# document

id: fd3af58a5f104bfa44e037ff699c6c41
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 41901
content:
"[...] direct empirical measures of vulnerability or exposure and are limited \r in their ability to assess how indirect effects of extreme events (e.g., \r morbidity, relocation, social disruption) may have changed or how \r changes may redistribute risk across populations."


id: 127b58789b5c3531e3c8c84311c028eb
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 449
content:
"There remain persistent difficulties in defining and measuring \r adaptation effectiveness and adequacy for many climate risks. No \r studies have systematically assessed the adequacy and effectiveness \r of adaptation at a global scale, across nations or sectors, or for \r different levels of warming. There has, however, been progress in \r operationalising assessment of adaptation feasibility (Cross-Chapter \r Box  FEASIB in Chapter 18). Effectiveness of adaptation-related \r responses reflects whether a particular response actually reduces \r climate risk, typically through reductions in vulnerability and exposure \r (Figure  1.7 in Section  1.4). Some adaptation-related responses may \r increase risk or create new risks (maladaptation) or have no or \r negligible impact on risk. Adequacy of adaptation-related responses \r refers to the extent to which responses are collectively sufficient \r to reduce the risks or impacts of climate change (Figure  1.7 in \r [...]"


id: 104a7a0e7a0dc2fbc1234d3394852e27
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 53
content:
"Based on the literature, the overall transformative nature of adaptation \r across most global regions and sectors is low (high confidence)\r (Figure  16.6). Documented adaptations tend to involve minor \r modifications to usual practices taken to address extreme weather \r conditions (high confidence). For example, changing crop variety or timing \r of crop planting to address floods or droughts, new types of irrigation, \r pursuing supplementary livelihoods, and home elevations are widely \r reported but typically do not reflect radical or novel shifts in practice or \r values and are therefore considered low depth (high confidence) (see \r SM16.1 for more examples). Adaptations documented in the literature \r are also frequently focused on a single sector or small geographic \r area (high confidence). Actions taken by individuals or households are \r generally small in scope (Hintz et al., 2018; Hlahla and Hill, 2018) unless \r [...]"


id: 49fead31427e46039069e679319cc962
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 10262
content:
"Adaptation-related responses are frequently motivated by a combination \r of climatic and non-climatic drivers, and interact with other transitions \r to affect risk. For societal responses, it is difficult to say whether they are \r triggered by observed or anticipated changes in climate, by non-climatic \r drivers or, as is the case in many societal responses, by a combination \r of all three. In the case of impacts, assessment typically focuses on \r detection and attribution vis a vis a counterfactual of no climate change. \r While there has been some effort to attribute reduced climate risk to \r adaptation-related responses (Toloo et al., 2013a; Toloo et al., 2013b; \r Hess et al., 2018; Weinberger et al., 2018), in many cases this has not \r been feasible given difficulties in defining adaptation and empirically \r disentangling the contribution of intersecting social transitions and \r changing risks. Literature on adaptation-related response frequently \r [...]"


id: b25b6700eae43b097e5a9b88d4e89361
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 28616
content:
"[...] draws on theories of change to assess the likely contribution of \r adaptations to changes in risk, including maladaptation and co-benefits."


id: d0958fee3224c9793ab785dec10ffdba
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 34045
content:
"Inter-regional risks from climate change--also called cross-border, transboundary, transnational or indirect risks--are risks that are \r transmitted across borders (e.g., transboundary water use) and/or via teleconnections (e.g., supply chains, global food markets) (Moser \r and Hart, 2015). The risks can result from impacts, including compound or concurrent impacts, that cascade across several tiers, in ways \r that either diminish or escalate risk within international systems (Carter et al., 2021). Risk transmission may occur through trade and \r finance networks, flows of people (Cross-Chapter Box MIGRATE in Chapter 7), biophysical flows (natural resources such as water) and \r ecosystem connections. However, not only risks are transmitted across borders and systems; the adaptation response may also reduce \r risks at the origin of the risk, along the transmission channel or at the recipient of the risk (Carter et al., 2021). This cross-chapter box \r [...]"


id: 84e50b704dcda3902998847e1e5eb801
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
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vector_id: 20517
content:
"[...] discusses four inter-regional risk channels (trade, finance, food and ecosystems) and how adaptation can govern these risks."


id: cbe553378b6a6cafba782db226455340
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
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vector_id: 33197
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"Most commodities are traded on global markets, and supply chains have become increasingly globalised. For instance, specialised industrial \r commodities such as semiconductors are geographically concentrated in a few countries (Challinor et al., 2017; Liverman, 2016). When \r climatic events like flooding or heat affect the location of these extraction and production activities, economies are not only disrupted \r locally but also across borders and in distant countries (high confidence), as exemplified by the Thailand flood 2011 that led to a shortage \r of key inputs to the automotive and electronics industry not only in Thailand but also in Japan, Europe and the USA (Figure Cross-Chapter \r Box INTEREG.1). For many industrialised countries like the UK, Japan, the USA and the European Union, there is increasing evidence that \r the trade impacts of climate change are significant and can have substantial domestic impacts (medium confidence) (Nakano, 2017; Willner \r [...]"


id: ece23a37c91f05a810bf414cf28aa548
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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"[...] et al., 2018, Section 13.9.1; Benzie and Persson, 2019; Knittel et al., 2020). Enhanced trade can transmit risks across borders and thereby \r amplify damages (Wenz and Levermann, 2016), but it can also increase resilience (Lim-Camacho et al., 2017; Willner et al., 2018)."


id: 8f082b060e51c1815873756ba3bcf1a
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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"The export of major food crops like wheat, maize and soybeans from many of the world's water-scarce area--the Middle East, North Africa, \r parts of South Asia, North China Plains, southwest USA, Australia--to relatively water-abundant parts of the world carries a high virtual \r water content (the net volume of water embedded in trade) (high confidence) (Hoekstra and Mekonnen, 2012; Dalin et al., 2017; Zhao \r et al., 2019, Chapter 4). Both importing and exporting countries are exposed to transboundary risk transmission through climate change \r impacts on distant water resources (Sartori et al., 2017; Zhao et al., 2019; Ercin et al., 2021). Climate change is projected to exacerbate \r risk and add new vulnerabilities for risk transmission (medium confidence). Rising atmospheric CO2 concentration is projected to decrease \r water efficiency of growing maize and temperate cereal crops in parts of the USA, East and Mediterranean Europe, South Africa, Argentina, \r [...]"


id: d4fd0428a549e56e3166544373ecec22
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
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vector_id: 34796
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"[...] Australia and Southeast Asia, with important implications for future trade in food grains (Fader et al., 2010). By 2050 (SRES B2 scenario), \r virtual water importing countries in Africa and the Middle East may be exposed to imported water stress as they rely on imports of food \r grains from countries which have unsustainable water use (Sartori et al., 2017). Until 2100, virtual trade in irrigation water is projected \r to almost triple (for SSP2-RCP6.5 scenarios) and the direction of virtual water flows is projected to reverse, with the currently exporting \r regions like South Asia becoming importers of virtual water (Graham et al., 2020). An additional 10-120% trade flow from water-abundant \r regions to water-scarce regions will be needed to sustain environmental flow requirements on a global scale by the end of the century \r (Pastor et al., 2019). Exports of agricultural commodities contribute to deforestation, over-exploitation of natural resources and pollution, \r [...]"


id: 8f382e7cf9e53e405e94246e7a169511
created_at: 2023-04-19 13:23:03
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vector_id: 22398
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"[...] affecting the natural capital base and ecosystem services (Agarwala and Coyle, 2020; Rabin et al., 2020, Section 12.5.4)."


id: 34aef98da17c0a4fc3f12f5e3f9db8b3
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 6505
content:
"A key area of advancement since AR5 is how incremental adaptation \r and transformational adaptation relate to limits to adaptation. \r Incremental adaptation maintains 'the essence and integrity of a \r system or process at a given scale', while transformational adaptation \r 'changes the fundamental attributes of a social-ecological system' \r (IPCC, 2018b). Both incremental and transformational adaptation may \r expand the adaptive possibilities for a system, providing additional \r adaptation options after a system reaches a soft limit (Felgenhauer, \r 2015; Pelling et  al., 2015; Termeer et  al., 2017, see also Chapters 1 \r and 17; Alston et al., 2018; Panda, 2018; Mechler and Deubelli, 2021). \r However, it is critical to note that adaptation, whether incremental \r or transformational, must support securing an actor's objectives or \r system's needs from intolerable risks. Once objectives or needs have \r been abandoned or transformed, a limit to adaptation has occurred. \r [...]"


id: 44c84d6e802d4415175b69512765346f
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 9327
content:
"[...] However, objectives or needs may change over time as values of a \r society change (Taebi et al., 2020), thus adding further complexity to \r assessing limits to adaptation."


id: e4b13e5cf9139807e260d33b11d792a8
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 37519
content:
"An expanding volume of empirical research highlights existing \r adaptation constraints that may lead to soft limits in Small Island \r Developing States (SIDS). Investigation of national communications \r among 19 SIDS found that financial constraints, institutional \r challenges and poor resource endowments were the most frequently \r reported as inhibiting adaptation for a range of climate impacts \r (Robinson, 2018b). Governance, financial and information constraints \r such as unclear property rights and lack of donor flexibility have led \r to hasty implementation of adaptation projects in Kiribati, whereas \r in Vanuatu and the Solomon Islands, limited awareness of rural \r adaptation needs and weak linkages between central governance \r and local communities have resulted in an urban bias in resource \r allocation (Kuruppu and Willie, 2015). Limited availability and use of \r information and technology also present constraints to adaptation; \r [...]"


id: 3e16f9e85d28f9a9a9a97a6b51dee581
created_at: 2023-04-19 13:23:03
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content:
"[...] many SIDS suffer from lack of data and established routines to identify \r losses and damages, and the combination of poor monitoring of slow\u0002onset changes and influence of non-climatic determinants of observed \r impacts challenges attribution (Thomas and Benjamin, 2018). The fact \r that climate information is often available only in the English language \r represents another common constraint for island communities (Betzold, \r 2015). Although Indigenous and local knowledge systems can provide \r important experience-based input to adaptation policies (Miyan et al., \r 2017), socio-cultural values and traditions such as attachment to \r place, religious beliefs and traditions can also constrain adaptation \r in island communities, particularly for more transformational forms of \r adaptation (Ha'apio et al., 2018; Oakes, 2019)."


id: 4d55b14045a1fdffcc42b9d8825f985
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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vector_id: 10885
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"The term 'residual risk' was not assessed in detail in AR5 and was \r used interchangeably with other terms, including 'residual impacts', \r 'residual loss and damage' and 'residual damage'. SR15 includes \r discussion of residual risks without an explicit definition and relates \r these to L oss and D amage and limits to adaptation, concluding \r that residual risks rise as global temperatures increase from 1.5degC to \r 2degC. SRCCL refers to residual risks arising from limits to adaptation \r related to land management. Such residual risk can emerge from \r irreversible forms of land degradation, such as coastal erosion when \r land completely disappears, collapse of infrastructure due to thawing \r of permafrost, and extreme forms of soil erosion. SROCC advanced \r the conceptualisation of residual risk and integrated it within the risk \r framework, defining residual risk as the risk that remains after actions \r have been taken to reduce hazards, exposure and/or vulnerability. \r [...]"


id: 31d4e51b3dd49eb7d9ad1988bd94c495
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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"[...] Residual risk is therefore generally higher where adaptation failure, \r insufficient adaptation or limits to adaptation occur. We use the SROCC \r definition of residual risk for our assessment in the following sections \r and identify residual risks that are associated with limits to adaptation."


id: fc9ca08001a651ad03609f0dd4306d87
created_at: 2023-04-19 13:23:03
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content:
"McNamara et al. (2017) provides an example of community-scaled adaptation that highlights how constraints affect limits, the relationship \r between soft and hard limits, and the potential need to abandon or transform objectives. Community members of Boigu Island, Australia, \r are already adapting to perceived climate change hazards--including sea level rise and coastal erosion--to secure their objective of \r sustaining livelihoods and way of life in their current location. Existing seawall and drainage systems provide inadequate protection \r from flooding during high tides, leading residents to elevate their houses to prevent damages. However, these adaptation measures have \r proved to be insufficient. Standing saltwater for extended periods of time after floods has resulted in losses and damages, including \r erosion of infrastructure, increased soil salinity, and heightened public health concerns. Additional adaptation efforts are constrained by \r [...]"


id: df5dfabfb04a69f1031455dac52097d5
created_at: 2023-04-19 13:23:03
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"[...] scarcity of elevated land, which inhibits movement of infrastructure within the community, and lack of financial, technical and human \r assets to improve coastal protection measures."


id: db1a51f54577a140057bf919e7131a5d
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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"These constraints are leading to a soft limit to adaptation, where risks would become unreasonable as sea levels continue to rise and \r practicable and affordable adaptation options are limited to currently available approaches. This soft limit could be overcome through \r addressing constraints and allowing further adaptation to take place, such as providing financial, technical and human resources for more \r effective coastal protection and drainage systems that would reduce flooding. However, if the effectiveness of these new adaptation \r measures decreases as sea levels rise further and if constraints are not able to be overcome, another soft limit may be reached. Eventually, \r if constraints are not addressed, no further adaptation measures are implemented, and climate hazards intensify, the area could become \r uninhabitable. This would then be a hard limit for adaptation; there would be no adaptation options available that would allow the \r [...]"


id: 483bd39c50140d75e6d5fb4f750f08d4
created_at: 2023-04-19 13:23:03
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"[...] community to sustain livelihoods and way of life in its present location. This hard limit to adaptation may necessitate abandoning the \r objective of remaining in the community. The objective of the community may then transform to sustaining their livelihoods in a less \r vulnerable location, which would necessitate relocation. However, such transformation of the community's objectives may be hindered \r by the expressed resistance of residents to migrate, due to their strong sense of place."


id: 20f88760dc67bbafcb1477c24fc2f02e
created_at: 2023-04-19 13:23:03
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"Soft limits to adaptation for coastal flooding and erosion are already \r being experienced in Samoa owing largely to financial, physical and \r technological constraints (Crichton and Esteban, 2018). While sea walls \r have been erected to minimise coastal erosion, these defences need \r regular upgrading and replacement as high swells, tropical cyclones \r and constant wave action erode their effectiveness. The high costs of \r installing, upgrading and enlarging such infrastructure has led to sea \r walls only being used in specific locations, leaving communities that \r are beyond the extent of these measures exposed to inundation and \r erosion. Native tree replanting has also been implemented, but coastal \r flooding and erosion persist as large swells lead to high failure rates \r of replanting efforts. Across SIDS, adaptation to coastal flooding and \r erosion in particular is increasingly facing soft limits due to high costs, \r [...]"


id: 924f55d8a142d78b05e64e6442e92435
created_at: 2023-04-19 13:23:03
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vector_id: 22962
content:
"[...] unavailability of technological options and limited physical space or \r environmental suitability for hard engineering or ecosystem-based \r approaches (Mackey and Ware, 2018; Nalau et al., 2018)."


id: c477e0fcb7e2143e253d55ba0d06daf7
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 31869
content:
"rise (Deutsch et al., 2018), increasing crop loss across Asia for which \r farmers are already experiencing a variety of adaptation constraints, \r including financial, economic and technological challenges (Sada et al., \r 2014; Tun Oo et al., 2017; Fahad and Wang, 2018). Extreme heatwaves \r are projected in the densely populated agricultural regions of South \r Asia, leading to increased risk of heat stress for farmers and resultant \r constraints on their ability to implement adaptive actions (Im et  al., \r 2017). However, socioeconomic constraints appear to have a higher \r influence on soft limits to adaptation in agriculture than biophysical \r constraints (Thomas et  al., 2021). For example, an examination of \r farmers' adaptation to climate change in Turkey found that constraints \r related to access to climate information and access to credit will \r likely limit the yield benefits of incremental adaptation (Karapinar \r [...]"


id: ec1f72d60dfddca548f9f8b5a02a81ff
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 38909
content:
"[...] and Ozertan, 2020). In Nepal, conservation policies restrict traditional \r grazing inside national parks, which promotes intensive agriculture and \r limits other cropping systems that have been implemented as climate \r change adaptation (Aryal et al., 2014)."


id: 39121d987e971d2fefb1384cf966f13e
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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"Palao et  al.. (2019) identify the possible need for transformational \r adaptation in Asian-Pacific agricultural practices due to changes in \r biophysical parameters as global average temperatures rise. In this \r context, transformational adaptation would consist of changing \r farming locations to different provinces or different elevations for \r the production of specific crops or introducing new farming systems. \r Nearly 50% of maize in the region along with 18% of potato and 8% \r of rice crops would need to either be shifted in location or use new \r cropping systems, with the most significant transformation being \r needed in China, India, Myanmar and the Philippines. For maize \r suitability by 2030, seven provinces in the east and northeast of China \r are projected to experience over 50% reduction in suitability, and two \r northern states in India may experience 70% reduction in suitability. \r Cassava and sweet potato may play a critical role in food resilience in \r [...]"


id: 5b4e3add14c9813f7aeddd9d94d739ee
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 13310
content:
"[...] these areas, as these crops are more resilient to climate change (Prain \r and Naziri, 2019)."


id: 30df2ef3364045be53650bda8bae3a41
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 5854
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"Lack of financial resources is found to be a significant constraint that \r contributes to soft limits to adaptation in agriculture across Asia. Although \r smallholder farmers are currently adapting to climate impacts, lack of \r finance and access to credit prevents upscaling of adaptive responses \r and has led to losses (Bauer, 2013; Patnaik and Narayanan, 2015; Bhatta \r and Aggarwal, 2016; Loria, 2016). Other constraints further contribute \r to soft limits, including governance and associated institutional factors \r such as ineffective agricultural policies and organisational capacities \r (Tun Oo et al., 2017), information and technology challenges such as \r limited availability and access to technologies on the ground (Singh \r et al., 2018), socio-cultural factors such as the social acceptability of \r adaptation measures that are affected by gender (Huyer, 2016; Ravera \r et al., 2016), and limited human capacity (Masud et al., 2017). A wide \r [...]"


id: 3d2c078e3ea92817f2ca7baa1a76d8f
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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"[...] range of pests and pathogens are predicted to become problematic \r to regional food crop production as average global temperatures "


id: 5ff63870c8d8e8e343fc2eb82901f003
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 14192
content:
"(Klomp and Valckx, 2014). Substantial immediate output losses and \r reduced economic growth due to extreme events have been observed \r in both the short and long term (Section  16.2.3). Estimates of the \r duration of negative effects of climate-related disasters differ, with \r some analyses suggesting that, on average, economies recover after \r 2 years (Klomp, 2016) and others finding negative effects of cyclones \r to persist 15-20 years following an event (Hsiang and Jina, 2014; IMF, \r 2017). Rising climate vulnerability has also been shown to increase \r the cost of debt (Kling et  al., 2018). Rising climatic risks negatively \r affect developing countries' ability to access financial markets (Cevik \r and Jalles, 2020), and their disclosure may result in capital flight \r (Cross-Chapter Box FINANCE in Chapter 17). Overall, the direct and \r indirect economic effects of climate change represent a major risk to \r financial system stability (Section 11.5.2). These risks and effects may \r [...]"


id: ee52f428e2d3b1b63fbd62d15857fabc
created_at: 2023-04-19 13:23:03
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vector_id: 39302
content:
"[...] further limit the availability of financial resources needed to overcome \r constraints, in particular for developing countries."


id: bb9594caf266da062106ee6f8a8b0b9d
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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vector_id: 30224
content:
"Sectoral studies indicate that climate impacts will result in higher \r levels of losses and damages and decreases in income, thereby \r increasing financial constraints (medium confidence). Yield losses \r for major agricultural crops are expected in nearly all world regions \r (Figure 5.7). Decreases in estimated marine fish catch potential and \r large economic impacts from ocean acidification are expected globally, \r leading to the risk of revenue loss (Section 5.8.3). Losses of primary \r productivity and farmed species of shellfish are expected in tropical \r and subtropical regions (Section 5.9.3.2.2). Economic losses have been \r observed in the power generation sector and transport infrastructure \r (Section 10.4.6.3.8), including economic losses from floods in urban \r areas (Section  4.2.4.5). However, some positive sectoral climate \r change impacts have been identified for the timber and forestry sector \r (Section 5.6.2), for primary productivity and farmed species of shellfish \r [...]"


id: 7616e31477f30c7dd09e20bc9db4c0fb
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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"[...] in high-latitude regions (Section 5.9.3.2.2) and for agriculture in high\u0002latitude regions (Section 5.4.1.1)."


id: 80107b896f29771c277462288e81929c
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 19660
content:
"A key risk is defined as a potentially severe risk and therefore especially \r relevant to the interpretation of dangerous anthropogenic interference \r (DAI) with the climate system, the prevention of which is the ultimate \r objective of the UNFCCC as stated in its Article 2 (Oppenheimer et al., \r 2014). Key risks are therefore a relevant lens for the interpretation of this \r policy framing. The severity of a risk is a context-specific judgement based \r on a number of criteria discussed below. KRs are 'potentially' severe \r because, while some could already reflect dangerous interference now, \r more typically they may become severe over time due to changes in the \r nature of hazards (or, more broadly, climatic impact drivers; IPCC, 2021) \r and/or of the exposure/vulnerability of societies or ecosystems to those \r hazards. They also may become severe due to the adverse consequences \r of adaptation or mitigation responses to the risk (on the former, see \r [...]"


id: 7edd9379f043fbbf28564e351f846c43
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 19475
content:
"[...] Section 17.5.1; the latter is not assessed separately here, except as it \r contributes to risks from climate hazards). Dangerous interferences in \r this chapter are considered over the course of the 21st century."


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created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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"At the household or community level, climate impacts may increase \r financial constraints (high confidence). Impacts on agriculture \r and food prices could force between 3 and 16  million people into \r extreme poverty (Hallegatte and Rozenberg, 2017). Within-country \r inequality is expected to increase following extreme weather events \r (Section  16.2.3.6 and Chapter 8). Households affected by climate\u0002related extreme events may be faced with continuous reconstruction \r efforts following extreme events (Adelekan and Fregene, 2015) or \r declines in critical livelihood resources in the agriculture, fisheries and \r tourism sectors (Forster et  al., 2014, Section  3.5.1). Further erosion \r of livelihood security of vulnerable households creates the risk of \r poverty traps, particularly for rural and urban landless (Sections 8.2.1, \r 8.3.3.1), for example in Malawi and Ethiopia (Section 9.9.3). Levels of \r labour productivity and economic outputs are projected to decrease as \r [...]"


id: 488846bbc414b45fda8cf587194d2f8e
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"[...] temperatures rise particularly in urban areas (Section 6.2.3.1). At the \r same time, higher utilities demand under higher urban temperatures \r exerts additional economic stresses on urban residents and households. \r Substantial, negative impacts on the livelihoods of over 180 million \r people are expected from changes to African grassland productivity \r (Section 5.5.3.1). In Western Uzbekistan, farmers' incomes are at risk \r of declining (Section 10.4.5.3). For SIDS, loss of livelihoods is expected \r due to negative climatic impacts on coastal environments and \r resources (Section 3.5.1). Negative effects on households from extreme "


id: f931a8f05a86e951277809c3e0389b98
created_at: 2023-04-19 13:23:03
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"Figure 16.8 |  Constraints associated with limits by region and sector. Data from Thomas et al. (2021), based on 1682 scientific publications reporting on adaptation-related \r responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/\r cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, \r and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing \r laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial \r [...]"


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"[...] resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: \r temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. Insufficient data: there is not enough literature to \r support an assessment (fewer than five studies available); Minor constraint: <20% of assessed literature identifies this constraint; Secondary constraint: 20-50% of assessed \r literature identifies this constraint; Primary constraint: >50% of assessed literature identifies this constraint."


id: a968b51c467f6f447b4895fb057216a6
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content:
"The authors of the sectoral and regional chapters and cross chapter \r papers of the WGII AR6 Report identified more than 120 key risks \r (SM16.7.4). Authors were asked to rely on the above definition and \r criteria to identify risks that could potentially become severe according \r to changes in the associated hazards, the study systems' exposure \r and/or vulnerability, and important adaptation strategies that could \r reduce these risks (see SM16.3 for methodology). Wherever possible, \r identification is based on literature that includes projected future \r conditions for all three components of risk and adaptation. Where \r literature was insufficient, potential severity is based on current \r vulnerability and exposure to climate hazards and the expectation that \r hazards will increase in frequency and/or intensity in the future. This \r approach is more limited in that it does not consider future changes \r in exposure and vulnerability nor in adaptation, but has the benefit of \r [...]"


id: 50ec297d6003285ca96b8f86065bce6f
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"defining 'severe' risks for each particular RKR. They also assess the \r conditions in terms of warming (more broadly, climatic impact drivers; \r (Ranasinghe et al., 2021), exposure/vulnerability and adaptation under \r which the RKR would become severe. For each of these dimensions, \r RKR teams considered generic levels ranging from High to Medium \r and Low. For warming levels, in line with WGI framing, High refers \r to climate outcomes consistent with RCP8.5 or higher, Low refers to \r climate outcomes consistent with RCP2.6 or lower, and Medium refers \r to outcomes for scenarios between RCPs 2.6 and 8.5. For reference, \r the full range of warming levels (across all climate models) associated \r with RCP8.5 for the 2081-2100 period is 3.0-6.2degC; for RCP2.6 it is \r 0.9-2.3degC; and for intermediate RCPs it is 1.8-3.6degC (Cross-Chapter \r Box  CLIMATE in Chapter 1). For Exposure-Vulnerability, levels are \r determined by the RKR teams relative to the range of future conditions \r [...]"


id: b35c75b407cb68d6a7bbbd1c711414c2
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content:
"[...] considered in the literature, for example based on the Shared \r Socioeconomic Pathways (SSPs) in which future conditions based on \r SSPs 1 or 5 represent Low exposure or vulnerability and those based \r on SSPs 3 or 4 represent High exposure or vulnerability (O'Neill et al., \r 2014; van Vuuren and Carter, 2014). For Adaptation, two main levels \r have been considered: High refers to near maximum potential, and Low \r refers to the continuation of today's trends. Despite being intertwined \r in reality, Exposure-Vulnerability and Adaptation conditions are \r distinguished to help understand their respective contributions to \r risk severity. Importantly, this assessment does not consider all risks, \r but only those that can be considered severe given the definition and \r criteria presented in Section 16.5.1. The assessment does not exclude \r the possibility that severe risks are already observed in some contexts, \r and considers projected risks through the end of this century."


id: 102ae0403a90e25e68b046a606170619
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"The RKRs are intended to capture the widest variety of KRs to \r human or ecological systems with a small number of categories that \r are easier to communicate and provide a manageable structure for \r further assessment. They expand the scope of some AR5 KR clusters \r (e.g., on coasts, health, food and water) and add new ones (e.g., \r on peace and human mobility). The RKRs encompass a diversity of \r types of systems, including an example of a geographically defined \r system (RKR-A on coastal regions), ecosystem well-being and integrity \r (RKR-B), a cross-cutting issue relevant to several outcomes of concern \r (RKR-C on critical infrastructure) and several topics focused directly on \r aspects of human well-being and security (RKR-D to RKR-H). This set \r of RKRs manages but does not eliminate overlap, instead providing \r alternative perspectives on underlying key risks that sometimes \r include complementary views on common risks. For example, the \r [...]"


