ). On the other hand, the default concentrations aligned with RCP8.5 or SSP5-8.5 and resulting climate futures derived by ESMs could be reached by lower emissions trajectories than RCP8.5 or SSP5-8.5. That is because the uncertainty range on carbon cycle feedbacks includes stronger feedbacks than assumed in the default derivation of RCP8.5 and SSP5-8.5 concentrations (Section 5.4; [[#Ciais--2013|Ciais et al., 2013]] ; [[#Friedlingstein--2014|Friedlingstein et al., 2014]] ; [[#Booth--2017|Booth et al., 2017]] ).

To address long-term scenario uncertainties, scenario storylines (or ‘narratives’) are often used (see [[#1.4.4|Section 1.4.4]] for a more general discussion on ‘storylines’, also covering ‘physical climate storylines’; [[#Rounsevell--2010|Rounsevell and Metzger, 2010]] ; [[#O’Neill--2014|O’Neill et al., 2014]] ). Scenario storylines are descriptions of a future world, and the related large-scale socio-economic development pathways towards that world that are deemed plausible within the current state of knowledge and historical experience ( [[#1.2.3|Section 1.2.3]] ; WGIII). Scenario storylines attempt to ‘stimulate, provoke, and communicate visions of what the future could hold for us’ ( [[#Rounsevell--2010|Rounsevell and Metzger, 2010]] ) in settings where either limited knowledge or inherent unpredictability in social systems prevent a forecast or numerical prediction. Scenario storylines have been used in previous climate research, and they are the explicit or implicit starting point of any scenario exercise, including for the SRES scenarios ( [[#IPCC--2000|IPCC, 2000]] ) and the SSPs (e.g., [[#O’Neill--2017a|O’Neill et al., 2017a]] ).

Recent technological or socio-economic trends might be informative for bounding near-term future trends, for example, if technological progress renders a mitigation technology cheaper than previously assumed. However, short-term emissions trends alone do not generally rule out an opposite trend in the future ( [[#van%20Vuuren--2010|van Vuuren et al., 2010]] ). The ranking of individual RCP emissions scenarios from the IAMs with regard to emissions levels is different for different time horizons, for example, 2020 compared with longer-term emissions levels. For example, the strongest climate change mitigation scenario, RCP2.6, was in fact the second highest CO <sub>2</sub> emissions scenario (jointly with RCP4.5) before 2020 in the set of RCPs and the strong global emissions decline in RCP2.6 only followed after 2020. Implicitly, this scenario feature was cautioning against the assumption that short-term trends predicate particular long-term trajectories. This is also the case in relation to the COVID-19 related drop in 2020 emissions. Potential changes in underlying drivers of emissions, such as those potentially incentivized by COVID-19 recovery stimulus packages, are more significant for longer-term emissions than the short-term deviation from recent emissions trends (Cross-Chapter Box 6.1 on COVID-19).

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'''Cross-Chapter Box 1.4 | The SSP Scenarios as Used in Workin''' '''g Group I (WGI)'''

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'''Contributing Authors:''' Jan S. Fuglestvedt (Norway), Celine Guivarch (France), Christopher Jones (United Kingdom), Malte Meinshausen (Australia/Germany), Zebedee R. J. Nicholls (Australia), Gian-Kasper Plattner (Switzerland), Keywan Riahi (Austria), Joeri Rogelj (United Kingdom/Belgium), Sophie Szopa (France), Claudia Tebaldi (United States of America), Anne-Marie Treguier (France), and Detlef van Vuuren (The Netherlands)

The nine new SSP emissions and concentrations scenarios (SSP1-1.9 to SSP5-8.5; Cross-Chapter Box 1.4, Table 1) offer unprecedented detail of input data for climate model simulations. They allow for a more comprehensive assessment of climate drivers and responses than has previously been available, in particular because some of the scenarios’ time series, (e.g., pollutants, emissions or changes in land use and land cover), are more diverse in the SSP scenarios than in the RCPs used in AR5 (Cross-Chapter Box 1.4, Figure 2; e.g., [[#Chuwah--2013|Chuwah et al., 2013]] ).

