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Lack of Finance as a Barrier to Climate Action Insufﬁcient ﬁnancing, and a lack of political frameworks and incentives for ﬁnance, are key causes of the implementation gaps for both mitigation and adaptation (high conﬁdence). Financial ﬂows remained heavily focused on mitigation, are uneven, and have developed heterogeneously across regions and sectors (high conﬁdence). In 2018, public and publicly mobilised private climate ﬁnance ﬂows from developed to developing countries were below the collective goal under the UNFCCC and Paris Agreement to mobilise USD 100 billion per year by 2020 in the context of meaningful mitigation action and transparency on implementation (medium conﬁdence). Public and private ﬁnance ﬂows for fossil fuels are still greater than those for climate adaptation and mitigation (high conﬁdence). The overwhelming majority of tracked climate ﬁnance is directed towards mitigation (very high conﬁdence). Nevertheless, average annual modelled investment requirements for 2020 to 2030 in scenarios that limit warming to 2°C or 1.5°C are a factor of three to six greater than current levels, and total mitigation investments (public, private, domestic and international) would need to increase across all sectors and regions (medium conﬁdence). Challenges remain for green bonds and similar products, in particular around integrity and additionality, as well as the limited applicability of these markets to many developing countries (high confidence). {WGII SPM C.3.2, WGII SPM C.5.4; WGIII SPM B.5.4, WGIII SPM E.5.1} Current global ﬁnancial ﬂows for adaptation including from public and private ﬁnance sources, are insufﬁcient for and constrain implementation of adaptation options, especially in developing countries (high conﬁdence). There are widening disparities between the estimated costs of adaptation and the documented ﬁnance allocated to adaptation (high conﬁdence).
Challenges remain for green bonds and similar products, in particular around integrity and additionality, as well as the limited applicability of these markets to many developing countries (high confidence). {WGII SPM C.3.2, WGII SPM C.5.4; WGIII SPM B.5.4, WGIII SPM E.5.1} Current global ﬁnancial ﬂows for adaptation including from public and private ﬁnance sources, are insufﬁcient for and constrain implementation of adaptation options, especially in developing countries (high conﬁdence). There are widening disparities between the estimated costs of adaptation and the documented ﬁnance allocated to adaptation (high conﬁdence). Adaptation ﬁnance needs are estimated to be higher than those assessed in AR5, and the enhanced mobilisation of and access to ﬁnancial resources are essential for implementation of adaptation and to reduce adaptation gaps (high conﬁdence). Annual ﬁnance ﬂows targeting adaptation for Africa, for example, are billions of USD less than the lowest adaptation cost estimates for near-term climate change (high conﬁdence). Adverse climate impacts can further reduce the availability of ﬁnancial resources by causing losses and damages and impeding national economic growth, thereby further increasing ﬁnancial constraints for adaptation particularly for developing countries and LDCs (medium conﬁdence). {WGII SPM C.1.2, WGII SPM C.3.2, WGII SPM C.5.4, WGII TS.D.1.6} Without effective mitigation and adaptation, losses and damages will continue to disproportionately affect the poorest and most vulnerable populations. Accelerated ﬁnancial support for developing countries from developed countries and other sources is a critical enabler to enhance mitigation action {WGIII SPM. E.5.3}. Many developing countries lack comprehensive data at the scale needed and lack adequate ﬁnancial resources needed for adaptation for reducing associated economic and non-economic losses and damages.
{WGII SPM C.1.2, WGII SPM C.3.2, WGII SPM C.5.4, WGII TS.D.1.6} Without effective mitigation and adaptation, losses and damages will continue to disproportionately affect the poorest and most vulnerable populations. Accelerated ﬁnancial support for developing countries from developed countries and other sources is a critical enabler to enhance mitigation action {WGIII SPM. E.5.3}. Many developing countries lack comprehensive data at the scale needed and lack adequate ﬁnancial resources needed for adaptation for reducing associated economic and non-economic losses and damages. (high conﬁdence) {WGII Cross-Chapter Box LOSS, WGII SPM C.3.1, WGII SPM C.3.2, WGII TS.D.1.3, WGII TS.D.1.5; WGIII SPM E.5.3} There are barriers to redirecting capital towards climate action both within and outside the global ﬁnancial sector. These barriers include: the inadequate assessment of climate-related risks and investment opportunities, regional mismatch between available capital and investment needs, home bias factors, country indebtedness levels, economic vulnerability, and limited institutional capacities. Challenges from outside the ﬁnancial sector include: limited local capital markets; unattractive risk-return proﬁles, in particular due to missing or weak regulatory environments that are inconsistent with ambition levels; limited institutional capacity to ensure safeguards; standardisation, aggregation, scalability and replicability of investment opportunities and ﬁnancing models; and, a pipeline ready for commercial investments. (high conﬁdence) {WGII SPM C.5.4; WGIII SPM E.5.2; SR1.5 SPM D.5.2}
63 Current Status and Trends Section 2 Cross-Section Box.2: Scenarios, Global Warming Levels, and Risks Modelled scenarios and pathways102 are used to explore future emissions, climate change, related impacts and risks, and possible mitigation and adaptation strategies and are based on a range of assumptions, including socio-economic variables and mitigation options. These are quantitative projections and are neither predictions nor forecasts. Global modelled emission pathways, including those based on cost effective approaches contain regionally differentiated assumptions and outcomes, and have to be assessed with the careful recognition of these assumptions. Most do not make explicit assumptions about global equity, environmental justice or intra-regional income distribution. IPCC is neutral with regard to the assumptions underlying the scenarios in the literature assessed in this report, which do not cover all possible futures103. {WGI Box SPM.1; WGII Box SPM.1; WGIII Box SPM.1; SROCC Box SPM.1; SRCCL Box SPM.1} Socio-economic Development, Scenarios, and Pathways The ﬁve Shared Socio-economic Pathways (SSP1 to SSP5) were designed to span a range of challenges to climate change mitigation and adaptation. For the assessment of climate impacts, risk and adaptation, the SSPs are used for future exposure, vulnerability and challenges to adaptation. Depending on levels of GHG mitigation, modelled emissions scenarios based on the SSPs can be consistent with low or high warming levels104. There are many different mitigation strategies that could be consistent with different levels of global warming in 2100 (see Figure 4.1). {WGI Box SPM.1; WGII Box SPM.1; WGIII Box SPM.1, WGIII Box TS.5, WGIII Annex III; SRCCL Box SPM.1, SRCCL Figure SPM.2} WGI assessed the climate response to ﬁve illustrative scenarios based on SSPs105 that cover the range of possible future development of anthropogenic drivers of climate change found in the literature. These scenarios combine socio-economic assumptions, levels of climate mitigation, land use and air pollution controls for aerosols and non-CH4 ozone precursors.
Depending on levels of GHG mitigation, modelled emissions scenarios based on the SSPs can be consistent with low or high warming levels104. There are many different mitigation strategies that could be consistent with different levels of global warming in 2100 (see Figure 4.1). {WGI Box SPM.1; WGII Box SPM.1; WGIII Box SPM.1, WGIII Box TS.5, WGIII Annex III; SRCCL Box SPM.1, SRCCL Figure SPM.2} WGI assessed the climate response to ﬁve illustrative scenarios based on SSPs105 that cover the range of possible future development of anthropogenic drivers of climate change found in the literature. These scenarios combine socio-economic assumptions, levels of climate mitigation, land use and air pollution controls for aerosols and non-CH4 ozone precursors. The high and very high GHG emissions scenarios (SSP3-7.0 and SSP5-8.5) have CO2 emissions that roughly double from current levels by 2100 and 2050, respectively106. The intermediate GHG emissions scenario (SSP2-4.5) has CO2 emissions remaining around current levels until the middle of the century. The very low and low GHG emissions scenarios (SSP1-1.9 and SSP1-2.6) have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 emissions. In addition, Representative Concentration Pathways (RCPs)107 were used by WGI and WGII to assess regional climate changes, impacts and risks. {WGI Box SPM.1} (Cross-Section Box.2 Figure 1) In WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways were categorised based on their projected global warming over the 21st century, with categories ranging from pathways that limit warming to 1.5°C with more than 50% likelihood108 with no or limited overshoot (C1) to pathways that exceed 4°C (C8).
The very low and low GHG emissions scenarios (SSP1-1.9 and SSP1-2.6) have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 emissions. In addition, Representative Concentration Pathways (RCPs)107 were used by WGI and WGII to assess regional climate changes, impacts and risks. {WGI Box SPM.1} (Cross-Section Box.2 Figure 1) In WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways were categorised based on their projected global warming over the 21st century, with categories ranging from pathways that limit warming to 1.5°C with more than 50% likelihood108 with no or limited overshoot (C1) to pathways that exceed 4°C (C8). Methods to project global warming associated with the modelled pathways were updated to ensure consistency with the AR6 WGI assessment of the climate system response109. {WGIII Box SPM.1,WGIII Table 3.1} (Table 3.1, Cross-Section Box.2 Figure 1) 102 In the literature, the terms pathways and scenarios are used interchangeably, with the former more frequently used in relation to climate goals. WGI primarily used the term scenarios and WGIII mostly used the term modelled emissions and mitigation pathways. The SYR primarily uses scenarios when referring to WGI and modelled emissions and mitigation pathways when referring to WGIII. {WGI Box SPM.1; WGIII footnote 44} 103 Around half of all modelled global emissions pathways assume cost-effective approaches that rely on least-cost mitigation/abatement options globally. The other half look at existing policies and regionally and sectorally differentiated actions. The underlying population assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion in 2100 (5–95th percentile) starting from 7.6 billion in 2019.
WGI primarily used the term scenarios and WGIII mostly used the term modelled emissions and mitigation pathways. The SYR primarily uses scenarios when referring to WGI and modelled emissions and mitigation pathways when referring to WGIII. {WGI Box SPM.1; WGIII footnote 44} 103 Around half of all modelled global emissions pathways assume cost-effective approaches that rely on least-cost mitigation/abatement options globally. The other half look at existing policies and regionally and sectorally differentiated actions. The underlying population assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion in 2100 (5–95th percentile) starting from 7.6 billion in 2019. The underlying assumptions on global GDP growth range from 2.5 to 3.5% per year in the 2019–2050 period and 1.3 to 2.1% per year in the 2050–2100 (5–95th percentile). {WGIII Box SPM.1} 104 High mitigation challenges, for example, due to assumptions of slow technological change, high levels of global population growth, and high fragmentation as in the Shared Socio-economic Pathway SSP3, may render modelled pathways that limit warming to 2°C (> 67%) or lower infeasible (medium conﬁdence). {WGIII SPM C.1.4; SRCCL Box SPM.1} 105 SSP-based scenarios are referred to as SSPx-y, where ‘SSPx’ refers to the Shared Socio-economic Pathway describing the socioeconomic trends underlying the scenarios, and ‘y’ refers to the level of radiative forcing (in watts per square metre, or Wm–2) resulting from the scenario in the year 2100. {WGI SPM footnote 22} 106 Very high emission scenarios have become less likely but cannot be ruled out. Temperature levels > 4°C may result from very high emission scenarios, but can also occur from lower emission scenarios if climate sensitivity or carbon cycle feedbacks are higher than the best estimate.
{WGIII SPM C.1.4; SRCCL Box SPM.1} 105 SSP-based scenarios are referred to as SSPx-y, where ‘SSPx’ refers to the Shared Socio-economic Pathway describing the socioeconomic trends underlying the scenarios, and ‘y’ refers to the level of radiative forcing (in watts per square metre, or Wm–2) resulting from the scenario in the year 2100. {WGI SPM footnote 22} 106 Very high emission scenarios have become less likely but cannot be ruled out. Temperature levels > 4°C may result from very high emission scenarios, but can also occur from lower emission scenarios if climate sensitivity or carbon cycle feedbacks are higher than the best estimate. {WGIII SPM C.1.3} 107 RCP-based scenarios are referred to as RCPy, where ‘y’ refers to the approximate level of radiative forcing (in watts per square metre, or Wm–2) resulting from the scenario in the year 2100. {WGII SPM footnote 21} 108 Denoted ‘>50%’ in this report. 109 The climate response to emissions is investigated with climate models, paleoclimatic insights and other lines of evidence. The assessment outcomes are used to categorise thousands of scenarios via simple physically-based climate models (emulators). {WGI TS.1.2.2}
64 Section 2 Section 1 Section 2 Global Warming Levels (GWLs) For many climate and risk variables, the geographical patterns of changes in climatic impact-drivers110 and climate impacts for a level of global warming111 are common to all scenarios considered and independent of timing when that level is reached. This motivates the use of GWLs as a dimension of integration. {WGI Box SPM.1.4, WGI TS.1.3.2; WGII Box SPM.1} (Figure 3.1, Figure 3.2) Risks Dynamic interactions between climate-related hazards, exposure and vulnerability of the affected human society, species, or ecosystems result in risks arising from climate change. AR6 assesses key risks across sectors and regions as well as providing an updated assessment of the Reasons for Concern (RFCs) – ﬁve globally aggregated categories of risk that evaluate risk accrual with increasing global surface temperature. Risks can also arise from climate change mitigation or adaptation responses when the response does not achieve its intended objective, or when it results in adverse effects for other societal objectives. {WGII SPM A, WGII Figure SPM.3, WGII Box TS.1, WGII Figure TS.4; SR1.5 Figure SPM.2; SROCC Errata Figure SPM.3; SRCCL Figure SPM.2} (3.1.2, Cross-Section Box.2 Figure 1, Figure 3.3) 110 See Annex I: Glossary 111 See Annex I: Glossary. Here, global warming is the 20-year average global surface temperature relative to 1850–1900. The assessed time of when a certain global warming level is reached under a particular scenario is deﬁned here as the mid-point of the ﬁrst 20-year running average period during which the assessed average global surface temperature change exceeds the level of global warming. {WGI SPM footnote 26, Cross-Section Box TS.1}
65 Current Status and Trends Section 2 which drives that change inﬂuence Emissions a) AR6 integrated assessment framework on future climate, impacts and mitigation Climate Impacts / Risks Mitigation Policy Adaptation Policy Socio-economic changes 0 1 2 3 4 5 6 7 °C b) Scenarios and pathways across AR6 Working Group reports c) Determinants of risk Temperature for SSP-based scenarios over the 21st century and C1-C8 at 2100 Risks can be represented as “burning embers” C1-C8 in 2100 increasing risk 2050 2100 0 50 100 2050 2100 GtCO2/yr SSP1-1.9 SSP1-2.6 SSP2-4.5 SSP3-7.0 SSP5-8.5 SSP1-1.9 SSP1-2.6 SSP2-4.5 SSP3-7.0 SSP5-8.5 RFC1 Unique and threatened systems color shading shows C1-C8 category color shading shows range for SSP3-7.0 and SSP1-2.6 Category in WGIII Category description GHG emissions scenarios (SSPx-y) in WGI & WGII RCPy* in WGI & WGII C1 limit warming to 1.5°C (>50%) with no or limited overshoot Very low (SSP1-1.9) Low (SSP1-2.6) RCP2.6 C2 return warming to 1.5°C (>50%) after a high overshoot C3 limit warming to 2°C (>67%) C4 limit warming to 2°C (>50%) C5 limit warming to 2.5°C (>50%) C6 limit warming to 3°C (>50%) Intermediate (SSP2-4.5) RCP 4.5 RCP 8.
0 and SSP1-2.6 Category in WGIII Category description GHG emissions scenarios (SSPx-y) in WGI & WGII RCPy* in WGI & WGII C1 limit warming to 1.5°C (>50%) with no or limited overshoot Very low (SSP1-1.9) Low (SSP1-2.6) RCP2.6 C2 return warming to 1.5°C (>50%) after a high overshoot C3 limit warming to 2°C (>67%) C4 limit warming to 2°C (>50%) C5 limit warming to 2.5°C (>50%) C6 limit warming to 3°C (>50%) Intermediate (SSP2-4.5) RCP 4.5 RCP 8.5 C7 limit warming to 4°C (>50%) High (SSP3-7.0) C8 exceed warming of 4°C (>50%) Very high (SSP5-8.5) Scenarios and warming levels structure our understanding across the cause-effect chain from emissions to climate change and risks CO2 emissions for SSP-based scenarios and C1-C8 categories Vulnerability Hazard Response Risk Exposure Climatic Impact- Drivers 0 1 2 3 4 5 °C inﬂuence shape * The terminology SSPx-y is used, where ‘SSPx’ refers to the Shared Socio-economic Pathway or ‘SSP’ describing the socio-economic trends underlying the scenario, and ‘y’ refers to the approximate level of radiative forcing (in watts per square metre, or Wm–2) resulting from the scenario in the year 2100. ** The AR5 scenarios (RCPy), which partly inform the AR6 WGI and WGII assessments, are indexed to a similar set of approximate 2100 radiative forcing levels (in W m-2). The SSP scenarios cover a broader range of GHG and air pollutant futures than the RCPs.
where ‘SSPx’ refers to the Shared Socio-economic Pathway or ‘SSP’ describing the socio-economic trends underlying the scenario, and ‘y’ refers to the approximate level of radiative forcing (in watts per square metre, or Wm–2) resulting from the scenario in the year 2100. The AR5 scenarios (RCPy), which partly inform the AR6 WGI and WGII assessments, are indexed to a similar set of approximate 2100 radiative forcing levels (in W m-2). The SSP scenarios cover a broader range of GHG and air pollutant futures than the RCPs. They are similar but not identical, with differences in concentration trajectories for different GHGs. The overall radiative forcing tends to be higher for the SSPs compared to the RCPs with the same label (medium conﬁdence). {WGI TS.1.3.1} * Limited overshoot refers to exceeding 1.5°C global warming by up to about 0.1°C, high overshoot by 0.1°C-0.3°C, in both cases for up to several decades.