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content:
"[...] water security RKR highlights the many key risks mediated by water \r quantity or quality, which are sometimes manifested as risk to food \r security (RKR-F) or health (RKR-E)."


id: 1b899e298f1a43a1954e46a3928fa53
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"global warming especially at lower latitudes (Section  3.4.2.2) (high \r confidence). In addition, depending on the local tide and sediment \r conditions, SLR associated with >1.5degC of global warming (SSP1-\r 2.6; 3.4.2.5) is sufficient to initiate shifts to alternate states in some \r seagrass and coastal wetland systems (van Belzen et  al., 2017; El\u0002Hacen et al., 2018, Section 3.4.2.5, Cross-Chapter Box SLR in Chapter \r 3), and submergence of some mangrove forests (Section  3.4.2.5). A \r striking example of risks becoming severe at higher levels of warming \r is the one of coral islands with low elevation (Section 15.3.4, Box 15.1): \r the risk of loss of habitability transitions from Moderate-to-High under \r RCP2.6 for most island types (urban and rural) to High-to-Very High \r under RCP8.5 (Duvat et  al., 2021), even under a high adaptation \r scenario (Oppenheimer et al., 2019), partly due to declining sediment \r supply (Perry et  al., 2018) and increased annual flooding (Giardino \r [...]"


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"even under Low warming (high confidence). These systems comprise a \r large fraction of unique and endemic biodiversity, with species impacts \r often exacerbated by multiple drivers of global change (Chapter 2, \r Chapter 3). Roughly one-third of all known plant species are extremely \r rare, vulnerable to climate impacts, and clustered in areas of higher \r projected rates of anthropogenic climate change (Enquist et al., 2019). \r Much evidence shows increased risk of the loss of 10% or more of \r terrestrial biodiversity with increasing anthropogenic climate change \r (Urban, 2015; Smith et  al., 2018) (medium confidence), likely with \r 2degC warming above pre-industrial level (Chapter 2), with consequent \r degradation of terrestrial, freshwater and ocean ecosystems (Oliver \r et al., 2015) and adverse impacts on ecosystem services (Pecl et al., \r 2017) and dependent human livelihoods (Dube et al., 2016). Adverse \r impacts on biodiversity may show lagged responses (Essl et al., 2015), \r [...]"


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"[...] and loss of a substantial fraction of species could occur abruptly, \r simultaneously across multiple taxa, below 4degC of global warming \r (Trisos et al., 2020)."


id: cd9469a12767dcdd6c65396bf0b8bc82
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"Landscape- and larger-scale shifts in ecosystem structure and function \r (order-of-magnitude increases or abrupt decreases in cover and/or \r biomass of novel growth forms or functional types) are occurring in non\u0002equilibrium ecosystems (systems which exist in multiple states, often \r disturbance-controlled) in response to changing disturbance regime, \r climate and rising CO2 (high confidence) Woody plant encroachment \r has been occurring in multiple ecosystems, including subtropical and \r tropical fire driven grassland and savanna systems, upland grassland \r systems, arid grasslands and shrublands (high confidence), leading \r to large-scale biodiversity changes, albedo changes, and impacts \r on water delivery, grazing services and human livelihoods (medium \r confidence). Expansion of grasses (alien and native) into xeric \r shrublands is occurring, causing increasing fire prevalence in previous \r fire-free vegetation (Cross-Chapter Paper 3). In tropical forests, \r [...]"


id: ad6176cd05a0656c60aed7e54a9f6d3c
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"[...] repeated droughts and recurrence of large-scale anthropogenic \r fires increase forest degradation, loss of biodiversity and ecosystem \r functioning (high confidence) (Anderson et  al., 2018b; Longo et  al., \r 2020). Accelerated growth rates and mortality of tropical trees is also \r adversely affecting tropical ecosystem functioning (McDowell et  al., \r 2018; Aleixo et al., 2019). Projected changes in ecosystem functioning, \r such as via wildfire (Section 2.5.5.2), tree mortality (Section 2.5.5.3) \r and woody encroachment under climate change (Chapter 2) would \r alter hydrological processes, with adverse implications for water yields \r and water supplies (Sankey et al., 2017; Robinne et al., 2018; Rodrigues \r et al., 2019; Uzun et al., 2020)."


id: 13282ff2398bb67c936bd1f1c99153ca
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content:
"Mass population-level mortality (>50% of individuals or colonies \r killed) and resulting abrupt ecological changes can be caused by \r simple or compound climate extreme events, such as exceedance \r of upper thermal limits by vulnerable terrestrial species (Fey et  al., \r 2015), who also note reduced mass mortality trends due to extreme \r low thermal events; marine heatwaves that can cause mortality, \r enhance invasive alien species establishment, and damage coastal \r ecological communities and small-scale fisheries (high confidence) \r (Section 3.4.2.7); and increased frequency and extent of wildfires that \r threaten populations dependent on habitat availability (like Koala \r Bears, Lam et al., 2020). Abrupt ecological changes are widespread and \r increasing in frequency (Turner et al., 2020), and include tree mortality \r due to insect infestation exacerbated by drought, and ecosystem \r transformation due to wildfire (Vogt et al., 2020). Freshwater ecosystems \r [...]"


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"[...] and their biodiversity are at high risk of biodiversity loss and turnover \r due to climate change (precipitation change and warming, including \r warming of water bodies), due to high sensitivity of processes and \r life histories to thermal conditions and water quality (Chapter 2) (high \r confidence). In marine systems, heatwaves cause damages in coastal \r systems, including extensive coral bleaching and mortality (very high \r confidence) (Section  3.4.2.1), mass mortality of invertebrate species \r (low to high confidence, depending on system) (Sections  3.4.2.2, \r Section 3.4.2.5, Section 3.4.4.1), and abrupt mortality of kelp-forest \r (high confidence) (Section 3.4.2.3) and seagrass-meadow habitat (high \r confidence) (Section  3.4.4.2). The biodiversity of polar seas shows \r strong impacts of climate change on phenological timing of plankton \r activity, Arctic fish species range contractions and species community \r [...]"


id: e6f399d6003842767912aa7f75deee5e
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"[...] change (Table  SM16.22) (high confidence). Extreme weather events \r and storm surges exacerbated by climate change have severe and \r sudden adverse impacts on coastal systems, including loss of seagrass \r meadows and mangrove forests (high confidence) (see Section 3.4.2.7, \r Section 3.4.2.8, Cross-Chapter Box EXTREMES in Chapter 2)."


id: 7c7bba03123f3f0643ba498b566d0d71
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content:
"The loss of a substantial fraction of biodiversity globally, abrupt impacts \r such as significant local biodiversity loss and mass population mortality \r events, and ecological disruption due to novel species interactions \r have been observed or are projected at global warming levels \r below 2degC (Chapter 2 Table SM2.5, Cross Chapter Box: EXTREMES in \r Chapter 2, Section 2.4.4.3.1, Section 2.4.2.3.3) (medium confidence). \r Simple and compound impacts of extreme climate events are already \r causing significant losses and damages in vulnerable ecosystems, \r including through the facilitation of important global change drivers of \r ecological disruption and homogenisation like invasive species (high \r confidence). Severe impacts on human livelihoods and infrastructure, \r and valuable ecosystem services, are all projected to accompany these \r changes. Adaptation potential for many of these risks is low due to \r the projected rate and magnitude of change, and to the requirement \r [...]"


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"[...] of significant amounts of land for terrestrial ecosystems (Hannah \r et al., 2020). Biodiversity conservation efforts may be hampered due \r to climate change impacts on the effectiveness of protected areas, \r with high sensitivity of effectiveness to forcing scenario (medium \r confidence). In addition, climate-related risks to ecosystems pose \r challenges to ecosystem-based adaptation responses ('nature-based \r solutions') (Section 2.1.3) (medium confidence)."


id: de83f35c5f282ec016a3250736884161
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content:
"confidence). Damages from multiple climate hazards to transport, \r energy, industry and social infrastructure in Europe could increase \r 10-fold by the 2080s, from 3.4 EUR billion annually to date, and 15-\r fold for transport infrastructure, under Medium warming (A1B, \r ~3degC by 2100) and with current adaptation levels, even if no further \r extension of the infrastructure in exposed areas is considered \r (Forzieri et al., 2018). Under High warming (RCP8.5) in 2100, the \r percent of roads in the USA that require rehabilitation due to high \r temperatures and precipitation is expected to increase to 23-33%, \r relative to 14% in 2100 when no climate change is considered \r (Mallick et  al., 2018). Projections of climate-induced changes in \r exposure are an incomplete measure of risk but in the absence \r of other metrics can serve as a proxy for the potential for severe \r impacts. In the circumpolar Arctic, 14.8% of critical infrastructure \r [...]"


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"[...] assets would be affected by climate change under RCP8.5 by 2050, \r with lifecycle replacement costs projected to increase by 27.7% if \r infrastructure is to be preserved at current adaptation levels (Suter \r et al., 2019). Under RCP8.5, the number of ports under high risk \r will increase from 3.8% in the present day to 14.4% by 2100, as \r a result of increased coastal flooding and overtopping due to SLR, \r as well as the heat stress impacts of higher temperatures (Izaguirre \r et  al., 2021). In the UK under High warming (4degC), the number \r of clean and wastewater treatment sites located in the 1-in-75-\r year floodplain will increase by a third relative to today by the \r 2080s under current vulnerability and adaptation levels (Dawson \r et al., 2018). A global assessment of changing climate and water \r resources for electricity generation finds considerable reductions in \r usable hydropower and thermoelectric capacity by 2050 for a range \r [...]"


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"[...] of warming scenarios from Low to High, with absolute declines on \r average for most (61-74%) of the world's hydropower resources \r and monthly maximum reductions above 30% of usable capacity \r for over two-thirds of 1427 thermoelectric power plants worldwide \r (Van Vliet et al., 2016). Many studies find large technical potential \r for coordinated adaptation-mitigation policies in the electricity \r sector to avoid a significant portion of projected climate change \r impacts (e.g., a two-thirds reduction, and in some cases fully offset) \r (Ciscar and Dowling, 2014; Van Vliet et al., 2016; Gerlak et al., 2018; \r Allen-Dumas et al., 2019)."


id: 90c2a5b05ffdfa7184cfb4557ebaf9eb
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content:
"RKR-C includes risks associated with the breakdown of physical \r infrastructure and networks which provide goods and services considered \r critical to the functioning of societies. It encompasses infrastructure \r systems for energy, water, transportation, telecommunications, health \r care and emergency response, as well as compound, cascading and cross\u0002boundary risks resulting from infrastructure interdependencies (Birkmann \r et  al., 2016; Fekete, 2019). Critical infrastructures such as transport \r or energy supply also play a central role in coping with climate risks, \r especially in acute disaster situations in which the services of transport \r infrastructure, communication technologies or electricity are particularly \r needed, despite the fact that these very systems are themselves exposed \r to disaster impacts (Garschagen et  al., 2016; Pescaroli et  al., 2018). \r The major hazards driving such risks are acute extreme events such as \r [...]"


id: 5beefb541f3b6a4ebd3dddd40442dbb0
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"[...] cyclones, floods, droughts or fires (high confidence), but cumulative and \r chronic hazards such as SLR are also considered."


id: f412aed038625c5ba532f5dc8d88e6b6
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content:
"RKR-C is considered severe when the functioning of critical infrastructure \r cannot be secured and maintained against climate change impacts, \r resulting in the frequent and widespread breakdown of service delivery \r and eventually a significant rise of detrimental impacts on people (lives, \r livelihoods and well-being), the economy (including averted growth) or \r the environment (disruption and loss of ecosystems) above historically \r observed levels. Severity in this RKR is assessed on two levels for (i) \r direct impacts of climate change on infrastructure assets and networks \r (e.g., amount of port infrastructure damaged or destroyed by SLR, \r flooding and storms) on which most of the literature focuses, as well as \r (ii) indirect and cascading downstream impacts to people, economy and \r environment (Markolf et al., 2019; Pyatkova et al., 2019; Chester et al., \r 2020), for which attribution is more difficult and uncertainties tend to \r [...]"


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content:
"[...] be much higher. Overall, the literature with quantified assessments of \r climate change infrastructure risks remains to be less extensive than \r for many other risks, particularly with regard to assessments focusing \r on the Global South. While climate-related changes in hazards are \r widely considered in the literature, changes in future exposure and \r vulnerability conditions are often not treated explicitly. In addition, \r the severity of infrastructure risks also depends on future trends in the \r capacity to maintain, repair and rebuild infrastructure and adapt it to \r new hazard intensities (medium evidence, high agreement). These are \r mostly not quantified in a forward-looking manner in the literature; \r however, damage projections (see below) indicate a rapidly rising \r demand for investment, straining the financial capacity of countries \r (medium evidence, high agreement)."


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"(Cervigni et al., 2015). On the Dawlish railway section (UK), the \r number of days with line restrictions is set to increase by up to \r 1170%, to as high as 84-120 yr-1 by 2100 due to 0.8 m SLR with \r High warming (Dawson et al., 2016). Next to the limited number of \r projections or scenarios of indirect impacts, additional inferences \r from studies focusing on past and current impacts can be drawn. \r Already today, climate-related impacts on transport and energy \r infrastructure reach far beyond the direct impacts on physical \r infrastructure, triggering indirect impacts on, for example, health \r and income (medium confidence). A case study of future flood \r hazard in Europe found that the indirect impact of a power outage \r on the local economy is six to eight times greater than the direct \r flood damage and asset repair costs, due to the interruption of daily \r [...]"


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content:
"[...] economic activity (Karagiannis et al., 2019). In low- and middle\u0002income countries, the annual costs from infrastructure disruptions \r reach up to 300 billion USD for firms and 90 billion USD for private \r households, with natural hazards such as floods being responsible \r for 10-70% of these disruptions, depending on the sectors and \r regions (Hallegatte et al., 2019). Power outages triggered by floods \r or droughts have also been found to have substantial health \r implications, particularly among low-income populations (Klinger \r et al., 2014), and shown to impede disaster recovery efforts and \r severely disrupt local economies (Karagiannis et al., 2019; Nicolas \r et al., 2019). In addition, risks associated with infrastructure have \r the potential to become particularly severe when hazard-driven \r infrastructure disruptions undermine the capacity of emergency \r response in disaster situations (limited evidence, high agreement). \r [...]"


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content:
"[...] A study on the UK shows, for example, that even a small increase in \r minor road flooding leads to a disproportionately high disruption \r of the efficacy of emergency services (Yu et  al., 2020). Similar \r risks have been found for rural areas, particularly in developing \r countries (Alegre et al., 2020)."


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content:
"Annual economic output losses in developing countries could exceed \r the worst country-level losses during historical economic recessions \r (medium confidence). Assuming global warming of ~4degC by 2100, \r historical adaptation levels and high vulnerability, losses across Sub\u0002Saharan Africa may reach 12% of GDP by 2050 (Baarsch et al., 2020) \r and 80% by 2100 (Burke et  al., 2015), and ~9% on average across \r developing countries by 2100 (Acevedo et  al., 2017). The largest \r estimates are debated and depend on assumptions about development \r trends, adaptive capacity, and whether temperature impacts the level \r or growth rate of economic activity (Kalkuhl and Wenz, 2020). Severe \r risks are more likely in (typically hotter) developing countries because \r of nonlinearities in the relationship between economic damages and \r temperature (Burke et al., 2015; Acevedo et al., 2017). These risks are \r highest in scenarios and countries with: a large portion of the workforce \r [...]"


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"[...] employed in highly exposed industries (Acevedo et al., 2017); a high \r concentration of population and economic activity on coastlines (Hsiang \r and Jina, 2014; Acevedo et al., 2017); and an increase in the frequency \r or intensity of disasters triggered by natural hazards (Berlemann and \r Wenzel, 2018; Botzen et al., 2019). Whether baseline economic growth \r may help avoid severe future risks is highly uncertain (Dell et al., 2012; \r Burke et al., 2015; Acevedo et al., 2017; Deryugina and Hsiang, 2017)."


id: 5220065b1e525ffa03510b77dad6681f
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 11719
content:
"and vulnerability, and the rate at which hazard frequency or \r intensity is expected to increase (Otto et  al., 2017; Roy et  al., \r 2018; Li et al., 2019, Section 8.5). Without effective adaptation \r measures, regions with high dependence on climate-sensitive \r livelihoods--particularly agriculture and fisheries in the tropics \r and coastal regions--would be severely impacted even at low \r levels of warming (high confidence) (Hoegh-Guldberg et  al., \r 2018b; Roy et al., 2018). For example, it is estimated that 330-\r 396 million people could be exposed to lower agricultural yields \r and associated livelihood impacts at warming between 1.5degC \r and 2degC (Byers et  al., 2018). Risks to the 200  million people \r with livelihoods derived from small-scale fisheries would also be \r severe, given sensitivity to ocean warming, acidification and coral \r reef loss occurring beyond 1.5degC (Cheung et al., 2018b; Froehlich \r [...]"


id: a19be11848280316c69ab7429520dc66
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 25649
content:
"[...] et al., 2018; Free et al., 2019; Barnard et al., 2021). Livelihoods in \r highly exposed locations, such as Small Island Developing States, \r low-lying coastal areas, arid or semiarid regions, the Arctic, and \r urban informal settlements or slums, are particularly vulnerable \r (Ford et al., 2015c; Hagenlocher et al., 2018; Ahmadalipour et al., \r 2019; Tamura et al., 2019). Within populations, the poor, women, \r children, the elderly and Indigenous populations are especially \r vulnerable due to a combination of factors, including gendered \r divisions of paid and/or unpaid labour, as well as barriers in access \r to information, skills, services or resources (Bose, 2017; Thomas \r et al., 2019b; Anderson and Singh, 2020; Adzawla and Baumuller, \r 2021) (high confidence). Future structural transformation \r could moderate risk severity by improving adaptive capacity, \r creating livelihoods in less climate-sensitive sectors, or by \r [...]"


id: 6e9e748f58fa10c020fe718158429846
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 16730
content:
"[...] enabling sustainable migration to less climate-sensitive locations \r (Henderson et  al., 2017; Roy et  al., 2018). However, successful \r risk moderation would depend upon simultaneous avoidance of \r both climate-change-related and mitigation-related (Doelman \r et  al., 2019; Fujimori et  al., 2019; Doelman et  al., 2020) or \r maladaptation-related risks (Magnan et  al., 2016; Benveniste \r et al., 2020; Schipper, 2020)."


id: ca54004a2bfff2389d21b120ca23074b
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 32940
content:
"A severe risk to health is the potential for a widespread, substantial \r worsening of health conditions due to climate change. We measure \r severity in terms of the magnitude of mortality and morbidity. We \r consider a severe mortality impact to be a sustained increase in the \r crude mortality rate (CMR) of more than about 2-4 deaths per 10,000 \r people yr-1. This range of increase is consistent with current mortality \r impacts with substantial global effects, including traffic fatalities (CMR \r of 1.6/10,000 yr-1; IHME, 2019) and the COVID-19 pandemic (CMR \r of 4/10,000 yr-1, as of April 2021, expressed as an annualised rate; \r Ritchie et  al., 2021). We use these global rates as thresholds in all \r cases, recognising that they reflect substantial variation across regions \r and sub-populations (for other points of comparison, see IHME, 2019). \r Morbidity impacts are measured in numbers of disease cases or hospital \r [...]"


id: 1f58022356a3800027529060826ef303
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 2717
content:
"[...] admissions. We find that severe health impacts are projected to occur for \r particular sub-populations and regions where vulnerability is currently \r high and is assumed to persist into the future; we focus our assessment \r on these cases. In other cases, literature is either inadequate or does not \r support severe outcomes."


id: 1d1e3c9be78c09e43a975f3b0c375020
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 2300
content:
"Climate change also could increase income inequality between \r countries (high confidence) as well as within them (medium evidence, \r high agreement) resulting from and exacerbating impacts on aggregate \r economic activity, poverty and livelihoods. Increasing inequality \r implies larger impacts on the least well-off, threatens their ability to \r respond to climate hazards, compromises basic principles of fairness \r and established global development goals, and potentially threatens \r the functioning of society and long-term progress (Roe and Siegel, \r 2011; Cingano, 2014; van der Weide and Milanovic, 2018). There is \r evidence that warming has slowed down the convergence in between\u0002country income in recent decades (Diffenbaugh and Burke, 2019). \r Future impacts may halt or even reverse this trend during this century \r owing to high sensitivity of developing economies (Burke et al., 2015; \r Pretis et al., 2018; Baarsch et al., 2020), although projections depend \r [...]"


id: 8de2a47700842ed8c25b55aa4c440114
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 22154
content:
"[...] as much or more on future socioeconomic development pathways \r and mitigation policies as on warming levels (Takakura et al., 2019; \r Harding et  al., 2020; Taconet et  al., 2020). Within countries, studies \r that find adverse impacts on low-income groups imply an increase \r in inequality (Hallegatte and Rozenberg, 2017; Hsiang et  al., 2017), \r although evidence for long-term climate impacts on within-country \r inequality at global scale remains limited."


id: a206351e5fbec7929395fe05e543ef74
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 25741
content:
"With high warming, the CMR for malaria among children under the \r age of 1 year could increase by 5.2-10.1/10,000 yr-1 in Africa under \r current vulnerability levels. This estimate assumes a net increase of \r 70-130 million more people exposed to potential disease transmission \r due to climate change in a high-warming scenario (RCP8.5, end of \r century) (Caminade et  al., 2014; Colon-Gonzalez et  al., 2021; Ryan \r et al., 2020), representing a 14-27% increase in the current population \r at risk (Ryan et al., 2020), and assumes children under 1 year of age \r are facing the same crude mortality in the future as for the African \r region today (IHME, 2019). The largest increase is observed in Eastern \r Africa, where the population exposed could nearly double by 2080 \r (Ryan et al., 2020) without accounting for population growth, driven \r mainly by changes among previously unexposed populations at higher \r altitude areas (Colon-Gonzalez et  al., 2021). Actual future disease \r [...]"


id: 45c3382baeffb4ed3bb1db80851f3cae
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 9488
content:
"[...] burden of malaria will be highly sensitive to regional socioeconomic \r development and the effectiveness of malaria intervention programs."


id: 98aab7de8820997b377576a62cc2e45b
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 24073
content:
"Climate change will pose severe risks in terms of increasing the number \r of undernourished people, affecting tens to hundreds of million people \r under High vulnerability and High warming, particularly among low\u0002income populations in developing countries (high confidence). Extreme \r weather events will increase risks of undernutrition even on a regional \r scale, via spikes in food price and reduced income (high confidence) \r (FAO et al., 2018, Hickey and Unwin, 2020; Mbow et al., 2019). The \r timing of these impacts and our ability to respond to them vary based \r on the level of GHG emissions and Shared Socioeconomic Pathways \r (SSP).. Under a low vulnerability development pathway (SSP1), climate \r change starts posing a moderate risk to food security above 1degC of \r global warming (i.e., impacts become detectable and attributable to \r climate-related factors), while beyond 2.5degC the risk becomes high \r (widespread impacts on larger numbers or proportion of population \r [...]"


id: d38e206b6015983fb94c4c2d83edd6b7
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 34558
content:
"[...] or area, but with the potential to adapt or recover) (Hurlbert et al., \r 2019). Under high vulnerability-high warming scenario (i.e., SSP3-\r RCP6.0), up to 183 million additional people are projected to become \r undernourished in low-income countries owing to climate change by \r 2050 (Mbow et al., 2019). Climate-related changes in food availability \r and diet quality are estimated to result in a crude mortality rate of \r about 54 deaths per million people with about 2degC warming by 2050 \r (SSP2, RCP8.5), most of them projected to occur in South and East Asia \r (67-231 deaths per million depending on the country) (Springmann \r et  al., 2016). In a medium vulnerability-high warming scenario "


id: c83a1244e8b2da84ae15af0ba7ab6380
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 32537
content:
"Climate change risks of micronutrient deficiency will become severe \r in high-vulnerability development pathways and in the absence of \r societal adaptation, leading to hundreds of millions of additional \r people lacking key nutrients for atmospheric CO2 levels above \r 500 ppm (high confidence) (Myers et  al., 2017; Nelson et  al., 2018; \r Mbow et al., 2019). For example, concentration of many micronutrients \r (e.g., phosphorus, potassium, calcium, sulphur, magnesium, iron, zinc, \r copper and manganese) can decrease by 5-10% under atmospheric \r CO2 concentrations of 690 ppm (3.5degC warming). The decline in zinc \r content is projected to lead to an additional 150-220 million people \r affected by zinc deficiency with increases in existing deficiencies in \r more than 1  billion people (Myers et  al., 2017). Similarly, decrease \r in protein and micronutrient content in rice due to a higher CO2\r concentration (568-590 ppm) can lead to 600  million people with \r [...]"