The core set of five illustrative SSP scenarios – SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 – was selected in this Report to align with the objective that the new generation of SSP scenarios should fill certain gaps identified in the RCPs. For example, a scenario assuming reduced air-pollution control and thus higher aerosol emissions was missing from the RCPs. Likewise, nominally the only ‘no-additional-climate-policy’ scenario in the set of RCPs was RCP8.5. The new SSP3-7.0 ‘no-additional-climate-policy’ scenario fills both these gaps. A very strong mitigation scenario in line with the 1.5°C goal of the Paris Agreement was also missing from the RCPs, and the SSP1-1.9 scenario now fills this gap, complementing the other strong mitigation scenario SSP1-2.6. The five core SSPs were also chosen to ensure some overlap with the RCP levels for radiative forcing at the year 2100 (specifically 2.6, 4.5, and 8.5; [[#O’Neill--2016|O’Neill et al., 2016]] ; [[#Tebaldi--2021|Tebaldi et al., 2021]] ), although effective radiative forcings are generally higher in the SSP scenarios compared to the equivalently named RCP pathways ( [[IPCC:Wg1:Chapter:Chapter-4#4.6.2|Section 4.6.2]] and Cross-Chapter Box 1.4, Figure 1). In theory, running scenarios with similar radiative forcings would permit analysis of the CMIP5 and CMIP6 outcomes for pairs of scenarios (e.g., RCP8.5 and SSP5-8.5) in terms of varying model characteristics rather than differences in the underlying scenarios. In practice, however, there are limitations to this approach (Sections 1.6.1.1 and 4.6.2).

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'''Cross-Chapter Box 1.4, Figure 1 |''' '''The SSP scenarios used in this Report, their indicative temperature evolution and radiative forcing categorization, and the five socio-economic storylines upon which they are built.''' The core set of scenarios used in this report – i.e., SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 – is shown together with an additional four SSPs that are part of ScenarioMIP, as well as previous RCP scenarios. In the '''left-hand panel''' , the indicative temperature evolution is shown (adapted from Meinshausen et al. , 2020) . The black stripes on the respective scenario family panels on the left-hand side indicate a larger set of IAM-based SSP scenarios that span the scenario range more fully, but are not used in this report. The SSP–radiative forcing matrix is shown on the '''right-hand panel''' , with the SSP socio-economic narratives shown as columns and the indicative radiative forcing categorization by 2100 shown as rows. Note that the descriptive labels for the five SSP narratives refer mainly to the reference scenario futures without additional climate policies. For example, SSP5 can accommodate strong mitigation scenarios leading to net zero emissions; these do not match a ‘fossil-fuelled development’ label. Further details on data sources and processing are available in the chapter data table (Table 1.SM.1).
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'''Cross-Chapter Box 1.4, Table 1 |'''

'''Overview of SSP scenarios used in this report.''' The middle column briefly describes the SSP scenarios and the right-hand column indicates the previous RCP scenarios that most closely match that SSP’s assessed global surface air temperature (GSAT) trajectory. RCP scenarios are generally found to result in larger modelled warming for the same nominal radiative forcing label ( [[IPCC:Wg1:Chapter:Chapter-4#4.6.2.2|Section 4.6.2.2]] ). The five core SSP scenarios used most commonly in this report are highlighted in bold . Further SSP scenarios are used where they allow assessment of specific aspects, e.g., air pollution policies in [[IPCC:Wg1:Chapter:Chapter-6|Chapter 6]] (SSP3-7.0-lowNTCF). RCPs are used in this report wherever the relevant scientific literature makes substantial use of regional or domain-specific model output that is based on these previous RCP pathways, such as sea level rise projections in [[IPCC:Wg1:Chapter:Chapter-9|Chapter 9]] (Section 9.6.3.1) or regional climate aspects in Chapters 10 and 12. See ( [[IPCC:Wg1:Chapter:Chapter-4|Chapter 4]] ( [[IPCC:Wg1:Chapter:Chapter-4#4.3.4|Section 4.3.4]] ) for the GSAT assessment for the SSP scenarios and [[IPCC:Wg1:Chapter:Chapter-4#4.6.2.2|Section 4.6.2.2]] for a comparison between SSPs and RCPs in terms of both radiative forcing and global surface temperature.
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{| class="wikitable"
|-
! '''SSPX-Y Scenario'''

! '''Description From an Emissions/Concentrations and Temperature Perspect''' '''ive (Table 4.2)'''

! '''Closes''' '''t RCP Scenarios'''

|-
| '''SSP1-1.9'''

| Holds warming to approximately 1.5°C above 1850–1900 in 2100 after slight overshoot (median) and implied net zero CO <sub>2</sub> emissions around the middle of the century.

| Not available. No equivalently low RCP scenario exists.

|-
| '''SSP1-2.6'''

| Stays below 2.0°C warming relative to 1850–1900 (median) with implied net zero CO <sub>2</sub> emissions in the second half of the century.

| RCP2.6, although RCP2.6 might be cooler for the same model settings.