66 Section 2 Section 1 Section 2 Cross-Section Box.2 Figure 1: Schematic of the AR6 framework for assessing future greenhouse gas emissions, climate change, risks, impacts and mitigation. Panel (a) The integrated framework encompasses socio-economic development and policy, emissions pathways and global surface temperature responses to the ﬁve scenarios considered by WGI (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) and eight global mean temperature change categorisations (C1–C8) assessed by WGIII, and the WGII risk assessment. The dashed arrow indicates that the inﬂuence from impacts/risks to socio-economic changes is not yet considered in the scenarios assessed in the AR6. Emissions include GHGs, aerosols, and ozone precursors. CO2 emissions are shown as an example on the left. The assessed global surface temperature changes across the 21st century relative to 1850-1900 for the ﬁve GHG emissions scenarios are shown as an example in the centre. Very likely ranges are shown for SSP1-2.6 and SSP3-7.0. Projected temperature outcomes at 2100 relative to 1850-1900 are shown for C1 to C8 categories with median (line) and the combined very likely range across scenarios (bar). On the right, future risks due to increasing warming are represented by an example ‘burning ember’ ﬁgure (see 3.1.2 for the deﬁnition of RFC1). Panel (b) Description and relationship of scenarios considered across AR6 Working Group reports. Panel (c) Illustration of risk arising from the interaction of hazard (driven by changes in climatic impact-drivers) with vulnerability, exposure and response to climate change. {WGI TS1.4, Figure 4.11; WGII Figure 1.5, WGII Figure 14.8; WGIII Table SPM.2, WGIII Figure 3.11}
67 Section 3 Long-Term Climate and Development Futures
68 Section 3 Section 1 Section 3 Section 3: Long-Term Climate and Development Futures 3.1 Long-Term Climate Change, Impacts and Related Risks Future warming will be driven by future emissions and will affect all major climate system components, with every region experiencing multiple and co-occurring changes. Many climate-related risks are assessed to be higher than in previous assessments, and projected long-term impacts are up to multiple times higher than currently observed. Multiple climatic and non-climatic risks will interact, resulting in compounding and cascading risks across sectors and regions. Sea level rise, as well as other irreversible changes, will continue for thousands of years, at rates depending on future emissions. (high conﬁdence) 3.1.1. Long-term Climate Change The uncertainty range on assessed future changes in global surface temperature is narrower than in the AR5. For the ﬁrst time in an IPCC assessment cycle, multi-model projections of global surface temperature, ocean warming and sea level are constrained using observations and the assessed climate sensitivity. The likely range of equilibrium climate sensitivity has been narrowed to 2.5°C to 4.0°C (with a best estimate of 3.0°C) based on multiple lines of evidence112, including improved understanding of cloud feedbacks. For related emissions scenarios, this leads to narrower uncertainty ranges for long-term projected global temperature change than in AR5. {WGI A.4, WGI Box SPM.1, WGI TS.3.2, WGI 4.3} Future warming depends on future GHG emissions, with cumulative net CO2 dominating.
Long-term Climate Change The uncertainty range on assessed future changes in global surface temperature is narrower than in the AR5. For the ﬁrst time in an IPCC assessment cycle, multi-model projections of global surface temperature, ocean warming and sea level are constrained using observations and the assessed climate sensitivity. The likely range of equilibrium climate sensitivity has been narrowed to 2.5°C to 4.0°C (with a best estimate of 3.0°C) based on multiple lines of evidence112, including improved understanding of cloud feedbacks. For related emissions scenarios, this leads to narrower uncertainty ranges for long-term projected global temperature change than in AR5. {WGI A.4, WGI Box SPM.1, WGI TS.3.2, WGI 4.3} Future warming depends on future GHG emissions, with cumulative net CO2 dominating. The assessed best estimates and very likely ranges of warming for 2081-2100 with respect to 1850–1900 vary from 1.4 [1.0 to 1.8]°C in the very low GHG emissions scenario (SSP1-1.9) to 2.7 [2.1 to 3.5]°C in the intermediate GHG emissions scenario (SSP2-4.5) and 4.4 [3.3 to 5.7]°C in the very high GHG emissions scenario (SSP5-8.5)113. {WGI SPM B.1.1, WGI Table SPM.1, WGI Figure SPM.4} (Cross-Section Box.2 Figure 1) Modelled pathways consistent with the continuation of policies implemented by the end of 2020 lead to global warming of 3.2 [2.2 to 3.5]°C (5–95% range) by 2100 (medium conﬁdence) (see also Section 2.3.1). Pathways of >4°C (≥50%) by 2100 would imply a reversal of current technology and/or mitigation policy trends (medium conﬁdence).
{WGI SPM B.1.1, WGI Table SPM.1, WGI Figure SPM.4} (Cross-Section Box.2 Figure 1) Modelled pathways consistent with the continuation of policies implemented by the end of 2020 lead to global warming of 3.2 [2.2 to 3.5]°C (5–95% range) by 2100 (medium conﬁdence) (see also Section 2.3.1). Pathways of >4°C (≥50%) by 2100 would imply a reversal of current technology and/or mitigation policy trends (medium conﬁdence). However, such warming could occur in emissions pathways consistent with policies implemented by the end of 2020 if climate sensitivity or carbon cycle feedbacks are higher than the best estimate (high conﬁdence). {WGIII SPM C.1.3} 112 Understanding of climate processes, the instrumental record, paleoclimates and model-based emergent constraints (see Annex I: Glossary). {WGI SPM footnote 21} 113 The best estimates [and very likely ranges] for the different scenarios are: 1.4 [1.0 to 1.8]°C (SSP1-1.9); 1.8 [1.3 to 2.4]°C (SSP1-2.6); 2.7 [2.1 to 3.5]°C (SSP2-4.5); 3.6 [2.8 to 4.6]°C (SSP3-7.0); and 4.4 [3.3 to 5.7]°C (SSP5-8.5).
{WGIII SPM C.1.3} 112 Understanding of climate processes, the instrumental record, paleoclimates and model-based emergent constraints (see Annex I: Glossary). {WGI SPM footnote 21} 113 The best estimates [and very likely ranges] for the different scenarios are: 1.4 [1.0 to 1.8]°C (SSP1-1.9); 1.8 [1.3 to 2.4]°C (SSP1-2.6); 2.7 [2.1 to 3.5]°C (SSP2-4.5); 3.6 [2.8 to 4.6]°C (SSP3-7.0); and 4.4 [3.3 to 5.7]°C (SSP5-8.5). {WGI Table SPM.1} (Cross-Section Box.2) 114 In the near term (2021–2040), the 1.5°C global warming level is very likely to be exceeded under the very high GHG emissions scenario (SSP5-8.5), likely to be exceeded under the intermediate and high GHG emissions scenarios (SSP2-4.5, SSP3-7.0), more likely than not to be exceeded under the low GHG emissions scenario (SSP1-2.6) and more likely than not to be reached under the very low GHG emissions scenario (SSP1-1.9). In all scenarios considered by WGI except the very high emissions scenario, the midpoint of the ﬁrst 20-year running average period during which the assessed global warming reaches 1.5°C lies in the ﬁrst half of the 2030s. In the very high GHG emissions scenario, this mid-point is in the late 2020s. The median ﬁve-year interval at which a 1.5°C global warming level is reached (50% probability) in categories of modelled pathways considered in WGIII is 2030–2035.
In all scenarios considered by WGI except the very high emissions scenario, the midpoint of the ﬁrst 20-year running average period during which the assessed global warming reaches 1.5°C lies in the ﬁrst half of the 2030s. In the very high GHG emissions scenario, this mid-point is in the late 2020s. The median ﬁve-year interval at which a 1.5°C global warming level is reached (50% probability) in categories of modelled pathways considered in WGIII is 2030–2035. {WGI SPM B.1.3, WGI Cross-Section Box TS.1, WGIII Table 3.2} (Cross-Section Box.2) 115 See Cross-Section Box.2. 116 Based on additional scenarios. Global warming will continue to increase in the near term in nearly all considered scenarios and modelled pathways. Deep, rapid, and sustained GHG emissions reductions, reaching net zero CO2 emissions and including strong emissions reductions of other GHGs, in particular CH4, are necessary to limit warming to 1.5°C (>50%) or less than 2°C (>67%) by the end of century (high conﬁdence). The best estimate of reaching 1.5°C of global warming lies in the ﬁrst half of the 2030s in most of the considered scenarios and modelled pathways114. In the very low GHG emissions scenario (SSP1-1.9), CO2 emissions reach net zero around 2050 and the best-estimate end-of-century warming is 1.4°C, after a temporary overshoot (see Section 3.3.4) of no more than 0.1°C above 1.5°C global warming. Global warming of 2°C will be exceeded during the 21st century unless deep reductions in CO2 and other GHG emissions occur in the coming decades.
The best estimate of reaching 1.5°C of global warming lies in the ﬁrst half of the 2030s in most of the considered scenarios and modelled pathways114. In the very low GHG emissions scenario (SSP1-1.9), CO2 emissions reach net zero around 2050 and the best-estimate end-of-century warming is 1.4°C, after a temporary overshoot (see Section 3.3.4) of no more than 0.1°C above 1.5°C global warming. Global warming of 2°C will be exceeded during the 21st century unless deep reductions in CO2 and other GHG emissions occur in the coming decades. Deep, rapid, and sustained reductions in GHG emissions would lead to improvements in air quality within a few years, to reductions in trends of global surface temperature discernible after around 20 years, and over longer time periods for many other climate impact-drivers115 (high conﬁdence). Targeted reductions of air pollutant emissions lead to more rapid improvements in air quality compared to reductions in GHG emissions only, but in the long term, further improvements are projected in scenarios that combine efforts to reduce air pollutants as well as GHG emissions (high conﬁdence)116. {WGI SPM B.1, WGI SPM B.1.3, WGI SPM D.1, WGI SPM D.2, WGI Figure SPM.4, WGI Table SPM.1, WGI Cross-Section Box TS.1; WGIII SPM C.3, WGIII Table SPM.2, WGIII Figure SPM.5, WGIII Box SPM.1 Figure 1, WGIII Table 3.2} (Table 3.1, Cross-Section Box.2 Figure 1) Changes in short-lived climate forcers (SLCF) resulting from the ﬁve considered scenarios lead to an additional net global warming in the near and long term (high conﬁdence). Simultaneous stringent climate change mitigation and air pollution control
69 Long-Term Climate and Development Futures Section 3 policies limit this additional warming and lead to strong beneﬁts for air quality (high conﬁdence). In high and very high GHG emissions scenarios (SSP3-7.0 and SSP5-8.5), combined changes in SLCF emissions, such as CH4, aerosol and ozone precursors, lead to a net global warming by 2100 of likely 0.4°C to 0.9°C relative to 2019. This is due to projected increases in atmospheric concentration of CH4, tropospheric ozone, hydroﬂuorocarbons and, when strong air pollution control is considered, reductions of cooling aerosols. In low and very low GHG emissions scenarios (SSP1-1.9 and SSP1-2.6), air pollution control policies, reductions in CH4 and other ozone precursors lead to a net cooling, whereas reductions in anthropogenic cooling aerosols lead to a net warming (high conﬁdence). Altogether, this causes a likely net warming of 0.0°C to 0.3°C due to SLCF changes in 2100 relative to 2019 and strong reductions in global surface ozone and particulate matter (high conﬁdence). {WGI SPM D.1.7, WGI Box TS.7} (Cross-Section Box.2) Continued GHG emissions will further affect all major climate system components, and many changes will be irreversible on centennial to millennial time scales. Many changes in the climate system become larger in direct relation to increasing global warming. With every additional increment of global warming, changes in extremes continue to become larger. Additional warming will lead to more frequent and intense marine heatwaves and is projected to further amplify permafrost thawing and loss of seasonal snow cover, glaciers, land ice and Arctic sea ice (high conﬁdence).
{WGI SPM D.1.7, WGI Box TS.7} (Cross-Section Box.2) Continued GHG emissions will further affect all major climate system components, and many changes will be irreversible on centennial to millennial time scales. Many changes in the climate system become larger in direct relation to increasing global warming. With every additional increment of global warming, changes in extremes continue to become larger. Additional warming will lead to more frequent and intense marine heatwaves and is projected to further amplify permafrost thawing and loss of seasonal snow cover, glaciers, land ice and Arctic sea ice (high conﬁdence). Continued global warming is projected to further intensify the global water cycle, including its variability, global monsoon precipitation117, and very wet and very dry weather and climate events and seasons (high conﬁdence). The portion of global land experiencing detectable changes in seasonal mean precipitation is projected to increase (medium conﬁdence) with more variable precipitation and surface water ﬂows over most land regions within seasons (high conﬁdence) and from year to year (medium conﬁdence). Many changes due to past and future GHG emissions are irreversible118 on centennial to millennial time scales, especially in the ocean, ice sheets and global sea level (see 3.1.3). Ocean acidiﬁcation (virtually certain), ocean deoxygenation (high conﬁdence) and global mean sea level (virtually certain) will continue to increase in the 21st century, at rates dependent on future emissions.
The portion of global land experiencing detectable changes in seasonal mean precipitation is projected to increase (medium conﬁdence) with more variable precipitation and surface water ﬂows over most land regions within seasons (high conﬁdence) and from year to year (medium conﬁdence). Many changes due to past and future GHG emissions are irreversible118 on centennial to millennial time scales, especially in the ocean, ice sheets and global sea level (see 3.1.3). Ocean acidiﬁcation (virtually certain), ocean deoxygenation (high conﬁdence) and global mean sea level (virtually certain) will continue to increase in the 21st century, at rates dependent on future emissions. {WGI SPM B.2, WGI SPM B.2.2, WGI SPM B.2.3, WGI SPM B.2.5, WGI SPM B.3, WGI SPM B.3.1, WGI SPM B.3.2, WGI SPM B.4, WGI SPM B.5, WGI SPM B.5.1, WGI SPM B.5.3, WGI Figure SPM.8} (Figure 3.1) With further global warming, every region is projected to increasingly experience concurrent and multiple changes in climatic impact-drivers. Increases in hot and decreases in cold climatic impact-drivers, such as temperature extremes, are projected in all regions (high conﬁdence). At 1.5°C global warming, heavy precipitation and ﬂooding events are projected to intensify and become more frequent in most regions in Africa, Asia (high conﬁdence), North America (medium to high conﬁdence) and Europe (medium conﬁdence).
Increases in hot and decreases in cold climatic impact-drivers, such as temperature extremes, are projected in all regions (high conﬁdence). At 1.5°C global warming, heavy precipitation and ﬂooding events are projected to intensify and become more frequent in most regions in Africa, Asia (high conﬁdence), North America (medium to high conﬁdence) and Europe (medium conﬁdence). At 2°C or above, these changes expand to more regions and/or become more signiﬁcant (high conﬁdence), and more frequent and/or severe agricultural and ecological droughts are projected in Europe, Africa, Australasia and North, Central and South America (medium to high conﬁdence). Other projected regional changes include 117 Particularly over South and South East Asia, East Asia and West Africa apart from the far west Sahel. {WGI SPM B.3.3} 118 See Annex I: Glossary. 119 See Annex I: Glossary. intensification of tropical cyclones and/or extratropical storms (medium conﬁdence), and increases in aridity and ﬁre weather119 (medium to high conﬁdence). Compound heatwaves and droughts become likely more frequent, including concurrently at multiple locations (high conﬁdence). {WGI SPM C.2, WGI SPM C.2.1, WGI SPM C.2.2, WGI SPM C.2.3, WGI SPM C.2.4, WGI SPM C.2.7}
70 Section 3 Section 1 Section 3 2011-2020 was around 1.1°C warmer than 1850-1900 the last time global surface temperature was sustained at or above 2.5°C was over 3 million years ago 4°C The world at 2°C The world at 1.5°C + + 1 0 The world at 3°C The world at small absolute changes may appear large as % or σ changes in dry regions urbanisation further intensifies heat extremes c) Annual wettest-day precipitation change Global warming level (GWL) above 1850-1900 a) Annual hottest-day temperature change b) Annual mean total column soil moisture change °C Annual wettest day precipitation is projected to increase in almost all continental regions, even in regions where projected annual mean soil moisture declines. Annual hottest day temperature is projected to increase most (1.5-2 times the GWL) in some mid-latitude and semi-arid regions, and in the South American Monsoon region. Projections of annual mean soil moisture largely follow projections in annual mean precipitation but also show some differences due to the inﬂuence of evapotranspiration. change (%) -40 -30 -20 -10 0 10 20 30 40 + + change (°C) 0 1 2 3 4 5 6 7 -1.5 -1.0 -0.5 0 0.5 1.0 1.5 change (σ) With every increment of global warming, regional changes in mean climate and extremes become more widespread and pronounced Figure 3.1: Projected changes of annual maximum daily temperature, annual mean total column soil moisture CMIP and annual maximum daily precipitation at global warming levels of 1.5°C, 2°C, 3°C, and 4°C relative to 1850-1900. Simulated (a) annual maximum temperature change (°C), (b) annual mean total column soil moisture (standard deviation), (c) annual maximum daily precipitation change (%).
change (%) -40 -30 -20 -10 0 10 20 30 40 + + change (°C) 0 1 2 3 4 5 6 7 -1.5 -1.0 -0.5 0 0.5 1.0 1.5 change (σ) With every increment of global warming, regional changes in mean climate and extremes become more widespread and pronounced Figure 3.1: Projected changes of annual maximum daily temperature, annual mean total column soil moisture CMIP and annual maximum daily precipitation at global warming levels of 1.5°C, 2°C, 3°C, and 4°C relative to 1850-1900. Simulated (a) annual maximum temperature change (°C), (b) annual mean total column soil moisture (standard deviation), (c) annual maximum daily precipitation change (%). Changes correspond to CMIP6 multi-model median changes. In panels (b) and (c), large positive relative changes in dry regions may correspond to small absolute changes. In panel (b), the unit is the standard deviation of interannual variability in soil moisture during 1850-1900. Standard deviation is a widely used metric in characterising drought severity. A projected reduction in mean soil moisture by one standard deviation corresponds to soil moisture conditions typical of droughts that occurred about once every six years during 1850-1900. The WGI Interactive Atlas (https://interactive-atlas.ipcc.ch/) can be used to explore additional changes in the climate system across the range of global warming levels presented in this ﬁgure. {WGI Figure SPM.5, WGI Figure TS.5, WGI Figure 11.11, WGI Figure 11.16, WGI Figure 11.19} (Cross-Section Box.2)
71 Long-Term Climate and Development Futures Section 3 3.1.2 Impacts and Related Risks For a given level of warming, many climate-related risks are assessed to be higher than in AR5 (high conﬁdence). Levels of risk120 for all Reasons for Concern121 (RFCs) are assessed to become high to very high at lower global warming levels compared to what was assessed in AR5 (high conﬁdence). This is based upon recent evidence of observed impacts, improved process understanding, and new knowledge on exposure and vulnerability of human and natural systems, including limits to adaptation. Depending on the level of global warming, the assessed long-term impacts will be up to multiple times higher than currently observed (high confidence) for 127 identiﬁed key risks, e.g., in terms of the number of affected people and species. Risks, including cascading risks (see 3.1.3) and risks from overshoot (see 3.3.4), are projected to become increasingly severe with every increment of global warming (very high confidence). {WGII SPM B.3.3, WGII SPM B.4, WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} (Figure 3.2, Figure 3.3) Climate-related risks for natural and human systems are higher for global warming of 1.5°C than at present (1.1°C) but lower than at 2°C (high conﬁdence) (see Section 2.1.2). Climate-related risks to health, livelihoods, food security, water supply, human security, and economic growth are projected to increase with global warming of 1.5°C. In terrestrial ecosystems, 3 to 14% of the tens of thousands of species assessed will likely face a very high risk of extinction at a GWL of 1.5°C. Coral reefs are projected to decline by a further 70–90% at 1.5°C of global warming (high conﬁdence).