id: 74f613ea0695ef68bd96df4a81bb3312
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 17813
content:
"[...] rice as a staple at risk of micronutrient deficiency by 2050 (Zhu et al., \r 2018). Additionally, the impact on protein content of increased CO2\r concentration (>500 ppm) can lead an additional 150 million people \r with protein deficiency by 2050 (within the total of 1.4 billion people \r with protein deficiency) in comparison with the scenario without \r increased CO2 concentration (Medek et al., 2017)."


id: a0532b13aa2fb9e815e372a42bdb4414
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 25416
content:
"Risks associated with water scarcity have the potential to become \r severe based on projections of large numbers of people becoming \r exposed to low levels of water availability per person, where 'water \r availability' includes fresh water in the landscape, including soil \r moisture and streamflows, available for all uses including agriculture \r as a dominant sector. Approximately 1.6  billion people currently \r experience 'chronic' water scarcity, defined as the availability of less \r than 1000 m3\r  of renewable sources of fresh water per person per \r year (Gosling and Arnell, 2016). In this context, we define a severe \r outcome as an additional 1  billion people experiencing 'chronic' \r water scarcity, relating to all uses of water, representing an increase \r of a magnitude comparable to current levels. The global number of \r people experiencing chronic water scarcity is projected to increase by \r approximately 800  million to 3  billion for 2degC global warming, and \r [...]"


id: 175bff3cd9cdb7756b4e8110cdb1632e
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 1333
content:
"[...] up to approximately 4 billion for 4degC global warming, considering the \r effects of climate change alone, with a 9 billion population (Gosling \r and Arnell, 2016). Severe outcomes are projected to occur even \r with no changes in exposure: present-day exposure is defined here \r as 'medium' since either an increase or decrease in exposure could \r be possible. Vulnerability is not quantified in the literature assessed \r here, so in this assessment it is considered that severe outcomes \r could occur with present-day levels of vulnerability, again defined \r here as 'medium'. Particularly severe outcomes (i.e., the high end \r of these ranges) are driven by regional patterns of climate change \r bringing severe reductions in precipitation and/or high levels of \r evapotranspiration in the most highly populated regions, leading \r to very substantial reductions in water availability compared with \r demand. There is strong consensus across models that water scarcity is \r [...]"


id: 1ff7559977e2213a2d2a889525e1d127
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 2837
content:
"[...] projected to increase across substantial parts of the world even though \r projections disagree on which specific areas would see this impact. \r Moreover, a projected decrease in water scarcity in some regions does \r not prevent the increase in water scarcity in other regions becoming \r severe. Hence there is high confidence that risks to water scarcity have \r the potential to become severe due to climate change. Consequences \r of water scarcity include potential competition and conflicts between \r water users (Vanham et  al., 2018), damaging livelihoods, hindering \r socioeconomic development and reducing human well-being, for \r example through malnutrition resulting from inadequate water \r supplies leading to long-term health impacts such as child stunting \r (Cooper et  al., 2019). The avoidance of these consequences at high \r levels of water scarcity would require transformational adaptations \r including large-scale interventions such as dams and water transfer \r [...]"


id: 32aa65cd6e98097ba7e6afc0ce7f0b39
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 6177
content:
"providing freedom and mental well-being, loss of sea ice can be \r argued to represent environmental dispossession of these communities \r (Durkalec et al., 2015). Traditional ways of life are therefore threatened, \r and resulting changes would be transformative rather than adaptive. \r Similarly, changes in streamflow affecting the availability of species for \r traditional hunting can also negatively impact Indigenous communities \r (Norton-Smith et al.). Such changes are already being seen at current \r levels of warming, but studies remain somewhat limited in number, so \r this assessment is assigned medium confidence because of medium \r evidence and medium agreement. WGI conclude that it is virtually \r certain that further warming will lead to further reductions in Northern \r Hemisphere snow cover, and mass loss in individual glacier regions \r is projected to be between approximately 30% and 100% by 2100 \r under high-warming scenarios (Chapter 4). Streamflows are projected \r [...]"


id: 2f1122b508b80e53bc543db0188bcb40
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 5553
content:
"[...] to change in most major river basins worldwide by several tens of \r percent at 4degC global warming (Chapter 4)."


id: 31ce774ab98007363122cee4e20c5934
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 6009
content:
"Risks associated with water-related extreme events and disasters \r have the potential to become severe based on projections of large \r numbers of people or high values of assets being affected. The risks \r to people from disasters can often only be quantified in terms of the \r hazard and exposure (the number of people affected), rather than the \r full consequences such as number of deaths, injuries or other health \r outcomes, as these often depend on complex or unpredictable factors \r such as the effectiveness of emergency and humanitarian responses or \r the access to healthcare. With approximately 50 million people per year \r currently affected by flooding (Alfieri et  al., 2017), we define severe \r outcomes as more than 100 million people affected by flooding. At 2degC \r global warming, between approximately 50  million and 150  million \r people are projected to be affected by flooding, with figures rising to \r 110  million to 330  million at 4degC global warming. These projections \r [...]"


id: d34f79eb480a037f7f06788e143d4c8a
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 34521
content:
"[...] assume present-day population and no additional adaptation, so no \r changes in exposure. Increased flood risk is projected by the WHO to \r lead to an additional 48,000 deaths of children under 15 years due to \r diarrhoea by 2030, with Sub-Saharan Africa impacted the most (WHO, \r 2014). Other consequences of floods that already occur include deaths \r by drowning, loss of access to fresh water, vector-borne diseases, \r mental health impacts, loss of livelihoods and loss of or damage to \r property. Many of these consequences depend on the vulnerability of \r individuals, households or communities to flooding impacts, for example \r through the presence or absence of measures to safeguard health \r and livelihoods, such as through infrastructure services, insurance or \r community support. The risks associated with these consequences \r could increase if there were no local adaptations to counter the effect \r of increased levels of hazard by reducing exposure and/or vulnerability. \r [...]"


id: 9d1f9702b2f8041ee53f8a16de148186
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 24878
content:
"[...] Climate-related changes to extreme events that would lead to these \r severe outcomes include increased frequency and/or magnitude of river \r floods of flash floods due to heavy or long-lasting precipitation, rapid \r snowmelt, or catastrophic failure of glacial lake moraine dams. These \r climate conditions are projected to increase with global warming."


id: c27c942b1a580e153ba5d438321b831a
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 31500
content:
"There is strong potential for increases in water scarcity, flooding, loss of \r snow and ice and changes in water bodies to lead to severe outcomes \r such as deaths from water-related diseases, drowning and starvation, \r long-term health impacts arising from malnutrition and diseases, \r loss of property, loss of existence or access to places of cultural \r significance, loss of livelihoods and loss of aspects of culture especially \r for Indigenous People with traditional lifestyles. The numbers of people \r affected are projected to range from hundreds of millions to several \r billion, depending on the level of global warming and socioeconomic \r futures. A key aspect of the risk is the high uncertainty in future regional \r precipitation changes in many regions of high vulnerability, including \r the potential for large and highly impactful changes, for which it may \r not be possible to provide adaptation measures before they become \r [...]"


id: 84390765b1c2f7e2c8c32f026c5c679
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 20417
content:
"Mobility is a universal strategy for pursuing well-being and managing \r household risks (Section 7.2.6; Cross-Chapter Box MIGRATE in Chapter \r 7, UN, 2018) and, where it occurs in a safe and orderly fashion, can \r reduce social inequality and facilitate sustainable development \r (Franco Gavonel et al., 2021). Involuntary mobility constitutes a key \r risk because it implies reduced human agency with high potential for \r significant economic losses and non-material costs, an unequal gender \r burden, and amplified vulnerability to other RKRs (Schwerdtle et al., \r 2018; Adger et al., 2020; Maharjan et al., 2020; Piggott-McKellar et al., \r 2020). Climate change also may erode or overwhelm human capacity \r to use mobility as a coping strategy, producing involuntarily immobile \r populations (Adams, 2016). A severe impact is when a large share of \r an affected population is forcibly displaced or prevented from moving, \r relative to normal mobility patterns, at local to global scale. However, \r [...]"


id: db9429466b181c0a69ca6a075cd06617
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 35916
content:
"[...] because mobility may be a favourable mechanism for reducing risk or \r an adverse outcome of risk, depending on the circumstances under \r which it occurs, it is not possible to specify a simple quantitative \r threshold for when impacts become severe."


id: f61de3734f9c57e76e43cf5e4af61a97
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 40659
content:
"Complex causal pathways and lack of long-term projection studies \r presently prevent making confident quantitative judgements about how \r risks to peace and human mobility will materialise in response to specific \r warming levels, development pathways and adaptation scenarios. \r Literature concludes with medium confidence that risks to peace will \r increase with warming, with the largest impacts expected in weather\u0002sensitive communities with low resilience to climate extremes and high \r prevalence of underlying risk factors (Theisen, 2017; Busby, 2018; Koubi, \r 2019; von Uexkull and Buhaug, 2021). However, climate-driven impacts \r on societies will depend critically on future political and socioeconomic \r development trajectories (limited evidence, high agreement), suggesting \r that risks due to climate change are relevant primarily for highly \r vulnerable populations and for pessimistic development scenarios. \r Overall risks to peace may decline despite warming if non-climatic \r [...]"


id: 25f81676dbec1384cf6928f4f4333007
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 3858
content:
"Climatic risks interact with economic, political and social drivers to \r create risks to human mobility both directly (through the threat of \r physical harm and destruction of property and infrastructure) and \r indirectly (via adverse impacts on livelihood and well-being). Extreme \r weather events are leading causes of forced displacement (Cross\u0002Chapter Box MIGRATE in Chapter 7, IDMC, 2020). Projected increases in \r the frequency and severity of extreme events ( Ranasinghe et al., 2021) \r in combination with future population growth in hazard-prone regions \r (e.g., Merkens et al., 2016) suggest that risks to mobility will increase \r in response to future global warming (Robalino et  al., 2015; Davis \r et al., 2018; Rigaud et al., 2018). For example, moving from RCP2.6 \r to RCP8.5 (entailing ~0.5degC additional global warming by 2050) is \r projected to increase internal migration by 2050 from 51 [31-72] \r million to 118 [92-143] million people across South Asia, Latin America \r [...]"


id: d3217b73243a549cf108053fbccfdee8
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 34489
content:
"[...] and Africa (Rigaud et al., 2018), although those estimates principally \r comprise migrants, whose decisions are also informed by non-climatic \r drivers, rather than involuntarily displaced people. Global levels of \r flood displacement are estimated to increase by 50% with each 1degC \r warming (Kam et al., 2021). Should future warming reduce adaptation \r options for vulnerable populations ( Section 16.4), a consequence may \r be higher levels of involuntary migration and immobility (Grecequet \r et  al., 2017; Otto et  al., 2017). There is little evidence that climate\u0002driven mobility negatively affects peace (Brzoska and Frohlich, 2016; \r Burrows and Kinney, 2016; Freeman, 2017; Petrova, 2021)."


id: 576a7dedec1e2a93391be0e0ddc2f952
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 12643
content:
"Regular human mobility will continue regardless of climate change, \r but mobility-related risks will increase with warming, notably in \r densely populated hazard-prone regions, in small islands and low-lying \r coastal zones, and among populations with limited coping capacity \r (RKR-A; Section CCP2.2.2; Chapter 7) (high confidence). Such risks can \r become severe even with limited levels of warming for populations \r with low adaptive capacity and whose settlements and livelihoods are \r critically sensitive to environmental conditions (medium evidence, high \r agreement). Likewise, risk of involuntary immobility could become \r severe for highly vulnerable populations with limited resources, even \r with moderate levels of warming (limited evidence, high agreement). \r Critically, population growth and shifting exposure will interact with \r warming to shape these risks (Davis et al., 2018; Hauer et al., 2020; \r Robinson, 2020a). Although climate-driven human mobility generally \r [...]"


id: 63fb166ead00524b0497e443d0f6a839
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 14879
content:
"[...] does not increase risks to peace (medium confidence), armed conflict \r is a major driver of forced displacement (high confidence)."


id: 3e58c35bb3e2fa87fae50c6e7689832
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 8146
content:
"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 \r of people. Details of confidence levels and scopes can be found in Section 16.5.2.3. In terms of severity condition levels (Section 16.5.2.3), for warming levels (coloured circles \r 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 \r 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, \r 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 \r [...]"


id: e5994fc55709efc03331a58666fb9a0c
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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vector_id: 37703
content:
"Some ecological risks (Chapter 2) are particularly sensitive to warming. \r For example, warm-water coral reefs are already experiencing High risk \r levels and are expected to face Very High risks under 1.5degC of glob\u0002al warming (Hoegh-Guldberg et al., 2018a; Bindoff et al., 2019). Some \r societal risks, such as human mortality due to extreme heat, also are \r sensitive to warming. A medium-warming scenario (relative to high \r warming) reduces projected global average mortality due to heat \r from seven deaths per 10,000 people yr-1 (7/10,000 yr-1) by 2100 to \r ~1/10,000 yr-1, assuming high-vulnerability societal conditions (Carle\u0002ton et al., 2020). At the national level, without considering adaptation, \r reductions in a broader measure of mortality are projected across a \r range of countries including Colombia, the Philippines, and several in \r Europe (Guo et al., 2018), and exposure of the US population to high\u0002mortality heatwaves is reduced by nearly half (Anderson et al., 2018a). \r [...]"


id: 2a40f5a6235907ab2905e0f2883cdd02
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"[...] Without considering changes in exposure or vulnerability, warming of \r 1.5-2degC (compared with 4-5degC) reduces global mortality impacts from \r an increase of 2.1-13.0% to 0.1-2.2% (Gasparrini et al., 2017; Vicedo\u0002Cabrera et al., 2018a) and impacts in China from up to 4/10,000 yr-1\r (Weinberger et al., 2017) to 0.3-0.5/10,000 yr-1 (Wang and Hijmans, \r 2019)."


id: 5888988b305b5e835375066f354488f5
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 12823
content:
"One approach to understand adaptation benefits for risk reduction is \r to contrast projected impacts for the same climate and development \r conditions but different levels of adaptation. For example, global-scale \r coastal protection studies considering both RCPs and SSPs suggest \r that, under a given RCP, the total flooded area may be reduced by 40% \r by using 1-m height dykes, compared with a no-adaptation baseline \r (Tamura et al., 2019). The global cost of SLR over the 21st century can be \r lowered by factor of two to four if local cost-benefit decisions consider \r migration an adaptation option, in addition to hard protection (Lincke \r and Hinkel, 2021). Under a low-warming scenario, it is estimated that \r adaptation (i.e., changes in crop variety and planting dates) could \r reduce the total number of people at risk of hunger globally by about \r 4%, and by about 10% in a high-warming scenario (Hasegawa et al., \r 2014). Impacts on heat-related mortality would be cut from 10 to 7 \r [...]"


id: 4a263a34fc6c0b78a51a7f7871dc945b
created_at: 2023-04-19 13:23:03
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content:
"[...] deaths per 10,000 people yr-1 in 2100 by adaptation actions beyond \r those assumed to be driven by income growth (Carleton et al., 2020). \r In a regional example, proactive adaptation efforts on infrastructure \r (especially roads, runways, buildings and airports) in Alaska, USA, \r could reduce damage-related expenditure by 45% under medium or \r high warming (Melvin et al., 2017)."


id: c219779296cf0bffb84a32e5acc6838
created_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"Another approach infers the potential future effectiveness of \r adaptation based on current sensitivity of impacts to interventions. \r For example, the future disease burden of malaria is likely to be \r highly dependent on the future development of health services, \r deployment of malaria programs and adaptation. Investments in \r water and sanitation infrastructure are also recognised to have the \r potential to reduce severe risks of waterborne disease, although \r these improvements likely need to provide transformative change \r (Cumming et al., 2019). The potential for severe risks may also be \r substantially reduced through the development of vaccines for \r specific enteric diseases (Riddle et al., 2018), although most current \r vaccines target viral pathogens, incidence for which tends to be \r inversely correlated with ambient temperature (Carlton et al., 2016). \r In addition, international migration as well as forced movement \r [...]"


id: b6262f8d38402e85170a049339dee44e
created_at: 2023-04-19 13:23:03
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content:
"[...] of people across borders will be influenced by developments in \r legal and political conditions (McLeman, 2019; Wrathall et  al., \r 2019), but the fact that these developments are unknown strongly \r limits any forecasts on the magnitude of adaptation benefits \r (Section 16.5.2.3.8)."


id: 8fa9f4a3493aad0eb9b8d74d395383a8
created_at: 2023-04-19 13:23:03
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content:
"While climate change will increase risk to society and ecosystems, \r future exposure and vulnerability conditions will also greatly impact \r outcomes of concern directly. Global economic damages to coastal \r assets from tropical cyclones are projected to increase by more than \r 300% due to coastal development alone, a much larger effect than \r projected climate change impacts through 2100 even in RCP8.5 \r (Gettelman et al., 2018). Similarly, global crop prices are more than \r three times more sensitive to alternative assumptions about changes \r in production technologies and demand than to alternative climate \r outcomes (Ren et al., 2016). Future water scarcity is driven mainly by \r both demographic change and socioeconomic changes affecting water \r demand and management. A measure of between-country inequality \r (Gini coefficient) would decline by more than 50% this century in \r low-vulnerability conditions, but would double in a high-vulnerability \r [...]"


id: 12cb28300acff9348dcfe470288cedc0
created_at: 2023-04-19 13:23:03
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content:
"[...] future (Crespo Cuaresma, 2017), outweighing the effect of climate \r (Taconet et al., 2020). Similarly, the global prevalence of armed conflict \r will roughly double this century in a high-vulnerability future, whereas \r it will drop by half in a low-vulnerability future (Hegre et al., 2016). In \r Sub-Saharan Africa, assumptions about governance and political rights \r are estimated to be far more important to the future risk of violent \r conflict than climate change (Witmer et al., 2017)."


id: 8a13fc08ea6289c7fbd18e08e3c5cbe4
created_at: 2023-04-19 13:23:03
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content:
"In terms of salt-water intrusion and salinisation, global comparative \r studies are still lacking but the general processes are well understood \r (e.g., White and Kaplan, 2017), and research on individual deltas is on \r the rise. In the Mekong Delta of Vietnam, one of the main rice-producing \r deltas globally, salinity intrusion has been observed to extend around \r 15 km inland during the rainy season and around 50 km during the dry \r season (Gugliotta et al., 2017), resulting in rice yield losses of up to 4 \r t ha-1 yr-1 (Khat et al., 2018). SLR, along with the expansion of dams \r and dry season irrigation upstream, is expected to further increase the \r salinity intrusion into the delta. This creates additional risk for food \r production as rice and other crops might be pushed beyond their \r adaptation limits in terms of salt tolerance, potentially affecting many \r of the 282,000 agriculture-based livelihoods in the Mekong Delta \r [...]"


id: e50617345018bf6a5b945be9950e2caa
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content:
"[...] and increasing the pressure for cost-intensive adaptation (Smajgl \r et  al., 2015). Genua-Olmedo et  al. (2016) find for the Ebro that in \r high scenario (RCP8.5, and SLR of almost 1 m by 2100), SLR-induced \r salinity intrusion will lead to almost a doubling of salinity levels and a \r decrease of mean rice productivity by over 20% in a high-SLR scenario \r with almost 1 m of SLR by the end of the century."


id: 64317498e8b24720580bb6d8d015654d
created_at: 2023-04-19 13:23:03
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vector_id: 14913
content:
"Large deltas, which are very dynamic risk hotspots of global importance \r and interest (Wigginton, 2015; Hill et al., 2020; Nicholls et al., 2020), \r serve well to illustrate how risk pathways develop over time, determined \r by climatic as well as non-climatic risk drivers and by adaptation. Deltas \r occupy less than 0.5% of the global land area but host over 5% of the \r global population (Dunn et al., 2019) and contribute major fractions of \r food production in many world regions (Kuenzer et al., 2020). Future \r risk in these areas is heavily driven by climate change but also greatly \r depends on past, current and future socioeconomic changes which \r influence future trends in exposure, vulnerability and adaptive capacity \r of natural and human systems (high confidence) (Oppenheimer et al., \r 2019). From a risk perspective, trends over the past decades have been \r unfavourable for many deltas, as most of them have experienced a \r [...]"


id: fad8ca1aa75586e03183b30ff54c66b9
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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vector_id: 41512
content:
"[...] simultaneous intensification of hazards, rise in exposure and stagnation \r or only limited reduction in vulnerability, particularly in low-income \r countries (high confidence) (Day et al., 2016; Tessler et al., 2016; Loucks, \r 2019; Oppenheimer et al., 2019; Hill et al., 2020)."


id: 3fb71c66733cb6829d666a98a3cfe24f
created_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"Next to the trends in hazards, future exposure of and in deltas is shaped \r particularly by the increase of population and infrastructure and the \r intensification of land use. Over the recent years, the population has been \r rising in major deltas, roughly along with overall national population \r trends (Szabo et al., 2016). In 2017, 339 million people lived in deltas \r with a high exposure to flooding, cyclones and other coastal hazards \r (Edmonds et  al., 2020). Over 40% of the global population exposed \r to flooding from tropical cyclones lived in deltas, more than 90% of \r which in developing countries and emerging economies (ibid.). Looking \r into the future, population in low-elevation coastal zones is expected \r to increase by 2050 across all SSPs with diverging developments in the \r second half of the century, and at the end of the century will reach well \r over 1 billion people in SSP3 (Jones and O'Neill, 2016; Merkens et al., \r [...]"


id: 77a6c086648032831c68d242ca06aa8d
created_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 18255
content:
"[...] 2016). A major part of this population is expected to reside in deltas \r with large cities or mega-urban agglomerations such as the Pearl River \r Delta, China. One of the first studies using the SSP-RCP framework on \r the delta scale suggests a strong increase in intensive agricultural land \r by the middle of the century in three SSPs (2, 3, 5) in the Volta Delta, \r Ghana, while the Mahanadi, India, and the Ganges-Brahmaputra-\r Meghna do not show a significant further increase (Kebede et  al., \r 2018). Hence, the amount of population and infrastructure as well as \r agricultural land is expected to rise further under certain SSPs, further \r increasing the exposure to future climate hazards."


id: dd96b4c530356215132dfdc17e662290
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 36252
content:
"Deltas face multiple interacting hazards, many of which over the past \r decades have been intensified by local and regional anthropogenic \r developments (e.g., the construction of dams, groundwater extraction, \r or agricultural irrigation practices) and most of which are expected \r to be exacerbated by climate change (high confidence) (Giosan \r et al., 2014; Tessler et al., 2015; Tessler et al., 2016; Arto et al., 2019; \r Oppenheimer et al., 2019). The most important hazards include SLR, \r inundation, salinity intrusion, cyclones, storms and erosion, many of \r which occur in combination. The potential for flooding and inundation \r depends on the relative sea level rise (RSLR) which results from \r global and regional SLR as well as local subsidence within the deltas. \r Subsidence caused by natural and human drivers (mainly compaction \r and groundwater extraction) is currently the most important cause for \r RSLR in many deltas and can exceed the rate of climate-induced SLR \r [...]"


id: 6cfe63dee3e4804bf144a2e638ecbd9e
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 16457
content:
"[...] by an order of magnitude (Oppenheimer et al., 2019). But in higher \r warming scenarios the relative importance of climate-driven SLR is \r expected to increase over time (Oppenheimer et al., 2019). In a global \r study covering 47 major deltas and assessing future trends of sediment \r delivery across four RCPs, three SSPs (1,2,3) and a projection of future \r dam construction, Dunn et al. (2019) find most deltas (33 out of the \r 47) will experience a mean decline of 38% in sediment flux by the end \r of the century when considering the average of the scenarios. Nienhuis \r et al. (2020) find in a global assessment that some deltas have gained \r land through increased sediment load (e.g., through deforestation), \r but recent land gains are unlikely to be sustained if SLR continues to \r accelerate. According to the latest assessments, it is virtually certain \r that global mean sea level will continue to rise over the 21st century, \r [...]"


id: ba0482055a5b41e2a662037a4f0d3785
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 29949
content:
"[...] with SLR by 2100 likely to reach 0.28-0.55 m in a an SSP1-1.9 and \r 0.63-1.01 m in an SSP5-8.5 scenario relative to 1995-2014 (IPCC, \r 2021). The combined effects of local subsidence and GMSL rise result \r in a significant increase in the potential for inundation of low-lying \r deltas across all RCPs, with some variation according to regional sea \r level change rates, without significant further adaptation measures \r (very high confidence)."


id: d154fda35e59faa0cef03bfd3f4f09fb
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 34180
content:
"living standards, food security and water security (RKR-D, RKR-F, RKR-G, \r respectively). Increased poverty, increased hunger and limited access to \r drinkable water are well-known drivers of poor health conditions. The \r role of impact cascades is even more prominent in the case of peace \r and human mobility (RKR-H), even though the scientific literature \r does not conclude on any clear and direct climate influence on armed \r conflict and human migration. Rather, climate-induced degradation of \r natural resources that are vital for subsistence agriculture and fisheries, \r transformational and long-term consequences on livelihoods (e.g., \r new risks, increasing precarious living conditions, gendered inequity, \r etc.), and erosion of social capital due to exacerbated tension within \r and between communities are considered among the main drivers of \r armed conflicts and forced displacement, therefore highlighting links \r [...]"


