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

=== 16.5.3 Variation of Key Risks across Levels of Global Warming, Exposure and Vulnerability, and Adaptation ===

<div id="h2-16-siblings" class="h2-siblings"></div>

This section builds on Sections 16.5.1 and 16.5.2 as well as on additional literature to illustrate how consequences associated with KRs and RKRs are projected to vary with three types of determinants: global average warming level, as a proxy for associated changes in climate hazards (CIDs, [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ); socioeconomic development pathway, as a means of capturing alternative future exposure and vulnerability conditions; and level of adaptation to reflect the extent to which successful adaptation is implemented. While these three dimensions are partly intertwined—for example, warming and adaptation scenarios are constrained by development pathways (Chapter 18)—this section assesses the influence of each dimension separately (Sections 16.5.3.2–16.5.3.4) to highlight how sensitivity varies across these dimensions for different KRs and RKRs. We then bring the dimensions together in an illustrative example (large deltas; [[#16.5.3|Section 16.5.3.5]] ).

<div id="16.5.3.1" class="h3-container"></div>

<span id="warming-level-including-risks-avoided-by-mitigation"></span>
==== 16.5.3.1 Warming Level, Including Risks Avoided by Mitigation ====

<div id="h3-36-siblings" class="h3-siblings"></div>

Studies illustrating sensitivity to warming level typically do so by contrasting projected impacts for the same socioeconomic conditions but different climate pathways or temperature levels, often based on Representative Concentration Pathways (RCPs) ( [[#van%20Vuuren--2014|van Vuuren and Carter, 2014]] ). We refer to future climate conditions either based on their global average warming level or as a ‘high warming’ scenario (based on RCP8.5), medium warming (RCP4.5 or RCP6.0) or low warming (RCP2.6 or 1.5°C scenarios). Because some of these scenarios assume no or minimal mitigation (RCP8.5, RCP6.0) while others do (RCP4.5, RCP2.6), differences in outcomes between them reflect risks avoided by mitigation (assuming consistent socioeconomic assumptions).

Some ecological risks (Chapter 2) are particularly sensitive to warming. For example, warm-water coral reefs are already experiencing High risk levels and are expected to face Very High risks under 1.5°C of global warming ( [[#Hoegh-Guldberg--2018a|Hoegh-Guldberg et al., 2018a]] ; [[#Bindoff--2019|Bindoff et al., 2019]] ). Some societal risks, such as human mortality due to extreme heat, also are sensitive to warming. A medium-warming scenario (relative to high warming) reduces projected global average mortality due to heat from seven deaths per 10,000 people yr –1 (7/10,000 yr −1 ) by 2100 to ~1/10,000 yr −1 , assuming high-vulnerability societal conditions ( [[#Carleton--2020|Carleton et al., 2020]] ). At the national level, without considering adaptation, reductions in a broader measure of mortality are projected across a range of countries including Colombia, the Philippines, and several in Europe ( [[#Guo--2018|Guo et al., 2018]] ), and exposure of the US population to high-mortality heatwaves is reduced by nearly half ( [[#Anderson--2018a|Anderson et al., 2018a]] ). Without considering changes in exposure or vulnerability, warming of 1.5–2°C (compared with 4–5°C) reduces global mortality impacts from an increase of 2.1–13.0% to 0.1–2.2% ( [[#Gasparrini--2017|Gasparrini et al., 2017]] ; [[#Vicedo-Cabrera--2018a|Vicedo-Cabrera et al., 2018a]] ) and impacts in China from up to 4/10,000 yr −1 ( [[#Weinberger--2017|Weinberger et al., 2017]] ) to 0.3–0.5/10,000 yr −1 ( [[#Wang--2019|Wang and Hijmans, 2019]] ).