Climate-related risks to health, livelihoods, food security, water supply, human security, and economic growth are projected to increase with global warming of 1.5°C. In terrestrial ecosystems, 3 to 14% of the tens of thousands of species assessed will likely face a very high risk of extinction at a GWL of 1.5°C. Coral reefs are projected to decline by a further 70–90% at 1.5°C of global warming (high conﬁdence). At this GWL, many low-elevation and small glaciers around the world would lose most of their mass or disappear within decades to centuries (high conﬁdence). Regions at disproportionately higher risk include Arctic ecosystems, dryland regions, small island developing states and Least Developed Countries (high conﬁdence). {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, SR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3) At 2°C of global warming, overall risk levels associated with the unequal distribution of impacts (RFC3), global aggregate impacts (RFC4) and large-scale singular events (RFC5) would be transitioning to high (medium conﬁdence), those associated with extreme weather events (RFC2) would be transitioning to very high (medium conﬁdence), and those associated with unique and threatened systems (RFC1) would be very high (high conﬁdence) (Figure 3.3, panel a).
{WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, SR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3) At 2°C of global warming, overall risk levels associated with the unequal distribution of impacts (RFC3), global aggregate impacts (RFC4) and large-scale singular events (RFC5) would be transitioning to high (medium conﬁdence), those associated with extreme weather events (RFC2) would be transitioning to very high (medium conﬁdence), and those associated with unique and threatened systems (RFC1) would be very high (high conﬁdence) (Figure 3.3, panel a). With about 2°C warming, climate-related 120 Undetectable risk level indicates no associated impacts are detectable and attributable to climate change; moderate risk indicates associated impacts are both detectable and attributable to climate change with at least medium conﬁdence, also accounting for the other speciﬁc criteria for key risks; high risk indicates severe and widespread impacts that are judged to be high on one or more criteria for assessing key risks; and very high risk level indicates very high risk of severe impacts and the presence of signiﬁcant irreversibility or the persistence of climate-related hazards, combined with limited ability to adapt due to the nature of the hazard or impacts/risks. {WGII Figure SPM.3} 121 The Reasons for Concern (RFC) framework communicates scientiﬁc understanding about accrual of risk for ﬁve broad categories (WGII Figure SPM.3). RFC1: Unique and threatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and have high endemism or other distinctive properties. Examples include coral reefs, the Arctic and its Indigenous Peoples, mountain glaciers and biodiversity hotspots.
{WGII Figure SPM.3} 121 The Reasons for Concern (RFC) framework communicates scientiﬁc understanding about accrual of risk for ﬁve broad categories (WGII Figure SPM.3). RFC1: Unique and threatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and have high endemism or other distinctive properties. Examples include coral reefs, the Arctic and its Indigenous Peoples, mountain glaciers and biodiversity hotspots. RFC2: Extreme weather events: risks/impacts to human health, livelihoods, assets and ecosystems from extreme weather events such as heatwaves, heavy rain, drought and associated wildﬁres, and coastal ﬂooding. RFC3: Distribution of impacts: risks/impacts that disproportionately affect particular groups due to uneven distribution of physical climate change hazards, exposure or vulnerability. RFC4: Global aggregate impacts: impacts to socio-ecological systems that can be aggregated globally into a single metric, such as monetary damages, lives affected, species lost or ecosystem degradation at a global scale. RFC5: Large-scale singular events: relatively large, abrupt and sometimes irreversible changes in systems caused by global warming, such as ice sheet instability or thermohaline circulation slowing. Assessment methods include a structured expert elicitation based on the literature described in WGII SM16.6 and are identical to AR5 but are enhanced by a structured approach to improve robustness and facilitate comparison between AR5 and AR6. For further explanations of global risk levels and Reasons for Concern, see WGII TS.AII. {WGII Figure SPM.3} changes in food availability and diet quality are estimated to increase nutrition-related diseases and the number of undernourished people, affecting tens (under low vulnerability and low warming) to hundreds of millions of people (under high vulnerability and high warming), particularly among low-income households in low- and middle-income countries in sub-Saharan Africa, South Asia and Central America (high conﬁdence). For example, snowmelt water availability for irrigation is projected to decline in some snowmelt dependent river basins by up to 20% (medium conﬁdence).
For further explanations of global risk levels and Reasons for Concern, see WGII TS.AII. {WGII Figure SPM.3} changes in food availability and diet quality are estimated to increase nutrition-related diseases and the number of undernourished people, affecting tens (under low vulnerability and low warming) to hundreds of millions of people (under high vulnerability and high warming), particularly among low-income households in low- and middle-income countries in sub-Saharan Africa, South Asia and Central America (high conﬁdence). For example, snowmelt water availability for irrigation is projected to decline in some snowmelt dependent river basins by up to 20% (medium conﬁdence). Climate change risks to cities, settlements and key infrastructure will rise sharply in the mid and long term with further global warming, especially in places already exposed to high temperatures, along coastlines, or with high vulnerabilities (high conﬁdence). {WGII SPM B.3.3, WGII SPM B.4.2, WGII SPM B.4.5, WGII TS C.3.3, WGII TS.C.12.2} (Figure 3.3) At global warming of 3°C, additional risks in many sectors and regions reach high or very high levels, implying widespread systemic impacts, irreversible change and many additional adaptation limits (see Section 3.2) (high conﬁdence). For example, very high extinction risk for endemic species in biodiversity hotspots is projected to increase at least tenfold if warming rises from 1.5°C to 3°C (medium conﬁdence). Projected increases in direct ﬂood damages are higher by 1.4 to 2 times at 2°C and 2.5 to 3.9 times at 3°C, compared to 1.5°C global warming without adaptation (medium conﬁdence).
For example, very high extinction risk for endemic species in biodiversity hotspots is projected to increase at least tenfold if warming rises from 1.5°C to 3°C (medium conﬁdence). Projected increases in direct ﬂood damages are higher by 1.4 to 2 times at 2°C and 2.5 to 3.9 times at 3°C, compared to 1.5°C global warming without adaptation (medium conﬁdence). {WGII SPM B.4.1, WGII SPM B.4.2, WGII Figure SPM.3, WGII TS Appendix AII, WGII Appendix I Global to Regional Atlas Figure AI.46} (Figure 3.2, Figure 3.3) Global warming of 4°C and above is projected to lead to far-reaching impacts on natural and human systems (high conﬁdence). Beyond 4°C of warming, projected impacts on natural systems include local extinction of ~50% of tropical marine species (medium conﬁdence) and biome shifts across 35% of global land area (medium conﬁdence). At this level of warming, approximately 10% of the global land area is projected to face both increasing high and decreasing low extreme streamﬂow, affecting, without additional adaptation, over 2.1 billion people (medium conﬁdence) and about 4 billion people are projected to experience water scarcity (medium conﬁdence). At 4°C of warming, the global burned area is projected to increase by 50 to 70% and the fire frequency by ~30% compared to today (medium confidence). {WGII SPM B.4.1, WGII SPM B.4.2, WGII TS.C.1.2, WGII TS.C.2.3, WGII TS.C.4.1, WGII TS.C.4.4} (Figure 3.2, Figure 3.3)
72 Section 3 Section 1 Section 3 Projected adverse impacts and related losses and damages from climate change escalate with every increment of global warming (very high conﬁdence), but they will also strongly depend on socio-economic development trajectories and adaptation actions to reduce vulnerability and exposure (high conﬁdence). For example, development pathways with higher demand for food, animal feed, and water, more resource-intensive consumption and production, and limited technological improvements result in higher risks from water scarcity in drylands, land degradation and food insecurity (high conﬁdence). Changes in, for example, demography or investments in health systems have effect on a variety of health-related outcomes including heat-related morbidity and mortality (Figure 3.3 Panel d). {WGII SPM B.3, WGII SPM B.4, WGII Figure SPM.3; SRCCL SPM A.6} With every increment of warming, climate change impacts and risks will become increasingly complex and more difﬁcult to manage. Many regions are projected to experience an increase in the probability of compound events with higher global warming, such as concurrent heatwaves and droughts, compound ﬂooding and ﬁre weather. In addition, multiple climatic and non-climatic risk drivers such as biodiversity loss or violent conﬂict will interact, resulting in compounding overall risk and risks cascading across sectors and regions. Furthermore, risks can arise from some responses that are intended to reduce the risks of climate change, e.g., adverse side effects of some emission reduction and carbon dioxide removal (CDR) measures (see 3.4.1).
Many regions are projected to experience an increase in the probability of compound events with higher global warming, such as concurrent heatwaves and droughts, compound ﬂooding and ﬁre weather. In addition, multiple climatic and non-climatic risk drivers such as biodiversity loss or violent conﬂict will interact, resulting in compounding overall risk and risks cascading across sectors and regions. Furthermore, risks can arise from some responses that are intended to reduce the risks of climate change, e.g., adverse side effects of some emission reduction and carbon dioxide removal (CDR) measures (see 3.4.1). (high confidence) {WGI SPM C.2.7, WGI Figure SPM.6, WGI TS.4.3; WGII SPM B.1.7, WGII B.2.2, WGII SPM B.5, WGII SPM B.5.4, WGII SPM C.4.2, WGII SPM B.5, WGII CCB2} Solar Radiation Modiﬁcation (SRM) approaches, if they were to be implemented, introduce a widespread range of new risks to people and ecosystems, which are not well understood. SRM has the potential to offset warming within one or two decades and ameliorate some climate hazards but would not restore climate to a previous state, and substantial residual or overcompensating climate change would occur at regional and seasonal scales (high conﬁdence). Effects of SRM would depend on the speciﬁc approach used122, and a sudden and sustained termination of SRM in a high CO2 emissions scenario would cause rapid climate change (high conﬁdence). SRM would not stop atmospheric CO2 concentrations from increasing nor reduce resulting ocean acidiﬁcation under continued anthropogenic emissions (high conﬁdence). Large uncertainties and knowledge gaps are associated with the potential of SRM approaches to reduce climate change risks. Lack of robust and formal SRM governance poses risks as deployment by a limited number of states could create international tensions.
SRM has the potential to offset warming within one or two decades and ameliorate some climate hazards but would not restore climate to a previous state, and substantial residual or overcompensating climate change would occur at regional and seasonal scales (high conﬁdence). Effects of SRM would depend on the speciﬁc approach used122, and a sudden and sustained termination of SRM in a high CO2 emissions scenario would cause rapid climate change (high conﬁdence). SRM would not stop atmospheric CO2 concentrations from increasing nor reduce resulting ocean acidiﬁcation under continued anthropogenic emissions (high conﬁdence). Large uncertainties and knowledge gaps are associated with the potential of SRM approaches to reduce climate change risks. Lack of robust and formal SRM governance poses risks as deployment by a limited number of states could create international tensions. {WGI 4.6; WGII SPM B.5.5; WGIII 14.4.5.1; WGIII 14 Cross-Working Group Box Solar Radiation Modification; SR1.5 SPM C.1.4} 122 Several SRM approaches have been proposed, including stratospheric aerosol injection, marine cloud brightening, ground-based albedo modiﬁcations, and ocean albedo change. See Annex I: Glossary.
73 Long-Term Climate and Development Futures Section 3 c1) Maize yield4 c2) Fisheries yield5 Changes (%) in maximum catch potential Changes (%) in yield -20 -10 -3 -30 -25 -15 -35% +20 +30 +35% +10 +3 +25 +15 1 0 days 300 100 200 10 150 250 50 365 days 0.1 0% 80 10 40 1 20 60 5 100% Areas with model disagreement Examples of impacts without additional adaptation 2.4 – 3.1°C 4.2 – 5.4°C 1.5°C 3.0°C 1.7 – 2.3°C 0.9 – 2.0°C 3.4 – 5.2°C 1.6 – 2.4°C 3.3 – 4.8°C 3.9 – 6.0°C 2.0°C 4.0°C Percentage of animal species and seagrasses exposed to potentially dangerous temperature conditions1, 2 Days per year where combined temperature and humidity conditions pose a risk of mortality to individuals3 5Projected regional impacts reﬂect ﬁsheries and marine ecosystem responses to ocean physical and biogeochemical conditions such as temperature, oxygen level and net primary production. Models do not represent changes in ﬁshing activities and some extreme climatic conditions. Projected changes in the Arctic regions have low conﬁdence due to uncertainties associated with modelling multiple interacting drivers and ecosystem responses. 4Projected regional impacts reﬂect biophysical responses to changing temperature, precipitation, solar radiation, humidity, wind, and CO2 enhancement of growth and water retention in currently cultivated areas. Models assume that irrigated areas are not water-limited. Models do not represent pests, diseases, future agro-technological changes and some extreme climate responses.
Models do not represent changes in ﬁshing activities and some extreme climatic conditions. Projected changes in the Arctic regions have low conﬁdence due to uncertainties associated with modelling multiple interacting drivers and ecosystem responses. 4Projected regional impacts reﬂect biophysical responses to changing temperature, precipitation, solar radiation, humidity, wind, and CO2 enhancement of growth and water retention in currently cultivated areas. Models assume that irrigated areas are not water-limited. Models do not represent pests, diseases, future agro-technological changes and some extreme climate responses. Future climate change is projected to increase the severity of impacts across natural and human systems and will increase regional differences Areas with little or no production, or not assessed 1Projected temperature conditions above the estimated historical (1850-2005) maximum mean annual temperature experienced by each species, assuming no species relocation. 2Includes 30,652 species of birds, mammals, reptiles, amphibians, marine ﬁsh, benthic marine invertebrates, krill, cephalopods, corals, and seagrasses. a) Risk of species losses b) Heat-humidity risks to human health c) Food production impacts 3Projected regional impacts utilize a global threshold beyond which daily mean surface air temperature and relative humidity may induce hyperthermia that poses a risk of mortality. The duration and intensity of heatwaves are not presented here. Heat-related health outcomes vary by location and are highly moderated by socio-economic, occupational and other non-climatic determinants of individual health and socio-economic vulnerability. The threshold used in these maps is based on a single study that synthesized data from 783 cases to determine the relationship between heat-humidity conditions and mortality drawn largely from observations in temperate climates. Historical 1991–2005
74 Section 3 Section 1 Section 3 Figure 3.2: Projected risks and impacts of climate change on natural and human systems at different global warming levels (GWLs) relative to 1850-1900 levels. Projected risks and impacts shown on the maps are based on outputs from different subsets of Earth system models that were used to project each impact indicator without additional adaptation. WGII provides further assessment of the impacts on human and natural systems using these projections and additional lines of evidence. (a) Risks of species losses as indicated by the percentage of assessed species exposed to potentially dangerous temperature conditions, as deﬁned by conditions beyond the estimated historical (1850–2005) maximum mean annual temperature experienced by each species, at GWLs of 1.5°C, 2°C, 3°C and 4°C. Underpinning projections of temperature are from 21 Earth system models and do not consider extreme events impacting ecosystems such as the Arctic. (b) Risk to human health as indicated by the days per year of population exposure to hypothermic conditions that pose a risk of mortality from surface air temperature and humidity conditions for historical period (1991–2005) and at GWLs of 1.7°C to 2.3°C (mean = 1.9°C; 13 climate models), 2.4°C to 3.1°C (2.7°C; 16 climate models) and 4.2°C to 5.4°C (4.7°C; 15 climate models). Interquartile ranges of WGLs by 2081–2100 under RCP2.6, RCP4.5 and RCP8.5. The presented index is consistent with common features found in many indices included within WGI and WGII assessments. (c) Impacts on food production: (c1) Changes in maize yield at projected GWLs of 1.6°C to 2.4°C (2.0°C), 3.3°C to 4.8°C (4.1°C) and 3.9°C to 6.0°C (4.9°C).
