Editing IPCC:AR6/WGII/Chapter-16 (section)

=== 16.5.2 Identification and Assessment of Key Risks and Representative Key Risks ===

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==== 16.5.2.1 Identification of Key Risks ====

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The authors of the sectoral and regional chapters and cross chapter papers of the WGII AR6 Report identified more than 120 key risks (SM16.7.4). Authors were asked to rely on the above definition and criteria to identify risks that could potentially become severe according to changes in the associated hazards, the study systems’ exposure and/or vulnerability, and important adaptation strategies that could reduce these risks (see SM16.3 for methodology). Wherever possible, identification is based on literature that includes projected future conditions for all three components of risk and adaptation. Where literature was insufficient, potential severity is based on current vulnerability and exposure to climate hazards and the expectation that hazards will increase in frequency and/or intensity in the future. This approach is more limited in that it does not consider future changes in exposure and vulnerability nor in adaptation, but has the benefit of being grounded in observed experience.

Table SM16.24 indicates that climate change presents a wide range of risks across scales, sectors and regions that could become severe under particular conditions of hazards, exposure and vulnerability, which may or may not occur. Some illustrations of the extent and diversity of KRs are provided here, and more detailed assessment can be found in the Chapters referenced in the table.

Global-scale KRs include threats to biodiversity in oceans, coastal regions and on land, particularly in biodiversity hotspots, as well as other ecological risks such as geographic shifts in vegetation, tree mortality, reduction in populations and reduction in growth (such as for shellfish). These ecological risks include cascading impacts on livelihoods and food security. Global-scale risks also include risks to people, property and infrastructure from river flooding and extreme heat (particularly in urban areas), risks to fisheries (with implications for living standards and food security) and some health risks from food-borne diseases as well as psychopathologies.

Many KRs are especially prominent in particular regions or systems, or for particular subgroups of the population. For example, coastal systems and small islands are a nexus of many KRs, including those to ecosystems and their services, especially coral reefs; people (health, livelihoods); and assets, including infrastructure. Risks to socio-ecological systems in polar regions are also identified as KRs, as are ecological risks to the Amazon Forest in South America and savannahs in Africa. For some regions, risks from wildfire are of particular concern, including in Australasia and North America. Vector-borne diseases are a particular concern in Africa and Asia. Loss of cultural heritage is identified as a KR in small islands, mountain regions, Africa, Australasia and North America.

For many risks, low-income populations are particularly vulnerable to KRs. Climate-related impacts on malnutrition and other forms of food insecurity will be larger for this group, along with small-holder farming households and Indigenous communities reliant on agriculture, and for women, children, the elderly and the socially isolated ( [[IPCC:Wg2:Chapter:Chapter-5#5.12|Section 5.12]] ). KRs in coastal communities are expected to affect low-income populations more strongly, including through risks to livelihoods of those reliant on coastal fisheries. KRs related to health are generally higher for low-income populations less likely to have adequate housing or access to infrastructure.

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==== 16.5.2.2 Identification of Representative Key Risks ====

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As in AR5 [[#Oppenheimer--2014|Oppenheimer et al. (2014)]] , major clusters of KRs are further analysed, and here referred to as ‘representative key risks’ (RKRs). RKRs were defined in a three-step process (SM16.3.1). First, half of [https://www.ipcc.ch/report/ar6/wg2/chapter/chapter-16 Chapter 16] authors independently mapped the KRs (SM16.7.4) to a set of candidate RKRs. Second, all [https://www.ipcc.ch/report/ar6/wg2/chapter/chapter-16 Chapter 16] authors discussed the set of independent results and proposed a list of RKRs, considering scope and overlap. Third, this proposal was discussed with a consultative group of about 20 WGII AR6 authors from other chapters closely involved in the KR identification process, and a final list of eight RKRs was identified (Table 16.6).

The RKRs are intended to capture the widest variety of KRs to human or ecological systems with a small number of categories that are easier to communicate and provide a manageable structure for further assessment. They expand the scope of some AR5 KR clusters (e.g., on coasts, health, food and water) and add new ones (e.g., on peace and human mobility). The RKRs encompass a diversity of types of systems, including an example of a geographically defined system (RKR ''-'' A on coastal regions), ecosystem well-being and integrity (RKR ''-'' B), a cross-cutting issue relevant to several outcomes of concern (RKR-C on critical infrastructure) and several topics focused directly on aspects of human well-being and security (RKR ''-'' D to RKR ''-'' H). This set of RKRs manages but does not eliminate overlap, instead providing alternative perspectives on underlying key risks that sometimes include complementary views on common risks. For example, the water security RKR highlights the many key risks mediated by water quantity or quality, which are sometimes manifested as risk to food security (RKR-F) or health (RKR-E).

'''Table 16.6 |''' Climate-related representative key risks (RKRs). The scope of each RKR is further described in the assessments in [[#16.5.2.3|Section 16.5.2.3]] . Relation to categories of overarching key risks identified in AR5 is provided for continuity.

{| class="wikitable"
|-
! Code

! Representative key risk

! Scope

! Relation to AR5 overarching key risks;

for definitions, refer to Oppenheimer et al.. (2014)

! Subsection assessment

|-
| RKR-A

| Risk to low-lying coastal socio-ecological systems

| Risks to ecosystem services, people, livelihoods and key infrastructure in low-lying coastal areas, and associated with a wide range of hazards, including sea level changes, ocean warming and acidification, weather extremes (storms, cyclones), sea ice loss, etc.

| Contains key risk (i), overlaps with key risks (iii) and (vii)

| 16.5.2.3.1

|-
| RKR-B

| Risk to terrestrial and ocean ecosystems

| Transformation of terrestrial and ocean/coastal ecosystems, including change in structure and/or functioning, and/or loss of biodiversity.

| Contained in key risks (vii) and (viii)

| 16.5.2.3.2

|-
| RKR-C

| Risks associated with critical physical infrastructure, networks and services

| Systemic risks due to extreme events leading to the breakdown of physical infrastructure and networks providing critical goods and services.

| Overlaps with key risk (iii)

| 16.5.2.3.3

|-
| RKR-D

| Risk to living standards

| Economic impacts across scales, including impacts on gross domestic product (GDP), poverty and livelihoods, as well as the exacerbating effects of impacts on socioeconomic inequality between and within countries.

| Broader version of key risk (ii)

| 16.5.2.3.4

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| RKR-E

| Risk to human health

| Human mortality and morbidity, including heat-related impacts and vector-borne and waterborne diseases.

| Broader version of key risk (iv)

| 16.5.2.3.5

|-
| RKR-F

| Risk to food security

| Food insecurity and the breakdown of food systems due to climate change effects on land or ocean resources.

| Overlaps with key risk (v)

| 16.5.2.3.6

|-
| RKR-G

| Risk to water security

| Risk from water-related hazards (floods and droughts) and water quality deterioration. Focus on water scarcity, water-related disasters and risk to indigenous and traditional cultures and ways of life.

| Overlaps with key risk (iv)

| 16.5.2.3.7

|-
| RKR-H

| Risks to peace and to human mobility

| Risks to peace within and among societies from armed conflict as well as risks to low-agency human mobility within and across state borders, including the potential for involuntarily immobile populations.

| New

| 16.5.2.3.8

|}

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==== 16.5.2.3 Assessment of Representative Key Risks ====

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Each RKR was assessed by a team of four to nine members drawn from Chapter 16, other WGII AR6 chapters, and external contributing authors (SM16.4). The following subsections describe the scope of the category of risk (underlying KR considered) and the approach to defining ‘severe’ risks for each particular RKR. They also assess the conditions in terms of warming (more broadly, climatic impact drivers; ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ), exposure/vulnerability and adaptation under which the RKR would become severe. For each of these dimensions, RKR teams considered generic levels ranging from High to Medium and Low. For warming levels, in line with WGI framing, High refers to climate outcomes consistent with RCP8.5 or higher, Low refers to climate outcomes consistent with RCP2.6 or lower, and Medium refers to outcomes for scenarios between RCPs 2.6 and 8.5. For reference, the full range of warming levels (across all climate models) associated with RCP8.5 for the 2081–2100 period is 3.0–6.2°C; for RCP2.6 it is 0.9–2.3°C; and for intermediate RCPs it is 1.8–3.6°C (Cross-Chapter Box CLIMATE in Chapter 1). For Exposure-Vulnerability, levels are determined by the RKR teams relative to the range of future conditions considered in the literature, for example based on the Shared Socioeconomic Pathways (SSPs) in which future conditions based on SSPs 1 or 5 represent Low exposure or vulnerability and those based on SSPs 3 or 4 represent High exposure or vulnerability ( [[#O’Neill--2014|O’Neill et al., 2014]] ; [[#van%20Vuuren--2014|van Vuuren and Carter, 2014]] ). For Adaptation, two main levels have been considered: High refers to near maximum potential, and Low refers to the continuation of today’s trends. Despite being intertwined in reality, Exposure-Vulnerability and Adaptation conditions are distinguished to help understand their respective contributions to risk severity. Importantly, this assessment does not consider all risks, but only those that can be considered severe given the definition and criteria presented in [[#16.5.1|Section 16.5.1]] . The assessment does not exclude the possibility that severe risks are already observed in some contexts, and considers projected risks through the end of this century.

Each RKR assessment followed a common set of guidelines (SM16.3) that included broad criteria for defining severity ( [[#16.5.1|Section 16.5.1]] ), consideration of complex risks and interactions within and across RKRs, and consideration of risks across a range of scales, regions, and ecological and human development contexts. The specific definition of severity within each RKR was determined by the author teams of that assessment, applying different combinations of key risk criteria and metrics as judged appropriate in each case. Definitions are transparent and use common criteria, but are nonetheless based on the respective author team’s judgement. Conclusions about severity and associated confidence statements are therefore conditional on those definitions.

Assessments are based on different types of evidence depending on the nature of the literature. In some cases, quantitative projections of potential impacts are available. In others and as for KR identification, the potential for severe risk is inferred from high levels of current vulnerability and the expectation that the relevant climate hazards (climatic impact drivers, CIDs) will increase in frequency or intensity in the future.

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===== 16.5.2.3.1 Risk to the integrity of low-lying coastal socio-ecological systems (RKR-A) =====

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RKR-A considers climate-change-related risks to low-lying coasts including their physical, ecological and human components. Low-lying systems are those occupying land below 10 m of elevation that is contiguous and hydrologically connected to the sea ( [[#McGranahan--2007|McGranahan et al., 2007]] ). The assessment builds on Key Risks identified in Chapters 3 and 15, Cross Chapter Paper 2 as well as in the SROCC ( [[#Magnan--2019|Magnan et al., 2019]] ; [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ). It highlights risks to (i) natural coastal protection and habitats; (ii) lives, livelihoods, culture and well-being; and (iii) critical physical infrastructure; it therefore overlaps with several other RKRs (Figures 16.10, 16.11) but within a coastal focus. It encompasses all latitudes and considers multiple sources of climate hazards, including SLR, ocean warming and acidification, permafrost thaw, and sea ice loss and changes in weather extremes.