A low-warming scenario (relative to high warming) reduces aggregate economic impacts from around 7% of global GDP to less than 1% (Takakura et al., 2019), and changes impacts on the number of people suffering from hunger from an increase (by 7–55 million) to a decrease (by up to 6 million) ( [[#Janssens--2020|Janssens et al., 2020]] ). Low versus high warming also reduces the coastal population at risk of flooding due to SLR from tripling by 2100 (relative to today) to doubling ( [[#Kulp--2019|Kulp and Strauss, 2019]] , [[#16.5.2.3|Section 16.5.2.3.2]] ). The SROCC estimates that SLR risks are reduced from Moderate-to-High to Moderate for large tropical agricultural deltas and resource-rich megacities, and from High and Very High to Moderate-to-High for Arctic human communities and urban atoll islands, respectively ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ).

Higher levels of warming are projected to also generate higher income inequality between countries (e.g., [[#Pretis--2018|Pretis et al., 2018]] ; Takakura et al., 2019) as well as within them ( [[#Hallegatte--2016|Hallegatte et al., 2016]] ) even though other drivers will be more important ( [[#16.5.2.3.5|Section 16.5.2.3.5]] ). Similarly, climate and weather events are expected to play an increasing role in shaping risks to peace ( ''limited evidence, medium agreement)'' and migration ( ''medium evidence, high agreement'' ) in the future, but uncertainty is high due to complex causal pathways and non-climate factors likely dominate outcomes ( [[#16.5.2.3.8|Section 16.5.2.3.8]] ). There is ''high agreement'' that future SLR will amplify levels of forced migration from small islands and low-lying coastal areas in the absence of appropriate adaptive responses ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ).

A synthesis of risk assessments in the recent IPCC Special Reports ( [[#Magnan--2021|Magnan et al., 2021]] ) concludes that an integrated measure of today’s global climate risk level will increase by the end of this century by two- to four-fold under low and high warming, respectively (based on aggregated scores developed in the study). An additional comparison of risk levels under +1.5°C and +2°C suggests that every additional 0.5°C of global warming will increase the risk level by about a third.

<div id="16.5.3.2" class="h3-container"></div>

<span id="exposure-and-vulnerability-trends"></span>
==== 16.5.3.2 Exposure and Vulnerability Trends ====

<div id="h3-37-siblings" class="h3-siblings"></div>

Development pathways describe plausible alternative futures of societal change and are critical to future risks because they affect outcomes of concern both through non-climate and climate-related channels ( ''very high confidence'' ).

Studies illustrating sensitivity to development pathways typically do so by contrasting projected impacts for the same climate pathway or temperature level but different levels of socioeconomic exposure and vulnerability, for example based on SSPs ( [[#O’Neill--2014|O’Neill et al., 2014]] ; [[#Van%20Vuuren--2014|Van Vuuren et al., 2014]] ). Or, they infer sensitivity to future development pathways based on differences in impacts across current populations with different levels of exposure or vulnerability. We refer to future conditions based on SSPs 1 or 5 as ‘low exposure’ or ‘low vulnerability’ conditions, and those based on SSPs 3 or 4 as ‘high exposure’ or ‘high vulnerability’ conditions ( [[#O’Neill--2014|O’Neill et al., 2014]] ; [[#van%20Vuuren--2014|van Vuuren and Carter, 2014]] ).

A wide range of climate change impacts depend strongly on development pathway ( ''high confidence'' ). A low (relative to high) exposure future, determined by limited population growth and urbanisation, results in about 30% fewer people exposed to extreme heat globally ( [[#Jones--2018b|Jones et al., 2018b]] ) and about 50% fewer in Africa ( [[#Rohat--2019a|Rohat et al., 2019a]] ), similar to the effect of a medium versus high level of global warming. Low-exposure conditions also reduce the fraction of the population in Europe at very high risk of heat stress from 39% to 11% ( [[#Rohat--2019b|Rohat et al., 2019b]] ). Demographic differences lead to a reduction in the global population exposed to mosquitos acting as viral disease vectors by more than half ( [[#Monaghan--2018|Monaghan et al., 2018]] ) and exposure to wildfire risk by nearly half ( [[#Knorr--2016|Knorr et al., 2016]] ).