Interquartile ranges of WGLs by 2081–2100 under RCP2.6, RCP4.5 and RCP8.5. The presented index is consistent with common features found in many indices included within WGI and WGII assessments. (c) Impacts on food production: (c1) Changes in maize yield at projected GWLs of 1.6°C to 2.4°C (2.0°C), 3.3°C to 4.8°C (4.1°C) and 3.9°C to 6.0°C (4.9°C). Median yield changes from an ensemble of 12 crop models, each driven by bias-adjusted outputs from 5 Earth system models from the Agricultural Model Intercomparison and Improvement Project (AgMIP) and the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Maps depict 2080–2099 compared to 1986–2005 for current growing regions (>10 ha), with the corresponding range of future global warming levels shown under SSP1-2.6, SSP3-7.0 and SSP5-8.5, respectively. Hatching indicates areas where <70% of the climate-crop model combinations agree on the sign of impact. (c2) Changes in maximum ﬁsheries catch potential by 2081–2099 relative to 1986-2005 at projected GWLs of 0.9°C to 2.0°C (1.5°C) and 3.4°C to 5.2°C (4.3°C). GWLs by 2081–2100 under RCP2.6 and RCP8.5. Hatching indicates where the two climate-ﬁsheries models disagree in the direction of change. Large relative changes in low yielding regions may correspond to small absolute changes. Biodiversity and ﬁsheries in Antarctica were not analysed due to data limitations. Food security is also affected by crop and ﬁshery failures not presented here. {WGII Fig.
Hatching indicates areas where <70% of the climate-crop model combinations agree on the sign of impact. (c2) Changes in maximum ﬁsheries catch potential by 2081–2099 relative to 1986-2005 at projected GWLs of 0.9°C to 2.0°C (1.5°C) and 3.4°C to 5.2°C (4.3°C). GWLs by 2081–2100 under RCP2.6 and RCP8.5. Hatching indicates where the two climate-ﬁsheries models disagree in the direction of change. Large relative changes in low yielding regions may correspond to small absolute changes. Biodiversity and ﬁsheries in Antarctica were not analysed due to data limitations. Food security is also affected by crop and ﬁshery failures not presented here. {WGII Fig. TS.5, WGII Fig TS.9, WGII Annex I: Global to Regional Atlas Figure AI.15, Figure AI.22, Figure AI.23, Figure AI.29; WGII 7.3.1.2, 7.2.4.1, SROCC Figure SPM.3} (3.1.2, Cross-Section Box.2)
75 Long-Term Climate and Development Futures Section 3 Salt marshes Rocky shores Seagrass meadows Epipelagic Warm-water corals Kelp forests AR5 AR6 AR5 AR6 AR5 AR6 AR5 AR6 AR5 AR6 Global surface temperature change relative to 1850–1900 Global Reasons for Concern (RFCs) in AR5 (2014) vs. AR6 (2022) °C 0 1 1.5 2 3 4 5 0 1 1.5 2 3 4 5 °C 0 –1 2000 2015 2050 2100 1 2 3 4 5 very low low intermediate high very high •••• •••• ••• •••• ••• •• ••• •• •• ••• •• • •• •• •• damage Wildﬁre ••• •• •• Dryland water scarcity ••• •• •• 0 2 3 4 1.5 1 Incomplete adaptation Proactive adaptation Limited adaptation •• •• •• •• •• Heat-related morbidity and mortality high Challenges to Adaptation low ••• •••• •••• ••• ••• ••• •••• ••• ••• ••• •• •• •• •• • ••• •• •• Conﬁdence level assigned to transition range midpoint of transition Risk/impact Low Very high Very high High Moderate Undetectable • ••• •• •••• Transition range °C °C Permafrost degradation ••• ••• •• e.g.
increase in the length of ﬁre season e.g. over 100 million additional people exposed 0 –1 1950 2000 2015 2050 1 2 3 4 50 100 0 75 25 Resource-rich coastal cities Large tropical agricultural deltas Arctic communities Urban atoll islands r R Maximum potential response No-to-moderate response r R r R r R r R Global mean sea level rise relative to 1900 50 100 0 1950 2000 2050 2100 75 25 cm cm very high high intermediate low very low c) Risks to coastal geographies increase with sea level rise and depend on responses 1986-2005 baseline low-likelihood, high impact storyline, including ice-sheet instability processes •••• ••• •• •••• •••• ••• d) Adaptation and socio-economic pathways affect levels of climate related risks b) Risks differ by system SSP1 SSP3 Risks are increasing with every increment of warming Global aggregate impacts Unique & threatened systems Extreme weather events Distribution of impacts Large scale singular events risk is the potential for adverse consequences ••• •• •• Tree mortality e.g. coral reefs decline >99% e.g. coral reefs decline by 70–90% Land-based systems Ocean/coastal ecosystems Food insecurity (availability, access) a) High risks are now assessed to occur at lower global warming levels The SSP1 pathway illustrates a world with low population growth, high income, and reduced inequalities, food produced in low GHG emission systems, effective land use regulation and high adaptive capacity (i.e., low challenges to adaptation). The SSP3 pathway has the opposite trends.
coral reefs decline >99% e.g. coral reefs decline by 70–90% Land-based systems Ocean/coastal ecosystems Food insecurity (availability, access) a) High risks are now assessed to occur at lower global warming levels The SSP1 pathway illustrates a world with low population growth, high income, and reduced inequalities, food produced in low GHG emission systems, effective land use regulation and high adaptive capacity (i.e., low challenges to adaptation). The SSP3 pathway has the opposite trends. shading represents the uncertainty ranges for the low and high emissions scenarios 2011-2020 was around 1.1°C warmer than 1850-1900 Carbon loss •• • •• •• •• ••• Biodiversity loss Risks are assessed with medium conﬁdence Limited adaptation (failure to proactively adapt; low investment in health systems); incomplete adaptation (incomplete adaptation planning; moderate investment in health systems); proactive adaptation (proactive adaptation management; higher investment in health systems)
76 Section 3 Section 1 Section 3 0 1 1.5 2 3 4 0 1 1.5 2 3 4 °C °C 0 1 1.5 2 3 4 0 1 1.5 2 3 4 °C °C Europe -Risks to people, economies and infrastructures due to coastal and inland ﬂooding -Stress and mortality to people due to increasing temperatures and heat extremes -Marine and terrestrial ecosystems disruptions -Water scarcity to multiple interconnected sectors -Losses in crop production, due to compound heat and dry conditions, and extreme weather Small Islands -Loss of terrestrial, marine and coastal biodiversity and ecosystem services -Loss of lives and assets, risk to food security and economic disruption due to destruction of settlements and infrastructure -Economic decline and livelihood failure of ﬁsheries, agriculture, tourism and from biodiversity loss from traditional agroecosystems -Reduced habitability of reef and non-reef islands leading to increased displacement -Risk to water security in almost every small island Africa -Species extinction and reduction or irreversible loss of ecosystems and their services, including freshwater, land and ocean ecosystems -Risk to food security, risk of malnutrition (micronutrient deﬁciency), and loss of livelihood due to reduced food production from crops, livestock and ﬁsheries -Risks to marine ecosystem health and to livelihoods in coastal communities -Increased human mortality and morbidity due to increased heat and infectious diseases (including vector-borne and diarrhoeal diseases) -Reduced economic output and growth,
risk to food security and economic disruption due to destruction of settlements and infrastructure -Economic decline and livelihood failure of ﬁsheries, agriculture, tourism and from biodiversity loss from traditional agroecosystems -Reduced habitability of reef and non-reef islands leading to increased displacement -Risk to water security in almost every small island Africa -Species extinction and reduction or irreversible loss of ecosystems and their services, including freshwater, land and ocean ecosystems -Risk to food security, risk of malnutrition (micronutrient deﬁciency), and loss of livelihood due to reduced food production from crops, livestock and ﬁsheries -Risks to marine ecosystem health and to livelihoods in coastal communities -Increased human mortality and morbidity due to increased heat and infectious diseases (including vector-borne and diarrhoeal diseases) -Reduced economic output and growth, and increased inequality and poverty rates -Increased risk to water and energy security due to drought and heat Aus- tralasia -Degradation of tropical shallow coral reefs and associated biodiversity and ecosystem service values -Loss of human and natural systems in low-lying coastal areas due to sea level rise -Impact on livelihoods and incomes due to decline in agricultural production -Increase in heat-related mortality and morbidity for people and wildlife -Loss of alpine biodiversity in Australia due to less snow Asia -Urban infrastructure damage and impacts on human well-being and health due to ﬂooding, especially in coastal cities and settlements -Biodiversity loss and habitat shifts as well as associated disruptions in dependent human systems across freshwater, land, and ocean ecosystems -More frequent, extensive coral bleaching and subsequent coral mortality induced by ocean warming and acidiﬁcation, sea level rise, marine heat waves and resource extraction -Decline in coastal ﬁshery resources due to sea level rise, decrease in precipitation in some parts and increase in temperature -Risk to food and water security due to increased temperature extremes, rainfall variability and drought Central and South America -Risk to water security -Severe health effects due to increasing epidemics,
especially in coastal cities and settlements -Biodiversity loss and habitat shifts as well as associated disruptions in dependent human systems across freshwater, land, and ocean ecosystems -More frequent, extensive coral bleaching and subsequent coral mortality induced by ocean warming and acidiﬁcation, sea level rise, marine heat waves and resource extraction -Decline in coastal ﬁshery resources due to sea level rise, decrease in precipitation in some parts and increase in temperature -Risk to food and water security due to increased temperature extremes, rainfall variability and drought Central and South America -Risk to water security -Severe health effects due to increasing epidemics, in particular vector-borne diseases -Coral reef ecosystems degradation due to coral bleaching -Risk to food security due to frequent/extreme droughts -Damages to life and infrastructure due to ﬂoods, landslides, sea level rise, storm surges and coastal erosion North America -Climate-sensitive mental health outcomes, human mortality and morbidity due to increasing average temperature, weather and climate extremes, and compound climate hazards -Risk of degradation of marine, coastal and terrestrial ecosystems, including loss of biodiversity, function, and protective services -Risk to freshwater resources with consequences for ecosystems, reduced surface water availability for irrigated agriculture, other human uses, and degraded water quality -Risk to food and nutritional security through changes in agriculture, livestock, hunting, ﬁsheries, and aquaculture productivity and access -Risks to well-being, livelihoods and economic activities from cascading and compounding climate hazards, including risks to coastal cities, settlements and infrastructure from sea level rise Delayed impacts of sea level rise in the Mediterranean Food production from crops, ﬁsheries and livestock in Africa Mortality and morbidity from heat and infectious disease in Africa Biodiversity and ecosystems in Africa Health and wellbeing in the Mediterranean Water scarcity to people in southeastern Europe Coastal ﬂooding to people and infrastructures in Europe Heat stress,
and degraded water quality -Risk to food and nutritional security through changes in agriculture, livestock, hunting, ﬁsheries, and aquaculture productivity and access -Risks to well-being, livelihoods and economic activities from cascading and compounding climate hazards, including risks to coastal cities, settlements and infrastructure from sea level rise Delayed impacts of sea level rise in the Mediterranean Food production from crops, ﬁsheries and livestock in Africa Mortality and morbidity from heat and infectious disease in Africa Biodiversity and ecosystems in Africa Health and wellbeing in the Mediterranean Water scarcity to people in southeastern Europe Coastal ﬂooding to people and infrastructures in Europe Heat stress, mortality and morbidity to people in Europe Water quality and availability in the Mediterranean ••• ••• ••• ••• ••• •• •• •• •• •••• ••• ••• Costs and damages related to maintenance and reconstruction of transportation infrastructure in North America Lyme disease in North America under incomplete adaptation scenario Loss and degradation of coral reefs in Australia Reduced viability of tourism- related activities in North America Cascading impacts on cities and settlements in Australasia Changes in ﬁsheries catch for Pollock and Paciﬁc Cod in the Arctic Costs and losses for key infrastructure in the Arctic Sea-ice dependent ecosystems in the Antarctic Changes in krill ﬁsheries in the Antarctic Sea-ice ecosystems from sea-ice change in the Arctic ••• ••• •• •• •• •• ••• •• •• ••• •• ••• ••• ••• ••• •• ••• •• •••••• •• •• • • ••• •• •• ••• ••• • ••• •• • •••• ••• ••• ••• •• ••• ••• •• • •• ••• e) Examples of key risks in different regions Absence of risk diagrams does not imply absence of risks within a region.
The development of synthetic diagrams for Small Islands, Asia and Central and South America was limited due to the paucity of adequately downscaled climate projections, with uncertainty in the direction of change, the diversity of climatologies and socioeconomic contexts across countries within a region, and the resulting few numbers of impact and risk projections for different warming levels. The risks listed are of at least medium conﬁdence level:
77 Long-Term Climate and Development Futures Section 3 Figure 3.3: Synthetic risk diagrams of global and sectoral assessments and examples of regional key risks. The burning embers result from a literature based expert elicitation. Panel (a): Left - Global surface temperature changes in °C relative to 1850–1900. These changes were obtained by combining CMIP6 model simulations with observational constraints based on past simulated warming, as well as an updated assessment of equilibrium climate sensitivity. Very likely ranges are shown for the low and high GHG emissions scenarios (SSP1-2.6 and SSP3-7.0). Right - Global Reasons for Concern, comparing AR6 (thick embers) and AR5 (thin embers) assessments. Diagrams are shown for each RFC, assuming low to no adaptation (i.e., adaptation is fragmented, localised and comprises incremental adjustments to existing practices). However, the transition to a very high-risk level has an emphasis on irreversibility and adaptation limits. The horizontal line denotes the present global warming of 1.1°C which is used to separate the observed, past impacts below the line from the future projected risks above it. Lines connect the midpoints of the transition from moderate to high risk across AR5 and AR6. Panel (b): Risks for land-based systems and ocean/coastal ecosystems. Diagrams shown for each risk assume low to no adaptation. Text bubbles indicate examples of impacts at a given warming level. Panel (c): Left - Global mean sea level change in centimetres, relative to 1900. The historical changes (black) are observed by tide gauges before 1992 and altimeters afterwards. The future changes to 2100 (coloured lines and shading) are assessed consistently with observational constraints based on emulation of CMIP, ice-sheet, and glacier models, and likely ranges are shown for SSP1-2.6 and SSP3-7.0.
Lines connect the midpoints of the transition from moderate to high risk across AR5 and AR6. Panel (b): Risks for land-based systems and ocean/coastal ecosystems. Diagrams shown for each risk assume low to no adaptation. Text bubbles indicate examples of impacts at a given warming level. Panel (c): Left - Global mean sea level change in centimetres, relative to 1900. The historical changes (black) are observed by tide gauges before 1992 and altimeters afterwards. The future changes to 2100 (coloured lines and shading) are assessed consistently with observational constraints based on emulation of CMIP, ice-sheet, and glacier models, and likely ranges are shown for SSP1-2.6 and SSP3-7.0. Right - Assessment of the combined risk of coastal ﬂooding, erosion and salinization for four illustrative coastal geographies in 2100, due to changing mean and extreme sea levels, under two response scenarios, with respect to the SROCC baseline period (1986–2005) and indicating the IPCC AR6 baseline period (1995–2014). The assessment does not account for changes in extreme sea level beyond those directly induced by mean sea level rise; risk levels could increase if other changes in extreme sea levels were considered (e.g., due to changes in cyclone intensity). “No-to-moderate response” describes efforts as of today (i.e., no further signiﬁcant action or new types of actions). “Maximum potential response” represents a combination of responses implemented to their full extent and thus signiﬁcant additional efforts compared to today, assuming minimal ﬁnancial, social and political barriers. The assessment criteria include exposure and vulnerability (density of assets, level of degradation of terrestrial and marine buffer ecosystems), coastal hazards (ﬂooding, shoreline erosion, salinization), in-situ responses (hard engineered coastal defences, ecosystem restoration or creation of new natural buffers areas, and subsidence management) and planned relocation. Planned relocation refers to managed retreat or resettlement. Forced displacement is not considered in this assessment.
“No-to-moderate response” describes efforts as of today (i.e., no further signiﬁcant action or new types of actions). “Maximum potential response” represents a combination of responses implemented to their full extent and thus signiﬁcant additional efforts compared to today, assuming minimal ﬁnancial, social and political barriers. The assessment criteria include exposure and vulnerability (density of assets, level of degradation of terrestrial and marine buffer ecosystems), coastal hazards (ﬂooding, shoreline erosion, salinization), in-situ responses (hard engineered coastal defences, ecosystem restoration or creation of new natural buffers areas, and subsidence management) and planned relocation. Planned relocation refers to managed retreat or resettlement. Forced displacement is not considered in this assessment. The term response is used here instead of adaptation because some responses, such as retreat, may or may not be considered to be adaptation. Panel (d): Left - Heat-sensitive human health outcomes under three scenarios of adaptation effectiveness. The diagrams are truncated at the nearest whole ºC within the range of temperature change in 2100 under three SSP scenarios. Right - Risks associated with food security due to climate change and patterns of socio-economic development. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3) excluding the effects of targeted mitigation and adaptation policies. Panel (e): Examples of regional key risks. Risks identiﬁed are of at least medium conﬁdence level. Key risks are identiﬁed based on the magnitude of adverse consequences (pervasiveness of the consequences, degree of change, irreversibility of consequences, potential for impact thresholds or tipping points, potential for cascading effects beyond system boundaries); likelihood of adverse consequences; temporal characteristics of the risk; and ability to respond to the risk, e.g., by adaptation.