Severe risks to low-lying coasts involve irreversible long-term loss of land, critical ecosystem services, livelihoods, well-being or culture in relation to increasing combined drivers, including climate hazards and exposure and vulnerability conditions. The definition depends on the local context because of variation in the perception of tolerable risks and the limits to adaptation ( [[#Handmer--2019|Handmer and Nalau, 2019]] ). Accordingly, a qualitative range of consequences is presented here, in place of a quantitative global severe risk threshold.

The literature suggests that severe risks generally occur at the nexus of high levels and rates of anthropogenic-driven change in climate hazards ( [[#16.2.3.2|Section 16.2.3.2]] ), concentrations of people and tangible and intangible assets, non-climate hazards such as sediment mining and ecosystem degradation ( [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.1|Section 3.4.2.1]] ), and the reaching of adaptation limits ( [[#16.4|Section 16.4]] ) ( ''medium evidence'' , ''high agreement'' ). In some Arctic communities and in communities reliant on warm-water coral reefs, even 1.5–2°C warming will lead to severe risks from loss of ecosystem services ( [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.2|Section 3.4.2.2]] ; Cross-Chapter Paper 6) ( ''high confidence'' ). Loss of land is already underway globally due to accelerating coastal erosion and will be amplified by increased sea level extremes and permanent flooding ( ''high confidence'' ; Oppenheimer et al. 2019, Ranasinghe et al. 2021). Observed impacts of and projected increases in high-intensity extreme events (Ranasinghe et al. 2021) also provide evidence for severe risk to occur on livelihoods, infrastructure and well-being ( [[#16.5.2.3.3|Section 16.5.2.3.3]] ) by mid-century ( ''high confidence'' ). Consequently, the combination of high warming, continued coastal development and low adaptation levels will challenge the habitability of many low-lying coastal communities in both developing and developed countries over the course of this century ( ''limited evidence'' , ''high agreement'' ) ( [[#Duvat--2021|Duvat et al., 2021]] ; [[#Horton--2021|Horton et al., 2021]] ). In some contexts, climate risks are already considered severe ( ''medium evidence'' , ''medium agreement'' ), and in others, even lower warming will induce severe risks to habitability, which will not necessarily be offset by ambitious adaptation ( ''limited evidence'' , ''medium agreement'' ).

# Natural coastal protection and habitats—severe risks from the loss of shoreline protection from reductions in wave attenuation ( [[#Beck--2018|Beck et al., 2018]] , Sections 3.5.5.1, 3.5.4.5) and sediment delivery (Sections 3.4.2.5, 15.3.3) are already observed in some coastal systems ( [[#16.2.3.1|Section 16.2.3.1]] ) and occur broadly even with 1.5°C of global warming ( [[#Hoegh-Guldberg--2018a|Hoegh-Guldberg et al., 2018a]] ; [[#Bindoff--2019|Bindoff et al., 2019]] , [[IPCC:Wg2:Chapter:Chapter-3#3.4.2|Section 3.4.2]] ). These impacts are the consequence of warming and SLR on coastal ecosystems.

Warm-water coral reefs are at risk of widespread loss of structural complexity and reef accretion by 2050 under 1.5°C global warming ( [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.1|Section 3.4.2.1]] ) ( ''high confidence'' ). Kelp forests may experience shifts in community structure ( [[#Arafeh-Dalmau--2019|Arafeh-Dalmau et al., 2019]] ; [[#Rogers-Bennett--2019|Rogers-Bennett and Catton, 2019]] ; [[#Smale--2020|Smale, 2020]] ; [[#Smith--2021|Smith et al., 2021]] ) with &gt;2°C of global warming especially at lower latitudes ( [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.2|Section 3.4.2.2]] ) ( ''high confidence'' ). In addition, depending on the local tide and sediment conditions, SLR associated with &gt;1.5°C of global warming (SSP1–2.6; 3.4.2.5) is sufficient to initiate shifts to alternate states in some seagrass and coastal wetland systems ( [[#van%20Belzen--2017|van Belzen et al., 2017]] ; [[#El-Hacen--2018|El-Hacen et al., 2018]] , [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.5|Section 3.4.2.5]] , Cross-Chapter Box SLR in Chapter 3), and submergence of some mangrove forests ( [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.5|Section 3.4.2.5]] ). A striking example of risks becoming severe at higher levels of warming is the one of coral islands with low elevation ( [[IPCC:Wg2:Chapter:Chapter-15#15.3.4|Section 15.3.4]] , Box 15.1): the risk of loss of habitability transitions from Moderate-to-High under RCP2.6 for most island types (urban and rural) to High-to-Very High under RCP8.5 ( [[#Duvat--2021|Duvat et al., 2021]] ), even under a high adaptation scenario ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ), partly due to declining sediment supply ( [[#Perry--2018|Perry et al., 2018]] ) and increased annual flooding ( [[#Giardino--2018|Giardino et al., 2018]] ; [[#Storlazzi--2018|Storlazzi et al., 2018]] ).

More broadly, about 28,000 km 2 of land have been lost globally since the 1980s due to anthropogenic factors (e.g., coastal structures, disruption of sediment fluxes) and coastal hazards ( [[#Mentaschi--2018|Mentaschi et al., 2018]] ), and an additional loss of 6000–17,000 km 2 is estimated by the end of the century due to coastal erosion alone associated with SLR in combination with other drivers ( [[#Hinkel--2013|Hinkel et al., 2013]] ).

# Impacts to lives, livelihoods, culture and well-being—in the absence of effective adaptation, changing extreme and slow-onset hazards combined with anthropogenic drivers (e.g., increased population pressure at the coast between +5% and +13.6% by 2100 compared with today, [[#Jones--2016|Jones and O’Neill, 2016]] ) will lead to loss of lives, livelihoods, health, well-being and/or culture ( [[#McGregor--2016|McGregor et al., 2016]] ; [[#Pinnegar--2019|Pinnegar et al., 2019]] ; [[#Pugatch--2019|Pugatch, 2019]] ; [[#Schneider--2020|Schneider and Asch, 2020]] ; [[#Thomas--2020|Thomas and Benjamin, 2020]] ; [[#McNamara--2021|McNamara et al., 2021]] ) ( ''high confidence'' ). Catastrophic examples that may foreshadow the future include Hurricane Sandy in 2012 ( [[#Strauss--2021|Strauss et al., 2021]] ) and Super Typhoon Haiyan in 2013 (&gt;6,000 deaths and inequities in access to safe housing; Trenberth et al. 2015) (Sections 6.2.2, 6.3.5.1). Although there is no unique definition of ‘intolerable’ loss, risks are generally expected to become severe over this century ( [[#Tschakert--2017|Tschakert et al., 2017]] ; [[#Dannenberg--2019|Dannenberg et al., 2019]] ; [[#Tschakert--2019|Tschakert et al., 2019]] ). Globally, with High warming, 90–380 million more people will be exposed to annual flood levels by the mid- and end-century, respectively, compared with 250 million people today ( [[#Kulp--2019|Kulp and Strauss, 2019]] ; [[#Kirezci--2020|Kirezci et al., 2020]] ), with potential implications on forced displacement or migration ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ; [[#Wrathall--2019|Wrathall et al., 2019]] ; [[#Hauer--2020|Hauer et al., 2020]] ; [[#Lincke--2021|Lincke and Hinkel, 2021]] , [[#16.5.2.3.8|Section 16.5.2.3.8]] ). Some of the largest fish-producing and fish-dependent ecoregions have already experienced losses of up to 35% in marine fisheries productivity due to warming ( [[#Free--2019|Free et al., 2019]] ), and about 11% of the global population will face increasing nutritional risks if current trajectories continue ( [[#Golden--2016|Golden et al., 2016]] ). While difficult to measure, current climate-driven losses to (Indigenous) knowledge, traditions ( [[#Tschakert--2019|Tschakert et al., 2019]] ; [[#Pearson--2021|Pearson et al., 2021]] ) and well-being ( [[#Ebi--2017|Ebi et al., 2017]] ; [[#Cunsolo--2018|Cunsolo and Ellis, 2018]] ; [[#Jaakkola--2018|Jaakkola et al., 2018]] ) indicate such risk as already severe in some regions ( ''limited evidence'' , ''medium agreement'' ), jeopardising communities’ realisation of their rights to food, health and culture. In the Arctic, climate-driven changes to ice and weather regimes have substantially affected traditional coastal-based hunting and fishing activities ( [[#Fawcett--2018|Fawcett et al., 2018]] ; [[#Galappaththi--2019|Galappaththi et al., 2019]] ; [[#Huntington--2020|Huntington et al., 2020]] ; [[#Nuttall--2020|Nuttall, 2020]] , Cross-Chapter Paper 6), and where permafrost thaw, SLR and coastal erosion are contributing to threatening cultural sites ( [[#Hollesen--2018|Hollesen et al., 2018]] ; [[#Fenger-Nielsen--2020|Fenger-Nielsen et al., 2020]] ).
# Critical physical infrastructure—severe risks are also illustrated through damages that lead to possibly long-lasting disruption of key services like transportation as well as energy generation and distribution in coastal areas ( [[#16.5.2.3.3|Section 16.5.2.3.3]] ) under all RCPs (Section [https://www.ipcc.ch/chapter/16#CCP2.2 CCP2.2.3] ) and if no additional adaptation ( ''medium confidence'' ). Critical transport infrastructure is already suffering from structural failures in polar regions, for instance, due to permafrost thaw and increased erosion associated with ocean warming, storm surge flooding and loss of sea ice ( [[#Melvin--2017|Melvin et al., 2017]] ; [[#Fang--2018|Fang et al., 2018]] , Sections 14.5.2.8, 16.2.3.2, Cross-Chapter Paper 6). One hundred airports are projected to be below mean sea level in 2100 with 2°C of warming (i.e., 0.62 m SLR, [[#Yesudian--2021|Yesudian and Dawson, 2021]] ), including in small islands ( [[#Monioudi--2018|Monioudi et al., 2018]] ; [[#Storlazzi--2018|Storlazzi et al., 2018]] ) and megacities. Projections show San Francisco International Airport, for instance, to be inundated by 2100 under the upper likely range of SLR in RCP8.5 (also considering subsidence trends, [[#Shirzaei--2018|Shirzaei and Bürgmann, 2018]] ). On the energy side, it is estimated that with 1.8 m SLR, for example, 4 out of 13 US nuclear power plant facilities will become exposed to storm surges and 3 others will be surrounded or submerged by seawater ( [[#Jordaan--2019|Jordaan et al., 2019]] ; [[#Jenkins--2020|Jenkins et al., 2020]] ).

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===== 16.5.2.3.2 Risk to terrestrial and ocean ecosystems (RKR-B) =====

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This risk refers to transformations of terrestrial and ocean/coastal ecosystems that would include significant changes in structure and/or functioning, and/or loss of a substantial fraction of species richness (commonly used to indicate loss of biodiversity). These are sourced mainly from Chapters 2 and 3, Cross-Chapter Paper 1, and reference the 1.5C report, [[IPCC:Wg2:Chapter:Chapter-4|Chapter 4]] from WGII AR5, and [[IPCC:Wg2:Chapter:Chapter-4|Chapter 4]] from WGII AR4 Reports.