Studies are increasingly going beyond exposure to incorporate future vulnerability, finding that it is often the dominant determinant of risk ( ''high confidence'' ). A low (relative to high) vulnerability future reduces the risk to global poverty by an order of magnitude, robustly across approaches that account for macroeconomic growth, structural change in the economy, inequality, and access to infrastructure services ( [[#Hallegatte--2017|Hallegatte and Rozenberg, 2017]] ), or for the exposure of vulnerable populations to multi-sector climate-related risks ( [[#Byers--2018|Byers et al., 2018]] ). A low (relative to high) vulnerability future also reduces the global mean number of temperature-attributable deaths in 2080–2095 due to enteric infections by an order of magnitude (from &gt;80,000 to &lt;7000; ( [[#Chua--2021|Chua et al., 2021]] )). Low future socioeconomic vulnerability to flooding reduces global fatalities and economic losses by 69–96% ( [[#Jongman--2015|Jongman et al., 2015]] ). Low vulnerability as measured by indicators including per capita GDP, education, governance, water demand and storage potential reduces water insecurity by a factor of three ( [[#Koutroulis--2019|Koutroulis et al., 2019]] ). A scenario with reduced barriers to trade reduces the number of people at risk of hunger due to climate change by 64% ( [[#Janssens--2020|Janssens et al., 2020]] ). Structural transformation of the economy (shift of the workforce from highly exposed sectors such as agriculture and fishing to less exposed sectors such as services) lowers GDP impact projections by 25–30% in today’s developing countries by 2100 ( [[#Acevedo--2017|Acevedo et al., 2017]] ).

The IPCC SRCCL supports the importance of societal conditions to climate-related risk ( [[#Hurlbert--2019|Hurlbert et al., 2019]] ), concluding that risks of water scarcity in drylands (i.e., desertification), land degradation and food insecurity are close to High [[#footnote-000|3]] beginning at 1.5°C under high-vulnerability conditions (SSP3), but remain close to Moderate up to slightly above 2°C for low-vulnerability conditions (SSP1). Specifically, risk of water scarcity in drylands (i.e., desertification) at 1.5°C warming is reduced in low vulnerability (relative to high vulnerability) conditions from High to Medium. Similarly, under a 2°C warming, risk is reduced from High to Moderate for food security and High to Moderate-to-High for land degradation.

While climate change will increase risk to society and ecosystems, future exposure and vulnerability conditions will also greatly impact outcomes of concern directly. Global economic damages to coastal assets from tropical cyclones are projected to increase by more than 300% due to coastal development alone, a much larger effect than projected climate change impacts through 2100 even in RCP8.5 ( [[#Gettelman--2018|Gettelman et al., 2018]] ). Similarly, global crop prices are more than three times more sensitive to alternative assumptions about changes in production technologies and demand than to alternative climate outcomes ( [[#Ren--2016|Ren et al., 2016]] ). Future water scarcity is driven mainly by both demographic change and socioeconomic changes affecting water demand and management. A measure of between-country inequality (Gini coefficient) would decline by more than 50% this century in low-vulnerability conditions, but would double in a high-vulnerability future ( [[#Crespo%20Cuaresma--2017|Crespo Cuaresma, 2017]] ), outweighing the effect of climate ( [[#Taconet--2020|Taconet et al., 2020]] ). Similarly, the global prevalence of armed conflict will roughly double this century in a high-vulnerability future, whereas it will drop by half in a low-vulnerability future ( [[#Hegre--2016|Hegre et al., 2016]] ). In Sub-Saharan Africa, assumptions about governance and political rights are estimated to be far more important to the future risk of violent conflict than climate change ( [[#Witmer--2017|Witmer et al., 2017]] ).