|-
| SSP4-3.4

| A scenario between SSP1-2.6 and SSP2-4.5 in terms of end-of-century radiative forcing. It does not stay below 2.0°C in most CMIP6 runs (Chapter 4) relative to 1850–1900.

| No 3.4 level of end-of-century radiative forcing was available in the RCPs. Nominally SSP4-3.4 sits between RCP 2.6 and RCP 4.5, although SSP4-3.4 might be more similar to RCP4.5. Also, in the early decades of the 21st century, SSP4-3.4 is close to RCP6.0, which featured lower radiative forcing than RCP4.5 in those decades.

|-
| '''SSP2-4.5'''

| Scenario approximately in line with the upper end of aggregate NDC emissions levels by 2030 (Sections [[#1.2.2|1.2.2]] and [[IPCC:Wg1:Chapter:Chapter-4#4.3|4.3]] ; SR1.5, ( [[#IPCC--2018|IPCC, 2018]] ), Box 1). CO <sub>2</sub> emissions remaining around current levels until the middle of the century. The SR1.5 assessed temperature projections for NDCs to be between 2.7°C and 3.4°C by 2100 ( [[#1.2.2|Section 1.2.2]] ; SR1.5 ( [[#IPCC--2018|IPCC, 2018]] ); Cross-Chapter Box 11.1), corresponding to the upper half of projected warming under SSP2-4.5 (Chapter 4). New or updated NDCs by the end of 2020 did not significantly change the emissions projections up to 2030, although more countries adopted 2050 net zero targets in line with SSP1-1.9 or SSP1-2.6. The SSP2-4.5 scenario deviates mildly from a ‘no-additional-climate-policy’ reference scenario, resulting in a best-estimate warming around 2.7°C by the end of the 21st century relative to 1850–1900 (Chapter 4).

| RCP4.5 and, until 2050, also RCP6.0. Forcing in the latter was even lower than RCP4.5 in the early decades of the 21st century.

|-
| SSP4-6.0

| The end-of-century nominal radiative forcing level of 6.0 W m <sup>–2</sup> can be considered a ‘no-additional-climate-policy’ reference scenario, under SSP1 and SSP4 socio-economic development narratives.

| RCP6.0 is nominally closest in the second half of the century, although global mean temperatures are estimated to be generally lower in RCPs compared to SSPs. Furthermore, RCP6.0 features lower warming than SSP4-6.0, as it has very similar temperature projections compared to the nominally lower RCP4.5 scenario in the first half of the century.

|-
| '''SSP3-7.0'''

| An intermediate-to-high reference scenario resulting from no additional climate policy under the SSP3 socio-economic development narrative. CO <sub>2</sub> emissions roughly double from current levels by 2100. SSP3-7.0 has particularly high non-CO <sub>2</sub> emissions, including high aerosols emissions.

| Between RCP6.0 and RCP8.5, although SSP3-7.0 non-CO <sub>2</sub> emissions and aerosols are higher than in any of the RCPs.

|-
| SSP3-7.0-lowNTCF

| A variation of the intermediate-to-high reference scenario SSP3-7.0 but with mitigation of CH <sub>4</sub> and/or short-lived species such as black carbon and other short-lived climate forcers (SLCF). Note that variants of SSP3-7.0-lowNTCF differ in terms of whether CH <sub>4</sub> emissions are reduced <sup>a</sup> (Sections 4.4 and 6.6).

| SSP3-7.0-lowNTCF is between RCP6.0 and RCP8.5, as RCP scenarios generally incorporated a narrow and comparatively low level of SLCF emissions across the range of RCPs.

|-
| SSP5-3.4-OS (Overshoot)

| A mitigation-focused variant of SSP5-8.5 that initially follows unconstrained emissions growth in a fossil fuel-intensive setting until 2040 and then implements the largest net negative CO <sub>2</sub> emissions of all SSP scenarios in the second half of 21st century to reach SSP1-2.6 forcing levels in the 22nd century. Used to consider reversibility and strong overshoot scenarios in, or example, Chapters 4 and 5.

| Not available. Initially, until 2040, similar to RCP8.5.

|-
| '''SSP5-8.5'''

| A high-reference scenario with no additional climate policy. CO <sub>2</sub> emissions roughly double from current levels by 2050. Emissions levels as high as SSP5-8.5 are not obtained by integrated assessment models (IAMs) under any of the SSPs other than the fossil-fuelled SSP5 socio-economic development pathway.