id: 67be40bc29a24e0978dc425e39ebd99b
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 15522
content:
"Multiple feedbacks between individual risks exist that have the \r potential to create cascades (WEF, 2018; IPCC, 2019c p. 680; Simpson \r et  al., 2021) and then to amplify systemic risks and impacts far \r beyond the level of individual RKRs (medium confidence). Scientific \r research, however, remains limited on whether such interactions \r would result in increasing or decreasing the initial impact(s), and \r hence risk severity across systems. Given the scope of this chapter on \r increasing risk severity, here we focus on assessing RKR interactions \r that lead to increasing risk. Drawing directly on RKR assessments \r (Sections 16.5.2.3.2-16.5.2.3.8), this section cites those assessments \r rather than primary literature. The arrows in Figure 16.11 are derived \r from a qualitative analysis by three authors of Chapter 16 of the material \r provided by chapters on KRs and RKR assessments (Section 16.5.2.3), \r and do not result from any systematic and quantitative approach as \r [...]"


id: e577490b2aca7a4eb5921a3ac950b178
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 37677
content:
"Interactions at the RKR level (Figure 16.11, panel A)--climate change \r will combine with pre-existing socioeconomic and ecological conditions \r (grey blocks on the left-hand-side of panel A in Figure  16.10) to \r generate direct and second-order effects (black plain arrows) both on \r the structure and/or functioning of ecosystems (RKR-B) and on some \r natural processes such as the hydrologic cycle (RKR-G), for example. This \r then translates into implications not only for biodiversity but also for \r natural resources that support livelihoods, which will in turn affect food \r security (especially food availability; RKR-F), water security (especially \r access to adequate quantities of acceptable quality water; RKR-G) \r and the living standards of already vulnerable groups and aggregate \r economic outputs at the global level (RKR-D). CIDs (IPCC, 2021) will \r also directly affect infrastructure that are critical to ensure some basic \r [...]"


id: b906a016fb8ad1bf38b1a9b1d1999895
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index: climate_gpt_v2
vector_id: 29756
content:
"[...] conditions for economies to function (RKR-C), for example through \r transportation within and outside the country, energy production \r and international trade. Such disturbances to socioecological systems \r and economies pose climate-related risks to human health (RKR-E) as \r well as to peace and human mobility (RKR-H). Indeed, while health \r is concerned with direct influence of climate change, for example \r through hotter air temperatures impacting morbidity and mortality or \r the spatial distribution of disease vectors such as mosquitos, it is also \r at risk of being stressed by direct and secondary climate impacts on "


id: 20f9e6fb6e56c554a50569ba4190fefa
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 3023
content:
"Within the AR6 cycle, the three IPCC Special Reports have all \r considered the relationships between climate change impacts and \r actions and the SDGs. SR15 discussed priorities for sustainable \r development in relation to climate adaptation efforts (Section 5.3.1, \r SR15); synergies and trade-offs of climate adaptation measures \r (Section 5.3.2, SR15); and the effect of adaptation pathways towards \r a 1.5degC warmer world (Section 5.3.3 SR15). The SRCCL considered \r impacts of desertification on SDGs 1 (no poverty), 2 (zero hunger), 13 \r (climate), 15 (life on land) and 5 (gender) (IPCC, 2019a, Figure 3.9). \r Trade-offs and synergies between SDGs 2 (zero hunger) and 13 \r (climate action) at the global level were recognised (IPCC, 2019a, \r Section  5.6.6, Figure  5.16). Various integrated response options, \r interventions and investments were also evaluated within the SDG \r framework (IPCC, 2019a, Section  6.4.3). The SROCC (Chapter 5) \r [...]"


id: ad7df0b0147836586ee82d5a360eb702
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index: climate_gpt_v2
vector_id: 27764
content:
"[...] concluded that climate change impacts on the ocean, overall, will \r negatively affect achieving the SDGs, with 14 (life below water) \r being most relevant (Singh et al., 2019)."


id: 96e1da04584da5ebdfcf3cad0bd86c6
created_at: 2023-04-19 13:23:03
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vector_id: 23741
content:
"There is high agreement in the literature that for addressing climate change risks SRM cannot be the main policy response to climate \r change and is, at best, a supplement to achieving sustained net zero or net negative CO2 emission levels globally (de Coninck et al., 2018; \r MacMartin et al., 2018; Buck et al., 2020; National Academies of Sciences and Medicine, 2021b). SRM contrasts with climate change \r mitigation activities, such as emission reductions and carbon dioxide removal (CDR), as it introduces a 'mask' to the climate change \r problem by altering the Earth's radiation budget, rather than attempting to address the root cause of the problem, which is the increase \r in greenhouse gases (GHGs) in the atmosphere. In addition, the effects of proposed SRM options would only last as long as a deployment \r is maintained--for example, requiring ca. yearly injection of aerosols in the case of SAI as the lifetime of aerosols in the stratosphere \r [...]"


id: 874aad61b313361ae667795d5005e187
created_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 20963
content:
"[...] is 1-3 years (Niemeier et al., 2011) or continuous spraying of sea salt in the case of MCB as the lifetime of sea salt aerosols in the \r atmosphere is only about 10 d--which contrasts with the long lifetime of CO2 and its climate effects, with global warming resulting from \r CO2 emissions likely remaining at a similar level for a hundred years or more (MacDougall et al., 2020) and long-term climate effects of \r emitted CO2 remaining for several hundreds to thousands of years (Solomon et al., 2009)."


id: 6e96327c7d449fb6e5d7924a7a0b28f7
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 16720
content:
"In the context of reaching the long-term global temperature goal of the Paris Agreement, there are different hypothetical scenarios \r of SRM deployment: early, substantial mitigation with no SRM, more limited or delayed mitigation with moderate SRM, unchecked \r emissions with total reliance on SRM, and regionally heterogeneous SRM. Each scenario presents different levels and distributions of \r SRM benefits, side effects and risks. The more intense the SRM deployment, the larger is the likelihood for the risks of side effects and \r environmental risks (e.g., Heutel et al., 2018). Regional disparities in climate hazards may result from both regionally deployed SRM \r options such as GBAM, and more globally uniform SRM such as SAI (Jones et al., 2018a; Seneviratne et al., 2018b). There is an emerging \r literature on smaller forcings of SAI to reduce global average warming, for instance, to hold global warming to 1.5degC or 2degC alongside \r [...]"


id: a51aa38f6ecd7caca4f7fc41cdc09ed4
created_at: 2023-04-19 13:23:03
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content_type: text
index: climate_gpt_v2
vector_id: 26276
content:
"[...] ambitious conventional mitigation (Jones et al., 2018a; MacMartin et al., 2018), or bring down temperature after an overshoot (Tilmes \r et al., 2020). If emissions reductions and CDR are deemed insufficient, SRM may be seen by some as the only option left to ensure the \r achievement of the Paris Agreement's temperature goal by 2100."


id: 475443be59e86539d9acd339484e06cf
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 9757
content:
"There is low confidence and large uncertainty in projected impacts of SRM on crop yields due in part to a limited number of studies. \r Because SRM would result in only a slight reduction in CO2 concentrations relative to the emission scenario without SRM (Chapter 5, \r WGI), the CO2 fertilisation effect on plant productivity is nearly the same in emissions scenarios with and without SRM. Nevertheless, \r changes in climate due to SRM are likely to have some impacts on crop yields. A single study indicates MCB may reduce crop failure rates \r compared with climate change from a doubling of CO2 pre-industrial concentrations (Parkes et al., 2015). Models suggest SAI cooling \r would reduce crop productivity at higher latitudes compared with a scenario without SRM by reducing the growing season length, \r but benefit crop productivity in lower latitudes by reducing heat stress (Pongratz et al., 2012; Xia et al., 2014; Zhan et al., 2019). Crop \r [...]"


id: b52c386e9927ebb8b9bfd1920d867941
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 29112
content:
"[...] productivity is also projected to be reduced where SAI reduces rainfall relative to the scenario without SRM, including a case where \r reduced Asian summer monsoon rainfall causes a reduction in groundnut yields (Xia et al., 2014; Yang et al., 2016). SAI will increase the \r fraction of diffuse sunlight, which is projected to increase photosynthesis in forested canopy, but will reduce the direct and total available \r sunlight, which tends to reduce photosynthesis. As total sunlight is reduced, there is a net reduction in crop photosynthesis with the result \r that any benefits to crops from avoided heat stress may be offset by reduced photosynthesis, as indicated by a single statistical modelling \r study (Proctor et al., 2018). SAI would reduce average surface ozone concentration (Xia et al., 2017) mainly as a result of aerosol-induced \r reduction in stratospheric ozone in polar regions, resulting in reduced downward transport of ozone to the troposphere (Pitari et al., 2014; \r [...]"


id: ae552da7c353d6cb3422e968a9112b90
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 27903
content:
"[...] Tilmes et al., 2018). The reduction in stratospheric ozone also allows more UV radiation to reach the surface. The reduction in surface \r ozone, together with an increase in surface UV radiation, would have important implications for crop yields but there is low confidence\r in our understanding of the net impact."


id: b1ef58b7ec113ded3c66d8520f2a123a
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 28527
content:
"Few studies have assessed potential SRM impacts on human health and well-being. SAI using sulphate aerosols is projected to deplete \r the ozone layer, increasing mortality from skin cancer, and SAI could increase particulate matter due to offsetting warming, reduced \r precipitation and deposition of SAI aerosols, which would increase mortality, but SAI also reduces surface-level ozone exposure, which \r would reduce mortality from air pollution, with net changes in mortality uncertain and depending on aerosol type and deployment \r scenario (Effiong and Neitzel, 2016; Eastham et al., 2018; Dai et al., 2020). However, these effects may be small compared with changes \r in risk from infectious disease (e.g., mosquito-borne illnesses) or food security due to SRM influences on climate (Carlson et al., 2020). \r Using volcanic eruptions as a natural analogue, a sudden implementation of SAI that forced the El Nino-Southern Oscillation (ENSO) \r [...]"


id: 43fec2f4615c41d482893732c1bd17d7
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"[...] system may increase risk of severe cholera outbreaks in Bengal (Trisos et al., 2018; Pinke et al., 2019). Considering only mean annual \r temperature and precipitation, SAI that stabilises global temperature at its present-day level is projected to reduce income inequality \r between countries compared with the highest warming pathway (RCP8.5) (Harding et al., 2020). Some integrated assessment model \r scenarios have included SAI (Arino et al., 2016; Emmerling and Tavoni, 2018; Heutel et al., 2018; Helwegen et al., 2019; Rickels et al., \r 2020) showing the indirect costs and benefits to welfare dominate, since the direct economic cost of SAI itself is expected to be relatively \r low (Moriyama et al., 2017; Smith and Wagner, 2018). There is a general lack of research on the wide scope of potential risk or risk "


id: 89a92284fca63de12043bcde243e34d9
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 21396
content:
"There is large uncertainty in terrestrial ecosystem responses to SRM. By decoupling increases in atmospheric greenhouse gas concentrations \r and temperature, SAI could generate substantial impacts on large-scale biogeochemical cycles, with feedbacks to regional and global \r climate variability and change (Zarnetske et al., 2021). Compared with a high-CO2 world without SRM, global-scale SRM simulations \r indicate reducing heat stress in low latitudes would increase plant productivity, but cooling would also slow down the process of nitrogen \r mineralisation, which could decrease plant productivity (Glienke et al., 2015; Duan et al., 2020). In high-latitude and polar regions, SRM \r may limit vegetation growth compared with a high-CO2 world without SRM, but net primary productivity may still be higher than pre\u0002industrial climate (Glienke et al., 2015). Tropical forests cycle more carbon and water than other terrestrial biomes, but large areas of \r [...]"


id: c6283aecb02641e0c24b96587eed4d85
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 32172
content:
"[...] the tropics may tip between savanna and tropical forest depending on rainfall and fire (Beer et al., 2010; Staver et al., 2011). Thus, SAI\u0002induced reductions in precipitation in Amazonia and central Africa are expected to change the biogeography of tropical ecosystems in \r ways different from both present-day climate and global warming without SAI (Simpson et al., 2019; Zarnetske et al., 2021). This would \r have potentially large consequences for ecosystem services (Chapter 2 and Chapter 9). When designing and evaluating SAI scenarios, \r biome-specific responses need to be considered if SAI approaches are to benefit rather than harm ecosystems. Regional precipitation \r change and sea salt deposition over land from MCB may increase or decrease primary productivity in tropical rainforests (Muri et al., \r 2015). SRM that fully offsets warming could reduce the dispersal velocity required for species to track shifting temperature niches, \r [...]"


id: 5b9bffb1cf7a1ba548f6be005492a153
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 13367
content:
"[...] whereas partially offsetting warming with SAI would not reduce this risk unless rates of warming were also reduced (Trisos et al., 2018; \r Dagon and Schrag, 2019). SAI may reduce high-fire-risk weather in Australia, Europe and parts of the Americas, compared with global \r warming without SAI (Burton et al., 2018). Yet SAI using sulphur injection could shift the spatial distribution of acid-induced aluminium \r soil toxicity into relatively undisturbed ecosystems in Europe and North America (Visioni et al., 2020). For the same amount of global \r mean cooling, SAI, MCB and CCT would have different effects on gross and net primary productivity because of different spatial patterns \r of temperature, available sunlight, and hydrological cycle changes (Duan et al., 2020). Large-scale modification of land surfaces for GBAM \r may have strong trade-offs with biodiversity and other ecosystem services, including food security (Seneviratne et al., 2018a). Although \r [...]"


id: 8b9fef47da4f66ee15508947da85c386
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 21734
content:
"[...] existing studies indicate SRM will have widespread impacts on ecosystems, risks and potential for risk reduction for marine and terrestrial \r ecosystems and biodiversity remain largely unknown."


id: 741504e9208b9ab8024d124415a721b
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 17664
content:
"A sudden and sustained termination of SRM in a high CO2 emissions scenario would cause rapid climate change (high confidence; WGI \r Chapter 4). More scenario analysis is needed on the potential likelihood of sudden termination (Kosugi, 2013; Irvine and Keith, 2020). \r A gradual phase-out of SRM combined with emission reduction and CDR could avoid these termination effects (medium confidence) \r (MacMartin et al., 2014; Keith and MacMartin, 2015; Tilmes et al., 2016). Several studies find that large and extremely rapid warming \r and abrupt changes to the water cycle would occur within a decade if a sudden termination of SAI occurred (McCusker et al., 2014; \r Crook et al., 2015b). The size of this 'termination shock' is proportional to the amount of radiative forcing being masked by SAI. A sudden \r termination of SAI could place many thousands of species at risk of extinction, because the resulting rapid warming would be too fast for \r [...]"


id: 1cec1abee782ae389297ae58dc6a81b
created_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"Studies on the public perception of SRM have used multiple methods: questionnaire surveys, workshops, and focus group interviews \r (Burns et al., 2016; Cummings et al., 2017). Most studies have been limited to Western societies, with some exceptions. Studies have \r repeatedly found that respondents are largely unaware of SRM (Merk et al., 2015). In the context of this general lack of familiarity, the \r public prefers CDR to SRM (Pidgeon et al., 2012), is very cautious about SRM deployment because of potential environmental side effects \r and governance concerns, and mostly rejects deployment for the foreseeable future. Studies also suggest conditional and reluctant \r support for research, including proposed field experiments, with conditions of proper governance (Sugiyama et al., 2020). Recent studies \r show that the perception varies with the intensity of deliberation (Merk et al., 2019), and that the public distinguishes different funding \r [...]"


id: c710c9ce3c3b7d962383bb4b291c7e1f
created_at: 2023-04-19 13:23:03
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content:
"[...] sources (Nelson et  al., 2021). Limited studies for developing countries show a tendency for respondents to be more open to SRM \r (Visschers et al., 2017; Sugiyama et al., 2020), perhaps because they experience climate change more directly (Carr and Yung, 2018). \r In some Anglophone countries, a small portion of the public believes in chemtrail conspiracy theories, which are easily found in social \r media (Tingley and Wagner, 2017; Allgaier, 2019). Since researchers rarely distinguish different SRM options in engagement studies, there \r remains uncertainty in public perception."


id: 9c8db9d30078b95701ec7b7670e465c4
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"There is broad literature on ethical considerations around SRM, mainly stemming from philosophy or political theory, and mainly focused \r on SAI (Flegal et al., 2019). There is concern that publicly debating, researching and potentially deploying SAI could involve a 'moral \r hazard', with potential to obstruct ongoing and future mitigation efforts (Morrow, 2014; Baatz, 2016; McLaren, 2016), while empirical \r evidence is limited and mostly at the individual, not societal, level (Burns et al., 2016; Merk et al., 2016; Merk et al., 2019). There is \r low agreement whether research and outdoors experimentation will create a 'slippery slope' towards eventual deployment, leading \r to a lock-in to long-term SRM, or can be effectively regulated at a later stage to avoid undesirable outcomes (Hulme, 2014; Parker, \r 2014; Callies, 2019; McKinnon, 2019). Regarding potential deployment of SRM, procedural, distributive and recognitional conceptions \r [...]"


id: b53b4ccc0fc8076de9bb042d058aaa9e
created_at: 2023-04-19 13:23:03
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content:
"[...] of justice are being explored (Svoboda and Irvine, 2014; Svoboda, 2017; Preston and Carr, 2018; Hourdequin, 2019). With the SRM \r research community's increasing focus on distributional impacts of SAI, researchers have started more explicitly considering inequality \r in participation and inclusion of vulnerable countries and marginalised social groups (Flegal and Gupta, 2018; Whyte, 2018; Taiwo and \r Talati, 2021), including considering stopping research (Stephens and Surprise, 2020; National Academies of Sciences and Medicine, \r 2021a). There is recognition that SRM research has been conducted predominantly by a relatively small number of experts in the Global \r North, and that more can be done to enable participation from diverse peoples and geographies in setting research agendas and research \r governance priorities, and undertaking research, with initial efforts to this effect (e.g., Rahman et al., 2018), noting unequal power \r [...]"


id: a591cc52a0ad1fb358c5c2f5ed199b93
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"[...] relations in participation could influence SRM research governance and potential implications for policy (Whyte, 2018; Taiwo and Talati, \r 2021; Winickoff et al., 2015; Frumhoff and Stephens, 2018; Biermann and Moller, 2019; McLaren and Corry, 2021; National Academies of \r Sciences and Medicine, 2021b)"


id: a29aa180e1dbbaa8940cef6a300fc77c
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 25825
content:
"Currently, there is no dedicated, formal international SRM governance for research, development, demonstration or deployment (see \r WGIII Chapter 14). Some multilateral agreements--such as the UN Convention on Biological Diversity or the Vienna Convention on \r the Protection of the Ozone Layer--indirectly and partially cover SRM, but none is comprehensive, and the lack of robust and formal \r SRM governance poses risks (Ricke et al., 2013; Talberg et al., 2018a; Reynolds, 2019a). While governance objectives range broadly, \r from prohibition to enabling research and potentially deployment (Sugiyama et al., 2018b; Gupta et al., 2020), there is agreement that \r SRM governance should cover all interacting stages of research through to any potential, eventual deployment with rules, institutions \r and norms (Reynolds, 2019b). Accordingly, governance arrangements are co-evolving with respective SRM technologies across the \r [...]"


id: 7ae7e9f10b79a5628d787a58bb777c77
created_at: 2023-04-19 13:23:03
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vector_id: 18823
content:
"[...] interacting stages of research, development, demonstration and--potentially--deployment (Rayner et al., 2013; Parker, 2014; Parson, \r 2014). Stakeholders are developing governance already in outdoors research, for example for MCB and OAC experiments on the Great \r Barrier Reef (McDonald et al., 2019). Co-evolution of governance and SRM research provides a chance for responsibly developing SRM \r technologies with broader public participation and political legitimacy, guarding against potential risks and harms relevant across a full \r range of scenarios, and ensuring that SRM is considered only as a part of a broader portfolio of responses to climate change (Stilgoe, \r 2015; Nicholson et al., 2018). For SAI, large-scale outdoor experiments even with low radiative forcing could be transboundary, and \r those with deployment-scale radiative forcing may not be distinguished from deployment, such that MacMartin and Kravitz (2019) \r [...]"


id: 4299a57ba7b546dde9339fb85d7e2ff9
created_at: 2023-04-19 13:23:03
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content:
"[...] argue for continued reliance on modelling until a decision on whether and how to deploy is made, with modelling helping governance \r development. For further discussion of SRM governance, see Chapter 14, WGIII."


id: de8ede5f05a2a46cf4676e590807289a
created_at: 2023-04-19 13:23:03
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content:
"Many linkages between SDG 13 (climate action) and other SDGs have \r been identified (very high confidence) (Blanc, 2015; Kelman, 2015; \r Northrop et  al., 2016; Hammill and Price-Kelly, 2017; ICSU, 2017; \r Mugambiwa and Tirivangasi, 2017; Dzebo et  al., 2018; Major et  al., \r 2018; Nilsson et al., 2018; Sanchez Rodriguez et al., 2018). In addition, \r interactions between different climate change actions and SDGs, \r and interactions among SDGs themselves, have also been assessed \r (Nilsson et al., 2016; IPCC, 2018a; McCollum et al., 2018; Fuso-Nerini \r et al., 2019; IPCC, 2019b; Cernev and Fenner, 2020). The Cross-Chapter \r Box GENDER in Chapter 18 assessment indicates the importance of \r gender considerations in achieving success and benefits in adaptation \r efforts. Aligning climate change adaptation to the SDGs could bring \r potential co-benefits and increased efficiency in funding, and reduce \r the gap between adaptation planning and implementation (very high \r [...]"


id: a5bd27a452cb81ce76e035a1d6c87866
created_at: 2023-04-19 13:23:03
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"Progress towards meeting the SDGs has been recognised to be \r able to reduce global disparities and support more climate resilient \r development pathways (IPCC WGII AR5, Chapter 13, p. 818; discussed \r further in Chapter 18). Nevertheless, we are still lagging in achieving the \r 2030 Goals (OECD, 2019; Sachs et al., 2021), and this affects societal \r vulnerability, readiness and risk response capacities (IPCC, 2019a, \r Chapters 6, 7, Chapters 6 and 8, this report). We assess the risk literature \r for linkages between key risks (grouped by RKRs) and the indicators of \r the SDGs (UN, 2015) using text analysis (details in SM16.5) to identify \r the potential level of effect of different risks on the SDGs. Some 940 \r documents were analysed. The SDG status is associated with projected \r climate hazards, also called climatic impact drivers (CIDs) (Ranasinghe \r et  al., 2021) (panel a), and RKRs (panel c), summarising hazard and \r [...]"


id: cebc12839e067893eb7d4e8da71bd30b
created_at: 2023-04-19 13:23:03
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"[...] exposure with vulnerability aspects, as expressed by challenges in \r achieving the SDGs (panel d), on a regional level (Figure 16.12)."


id: 2941964e5f40f284f1b08c94e7090138
created_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 4475
content:
"The analysis of RKR linkages to SDGs is also useful in identifying gaps \r and susceptibilities, especially for developing future climate resilient \r development targets. This aspect is discussed further in Chapter 18. \r Gaps may arise as SDG targets and indicators are not specifically \r focused on systems affected by climate change risks or impacts. For \r example, in the SRCCL Section 7.1.2, Hurlbert et al. (2019) noted the \r absence of an explicit goal for conserving freshwater ecosystems and \r ecosystem services in the SDGs. Such gaps (Tasaki and Kameyama, \r 2015; Guppy et al., 2019) are inevitable as the current SDG targets \r and indicators focus on overall sustainable development. As another \r example, projected increases in frequency and intensity of hot \r temperature extremes are likely to result in increased heat-related \r illness and mortality, yet heat extremes are not called out as an SDG \r indicator under SDGs 3 (good health and well-being) or 13 (climate \r [...]"


id: 95cca881fceae428264c0df69030427c
created_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 23548
content:
"[...] action). The gaps on climate-related metrics for impacts on health \r are just beginning to be evaluated (Lloyd and Hales, 2019, see also \r Section  7.1.6). The current SDG 13 (climate action) targets also do \r not specifically track the possibility of differential impacts on society \r from disasters and extreme weather events (RFC2). For example, the \r first indicator (Section 13.1.1.1), 'Number of deaths, missing persons \r and directly affected persons attributed to disasters per 100,000 \r population', does not include any requirement for disaggregated data, \r unlike several other socioeconomic and population SDG indicators, \r making it difficult to track the different effects that climate-related \r disasters are expected to have on men, women and children across \r different segments of society, relevant for distributional impacts \r (RFC3) (see also Section 8.3, Cross-Chapter Box GENDER in Chapter \r 18). The risk consequences identified and discussed in each RKR \r [...]"


id: 50ecfd688fc9ea8ed4cc8408704ec7d3
created_at: 2023-04-19 13:23:03
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content:
"[...] (Section 16.5.2) provide useful entry points for identifying indicators \r and metrics for monitoring and evaluating specific impacts of key \r climate change risks. In addition, the sector and region chapters have \r considered various adaptation responses relevant to the SDGs (see, for \r example, Sections 3.6, 4.7.5, 5.13.3, 8.2.1.6, 10.6.1, 13.11.4, 14.6.3) \r with relevant metrics for evaluation."


id: 8a9d790cb5113358e3e196e2c0df64b1
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"Linkages between the 17 SDGs and the eight RKRs (Figure  16.12 \r bottom left panel) are mapped to the regional SDG status (Figure 16.12 \r bottom right panel) and related to the CIDs (Figure  16.12 top left \r panel). Interconnections between CIDs and RKRs are complicated by \r the possibility of concurrent weather events, extremes and longer\u0002term trends. Risks are compounded by existing vulnerabilities (Iwama \r et al., 2016; Thomas et al., 2019b; Birkmann et al., 2021) and cascading \r consequences (Pescaroli and Alexander, 2015; Pescaroli and Alexander, \r 2018; Yokohata et al., 2019) (see, for example, Sections 3.4.3.5, 5.12, \r 6.2.6, 7.2.2.2) as well as interactions. The level of challenges faced in \r attaining the SDGs is one metric for assessing vulnerability and lack of \r capacity to manage risks (Cernev and Fenner, 2020). Other metrics are \r also available (Parker et al., 2019; Garschagen et al., 2021b; Birkmann \r [...]"