Right - Risks associated with food security due to climate change and patterns of socio-economic development. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3) excluding the effects of targeted mitigation and adaptation policies. Panel (e): Examples of regional key risks. Risks identiﬁed are of at least medium conﬁdence level. Key risks are identiﬁed based on the magnitude of adverse consequences (pervasiveness of the consequences, degree of change, irreversibility of consequences, potential for impact thresholds or tipping points, potential for cascading effects beyond system boundaries); likelihood of adverse consequences; temporal characteristics of the risk; and ability to respond to the risk, e.g., by adaptation. {WGI Figure SPM.8; WGII SPM B.3.3, WGII Figure SPM.3, WGII SM 16.6, WGII SM 16.7.4; SROCC Figure SPM.3d, SROCC SPM.5a, SROCC 4SM; SRCCL Figure SPM.2, SRCCL 7.3.1, SRCCL 7 SM} (Cross-Section Box.2) 3.1.3 The Likelihood and Risks of Abrupt and Irreversible Change The likelihood of abrupt and irreversible changes and their impacts increase with higher global warming levels (high conﬁdence). As warming levels increase, so do the risks of species extinction or irreversible loss of biodiversity in ecosystems such as forests (medium conﬁdence), coral reefs (very high conﬁdence) and in Arctic regions (high conﬁdence). Risks associated with large-scale singular events or tipping points, such as ice sheet instability or ecosystem loss from tropical forests, transition to high risk between 1.5°C to 2.5°C (medium conﬁdence) and to very high risk between 2.5°C to 4°C (low conﬁdence).
As warming levels increase, so do the risks of species extinction or irreversible loss of biodiversity in ecosystems such as forests (medium conﬁdence), coral reefs (very high conﬁdence) and in Arctic regions (high conﬁdence). Risks associated with large-scale singular events or tipping points, such as ice sheet instability or ecosystem loss from tropical forests, transition to high risk between 1.5°C to 2.5°C (medium conﬁdence) and to very high risk between 2.5°C to 4°C (low conﬁdence). The response of biogeochemical cycles to anthropogenic perturbations can be abrupt at regional scales and irreversible on decadal to century time scales (high conﬁdence). The probability of crossing uncertain regional thresholds increases with further warming (high conﬁdence). {WGI SPM C.3.2, WGI Box TS.9, WGI TS.2.6; WGII Figure SPM.3, WGII SPM B.3.1, WGII SPM B.4.1, WGII SPM B.5.2, WGII Table TS.1, WGII TS.C.1, WGII TS.C.13.3; SROCC SPM B.4} Sea level rise is unavoidable for centuries to millennia due to continuing deep ocean warming and ice sheet melt, and sea levels will remain elevated for thousands of years (high conﬁdence). Global mean sea level rise will continue in the 21st century (virtually certain), with projected regional relative sea level rise within 20% of the global mean along two-thirds of the global coastline (medium conﬁdence). The magnitude, the rate, the timing of threshold exceedances, and the long-term commitment of sea level rise depend on emissions, with higher emissions leading to greater and faster rates of sea level rise.
Global mean sea level rise will continue in the 21st century (virtually certain), with projected regional relative sea level rise within 20% of the global mean along two-thirds of the global coastline (medium conﬁdence). The magnitude, the rate, the timing of threshold exceedances, and the long-term commitment of sea level rise depend on emissions, with higher emissions leading to greater and faster rates of sea level rise. Due to relative sea level rise, extreme sea level events that occurred once per century in the recent past are projected to occur at least annually at more than half of all tide gauge locations by 2100 123 This outcome is characterised by deep uncertainty: Its likelihood defies quantitative assessment but is considered due to its high potential impact. {WGI Box TS.1; WGII Cross-Chapter Box DEEP} and risks for coastal ecosystems, people and infrastructure will continue to increase beyond 2100 (high conﬁdence). At sustained warming levels between 2°C and 3°C, the Greenland and West Antarctic ice sheets will be lost almost completely and irreversibly over multiple millennia (limited evidence). The probability and rate of ice mass loss increase with higher global surface temperatures (high conﬁdence). Over the next 2000 years, global mean sea level will rise by about 2 to 3 m if warming is limited to 1.5°C and 2 to 6 m if limited to 2°C (low conﬁdence). Projections of multi-millennial global mean sea level rise are consistent with reconstructed levels during past warm climate periods: global mean sea level was very likely 5 to 25 m higher than today roughly 3 million years ago, when global temperatures were 2.5°C to 4°C higher than 1850–1900 (medium conﬁdence). Further examples of unavoidable changes in the climate system due to multi-decadal or longer response timescales include continued glacier melt (very high conﬁdence) and permafrost carbon loss (high conﬁdence).
Over the next 2000 years, global mean sea level will rise by about 2 to 3 m if warming is limited to 1.5°C and 2 to 6 m if limited to 2°C (low conﬁdence). Projections of multi-millennial global mean sea level rise are consistent with reconstructed levels during past warm climate periods: global mean sea level was very likely 5 to 25 m higher than today roughly 3 million years ago, when global temperatures were 2.5°C to 4°C higher than 1850–1900 (medium conﬁdence). Further examples of unavoidable changes in the climate system due to multi-decadal or longer response timescales include continued glacier melt (very high conﬁdence) and permafrost carbon loss (high conﬁdence). {WGI SPM B.5.2, WGI SPM B.5.3, WGI SPM B.5.4, WGI SPM C.2.5, WGI Box TS.4, WGI Box TS.9, WGI 9.5.1; WGII TS C.5; SROCC SPM B.3, SROCC SPM B.6, SROCC SPM B.9} (Figure 3.4) The probability of low-likelihood outcomes associated with potentially very large impacts increases with higher global warming levels (high conﬁdence). Warming substantially above the assessed very likely range for a given scenario cannot be ruled out, and there is high conﬁdence this would lead to regional changes greater than assessed in many aspects of the climate system. Low-likelihood, high-impact outcomes could occur at regional scales even for global warming within the very likely assessed range for a given GHG emissions scenario. Global mean sea level rise above the likely range – approaching 2 m by 2100 and in excess of 15 m by 2300 under a very high GHG emissions scenario (SSP5-8.5) (low confidence) – cannot be ruled out due to deep uncertainty in ice-sheet processes123 and would have severe
78 Section 3 Section 1 Section 3 impacts on populations in low elevation coastal zones. If global warming increases, some compound extreme events124 will become more frequent, with higher likelihood of unprecedented intensities, durations or spatial extent (high confidence). The Atlantic Meridional Overturning Circulation is very likely to weaken over the 21st century for all considered scenarios (high conﬁdence), however an abrupt collapse is not expected before 2100 (medium conﬁdence). If such a low probability event were to occur, it would very likely cause abrupt shifts in regional weather patterns and water cycle, 124 See Annex I: Glossary. Examples of compound extreme events are concurrent heatwaves and droughts or compound ﬂooding. {WGI SPM Footnote 18} such as a southward shift in the tropical rain belt, and large impacts on ecosystems and human activities. A sequence of large explosive volcanic eruptions within decades, as have occurred in the past, is a low-likelihood high-impact event that would lead to substantial cooling globally and regional climate perturbations over several decades. {WGI SPM B.5.3, WGI SPM C.3, WGI SPM C.3.1, WGI SPM C.3.2, WGI SPM C.3.3, WGI SPM C.3.4, WGI SPM C.3.5, WGI Figure SPM.8, WGI Box TS.3, WGI Figure TS.6, WGI Box 9.4; WGII SPM B.4.5, WGII SPM C.2.8; SROCC SPM B.2.7} (Figure 3.4, Cross-Section Box.2) 3.2 Long-term Adaptation Options and Limits With increasing warming, adaptation options will become more constrained and less effective. At higher levels of warming, losses and damages will increase, and additional human and natural systems will reach adaptation limits. Integrated, cross-cutting multi-sectoral solutions increase the effectiveness of adaptation.
At higher levels of warming, losses and damages will increase, and additional human and natural systems will reach adaptation limits. Integrated, cross-cutting multi-sectoral solutions increase the effectiveness of adaptation. Maladaptation can create lock-ins of vulnerability, exposure and risks but can be avoided by long-term planning and the implementation of adaptation actions that are ﬂexible, multi-sectoral and inclusive. (high conﬁdence) The effectiveness of adaptation to reduce climate risk is documented for speciﬁc contexts, sectors and regions and will decrease with increasing warming (high conﬁdence)125. For example, common adaptation responses in agriculture – adopting improved cultivars and agronomic practices, and changes in cropping patterns and crop systems – will become less effective from 2°C to higher levels of warming (high confidence). The effectiveness of most water-related adaptation options to reduce projected risks declines with increasing warming (high confidence). Adaptations for hydropower and thermo-electric power generation are effective in most regions up to 1.5°C to 2°C, with decreasing effectiveness at higher levels of warming (medium conﬁdence). Ecosystem-based Adaptation is vulnerable to climate change impacts, with effectiveness declining with increasing global warming (high conﬁdence). Globally, adaptation options related to agroforestry and forestry have a sharp decline in effectiveness at 3°C, with a substantial increase in residual risk (medium conﬁdence). {WGII SPM C.2, WGII SPM C.2.1, WGII SPM C.2.5, WGII SPM C.2.10, WGII Figure TS.6 Panel (e), 4.7.2} With increasing global warming, more limits to adaptation will be reached and losses and damages, strongly concentrated among the poorest vulnerable populations, will increase (high conﬁdence). Already below 1.5°C, autonomous and evolutionary adaptation responses by terrestrial and aquatic ecosystems will increasingly face hard limits (high conﬁdence) (Section 2.1.2).
Globally, adaptation options related to agroforestry and forestry have a sharp decline in effectiveness at 3°C, with a substantial increase in residual risk (medium conﬁdence). {WGII SPM C.2, WGII SPM C.2.1, WGII SPM C.2.5, WGII SPM C.2.10, WGII Figure TS.6 Panel (e), 4.7.2} With increasing global warming, more limits to adaptation will be reached and losses and damages, strongly concentrated among the poorest vulnerable populations, will increase (high conﬁdence). Already below 1.5°C, autonomous and evolutionary adaptation responses by terrestrial and aquatic ecosystems will increasingly face hard limits (high conﬁdence) (Section 2.1.2). Above 1.5°C, some ecosystem-based adaptation measures will lose their effectiveness in providing beneﬁts to people as these ecosystems will reach hard adaptation limits (high conﬁdence). Adaptation to address the risks of heat stress, heat mortality and reduced capacities for outdoor work for humans face soft and hard limits across regions that become signiﬁcantly more severe at 1.5°C, and are particularly relevant for regions with warm climates (high conﬁdence). Above 1.5°C global warming level, limited freshwater resources pose potential hard limits for small islands and for regions dependent on glacier and snow melt 124 See Annex I: Glossary. Examples of compound extreme events are concurrent heatwaves and droughts or compound ﬂooding. {WGI SPM Footnote 18} 125 There are limitations to assessing the full scope of adaptation options available in the future since not all possible future adaptation responses can be incorporated in climate impact models, and projections of future adaptation depend on currently available technologies or approaches. {WGII 4.7.2} (medium confidence). By 2°C, soft limits are projected for multiple staple crops, particularly in tropical regions (high conﬁdence).
Above 1.5°C global warming level, limited freshwater resources pose potential hard limits for small islands and for regions dependent on glacier and snow melt 124 See Annex I: Glossary. Examples of compound extreme events are concurrent heatwaves and droughts or compound ﬂooding. {WGI SPM Footnote 18} 125 There are limitations to assessing the full scope of adaptation options available in the future since not all possible future adaptation responses can be incorporated in climate impact models, and projections of future adaptation depend on currently available technologies or approaches. {WGII 4.7.2} (medium confidence). By 2°C, soft limits are projected for multiple staple crops, particularly in tropical regions (high conﬁdence). By 3°C, soft limits are projected for some water management measures for many regions, with hard limits projected for parts of Europe (medium conﬁdence). {WGII SPM C.3, WGII SPM C.3.3, WGII SPM C.3.4, WGII SPM C.3.5, WGII TS.D.2.2, WGII TS.D.2.3; SR1.5 SPM B.6; SROCC SPM C.1} Integrated, cross-cutting multi-sectoral solutions increase the effectiveness of adaptation. For example, inclusive, integrated and long-term planning at local, municipal, sub-national and national scales, together with effective regulation and monitoring systems and ﬁnancial and technological resources and capabilities foster urban and rural system transition. There are a range of cross-cutting adaptation options, such as disaster risk management, early warning systems, climate services and risk spreading and sharing that have broad applicability across sectors and provide greater beneﬁts to other adaptation options when combined. Transitioning from incremental to transformational adaptation, and addressing a range of constraints, primarily in the ﬁnancial, governance, institutional and policy domains, can help overcome soft adaptation limits. However, adaptation does not prevent all losses and damages, even with effective adaptation and before reaching soft and hard limits.
For example, inclusive, integrated and long-term planning at local, municipal, sub-national and national scales, together with effective regulation and monitoring systems and ﬁnancial and technological resources and capabilities foster urban and rural system transition. There are a range of cross-cutting adaptation options, such as disaster risk management, early warning systems, climate services and risk spreading and sharing that have broad applicability across sectors and provide greater beneﬁts to other adaptation options when combined. Transitioning from incremental to transformational adaptation, and addressing a range of constraints, primarily in the ﬁnancial, governance, institutional and policy domains, can help overcome soft adaptation limits. However, adaptation does not prevent all losses and damages, even with effective adaptation and before reaching soft and hard limits. (high conﬁdence) {WGII SPM C.2, WGII SPM C.2.6, WGII SPM.C.2.13, WGII SPM C.3.1, WGII SPM.C.3.4, WGII SPM C.3.5, WGII Figure TS.6 Panel (e)} Maladaptive responses to climate change can create lock-ins of vulnerability, exposure and risks that are difﬁcult and expensive to change and exacerbate existing inequalities. Actions that focus on sectors and risks in isolation and on short-term gains often lead to maladaptation. Adaptation options can become maladaptive due to their environmental impacts that constrain ecosystem services and decrease biodiversity and ecosystem resilience to climate change or by causing adverse outcomes for different groups, exacerbating inequity. Maladaptation can be avoided by ﬂexible, multi-sectoral, inclusive and
79 Long-Term Climate and Development Futures Section 3 long-term planning and implementation of adaptation actions with beneﬁts to many sectors and systems. (high conﬁdence) {WGII SPM C.4, WGII SPM.C.4.1, WGII SPM C.4.2, WGII SPM C.4.3} Sea level rise poses a distinctive and severe adaptation challenge as it implies both dealing with slow onset changes and increases in the frequency and magnitude of extreme sea level events (high conﬁdence). Such adaptation challenges would occur much earlier under high rates of sea level rise (high conﬁdence). Responses to ongoing sea level rise and land subsidence include protection, accommodation, advance and planned relocation (high conﬁdence). These responses are more effective if combined and/or sequenced, planned well ahead, aligned with sociocultural values and underpinned by inclusive community engagement processes (high conﬁdence). Ecosystem-based solutions such as wetlands provide co-beneﬁts for the environment and climate mitigation, and reduce costs for ﬂood defences (medium conﬁdence), but have site-speciﬁc physical limits, at least above 1.5ºC of global warming (high conﬁdence) and lose effectiveness at high rates of sea level rise beyond 0.5 to 1 cm yr-1 (medium conﬁdence). Seawalls can be maladaptive as they effectively reduce impacts in the short term but can also result in lock-ins and increase exposure to climate risks in the long term unless they are integrated into a long-term adaptive plan (high conﬁdence). {WGI SPM C.2.5; WGII SPM C.2.8, WGII SPM C.4.1; WGII 13.10, WGII Cross-Chapter Box SLR; SROCC SPM B.9, SROCC SPM C.3.2, SROCC Figure SPM.4, SROCC Figure SPM.5c} (Figure 3.4)
80 Section 3 Section 1 Section 3 2020 2100 2050 2150 Ecosystem-based adaptation Sediment-based protection Elevating houses Protect levees Protect barriers Planned relocation ≈30 years ≈50 years ≥100 years ≈100 years ≈15 years ≈15 years Indicative time for planning and implementation Typical intended lifetime of measures Long-living societal legacy 0 1m 2m 3m 0 1m 2m 4m 5m 6m 7m 3m 4m 5m 15m 2000 2020 1950 1900 2100 2050 2150 2300 Sea level rise greater than 15m cannot be ruled out with very high emissions Low-likelihood, high-impact storyline, including ice sheet instability processes under the very high emissions scenario Observed Unavoidable sea level rise will cause: These cascade into risks to: livelihoods, settlements, health, well-being, food and water security and cultural values.