| RCP8.5, although CO <sub>2</sub> emissions under SSP5-8.5 are higher towards the end of the century (Cross-Chapter Box 1.4, Figure 2). CH <sub>4</sub> emissions under SSP5-8.5 are lower than under RCP 8.5. When used with the same model settings, SSP5-8.5 may result in slightly higher temperatures than RCP8.5 ( [[IPCC:Wg1:Chapter:Chapter-4#4.6.2|Section 4.6.2]] ).

|}
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<sup>a</sup> The AerChemMIP variant of SSP3-7.0 -lowNTCF (Collins et al. , 2017) only reduced aerosol and ozone precursors compared to SSP3-7.0 , not methane. The SSP3-7.0-lowNTCF variant by the integrated assessment models also reduced methane emissions (Gidden et al. , 2019), which creates differences between SSP3-7.0-lowNTCF and SSP3-7.0 also in terms of methane concentrations and some fluorinated gas concentrations that have OH related sinks (Meinshausen et al., 2020).

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'''Cross-Chapter Box 1.4, Table 2 |'''

'''Overview of key climate forcer datasets used as input by ESMs for historical and future SSP scenario experiments.''' The data is available from the Earth System Grid Federation ( [[#ESGF--2021|ESGF, 2021]] ) described in [[#Eyring--2016|Eyring et al. (2016)]] .
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{| class="wikitable"
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| '''Climate Forcer'''

| '''Description'''

|-
| CO <sub>2</sub> Emissions (emissions-driven runs only)

| Harmonized historical and future gridded emissions of anthropogenic CO <sub>2</sub> emissions ( [[#Hoesly--2018|Hoesly et al., 2018]] ; [[#Gidden--2019|Gidden et al., 2019]] ) are used instead of the prescribed CO <sub>2</sub> concentrations. See ( [[IPCC:Wg1:Chapter:Chapter-4|Chapter 4]] ( [[IPCC:Wg1:Chapter:Chapter-4#4.3.1|Section 4.3.1]] ).

|-
| Historical and Future GHG Concentrations

| GHG surface air mole fractions of 43 species, including CO <sub>2</sub> , CH <sub>4</sub> , N <sub>2</sub> O, HFCs, PFCs, halons, HCFCs, CFCs, sulphur hexafluoride (SF <sub>6</sub> ), ammonia (NF <sub>3</sub> ), including latitudinal gradients and seasonality from year 1 to 2500 ( [[#Meinshausen--2017|Meinshausen et al., 2017]] , 2020).

|-
| Land-Use Change and Management Patterns

| Globally gridded land use- and land cover-change datasets ( [[#Hurtt--2020|Hurtt et al., 2020]] ; [[#Ma--2020|Ma et al., 2020]] )

|-
| Biomass Burning Emissions

| Historical fire-related gridded emissions, including sulphur dioxide (SO <sub>2</sub> ), nitrogen oxides (NO <sub>x</sub> ), carbon monoxide (CO), black carbon (BC), organic carbon (OC), NH <sub>3</sub> , non-methane volatile organic compounds (NMVOCs), relevant to concentration-driven historical and future SSP scenario runs ( [[#van%20Marle--2017|van Marle et al., 2017]] ).

|-
| Stratospheric and Tropospheric Ozone

| Historical and future ozone dataset, also with total column ozone ( [[#CCMI--2021|CCMI, 2021]] ).

|-
| Reactive Gas Emissions

| Gridded global anthropogenic emissions of reactive gases and aerosol precursors, including CO, SO <sub>x</sub> , CH <sub>4,</sub> NO <sub>x</sub> , NMVOCs, or NH <sub>3</sub> ( [[#Hoesly--2018|Hoesly et al., 2018]] ; [[#Feng--2020|Feng et al., 2020]] ).

|-
| Solar Forcing

| Radiative and particle input of solar variability from 1850 through to 2300 ( [[#Matthes--2017|Matthes et al., 2017]] ). Future variations in solar forcing also reflect long-term multi-decadal trends.

|-
| Volcanic Forcing

| Historical stratospheric aerosol climatology ( [[#Thomason--2018|Thomason et al., 2018]] ), with the mean stratospheric volcanic aerosol prescribed in future projections.