Severe adverse impacts on biodiversity include significant risk of species extinction (e.g., loss of a substantial fraction (one-tenth or more) of species from a local to global scale), mass population mortality (&gt;50% of individuals or colonies killed), ecological disruption (order-of-magnitude increases or abrupt reductions of population numbers or biomass), shifts in ecosystem structure and function (order-of magnitude increases or abrupt decreases in cover and/or biomass of novel growth forms or functional types) and/or a socioeconomically material increase in environmental risk (e.g., destruction by wildfire) or socioeconomically material decline in goods and services (e.g., carbon stock losses, loss of grazing, loss of pollination). Metrics relevant to SDGs are also germane.

A substantial proportion of biodiversity is at risk of being lost below 2°C of global warming (Chapter 2), due to range reductions and loss globally, with this risk amplified roughly three times in insular ecosystems and biodiversity hotspots, due to the increased vulnerability of endemic species ( [[#Manes--2021|Manes et al., 2021]] ). High-latitude, high-altitude, insular, freshwater, and coral reef ecosystems and biodiversity hotspots (Chapter 2, Cross-Chapter Paper 1) are at appreciable risk of substantial biodiversity loss due to climate change even under Low warming ( ''high confidence'' ). These systems comprise a large fraction of unique and endemic biodiversity, with species impacts often exacerbated by multiple drivers of global change (Chapter 2, Chapter 3). Roughly one-third of all known plant species are extremely rare, vulnerable to climate impacts, and clustered in areas of higher projected rates of anthropogenic climate change ( [[#Enquist--2019|Enquist et al., 2019]] ). Much evidence shows increased risk of the loss of 10% or more of terrestrial biodiversity with increasing anthropogenic climate change ( [[#Urban--2015|Urban, 2015]] ; [[#Smith--2018|Smith et al., 2018]] ) ( ''medium confidence'' ), ''likely'' with 2°C warming above pre-industrial level (Chapter 2), with consequent degradation of terrestrial, freshwater and ocean ecosystems ( [[#Oliver--2015|Oliver et al., 2015]] ) and adverse impacts on ecosystem services ( [[#Pecl--2017|Pecl et al., 2017]] ) and dependent human livelihoods ( [[#Dube--2016|Dube et al., 2016]] ). Adverse impacts on biodiversity may show lagged responses ( [[#Essl--2015|Essl et al., 2015]] ), and loss of a substantial fraction of species could occur abruptly, simultaneously across multiple taxa, below 4°C of global warming ( [[#Trisos--2020|Trisos et al., 2020]] ).

Mass population-level mortality (&gt;50% of individuals or colonies killed) and resulting abrupt ecological changes can be caused by simple or compound climate extreme events, such as exceedance of upper thermal limits by vulnerable terrestrial species ( [[#Fey--2015|Fey et al., 2015]] ), who also note reduced mass mortality trends due to extreme low thermal events; marine heatwaves that can cause mortality, enhance invasive alien species establishment, and damage coastal ecological communities and small-scale fisheries ( ''high confidence'' ) ( [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.7|Section 3.4.2.7]] ); and increased frequency and extent of wildfires that threaten populations dependent on habitat availability (like Koala Bears, [[#Lam--2020|Lam et al., 2020]] ). Abrupt ecological changes are widespread and increasing in frequency ( [[#Turner--2020|Turner et al., 2020]] ), and include tree mortality due to insect infestation exacerbated by drought, and ecosystem transformation due to wildfire ( [[#Vogt--2020|Vogt et al., 2020]] ). Freshwater ecosystems and their biodiversity are at high risk of biodiversity loss and turnover due to climate change (precipitation change and warming, including warming of water bodies), due to high sensitivity of processes and life histories to thermal conditions and water quality (Chapter 2) ( ''high confidence'' ). In marine systems, heatwaves cause damages in coastal systems, including extensive coral bleaching and mortality ( ''very high confidence'' ) ( [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.1|Section 3.4.2.1]] ), mass mortality of invertebrate species ( ''low'' to ''high confidence'' , depending on system) (Sections 3.4.2.2, [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.5|Section 3.4.2.5]] , [[IPCC:Wg2:Chapter:Chapter-3#3.4.4|Section 3.4.4.1]] ), and abrupt mortality of kelp-forest ( ''high confidence'' ) ( [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.3|Section 3.4.2.3]] ) and seagrass-meadow habitat ( ''high confidence'' ) ( [[IPCC:Wg2:Chapter:Chapter-3#3.4.4|Section 3.4.4.2]] ). The biodiversity of polar seas shows strong impacts of climate change on phenological timing of plankton activity, Arctic fish species range contractions and species community change (Table SM16.22) ( ''high confidence'' ). Extreme weather events and storm surges exacerbated by climate change have severe and sudden adverse impacts on coastal systems, including loss of seagrass meadows and mangrove forests ( ''high confidence'' ) (see [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.7|Section 3.4.2.7]] , [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.8|Section 3.4.2.8]] , Cross-Chapter Box EXTREMES in Chapter 2).

Ecological disruption (order-of-magnitude increases or abrupt reductions of population numbers or biomass) can occur due to unprecedented inter-species interactions with unpredictable outcomes in ‘novel ecosystems’ (Chapter 2) as species shift geographic ranges idiosyncratically in response to climatic drivers (Table SM16.22). Idiosyncratic geographic shifts are now observed in an appreciable fraction of species studied (Chapter 2, Table 16.2). Commensal or parasitic diseases may infect immunologically naive hosts (e.g., chytrid fungus in amphibians). Atypical disturbance regimes may be enhanced, for example, with the spread of flammable plant species (e.g., [[#du%20Toit--2015|du Toit et al., 2015]] ), exacerbated by introduced species (e.g., [[#Martin--2015|Martin et al., 2015]] ), thus significantly increasing risk of losses and damages to infrastructure and livelihoods, as well as ecological degradation, and challenging existing management approaches.

Landscape- and larger-scale shifts in ecosystem structure and function (order-of-magnitude increases or abrupt decreases in cover and/or biomass of novel growth forms or functional types) are occurring in non-equilibrium ecosystems (systems which exist in multiple states, often disturbance-controlled) in response to changing disturbance regime, climate and rising CO 2 ( ''high confidence'' ) Woody plant encroachment has been occurring in multiple ecosystems, including subtropical and tropical fire driven grassland and savanna systems, upland grassland systems, arid grasslands and shrublands ( ''high confidence'' ), leading to large-scale biodiversity changes, albedo changes, and impacts on water delivery, grazing services and human livelihoods ( ''medium confidence'' ). Expansion of grasses (alien and native) into xeric shrublands is occurring, causing increasing fire prevalence in previous fire-free vegetation (Cross-Chapter Paper 3). In tropical forests, repeated droughts and recurrence of large-scale anthropogenic fires increase forest degradation, loss of biodiversity and ecosystem functioning ( ''high confidence'' ) ( [[#Anderson--2018b|Anderson et al., 2018b]] ; Longo et al., 2020). Accelerated growth rates and mortality of tropical trees is also adversely affecting tropical ecosystem functioning ( [[#McDowell--2018|McDowell et al., 2018]] ; [[#Aleixo--2019|Aleixo et al., 2019]] ). Projected changes in ecosystem functioning, such as via wildfire ( [[IPCC:Wg2:Chapter:Chapter-2#2.5|Section 2.5.5.2]] ), tree mortality ( [[IPCC:Wg2:Chapter:Chapter-2#2.5|Section 2.5.5.3]] ) and woody encroachment under climate change (Chapter 2) would alter hydrological processes, with adverse implications for water yields and water supplies ( [[#Sankey--2017|Sankey et al., 2017]] ; [[#Robinne--2018|Robinne et al., 2018]] ; [[#Rodrigues--2019|Rodrigues et al., 2019]] ; [[#Uzun--2020|Uzun et al., 2020]] ).

The loss of a substantial fraction of biodiversity globally, abrupt impacts such as significant local biodiversity loss and mass population mortality events, and ecological disruption due to novel species interactions have been observed or are projected at global warming levels below 2°C ( [[IPCC:Wg2:Chapter:Chapter-2|Chapter 2]] Table SM2.5, Cross Chapter Box: EXTREMES in Chapter 2, [[IPCC:Wg2:Chapter:Chapter-2#2.4.4.3.1|Section 2.4.4.3.1]] , [[IPCC:Wg2:Chapter:Chapter-2#2.4.2.3.3|Section 2.4.2.3.3]] ) ( ''medium confidence'' ). Simple and compound impacts of extreme climate events are already causing significant losses and damages in vulnerable ecosystems, including through the facilitation of important global change drivers of ecological disruption and homogenisation like invasive species ( ''high confidence'' ). Severe impacts on human livelihoods and infrastructure, and valuable ecosystem services, are all projected to accompany these changes. Adaptation potential for many of these risks is low due to the projected rate and magnitude of change, and to the requirement of significant amounts of land for terrestrial ecosystems ( [[#Hannah--2020|Hannah et al., 2020]] ). Biodiversity conservation efforts may be hampered due to climate change impacts on the effectiveness of protected areas, with high sensitivity of effectiveness to forcing scenario ( ''medium confidence'' ). In addition, climate-related risks to ecosystems pose challenges to ecosystem-based adaptation responses (‘nature-based solutions’) ( [[IPCC:Wg2:Chapter:Chapter-2#2.1|Section 2.1.3]] ) ( ''medium confidence'' ).

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<span id="risk-to-critical-physical-infrastructure-and-networks-rkr-c"></span>
===== 16.5.2.3.3 Risk to critical physical infrastructure and networks (RKR-C) =====

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RKR-C includes risks associated with the breakdown of physical infrastructure and networks which provide goods and services considered critical to the functioning of societies. It encompasses infrastructure systems for energy, water, transportation, telecommunications, health care and emergency response, as well as compound, cascading and cross-boundary risks resulting from infrastructure interdependencies ( [[#Birkmann--2016|Birkmann et al., 2016]] ; [[#Fekete--2019|Fekete, 2019]] ). Critical infrastructures such as transport or energy supply also play a central role in coping with climate risks, especially in acute disaster situations in which the services of transport infrastructure, communication technologies or electricity are particularly needed, despite the fact that these very systems are themselves exposed to disaster impacts ( [[#Garschagen--2016|Garschagen et al., 2016]] ; [[#Pescaroli--2018|Pescaroli et al., 2018]] ). The major hazards driving such risks are acute extreme events such as cyclones, floods, droughts or fires ( ''high confidence'' ), but cumulative and chronic hazards such as SLR are also considered.

RKR-C is considered severe when the functioning of critical infrastructure cannot be secured and maintained against climate change impacts, resulting in the frequent and widespread breakdown of service delivery and eventually a significant rise of detrimental impacts on people (lives, livelihoods and well-being), the economy (including averted growth) or the environment (disruption and loss of ecosystems) above historically observed levels. Severity in this RKR is assessed on two levels for (i) direct impacts of climate change on infrastructure assets and networks (e.g., amount of port infrastructure damaged or destroyed by SLR, flooding and storms) on which most of the literature focuses, as well as (ii) indirect and cascading downstream impacts to people, economy and environment ( [[#Markolf--2019|Markolf et al., 2019]] ; [[#Pyatkova--2019|Pyatkova et al., 2019]] ; [[#Chester--2020|Chester et al., 2020]] ), for which attribution is more difficult and uncertainties tend to be much higher. Overall, the literature with quantified assessments of climate change infrastructure risks remains to be less extensive than for many other risks, particularly with regard to assessments focusing on the Global South. While climate-related changes in hazards are widely considered in the literature, changes in future exposure and vulnerability conditions are often not treated explicitly. In addition, the severity of infrastructure risks also depends on future trends in the capacity to maintain, repair and rebuild infrastructure and adapt it to new hazard intensities ( ''medium evidence'' , ''high agreement'' ). These are mostly not quantified in a forward-looking manner in the literature; however, damage projections (see below) indicate a rapidly rising demand for investment, straining the financial capacity of countries ( ''medium evidence'' , ''high agreement'' ).