Losses of coastal ecosystems and ecosystem services Groundwater salinisation Flooding and damages to coastal infrastructure Global sea level rise in meters relative to 1900 sea level rise by 2100 depends on the emissions scenario this can be chronic high tide flooding and extreme flooding during storms likely ranges of sea level rise very low low intermediate high very high low emissions scenario range very high emissions scenario range a) Sea level rise: observations and projections 2020-2100, 2150, 2300 (relative to 1900) Sea level rise will continue for millennia, but how fast and how much depends on future emissions Example: timing of 0.5m sea level rise 2000 2100 2200 2300+ very low very high Higher greenhouse gas emissions lead to larger and faster sea level rise, demanding earlier and stronger responses, and reducing the lifetime of some options Key Responding to sea level rise requires long-term planning b) Typical timescales of coastal risk-management measures 1 billion people exposed By 2050: Extreme sea level events that occured once per century will be 20-30 times more frequent
81 Long-Term Climate and Development Futures Section 3 Figure 3.4: Observed and projected global mean sea level change and its impacts, and time scales of coastal risk management. Panel (a): Global mean sea level change in metres relative to 1900. The historical changes (black) are observed by tide gauges before 1992 and altimeters afterwards. The future changes to 2100 and for 2150 (coloured lines and shading) are assessed consistently with observational constraints based on emulation of CMIP, ice-sheet, and glacier models, and median values and likely ranges are shown for the considered scenarios. Relative to 1995-2014, the likely global mean sea level rise by 2050 is between 0.15 to 0.23 m in the very low GHG emissions scenario (SSP1-1.9) and 0.20 to 0.29 m in the very high GHG emissions scenario (SSP5-8.5); by 2100 between 0.28 to 0.55 m under SSP1-1.9 and 0.63 to 1.01 m under SSP5-8.5; and by 2150 between 0.37 to 0.86 m under SSP1-1.9 and 0.98 to 1.88 m under SSP5-8.5 (medium conﬁdence). Changes relative to 1900 are calculated by adding 0.158 m (observed global mean sea level rise from 1900 to 1995-2014) to simulated changes relative to 1995-2014. The future changes to 2300 (bars) are based on literature assessment, representing the 17th–83rd percentile range for SSP1-2.6 (0.3 to 3.1 m) and SSP5-8.5 (1.7 to 6.8 m). Red dashed lines: Low-likelihood, high-impact storyline, including ice sheet instability processes.
Changes relative to 1900 are calculated by adding 0.158 m (observed global mean sea level rise from 1900 to 1995-2014) to simulated changes relative to 1995-2014. The future changes to 2300 (bars) are based on literature assessment, representing the 17th–83rd percentile range for SSP1-2.6 (0.3 to 3.1 m) and SSP5-8.5 (1.7 to 6.8 m). Red dashed lines: Low-likelihood, high-impact storyline, including ice sheet instability processes. These indicate the potential impact of deeply uncertain processes, and show the 83rd percentile of SSP5-8.5 projections that include low-likelihood, high- impact processes that cannot be ruled out; because of low conﬁdence in projections of these processes, this is not part of a likely range. IPCC AR6 global and regional sea level projections are hosted at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. The low-lying coastal zone is currently home to around 896 million people (nearly 11% of the 2020 global population), projected to reach more than one billion by 2050 across all ﬁve SSPs. Panel (b): Typical time scales for the planning, implementation (dashed bars) and operational lifetime of current coastal risk-management measures (blue bars). Higher rates of sea level rise demand earlier and stronger responses and reduce the lifetime of measures (inset). As the scale and pace of sea level rise accelerates beyond 2050, long-term adjustments may in some locations be beyond the limits of current adaptation options and for some small islands and low-lying coasts could be an existential risk. {WGI SPM B.5, WGI C.2.5, WGI Figure SPM.8, WGI 9.6; WGII SPM B.4.5, WGII B.5.2, WGII C.2.8, WGII D.3.3, WGII TS.D.7, WGII Cross-Chapter Box SLR} (Cross-Section Box.2)
82 Section 3 Section 1 Section 3 3.3 Mitigation Pathways Limiting human-caused global warming requires net zero anthropogenic CO2 emissions. Pathways consistent with 1.5°C and 2°C carbon budgets imply rapid, deep, and in most cases immediate GHG emission reductions in all sectors (high conﬁdence). Exceeding a warming level and returning (i.e. overshoot) implies increased risks and potential irreversible impacts; achieving and sustaining global net negative CO2 emissions would reduce warming (high conﬁdence). 3.3.1 Remaining Carbon Budgets Limiting global temperature increase to a speciﬁc level requires limiting cumulative net CO2 emissions to within a ﬁnite carbon budget126, along with strong reductions in other GHGs. For every 1000 GtCO2 emitted by human activity, global mean temperature rises by likely 0.27°C to 0.63°C (best estimate of 0.45°C). This relationship implies that there is a ﬁnite carbon budget that cannot be exceeded in order to limit warming to any given level. {WGI SPM D.1, WGI SPM D.1.1; SR1.5 SPM C.1.3} (Figure 3.5) The best estimates of the remaining carbon budget (RCB) from the beginning of 2020 for limiting warming to 1.5°C with a 50% likelihood127 is estimated to be 500 GtCO2; for 2°C (67% likelihood) this is 1150 GtCO2.128 Remaining carbon budgets have been quantiﬁed based on the assessed value of TCRE and its uncertainty, estimates of historical warming, climate system feedbacks such as emissions from thawing permafrost, and the global surface temperature change after global anthropogenic CO2 emissions reach net zero, as well as variations in projected warming from non-CO2 emissions due in part to mitigation action. The stronger the reductions in non-CO2 emissions the lower the resulting temperatures are for a given RCB or the larger RCB for the same level of temperature change.
The stronger the reductions in non-CO2 emissions the lower the resulting temperatures are for a given RCB or the larger RCB for the same level of temperature change. For instance, the RCB for limiting warming to 1.5°C with a 50% likelihood could vary between 300 to 600 GtCO2 depending on non-CO2 warming129. Limiting warming to 2°C with a 67% (or 83%) likelihood would imply a RCB of 1150 (900) GtCO2 from the beginning of 2020. To stay below 2°C with a 50% likelihood, the RCB is higher, i.e., 1350 GtCO2130. {WGI SPM D.1.2, WGI Table SPM.2; WGIII Box SPM.1, WGIII Box 3.4; SR1.5 SPM C.1.3} 126 See Annex I: Glossary. 127 This likelihood is based on the uncertainty in transient climate response to cumulative net CO2 emissions and additional Earth system feedbacks and provides the probability that global warming will not exceed the temperature levels speciﬁed. {WGI Table SPM.1} 128 Global databases make different choices about which emissions and removals occurring on land are considered anthropogenic. Most countries report their anthropogenic land CO2 ﬂuxes including ﬂuxes due to human-caused environmental change (e.g., CO2 fertilisation) on ‘managed’ land in their National GHG inventories. Using emissions estimates based on these inventories, the remaining carbon budgets must be correspondingly reduced. {WGIII SPM Footnote 9, WGIII TS.3, WGIII Cross-Chapter Box 6} 129 The central case RCB assumes future non-CO2 warming (the net additional contribution of aerosols and non-CO2 GHG) of around 0.1°C above 2010–2019 in line with stringent mitigation scenarios. If additional non-CO2 warming is higher, the RCB for limiting warming to 1.5°C with a 50% likelihood shrinks to around 300 GtCO2.
Most countries report their anthropogenic land CO2 ﬂuxes including ﬂuxes due to human-caused environmental change (e.g., CO2 fertilisation) on ‘managed’ land in their National GHG inventories. Using emissions estimates based on these inventories, the remaining carbon budgets must be correspondingly reduced. {WGIII SPM Footnote 9, WGIII TS.3, WGIII Cross-Chapter Box 6} 129 The central case RCB assumes future non-CO2 warming (the net additional contribution of aerosols and non-CO2 GHG) of around 0.1°C above 2010–2019 in line with stringent mitigation scenarios. If additional non-CO2 warming is higher, the RCB for limiting warming to 1.5°C with a 50% likelihood shrinks to around 300 GtCO2. If, however, additional non-CO2 warming is limited to only 0.05°C (via stronger reductions of CH4 and N2O through a combination of deep structural and behavioural changes, e.g., dietary changes), the RCB could be around 600 GtCO2 for 1.5°C warming. {WGI Table SPM.2, WGI Box TS.7; WGIII Box 3.4} 130 When adjusted for emissions since previous reports, these RCB estimates are similar to SR1.5 but larger than AR5 values due to methodological improvements. {WGI SPM D.1.3} 131 Uncertainties for total carbon budgets have not been assessed and could affect the speciﬁc calculated fractions. 132 See footnote 131. 133 These projected adjustments of carbon sinks to stabilisation or decline of atmospheric CO2 concentrations are accounted for in calculations of remaining carbon budgets. {WGI SPM footnote 32} If the annual CO2 emissions between 2020–2030 stayed, on average, at the same level as 2019, the resulting cumulative emissions would almost exhaust the remaining carbon budget for 1.5°C (50%), and exhaust more than a third of the remaining carbon budget for 2°C (67%) (Figure 3.5).
{WGI SPM D.1.3} 131 Uncertainties for total carbon budgets have not been assessed and could affect the speciﬁc calculated fractions. 132 See footnote 131. 133 These projected adjustments of carbon sinks to stabilisation or decline of atmospheric CO2 concentrations are accounted for in calculations of remaining carbon budgets. {WGI SPM footnote 32} If the annual CO2 emissions between 2020–2030 stayed, on average, at the same level as 2019, the resulting cumulative emissions would almost exhaust the remaining carbon budget for 1.5°C (50%), and exhaust more than a third of the remaining carbon budget for 2°C (67%) (Figure 3.5). Based on central estimates only, historical cumulative net CO2 emissions between 1850 and 2019 (2400 ±240 GtCO2) amount to about four-ﬁfths131 of the total carbon budget for a 50% probability of limiting global warming to 1.5°C (central estimate about 2900 GtCO2) and to about two-thirds132 of the total carbon budget for a 67% probability to limit global warming to 2°C (central estimate about 3550 GtCO2). {WGI Table SPM.2; WGIII SPM B.1.3, WGIII Table 2.1} In scenarios with increasing CO2 emissions, the land and ocean carbon sinks are projected to be less effective at slowing the accumulation of CO2 in the atmosphere (high conﬁdence). While natural land and ocean carbon sinks are projected to take up, in absolute terms, a progressively larger amount of CO2 under higher compared to lower CO2 emissions scenarios, they become less effective, that is, the proportion of emissions taken up by land and ocean decreases with increasing cumulative net CO2 emissions (high conﬁdence). Additional ecosystem responses to warming not yet fully included in climate models, such as GHG ﬂuxes from wetlands, permafrost thaw, and wildﬁres, would further increase concentrations of these gases in the atmosphere (high conﬁdence).
While natural land and ocean carbon sinks are projected to take up, in absolute terms, a progressively larger amount of CO2 under higher compared to lower CO2 emissions scenarios, they become less effective, that is, the proportion of emissions taken up by land and ocean decreases with increasing cumulative net CO2 emissions (high conﬁdence). Additional ecosystem responses to warming not yet fully included in climate models, such as GHG ﬂuxes from wetlands, permafrost thaw, and wildﬁres, would further increase concentrations of these gases in the atmosphere (high conﬁdence). In scenarios where CO2 concentrations peak and decline during the 21st century, the land and ocean begin to take up less carbon in response to declining atmospheric CO2 concentrations (high conﬁdence) and turn into a weak net source by 2100 in the very low GHG emissions scenario (medium confidence)133. {WGI SPM B.4, WGI SPM B.4.1, WGI SPM B.4.2, WGI SPM B.4.3}
83 Long-Term Climate and Development Futures Section 3 0 1000 500 1500 2000 2020 a) Carbon budgets and emissions Lifetime emissions from fossil fuel infrastructure without additional abatement, if historical operating patterns are maintained 2020–2030 CO2 emissions assuming constant at 2019 level 1.5°C (>50% chance) 2°C (83% chance) 2°C (>67% chance) Existing Existing and planned Historical emissions 1850-2019 2°C (83%) 1.5°C (>50%) Carbon budgets 1000 0 2000 Remaining carbon budgets diﬀerent emissions scenarios and their ranges of warming Remaining carbon budgets to limit warming to 1.5°C could soon be exhausted, and those for 2°C largely depleted Remaining carbon budgets are similar to emissions from use of existing and planned fossil fuel infrastructure, without additional abatement these emissions determine how much warming we will experience Warming since 1850-1900 °C Cumulative CO2 emissions (GtCO2) since 1850 Historical global warming SSP1-1.9 SSP1-2.6 SSP2-4.5 SSP3-7.0 SSP5-8.5 1000 2000 3000 4000 4500 –0.5 0 0.5 1 1.5 2 2.5 3 historical since 2020 Cumulative CO2 emissions (GtCO2) this line indicates maximum emissions to stay within 2°C of warming (with 83% chance) Every ton of CO2 adds to global warming b) Cumulative CO2 emissions and warming until 2050 Figure 3.5: Cumulative past, projected, and committed emissions, and associated global temperature changes.
Panel (a) Assessed remaining carbon budgets to limit warming more likely than not to 1.5°C, to 2°C with a 83% and 67% likelihood, compared to cumulative emissions corresponding to constant 2019 emissions until 2030, existing and planned fossil fuel infrastructures (in GtCO2). For remaining carbon budgets, thin lines indicate the uncertainty due to the contribution of non-CO2 warming. For lifetime emissions from fossil fuel infrastructure, thin lines indicate the assessed sensitivity range. Panel (b) Relationship between cumulative CO2 emissions and the increase in global surface temperature. Historical data (thin black line) shows historical CO2 emissions versus observed global surface temperature increase relative to the period 1850-1900. The grey range with its central line shows a corresponding estimate of the human-caused share of historical warming. Coloured areas show the assessed very likely range of global surface temperature projections, and thick coloured central lines show the median estimate as a function of cumulative CO2 emissions for the selected scenarios SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. Projections until 2050 use the cumulative CO2 emissions of each respective scenario, and the projected global warming includes the contribution from all anthropogenic forcers. {WGI SPM D.1, WGI Figure SPM.10, WGI Table SPM.2; WGIII SPM B.1, WGIII SPM B.7, WGIII 2.7; SR1.5 SPM C.1.3}
84 Section 3 Section 1 Section 3 2030 43 [34-60] 41 [31-59] 48 [35-61] 23 [0-44] 21 [1-42] 27 [13-45] 5 [0-14] 10 [0-27] 2040 2050 84 [73-98] 85 [72-100] 84 [76-93] 75 [62-91] 64 [53-77] 63 [52-76] 68 [56-83] 49 [35-65] 29 [11-48] 5 [-2 to 18] Net zero CO2 (% net zero pathways) 2050-2055 (100%) [2035-2070] 2055-2060 (100%) [2045-2070] 2070-2075 (93%) [2055-...] 2070-2075 (91%) [2055-...] 2065-2070 (97%) [2055-2090] 2080-2085 (86%) [2065-...] Net zero GHGs (5) (% net zero pathways) 2095-2100 (52%) [2050-...] 2070-2075 (100%) [2050-2090] ...-... (0%) [...-...] 2070-2075 (87%) [2055-...] ...-... (30%) [2075-...] ...-... (24%) [2080-...] ...-... (41%) [2075-...] ...-... (31%) [2075-...
..] 2065-2070 (97%) [2055-2090] 2080-2085 (86%) [2065-...] Net zero GHGs (5) (% net zero pathways) 2095-2100 (52%) [2050-...] 2070-2075 (100%) [2050-2090] ...-... (0%) [...-...] 2070-2075 (87%) [2055-...] ...-... (30%) [2075-...] ...-... (24%) [2080-...] ...-... (41%) [2075-...] ...-... (31%) [2075-...] 2020 to net zero CO2 510 [330-710] 550 [340-760] 460 [320-590] 720 [530-930] 890 [640-1160] 860 [640-1180] 910 [720-1150] 1210 [970-1490] 1780 [1400-2360] 2020– 2100 320 [-210-570] 160 [-220-620] 360 [10-540] 400 [-90-620] 800 [510-1140] 790 [480-1150] 800 [560-1050] 1160 [700-1490] at peak warming 1.6 1.6 1.6 1.7 1.7 1.7 1.8 1.9 2100 1.3 1.2 1.4 1.4 1.6 1.6 1.6 1.8 <1.5°C 38 [33-58] 38 [34-60] 37 [33-56] 24 [15-42] 20 [13-41] 21 [14-42] 17 [12-35] 11 [7-22] <2.