id: 4cb262c22bc15294423c6821cef4344d
created_at: 2023-04-19 13:23:03
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content:
"[...] et al., 2022). From Figure 16.12, aside from SDG13 (climate action), the \r strongest connections and risk challenges are with zero hunger (SDG2), \r sustainable cities and communities (SDG11), life below water (SDG14), \r decent work and economic growth (SDG8), no poverty (SDG1), clean \r water and sanitation (SDG6) and good health and well-being (SDG3) \r (high confidence). Other SDGs have strong linkages with specific RKRs, \r for example, terrestrial and marine ecosystems with life on land (SDG15); \r infrastructure (RKR-C) with industry, innovation and infrastructure (SDG9) \r and affordable and clean energy (SDG7); living standards (RKR-D) with "


id: e15ff4f28fd378cbf4a21d2d178b53d3
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"We draw important distinctions between RFC and RKR. First, RFCs \r assess risks that might be of global concern, while RKRs also include \r risks that may be of concern only locally or for specific population \r groups (Figure 16.13). RFCs focus on the full range of increasing risk, \r and locate transitions between four categories of risk: undetectable, \r moderate, high, and very high. RKRs focus on severe risks, and attempt \r to elaborate when/where severe impacts may occur. RKR assessments \r focus on the conditions under which some risks would become severe \r over the course of this century, while RFCs evaluate changes in risk \r levels against gradual increase in temperature levels. The RKR analysis \r used specific definitions of severity including quantified thresholds \r where possible, and this is distinct from the approach based on the \r combined elements of risk used in the RFC expert elicitation process. \r Severity as defined in the RKRs is associated with high or very high \r [...]"


id: d6a440918d368c1bc611a978b4ad3408
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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vector_id: 35067
content:
"[...] risk levels but does not align precisely with either of those categories, \r and a further difference arises from a more explicit emphasis on \r irreversibility and adaptation limits in the very high risk category in the \r RFCs. Thus, RKR and RFC neither map directly to one another in terms \r of content, nor in terms of the response metric."


id: aa66fc4e4ac75719abb64bf97616b492
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index: climate_gpt_v2
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content:
"The treatment of vulnerability and adaptation is different in the RKR \r and RFC assessments. The RKR assessment considered specifically three \r alternative levels of vulnerability, whereas the RFC process did not \r explicitly differentiate risk by level of vulnerability. Therefore, the global \r warming levels at which the various RKR assessments identify risk of \r severe impacts are not directly comparable to risk transitions identified \r in the RFC assessments. In addition, RKRs consider implications of \r low versus high adaptation in order to illustrate the potential role of \r ambitious adaptation efforts to limit risk severity; RFCs consider risks in \r a no/low adaptation scenario only, although there is some discussion \r of the potential role of adaptation in assessing the transition to very \r high risk. Last, both RKRs and RFCs focus on the 21st century scale, \r though recognising risk will continue to increase after 2100, but treat \r [...]"


id: 7b37cb83c6a3096cc2489341f3a85190
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 18876
content:
"[...] this timing issue differently: RKRs assess severe risks over the course \r of this century and distinguish risks that are already severe, that will \r become severe by the mid-century, or that will become severe by the \r end of the century; while RFCs assess risk level irrespective of their \r timing, but according to different temperature levels."


id: 57c2e9f8b8bd01f86221e1c45373dc81
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 12701
content:
"high, and very high) reached at various levels of global average \r warming are informed by evidence of observed impacts illustrated \r in Section 16.2 and variations in individual key risks under different \r scenarios of climate change, socioeconomics and adaptation effort \r in Section  16.5. We follow the methodological advances from \r SRCCL Chapter 7 (Hurlbert et  al., 2019), which used an expert \r elicitation protocol for developing the burning embers (Zommers \r et  al., 2020). Specifically, we used expert participants from within \r the AR6 author team and a protocol based on the modified Delphi \r technique (Mukherjee et  al., 2015) and the Sheffield Elicitation \r Framework (Oakley and O'Hagan, 2010; Gosling, 2018). This \r approach (Figure  16.14) includes a two-round elicitation process \r with a first round of independent anonymous judgements about \r the global warming level at which risk levels transition from one \r [...]"


id: 49796e59023fd1d71ada7d12bf5ab58d
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index: climate_gpt_v2
vector_id: 10151
content:
"[...] to the next, and a final round of group discussion and deliberation \r to develop consensus. The results are then reported, and additional \r references are made to findings from other relevant chapters in this \r report. Then, authors who had not participated in the elicitation as \r part of independent appraisal review the results."


id: f3161993ede49a24a3746c43eb98120f
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 40149
content:
"The RFC assessment reflects the latest understanding of warming \r reported in WGI AR6. Global surface temperature was 1.09 [0.95 to \r 1.20]degC higher in 2011-2020 than 1850-1900, with stronger warming \r over land (1.59 [1.34 to 1.83]degC) than over the ocean (0.88 [0.68 to \r 1.01]degC) (WGI AR6 Cross Chapter Box 2.3 Table 1, Eyring et al. in Gulev \r et al., 2021). Warming levels are commonly reported and studied in the \r impacts literature using two scales of spatially averaged temperature rise, \r global surface air temperature (GSAT), commonly produced by General \r Circulation Models (GCMs) when projecting climate changes, and global \r mean surface temperature (GMST), commonly used in empirical studies. \r Both have the same reference point of pre-industrial of 1850-1900. \r The ember diagrams presented here use GSAT, which is consistent with \r most literature of projected risk (largely based on the output of climate \r models). To the extent that the embers also draw on the observed \r [...]"


id: 339bb7beed0d22c5a2233adeea358613
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index: climate_gpt_v2
vector_id: 6328
content:
"[...] impacts literature using GMST, this potential variation is minimal as the \r average levels of GSAT and GMST have been shown to match closely (for "


id: 41a9f750f895548655430fce673bdc9e
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 8742
content:
"representing high and very high biodiversity risk, respectively (medium \r confidence) (Section 2.5.4). Similarly, WGI AR6 finds that 'Over the 21st \r century and beyond, abrupt and irreversible regional changes in the \r water cycle, including changes in seasonal precipitation, streamflow \r and aridity, cannot be excluded'. Thus, information about irreversibility \r provides information about the potential outcome of temperature \r overshoot scenarios. Other types of losses, such as loss of human or \r species life, are irreversible even if the loss process ceases in the future. \r The less resilient a system is, the more likely it is to suffer irreversible \r damage during a temperature overshoot; the more resilient it is, the \r more likely it is to be able to withstand the overshoot or recover \r afterwards. Very high levels of risk, as assessed here in the RFC, are \r associated with a wide range of criteria for risk assessment including \r [...]"


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"[...] irreversibility. While not all very high risks are irreversible, in general, \r risks reaching a very high level include a component of irreversible \r risks that would persist during and after an overshooting of a given \r temperature level."


id: 5931a5780406329f603a096a80350e3a
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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content:
"systems respond when a transient level of warming is first reached, \r and then further, how they continue to develop if that transient level of \r warming is then maintained indefinitely). We note that this important \r factor is captured in the RFC assessment (and ember diagrams), since the \r timing of risk accrual is one of the criteria for the assessment of the level \r of risk (Section 16.5.1). Risks that are known to evolve only over very \r long-time scales contribute less to the level of risk than those which are \r known to occur rapidly. This is because SLR also depends on the dynamics \r of global warming, including the rate of change of radiative forcing, and \r time lags of several decades, including between atmospheric and ocean \r warming, and in reaching equilibrium sea level state (Oppenheimer \r et al., 2019; Fox-Kemper et al., 2021). However, longer-term risks that \r would arise if those transient temperatures were maintained are also \r [...]"


id: 56c9555f5af9c9d288c679e2fe05ce59
created_at: 2023-04-19 13:23:03
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"[...] included, and this is particularly important in RFC5 (large-scale singular \r events). Note that risks that take place over a very long time scale are \r considered to be of lower concern than more imminent risks. However, \r changes of very large magnitude can still be very important even if far \r away in time, especially if these changes are irreversible (or reversible \r only on extremely long time scales) (see Section 16.5.1)."


id: d0b9e94dff4c9091a5b406444e4833f5
created_at: 2023-04-19 13:23:03
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content:
"Although the embers do not indicate the decade in which certain \r risks are projected to occur, clearly this depends strongly on the level \r of mitigation action as well as the degree of adaptation. Hence, the \r ember diagram (Figure 16. 15 ) is shown alongside a graphic illustrating \r possible global temperature time series emerging from alternative future \r scenarios assessed by WGI AR6 which imply different levels of mitigation \r effort. For example, in a scenario with a high level of mitigation effort \r (SSP1-1.9) reaching net zero emissions in the 2050s, it is extremely likely\r that global warming remains below 2degC and more than 50% likely that it \r will remain below 1.6degC (AR6 WGI 4.3.1.1, Meinshausen et al., 2020). On \r the other hand, a level of 2degC warming is extremely likely to be exceeded \r during the 21st century under the three scenarios assessed by WGI AR6 \r [...]"


id: cd4bc63dd66399f49663968d6c72b605
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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content:
"[...] in which GHG emissions do not fall below current levels before mid\u0002century (i.e., SSP2-4.5, SSP3-7.0, SSP-8.5) (WGI AR6 4.3.1.1, Lee et al., \r 2021). WGI AR6 has assessed that 'global surface temperature averaged \r over 2081-2100 is very likely to be higher by 1.0degC-1.8degC under the \r lowest CO2 emission scenario considered in this report (SSP1-1.9) and \r by 3.3degC-5.7degC under the highest CO2 emission scenario (SSP5-8.5)'. \r However, almost all scenarios assessed by IPCC AR6 WGI reach 1.5degC \r global warming level in the early 2030s (WGI AR6 SPM, IPCC, 2021)."


id: 1911ab9ec4e98c97681ee07badb4e8fd
created_at: 2023-04-19 13:23:03
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content:
"The ember diagrams in Figure 16. 15 capture only the risks arising from \r exposure of vulnerable socio-ecological systems to climatic hazards \r across a range of socioeconomic futures. They do not capture any \r risk component arising solely from changes in population or level of \r development. Importantly, they also do not capture additional risks \r that may arise from the human response to climate change, including \r climate change mitigation or unintended negative consequences of \r adaptation-related responses (i.e., maladaptation) (Section  17.5.1). \r Such risks are discussed in SRCCL Chapter 7, for example, adverse \r effects of the very large-scale use of land and water for primary \r bioenergy production on food production and biodiversity (Hurlbert \r et al., 2019). Contributions of mitigation or maladaptation to risk can \r be important, however, and are discussed further in the context of \r specific RFCs in Section 16.6.3. In general, such components of risk are \r [...]"


id: e8c334dadd4720b7aefff3404c14d805
created_at: 2023-04-19 13:23:03
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content:
"[...] difficult to quantify, and can be minimised by good design of climate \r change mitigation and adaptation. Thus, the effect is excluded from \r the ember diagrams to allow a clearer representation of the accrual of \r climate change risk with global warming."


id: 352dca008e12d8cb9cf4b5dec6b24803
created_at: 2023-04-19 13:23:03
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content:
"AR5 Oppenheimer et al. (2014) defined 'emergent risk' as a risk that \r arises from the interaction of phenomena in a complex system. While \r emergent risk is a relevant consideration for this RFC risk assessment, \r this type of risk has not been explicitly accounted for in the burning \r ember assessment because of the limited literature basis. Unlike known \r or identified risks, emergent risks are characterised by the uncertainty \r of consequences and/or probabilities of occurrence. The International \r Risk Governance Council (IRGC) suggests three categories of emergent \r risks: (1) high uncertainty and a lack of knowledge about potential \r impacts and interactions with risk-absorbing systems; (2) increasing \r complexity, emergent interactions and systemic dependencies that \r can lead to nonlinear impacts and surprises; and (3) changes in \r context (for example, social and behavioural trends, organisational \r settings, regulations, natural environments) that may alter the nature, \r [...]"


id: eaf5cdac61dc0bddec8fe625b91510ab
created_at: 2023-04-19 13:23:03
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content:
"The concept of temperature overshoot, defined as 'exceedance of a \r specified global warming level followed by a decline to or below that \r level during a specified period of time' is a relevant consideration for \r this RFC risk assessment; however, the effect of overshoot has not \r explicitly been considered in the burning ember assessment because \r of the limited literature basis. However, despite the lack of directly \r assessed overshoot scenarios, the current literature provides several \r salient examples of irreversible changes that are projected to occur \r once global temperatures reach a particular level. For example, coral \r reefs are unable to survive repeated bleaching events that are too close \r together, leading to irreversible loss of the reefs even if bleaching were \r to cease (see Section 16.6.3.1 RFC1). Species extinction is irreversible, \r and Chapter 2 assesses that, at ~1.6degC, >10% of species are projected \r [...]"


id: 7d6ef1b5ecf3af571cfd523cab72f3f
created_at: 2023-04-19 13:23:03
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"In this section, we present the results of the expert elicitation in the \r form of the burning embers diagram, alongside a description of the \r recent literature and scientific evidence for each of the RFCs in turn. The \r consensus transition values are illustrated in Figure 16. 15 , an updated \r version of the burning embers diagram that describes the additional \r risk due to climate change for each RFC when a temperature level \r is reached and then sustained or exceeded (Table SM16.20 presents \r the consensus values of the transition range and median estimate in \r terms of global warming level by risk level for each of the five RFC \r embers). The shading of each ember provides a qualitative indication \r of the increase in risk with temperature, and we retain the colour \r scheme employed in the most recent versions of this figure, where \r white, yellow, red and purple indicate undetectable, moderate, high \r and very high additional risk, respectively. These transitions were \r [...]"


id: 5f0bf9ac255246bdd1538b3f3f707a39
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"[...] assessed under conditions of low to no adaptation compared with \r today, in accordance with definitions provided in 16.3 (i.e., adaptation \r consists of fragmented, localised, incremental adjustments to existing \r practices), though the effect of adaptation on risk for individual RFCs \r and related literature is discussed further below."


id: 291c556d4770a8960bb9b0a284c716d3
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"The transitions here are informed by these assessments, along with \r the assessment in Chapter 2 on species high extinction risk and on \r ecosystem transitions. It also draws substantially from information \r in Cross-Chapter Paper 1 and Table  SM16.22 on risks to unique \r and threatened biological systems. Some unique and threatened \r systems, such as coral reefs and sea-ice-dependent ecosystems, were \r already showing attributable impacts with high confidence (see \r Table SM16.22 , Cross-Chapter Paper 1 and Chapter 2) based on data \r collected in the mid to latter 20th century, when global warming of \r 0.5degC above pre-industrial levels had taken place, as noted already in \r AR3. In this AR6 assessment, the temperature range for the transition \r from undetectable to moderate risk is still located at a median value \r of 0.5degC above pre-industrial levels, with very high confidence. Since \r impacts were first detected in coral reef systems in the 1980s when \r [...]"


id: 3cd4711b977a0e91bf56efbb0d0eba3a
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"[...] warming of ~0.4degC of global warming had occurred (SR15 Chapter \r 3), this provides the temperature at which the transition begins. The \r September Arctic sea ice volume has declined by 55-65% between \r 1979 and 2010 (AR6 WGI, Schweiger et al., 2019) as global warming \r increased from around 0.36degC in 1979 to around 0.9degC in 2010. These \r provide evidence of a start to the transition from undetectable to \r moderate risk at 0.4degC above pre-industrial levels. Recent evidence of \r observed impacts on mountaintop ecosystems and sea-ice-dependent \r species, and of range shifts in multiple ecosystems during 1990-2000, \r which AR6 WGI now assesses as corresponding to a global warming \r of 0.69degC (see WGI AR6 Cross-Chapter Box 2.3, Figure 1, Gulev et al., \r 2021), provides evidence for an upper limit to this transition of 0.7degC \r with very high confidence. Overall, the transition is located at a median \r [...]"


id: 71b1fb00fb0722c473893fcd8fca5607
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content:
"[...] of 0.5degC with lower and upper limits of 0.4degC and 0.7degC, respectively, \r with very high confidence."


id: d35f1055afe0929d6097ce46f8418124
created_at: 2023-04-19 13:23:03
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content:
"This RFC addresses the potential for increased damage to or irreversible \r loss of a wide range of physical, biological and human systems that \r are unique (i.e., restricted to relatively narrow geographical ranges and \r have high endemism or other distinctive properties) and are threatened \r by future changes in climate (Smith et  al., 2001; Smith et  al., 2009; \r Oppenheimer et al., 2014). The specific examples of such systems given in \r previous IPCC assessment reports has remained broadly consistent, with \r AR4 including 'coral reefs, tropical glaciers, endangered species, unique \r ecosystems, biodiversity hotspots, small island states, and indigenous \r communities' (Smith 2009), AR5 including 'a wide range of physical, \r biological, and human systems that are restricted to relatively narrow \r geographical ranges' and 'are threatened by future changes in climate' \r (Smith et  al., 2001), and SR15 Chapter 3 including 'ecological and \r [...]"


id: 892e7ca514c1d503f2497e021bef5d7a
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"[...] human systems that have restricted geographic ranges constrained by \r climate related conditions and have high endemism or other distinctive \r properties. Examples include coral reefs, the Arctic and its Indigenous \r People, mountain glaciers and biodiversity hotspots'. In this cycle, we \r retain the definition used in SR15 as most explicit and inclusive of the \r previous definitions."


id: 8b8a5b18fb115939cb6469f8b55c9697
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"(b) Embers are shown for each RFC, assuming low to no adaptation (i.e., adaptation is fragmented, localised, incremental adjustments to existing practices). The dashed horizontal \r line denotes the present global warming of 1.09degC (IPCC WGI Figure SPM.8a ) which is used to separate the observed, past impacts below the line from the future projected risks \r above it. RFC1 Unique and threatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and have high \r endemism or other distinctive properties. Examples include coral reefs, the Arctic and its Indigenous People, mountain glaciers and biodiversity hotspots. RFC2 Extreme weather \r events: risks/impacts to human health, livelihoods, assets and ecosystems from extreme weather events such as heatwaves, heavy rain, drought and associated wildfires, and \r [...]"


id: 51a753386150c32996f0544103ea363c
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"[...] coastal flooding. RFC3 Distribution of impacts: risks/impacts that disproportionately affect particular groups owing to uneven distribution of physical climate change hazards, \r exposure or vulnerability. RFC4 Global aggregate impacts: impacts to socio-ecological systems that can be aggregated globally into a single metric, such as monetary damages, \r lives affected, species lost or ecosystem degradation at a global scale. RFC5 Large-scale singular events: relatively large, abrupt and sometimes irreversible changes in systems \r caused by global warming, such as ice sheet disintegration or thermohaline circulation slowing. Comparison of the increase of risk across RFCs indicates the relative sensitivity of \r RFCs to increases in GSAT. The levels of risk illustrated reflect the judgements of IPCC author experts from WGI and WGII."


id: 8261e5cea053e2826fdb86f1f938c513
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"mortality (sometimes associated with insect damage and wildfire) has \r caused the mortality of up to 20% of trees in western North America, \r the African Sahel, and North Africa, linked to a warming of 0.3-0.9degC \r above pre-industrial levels, and is implicated in more than 100 other \r cases of drought-induced tree mortality in Africa, Asia, Australia, Europe, \r and North and South America (high confidence). Species in biodiversity \r hotspots already show changes in response to climate change (CCP1, \r high confidence). Roman-Palacios and Wiens (2020) attribute local \r extinctions of several taxonomic groups between the latter 20th century \r and 2003-2012, (corresponding to warming of less than 0.85degC) to \r climate-change-related temperature extremes for up to 44% (0-75%) \r of species. Widespread declines of up to 35% in the species richness \r of the unique pollinator group, bumble bees, between 1901-1974 \r and 2000-2014 are also attributed to climate change, via increasing \r [...]"


id: de26e05f8d5ba8be2aa988bc0847fc93
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"[...] exceedance of their thermal tolerance limits across Europe and North \r America (Soroye et al., 2020). The first extinctions attributed to climate \r change have been now detected with the present 1.2degC warming, \r including that of the Bramble Cay melomys (Melomys rubicola), a sub\u0002species of the lemuroid ringtail possum (Hemibelideus lemuroides), and \r golden toad (Incilius periglenes) (Chapter 2). An increasing frequency \r or unprecedented occurrence of mass animal mortality due to climate\u0002change-enhanced heatwaves has also been observed in recent years on \r more than one continent, including temperature-vulnerable terrestrial \r birds and mammals in South Africa and Australia (Ratnayake et  al., \r 2019; McKechnie et al., 2021). There have also been 90% declines in sea\u0002ice-dependent species such as sea lions and penguins in the Antarctic \r (Table SM16.22 ). A strong effect of climate change on the observed \r contraction of ranges of polar fish species and strong expansion of \r [...]"


id: 6021a449e843a1f4c07b604bbad2d989
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"[...] ranges of arcto-boreal or boreal fish was observed between 2004 and \r 2012 (Frainer et al.., 2017). Even if current human-driven habitat loss \r is excluded, many hotspots are projected to cease to be refugia (i.e., to \r remain climatically suitable for >75% of the species they contain which \r have been modelled), at 1.0-1.5degC (Cross-Chapter Paper 1)."


id: 7ab14ab71f7e0d11ef2bea4211792f5b
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"action is not effective if the unique and threatened systems in question \r reach a hard limit to adaptation (as in the case of the loss of Arctic \r summer sea ice, the submergence of a small island, the contraction \r and elimination of a species' climatic niche from a mountaintop, or the \r degradation of a coral reef) (Section  16.4). Furthermore, adaptation \r benefits deriving from restoration rapidly diminish with increasing \r temperature (Cross-Chapter Paper 1). One study quantifies how land \r management (in terms of protecting existing ecosystems or restoring \r lost ones) might reduce extinctions in biodiversity hotspots or globally \r significant terrestrial biodiversity areas more generally (Warren et al., \r 2018b). While the latter suggests that substantial benefits can result \r globally in terrestrial systems, allowing less unique systems to persist at \r higher levels of warming but only under a high adaptation scenario in \r [...]"


id: cc6bbbf876d1825a528480f376dff401
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"[...] which globally applied terrestrial ecosystem restoration and protected \r area expansion takes place, this is less likely for many of the unique \r and threatened terrestrial systems which are more vulnerable than \r the globally significant biodiversity areas treated in that study (which \r excludes coral reefs and Arctic sea-ice-dependent systems). Such high \r levels of adaptation globally are likely infeasible owing to competition \r for land use with food production (Portner et al., 2021). Novel targeted \r adaptation interventions for coral reefs such as artificial upwelling \r and local radiation management show some promise for reducing the \r adverse effects of thermal stress and resulting coral bleaching (Condie \r et al., 2021), but are far from implementation (Sawall et  al., 2020; \r Kleypas et  al., 2021). Larger benefits in this RFC could theoretically \r accrue only if adaptation action became ubiquitous and extensive, \r [...]"


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"[...] which experts considered infeasible at the scales required. Small island \r communities are confronted by socio-ecological limits to adaptation \r well before 2100, especially those reliant on coral reef systems for \r their livelihoods, even for a low-emissions pathway (Chapter 3) (high \r confidence). At warming levels beyond 1.5degC, the potential to reach \r biophysical limits to adaptation due to limited water resources are \r reported for small islands (medium confidence) and unique systems \r dependent on glaciers and snowmelt (Chapter 4) (medium confidence)."


id: c231e4640bed4fde5483ac3691d1e044
created_at: 2023-04-19 13:23:03
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"extinction increases with warming in all climate change projections, \r for all native species studied in biodiversity hotspots (Cross-Chapter \r Paper 1, high confidence), being roughly threefold greater for endemic \r than more widespread species for global warming of 3degC above pre\u0002industrial levels than 1.5degC) (Manes et al., 2021, Cross-Chapter Paper \r 1) (medium confidence). The Arctic is projected to be practically ice free \r in September in some years for global warming of between 1.5degC and \r 2degC (WGI AR6 Section 9.3.1.1, Fox-Kemper et al., 2021), undermining \r the persistence of ice-dependent species such as polar bears, ringed \r seals and walrus (Meredith et  al., 2019), and adversely affecting \r Indigenous communities. Warming of 1.5degC is also assessed (Chapter \r 3) to reduce the habitability of small islands, due to the combined \r impacts of several key risks (high confidence). Hence, the transition \r [...]"


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"[...] from high to very high risk in these systems is assessed to occur with \r high confidence beginning at 1.2degC, passing through a median value of \r 1.5degC, and completing (i.e., reaching its upper bound) at 2degC warming."


id: 65cd845b8e7e5557ec0f4dcd0c175f72
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content:
"Assessment of a high level of risk requires a higher level of magnitude, \r severity and spatial extent of the risks. Events prior to that already \r had substantial impacts, such as the 2003 European heatwave (IPCC \r SREX Chapter 9). Examples of impactful events in the early 2010s (at \r ca. 0.95degC of global warming; WGI AR6 Chapter 2, Gulev et al., 2021) \r include the 2010 Russian heatwave (Barriopedro et al., 2011) and the \r 2010 Amazon drought (Lewis et al., 2011). Later impactful events include, \r among others, the 2013 heatwave in eastern China (Sun et al., 2014), the \r 2017 tropical cyclone Harvey (Risser and Wehner, 2017; Van Oldenborgh \r et al., 2017) and the 2018 concurrent North Hemisphere heatwaves in \r Europe, North America and Asia (Vogel et al., 2019). Very recent events \r with severe and unprecedented impacts attributed to anthropogenic \r climate change indicate that thresholds to high risks may already \r [...]"


id: e3da7f0bd179424b3804d4ced3862f79
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"[...] have been crossed at recent levels of global warming (ca. 1.1-1.2degC), \r including the Siberian fires and the 2019 Australian bushfires that were \r linked to extreme heat and drought conditions (Van Oldenborgh et al., \r 2017) and extreme precipitation linked to increased storm activity in the \r USA (Van Oldenborgh et al., 2017). Severe and unprecedented impacts \r occurred with current low levels of adaptation (Section 16.2.3.4). The \r global-scale risk of wildfire considerably degrading ecosystems and \r increasing illnesses and death of people has been assessed to transition \r from undetectable to moderate over the range 0.6-0.9degC with high \r confidence (Chapter 2, Table SM2.5, Figure 2.11)."