<div id="16.5.3.3" class="h3-container"></div>

<span id="climate-adaptation-scenarios"></span>
==== 16.5.3.3 Climate Adaptation Scenarios ====

<div id="h3-38-siblings" class="h3-siblings"></div>

One approach to understand adaptation benefits for risk reduction is to contrast projected impacts for the same climate and development conditions but different levels of adaptation. For example, global-scale coastal protection studies considering both RCPs and SSPs suggest that, under a given RCP, the total flooded area may be reduced by 40% by using 1-m height dykes, compared with a no-adaptation baseline ( [[#Tamura--2019|Tamura et al., 2019]] ). The global cost of SLR over the 21st century can be lowered by factor of two to four if local cost–benefit decisions consider migration an adaptation option, in addition to hard protection ( [[#Lincke--2021|Lincke and Hinkel, 2021]] ). Under a low-warming scenario, it is estimated that adaptation (i.e., changes in crop variety and planting dates) could reduce the total number of people at risk of hunger globally by about 4%, and by about 10% in a high-warming scenario ( [[#Hasegawa--2014|Hasegawa et al., 2014]] ). Impacts on heat-related mortality would be cut from 10 to 7 deaths per 10,000 people yr –1 in 2100 by adaptation actions beyond those assumed to be driven by income growth ( [[#Carleton--2020|Carleton et al., 2020]] ). In a regional example, proactive adaptation efforts on infrastructure (especially roads, runways, buildings and airports) in Alaska, USA, could reduce damage-related expenditure by 45% under medium or high warming ( [[#Melvin--2017|Melvin et al., 2017]] ).

Another approach infers the potential future effectiveness of adaptation based on current sensitivity of impacts to interventions. For example, the future disease burden of malaria is likely to be highly dependent on the future development of health services, deployment of malaria programs and adaptation. Investments in water and sanitation infrastructure are also recognised to have the potential to reduce severe risks of waterborne disease, although these improvements likely need to provide transformative change ( [[#Cumming--2019|Cumming et al., 2019]] ). The potential for severe risks may also be substantially reduced through the development of vaccines for specific enteric diseases ( [[#Riddle--2018|Riddle et al., 2018]] ), although most current vaccines target viral pathogens, incidence for which tends to be inversely correlated with ambient temperature ( [[#Carlton--2016|Carlton et al., 2016]] ). In addition, international migration as well as forced movement of people across borders will be influenced by developments in legal and political conditions ( [[#McLeman--2019|McLeman, 2019]] ; [[#Wrathall--2019|Wrathall et al., 2019]] ), but the fact that these developments are unknown strongly limits any forecasts on the magnitude of adaptation benefits ( [[#16.5.2.3.8|Section 16.5.2.3.8]] ).

Last, there is growing concern that even ambitious adaptation efforts will not eliminate residual risks from climate change ( [[#16.4.2|Section 16.4.2]] ). A synthesis of risk assessments in the recent IPCC Special Reports ( [[#Magnan--2021|Magnan et al., 2021]] ) concludes that high societal adaptation is expected to reduce the aggregated score—the proxy used in the study—of global risk from anthropogenic climate change by about 40% under all RCPs by the end of the century, compared with risk levels projected without adaptation. It, however, also shows that, even for the lowest warming scenario, a residual risk one-third greater than today’s risk level would still remain (with a doubling of today’s aggregated score under the high-emissions scenario).

<div id="16.5.3.4" class="h3-container"></div>

<span id="illustration-risk-and-adaptation-pathways-in-densely-populated-and-agricultural-deltas"></span>
==== 16.5.3.4 Illustration: Risk and Adaptation Pathways in Densely Populated and Agricultural Deltas ====