# Risks related to direct impacts on critical infrastructure would become severe with high warming, current infrastructure development regimes and minimal adaptation ( ''high confidence'' ), and in some contexts even with low warming, current vulnerability and no additional adaptation ( ''medium confidence'' ), with severity defined as infrastructure damage and required maintenance costs exceeding multiple times the current levels. Transport and energy infrastructure in coasts and polar systems and along rivers are projected to face a particularly steep rise in risk, resulting in severe risk even under medium warming ( ''high confidence'' ). Risk in relation to the increasing intensity and frequency of extreme events might become severe before the middle of the century ( ''medium confidence'' ). Damages from multiple climate hazards to transport, energy, industry and social infrastructure in Europe could increase 10-fold by the 2080s, from 3.4 € billion annually to date, and 15-fold for transport infrastructure, under Medium warming (A1B, ~3°C by 2100) and with current adaptation levels, even if no further extension of the infrastructure in exposed areas is considered ( [[#Forzieri--2018|Forzieri et al., 2018]] ). Under High warming (RCP8.5) in 2100, the percent of roads in the USA that require rehabilitation due to high temperatures and precipitation is expected to increase to 23–33%, relative to 14% in 2100 when no climate change is considered ( [[#Mallick--2018|Mallick et al., 2018]] ). Projections of climate-induced changes in exposure are an incomplete measure of risk but in the absence of other metrics can serve as a proxy for the potential for severe impacts. In the circumpolar Arctic, 14.8% of critical infrastructure assets would be affected by climate change under RCP8.5 by 2050, with lifecycle replacement costs projected to increase by 27.7% if infrastructure is to be preserved at current adaptation levels ( [[#Suter--2019|Suter et al., 2019]] ). Under RCP8.5, the number of ports under high risk will increase from 3.8% in the present day to 14.4% by 2100, as a result of increased coastal flooding and overtopping due to SLR, as well as the heat stress impacts of higher temperatures ( [[#Izaguirre--2021|Izaguirre et al., 2021]] ). In the UK under High warming (4°C), the number of clean and wastewater treatment sites located in the 1-in-75-year floodplain will increase by a third relative to today by the 2080s under current vulnerability and adaptation levels ( [[#Dawson--2018|Dawson et al., 2018]] ). A global assessment of changing climate and water resources for electricity generation finds considerable reductions in usable hydropower and thermoelectric capacity by 2050 for a range of warming scenarios from Low to High, with absolute declines on average for most (61–74%) of the world’s hydropower resources and monthly maximum reductions above 30% of usable capacity for over two-thirds of 1427 thermoelectric power plants worldwide ( [[#Van%20Vliet--2016|Van Vliet et al., 2016]] ). Many studies find large technical potential for coordinated adaptation–mitigation policies in the electricity sector to avoid a significant portion of projected climate change impacts (e.g., a two-thirds reduction, and in some cases fully offset) ( [[#Ciscar--2014|Ciscar and Dowling, 2014]] ; [[#Van%20Vliet--2016|Van Vliet et al., 2016]] ; [[#Gerlak--2018|Gerlak et al., 2018]] ; [[#Allen-Dumas--2019|Allen-Dumas et al., 2019]] ).
# Studies quantifying the indirect impacts of infrastructure failure on lives, livelihoods and economies are still rare but emerging, suggesting that risks would become severe in many contexts globally with high warming, current vulnerability and no additional adaptation ( ''medium confidence'' ). Severity in this context is defined as the potential to disrupt the lives, livelihoods and well-being of a significantly increased proportion of the population and to significantly forestall economic growth and development potential. Global risks to air travel from SLR, expressed in terms of expected annual route disruptions, could increase by a factor of between 17 and 69 by 2100 under the 1.5°C and the 95th percentile value of the RCP8.5 SLR scenario, respectively ( [[#Yesudian--2021|Yesudian and Dawson, 2021]] ). By 2050, up to 185,000 airline passengers per year may be grounded due to extreme heat (48°C) if no additional adaptation is taken, roughly 23 times more than today ( [[#McKinsey%20Global%20Institute--2020|McKinsey Global Institute, 2020]] ). In Africa, under RCP8.5 and without additional adaptation, a 250% increase in disruption time of the transport network is expected by 2050 due to extreme temperatures, a 76% increase due to precipitation, and 1400% increase due to flooding ( [[#Cervigni--2015|Cervigni et al., 2015]] ). On the Dawlish railway section (UK), the number of days with line restrictions is set to increase by up to 1170%, to as high as 84–120 yr –1 by 2100 due to 0.8 m SLR with High warming ( [[#Dawson--2016|Dawson et al., 2016]] ). Next to the limited number of projections or scenarios of indirect impacts, additional inferences from studies focusing on past and current impacts can be drawn. Already today, climate-related impacts on transport and energy infrastructure reach far beyond the direct impacts on physical infrastructure, triggering indirect impacts on, for example, health and income ( ''medium confidence'' ). A case study of future flood hazard in Europe found that the indirect impact of a power outage on the local economy is six to eight times greater than the direct flood damage and asset repair costs, due to the interruption of daily economic activity ( [[#Karagiannis--2019|Karagiannis et al., 2019]] ). In low- and middle-income countries, the annual costs from infrastructure disruptions reach up to 300 billion USD for firms and 90 billion USD for private households, with natural hazards such as floods being responsible for 10–70% of these disruptions, depending on the sectors and regions ( [[#Hallegatte--2019|Hallegatte et al., 2019]] ). Power outages triggered by floods or droughts have also been found to have substantial health implications, particularly among low-income populations ( [[#Klinger--2014|Klinger et al., 2014]] ), and shown to impede disaster recovery efforts and severely disrupt local economies ( [[#Karagiannis--2019|Karagiannis et al., 2019]] ; [[#Nicolas--2019|Nicolas et al., 2019]] ). In addition, risks associated with infrastructure have the potential to become particularly severe when hazard-driven infrastructure disruptions undermine the capacity of emergency response in disaster situations ( ''limited evidence'' , ''high agreement'' ). A study on the UK shows, for example, that even a small increase in minor road flooding leads to a disproportionately high disruption of the efficacy of emergency services ( [[#Yu--2020|Yu et al., 2020]] ). Similar risks have been found for rural areas, particularly in developing countries ( [[#Alegre--2020|Alegre et al., 2020]] ).

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<span id="risk-to-living-standards-rkr-d"></span>
===== 16.5.2.3.4 Risk to living standards (RKR-D) =====

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This RKR includes risks to (i) aggregate economic output at the global and national levels, (ii) poverty and (iii) livelihoods, and their implications for economic inequality. It is informed by key risks identified by regional and sectoral chapters. Risks are potentially severe as measured by the magnitude of impacts in comparison with historical events or as inferred from the number of people currently vulnerable.

# Risks to aggregate economic output would become severe at the global scale with high warming and minimal adaptation ( ''medium confidence'' ), with severity defined as the potential for persistent annual economic losses due to climate change to match or exceed losses during the world’s worst historical economic recessions. With historically observed levels of adaptation, warming of ~4°C may cause a 10–23% decline in annual global GDP by 2100 relative to global GDP without warming, due to temperature impacts alone ( [[#Burke--2015|Burke et al., 2015]] ; [[#Kahn--2019|Kahn et al., 2019]] ; [[#Kalkuhl--2020|Kalkuhl and Wenz, 2020]] ). These magnitudes exceed economic losses during the Great Recession (2008–2009, ~5% decline in global GDP, up to 15–18% in some countries) and the COVID-19 pandemic (2020, ~3% decline globally, up to 10% in some countries) ( [[#IMF--2020|IMF, 2020]] ; [[#IMF--2021|IMF, 2021]] ). Unlike past recessions, climate change impacts would occur continuously every year. However, smaller effects (1–8%) are found when using alternative methodologies ( [[#Diaz--2017|Diaz and Moore, 2017]] ; [[#Nordhaus--2017|Nordhaus and Moffat, 2017]] ; [[#Kompas--2018|Kompas et al., 2018]] ; [[#Kalkuhl--2020|Kalkuhl and Wenz, 2020]] ), assuming less warming ( [[#Kahn--2019|Kahn et al., 2019]] ; Takakura et al., 2019), and assuming lower vulnerability and/or more adaptation ( [[#Diaz--2017|Diaz and Moore, 2017]] ); this literature is comprehensively summarised in Cross-Working Group Chapter Box ECONOMIC. Impacts at high levels of warming are particularly uncertain, as all methodologies require extrapolation and insufficiently incorporate possible tipping elements in the climate system ( [[#Kopp--2016|Kopp et al., 2016]] ).

Annual economic output losses in developing countries could exceed the worst country-level losses during historical economic recessions ( ''medium confidence'' ). Assuming global warming of ~4°C by 2100, historical adaptation levels and high vulnerability, losses across Sub-Saharan Africa may reach 12% of GDP by 2050 ( [[#Baarsch--2020|Baarsch et al., 2020]] ) and 80% by 2100 ( [[#Burke--2015|Burke et al., 2015]] ), and ~9% on average across developing countries by 2100 ( [[#Acevedo--2017|Acevedo et al., 2017]] ). The largest estimates are debated and depend on assumptions about development trends, adaptive capacity, and whether temperature impacts the level or growth rate of economic activity ( [[#Kalkuhl--2020|Kalkuhl and Wenz, 2020]] ). Severe risks are more likely in (typically hotter) developing countries because of nonlinearities in the relationship between economic damages and temperature ( [[#Burke--2015|Burke et al., 2015]] ; [[#Acevedo--2017|Acevedo et al., 2017]] ). These risks are highest in scenarios and countries with: a large portion of the workforce employed in highly exposed industries ( [[#Acevedo--2017|Acevedo et al., 2017]] ); a high concentration of population and economic activity on coastlines ( [[#Hsiang--2014|Hsiang and Jina, 2014]] ; [[#Acevedo--2017|Acevedo et al., 2017]] ); and an increase in the frequency or intensity of disasters triggered by natural hazards ( [[#Berlemann--2018|Berlemann and Wenzel, 2018]] ; [[#Botzen--2019|Botzen et al., 2019]] ). Whether baseline economic growth may help avoid severe future risks is highly uncertain ( [[#Dell--2012|Dell et al., 2012]] ; [[#Burke--2015|Burke et al., 2015]] ; [[#Acevedo--2017|Acevedo et al., 2017]] ; [[#Deryugina--2017|Deryugina and Hsiang, 2017]] ).

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[[File:74d211f7daf2c1526c89022ebf172002 IPCC_AR6_WGII_Figure_16_009.png]]

'''Figure 16.9 |''' '''Illustrative examples from individual studies of risks to living standards and the conditions under which they could become severe.''' Selected studies are not representative of the literature, but provide examples of potentially severe risks to aggregate economic output, poverty and livelihoods. High, medium and low levels of warming, exposure/vulnerability and adaptation are defined as in Figure 16.10.