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"AR5 identified a transition from undetectable to moderate risk below \r 'recent' temperatures (i.e., during 1986-2005, which then corresponded \r to a global warming of 0.6degC above pre-industrial levels). SR15 \r Section 3.5.2.2 (Hoegh-Guldberg et al., 2018b) concluded that differences \r of 0.5degC in global warming led to detectable changes in extreme weather \r and climate events on the global scale and for large regions. IPCC WGI \r AR6 Chapter 11 confirms this assessment and concludes that 'new \r evidence strengthens the conclusion from SR15 that even relatively small \r incremental increases in global warming (+0.5degC) cause statistically \r significant changes in extremes on the global scale and for large regions'.\r Substantial literature is available for comparisons at +1.5degC versus +2degC \r of global warming, but the conclusions are assessed to also apply at \r lower global warming levels and smaller increments of global warming \r [...]"


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"[...] given the identified linearity of regional responses of several extremes in \r relation to global warming (Seneviratne et al., 2016; Wartenburger et al., \r 2017; Tebaldi and Knutti, 2018) and the identification of emergence of \r global signals in climate extremes for global warming levels as small as \r 0.1degC (Seneviratne and Hauser, 2020, WGI AR6, Chapter 11, Figure 11.8; \r WGI Cross-Chapter Box 12.1). Further analyses are consistent with this \r assessment, based on model simulations (Fischer and Knutti, 2015; \r Schleussner et  al., 2017; Kirchmeier-Young et  al., 2019a; Seneviratne \r and Hauser, 2020) and observational evidence (Zwiers et al., 2011; Dunn \r et al., 2020). A global warming of +0.5degC above pre-industrial conditions \r corresponds approximately to climate conditions in the 1980s (Chapter 2, \r Figure 2.11), a time frame at which detectable changes in some extremes \r were established at the global scale based on observations (Dunn et al., \r [...]"


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"[...] 2020). Heat-related mortality has also been assessed to have increased \r considerably because of climate change (Ebi et al., 2021; Vicedo-Cabrera "


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"increase in the probability of compound events, such as an increase in \r concurrent heatwaves and droughts (high confidence) (WGI AR6 Chapter \r 11). There is medium confidence that weather conditions that promote \r wildfires (fire weather) have become more probable in southern Europe, \r northern Eurasia, the USA and Australia over the last century (WGI AR6 \r Chapter 11; SRCCL Chapter 2, Jolly et al., 2015; Abatzoglou and Williams, \r 2016). Furthermore, food security and livelihoods are being affected by \r short-term food shortages caused by climate extremes (Section 5.12.1; \r Chapter 16, Food Security RKR) which have affected the productivity of \r all agricultural and fishery sectors (high confidence). The frequency of \r sudden food production losses has increased since at least mid-20th \r century on land and sea (medium evidence, high agreement). Droughts, \r floods and marine heatwaves contribute to reduced food availability and \r [...]"


id: 91285bbba67e0a4a94cfa7dace52e282
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 22741
content:
"[...] increased food prices, threatening food security, nutrition and livelihoods \r of millions (high confidence). Changes in sea surface temperatures drive \r simultaneous variation in climate extremes, increasing the risk of multi\u0002breadbasket failures (Cai et al., 2014; Perry et al., 2017). Droughts induced \r by the 2015-2016 El Nino, partially attributable to human influences \r (medium confidence), caused acute food insecurity in various regions, \r including eastern and southern Africa and the dry corridor of Central \r America (high confidence). Human-induced climate change warming \r also worsened the 2007 drought in southern Africa, causing food \r shortages, price spikes and acute food insecurity in Lesotho (Verschuur \r et al., 2021). In the fisheries and aquaculture sector, marine heatwaves \r are estimated to have doubled in frequency between 1982 and 2016, \r as well as increasing in intensity and length, with consequences for fish \r [...]"


id: fb7d278d93c22f7f101ade18dfa19244
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 41620
content:
"[...] mortality (Chapter 5; Smale et al., 2019; Laufkotter et al., 2020). In the \r northeast Pacific, a recent 5-year warm period impacted the migration, \r distribution and abundance of key fish resources (high confidence). \r At 1degC warming, the number of people affected by six categories of \r extreme events was found to have already increased by a factor of 2.3 \r relative to pre-industrial (Lange et al., 2020)."


id: 415a1874fc1b6c92cf09b7b3dee2548b
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 8683
content:
"As in RFC1, one of the criteria for identification of very high risks is \r limits to adaptation. Though the literature explicitly considering societal \r adaptation to extreme weather events is limited, there is evidence \r that investments in hydro-meteorological information, early-warning \r systems and anticipatory forecast-based finance are a cost-effective \r way to prevent some of the most adverse effects of extreme events \r (Coughlan de Perez et  al., 2016; Fakhruddin and Schick, 2019; Merz \r et al., 2020). Despite a lack of systematic methods for assessing general \r adaptation effectiveness, there is some evidence of risk reduction for \r particular places and hazards, especially flood and heat vulnerability \r (Section  16.3.2.4), including investment in flood protection, building \r design and monitoring and forecasting, air conditioning, reduced social \r vulnerability, and improved population health. One study finds declining \r [...]"


id: 1a543df222409e8145c6192b4bceafc0
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 1831
content:
"[...] global mortality and economic loss due to extreme weather events \r over the past four decades (Formetta and Feyen, 2019) especially in \r low-income countries. Using SSP2 as a proxy for expanded adaptation, \r Ebi et al. (2021) assess that the transition to high risk for heat-related \r mortality increases to 1.8degC (compared with 1.5degC with less adaptation \r under SSP3). There is evidence of adaptation avoiding heat-related \r mortality at low levels of global warming, using early-warning and \r response systems and sustainable alterations of the thermal environment \r at the individual, building, urban and landscape levels (Jay et al., 2021). \r Despite the evidence that adaptation can reduce risks of heat stress, the \r impact of projected climate change on temperature-related mortality \r is expected to be a net increase under a wide range of climate change \r scenarios, even with adaptation (Chapter 7, high confidence). Much \r [...]"


id: cf7657848500149021e97a16934738ea
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 33853
content:
"[...] of the adaptation literature focuses on coping with long-term gradual \r climate change and largely does not take into account the increased \r difficulty of adapting to climate extremes and general higher variability \r in climate that is projected to occur in the future. However, expanding \r and more coordinated adaptation, including wider implementation and \r multi-level coordination, has the potential to reduce the risks to crops \r from heatwaves at intermediate (but not high) levels of warming.(IPCC \r AR5 Ch7, Ahmed et al., 2018; Ahmed et al., 2019, Section 16.3.2.2; EEA, \r 2019; Raza et al., 2019; Tripathi and Sindhi, 2020).\r The transition from high to very high risk for the RFC2 was not assessed \r in the AR5 or in SR15. Some new evidence suggests, however, that \r very high risks associated with weather and climate extremes would\r be reached at higher levels of global warming. In particular, changes \r in several hazards would be more widespread and pronounced at 2degC \r [...]"


id: e1b10e90512f80c0aa0d1ccb436775ee
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 36976
content:
"[...] compared with 1.5degC global warming, including increases in multiple \r and concurrent extremes (IPCC WGI AR6 SPM; IPCC WGI AR6 Chapter \r 11, IPCC WGI AR6 Chapter 12). On average over land, high temperature "


id: 6de087d5cc87b640497aacf95b9331ca
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 16592
content:
"events that would have occurred once in 50 years in the absence of \r anthropogenic climate change are projected to become 13.9  times \r more likely with 2degC warming, and 39.2  times more likely with 4degC \r warming (IPCC AR6 WGI SPM Figure  SPM.6, IPCC, 2021), indicating \r a nonlinear increase with warming. Chapter 2 assessed that risk of \r wildfire transitions from moderate to high over the range 1.5degC to 2.5degC \r warming (medium confidence, Table SM2.5 , Figure 2.11). The intensity \r of heavy precipitation events increases overall by about 7% for each \r additional degree of global warming (IPCC AR6 WGI SPM), while their \r frequency increases nonlinearly. Events that would have occurred once \r every 10 years in a climate without human influence are projected to \r become 1.7 times more likely with 2degC warming, and 2.7 times more \r likely with 4degC warming (IPCC AR6 WGI SPM Figure SPM.6). Several \r AR6 regions are projected to be affected by increases in agricultural and \r [...]"


id: 2b33b9a80b2bc1d7f1617b35df155c45
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 4844
content:
"[...] ecological droughts at 2degC of global warming, including western North \r America, central North America, northern Central America, southern \r Central America, the Caribbean, northern South America, northeastern \r South America, South American Monsoon, southwestern South America, \r southern South America, West and Central Europe, the Mediterranean, \r western Southern Africa, eastern Southern Africa, Madagascar, \r eastern Australia and southern Australia (IPCC WGI AR6, Chapter 11, \r Seneviratne et al., 2021). This is a substantially larger number compared \r with projections at 1.5degC (IPCC WGI AR6, Chapter 11, Seneviratne et al., \r 2021). In these drying regions, events that would have occurred once \r every 10 years in a climate without human influence are projected to \r happen 2.4 times more frequently at 2degC of global warming (IPCC WGI \r AR6 SPM Figure SPM.6). Urban land exposed to floods and droughts \r is very likely to have more than doubled between 2000 and 2030, \r [...]"


id: 83e09dff6cff1bdf5ce12471ab21c2cf
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 20348
content:
"[...] and the risk of flooding accelerates after 2050 (Chapter 4). At 2degC of \r global warming, there are also significant projected increases in fluvial \r flood frequency and resultant risks associated with higher populations \r exposed to these flood risks (Alfieri et al., 2017; Dottori et al., 2018)."


id: e3ff5489e9dff3b0cc8b87c139cea3de
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 37407
content:
"Based on the available evidence, we assess that there is medium \r confidence that the transition to very high risk would happen at a \r median value 2degC of global warming, considering the increased risk for \r breadbasket failure and irreversible impacts associated with changes \r in extremes at this warming level (e.g., damages to ecosystems, health \r impacts, severe coastal storms), but that due to the disproportionate \r increases in risk between 1.5degC and 2degC this transition begins already \r at 1.8degC. The higher range for this transition is set with medium \r confidence at 2.5degC in this low/no adaptation scenario, owing to the \r further projected nonlinear increases in risks associated with high \r temperature events above 2degC (WGI AR6 Figure SPM.6, IPCC, 2021; \r Cross-Chapter Box 12.1, Ranasinghe et al., 2021), and also the limits to \r adaptation associated with dealing with a rapid escalation of extreme \r weather events globally during this century; extreme events are \r [...]"


id: 75c595b5d240a333aa1d5f8d2a352d92
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 17951
content:
"[...] particularly difficult to adapt to and thus more often exceed hard limits \r to adaptation, particularly in natural ecosystem settings (Section 16.4)."


id: 576718f791dee6cd4dda2e127780e7dd
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 12638
content:
"Heat-related mortality is assessed to increase from high to very high \r by 3degC under SSP3, a socioeconomic scenario with large challenges to \r adaptation (Ebi et al., 2021). SRCCL assessed that very high risks would be \r reached in association with wildfire above 3degC of global warming (IPCC, \r 2019a). Chapter 2 has assessed that risk of fire weather itself transitions \r from high to very high over the range 3degC to 4.5degC warming (medium \r confidence, Table  SM2.5, Figure  2.11). Matthews et  al. (2017) show \r that, at 1.5degC of global warming, about 40% of all megacities would be \r affected at least 1 d yr-1 with a heat index above 40.6degC (i.e., with 40.6degC \r 'feels-like' temperatures, accounting for moisture effects). This number \r would reach about 65% of megacities at 2.7degC and close to 80% at 4degC. \r In addition, there is evidence for a higher risk of concurrent heat extremes \r at different locations with increasing global warming (Vogel et al., 2019), \r [...]"


id: 6ef208acde7ada4e7d63e19fbb35cb1b
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 16790
content:
"[...] meaning that several cities could be affected by deadly heatwaves \r simultaneously. Laufkotter et  al. (2020) found that marine heatwave \r events would become annual to decadal events under 3degC of global \r warming, with consequences for aquaculture (Chapter 5). Gaupp et al. \r (2019) conclude that risks of simultaneous crop failure across worldwide \r breadbasket regions, due to changes in maximum temperatures in the \r crop-growth-relevant season or cumulative precipitation in relevant time \r frames, increase disproportionately between 1.5degC and 2degC of global \r warming. Populations exposed to extreme weather and climate events \r may consume inadequate or insufficient food, leading to malnutrition \r and increasing the risk of disease (Chapter 5, high confidence). Hence, "


id: b8097f086e079a5d3e9cdc054be84bdf
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 29594
content:
"nutrition-related health (Springmann et  al., 2016; Lloyd et  al., 2018; \r Sulser et al., 2021) and exposure to stressors such as drought, floods \r (Alfieri et al., 2017; Hirabayashi et al., 2021) and extreme heat (Dosio \r et al., 2018; Harrington et al., 2018; Sun et al., 2019). One study (Gaupp \r et al., 2019) found that the risk of simultaneous crop failure in maize is \r estimated to increase from 6% to 40% at 1.5degC relative to the historical \r baseline climate. In particular, further research on projected regional \r yield declines of wheat and maize between 1.5degC and 2degC, especially \r in Africa, has accrued Asseng et al. (2015), including in Ethiopia (Abera \r et  al., 2018) with associated economic effects (Wang et  al., 2019). \r Optimum maize production areas in East Asia are projected to reduce in \r area by 38% for global warming of 1.5-2.0degC (He et al., 2019). A study \r of Jamaica also estimated that warming of less than 1.5degC will have an \r [...]"


id: 6234b370752f97336230fcb574721b56
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 14553
content:
"[...] overall negative impact on crop suitability and a general reduction in \r the range of crops, but above 1.5degC, irreversible changes to Jamaica's \r agriculture sector were projected (Rhiney et al., 2018)."


id: 96b0620c7302bc5977892d050a1722ec
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 23715
content:
"Very high risk implies limited ability to adapt. Adaptation potential not \r only differs across sectors and regions, but also occurs on different \r time scales depending on the nature and implementation level of the \r adaptation option under consideration and the system in which it is \r to be deployed. The costs of adaptation actions that would be needed \r to offset projected climate change impacts for major crop production \r are projected to rise once global warming reaches 1.5degC (Iizumi et al., \r 2020). It has been estimated that the number of additional people \r at risk of hunger with 2.0degC global warming could be reduced from \r 40 million to 30 million by raising the level of adaptation action (Baldos \r and Hertel, 2014), but beyond this level of warming residual impacts \r are projected to escalate (Iizumi et al., 2020). Chapter 5 assessed the \r potential of existing farm management practices to reduce yield losses, \r [...]"


id: 7098dc834380c53e0f9f97730b1e10c0
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 17067
content:
"[...] finding an average 8% loss reduction in mid-century and 11% by end\u0002century (Section 5.4.4.1), which is insufficient to offset the negative \r impacts from climate change, particularly in currently warmer regions \r (Section 5.4.3.2). The literature indicates that, globally, crop production \r may be sustained below 2.0degC warming with adaptation, but negative \r impacts will prevail at 2.0degC warming and above in currently warm \r regions (Section  5.4.4.1). Importantly, residual damage (that which \r cannot be avoided despite adaptation) is projected to rise around \r 2.0degC global warming (Iizumi et al., 2020). Evidence of constraints and \r limits for food, fibre and other ecosystem products for the different \r regions is evident for the various regions (Section 16.4.3.1) indicating \r limited ability to adapt. Adaptation costs are also higher relative to \r GDP in low-income countries, for example for the building of sea dikes \r (Brown et al., 2021)."


id: 26d5fbd5f7991754f88da508605e0adf
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 3992
content:
"Very high risks to crop production are assessed to occur in Africa above \r ~2.5degC warming (Figure 9.6) and below 4degC in Europe (Figure 13.29 \r ). Very high risks of mortality and morbidity due to heat extremes and \r infectious disease are assessed to occur in Africa with 2.5degC warming \r (Figure 9.6); heat stress, mortality and morbidity in Europe are assessed \r to reach a very high level of risk at ~3.2degC (Figure 13.30). Heat-related \r mortality risk and cascading effects on cities both transition to a very \r high level by ~2.5degC warming in Australasia (Figure  11.7). Risks to \r water scarcity in North America are projected to reach very high levels \r with 3.5degC warming (Figure 14.4). Hence, this assessment concludes \r with medium confidence that a transition from high to very high risks, \r in terms of distribution of impacts, begins at 2degC global warming, \r with a full transition to very high risks completed by 3.5degC. However, \r [...]"


id: 1df4cb0508191a2cf63648cba2e2bf59
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 2461
content:
"[...] it should be noted that many studies upon which this assessment \r has been based have not taken into account the impacts of extreme \r weather events and oscillations in sea surface temperatures; hence, \r risks at a given level of global warming might be underestimated in \r the literature."


id: 1fdb7104eb8777bad861b8359467d043
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 2809
content:
"In previous reports, the transition from high to very high risk for the \r distribution of impacts was not assessed due to limited available \r literature, but there is now sufficient evidence to do so. A range of \r literature quantifies the increasing regional probability of drought as \r compared with the present day, with projected increases in the area \r exposed to drought (Carrao et al., 2018; Pokhrel et al., 2021), as well as \r in the duration (Naumann et al., 2018) and frequency of droughts, with \r higher warming levels. Naumann et al. (2018) showed that, for drying \r areas, drought durations are projected to rise from 2 months per degC \r below 1.5degC to 4.2 months per degC near 3degC warming. Most of Africa, \r Australia, southern Europe, southern and central USA, Central America, \r the Caribbean, northwest China, and parts of Southern America are \r projected to experience more frequent droughts. Adverse effects of \r climate change on food production are projected to become much \r [...]"


id: f5a60df1a0454286b91691affab9bd5b
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 40584
content:
"[...] more severe (Section  5.4.3.2) when global temperatures rise more \r than 2degC globally, but there are predicted to be much more negative \r impacts experienced sooner on food security in low to mid-latitudes \r (Richardson et al., 2018a) (Section 5.4.1). For instance, climate change \r by 2050 is projected to increase the number of people at risk of hunger \r by between 8 and 80 million with 2-3degC warming compared with no\u0002climate-change conditions (Baldos and Hertel, 2014; Hasegawa et al., \r 2018; Nelson et al., 2018; Janssens et al., 2020). In addition to effects \r upon crop yield, agricultural labour productivity, food access and \r food-related health are projected to be negatively impacted by 2-3degC \r warming (Springmann et al., 2016; de Lima et al., 2021). Regionally, \r substantial regional disparity in risks to food production is projected "


id: 5972b94706eb19538c1385d972186e90
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 12974
content:
"In AR5 Section 19.6.3.5 (Oppenheimer et al., 2014), the transition from \r undetectable to moderate risk was assessed between 1.6degC and 2.6degC \r above pre-industrial levels (i.e., 1degC and 2degC above the 1986-2005 \r level) based on impacts to both Earth's biodiversity and the overall \r global economy with medium confidence. The risk transition between \r moderate and high risk was set around 3.6degC above pre-industrial \r levels (i.e., 3degC above the 1986-2005 level), based on literature \r finding extensive species vulnerability and biodiversity damage with \r associated loss of ecosystem goods and services at 3.5degC (Foden et al., \r 2013; Warren et al., 2013). In SR15 Section 3.5.2.4 (Hoegh-Guldberg \r et al., 2018b), economic literature on potential socioeconomic threshold \r events and empirical studies of global economic damages, combined \r with new evidence on biome shifts, extinction risk, species range loss \r [...]"


id: fcb5c845c04a15f3c16af980781426ef
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 41822
content:
"[...] (especially noting the integral role of insects in ecosystem function) \r and ecosystem degradation, were assessed, and the upper bound of \r the transition to moderate risk was lowered to 1.5degC warming above \r pre-industrial levels, and the transition from moderate and high risk \r was lowered to between 1.5degC and 2.5degC (medium confidence). The \r boundary between high risk and very high risk was not assessed in "


id: e3eedf4be892b29170b184397c2e34a
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 37390
content:
"Since AR5, many new global estimates of the aggregate, economy-wide \r risks of climate change have been produced, though, as was the case \r in AR5, these continue to exhibit a low level of agreement, including \r for today's level of global warming, due primarily to differences in \r methods. Cross-Working Group Box ECONOMIC in this chapter includes \r a more thorough discussion of advancements and limitations of global \r economic impact estimates and methodologies, finding significant \r variation in estimates that increases with warming, indicating higher risk \r in terms of economic costs at higher temperatures (high confidence). \r Climate change has been found to exacerbate poverty through declines \r in agricultural productivity, changes in agricultural prices and extreme \r weather events (Hertel and Lobell, 2014; Hallegatte and Rozenberg, \r 2017). In terms of biodiversity risks, the literature indicates that losses \r in terrestrial and marine ecosystems increase substantially between \r [...]"


id: 3f0af1b83896d376eca963c939089573
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 8275
content:
"[...] 1.5degC and 2degC of warming (Hoegh-Guldberg et al., 2018b). Since SR15, \r further evidence of degradation of biodiversity and ecosystem services \r and ocean acidification at the global aggregate level has continued to \r accrue due to climate change (see Chapter 2)."


id: 158c1d4c6989a8cb5db67594f442d3f3
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 1004
content:
"Section 16.5.2.3.4 (RKR-D, underlying key risk on poverty) reports that, \r under medium warming pathways, climate change risks to poverty \r would become severe if vulnerability is high and adaptation is low \r (limited evidence, high agreement). At and beyond 1.5degC, approximately \r 200  million people with livelihoods derived from small-scale fisheries \r would face severe risk, given sensitivity to ocean warming, acidification \r and coral reef loss (Cheung et  al., 2018a; Froehlich et  al., 2018; Free \r et  al., 2019). Warming between 1.5degC and 2degC could expose 330-\r 396 million people to lower agricultural yields and associated livelihood \r impacts (Byers et al., 2018; Hoegh-Guldberg et al., 2018a), due to a high \r dependency of climate-sensitive livelihoods to agriculture globally (World \r Bank, 2020). Models project that climate change will increase the number \r of people at risk of hunger in 2050 by 8-80 million people globally, with \r [...]"


id: 4b2a35d4b4c4bddfe6467b5cb4153b87
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 10469
content:
"[...] the range depending on the level of warming (1.5-2.9degC) and SSPs \r (Nelson et al., 2018; Mbow et al., 2019; Janssens et al., 2020). Higher \r atmospheric concentrations of carbon dioxide reduce the nutritional \r quality of wheat, rice and other major crops, potentially affecting millions \r of people at a doubling of carbon dioxide relative to pre-industrial \r (very high confidence) (Section  7.3.1). Global ocean animal biomass \r is projected to decrease on average by 5% per 1degC increase; hence, a \r 2.5degC level of warming is associated with ~13% decline in ocean animal \r biomass, which would considerably reduce marine food provisioning, \r fisheries distribution and revenue value, with further consequences for \r ecosystem functioning (Chapter 5, medium confidence)."


id: 347ad1db7c4d0885652a430160cac3f4
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 6469
content:
"For this RFC, the transition from undetectable to moderate risk to \r global aggregate impacts is assessed with medium confidence to occur \r between 1.0degC (start of transition) and 1.5degC (completion of transition) \r with a median judgement of transition at 1.3degC, based on evidence of a \r combination of economic consequences, widespread impacts to climate\u0002sensitive livelihoods, changes in biomes, and loss of terrestrial and marine \r biodiversity. The start of the transition from undetectable to moderate \r risk is located at recent temperatures based on observed impacts \r to biodiversity (Section  16.2.3.1). Experts noted aggregate impacts \r on biodiversity are detectable, with damages that have had global \r significance (e.g., drought, pine bark beetles, coral reef ecosystems). \r Consistent with the start of this transition at 1degC, a similar elicitation \r conducted in Chapter 2 assessed that risks to biodiversity globally have \r [...]"


id: ab3b68705cb76f58fb03328bed1468d5
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 27354
content:
"[...] already transitioned to a moderate level with 1degC warming, while risks \r of widespread tree mortality are already moderate with 0.9degC warming \r and moderate risks of ecosystem structure change began with warming \r of 0.5degC (Table  SM2.5, Figure  2.11). Human-induced warming has \r slowed growth of agricultural productivity over the past 50 years in mid\u0002and low latitudes (Chapter 5; Hurlbert et al., 2019). Although there is \r not yet strong evidence of attributable loss of life and livelihoods at the \r global level (Sections 16.5.2.3.4, 16.5.2.3.5), experts found that regional \r evidence of such observed impacts was still relevant to defining the \r beginning of the transition (e.g., Table SM16.22, Chapter 9). Informing \r the median value and upper bound of the transition to moderate risk, \r empirical studies and scenario analyses have found that regions with \r high dependence on climate-sensitive livelihoods like agriculture, \r [...]"


id: e07095619dd46f14b4ed35d398648ac9
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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content:
"[...] fisheries and forestry would be severely impacted even at low levels of \r warming under conditions of low adaptation (RKR-D, Lobell et al., 2011; \r Hoegh-Guldberg et al., 2018b).\r The transition to high risk is assessed with medium confidence to occur \r between 1.5degC (start of transition) and 2.5degC (completion of transition) \r with a median judgement of transition at 2.0degC. Though economic \r estimates exhibit wide variation and low agreement at warming levels "


id: e030d2a52262cad3f587f5a5574210d8
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 36691
content:
"Losses in terrestrial and marine biodiversity increase substantially beyond \r 1.5degC of warming (Hoegh-Guldberg et al., 2018b). Section 16.5.2.3.2 \r (RKR-B, risks to terrestrial and marine ecosystems) finds that substantial \r biodiversity loss globally, abrupt local ecosystem mortality impacts, and \r ecological species disruption are all projected at global warming levels \r below 3degC, with insular systems and biodiversity hotspots at risk below \r 2degC (medium confidence). Insects play a critical role in providing vital \r ecosystem services that underpin human systems, with major losses \r of their climatically determined geographic range at 2degC warming \r implying adverse effects on ecosystem functioning. Consistent with \r the transitions presented here, a similar burning ember developed in \r Chapter 2 assessed a transition from moderate to high risks globally \r for marine and terrestrial biodiversity (e.g., widespread death of trees, \r [...]"