|}
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In contrast to stylized assumptions about the future evolution of emissions (e.g., a linear phase-out from year A to year B), these SSP scenarios are the result of a detailed scenario generation process (Sections 1.6.1.1 and 1.6.1.2). While IAMs produce internally consistent future-emissions time series for CO <sub>2</sub> , CH <sub>4</sub> , N <sub>2</sub> O, and aerosols for the SSP scenarios ( [[#Riahi--2017|Riahi et al., 2017]] ; [[#Rogelj--2018a|Rogelj et al., 2018a]] ), these emissions scenarios are subject to several processing steps for harmonization ( [[#Gidden--2018|Gidden et al., 2018]] ) and in-filling ( [[#Lamboll--2020|Lamboll et al., 2020]] ), before also being complemented by several datasets so that ESMs can run these SSPs ( [[#Durack--2018|Durack et al., 2018]] ; [[#Tebaldi--2021|Tebaldi et al., 2021]] ). Although five scenarios are the primary focus of WGI, a total of nine SSP scenarios have been prepared with all the necessary detail to drive the ESMs as part of the CMIP6 (Cross-Chapter Box 1.4, Figure 1 and Table 2).

ESMs are driven by either emissions or concentrations scenarios. Inferring concentration changes from emissions time series requires using carbon cycle and other gas cycle models. To aid comparability across ESMs, and in order to allow participation of ESMs that do not have coupled carbon and other gas cycle models in CMIP6, most of the CMIP6 ESM experiments are so-called ‘concentration-driven’ runs, with concentrations of CO <sub>2</sub> , CH <sub>4</sub> , N <sub>2</sub> O and other well-mixed GHGs prescribed in conjunction with aerosol emissions, ozone changes and effects from human-induced land-cover changes that may be radiatively active via albedo changes (Cross-Chapter Box 1.4, Figure 2). In these concentration-driven climate projections, the uncertainty in projected future climate change resulting from our limited understanding of how the carbon cycle and other gas cycles will evolve in the future is not captured. For example, when deriving the default concentrations for these scenarios, permafrost and other carbon cycle feedbacks are considered using default settings, with a single time series prescribed for all ESMs ( [[#Meinshausen--2020|Meinshausen et al., 2020]] ). Thus, associated uncertainties ( [[#Joos--2013|Joos et al., 2013]] ; [[#Schuur--2015|Schuur et al., 2015]] ) are not considered.

The so-called ‘emissions-driven’ experiments ( [[#Jones--2016|Jones et al., 2016]] ) use the same input datasets as concentration-driven ESM experiments, except that they use CO <sub>2</sub> emissions rather than concentrations ( [[IPCC:Wg1:Chapter:Chapter-5|Chapter 5]] and [[IPCC:Wg1:Chapter:Chapter-4#4.3.1|Section 4.3.1]] ). In these experiments, atmospheric CO <sub>2</sub> concentrations are calculated internally using the ESM interactive carbon cycle module and thus differ from the prescribed default CO <sub>2</sub> concentrations used in the concentration-driven runs. In the particular case of SSP5-8.5, the emissions-driven runs are assessed to add no significant additional uncertainty to future global surface air temperature (GSAT) projections ( [[IPCC:Wg1:Chapter:Chapter-4#4.3.1|Section 4.3.1]] ). However, generally, when assessing uncertainties in future climate projections, it is important to consider which elements of the cause–effect chain, from emissions to the resulting climate change, are interactively included as part of the model projections, and which are externally prescribed using default settings.

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'''Cross-Chapter Box 1.4, Figure 2 |''' '''Comparison between the Shared Socio-economic Pathways (SSP) scenarios and the Representative Concentration Pathway (RCP) scenarios in terms of their CO''' <sub>2</sub> ''', CH''' <sub>4</sub> '''and N''' <sub>2</sub> '''O atmospheric concentrations (a–c), and their global emissions of CO''' <sub>2</sub> ''', CH''' <sub>4</sub> ''', N''' <sub>2</sub> '''O, black carbon (BC), organic carbon (OC), sulphur dioxide (SO''' <sub>2</sub> '''), ammonia (NH''' <sub>3</sub> '''), nitrogen oxides (NOx), volatile organic compounds (VOC), sulphur hexafluoride (SF6), perfluorocarbons (PFCs), and hydrofluorocarbons (HFCs) (d–o).'''
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'''Cross-Chapter Box 1.4, Figure 2:''' Also shown are gridded emissions differences for SO <sub>2</sub> '''(p)''' and black carbon '''(q)''' for the year 2000 between the input emissions datasets that underpinned the CMIP5 and CMIP6 model intercomparisons. Historical emissions estimates are provided in black in panels '''(d–o)''' . The range of concentrations and emissions investigated under the RCP pathways is shaded grey. Panels (p) and (q) adapted from Figure 7 in [[#Hoesly--2018|Hoesly et al. (2018)]] . Further details on data sources and processing are available in the chapter data table (Table 1.SM.1).

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