# Under medium warming pathways, climate change risks to poverty would become severe if vulnerability is high and adaptation is low ( ''limited evidence'' , ''high agreement'' ). We define poverty in terms of absolute consumption levels and define severity as tens to hundreds of millions of additional people in poverty relative to the number without climate change (globally) or an absolute increase in the number of people living in poverty compared with today (nationally or locally). This global impact is comparable to the effect of the 2007 food price shock ( [[#De%20Hoyos--2009|De Hoyos and Medvedev, 2009]] ) and the 2020 COVID-19 pandemic ( [[#World%20Bank--2020|World Bank, 2020]] ) and can be compared to about 700 million in poverty in 2017, down from 1.9 billion in 1990 ( [[#World%20Bank--2020|World Bank, 2020]] ).

In a high-vulnerability development pathway, climate change in 2030 could push 35–132 million people into extreme poverty, in addition to the people already in poverty assuming climate is unchanged (disregarding impacts from natural variability; [[#Hallegatte--2017|Hallegatte and Rozenberg, 2017]] ; [[#Jafino--2020|Jafino et al., 2020]] ). In a low-warming pathway, risks from mitigation costs could also be severe if no progressive redistribution from carbon pricing revenues is applied (Soergel et al., 2021). At the national level, there is ''limited evidence'' of climate change causing an absolute increase in poverty (e.g., absolute increase of ~1–2% yr −1 through 2040, [[#Montaud--2017|Montaud et al., 2017]] ). Potentially severe risks to poverty are also supported by (1) the observed impacts of past disasters ( [[#Winsemius--2018|Winsemius et al., 2018]] ; [[#Hallegatte--2020|Hallegatte et al., 2020]] ; [[#Rentschler--2020|Rentschler and Melda, 2020]] ) and previous crises such as food price shocks ( [[#Ivanic--2008|Ivanic and Martin, 2008]] ) or current diseases ( [[#WHO--2018|WHO, 2018]] ) on poor people and on poverty; (2) the expectation that these events will become more intense or frequent in some regions (WGI Chapter 12, [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ); and (3) population growth and the low adaptive and coping capacities of the poor ( [[#Leichenko--2014|Leichenko and Silva, 2014]] ; [[#Huynh--2018|Huynh and Stringer, 2018]] ; [[#Thomas--2020|Thomas et al., 2020]] ). This literature provides indirect evidence that climate change will keep many people poor and may cause more than tens of millions to fall into poverty ( ''limited evidence'' , ''high agreement'' ).

# Climate change poses severe risks to livelihoods at low levels of warming, high exposure/vulnerability and low adaptation in climate-sensitive regions, ecosystems and economic sectors ( ''high confidence'' ), where severity refers to the disruption of livelihoods for tens to hundreds of millions of additional people ( [[#Arnell--2014|Arnell and Lloyd-Hughes, 2014]] ; [[#Liu--2018|Liu et al., 2018]] ). More widespread severe risks would occur at high levels of warming (with high exposure/vulnerability and low adaptation) where there is additional potential for one or more social or ecological tipping points to be triggered ( [[#Cai--2015|Cai et al., 2015]] ; [[#Cai--2016b|Cai et al., 2016b]] ; [[#Kopp--2016|Kopp et al., 2016]] ; [[#Steffen--2018|Steffen et al., 2018]] ; [[#Lenton--2019|Lenton et al., 2019]] ), and for severe impacts on livelihoods to cascade from relatively more climate-sensitive to relatively less climate-sensitive sectors and regions ( ''medium confidence'' ) ( [[#Lawrence--2020|Lawrence et al., 2020]] ). Severity assessment is based on the current magnitude of exposure and vulnerability across multiple social and ecological systems, projected future exposure and vulnerability, and the rate at which hazard frequency or intensity is expected to increase ( [[#Otto--2017|Otto et al., 2017]] ; [[#Roy--2018|Roy et al., 2018]] ; [[#Li--2019|Li et al., 2019]] , [[IPCC:Wg2:Chapter:Chapter-8#8.5|Section 8.5]] ). Without effective adaptation measures, regions with high dependence on climate-sensitive livelihoods—particularly agriculture and fisheries in the tropics and coastal regions—would be severely impacted even at low levels of warming ( ''high confidence'' ) ( [[#Hoegh-Guldberg--2018b|Hoegh-Guldberg et al., 2018b]] ; [[#Roy--2018|Roy et al., 2018]] ). For example, it is estimated that 330–396 million people could be exposed to lower agricultural yields and associated livelihood impacts at warming between 1.5°C and 2°C ( [[#Byers--2018|Byers et al., 2018]] ). Risks to the 200 million people with livelihoods derived from small-scale fisheries would also be severe, given sensitivity to ocean warming, acidification and coral reef loss occurring beyond 1.5°C ( [[#Cheung--2018b|Cheung et al., 2018b]] ; [[#Froehlich--2018|Froehlich et al., 2018]] ; [[#Free--2019|Free et al., 2019]] ; [[#Barnard--2021|Barnard et al., 2021]] ). Livelihoods in highly exposed locations, such as Small Island Developing States, low-lying coastal areas, arid or semiarid regions, the Arctic, and urban informal settlements or slums, are particularly vulnerable ( [[#Ford--2015c|Ford et al., 2015c]] ; [[#Hagenlocher--2018|Hagenlocher et al., 2018]] ; [[#Ahmadalipour--2019|Ahmadalipour et al., 2019]] ; [[#Tamura--2019|Tamura et al., 2019]] ). Within populations, the poor, women, children, the elderly and Indigenous populations are especially vulnerable due to a combination of factors, including gendered divisions of paid and/or unpaid labour, as well as barriers in access to information, skills, services or resources ( [[#Bose--2017|Bose, 2017]] ; [[#Thomas--2019b|Thomas et al., 2019b]] ; [[#Anderson--2020|Anderson and Singh, 2020]] ; [[#Adzawla--2021|Adzawla and Baumüller, 2021]] ) ( ''high confidence'' ). Future structural transformation could moderate risk severity by improving adaptive capacity, creating livelihoods in less climate-sensitive sectors, or by enabling sustainable migration to less climate-sensitive locations ( [[#Henderson--2017|Henderson et al., 2017]] ; [[#Roy--2018|Roy et al., 2018]] ). However, successful risk moderation would depend upon simultaneous avoidance of both climate-change-related and mitigation-related ( [[#Doelman--2019|Doelman et al., 2019]] ; [[#Fujimori--2019|Fujimori et al., 2019]] ; [[#Doelman--2020|Doelman et al., 2020]] ) or maladaptation-related risks ( [[#Magnan--2016|Magnan et al., 2016]] ; [[#Benveniste--2020|Benveniste et al., 2020]] ; [[#Schipper--2020|Schipper, 2020]] ).

Climate change also could increase income inequality between countries ( ''high confidence'' ) as well as within them ( ''medium evidence'' , ''high agreement'' ) resulting from and exacerbating impacts on aggregate economic activity, poverty and livelihoods. Increasing inequality implies larger impacts on the least well-off, threatens their ability to respond to climate hazards, compromises basic principles of fairness and established global development goals, and potentially threatens the functioning of society and long-term progress ( [[#Roe--2011|Roe and Siegel, 2011]] ; [[#Cingano--2014|Cingano, 2014]] ; [[#van%20der%20Weide--2018|van der Weide and Milanovic, 2018]] ). There is evidence that warming has slowed down the convergence in between-country income in recent decades ( [[#Diffenbaugh--2019|Diffenbaugh and Burke, 2019]] ). Future impacts may halt or even reverse this trend during this century owing to high sensitivity of developing economies ( [[#Burke--2015|Burke et al., 2015]] ; [[#Pretis--2018|Pretis et al., 2018]] ; [[#Baarsch--2020|Baarsch et al., 2020]] ), although projections depend as much or more on future socioeconomic development pathways and mitigation policies as on warming levels (Takakura et al., 2019; [[#Harding--2020|Harding et al., 2020]] ; [[#Taconet--2020|Taconet et al., 2020]] ). Within countries, studies that find adverse impacts on low-income groups imply an increase in inequality ( [[#Hallegatte--2017|Hallegatte and Rozenberg, 2017]] ; [[#Hsiang--2017|Hsiang et al., 2017]] ), although evidence for long-term climate impacts on within-country inequality at global scale remains limited.

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<span id="risk-to-human-health-rkr-e"></span>
===== 16.5.2.3.5 Risk to human health (RKR-E) =====

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This RKR includes (i) mortality from heat, and morbidity and mortality from (ii) vector-borne diseases and (iii) waterborne diseases. It builds on KRs identified primarily in [[IPCC:Wg2:Chapter:Chapter-7|Chapter 7]] and health risks in regional chapters.

A severe risk to health is the potential for a widespread, substantial worsening of health conditions due to climate change. We measure severity in terms of the magnitude of mortality and morbidity. We consider a severe mortality impact to be a sustained increase in the crude mortality rate (CMR) of more than about 2–4 deaths per 10,000 people yr –1 . This range of increase is consistent with current mortality impacts with substantial global effects, including traffic fatalities (CMR of 1.6/10,000 yr −1 ; [[#IHME--2019|IHME, 2019]] ) and the COVID-19 pandemic (CMR of 4/10,000 yr −1 , as of April 2021, expressed as an annualised rate; [[#Ritchie--2021|Ritchie et al., 2021]] ). We use these global rates as thresholds in all cases, recognising that they reflect substantial variation across regions and sub-populations (for other points of comparison, see [[#IHME--2019|IHME, 2019]] ). Morbidity impacts are measured in numbers of disease cases or hospital admissions. We find that severe health impacts are projected to occur for particular sub-populations and regions where vulnerability is currently high and is assumed to persist into the future; we focus our assessment on these cases. In other cases, literature is either inadequate or does not support severe outcomes.

# Risks of heat-related mortality would become severe at global and regional scales with high levels of warming and vulnerability ( ''medium confidence'' ). Under these conditions (SSP3–8.5), accounting for adaptation, heat mortality would increase the global CMR by up to 7/10,000 yr −1 by 2100 ( [[#Carleton--2020|Carleton et al., 2020]] ). For example, the USA would experience a CMR increase of 2–4/10,000 yr −1 by the end of the century (medium vulnerability without adaptation, and recent vulnerability with adaptation, respectively) ( [[#Weinberger--2017|Weinberger et al., 2017]] ; [[#Shindell--2020|Shindell et al., 2020]] ). Also assuming no adaptation and recent vulnerability, most populations of the world would experience an increase of 2–10 percentage points in the percentage of deaths attributable to heat by the end of the century (RCP8.5) (Vicedo-Cabrera, 2018a; Gasparrini, 2017). Harmful conditions for health are expected to increase in frequency and intensity over all land areas along with the rising temperatures in the coming decades ( [[#Pal--2016|Pal and Eltahir, 2016]] ; [[#Russo--2017|Russo et al., 2017]] ; [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ; [[#Saeed--2021|Saeed et al., 2021]] ; [[#Schwingshackl--2021|Schwingshackl et al., 2021]] ). Projections of exposure are an incomplete measure of risk but suggest the potential for severe impacts. For example, the percent of global population exposed to deadly heat stress would increase from today’s 30% to 48–74% by the end of the century depending on level of warming and population distribution ( [[#Mora--2017|Mora et al., 2017]] ). Projected impacts are larger if exposure and/or vulnerability increases due to ageing of the population or increased inequality ( [[#Weinberger--2017|Weinberger et al., 2017]] ; [[#Chen--2020a|Chen et al., 2020a]] ; [[#IPCC--2021|IPCC, 2021]] ) and with limited adaptation capacity (e.g., poor infrastructure, limited air conditioning, few medical and public health resources) (SM16.7.4) ( [[#Carleton--2020|Carleton et al., 2020]] ). Higher risks are also expected in urban areas owing to hazard amplification (i.e., urban heat island effect) and in highly dense settlements with other environmental hazards such as air pollution ( [[#Zhao--2018|Zhao et al., 2018]] ; [[#Sera--2019|Sera et al., 2019]] ).
# Risks of vector-borne disease would become severe with high warming and current vulnerability, concentrated in children and in sensitive regions ( ''medium confidence'' ). Severity is defined by regionally substantial numbers of additional malaria deaths, disease cases and episodic hospitalisation demands (for dengue).