<div id="h3-39-siblings" class="h3-siblings"></div>

Large deltas, which are very dynamic risk hotspots of global importance and interest ( [[#Wigginton--2015|Wigginton, 2015]] ; [[#Hill--2020|Hill et al., 2020]] ; [[#Nicholls--2020|Nicholls et al., 2020]] ), serve well to illustrate how risk pathways develop over time, determined by climatic as well as non-climatic risk drivers and by adaptation. Deltas occupy less than 0.5% of the global land area but host over 5% of the global population ( [[#Dunn--2019|Dunn et al., 2019]] ) and contribute major fractions of food production in many world regions ( [[#Kuenzer--2020|Kuenzer et al., 2020]] ). Future risk in these areas is heavily driven by climate change but also greatly depends on past, current and future socioeconomic changes which influence future trends in exposure, vulnerability and adaptive capacity of natural and human systems ( ''high confidence'' ) ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ). From a risk perspective, trends over the past decades have been unfavourable for many deltas, as most of them have experienced a simultaneous intensification of hazards, rise in exposure and stagnation or only limited reduction in vulnerability, particularly in low-income countries ( ''high confidence'' ) ( [[#Day--2016|Day et al., 2016]] ; [[#Tessler--2016|Tessler et al., 2016]] ; [[#Loucks--2019|Loucks, 2019]] ; [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ; [[#Hill--2020|Hill et al., 2020]] ).

<div id="16.5.3.4.1" class="h4-container"></div>

<span id="hazard-trends-in-deltas"></span>
===== 16.5.3.4.1 Hazard trends in deltas =====

<div id="h4-14-siblings" class="h4-siblings"></div>

Deltas face multiple interacting hazards, many of which over the past decades have been intensified by local and regional anthropogenic developments (e.g., the construction of dams, groundwater extraction, or agricultural irrigation practices) and most of which are expected to be exacerbated by climate change ( ''high confidence'' ) ( [[#Giosan--2014|Giosan et al., 2014]] ; [[#Tessler--2015|Tessler et al., 2015]] ; [[#Tessler--2016|Tessler et al., 2016]] ; [[#Arto--2019|Arto et al., 2019]] ; [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ). The most important hazards include SLR, inundation, salinity intrusion, cyclones, storms and erosion, many of which occur in combination. The potential for flooding and inundation depends on the relative sea level rise (RSLR) which results from global and regional SLR as well as local subsidence within the deltas. Subsidence caused by natural and human drivers (mainly compaction and groundwater extraction) is currently the most important cause for RSLR in many deltas and can exceed the rate of climate-induced SLR by an order of magnitude ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ). But in higher warming scenarios the relative importance of climate-driven SLR is expected to increase over time ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ). In a global study covering 47 major deltas and assessing future trends of sediment delivery across four RCPs, three SSPs (1,2,3) and a projection of future dam construction, [[#Dunn--2019|Dunn et al. (2019)]] find most deltas (33 out of the 47) will experience a mean decline of 38% in sediment flux by the end of the century when considering the average of the scenarios. [[#Nienhuis--2020|Nienhuis et al. (2020)]] find in a global assessment that some deltas have gained land through increased sediment load (e.g., through deforestation), but recent land gains are unlikely to be sustained if SLR continues to accelerate. According to the latest assessments, it is ''virtually certain'' that global mean sea level will continue to rise over the 21st century, with SLR by 2100 ''likely'' to reach 0.28–0.55 m in a an SSP1–1.9 and 0.63–1.01 m in an SSP5–8.5 scenario relative to 1995–2014 ( [[#IPCC--2021|IPCC, 2021]] ). The combined effects of local subsidence and GMSL rise result in a significant increase in the potential for inundation of low-lying deltas across all RCPs, with some variation according to regional sea level change rates, without significant further adaptation measures ( ''very high confidence'' ).

In terms of salt-water intrusion and salinisation, global comparative studies are still lacking but the general processes are well understood (e.g., [[#White--2017|White and Kaplan, 2017]] ), and research on individual deltas is on the rise. In the Mekong Delta of Vietnam, one of the main rice-producing deltas globally, salinity intrusion has been observed to extend around 15 km inland during the rainy season and around 50 km during the dry season ( [[#Gugliotta--2017|Gugliotta et al., 2017]] ), resulting in rice yield losses of up to 4 t ha −1 yr −1 ( [[#Khat--2018|Khat et al., 2018]] ). SLR, along with the expansion of dams and dry season irrigation upstream, is expected to further increase the salinity intrusion into the delta. This creates additional risk for food production as rice and other crops might be pushed beyond their adaptation limits in terms of salt tolerance, potentially affecting many of the 282,000 agriculture-based livelihoods in the Mekong Delta and increasing the pressure for cost-intensive adaptation ( [[#Smajgl--2015|Smajgl et al., 2015]] ). [[#Genua-Olmedo--2016|Genua-Olmedo et al. (2016)]] find for the Ebro that in high scenario (RCP8.5, and SLR of almost 1 m by 2100), SLR-induced salinity intrusion will lead to almost a doubling of salinity levels and a decrease of mean rice productivity by over 20% in a high-SLR scenario with almost 1 m of SLR by the end of the century.