6 1.6 1.6 1.7 1.7 1.7 1.8 1.9 2100 1.3 1.2 1.4 1.4 1.6 1.6 1.6 1.8 <1.5°C 38 [33-58] 38 [34-60] 37 [33-56] 24 [15-42] 20 [13-41] 21 [14-42] 17 [12-35] 11 [7-22] <2.0°C 90 [86-97] 90 [85-97] 89 [87-96] 82 [71-93] 76 [68-91] 78 [69-91] 73 [67-87] 59 [50-77] <3.0°C 100 [99-100] 100 [99-100] 100 [99-100] 100 [99-100] 99 [98-100] 100 [98-100] 99 [98-99] 98 91 [95-99] p50 [p5-p95] (1) GHG emissions reductions from 2019 (%) (3) Emissions milestones (4) Cumulative CO2 emissions [Gt CO2](6) Likelihood of peak global warming staying below (%) Global mean temperature changes 50% probability (°C) 69 [58-90] 66 [58-89] 70 [62-87] 55 [40-71] 46 [34-63] 47 [35-63] 46 [34-63] 31 [20-5] 18 [4-33] 3 [-14 to 14] 6 [-1 to 18] 2 [-10 to 11] Median 5-year intervals at which projected CO2 & GHG emissions of pathways in this category reach net-zero, with the 5th-95th percentile interval in square brackets. Percentage of net zero pathways is denoted in round brackets.
with the 5th-95th percentile interval in square brackets. Percentage of net zero pathways is denoted in round brackets. Three dots (…) denotes net zero not reached for that percentile. Median cumulative net CO2 emissions across the projected scenarios in this category until reaching net-zero or until 2100, with the 5th-95th percentile interval in square brackets. Projected temperature change of pathways in this category (50% probability across the range of climate uncertainties), relative to 1850-1900, at peak warming and in 2100, for the median value across the scenarios and the 5th-95th percentile interval in square brackets. Median likelihood that the projected pathways in this category stay below a given global warming level, with the 5th-95th percentile interval in square brackets. Projected median GHG emissions reductions of pathways in the year across the scenarios compared to modelled 2019, with the 5th-95th percentile in brackets. Negative numbers indicate increase in emissions compared to 2019 Modelled global emissions pathways categorised by projected global warming levels (GWL). Detailed likelihood definitions are provided in SPM Box1. The five illustrative scenarios (SSPx-yy) considered by AR6 WGI and the Illustrative (Mitigation) Pathways assessed in WGIII are aligned with the tempera- ture categories and are indicated in a separate column. Global emission pathways contain regionally differentiated information. This assessment focuses on their global characteristics. ...-... (41%) [2080-...] ...-... (12%) [2090-...] no net-zero no peaking by 2100 no net-zero no net-zero 1780 [1260-2360] 2790 [2440-3520] [1.4-1.6] [1.4-1.6] [1.5-1.
Detailed likelihood definitions are provided in SPM Box1. The five illustrative scenarios (SSPx-yy) considered by AR6 WGI and the Illustrative (Mitigation) Pathways assessed in WGIII are aligned with the tempera- ture categories and are indicated in a separate column. Global emission pathways contain regionally differentiated information. This assessment focuses on their global characteristics. ...-... (41%) [2080-...] ...-... (12%) [2090-...] no net-zero no peaking by 2100 no net-zero no net-zero 1780 [1260-2360] 2790 [2440-3520] [1.4-1.6] [1.4-1.6] [1.5-1.6] [1.5-1.8] [1.6-1.8] [1.6-1.8] [1.6-1.8] [1.7-2.0] [1.9-2.5] [1.1-1.5] [1.1-1.4] [1.3-1.5] [1.2-1.5] [1.5-1.8] [1.5-1.8] [1.5-1.7] [1.5-2.0] [1.9-2.5] [2.4-2.9] 2.2 2.1 2.7 4 [0-10] 37 [18-59] [83-98] 71 0 [0-0] 8 [2-18] [53-88] Category/ subset label limit warming to 1.5°C (>50%) with no or limited overshoot … with net zero GHGs … without net zero GHGs return warming to 1.
1-1.5] [1.1-1.4] [1.3-1.5] [1.2-1.5] [1.5-1.8] [1.5-1.8] [1.5-1.7] [1.5-2.0] [1.9-2.5] [2.4-2.9] 2.2 2.1 2.7 4 [0-10] 37 [18-59] [83-98] 71 0 [0-0] 8 [2-18] [53-88] Category/ subset label limit warming to 1.5°C (>50%) with no or limited overshoot … with net zero GHGs … without net zero GHGs return warming to 1.5°C (>50%) after a high overshoot limit warming to 2°C (>67%) … with action starting in 2020 … NDCs until 2030 limit warming to 2°C (>50%) limit warming to 2.5°C (>50%) limit warming to 3°C (>50%) [212] Category (2) [# pathways] C1 [97] C1a [50] C1b [47] C2 [133] C3 [311] C3a [204] C3b [97] C4 [159] C5 C6 [97] Table 3.1: Key characteristics of the modelled global emissions pathways. Summary of projected CO2 and GHG emissions, projected net zero timings and the resulting global warming outcomes. Pathways are categorised (columns), according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) and 2100 warming levels.
5°C (>50%) limit warming to 3°C (>50%) [212] Category (2) [# pathways] C1 [97] C1a [50] C1b [47] C2 [133] C3 [311] C3a [204] C3b [97] C4 [159] C5 C6 [97] Table 3.1: Key characteristics of the modelled global emissions pathways. Summary of projected CO2 and GHG emissions, projected net zero timings and the resulting global warming outcomes. Pathways are categorised (columns), according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) and 2100 warming levels. Values shown are for the median [p50] and 5–95th percentiles [p5–p95], noting that not all pathways achieve net zero CO2 or GHGs. {WGIII Table SPM.2} 1 Detailed explanations on the Table are provided in WGIII Box SPM.1 and WGIII Table SPM.2. The relationship between the temperature categories and SSP/RCPs is discussed in Cross-Section Box.2. Values in the table refer to the 50th and [5–95th] percentile values across the pathways falling within a given category as deﬁned in WGIII Box SPM.1. The three dots (…) sign denotes that the value cannot be given (as the value is after 2100 or, for net zero, net zero is not reached). Based on the assessment of climate emulators in AR6 WG I (Chapter 7, Box 7.1), two climate emulators were used for the probabilistic assessment of the resulting warming of the pathways. For the ‘Temperature Change’ and ‘Likelihood’ columns, the non-bracketed values represent the 50th percentile across the pathways in that category and the median [50th percentile] across the warming estimates of the probabilistic MAGICC climate model emulator.
Values in the table refer to the 50th and [5–95th] percentile values across the pathways falling within a given category as deﬁned in WGIII Box SPM.1. The three dots (…) sign denotes that the value cannot be given (as the value is after 2100 or, for net zero, net zero is not reached). Based on the assessment of climate emulators in AR6 WG I (Chapter 7, Box 7.1), two climate emulators were used for the probabilistic assessment of the resulting warming of the pathways. For the ‘Temperature Change’ and ‘Likelihood’ columns, the non-bracketed values represent the 50th percentile across the pathways in that category and the median [50th percentile] across the warming estimates of the probabilistic MAGICC climate model emulator. For the bracketed ranges in the “likelihood” column, the median warming for every pathway in that category is calculated for each of the two climate model emulators (MAGICC and FaIR). These ranges cover both the uncertainty of the emissions pathways as well as the climate emulators’ uncertainty. All global warming levels are relative to 1850-1900. 2 C3 pathways are sub-categorised according to the timing of policy action to match the emissions pathways in WGIII Figure SPM.4. 3 Global emission reductions in mitigation pathways are reported on a pathway-by-pathway basis relative to harmonised modelled global emissions in 2019 rather than
85 Long-Term Climate and Development Futures Section 3 3.3.2 Net Zero Emissions: Timing and Implications From a physical science perspective, limiting human-caused global warming to a speciﬁc level requires limiting cumulative CO2 emissions, reaching net zero or net negative CO2 emissions, along with strong reductions of other GHG emissions (see Cross-Section Box.1). Global modelled pathways that reach and sustain net zero GHG emissions are projected to result in a gradual decline in surface temperature (high conﬁdence). Reaching net zero GHG emissions primarily requires deep reductions in CO2, methane, and other GHG emissions, and implies net negative CO2 emissions.134 Carbon dioxide removal (CDR) will be necessary to achieve net negative CO2 emissions135. Achieving global net zero CO2 emissions, with remaining anthropogenic CO2 emissions balanced by durably stored CO2 from anthropogenic removal, is a requirement to stabilise CO2-induced global surface temperature increase (see 3.3.3) (high conﬁdence). This is different from achieving net zero GHG emissions, where metric-weighted anthropogenic GHG emissions (see Cross-Section Box.1) equal CO2 removal (high conﬁdence). Emissions pathways that reach and sustain net zero GHG emissions deﬁned by the 100-year global warming potential imply net negative CO2 emissions and are projected to result in a gradual decline in surface temperature after an earlier peak (high conﬁdence). While reaching net zero CO2 or net zero GHG emissions requires deep and rapid reductions in gross emissions, the deployment of CDR to counterbalance hard- to-abate residual emissions (e.g., some emissions from agriculture, aviation, shipping, and industrial processes) is unavoidable (high conﬁdence).
This is different from achieving net zero GHG emissions, where metric-weighted anthropogenic GHG emissions (see Cross-Section Box.1) equal CO2 removal (high conﬁdence). Emissions pathways that reach and sustain net zero GHG emissions deﬁned by the 100-year global warming potential imply net negative CO2 emissions and are projected to result in a gradual decline in surface temperature after an earlier peak (high conﬁdence). While reaching net zero CO2 or net zero GHG emissions requires deep and rapid reductions in gross emissions, the deployment of CDR to counterbalance hard- to-abate residual emissions (e.g., some emissions from agriculture, aviation, shipping, and industrial processes) is unavoidable (high conﬁdence). {WGI SPM D.1, WGI SPM D.1.1, WGI SPM D.1.8; WGIII SPM C.2, WGIII SPM C.3, WGIII SPM C.11, WGIII Box TS.6; SR1.5 SPM A.2.2} In modelled pathways, the timing of net zero CO2 emissions, followed by net zero GHG emissions, depends on several variables, including the desired climate outcome, the mitigation strategy and the gases covered (high conﬁdence). Global net zero CO2 emissions are reached in the early 2050s in pathways that limit warming to 1.5°C (>50%) with no or limited overshoot, and around the early 2070s in pathways that limit warming to 2°C (>67%). While non-CO2 GHG emissions are strongly reduced in all pathways that limit warming to 2°C (>67%) or lower, residual emissions of CH4 and N2O and F-gases of about 8 [5–11] GtCO2-eq yr-1 remain at the time of 134 Net zero GHG emissions deﬁned by the 100-year global warming potential. See footnote 70. 135 See Section 3.3.3 and 3.4.1. net zero GHG, counterbalanced by net negative CO2 emissions.
Global net zero CO2 emissions are reached in the early 2050s in pathways that limit warming to 1.5°C (>50%) with no or limited overshoot, and around the early 2070s in pathways that limit warming to 2°C (>67%). While non-CO2 GHG emissions are strongly reduced in all pathways that limit warming to 2°C (>67%) or lower, residual emissions of CH4 and N2O and F-gases of about 8 [5–11] GtCO2-eq yr-1 remain at the time of 134 Net zero GHG emissions deﬁned by the 100-year global warming potential. See footnote 70. 135 See Section 3.3.3 and 3.4.1. net zero GHG, counterbalanced by net negative CO2 emissions. As a result, net zero CO2 would be reached before net zero GHGs (high conﬁdence). {WGIII SPM C.2, WGIII SPM C.2.3, WGIII SPM C.2.4, WGIII Table SPM.2, WGIII 3.3} (Figure 3.6) the global emissions reported in WGIII SPM Section B and WGIII Chapter 2; this ensures internal consistency in assumptions about emission sources and activities, as well as consistency with temperature projections based on the physical climate science assessment by WGI (see WGIII SPM Footnote 49). Negative values (e.g., in C5, C6) represent an increase in emissions. The modelled GHG emissions in 2019 are 55 [53–58] GtCO2-eq, thus within the uncertainty ranges of estimates for 2019 emissions [53-66] GtCO2-eq (see 2.1.1). 4 Emissions milestones are provided for 5-year intervals in order to be consistent with the underlying 5-year time-step data of the modelled pathways. Ranges in square brackets underneath refer to the range across the pathways, comprising the lower bound of the 5th percentile 5-year interval and the upper bound of the 95th percentile 5-year interval.
Negative values (e.g., in C5, C6) represent an increase in emissions. The modelled GHG emissions in 2019 are 55 [53–58] GtCO2-eq, thus within the uncertainty ranges of estimates for 2019 emissions [53-66] GtCO2-eq (see 2.1.1). 4 Emissions milestones are provided for 5-year intervals in order to be consistent with the underlying 5-year time-step data of the modelled pathways. Ranges in square brackets underneath refer to the range across the pathways, comprising the lower bound of the 5th percentile 5-year interval and the upper bound of the 95th percentile 5-year interval. Numbers in round brackets signify the fraction of pathways that reach speciﬁc milestones over the 21st century. Percentiles reported across all pathways in that category include those that do not reach net zero before 2100. 5 For cases where models do not report all GHGs, missing GHG species are inﬁlled and aggregated into a Kyoto basket of GHG emissions in CO2-eq deﬁned by the 100-year global warming potential. For each pathway, reporting of CO2, CH4, and N2O emissions was the minimum required for the assessment of the climate response and the assignment to a climate category. Emissions pathways without climate assessment are not included in the ranges presented here. See WGIII Annex III.II.5. 6 Cumulative emissions are calculated from the start of 2020 to the time of net zero and 2100, respectively. They are based on harmonised net CO2 emissions, ensuring consistency with the WG I assessment of the remaining carbon budget. {WGIII Box 3.4, WGIII SPM Footnote 50}
86 Section 3 Section 1 Section 3 2000 2020 2040 2060 2080 2100 0 20 40 60 2000 2020 2040 2060 2080 2100 0 20 40 60 2000 2020 2040 2060 2080 2100 2000 2020 2040 2060 2080 2100 Gigatons of CO2 equivalent per year (GtCO2-eq/yr) CO2 GHG CO2 GHG CH4 CO2 GHG CH4 a) While keeping warming to 1.5°C (>50%) with no or limited overshoot b) While keeping warming to 2°C (>67%) c) Timing for net zero net zero net zero Historical Historical Policies in place in 2020 Policies in place in 2020 GHGs reach net zero later than CO2 not all scenarios reach net zero GHG by 2100 Global modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot reach net zero CO2 emissions around 2050 Total greenhouse gases (GHG) reach net zero later Figure 3.6: Total GHG, CO2 and CH4 emissions and timing of reaching net zero in different mitigation pathways. Top row: GHG, CO2 and CH4 emissions over time (in GtCO2eq) with historical emissions, projected emissions in line with policies implemented until the end of 2020 (grey), and pathways consistent with temperature goals in colour (blue, purple, and brown, respectively). Panel (a) (left) shows pathways that limit warming to 1.5°C (>50%) with no or limited overshoot (C1) and Panel (b) (right) shows pathways that limit warming to 2°C (>67%) (C3).
Top row: GHG, CO2 and CH4 emissions over time (in GtCO2eq) with historical emissions, projected emissions in line with policies implemented until the end of 2020 (grey), and pathways consistent with temperature goals in colour (blue, purple, and brown, respectively). Panel (a) (left) shows pathways that limit warming to 1.5°C (>50%) with no or limited overshoot (C1) and Panel (b) (right) shows pathways that limit warming to 2°C (>67%) (C3). Bottom row: Panel (c) shows median (vertical line), likely (bar) and very likely (thin lines) timing of reaching net zero GHG and CO2 emissions for global modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot (C1) (left) or 2°C (>67%) (C3) (right). {WGIII Figure SPM.5} 3.3.3 Sectoral Contributions to Mitigation All global modelled pathways that limit warming to 2°C (>67%) or lower by 2100 involve rapid and deep and in most cases immediate GHG emissions reductions in all sectors (see also 4.1, 4.5). Reductions in GHG emissions in industry, transport, buildings, and urban areas can be achieved through a combination of energy efﬁciency and conservation and a transition to low-GHG technologies and energy carriers (see also 4.5, Figure 4.4). Socio-cultural options and behavioural change can reduce global GHG emissions of end-use sectors, with most of the potential in developed countries, if combined with improved 136 CCS is an option to reduce emissions from large-scale fossil-based energy and industry sources provided geological storage is available. When CO2 is captured directly from the atmosphere (DACCS), or from biomass (BECCS), CCS provides the storage component of these CDR methods. CO2 capture and subsurface injection is a mature technology for gas processing and enhanced oil recovery.
Reductions in GHG emissions in industry, transport, buildings, and urban areas can be achieved through a combination of energy efﬁciency and conservation and a transition to low-GHG technologies and energy carriers (see also 4.5, Figure 4.4). Socio-cultural options and behavioural change can reduce global GHG emissions of end-use sectors, with most of the potential in developed countries, if combined with improved 136 CCS is an option to reduce emissions from large-scale fossil-based energy and industry sources provided geological storage is available. When CO2 is captured directly from the atmosphere (DACCS), or from biomass (BECCS), CCS provides the storage component of these CDR methods. CO2 capture and subsurface injection is a mature technology for gas processing and enhanced oil recovery. In contrast to the oil and gas sector, CCS is less mature in the power sector, as well as in cement and chemicals production, where it is a critical mitigation option. The technical geological storage capacity is estimated to be on the order of 1000 GtCO2, which is more than the CO2 storage requirements through 2100 to limit global warming to 1.5°C, although the regional availability of geological storage could be a limiting factor. If the geological storage site is appropriately selected and managed, it is estimated that the CO2 can be permanently isolated from the atmosphere. Implementation of CCS currently faces technological, economic, institutional, ecological environmental and socio-cultural barriers. Currently, global rates of CCS deployment are far below those in modelled pathways limiting global warming to 1.5°C to 2°C. Enabling conditions such as policy instruments, greater public support and technological innovation could reduce these barriers. (high conﬁdence) {WGIII SPM C.4.6} infrastructure design and access.