With high warming, the CMR for malaria among children under the age of 1 year could increase by 5.2–10.1/10,000 yr −1 in Africa under current vulnerability levels. This estimate assumes a net increase of 70–130 million more people exposed to potential disease transmission due to climate change in a high-warming scenario (RCP8.5, end of century) ( [[#Caminade--2014|Caminade et al., 2014]] ; Colón- [[#González--2021|González et al., 2021]] ; [[#Ryan--2020|Ryan et al., 2020]] ), representing a 14–27% increase in the current population at risk ( [[#Ryan--2020|Ryan et al., 2020]] ), and assumes children under 1 year of age are facing the same crude mortality in the future as for the African region today ( [[#IHME--2019|IHME, 2019]] ). The largest increase is observed in Eastern Africa, where the population exposed could nearly double by 2080 ( [[#Ryan--2020|Ryan et al., 2020]] ) without accounting for population growth, driven mainly by changes among previously unexposed populations at higher altitude areas (Colón- [[#González--2021|González et al., 2021]] ). Actual future disease burden of malaria will be highly sensitive to regional socioeconomic development and the effectiveness of malaria intervention programs.

For dengue, with high warming and current levels of vulnerability there could be as much as a doubling of cases and hospital admissions per year globally, relative to today, driven by both warming and population growth. These estimates are derived by assuming similar relative incidence rates as today ( [[#Shepard--2016|Shepard et al., 2016]] ) combined with projections of a more than doubling of the population exposed to potential disease transmission by the end of the century in a high-warming scenario (RCP8.5), although much of this increase is driven by population growth ( [[#Colón-González--2018|Colón-González et al., 2018]] ; [[#Monaghan--2018|Monaghan et al., 2018]] ; [[#Messina--2019|Messina et al., 2019]] ). There are around 3 billion people exposed to dengue today.

# Climate change would lead to severe risks of morbidity and mortality caused by waterborne diseases, particularly for diarrhoea in children in many lower- and middle-income countries (LMICs) and where vulnerability remains high ( ''medium confidence'' ). The global CMR for diarrhoea is 1.98 for all ages, but varies by region and age group, reaching as high as 53 for &lt;1-year-olds in Africa ( [[#IHME--2019|IHME, 2019]] ). In these vulnerable populations, even a small percentage increase can lead to substantial additional morbidity and mortality. For example, assuming no change in vulnerability or population, an increase in diarrhoea mortality of only 5% over 2019 baseline rates would create a severe risk (CMR of 2.0) for children under the age of 1 in the World Health Organization (WHO) Africa (AFRO) region. This percent increase due to climate change is plausible since diarrhoea incidence increases of 7% (95% confidence interval 3–10%) are associated with a 1°C increase in ambient temperature ( [[#WHO--2014|WHO, 2014]] ; [[#Carlton--2016|Carlton et al., 2016]] ), and diarrhoea is positively associated with heavy rainfall and flooding events ( [[#Levy--2016|Levy et al., 2016]] ), expected in some regions (WGI). Assuming vulnerability remains the same as today, mortality and morbidity rates would increase equivalently.

However, risks will be highly dependent on development trajectories, given that waterborne disease transmission is exacerbated by lack of clean drinking water and sanitation systems, inadequate food safety and hygiene conditions, lack of flood and drought protections, and interactions with other risks such as cholera outbreaks, food insecurity and infrastructure damage. Climate change threatens the progress that has been made towards reducing the burden of diarrhoea. For example, in Sub-Saharan Africa, while overall diarrhoea rates are expected to continue to decline (GBD 2016 Diarrhoeal Disease Collaborators, 2018), warming in 2030 (relative to the late 20th century) is projected to lead to diarrhoeal deaths in children under 15 equivalent to a CMR increase of 0.56/10,000 yr −1 (based on population projections for the region and age group; UN, 2020; [[#WHO--2014|WHO, 2014]] ). In China, by 2030, climate change could delay progress towards reducing waterborne disease burden by 8–85 months ( [[#Hodges--2014|Hodges et al., 2014]] ).

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===== 16.5.2.3.6 Risk to food security (RKR-F) =====

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Climate change affects food security primarily through impacts on food production, including crops, livestock and fisheries, as well as disruptions in food supply chains, linked to global warming, drought, flooding, precipitation variability and weather extremes ( [[#Myers--2017|Myers et al., 2017]] ; [[#FAO--2018|FAO et al., 2018]] ; [[#Mbow--2019|Mbow et al., 2019]] ). This RKR builds on Key Risks identified primarily in the Food, Fibre and Other Ecosystem Products Chapter, some sectoral (Health), and regional (Africa, Australasia, Central and South America, North America) chapters, as well as SR15, SRCCL and SROCC.

The severity of the risk to food security is defined here using a combination of criteria including the magnitude and likelihood of adverse consequences, affecting tens to hundreds of millions of people, timing of the risk and ability to respond to the risk. In this assessment, we use the number of undernourished people as a proxy outcome of these dimensions and their multiple interactions.

Climate change will pose severe risks in terms of increasing the number of undernourished people, affecting tens to hundreds of million people under High vulnerability and High warming, particularly among low-income populations in developing countries ( ''high confidence'' ). Extreme weather events will increase risks of undernutrition even on a regional scale, via spikes in food price and reduced income ( ''high confidence'' ) ( [[#FAO--2018|FAO et al., 2018]] , Hickey and Unwin, 2020; [[#Mbow--2019|Mbow et al., 2019]] ). The timing of these impacts and our ability to respond to them vary based on the level of GHG emissions and Shared Socioeconomic Pathways (SSP).. Under a low vulnerability development pathway (SSP1), climate change starts posing a moderate risk to food security above 1°C of global warming (i.e., impacts become detectable and attributable to climate-related factors), while beyond 2.5°C the risk becomes high (widespread impacts on larger numbers or proportion of population or area, but with the potential to adapt or recover) ( [[#Hurlbert--2019|Hurlbert et al., 2019]] ). Under high vulnerability–high warming scenario (i.e., SSP3-RCP6.0), up to 183 million additional people are projected to become undernourished in low-income countries owing to climate change by 2050 ( [[#Mbow--2019|Mbow et al., 2019]] ). Climate-related changes in food availability and diet quality are estimated to result in a crude mortality rate of about 54 deaths per million people with about 2°C warming by 2050 (SSP2, RCP8.5), most of them projected to occur in South and East Asia (67–231 deaths per million depending on the country) ( [[#Springmann--2016|Springmann et al., 2016]] ). In a medium vulnerability–high warming scenario (SSP2, RCP6.0), [[#Hasegawa--2018|Hasegawa et al. (2018)]] project that the number of undernourished people increases by 24 million in 2050, compared with outcomes without climate change and accounting for the CO 2 fertilisation effect. This number increases by around 78 million in a low-warming scenario (RCP2.6) accounting for the impacts of both climate change and mitigation policies. Caveats to these modelling studies are that most models (crop models in particular) are designed for long-term change in climate but not suited to project the impacts of short-term extreme events. The inclusion of adaptation measures into modelling estimates remains selective and partial.

Climate change risks of micronutrient deficiency will become severe in high-vulnerability development pathways and in the absence of societal adaptation, leading to hundreds of millions of additional people lacking key nutrients for atmospheric CO 2 levels above 500 ppm ( ''high confidence'' ) ( [[#Myers--2017|Myers et al., 2017]] ; [[#Nelson--2018|Nelson et al., 2018]] ; [[#Mbow--2019|Mbow et al., 2019]] ). For example, concentration of many micronutrients (e.g., phosphorus, potassium, calcium, sulphur, magnesium, iron, zinc, copper and manganese) can decrease by 5–10% under atmospheric CO 2 concentrations of 690 ppm (3.5°C warming). The decline in zinc content is projected to lead to an additional 150–220 million people affected by zinc deficiency with increases in existing deficiencies in more than 1 billion people ( [[#Myers--2017|Myers et al., 2017]] ). Similarly, decrease in protein and micronutrient content in rice due to a higher CO 2 concentration (568–590 ppm) can lead to 600 million people with rice as a staple at risk of micronutrient deficiency by 2050 ( [[#Zhu--2018|Zhu et al., 2018]] ). Additionally, the impact on protein content of increased CO 2 concentration (&gt;500 ppm) can lead an additional 150 million people with protein deficiency by 2050 (within the total of 1.4 billion people with protein deficiency) in comparison with the scenario without increased CO 2 concentration ( [[#Medek--2017|Medek et al., 2017]] ).

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===== 16.5.2.3.7 Risk to water security (RKR-G) =====

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Water security encompasses multiple dimensions: water for sanitation and hygiene, food production, economic activities, ecosystems, water-induced disasters, and use of water for cultural purposes (Chapter 4; Box 4.1; [[IPCC:Wg2:Chapter:Chapter-4#4.6.1|Section 4.6.1]] ). Water security risks are a combination of water-related hazards such as floods, droughts and water quality deterioration, and exposure of vulnerable groups exposed to too little, too much or contaminated water. Reasons for these can include both environmental conditions and issues of safety and access influenced by effectiveness of water governance ( [[#Sadoff--2020|Sadoff et al., 2020]] ). These are manifest through loss of lives, property, livelihoods and culture, and impacts on human health and nutrition, ecosystems and water-related conflicts which in turn can drive forced human displacement.

This RKR focuses on three types of risks with the potential to become severe: those associated with water scarcity, those driven by water-related disasters, and those impacting indigenous and traditional cultures and ways of life. Risk to water security constitutes a potentially severe risk because climate change could impact the hydrologic cycle in ways that would lead to substantial consequences for the health, livelihoods, property and cultures of large numbers of people. For those associated with water scarcity, ‘severe’ refers to magnitude (number of people in areas where water scarcity falls below recognised thresholds for adequate water supply per capita), along with the likelihood of unforeseen increases in water scarcity that outpace the ability to prepare for the increased risk by putting in place new large-scale infrastructure within the required time scale. For those associated with extreme events, ‘severe’ refers to magnitude (numbers of people affected, including deaths, physical health impacts including disease, mental health impacts, loss of livelihoods, loss of or damage to property) and timing (e.g., events coinciding with other stresses, e.g., a pandemic occurring at a time when local infrastructures are weakened by an extreme weather event). Important water-related extreme events include river flooding caused by heavy and/or prolonged rainfall, glacial lake outburst floods, and droughts. For those impacting cultures, ‘severe’ refers to the loss of key aspects of traditional ways of life. This includes consequences of the above two KRs.