id: e19852ca481f7fb31aecca76c5bd57de
created_at: 2023-04-19 13:23:03
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content:
"[...] damages to ecosystems, and reduced provision of ecosystem services, \r and structural change, including biome shifts) beginning between 1.0degC \r and 2.0degC warming ( Table SM2.5, Figure 2.11)."


id: 33e4d5b9b21a9405ba895a3843159648
created_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 6370
content:
"Though explicit treatment of adaptation is limited in the RFC4 impacts \r literature (i.e., studies that compare risks for specific adaptation scenarios \r in terms of globally aggregated impacts with quantified findings), \r there is evidence of the potential for investments in improved hydro\u0002meteorological information and early-warning systems to avoid some \r of the most adverse social and economic impacts from extreme weather \r events in both developed and developing countries, with benefits at a \r globally significant level (Hallegatte, 2012). Studies of adaptation in the \r agriculture sector (e.g., changing crop variety, timing of crop planting, \r new types of irrigation, etc.) and infrastructure (e.g., coastal protection, \r hardening of critical infrastructure, flood and climate-resistant building \r materials and water storage) show large potential benefits in terms of \r reduced impacts to lives and livelihoods (van Hooff et al., 2015; Mees, \r [...]"


id: 2851a0b33094d742539960a22e777c70
created_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 4293
content:
"[...] 2017). At higher warming levels, however, potential adaptations to \r address biodiversity loss are expected to be limited due to the projected \r rate and magnitude of change as well as the resources required (Hannah \r et al., 2020)."


id: 55f77e5cb4f4dde80371bde41e0ae6fc
created_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 12398
content:
"This RFC, large-scale singular events (sometimes called tipping points or \r critical thresholds), considers abrupt, drastic and sometimes irreversible \r changes in physical, ecological or social systems in response to smooth \r variations in driving forces (accompanied by natural variability) \r (Oppenheimer et al., 2014; O'Neill et al., 2017). SR15 Section 3.5.2.5 \r presented four examples, including the cryosphere (West Antarctic ice \r sheet, Greenland ice sheet), thermohaline circulation (slowdown of \r the Atlantic Meridional Overturning Circulation), the El Nino-Southern \r Oscillation (ENSO) as a global mode of climate variability, and the role \r of the Southern Ocean in the global carbon cycle (Hoegh-Guldberg \r et al., 2018b). While most of the literature assessed here focuses on \r the resultant changes to climate-related hazards such as sea level rise, \r in this assessment, evidence about the implications of accelerated \r [...]"


id: 5c77ad195b3a1c2bb7e756d6590983ba
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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content:
"[...] sea level rise for human and natural systems is also considered. If sea \r level rise is accelerated by ice sheet melt, the associated impacts are \r projected to occur decades earlier than otherwise, directly affecting \r coastal systems including cities and settlements by the sea (CCP2) and \r wetlands (Chapter 2). The associated disruption to ports is projected \r to severely compromise global supply chains and maritime trade with \r local-global geo-political and economic consequences. To compensate \r for this acceleration, adaptation would need to occur much faster and \r at a much greater scale than otherwise, or indeed than has previously \r been observed (CCP2). The costs of accommodating port growth and \r adapting to sea level rise amount to USD 22-768 billion before 2050 \r globally (medium evidence, high agreement) (see Sections  2.1, 2.2; \r Cross-Chapter Box SLR in Chapter 3)."


id: 9e958649baa8fa31c97519a39b3ff7ff
created_at: 2023-04-19 13:23:03
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content:
"The transition to very high risks is assessed to occur within a range of \r 2.5-4.5degC with medium confidence over the range, and low confidence\r assessed over a narrowed 'best estimate' range of 2.7-3.7degC. The \r lower end of the range reflects the loss of an increasingly large \r fraction of biodiversity globally. Chapter 2 has assessed a transition \r from high to very high risks globally for biodiversity (marine and \r terrestrial) completing at ~2.5degC warming, noting widespread death \r of trees, damages to ecosystems, and reduced provision of ecosystem \r services over the temperature range 2.5-4.5degC ( Table  SM2.5, \r Figure 2.11) and, similarly, a transition from high to very high risks of \r ecosystem structure change (including biome shifts) between 3degC and \r 5degC warming ( Table SM2.5, Figure 2.11). A global study of 115,000 \r common species projects climatically determined geographic range \r losses of over 50% in 49% of insects, 44% of plants and 26% of \r [...]"


id: a536e6ebb3e697b95d110d6326df2e3e
created_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 26293
content:
"[...] vertebrates with global warming of 3.2degC, implying an associated \r effect on provisional and regulating ecosystem services that support \r human well-being, including pollination and detritivory (Warren \r et al., 2018a). The risk of abrupt impacts on ecosystems as multiple \r species approach tolerance limits simultaneously is projected to \r threaten up to 15% of ecological communities with 4degC of warming \r (Trisos et al., 2020). Under a 4degC warming scenario, models project \r global annual damages associated with SLR of $31,000 billion yr-1 in \r 2100 (Brown et al., 2021)"


id: 3d147aed30b9b98555992a90464c335f
created_at: 2023-04-19 13:23:03
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content:
"In terms of global economic impact, while an emerging economic \r literature is addressing many gaps and critiques of previous damage \r estimates for high warming (e.g., Jensen and Traeger, 2014; Burke et al., \r 2015; Lontzek et al., 2015; Moore and Diaz, 2015; Lemoine and Traeger, \r 2016; Moore et  al., 2017a; Cai and Lontzek; Takakura et  al., 2019, \r discussed further in Cross-Working Group Box ECONOMIC; Carleton \r et  al., 2020; Mejean et  al., 2020; Rode et  al., 2021), there remains \r wide variation across disparate methodologies, though the spread \r of estimates increases with warming in all methodologies, indicating \r higher risk in terms of economic costs at higher temperatures (high \r confidence). Section 16.5.2.3.4 (RKR-D) finds that risks to aggregate \r economic output would become severe at the global scale at high \r warming (~4.4degC) and minimal adaptation (medium confidence), \r defining severity as 'the potential for persistent annual economic \r [...]"


id: 36d607379262a5bcb71f6fc2f1b42c6d
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"This Cross-Working Group Box assesses literature estimating the potential global aggregate economic costs of climate change and the \r social cost of carbon (SCC), where the former are sometimes referred to as estimates of global 'climate damages' and the latter are \r estimates of the potential monetised impacts to society of an additional metric ton of carbon dioxide emitted to the atmosphere. These \r measures include the economic costs of climate change that could be felt in market sectors such as agriculture, energy services, labour \r productivity and coastal resources, as well as non-market impacts such as other types of human health risks (including mortality effects) \r and ecosystems. Global economic impacts estimates can inform decisions about global climate management strategy, while SCC estimates \r can inform globally incremental emissions decisions. In practice, economic damage estimates have been used to explore economically \r [...]"


id: e823bf5dc881312f4231c9fc3c94cfbd
created_at: 2023-04-19 13:23:03
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content:
"[...] efficient ('economically optimal') global emissions pathways (e.g., Nordhaus and Moffat, 2017), while SCCs have been used to inform \r federal and state-level policy assessment in some countries (Greenstone et al., 2013; Rose and Bistline, 2016), but the type of SCC and \r application matters (Rose, 2017). This literature has been assessed in previous WGII reports (e.g., Arent et al., 2014), and this box serves \r this need for this report. The assessment in this box was performed jointly across WGII and WGIII, building on the foundation of WGII AR6 \r Chapter 16's 'Risk to living standards' assessment (Section 16.5.2.3.4), which includes consideration of severe risks to global aggregate \r economic output, and WGIII AR6 Chapter 3's assessment of the benefits of mitigation. It also informs Chapter 16's global aggregate \r impacts Reasons for Concern and supports Chapter 18's assessment of global emissions transitions, risk management and climate resilient \r [...]"


id: 4c715fc2bd052bf0c677bdfae3c9d20e
created_at: 2023-04-19 13:23:03
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"[...] development. In keeping with the broad risk framing presented in Chapter 1 of this report, other lines of evidence regarding climate risks, \r beyond monetary estimates, should be considered in decision making, including key risks and Reasons for Concern."


id: 939fedd16a8f209ac6bb481015bf3d21
created_at: 2023-04-19 13:23:03
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content:
"There are several broad approaches to estimating climate damages, including biophysical process models, structural economic models, \r statistical methods (also called empirical or econometric) and hybrid approaches, with each methodology having strengths and \r weaknesses. Process models simulate physical, natural science and/or engineering processes and their response to climate variables, \r which are then monetised (e.g., Anthoff and Tol, 2014; Sieg et al., 2019; Narita et al., 2020). Process approaches have the advantage \r of being explicit and interpretable, though they can be computationally intensive; may omit relevant impact channels, interactions and \r market dynamics affecting valuation; and often lack a rigorous empirical basis for calibration (Fisher-Vanden et al.). Structural economic \r modelling represents climate impacts on inputs, production, household consumption, aggregate investment, and markets for economic \r [...]"


id: 47f5b120853b75be10664b2f5f5c298c
created_at: 2023-04-19 13:23:03
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"[...] sectors and regional economies (e.g., Reilly et al., 2007; Roson and Van der Mensbrugghe, 2012; Anthoff and Tol, 2014; Dellink et al., 2019; \r Takakura et al., 2019), often using computable general equilibrium (CGE) frameworks. Structural models can evaluate how market and \r non-market impacts might enter and transmit through economies, and adaptation responses within input and output markets, consumer \r and investment choices, and inter-regional trade (e.g., Darwin and Tol, 2001; Dellink et  al., 2019; Takakura et  al., 2019). Statistical \r methods estimate economic impacts in a given sector (e.g., Auffhammer, 2018) or in aggregate (e.g., Dell et al., 2014; Burke et al., 2015; \r Hsiang et al., 2017; Pretis et al., 2018; Kahn et al., 2019), inferred from observed changes in economic factors, weather and climate, with \r responses and net results constrained by available data. Since AR5, hybrid approaches have taken different forms to integrate process, \r [...]"


id: 923e7ad340a92c14ca80622617f3c11d
created_at: 2023-04-19 13:23:03
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"[...] statistical and/or structural methods, and represent a potentially promising means of leveraging the strengths of different approaches \r (e.g., Moore and Diaz, 2015; and Hsiang et al., 2017; Moore et al., 2017a; Ricke et al., 2018; Yumashev et al., 2019; Chen et al., 2020b). \r There is also a small literature that uses expert elicitation to gather subjective assessments of climate risks and potential economic \r impacts (Nordhaus, 1994; IPCC, 2019a; Pindyck, 2019)."


id: 1dc8676192aa3b7afeb2aae3fd235131
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content:
"Additional methodological challenges to address (see, for instance, EPRI, 2021; Piontek et al., 2021) include how to capture and represent \r uncertainty and variability in potential damage responses for a given climate and societal condition, combine estimates from different methods \r and sources (including aggregating independent sectoral and regional results), assess sensitivity and evaluate robustness of estimates \r (including sensitivity to model specification), capture interactions and spillovers between regions and sectors, estimate societal welfare \r implications (versus gross domestic product [GDP] changes) of market and non-market impacts, consider distributional effects, represent \r micro- and macro-adaptation processes (and adaptation costs), specify non-gradual damages and nonlinearities, and improve understanding \r of potential long-run economic growth effects. Note that the treatment of time preference, risk aversion and equity considerations have \r [...]"


id: da23dc9346eac6c52520d9767a754648
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content:
"[...] important welfare implications for the aggregation of both potential economic impacts and climate change mitigation costs."


id: be32499285c0c136c1eace47020e94e7
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 30732
content:
"In addition to updated and new methods and estimates, newer literature has explored non-gradual damages, such as climatic and \r socioeconomic tipping points (Lontzek et al., 2015; Mejean et al., 2020), potential damage to economic growth (e.g., Burke et al., 2015; \r Moore and Diaz, 2015), valuing uncertainty in potential damages (Jensen and Traeger, 2014; Lemoine and Traeger, 2016; Cai and Lontzek) \r and representing adaptation (Takakura et al., 2019; Carleton et al., 2020; Rode et al., 2021). Going forward, to help advance science \r and decisions, a key research priority is to understand and evaluate methodological strengths and weaknesses in damage estimation, \r and reconcile the differences affecting comparability in such a way that it informs use of the different lines of evidence. This will require \r greater transparency and assessment of details and assumptions in individual methods, communication and evaluation of alternatives \r [...]"


id: b756fe43d66617e2034d8dc94e8ae27c
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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content:
"[...] for specifying or calibrating climate damage functional representations with respect to climate and non-climate drivers and potential \r nonlinearities, including evaluating data sufficiency for levels within and beyond observations and for characterising physical system \r dynamics, and evaluating the sensitivity of results to model specification and input parameter choices (Cropper et al., 2017). Improving \r the robustness of economic impact estimates is an active area of research. Below we describe the latest estimates."


id: be2b0219319995d5c8c3e98823046e93
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
vector_id: 30723
content:
"Global aggregate economic impact estimates (Figure Cross-Working Group Box  ECONOMIC.1) are generally found to increase with \r global average temperature change, as well as vary by other drivers, such as income and population and the composition of the economy. \r Most estimates are nonlinear with higher marginal economic impacts at higher temperature, although some recover declining marginal \r economic impacts, and functional forms cannot be determined for all studies. The drivers of nonlinearity found in economic impact \r estimates, and the differences in nonlinearity across estimates (e.g., convex versus concave, degree of curvature), are not well understood, \r with methodology construction, assumptions and data all being potential factors. Relative to AR5, there have been more estimates and \r greater variation in estimates, including some recent estimates significantly higher than the range reported in AR5. For most of the \r [...]"


id: bbafa078dc5c16a701396ac58e00158
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"[...] studies shown in Figure Cross-Working Group Box ECONOMIC.1, the visible variation within a study represents alternative socioeconomic \r projections and climate modelling, not economic impacts response uncertainty for a given socioeconomic and climate condition. Response \r uncertainty could be significant, as indicated by some of the results shown in the figure (e.g., Burke et al., 2015; Rose et al., 2017), but \r methodological differences in how uncertainty is characterised (model specification, errors and confidence intervals versus distributions \r of results) limit comparability and assessment. Note that modelling factors between global temperature change and the economic impact \r calculation, such as regional temperature pattern assumptions or assumed SLR dynamics, can also impact calculated estimates (e.g., \r Warren et al.., 2021 PAGE09 estimates versus those in Rose et al.., 2017, Chen et al.., 2020 PAGE-ICE estimates versus Burke et al.., 2015)."


id: 99a79a8d0491af6aae9ea2837c4f35e1
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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content:
"Figure Cross-Working Group Box ECONOMIC.1 |  Global aggregate economic impact estimates by global warming level (annual % global GDP loss \r relative to GDP without additional climate change). Top row panels present estimates by methodology type: (a) statistical modelling, (b) structural modelling and \r (c) meta-analyses, with all estimates from a paper in the same colour and estimates from methodologies other than that highlighted by the panel in grey for reference. \r Second row left panel (d) presents AR5 estimates. Second row right panel (e) presents all estimates in one figure, with the same colours as panels (a-d) using outlined \r dots for the statistical modelling estimates, solid dots for structural modelling estimates, and triangles for meta-analysis estimates. In all panels, lines represent functions, \r with dashed and dotted lines 5th and 95th percentile functions from structural modelling. To avoid duplication, estimates from papers using the economic impacts \r [...]"


id: 923a9d34ed12feca3894c3f075fb5289
created_at: 2023-04-19 13:23:03
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"[...] estimates or model formulations already represented in the figure are not included (e.g., Diaz and Moore, 2017; Chen et al., 2020b; Glanemann et al., 2020; Warren et al., \r 2021). The exception is Burke et al. (2018), with the different estimates shown representing variation across climate scenarios for a given aggregate economic impacts \r specification from Burke et al. (2015)--the 'pooled, short run' statistical specification. Results shown for the latter are estimates with the author's different statistical \r model specifications (and a fixed climate scenario, SSP5). From top to bottom, the Burke et al. (2015) estimates are for the 'pooled, long run', 'differentiated, long run', \r 'pooled, short run' (authors' base case) and 'differentiated, short run' statistical specifications. For Howard and Sterner (2017), the authors' preferred function is shown. \r [...]"


id: c5b853844cf5f63796c8cec7a1f2db2a
created_at: 2023-04-19 13:23:03
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content:
"[...] Overall, estimates shown in the figure can correspond to different future years, reflecting different socioeconomic conditions and climate pathways to a global warming \r level. Global average temperature change bars relative to the period 1850-1900 are shown below the economic cost estimates to provide context to potential future \r warming. Shown are the WGI AR6 assessed best estimates and 90% intervals for the illustrative emissions scenarios considered for the near term 2021-2040, mid-term \r 2041-2060 and long term 2081-2100."


id: 6aed8062d80ada642e01193c899c13ab
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"Differences in methodology type and scope complicate comparison, assessment and synthesis (Cropper et al., 2017; Diaz and Moore, \r 2017; EPRI, 2021; Piontek et  al., 2021). In particular, structural economic modelling and empirical aggregate output modelling are \r fundamentally different, which has been identified as an issue affecting the comparability of results (Cropper et al., 2017). The different \r methodologies affect outcomes, with global aggregate estimates based on statistical methodologies typically higher than those from \r structural modelling (Figure Cross-Working Group Box ECONOMIC.1). This is, in part, due to the relationships in observational data \r captured by statistical modelling, assumed persistence of impacts in statistical modelling, broader adaptation responses in structural \r modelling, and differences in the representation of future societies and how they might evolve, respond and interact. Within statistical \r [...]"


id: f80553adcf518d229f1637fc56c5b769
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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content:
"[...] modelling, results are also found to be very sensitive to the statistical model specification (e.g., Burke et al., 2015; Newell et al., 2021). \r Within structural modelling, differences in representations of biophysical changes and economic structural dynamics contribute to \r differences across structural estimates (e.g., Rose et al., 2017)."


id: 7644b609a9606df9addd53fdca1aff34
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
content_type: text
index: climate_gpt_v2
vector_id: 18027
content:
"The global economic impact estimates discussed in the previous section serve as a key input into the calculation of the value of potential \r net damages caused by a marginal ton of carbon dioxide emissions, or the SCC. To compute an SCC, damage estimates are commonly \r combined in a multi-century modelling framework with socioeconomic and emissions projections, a physical model of the climate, \r including a SLR component, and assumptions about the discount rate, with current frameworks having highly stylised representations of \r these components. Though we do not present quantitative estimates here, due to the challenge of comparability, for economic impacts \r methodologies (as discussed above) as well as other SCC estimation elements, large variations in SCC estimates are found in the \r literature assessed due to, among other things, differences in modelling component representations, input and parameter assumptions, \r [...]"


id: f0af19529f3c5eec2eefff6d9a8d16
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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vector_id: 39716
content:
"[...] considerations of uncertainty, and discounting, inflation, and emissions year (e.g., Tol, 2009; Tol, 2018; Pezzey, 2019; Iese et al., 2021). \r There are also different 'variants' of SCC estimates that differ conceptually, and in magnitude, depending on the reference condition for \r evaluating the impact of a marginal metric ton--is it being evaluated relative to a no-climate-policy baseline, an economically efficient \r pathway that weighs the benefits and costs of emissions mitigation, or a pathway based on a particular climate policy or goal such as \r 2degC or a concentration target (Rose et al., 2017)? The variant of SCC has implications for its applicability to different policy contexts (Rose \r and Bistline, 2016)."


id: 220ff4ad97358914a1f49bb96d55a82d
created_at: 2023-04-19 13:23:03
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vector_id: 3219
content:
"The literature has also assessed the application of aggregate economic impact cost and SCC estimates (Rose and Bistline, 2016; Rose \r et al., 2017; Kaufman et al., 2020) and identified conceptual and technical issues that need to be considered when using results to inform \r policy decisions. These issues include: accounting for endogenous marginal benefits and socioeconomic conditions in evaluating policies \r with non-incremental global emissions implications; consistency in assumptions and treatment of uncertainty across benefit and cost \r calculations; fully accounting for the streams of both mitigation costs and benefits over time; avoiding inefficiently valuing or pricing \r emissions more than once across policies and jurisdictions; and accounting for emissions leakage to capture net climate implications. \r Furthermore, concerns about the robustness of estimates have led some to recommend considering alternatives, such as using marginal \r [...]"


id: 4ee5b8e66ff1ea8cee11ef395d7141c2
created_at: 2023-04-19 13:23:03
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vector_id: 11162
content:
"[...] mitigation cost estimates based on modelling of policy goals instead of the SCC (e.g., Rose, 2012; Pezzey, 2019; Kaufman et al., 2020), \r although this comes with its own set of assumptions and technical challenges."


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"AR6 provides new evidence that relates to the location of the \r transition from undetectable to moderate risk. At the time of SR15, \r observations were suggesting that MISI might already be taking place \r in some parts of the WAIS, while AR5 supported assessment of an \r additional MISI contribution to SLR of several additional tenths of a \r metre over the next two centuries. Since SR15, new observations (WGI \r AR6 Section 9.4.2.1, Fox-Kemper et al., 2021) support the assessment \r of enhanced grounding line retreat and subsequent mass loss through \r basal melt in various parts of Antarctica, and year 2100 sea level \r projections for the RCP8.5 scenario have increased by 10-12 cm \r owing to ice dynamics. However, the onset of MISI is driven by ocean \r warming in specific locations (ice cavities beneath floating ice shelves), \r and the relation between these ocean temperatures and global mean \r [...]"


id: e2f2a9750aad17a0ebbb2139c3a5fccc
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"[...] temperature is indirect and ambiguous. In addition, MISI implies a self\u0002sustaining instability in the absence of further forcing. Because forcing \r is still increasing, it cannot be unambiguously assessed whether MISI \r is driving the observed retreat of grounding lines in the WAIS, or \r whether this retreat is a purely forced response (and would stop if \r the warming stops) or is just a manifestation of natural variability in \r upwelling of warmer waters on the Antarctic continental shelves and, \r as a result, is just a temporary effect. Consistent with SROCC, AR6 \r states with medium confidence that sustained mass losses of several \r major glaciers in the Amundsen Sea Embayment (ASE) are compatible \r with the onset of MISI, but that whether unstable WAIS retreat has \r already begun or is imminent remains a critical uncertainty."


id: e9825e9e659fd3f490889bdb014c8722
created_at: 2023-04-19 13:23:03
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"In the Amazon Forest, increases in tree mortality and a decline in the \r carbon sink are already reported (Brienen et al., 2015; Hubau et al., \r 2020), and old-growth Amazon Rainforest may have become a net \r carbon source for the period 2010-2019 (Qin et al., 2021). Estimates \r which include land use emissions indicate the region may have become \r a net carbon source (Gatti et al., 2021). Fire activity is an important \r driver, and both bigger fires (Lizundia-Loiola et al., 2020) and longer \r fire season (Jolly et al., 2015) have been reported in South America, \r although this is strongly linked to land use and land use change as \r well as climate (Kelley et al., 2021), and indeed land use change may \r be a stronger driver of potential loss of the Amazon Forest than climate \r change. The risk of climate-change-related loss of the Amazon Forest is \r assessed already above 'undetectable', but has only emerged over the \r [...]"


id: fcb843aa1b35ebae9da28bdd9ccf1e18
created_at: 2023-04-19 13:23:03
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content:
"[...] last few years, when global warming had reached 1degC, and is linked \r to land use as well as GSAT levels. Chapter 2 has assessed ecosystem \r carbon loss from tipping points in tropical forest and loss of Arctic \r permafrost, and finds a transition to moderate risk over the range \r 0.6-0.9degC (medium confidence). Specifically, WGII AR6 Table  SM2.5 "


id: df644eb16662514214e2e9680461d613
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content:
"and 2-6 m at 2.0degC peak warming (WGI AR6 TS, Box TS.4 Figure 1; \r Arias et  al., 2021). This is an important feature of the approach to \r this RFC (i.e., it is not primarily focused on implications for the next \r 100-200  years). In addition, since the AR5, there is new evidence \r about the Last Interglacial (LIG), when global mean temperature was \r about 0.5-1.5degC above the pre-industrial era. AR6 assesses that it is \r virtually certain that sea level was higher than today at that time, likely \r by 5-10 m (medium confidence) (B.5.4 WGI AR6 SPM,(IPCC, 2021)). \r Mid-Pliocene temperatures of 2.5degC (about 3 million years ago when \r global temperatures were 2.5-4degC higher) also provide evidence as \r an upper limit for the transition to high risk associated with long\u0002term equilibrium SLR of 5-25 m (WGI AR6 SPM B.5.4). Projected SLR \r for 2300 in an RCP8.5 or SSP5-8.5 scenario (consistent with a peak \r warming range of 4-6degC, varies between 1.7-6.8 m and 2.2-5.9 m, \r [...]"


id: 49f4d96ed0122573747a3c78cb069c33
created_at: 2023-04-19 13:23:03
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"[...] respectively (WGI AR6 TS Box  TS.4, Arias et  al., 2021), and when \r accounting for marine ice cliff instability taking place on Antarctica, \r these numbers may increase to a range of 9.5-16.2 m (WGI AR6 TS \r Box TS.4, Arias et al., 2021)."