The technical geological storage capacity is estimated to be on the order of 1000 GtCO2, which is more than the CO2 storage requirements through 2100 to limit global warming to 1.5°C, although the regional availability of geological storage could be a limiting factor. If the geological storage site is appropriately selected and managed, it is estimated that the CO2 can be permanently isolated from the atmosphere. Implementation of CCS currently faces technological, economic, institutional, ecological environmental and socio-cultural barriers. Currently, global rates of CCS deployment are far below those in modelled pathways limiting global warming to 1.5°C to 2°C. Enabling conditions such as policy instruments, greater public support and technological innovation could reduce these barriers. (high conﬁdence) {WGIII SPM C.4.6} infrastructure design and access. (high conﬁdence) {WGIII SPM C.3, WGIII SPM C.5, WGIII SPM C.6, WGIII SPM C.7.3, WGIII SPM C.8, WGIII SPM C.10.2} Global modelled mitigation pathways reaching net zero CO2 and GHG emissions include transitioning from fossil fuels without carbon capture and storage (CCS) to very low- or zero-carbon energy sources, such as renewables or fossil fuels with CCS, demand-side measures and improving efﬁciency, reducing non-CO2 GHG emissions, and CDR136. In global modelled pathways that limit warming to 2°C or below, almost all electricity is supplied
87 Long-Term Climate and Development Futures Section 3 from zero or low-carbon sources in 2050, such as renewables or fossil fuels with CO2 capture and storage, combined with increased electriﬁcation of energy demand. Such pathways meet energy service demand with relatively low energy use, through e.g., enhanced energy efﬁciency and behavioural changes and increased electriﬁcation of energy end use. Modelled global pathways limiting global warming to 1.5°C (>50%) with no or limited overshoot generally implement such changes faster than pathways limiting global warming to 2°C (>67%). (high conﬁdence) {WGIII SPM C.3, WGIII SPM C.3.2, WGIII SPM C.4, WGIII TS.4.2; SR1.5 SPM C.2.2} AFOLU mitigation options, when sustainably implemented, can deliver large-scale GHG emission reductions and enhanced CO2 removal; however, barriers to implementation and trade-offs may result from the impacts of climate change, competing demands on land, conﬂicts with food security and livelihoods, the complexity of land ownership and management systems, and cultural aspects (see 3.4.1). All assessed modelled pathways that limit warming to 2°C (>67%) or lower by 2100 include land-based mitigation and land-use change, with most including different combinations of reforestation, afforestation, reduced deforestation, and bioenergy. However, accumulated carbon in vegetation and soils is at risk from future loss (or sink reversal) triggered by climate change and disturbances such as ﬂood, drought, ﬁre, or pest outbreaks, or future poor management.
All assessed modelled pathways that limit warming to 2°C (>67%) or lower by 2100 include land-based mitigation and land-use change, with most including different combinations of reforestation, afforestation, reduced deforestation, and bioenergy. However, accumulated carbon in vegetation and soils is at risk from future loss (or sink reversal) triggered by climate change and disturbances such as ﬂood, drought, ﬁre, or pest outbreaks, or future poor management. (high conﬁdence) {WGI SPM B.4.3; WGII SPM B.2.3, WGII SPM B.5.4; WGIII SPM C.9, WGIII SPM C.11.3, WGIII SPM D.2.3, WGIII TS.4.2, 3.4; SR1.5 SPM C.2.5; SRCCL SPM B.1.4, SRCCL SPM B.3, SRCCL SPM B.7} In addition to deep, rapid, and sustained emission reductions, CDR can fulﬁl three complementary roles: lowering net CO2 or net GHG emissions in the near term; counterbalancing ‘hard-to-abate’ residual emissions (e.g., some emissions from agriculture, aviation, shipping, industrial processes) to help reach net zero CO2 or GHG emissions, and achieving net negative CO2 or GHG emissions if deployed at levels exceeding annual residual emissions (high conﬁdence). CDR methods vary in terms of their maturity, removal process, time scale of carbon storage, storage medium, mitigation potential, cost, co-beneﬁts, impacts and risks, and governance requirements (high conﬁdence).
CDR methods vary in terms of their maturity, removal process, time scale of carbon storage, storage medium, mitigation potential, cost, co-beneﬁts, impacts and risks, and governance requirements (high conﬁdence). Speciﬁcally, maturity ranges from lower maturity (e.g., ocean alkalinisation) to higher maturity (e.g., reforestation); removal and storage potential ranges from lower potential (<1 Gt CO2 yr-1, e.g., blue carbon management) to higher potential (>3 Gt CO2 yr-1, e.g., agroforestry); costs range from lower cost (e.g., –45 to 100 USD tCO2-1 for soil carbon sequestration) to higher cost (e.g., 100 to 300 USD tCO2-1 for direct air carbon dioxide capture and storage) (medium conﬁdence). Estimated storage timescales vary from decades to centuries for methods that store carbon in vegetation and through soil carbon management, to ten thousand years or more for methods that store carbon in geological formations (high conﬁdence). Afforestation, reforestation, improved forest management, agroforestry and soil carbon sequestration are currently the only widely practiced CDR methods (high conﬁdence). Methods and levels of CDR deployment in global modelled mitigation pathways vary depending on assumptions about costs, availability and constraints (high conﬁdence). {WGIII SPM C.3.5, WGIII SPM C.11.1, WGIII SPM C.11.4} 137 Limited overshoot refers to exceeding 1.5°C global warming by up to about 0.1°C, high overshoot by 0.1°C to 0.3°C, in both cases for up to several decades. {WGIII Box SPM.1} 3.3.4 Overshoot Pathways: Increased Risks and Other Implications Exceeding a speciﬁc remaining carbon budget results in higher global warming.
Methods and levels of CDR deployment in global modelled mitigation pathways vary depending on assumptions about costs, availability and constraints (high conﬁdence). {WGIII SPM C.3.5, WGIII SPM C.11.1, WGIII SPM C.11.4} 137 Limited overshoot refers to exceeding 1.5°C global warming by up to about 0.1°C, high overshoot by 0.1°C to 0.3°C, in both cases for up to several decades. {WGIII Box SPM.1} 3.3.4 Overshoot Pathways: Increased Risks and Other Implications Exceeding a speciﬁc remaining carbon budget results in higher global warming. Achieving and sustaining net negative global CO2 emissions could reverse the resulting temperature exceedance (high conﬁdence). Continued reductions in emissions of short-lived climate forcers, particularly methane, after peak temperature has been reached, would also further reduce warming (high conﬁdence). Only a small number of the most ambitious global modelled pathways limit global warming to 1.5°C (>50%) without overshoot. {WGI SPM D.1.1, WGI SPM D.1.6, WGI SPM D.1.7; WGIII TS.4.2} Overshoot of a warming level results in more adverse impacts, some irreversible, and additional risks for human and natural systems compared to staying below that warming level, with risks growing with the magnitude and duration of overshoot (high conﬁdence). Compared to pathways without overshoot, societies and ecosystems would be exposed to greater and more widespread changes in climatic impact-drivers, such as extreme heat and extreme precipitation, with increasing risks to infrastructure, low-lying coastal settlements, and associated livelihoods (high conﬁdence). Overshooting 1.5°C will result in irreversible adverse impacts on certain ecosystems with low resilience, such as polar, mountain, and coastal ecosystems, impacted by ice-sheet melt, glacier melt, or by accelerating and higher committed sea level rise (high conﬁdence).
Compared to pathways without overshoot, societies and ecosystems would be exposed to greater and more widespread changes in climatic impact-drivers, such as extreme heat and extreme precipitation, with increasing risks to infrastructure, low-lying coastal settlements, and associated livelihoods (high conﬁdence). Overshooting 1.5°C will result in irreversible adverse impacts on certain ecosystems with low resilience, such as polar, mountain, and coastal ecosystems, impacted by ice-sheet melt, glacier melt, or by accelerating and higher committed sea level rise (high conﬁdence). Overshoot increases the risks of severe impacts, such as increased wildﬁres, mass mortality of trees, drying of peatlands, thawing of permafrost and weakening natural land carbon sinks; such impacts could increase releases of GHGs making temperature reversal more challenging (medium conﬁdence). {WGI SPM C.2, WGI SPM C.2.1, WGI SPM C.2.3; WGII SPM B.6, WGII SPM B.6.1, WGII SPM B.6.2; SR1.5 3.6} The larger the overshoot, the more net negative CO2 emissions needed to return to a given warming level (high conﬁdence). Reducing global temperature by removing CO2 would require net negative emissions of 220 GtCO2 (best estimate, with a likely range of 160 to 370 GtCO2) for every tenth of a degree (medium conﬁdence).
{WGI SPM C.2, WGI SPM C.2.1, WGI SPM C.2.3; WGII SPM B.6, WGII SPM B.6.1, WGII SPM B.6.2; SR1.5 3.6} The larger the overshoot, the more net negative CO2 emissions needed to return to a given warming level (high conﬁdence). Reducing global temperature by removing CO2 would require net negative emissions of 220 GtCO2 (best estimate, with a likely range of 160 to 370 GtCO2) for every tenth of a degree (medium conﬁdence). Modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot reach median values of cumulative net negative emissions of 220 GtCO2 by 2100, pathways that return warming to 1.5°C (>50%) after high overshoot reach median values of 360 GtCO2 (high conﬁdence).137 More rapid reduction in CO2 and non-CO2 emissions, particularly methane, limits peak warming levels and reduces the requirement for net negative CO2 emissions and CDR, thereby reducing feasibility and sustainability concerns, and social and environmental risks (high confidence). {WGI SPM D.1.1; WGIII SPM B.6.4, WGIII SPM C.2, WGIII SPM C.2.2, WGIII Table SPM.2}
88 Section 3 Section 1 Section 3 3.4.1 Synergies and trade-offs, costs and beneﬁts Mitigation and adaptation options can lead to synergies and trade-offs with other aspects of sustainable development (see also Section 4.6, Figure 4.4). Synergies and trade-offs depend on the pace and magnitude of changes and the development context including inequalities, with consideration of climate justice. The potential or effectiveness of some adaptation and mitigation options decreases as climate change intensiﬁes (see also Sections 3.2, 3.3.3, 4.5). (high conﬁdence) {WGII SPM C.2, WGII Figure SPM.4b; WGIII SPM D.1, WGIII SPM D.1.2, WGIII TS.5.1, WGIII Figure SPM.8; SR1.5 SPM D.3, SR1.5 SPM D.4; SRCCL SPM B.2, SRCCL SPM B.3, SRCCL SPM D.3.2, SRCCL Figure SPM.3} In the energy sector, transitions to low-emission systems will have multiple co-beneﬁts, including improvements in air quality and health. There are potential synergies between sustainable development and, for instance, energy efﬁciency and renewable energy. (high conﬁdence) {WGIII SPM C.4.2, WGIII SPM D.1.3} For agriculture, land, and food systems, many land management options and demand-side response options (e.g., dietary choices, reduced post-harvest losses, reduced food waste) can contribute to eradicating poverty and eliminating hunger while promoting good health and well-being, clean water and sanitation, and life on land (medium confidence). In contrast, certain adaptation options that promote intensification of production, such as irrigation, may have negative effects on sustainability (e.g., for biodiversity, ecosystem services, groundwater depletion, and water quality) (high confidence).
There are potential synergies between sustainable development and, for instance, energy efﬁciency and renewable energy. (high conﬁdence) {WGIII SPM C.4.2, WGIII SPM D.1.3} For agriculture, land, and food systems, many land management options and demand-side response options (e.g., dietary choices, reduced post-harvest losses, reduced food waste) can contribute to eradicating poverty and eliminating hunger while promoting good health and well-being, clean water and sanitation, and life on land (medium confidence). In contrast, certain adaptation options that promote intensification of production, such as irrigation, may have negative effects on sustainability (e.g., for biodiversity, ecosystem services, groundwater depletion, and water quality) (high confidence). {WGII TS.D.5.5; WGIII SPM D.10; SRCCL SPM B.2.3} Reforestation, improved forest management, soil carbon sequestration, peatland restoration and coastal blue carbon management are examples of CDR methods that can enhance biodiversity and ecosystem functions, employment and local livelihoods, depending on context139. However, afforestation or production of biomass crops for bioenergy with carbon dioxide capture and storage or biochar can have adverse socio-economic and environmental impacts, including on biodiversity, food and water security, local livelihoods and the rights of Indigenous Peoples, especially if implemented at large scales and where land tenure is insecure. (high conﬁdence) {WGII SPM B.5.4, WGII SPM C.2.4; WGIII SPM C.11.2; SR1.5 SPM C.3.4, SR1.5 SPM C.3.5; SRCCL SPM B.3, SRCCL SPM B.7.3, SRCCL Figure SPM.3} 139 The impacts, risks, and co-beneﬁts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speciﬁc context, implementation and scale (high conﬁdence).
(high conﬁdence) {WGII SPM B.5.4, WGII SPM C.2.4; WGIII SPM C.11.2; SR1.5 SPM C.3.4, SR1.5 SPM C.3.5; SRCCL SPM B.3, SRCCL SPM B.7.3, SRCCL Figure SPM.3} 139 The impacts, risks, and co-beneﬁts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speciﬁc context, implementation and scale (high conﬁdence). {WGIII SPM C.11.2} 140 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5°C. {WGIII SPM footnote 68} Modelled pathways that assume using resources more efﬁciently or shift global development towards sustainability include fewer challenges, such as dependence on CDR and pressure on land and biodiversity, and have the most pronounced synergies with respect to sustainable development (high conﬁdence). {WGIII SPM C.3.6; SR1.5 SPM D.4.2} Strengthening climate change mitigation action entails more rapid transitions and higher up-front investments, but brings beneﬁts from avoiding damages from climate change and reduced adaptation costs. The aggregate effects of climate change mitigation on global GDP (excluding damages from climate change and adaptation costs) are small compared to global projected GDP growth. Projected estimates of global aggregate net economic damages and the costs of adaptation generally increase with global warming level. (high conﬁdence) {WGII SPM B.4.6, WGII TS.C.10; WGIII SPM C.12.2, WGIII SPM C.12.3} Cost-beneﬁt analysis remains limited in its ability to represent all damages from climate change, including non-monetary damages, or to capture the heterogeneous nature of damages and the risk of catastrophic damages (high conﬁdence).
The aggregate effects of climate change mitigation on global GDP (excluding damages from climate change and adaptation costs) are small compared to global projected GDP growth. Projected estimates of global aggregate net economic damages and the costs of adaptation generally increase with global warming level. (high conﬁdence) {WGII SPM B.4.6, WGII TS.C.10; WGIII SPM C.12.2, WGIII SPM C.12.3} Cost-beneﬁt analysis remains limited in its ability to represent all damages from climate change, including non-monetary damages, or to capture the heterogeneous nature of damages and the risk of catastrophic damages (high conﬁdence). Even without accounting for these factors or for the co-beneﬁts of mitigation, the global beneﬁts of limiting warming to 2°C exceed the cost of mitigation (medium conﬁdence). This ﬁnding is robust against a wide range of assumptions about social preferences on inequalities and discounting over time (medium conﬁdence). Limiting global warming to 1.5°C instead of 2°C would increase the costs of mitigation, but also increase the beneﬁts in terms of reduced impacts and related risks (see 3.1.1, 3.1.2) and reduced adaptation needs (high confidence)140. {WGII SPM B.4, WGII SPM B.6; WGIII SPM C.12, WGIII SPM C.12.2, WGIII SPM C.12.3 WGIII Box TS.7; SR1.5 SPM B.3, SR1.5 SPM B.5, SR1.5 SPM B.6} Considering other sustainable development dimensions, such as the potentially strong economic beneﬁts on human health from air quality improvement, may enhance the estimated beneﬁts of mitigation (medium conﬁdence). The economic effects of strengthened mitigation action vary across regions and countries, depending notably on economic structure, regional emissions reductions, policy design and level of international cooperation (high conﬁdence).
{WGII SPM B.4, WGII SPM B.6; WGIII SPM C.12, WGIII SPM C.12.2, WGIII SPM C.12.3 WGIII Box TS.7; SR1.5 SPM B.3, SR1.5 SPM B.5, SR1.5 SPM B.6} Considering other sustainable development dimensions, such as the potentially strong economic beneﬁts on human health from air quality improvement, may enhance the estimated beneﬁts of mitigation (medium conﬁdence). The economic effects of strengthened mitigation action vary across regions and countries, depending notably on economic structure, regional emissions reductions, policy design and level of international cooperation (high conﬁdence). Ambitious mitigation pathways imply large and sometimes disruptive changes in economic structure, with implications for near-term actions (Section 4.2), equity (Section 4.4), sustainability (Section 4.6), and ﬁnance (Section 4.8) (high conﬁdence). {WGIII SPM C.12.2, WGIII SPM D.3.2, WGIII TS.4.2} 3.4 Long-Term Interactions Between Adaptation, Mitigation and Sustainable Development Mitigation and adaptation can lead to synergies and trade-offs with sustainable development (high conﬁdence). Accelerated and equitable mitigation and adaptation bring beneﬁts from avoiding damages from climate change and are critical to achieving sustainable development (high conﬁdence). Climate resilient development138 pathways are progressively constrained by every increment of further warming (very high conﬁdence). There is a rapidly closing window of opportunity to secure a liveable and sustainable future for all (very high conﬁdence). 138 See Annex I: Glossary. 139 The impacts, risks, and co-beneﬁts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speciﬁc context, implementation and scale (high conﬁdence).
Accelerated and equitable mitigation and adaptation bring beneﬁts from avoiding damages from climate change and are critical to achieving sustainable development (high conﬁdence). Climate resilient development138 pathways are progressively constrained by every increment of further warming (very high conﬁdence). There is a rapidly closing window of opportunity to secure a liveable and sustainable future for all (very high conﬁdence). 138 See Annex I: Glossary. 139 The impacts, risks, and co-beneﬁts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speciﬁc context, implementation and scale (high conﬁdence). {WGIII SPM C.11.2} 140 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5°C. {WGIII SPM footnote 68}

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