Risks associated with water scarcity have the potential to become severe based on projections of large numbers of people becoming exposed to low levels of water availability per person, where ‘water availability’ includes fresh water in the landscape, including soil moisture and streamflows, available for all uses including agriculture as a dominant sector. Approximately 1.6 billion people currently experience ‘chronic’ water scarcity, defined as the availability of less than 1000 m 3 of renewable sources of fresh water per person per year ( [[#Gosling--2016|Gosling and Arnell, 2016]] ). In this context, we define a severe outcome as an additional 1 billion people experiencing ‘chronic’ water scarcity, relating to all uses of water, representing an increase of a magnitude comparable to current levels. The global number of people experiencing chronic water scarcity is projected to increase by approximately 800 million to 3 billion for 2°C global warming, and up to approximately 4 billion for 4°C global warming, considering the effects of climate change alone, with a 9 billion population ( [[#Gosling--2016|Gosling and Arnell, 2016]] ). Severe outcomes are projected to occur even with no changes in exposure: present-day exposure is defined here as ‘medium’ since either an increase or decrease in exposure could be possible. Vulnerability is not quantified in the literature assessed here, so in this assessment it is considered that severe outcomes could occur with present-day levels of vulnerability, again defined here as ‘medium’. Particularly severe outcomes (i.e., the high end of these ranges) are driven by regional patterns of climate change bringing severe reductions in precipitation and/or high levels of evapotranspiration in the most highly populated regions, leading to very substantial reductions in water availability compared with demand. There is strong consensus across models that water scarcity is projected to increase across substantial parts of the world even though projections disagree on which specific areas would see this impact. Moreover, a projected decrease in water scarcity in some regions does not prevent the increase in water scarcity in other regions becoming severe. Hence there is ''high confidence'' that risks to water scarcity have the potential to become severe due to climate change. Consequences of water scarcity include potential competition and conflicts between water users ( [[#Vanham--2018|Vanham et al., 2018]] ), damaging livelihoods, hindering socioeconomic development and reducing human well-being, for example through malnutrition resulting from inadequate water supplies leading to long-term health impacts such as child stunting ( [[#Cooper--2019|Cooper et al., 2019]] ). The avoidance of these consequences at high levels of water scarcity would require transformational adaptations including large-scale interventions such as dams and water transfer infrastructure ( [[#Greve--2018|Greve et al., 2018]] ). Since these require many years or even decades for planning and construction, and are also costly and irreversible and can potentially lead to lock-in and maladaptation, the potential for inadequate policy decisions made in the context of high uncertainties in regional climate changes brings the risk of a shortfall in adaptation. Around 2050, at approximately 2°C global warming, the risk of a substantial adaptation shortfall and hence severe outcomes for water scarcity have a relatively high likelihood across large parts of the southern USA and Mexico, northern Africa, parts of the Middle-East, northern China, and southern Australia, as well as many parts of Northwest India and Pakistan ( [[#Greve--2018|Greve et al., 2018]] ).

Risks associated with water-related extreme events and disasters have the potential to become severe based on projections of large numbers of people or high values of assets being affected. The risks to people from disasters can often only be quantified in terms of the hazard and exposure (the number of people affected), rather than the full consequences such as number of deaths, injuries or other health outcomes, as these often depend on complex or unpredictable factors such as the effectiveness of emergency and humanitarian responses or the access to healthcare. With approximately 50 million people per year currently affected by flooding ( [[#Alfieri--2017|Alfieri et al., 2017]] ), we define severe outcomes as more than 100 million people affected by flooding. At 2°C global warming, between approximately 50 million and 150 million people are projected to be affected by flooding, with figures rising to 110 million to 330 million at 4°C global warming. These projections assume present-day population and no additional adaptation, so no changes in exposure. Increased flood risk is projected by the WHO to lead to an additional 48,000 deaths of children under 15 years due to diarrhoea by 2030, with Sub-Saharan Africa impacted the most ( [[#WHO--2014|WHO, 2014]] ). Other consequences of floods that already occur include deaths by drowning, loss of access to fresh water, vector-borne diseases, mental health impacts, loss of livelihoods and loss of or damage to property. Many of these consequences depend on the vulnerability of individuals, households or communities to flooding impacts, for example through the presence or absence of measures to safeguard health and livelihoods, such as through infrastructure services, insurance or community support. The risks associated with these consequences could increase if there were no local adaptations to counter the effect of increased levels of hazard by reducing exposure and/or vulnerability. Climate-related changes to extreme events that would lead to these severe outcomes include increased frequency and/or magnitude of river floods of flash floods due to heavy or long-lasting precipitation, rapid snowmelt, or catastrophic failure of glacial lake moraine dams. These climate conditions are projected to increase with global warming.

Risks to cultural uses of water can become severe if there is permanent loss of aspects of communities’ cultures due to changes in water, including loss of areas of ice or snow with spiritual meanings, loss of culturally important places of access to such places, and loss of culturally important subsistence practices including by Indigenous People (Chapter 4). This includes mountain regions where changes in the cryosphere are having profound impacts (Cross-Chapter Paper 5). In these cases, severe outcomes would be defined locally rather than globally. Communities that lost a dominant environmental characteristic deeply associated with its cultural identity would be considered to be severely impacted. For example, due to the central role that travel on sea ice plays in the life of Inuit communities, providing freedom and mental well-being, loss of sea ice can be argued to represent environmental dispossession of these communities ( [[#Durkalec--2015|Durkalec et al., 2015]] ). Traditional ways of life are therefore threatened, and resulting changes would be transformative rather than adaptive. Similarly, changes in streamflow affecting the availability of species for traditional hunting can also negatively impact Indigenous communities (Norton-Smith et al.). Such changes are already being seen at current levels of warming, but studies remain somewhat limited in number, so this assessment is assigned ''medium confidence'' because of ''medium evidence'' and medium agreement. WGI conclude that it is ''virtually certain'' that further warming will lead to further reductions in Northern Hemisphere snow cover, and mass loss in individual glacier regions is projected to be between approximately 30% and 100% by 2100 under high-warming scenarios (Chapter 4). Streamflows are projected to change in most major river basins worldwide by several tens of percent at 4°C global warming (Chapter 4).

There is strong potential for increases in water scarcity, flooding, loss of snow and ice and changes in water bodies to lead to severe outcomes such as deaths from water-related diseases, drowning and starvation, long-term health impacts arising from malnutrition and diseases, loss of property, loss of existence or access to places of cultural significance, loss of livelihoods and loss of aspects of culture especially for Indigenous People with traditional lifestyles. The numbers of people affected are projected to range from hundreds of millions to several billion, depending on the level of global warming and socioeconomic futures. A key aspect of the risk is the high uncertainty in future regional precipitation changes in many regions of high vulnerability, including the potential for large and highly impactful changes, for which it may not be possible to provide adaptation measures before they become needed, leading to a high likelihood of adaptation deficits.

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===== 16.5.2.3.8 Risks to peace and to human mobility (RKR-H) =====

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This RKR includes risks to peace within and among societies from armed conflict as well as risks to human mobility, epitomised by involuntary migration and displacement within and across state borders and involuntary immobility. Breakdown of peace and the inability of people to choose to move or stay challenge core elements of human security ( [[#Adger--2014|Adger et al., 2014]] ). Risks to peace also inform the agency and viability of mobility decisions. However, evidence does not indicate that human mobility constitutes a general risk to peace.

Breakdown of peace, materialised as overt or covert violence across social and spatial scales, constitutes a key risk because of its potential to cause widespread loss of life, livelihood and well-being. Such impacts are considered severe if they result in at least 1000 excess battle-related deaths in a country in a year. This threshold is consistent with the conventional definition of war ( [[#Pettersson--2020|Pettersson and Öberg, 2020]] ). However, because armed conflict routinely causes significant material destruction, triggers mass displacement, threatens health and food security, and undermines economic activity and living standards ( [[#Baumann--2016|Baumann and Kuemmerle, 2016]] ; [[#FAO--2017|FAO et al., 2017]] ; [[#de%20Waal--2018|de Waal, 2018]] ), risks to peace can be considered severe also when conflict has cascading effects on other aspects of well-being and amplifies vulnerability to other RKRs. Beyond the magnitude of such impacts, the rapidity with which armed conflict can escalate and the challenges of ending violence once it has broken out imply potentially very limited time and ability to respond for populations at risk.

Mobility is a universal strategy for pursuing well-being and managing household risks ( [[IPCC:Wg2:Chapter:Chapter-7#7.2.6|Section 7.2.6]] ; Cross-Chapter Box MIGRATE in Chapter 7, [[#UN--2018|UN, 2018]] ) and, where it occurs in a safe and orderly fashion, can reduce social inequality and facilitate sustainable development (Franco [[#Gavonel--2021|Gavonel et al., 2021]] ). Involuntary mobility constitutes a key risk because it implies reduced human agency with high potential for significant economic losses and non-material costs, an unequal gender burden, and amplified vulnerability to other RKRs ( [[#Schwerdtle--2018|Schwerdtle et al., 2018]] ; [[#Adger--2020|Adger et al., 2020]] ; [[#Maharjan--2020|Maharjan et al., 2020]] ; [[#Piggott-McKellar--2020|Piggott-McKellar et al., 2020]] ). Climate change also may erode or overwhelm human capacity to use mobility as a coping strategy, producing involuntarily immobile populations ( [[#Adams--2016|Adams, 2016]] ). A severe impact is when a large share of an affected population is forcibly displaced or prevented from moving, relative to normal mobility patterns, at local to global scale. However, because mobility may be a favourable mechanism for reducing risk or an adverse outcome of risk, depending on the circumstances under which it occurs, it is not possible to specify a simple quantitative threshold for when impacts become severe.

Complex causal pathways and lack of long-term projection studies presently prevent making confident quantitative judgements about how risks to peace and human mobility will materialise in response to specific warming levels, development pathways and adaptation scenarios. Literature concludes with ''medium confidence'' that risks to peace will increase with warming, with the largest impacts expected in weather-sensitive communities with low resilience to climate extremes and high prevalence of underlying risk factors ( [[#Theisen--2017|Theisen, 2017]] ; [[#Busby--2018|Busby, 2018]] ; [[#Koubi--2019|Koubi, 2019]] ; [[#von%20Uexkull--2021|von Uexkull and Buhaug, 2021]] ). However, climate-driven impacts on societies will depend critically on future political and socioeconomic development trajectories ( ''limited evidence'' , ''high agreement'' ), suggesting that risks due to climate change are relevant primarily for highly vulnerable populations and for pessimistic development scenarios. Overall risks to peace may decline despite warming if non-climatic determinants are reduced sufficiently in the future.