<div id="16.5.3.4.2" class="h4-container"></div>

<span id="exposure-trends-in-deltas"></span>
===== 16.5.3.4.2 Exposure trends in deltas =====

<div id="h4-15-siblings" class="h4-siblings"></div>

Next to the trends in hazards, future exposure of and in deltas is shaped particularly by the increase of population and infrastructure and the intensification of land use. Over the recent years, the population has been rising in major deltas, roughly along with overall national population trends ( [[#Szabo--2016|Szabo et al., 2016]] ). In 2017, 339 million people lived in deltas with a high exposure to flooding, cyclones and other coastal hazards ( [[#Edmonds--2020|Edmonds et al., 2020]] ). Over 40% of the global population exposed to flooding from tropical cyclones lived in deltas, more than 90% of which in developing countries and emerging economies (ibid.). Looking into the future, population in low-elevation coastal zones is expected to increase by 2050 across all SSPs with diverging developments in the second half of the century, and at the end of the century will reach well over 1 billion people in SSP3 ( [[#Jones--2016|Jones and O’Neill, 2016]] ; [[#Merkens--2016|Merkens et al., 2016]] ). A major part of this population is expected to reside in deltas with large cities or mega-urban agglomerations such as the Pearl River Delta, China. One of the first studies using the SSP-RCP framework on the delta scale suggests a strong increase in intensive agricultural land by the middle of the century in three SSPs (2, 3, 5) in the Volta Delta, Ghana, while the Mahanadi, India, and the Ganges–Brahmaputra–Meghna do not show a significant further increase ( [[#Kebede--2018|Kebede et al., 2018]] ). Hence, the amount of population and infrastructure as well as agricultural land is expected to rise further under certain SSPs, further increasing the exposure to future climate hazards.

<div id="16.5.3.4.3" class="h4-container"></div>

<span id="vulnerability-trends-in-deltas"></span>
===== 16.5.3.4.3 Vulnerability trends in deltas =====

<div id="h4-16-siblings" class="h4-siblings"></div>

Deltas are characterised by multi-faceted vulnerabilities of their environment and human populations. Over 200 indicators are being used in the literature to characterise and analyse vulnerability in deltas, spanning social, ecological and economic aspects ( [[#Sebesvari--2016|Sebesvari et al., 2016]] ). However, only a few studies model or dynamically assess trends in vulnerability, particularly for the future, at global scale, or take a comparative approach. But overall, a global trend assessment suggests that social vulnerability to climate hazards has been improving over the past years in all world regions hosting major deltas apart from Oceania, yet with emerging economies and developing countries in Africa showing less improvement than the Americas, Asia and Europe ( [[#Feldmeyer--2017|Feldmeyer et al., 2017]] ). An analysis of 48 major deltas finds that vulnerability therefore is a less dominant source of future increase in risk than exposure ( [[#Haasnoot--2012|Haasnoot et al., 2012]] ). However, case study research from individual deltas suggests that delta populations, particularly those with agriculture-based livelihoods, have seen more limited vulnerability reduction due in particular to the impacts of environmental hazards, stress and disasters ( ''high confidence'' ). In the Mekong Delta, for instance, the strong economic growth since the beginning of Vietnam’s reform process has not led to a reduction of vulnerability across the board for all socioeconomic groups ( [[#Garschagen--2015|Garschagen, 2015]] ). Rather, issues such as widespread landlessness or continued poverty have maintained and, in some respect, increased social vulnerability.

<div id="16.5.4" class="h2-container"></div>

<span id="rkr-interactions"></span>