Regular human mobility will continue regardless of climate change, but mobility-related risks will increase with warming, notably in densely populated hazard-prone regions, in small islands and low-lying coastal zones, and among populations with limited coping capacity (RKR-A; Section [https://www.ipcc.ch/chapter/16#CCP2.2 CCP2.2.2] ; Chapter 7) ( ''high confidence'' ). Such risks can become severe even with limited levels of warming for populations with low adaptive capacity and whose settlements and livelihoods are critically sensitive to environmental conditions ( ''medium evidence'' , ''high agreement'' ). Likewise, risk of involuntary immobility could become severe for highly vulnerable populations with limited resources, even with moderate levels of warming ( ''limited evidence'' , ''high agreement'' ). Critically, population growth and shifting exposure will interact with warming to shape these risks ( [[#Davis--2018|Davis et al., 2018]] ; [[#Hauer--2020|Hauer et al., 2020]] ; [[#Robinson--2020a|Robinson, 2020a]] ). Although climate-driven human mobility generally does not increase risks to peace ( ''medium confidence'' ), armed conflict is a major driver of forced displacement ( ''high confidence'' ).

Expert elicitation estimates that 4°C warming above pre-industrial levels will have severe and widespread effects on armed conflict with 26% probability, assuming no change from present levels in non-climatic drivers ( [[#Mach--2019|Mach et al., 2019]] ). That judgement refers to impacts that exceed the threshold for severity considered here, suggesting that global warming of 4°C would produce severe risks to peace under present societal conditions ( ''low confidence'' ). Future risks to peace will remain strongly influenced by socioeconomic development ( [[#Hegre--2016|Hegre et al., 2016]] ). A study of Sub-Saharan Africa that accounts for both temperature and socioeconomic changes, 2015–2065, concludes that determinants other than rising temperatures, notably quality of governance, will remain most influential in shaping overall levels of violence even in the high-warming RCP8.5 scenario ( [[#Witmer--2017|Witmer et al., 2017]] ).

A larger empirical literature offers indirect evidence that climate change may produce severe risks to peace within this century by demonstrating how climate variability and extremes affect contemporary conflict dynamics, especially in contexts marked by low economic development, high economic dependence on climate-sensitive activities, high or increasing social marginalisation, and fragile governance ( ''medium confidence'' ) (Sections 7.2.7, 16.2, [[#Schleussner--2016a|Schleussner et al., 2016a]] ; [[#Von%20Uexkull--2016|Von Uexkull et al., 2016]] ; [[#Busby--2018|Busby, 2018]] ; [[#Harari--2018|Harari and Ferrara, 2018]] ; [[#Ide--2020|Ide et al., 2020]] ; [[#Scartozzi--2020|Scartozzi, 2020]] ).

Climatic risks interact with economic, political and social drivers to create risks to human mobility both directly (through the threat of physical harm and destruction of property and infrastructure) and indirectly (via adverse impacts on livelihood and well-being). Extreme weather events are leading causes of forced displacement (Cross-Chapter Box MIGRATE in Chapter 7, [[#IDMC--2020|IDMC, 2020]] ). Projected increases in the frequency and severity of extreme events ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ) in combination with future population growth in hazard-prone regions (e.g., [[#Merkens--2016|Merkens et al., 2016]] ) suggest that risks to mobility will increase in response to future global warming ( [[#Robalino--2015|Robalino et al., 2015]] ; [[#Davis--2018|Davis et al., 2018]] ; [[#Rigaud--2018|Rigaud et al., 2018]] ). For example, moving from RCP2.6 to RCP8.5 (entailing ~0.5°C additional global warming by 2050) is projected to increase internal migration by 2050 from 51 [31–72] million to 118 [92–143] million people across South Asia, Latin America and Africa ( [[#Rigaud--2018|Rigaud et al., 2018]] ), although those estimates principally comprise migrants, whose decisions are also informed by non-climatic drivers, rather than involuntarily displaced people. Global levels of flood displacement are estimated to increase by 50% with each 1°C warming ( [[#Kam--2021|Kam et al., 2021]] ). Should future warming reduce adaptation options for vulnerable populations ( [[#16.4|Section 16.4]] ), a consequence may be higher levels of involuntary migration and immobility ( [[#Grecequet--2017|Grecequet et al., 2017]] ; [[#Otto--2017|Otto et al., 2017]] ). There is little evidence that climate-driven mobility negatively affects peace ( [[#Brzoska--2016|Brzoska and]] [[#Fröhlich--2016|Fröhlich, 2016]] ; [[#Burrows--2016|Burrows and Kinney, 2016]] ; [[#Freeman--2017|Freeman, 2017]] ; [[#Petrova--2021|Petrova, 2021]] ).

There is ''high agreement'' that even moderate levels of future SLR will severely amplify involuntary migration and displacement in small islands and densely populated low-lying coastal areas in the absence of appropriate adaptive responses ( ''high confidence'' ) ( [[#Hauer--2017|Hauer, 2017]] ; [[#IPCC--2019b|IPCC, 2019b]] ; [[#Hauer--2020|Hauer et al., 2020]] ; [[#McMichael--2020|McMichael et al., 2020]] , Sections 15.3.4, 16.4). In some contexts, climate change also may accelerate migration towards high-exposure coastal areas ( [[#Bell--2021|Bell et al., 2021]] ). Under a high-emissions RCP8.5 scenario (global median 0.7 m SLR by 2100), the number of people exposed to annual coastal flooding may more than double by 2100 compared with present numbers ( [[#Kulp--2019|Kulp and Strauss, 2019]] ). In the USA alone, SLR of 0.9 m could potentially put 4.2 million people at risk of inundation by the end of this century ( [[#Hauer--2017|Hauer, 2017]] ). However, number of people exposed to SLR does not evenly translate to forcibly displaced populations ( [[#Hauer--2020|Hauer et al., 2020]] ). Ascertaining how many people will move forcibly or as an adaptive response to SLR is inherently challenging because of the complex and highly individual nature of migration decisions ( [[#Black--2013|Black et al., 2013]] ; [[#Boas--2019|Boas et al., 2019]] ; [[#Piguet--2019|Piguet, 2019]] ; [[#Bell--2021|Bell et al., 2021]] ). Implications of climate change for risks to human mobility across borders are even harder to quantify and highly uncertain, due to unknown developments in legal and political conditions that govern international migration ( [[#McLeman--2019|McLeman, 2019]] ; [[#Wrathall--2019|Wrathall et al., 2019]] ).

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==== 16.5.2.4 Synthesis of the Assessment of Representative Key Risks ====

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Figure 16.10 provides a synthesis of the RKRs and the conditions that lead to severe risks over the course of the 21st century, as assessed in Sections 16.5.2.3.1–16.5.2.3.8 (see Table SM16.14 for further description). It identifies sets of conditions—defined by levels of warming, exposure/vulnerability and adaptation—that would produce severe risk with a particular level of confidence. The risks are of two scopes: broadly applicable, meaning that the risks described by a particular KR or RKR would be severe pervasively and even globally; and specific, meaning that these risks would apply to particular areas, sectors or groups of people.

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'''Figure 16.10 |''' '''Synthesis of the severity conditions for Representative Key Risks by the end of this century.''' The figure does not aim to describe severity conditions exhaustively for each RKR, but rather to illustrate the risks highlighted in this report (Sections 16.5.2.3.1 to 16.5.2.3.8). Coloured circles represent the levels of warming (climate), exposure/vulnerability, and adaptation that would lead to severe risks for particular key risks and RKRs. Each set of three circles represents a combination of conditions that would lead to severe risk with a particular level of confidence, indicated by the number of black dots to the right of the set, and for a particular scope, indicated by the number of stars to the left of the set. The two scopes are ‘broadly applicable’, meaning applicable pervasively and even globally, and ‘specific’, meaning applicable to particular areas, sectors or groups of people. Details of confidence levels and scopes can be found in [[#16.5.2.3|Section 16.5.2.3]] . In terms of severity condition levels ( [[#16.5.2.3|Section 16.5.2.3]] ), for warming levels (coloured circles labelled ‘C’ in the figure), High refers to climate outcomes consistent with RCP8.5 or higher, Low refers to climate outcomes consistent with RCP2.6 or lower, and Medium refers to intermediary climate scenarios. Exposure-Vulnerability levels are determined by the RKR teams relative to the range of future conditions considered in the literature. For Adaptation, High refers to near maximum potential and Low refers to the continuation of today’s trends. Despite being intertwined in reality, Exposure-Vulnerability and Adaptation conditions are distinguished to help understand their respective contributions to risk severity.

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===== Five main messages arise from this synthesis: =====

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Severe risk is rarely driven by a single determinant (warming, exposure/vulnerability, adaptation), but rather by a combination of conditions that jointly produce the level of pervasiveness of consequences, irreversibility, thresholds, cascading effects, likelihood of consequences, temporal characteristics of risk and the systems’ ability to respond ( ''medium'' to ''high confidence'' ). In other words, climate risk is not a matter of changing CIDs only, but of the confrontation between changing CIDs and changing socio-ecological conditions.

In most of the RKRs, severe risk for broadly applicable situations requires high levels of warming or exposure/vulnerability, or low adaptation. In many cases, it is associated with several of these conditions occurring simultaneously (e.g., high warming and high vulnerability). Examples include low-lying coastal areas (RKR-A; ''medium confidence'' ), loss of livelihoods (RKR-D; ''medium confidence'' ) or armed conflicts (RKR-H; ''low confidence'' ).

High warming and exposure/vulnerability combined with low adaptation is, however, not necessarily required to lead to severe risk, and various other sets of conditions can lead to such an outcome. For example:

''Without high levels of warming'' . T his is especially the case for terrestrial and marine ecosystems (RKR-B) and water security (RKR-G) for which even medium to low levels of warming will generate severe risk, depending on the processes considered (e.g., mass population-level mortality and ecological disruption for ecosystems). This is also the case when more specific situations are considered, for example in the case of (in)voluntary mobility of vulnerable populations with limited resources (RKR-H), and for some critical infrastructure in already highly exposed and vulnerable contexts (RKR-C).

''With high levels of adaptation.'' H igh levels of adaptation will not necessarily avoid severe risk, as is illustrated by the cases of coral-dependent and arctic coastal communities (RKR-A), some terrestrial and marine ecosystems (RKR-B), and water scarcity and the cultural uses of water (RKR-G).

All RKR assessments indicate that risks are higher in high-vulnerability development pathways, and in some cases high vulnerability can occur in high-income societies. Examples include the possibility of increasing coastal settlement and the location of critical infrastructure in highly exposed locations (RKR-A, RKR-C), including to floods (RKR-G) and risks to terrestrial and marine ecosystems (RKR-B). The assessment therefore shows that, depending on socioeconomic trends especially in terms of equity, social justice and income sustainability, as well as on the ability to shift towards more climate-resilient economic and settlement systems (e.g., at the coast), higher-income societies also are at serious risk of being substantially affected in the decades to century to come.

In terms of the time frames, most of the RKRs conclude that severe risks to many dimensions (ecosystems, health, etc.) are expected to occur by the end of the 21st century and across the globe. Some RKRs, however, highlight that severe risk could occur far earlier, for example as soon as a warming level of 1.5°C or 2°C is reached, which means potentially well before mid-century ( [[#IPCC--2021|IPCC, 2021]] ). In some cases, risks are already considered severe, for example after major climatic events such as tropical storms (RKR-A).

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