id: 9acdb3fc01642abf67471130b54e8fc1
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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content:
"CMIP6 climate models project drying in the Amazon--especially in \r June-July-August, irrespective of future forcing scenario, but which \r increases with GSAT/higher scenarios (Lee et  al., 2021). For higher \r GSAT levels, Burton et  al. (2021) explore different forcing scenarios \r and found, regardless of scenario, burned area increases markedly \r with GSAT. New understanding of the role of vegetation stomata will \r act to exacerbate this drying (Richardson et al., 2018b). A transition \r to high risk of savannisation for the Amazon alone was assessed to \r lie between 1.5degC and 3degC with a median value of 2.0degC. A mean \r temperature increase of 2degC could reduce Arctic permafrost area ~15% \r by 2100 (Comyn-Platt et al., 2018). Chapter 2 has assessed ecosystem \r carbon loss from tipping points in tropical forest and loss of Arctic \r permafrost, and finds a transition from moderate to high risk over \r the range 1.5degC to 3degC with a median of 2degC (medium confidence,\r [...]"


id: ed6c6e2ebbc488bf19ab6bea0e873627
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"[...] Table SM2.5, Figure 2.11). Its assessment of the transition from high \r to very high risk is located over the range 3-5degC (low confidence,\r Table SM2.5, Figure 2.11) based on the potential for Amazon Forest \r dieback between 4degC and 5degC temperature increase above the pre\u0002industrial period (Salazar and Nobre, 2010)."


id: 9db95901c046292e62609f7b6d8bda48
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"There is high confidence in the existence of threshold behaviour of \r the Greenland Ice Sheet in a warmer climate (WGI AR6 Ch 9, Fox\u0002Kemper et al., 2021); however, there is low agreement on the nature \r of the thresholds and the associated tipping points. Similarly, the \r likelihood for accelerated and irreversible mass loss from Antarctica \r increases with increasing temperatures, but thresholds cannot yet be \r unambiguously identified. By the year 2100, sea level projections (AR6 \r WGI Figure SPM.8 (IPCC, 2021)) now range from 0.57 m (0.37-0.85 m) \r for the SSP1-1.9 scenario to 1.35 m (1.02-1.89 m) for the SS5-8.5 \r scenario and become 1.99 m for the latter scenario (1.02-4.83 m) in the \r case of low-likelihood, high-impact outcomes resulting from ice sheet \r instability, for which there is limited evidence. It should be noted that \r inclusion of such low-likelihood, high-impact outcomes dominated by \r not-well-understood processes affecting ice dynamics on the large ice \r [...]"


id: b6e3781724e44a06fd920d90dfc38009
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"[...] caps of Greenland, and in particular Antarctica, would also enhance \r the sea level projections for other scenarios, but to a lesser extent for \r increasingly weaker forcing. No quantitative assessment of their effect \r in other scenarios than SSP5-8.5 yet exists as such simulations with ice \r sheet models have not been carried out, or only in a very limited amount."


id: af8aa6d41f278aa9efd6ec21a8e32d0e
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"Lack of evidence on the potential for adaptation to adequately reduce \r risk is a critical gap in our ability to assess global risk transitions at \r the RFC level, but not the only gap. In some cases, such as RFC1, \r the widespread nature and rapid speed of the escalating risks, in \r combination with limited ability to adapt, means that transitions \r to high risk may occur despite medium or even high levels of \r adaptation. Risks that are largely natural and not widely mediated \r by human vulnerability are thus less likely to have risk transitions \r that shift under higher societal adaptation. Risk transitions that \r are mediated through human systems, such as distribution impacts, \r for example, are more likely to shift in response to adaptation as \r impacts are strongly mediated through vulnerability within human \r systems, but such a shift is difficult to quantify given knowledge \r gaps in the literature (Section 16.3). However, in some circumstances, \r [...]"


id: de5305894c2862dff0878e504efb989d
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"[...] expanded global adaptation could slow some of these transitions \r (low confidence); in the case of RFC2, RFC3 and RFC4, the literature \r suggests that coordinated global adaptation could increase the \r global temperature at which risks transition from moderate to high, \r for example the prevention of mortality associated with heat stress \r within RFC2."


id: 1d631bde429bec208dd796daf4e31a34
created_at: 2023-04-19 13:23:03
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content:
"A higher level of adaptation, applied globally and effectively, could \r have larger benefits for several RFC, either postponing the onset of \r a high level of risk until a higher level of warming is reached (and \r allowing time for mitigation efforts) or allowing a system to survive \r a temporary overshoot of a lower temperature threshold. Adaptations \r are likely to have significant potential to reduce risks (Magnan et al., \r 2021), in particular for risks mediated through human systems. \r However, there is limited evidence available to assess the extent to \r which current or potential adaptations are or would be adequate in \r reducing climate risks at different levels of warming, and adaptation \r implications for risk transitions will be highly localised. Pathways \r and opportunities for risk management and adaptation actions with \r transformational potential are discussed in Chapter 17, together with \r enabling factors, governance frameworks, financing, success factors, \r [...]"


id: f1eb1ae2fec434487cdf954299ebb777
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"[...] and monitoring and evaluation discussed in Chapter 18, supporting \r sustainable system transitions and leading to options for climate \r resilient development pathways."


id: 66c9939fe951c0c31b6c1ba7fd630436
created_at: 2023-04-19 13:23:03
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"The IPCC defines key risks related to climate change as potentially severe risks that are relevant to the primary goal \r of the United Nations Framework Convention on Climate Change treaty to avoid 'dangerous human interference \r with the climate system', and whatever the scale considered (global to local). What constitutes 'dangerous' or \r 'severe' risks is partly a value judgement and can therefore vary widely across people, communities or countries. \r However, the severity of risks also depends on criteria like the magnitude, irreversibility, timing, likelihood of the \r impacts they describe, and the adaptive capacity of the affected systems (species or societies). The Working Group \r II authors use these criteria in various ways to identify those risks that could become especially large in the future \r owing to the interaction of physical changes to the climate system with vulnerable populations and ecosystems \r [...]"


id: 461632e0ee175018f78a20c732fe2dd7
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"[...] exposed to them. For example, some natural systems may be at risk of collapsing, as is the case for warm-water \r coral reefs by mid-century, even if global warming is limited to +1.5degC. For human systems, severe risks can include \r increasing restriction of water resources that are already being observed; mortality or economic damages that are \r large compared with historical crises; or impacts on coastal systems from SLR and storms that could make some \r locations uninhabitable."


id: 6707ba64f302c7468f53a7990da3bab
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content:
"These representative key risks are expected to increase in the coming decades and will depend strongly not only \r on how much climate change occurs, but also on how the exposure and vulnerability of society changes, as well \r as on the extent to which adaptation efforts will be effective enough to substantially reduce the magnitude of \r severe risks. The report finds that risks are highest when high warming combines with development pathways with \r continued high levels of poverty and inequality, poor health systems, lack of capacity to invest in infrastructure, \r and other characteristics making societies highly vulnerable. Some regions already have high levels of exposure and \r vulnerability, such as in many developing countries as well as communities in small islands, Arctic areas and high \r mountains; in these regions, even low levels of warming will contribute to severe risks in the coming decades. Some \r [...]"


id: 435aa7989a91e67537e4b93f9fc63f57
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"[...] risks in industrialised countries could also become severe over the course of this century, for example if climate \r change affects critical infrastructure such as transport hubs, power plants or financial centres. In some cases, such \r as coral reef environments and areas already severely affected by intense extreme events (e.g., recent typhoons or \r wildfires), climate risks are already considered severe."


id: c86973b46ee4b99fae299ac13c6b83de
created_at: 2023-04-19 13:23:03
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"Adaptation-related responses are actions that are taken with the intention of managing risks by reducing \r vulnerability or exposure to climate hazards. While mitigation responses aim to reduce greenhouse gas emissions \r and slow warming, adaptations respond to the impacts and risks that are unavoidable, either due to past emissions \r or failure to reduce emissions. However, while these responses intend to reduce risks, it is difficult to determine \r precise levels of risk reduction that can be attributed to adaptation. Changing levels of risk as well as other actions--\r such as economic development--make it challenging to definitively connect specific levels of risk reduction with \r adaptation. Although it is not feasible to assess the adequacy of adaptation for risk reduction at global or regional \r levels, evidence from specific localised adaptation projects do show that adaptation-related responses reduce \r [...]"


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"[...] risk. Moreover, many adaptation measures offer near-term co-benefits related to mitigation and to sustainable \r development, including enhancing food security and reducing poverty."


id: 711c9a727444006c9aac11e69d40dc63
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"While adaptation is important to reduce risk, adaptation cannot prevent all climate impacts from occurring. \r Adaptation has soft and hard limits, points at which adaptive actions are unable to prevent risks. Soft limits can \r change over time as additional adaptation options become available, while hard limits will not change as there are \r no additional adaptive actions that are possible. Soft limits occur largely due to constraints--factors that make it \r harder to plan and implement adaptation, such as lack of financial resources or insufficient human capacity. Across \r regions and sectors, the most challenging constraints to adaptation are financial and those related to governance, \r institutions and policy measures. Limited funding and ineffective governance structures make it difficult to plan \r and implement adaptation-related responses which can lead to insufficient adaptation to prevent risks. Small-scale \r [...]"


id: 94acbe80dbac46255b72ebcdea621169
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content:
"[...] farmers and coastal communities are already facing soft limits to adaptation as measures that they have put in \r place are not enough to prevent loss. If constraints that are limiting adaptation are addressed, then additional \r adaptation can take place and these soft limits can be overcome. Evidence on limits to adaptation is largely focused \r on terrestrial and aquatic species and ecosystems, coastal communities, water security, agricultural production, and \r human health and heat."


id: 6508c9caa4e5ad4886584326a84cfd09
created_at: 2023-04-19 13:23:03
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vector_id: 15042
content:
"Global mean temperature has already risen by more than 1degC, and that also means that the impacts of climate change \r become more visible. Many natural and human systems are sensitive to weather conditions. Crop yields, river floods \r and associated damages, ecosystems such as coral reefs, or the extent of wildfires are affected by temperatures \r and precipitation changes. Other factors also come into play. So, for example, crop yields around the world have \r increased over the last decades because of increasing fertilizer input, improved management and varieties. How do \r we detect the effect of climate change itself on these systems, when the other factors are excluded? This question \r is central for impact attribution. 'Impact of climate change' is defined as the difference between the observed \r state of the system (e.g., level of crop yields, damage induced by a river flood, coral bleaching) and the state of the \r [...]"


id: 4bd05bcaeb7965c61215186b9fd8238e
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"[...] system assuming the same observed levels of non-climate-related drivers (e.g., fertilizer input, land use patterns or \r settlement structures) but no climate change."


id: fa5b421d396e3467a5058d9ebc795385
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updated_at: 2023-04-19 13:23:03
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content:
"Overall, however, the extent of adaptation-related responses globally is low. On average, responses tend to be \r local, incremental, fragmented, and consistent with Business-As-Usual practices. There are no global regions or \r sectors where the overall adaptation-related response has been rapid, widespread, substantial and has overcome or \r challenged key barriers. The extent of adaptation thus remains low globally, with significant potential for increased \r scope, depth, speed and the challenging of adaptation limits. Examples of low-extent adaptations include shifts by \r subsistence farmers in crop variety or timing, household flood barriers to protect houses and gardens, and harvesting \r of water for home and farm use. In contrast, high-extent adaptation means that responses are widespread and \r coordinated, involve major shifts from normal practices, are rapid, and challenge existing constraints to adaptation. \r [...]"


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content:
"[...] Examples of high-extent adaptations include planned relocation of populations away from increasingly flood-prone \r areas, and widely implemented social support to communities to prevent migration or displacement due to climate \r hazards."


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content:
"A picture speaks a thousand words. The use of images to share ideas and information to convey scientific \r understanding is an inclusive approach for communicating complex ideas. A risk variation diagram is a simple way \r to present the risk levels that have been evaluated for any particular system. These diagrams take the form of bar \r charts where each bar represents a different category of risk. The traffic light colour system is used as a basis for \r doing the risks, making it universally understandable. These diagrams are known colloquially as 'burning ember' \r diagrams, and have been a cornerstone of IPCC assessments since the Third Assessment Report, and further developed \r and updated in subsequent reports. The fact that the diagrams are designed to be simple, intuitive and easily \r understood with the caption alone has contributed to their longstanding effectiveness. Here, in Figure FAQ16.5.1 \r [...]"


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"[...] below, we provide a simplified figure of this chapter's burning embers for five categories of global aggregate risk, \r called Reasons for Concern (RFCs), which collectively synthesise how global risk changes with temperature. The \r diagram shows the levels of concern that scientists have about the consequences of climate change (for a specified \r risk category and scope), and how this relates to the level of temperature rise."


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content:
"Figure FAQ16.5.1 |  Simplified presentation of the five Reasons for Concern burning ember diagrams as assessed in this report (adapted from \r Figure 16.15). The colours indicate the level of risk accrual with global warming for a low-adaptation scenario. RFC1 Unique and threatened systems: ecological \r and human systems that have restricted geographic ranges constrained by climate-related conditions and have high endemism or other distinctive properties. \r Examples include coral reefs, the Arctic and its Indigenous People, mountain glaciers and biodiversity hotspots. RFC2 Extreme weather events: risks/impacts to \r human health, livelihoods, assets and ecosystems from extreme weather events such as heatwaves, heavy rain, drought and associated wildfires, and coastal \r flooding. RFC3 Distribution of impacts: risks/impacts that disproportionately affect particular groups owing to uneven distribution of physical climate change \r [...]"


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"[...] hazards, exposure or vulnerability. RFC4 Global aggregate impacts: impacts to socio-ecological systems that can be aggregated globally into a single metric, \r such as monetary damages, lives affected, species lost or ecosystem degradation at a global scale. RFC5 Large-scale singular events: relatively large, abrupt and \r sometimes irreversible changes in systems caused by global warming, such as ice sheet disintegration or thermohaline circulation slowing."


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"Contributing Authors: Rawshan Ara Begum (Malaysia/Australia/Bangladesh), Lea Berrang\u0002Ford (UK/Canada), Rachel Bezner Kerr (Canada), Sukaina Bharwani (UK), Robbert Biesbroek (the \r Netherlands), Laurens Bouwer (the Netherlands), Emily Boyd (Sweden), Lily Burge (UK), Massimo \r Cattino (Italy), Isabelle Cojocaru-Durand (Canada), Riyanti Djalante (Japan), Mauricio Dominguez \r Aguilar (Mexico), Kristie Ebi (USA), Hannah Farkas (USA), Simon French (UK), Katja Frieler (Germany), \r Matthias Garschagen (Germany), Adugna Gemeda (Ethiopia), Francois Gemenne (Belgium), \r Michael Gerrard (USA), Elisabeth Anne Gilmore (USA), Nicoletta Giulivi (Italy/Guatemala), Maron \r Greenleaf (USA), Marjolijn Haasnoot (the Netherlands), Ralph Hamman (Germany), Kirstin \r Holsman (USA), Christian Huggel (Switzerland), Margot Hurlbert (Canada), Kripa Jagannathan \r (India/USA), Catalina Jaime (UK/Colombia), Richard Jones (UK), Sirkku Juhola (Finland), Rachel E. \r [...]"


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"[...] Keeton (the Netherlands/USA), Zoe Klobus (USA), Carola Kloeck (Germany/France), Bettina Koelle \r (South Africa/Germany), Robert Kopp (USA), Carolien Kraan (the Netherlands), Judy Lawrence \r (New Zealand), Timo Leiter (Germany/UK), Robert Lempert (USA), Debora Ley (Mexico), Tabea \r Lissner (Germany), Megan Lukas-Sithole (South Africa), Katharine Mach (USA), Alexandre Magnan \r (France), Kathleen Miller (USA), Lionel Mok (Canada), Veruska Muccione (Italy), Rupa Mukerji \r (India), Johanna Nalau (Australia/Finland), Baysa Naran (Mongolia), Camille Parmesan (USA), Lei \r Pei (China), Mark Pelling (UK), Rosa Perez (Phillippines), Lavinia Perumal (South Africa), Patricia \r Pinho (Brazil), Madeleine Rawlins (UK), Neha Rai (UK), Britta Rennkamp (South Africa/Germany), \r Alexandra Rinaldi (USA), Olivia Rumble (South Africa), Liane Schalatek (USA), Emma Lisa Freia \r Schipper (Sweden/USA), Pasang Yangjee Sherpa (USA/Nepal), Sabrina Shih (USA), Roopam Shukla \r [...]"


id: db1ce3df2de5c4b2cae59bb0d32fd7b0
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"[...] (India/Germany), Rachael Shwom (USA), Nick Simpson (Zimbabwe/SouthAfrica), Chandni Singh \r (India), Doreen Stabinsky (USA), Adelle Thomas (Bahamas), M. Cristina Tirado-von der Pahlen \r (USA/Spain),  Cathy Vaughn (USA), Maria Alejandra Velez (Colombia), Ivo Wallimann-Helmer \r (Switzerland), Charlene Watson (UK), Romain Weikmans (Belgium), Andrew Jordan Wilson (USA), \r Katy Wilson (UK), Mark Workman (UK), Anita Wreford (New Zealand)"


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"arrangements of public, private and community actors, is being \r increasingly recognised as important across many decision\u0002making settings (high confidence). Public governance leadership has \r the largest role for social safety nets, spatial planning and building codes \r (high confidence). Private sector governance is important for insurance \r and for minimising the stressors that can negatively impact ecosystems \r and their functions, especially in the absence of public regulations or \r enforcement (medium confidence). Communities and individuals play \r the largest role in governance of adaptations to farming and fishery \r practices and ecosystem-based adaptations (medium confidence). \r Informal or individual-led decision-making is more common in food \r security and livelihood-related adaptations, such as changes to diets, \r livelihood diversification and seasonal migration (high confidence). \r People who have experienced climate shocks are more likely to take \r [...]"


id: d486155494c19de0fea27783e8a94559
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"[...] on informal adaptation measures, and in places where people are more \r exposed to extreme events, autonomous adaptation is more common \r (high confidence) {17.2.1, 17.3.2, 17.4.2}."


id: 59038affa623740ce33f95cd75373099
created_at: 2023-04-19 13:23:03
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"National and international legal and policy frameworks \r and instruments support the planning and implementation \r of adaptation and climate risk management across scales, \r especially when combined with guidelines for action (medium \r confidence). Nationally Determined Contributions (NDCs) have been \r drivers of national adaptation planning, with cascading effects on \r sectors and sub-national action, especially in developing countries \r (high confidence). Nearly all developing countries (particularly \r Small Island Developing States [SIDS]) that included an adaptation \r component in their NDCs consider adaptation the most urgent aspect \r of their national climate change response (high confidence). A steady \r increase in national and sub-national laws, policies and regulations \r that mandate reporting and risk disclosure has promoted adaptation \r response across public agencies, private firms and community \r organisations (high confidence). Greater adaptation is present where \r [...]"


id: 5db945b7fdfd1299e7301011608b6e44
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"[...] national climate laws and policies require adaptation action from \r lower levels of government and include guidelines on how to do so \r (medium confidence) {17.4.2}."


id: a3f27ca52eb500943815060534b2f654
created_at: 2023-04-19 13:23:03
updated_at: 2023-04-19 13:23:03
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"Recognition of the critical role of financing for adaptation \r and resilience as an important enabler for climate risk \r management has strengthened (high confidence). Yet, since \r the Intergovernmental Panel on Climate Change (IPCC) 5th \r Assessment Report (AR5), the gap between the estimated costs \r of adaptation and the documented (tracked) finance allocated \r to adaptation has widened (high confidence). Estimated global \r and regional costs of adaptation vary widely due to differences in \r assumptions, methods and data; the majority of more recent estimates \r are higher than the figures presented in AR5 (high confidence). A \r high proportion of developing country NDC adaptation contributions \r are conditional on external financial support, emphasising the \r crucial role of international finance to achieving adaptation efforts \r commensurate with climate risks (high confidence). Developed country \r climate finance leveraged for developing countries for mitigation and \r [...]"


id: 8dffe485932b6b909252a19412fe252d
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updated_at: 2023-04-19 13:23:03
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index: climate_gpt_v2
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content:
"Private sector financing for adaptation has been increasingly \r promoted as a response to realised adaptation finance needs \r (high confidence). However, private sector financing of \r adaptation has been limited, especially in developing countries \r (high confidence). Tracked private sector finance for climate change \r action has grown substantially since 2015, but the proportion \r directed towards adaptation has remained small (high confidence); \r in 2018, these contributions were 0.05% of total climate finance and \r 1% of adaptation finance. A key challenge for private sector financing \r of adaptation is demonstrating financial return on investment, as \r many benefits of adaptation arise as avoided damages or public \r goods, rather than direct revenue streams (medium confidence). \r Leveraging private finance in developing countries is often more \r difficult because of risk (perceived and real) to investors, reducing \r [...]"


id: 1c221ced8b7e4572f85c182512eb5af5
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"[...] the pool of potential investors and/or raising the cost (interest) of \r investment (medium confidence) {17.4.3.; Cross-Chapter Box Finance \r in this Chapter}."


id: aff72b1746b6b4a4e4e5779e4326b288
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"Decision support tools and decision-analytic methods are \r available and are being applied for managing climate risks in \r varied contexts, including where deep uncertainty is present \r (high confidence). These tools and methods have been shown \r to support deliberative processes where stakeholders jointly \r consider factors such as the rate and magnitude of change \r and their uncertainties, associated impacts and timescales of \r adaptation needed along multiple pathways and scenarios of \r future risks (high confidence). However, comparative evidence \r on the relative utility of different analytical methods in their use \r by decision makers for managing climate risks is an important gap \r (medium confidence). Nevertheless, robust decision-making, using \r pathway analyses to determine 'no regrets' options among trade-offs, \r has been shown to be a useful starting point under deep uncertainty \r [...]"


id: 1a32542da6b295091169e2ada51cb54f
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"[...] (medium confidence). Methods for analysing options differ across geo\u0002political scales, with modelling studies being a particularly prominent \r method across scales from community and urban to regional and \r national (high confidence) {17.3.1, 17.3.2, 17.6, Cross-Chapter \r Box DEEP in this Chapter}."


id: 4fc53e8423412de2d97fbcf2e5967a82
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"Catalysing conditions and windows of opportunity can drive \r shifts in motivation and adaptation effort, stimulating more \r rapid uptake of existing and new adaptation options (medium \r confidence). Decision makers can take advantage of windows of \r opportunity to promote rapid and effective responses in reactive \r and proactive cases. Disaster events or shocks such as wildfires, \r tropical cyclones, heatwaves or coral bleaching have catalysing \r characteristics (high confidence). Additional types of catalysing \r conditions include climate litigation and the presence of individuals \r and organisations that act as policy and decision innovators, including \r government and business innovators in cities (medium confidence), \r stimulating action within and beyond their immediate contexts \r (medium confidence). Litigation on failure of government and business \r to adapt is becoming more frequent and is expected to increase as \r [...]"


id: 2a4d43db2adcbdf7959e441f9bd48c48
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"[...] climate impact attribution science matures further (high confidence) \r {Cross-Chapter Box LOSS in this Chapter; 17.4.5.2, 17.4.5.3}."


id: a640b7f74486d8b119fab7dae068f8b6
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"Monitoring and evaluation (M&E) are essential for tracking \r adaptation progress and learning about adaptation success \r and maladaptation (high confidence). M&E application has \r increased since AR5 at the local, project and national level, but \r is still at an early stage in most countries (high confidence) \r and underutilised as a way to assess adaptation outcomes \r at longer time frames (high confidence). About one-third of \r countries have undertaken steps to develop national adaptation M&E \r systems, but fewer than half of these are reporting on implementation \r (medium confidence). M&E, as well as tracking global progress \r on adaptation, are confronted with a number of challenges (high \r confidence), such as a comparability in what counts as adaptation \r and limited availability of data across scales. The relative strength \r and weaknesses of different approaches and their applicability have \r not been systematically assessed, but the diversity of approaches \r [...]"


id: fb05d889ff5622e061c7db8b713cc489
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"[...] being used could provide a more comprehensive assessment of \r global adaptation progress {17.5.2, Cross-Chapter Box PROGRESS in \r this Chapter}."


id: 919803283520d86c07df4b2bc50e0f2b
created_at: 2023-04-19 13:23:03
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"Effective management of climate risks is dependent on \r systematically integrating adaptations across interacting \r climate risks, ensuring that measures of success include factors \r important to climate resilient development, and accounting \r for the dynamic nature of climate risks over time (very high \r confidence). Across the Working Group II report are examples of \r how managing adaptations to reduce climate risks can negatively \r or positively affect sustainable development, thereby impacting the \r potential for climate resilient development. Climate risks can emerge \r at different rates and time horizons, and the interactions between \r risks vary from region to region (very high confidence). The need to \r manage these risks in an integrated manner is demonstrated by the \r diverse and interacting impacts of climate risks on ecosystems, cities, \r health, and poverty and livelihoods, such as in the water-energy-\r food nexus (high confidence). Expertise and resources for integrated \r [...]"


id: ebac646603cd7ef1e83fec61a19945af
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"[...] risk management vary between the developed and developing \r countries (high confidence). Integrated pathways for managing \r climate risks will be most suitable when 'low regrets' anticipatory \r options are established jointly across sectors in a timely manner, \r path dependencies are avoided in order to not limit future options for \r climate resilient development, and maladaptations across sectors are \r avoided (high confidence). National Adaptation Plans have potential \r to integrate participatory, iterative processes to monitor, review and \r update adaptations as knowledge, experience and resources become \r available {17.6; Cross-Chapter Box DEEP in this Chapter}."


id: 8df2e78adea337af52e6887f748190e2
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"Addressing the impacts and risks associated with observed and \r projected climate change (Chapter 16) is fundamentally and \r intricately tied to the decision-making options available to manage \r those risks. Climate risk decision-making focuses on the processes \r needed to identify and characterise those risks as well as generate \r plans and policies to reduce the likelihood and/or magnitude of \r adverse potential consequences, based on assessed or perceived risks \r (derived from the definition of risk and risk management in Chapter \r 1). This chapter presents an assessment of the evidence on climate \r risk decision-making as a set of processes that involve a range of \r actors in different contexts resulting in diverse outcomes. The climate \r risk decision makers and their actions are the central focus of the \r assessment. The chapter is an assessment of the evidence of the \r decision-making options that are available in practice, and functions \r [...]"


id: 260f01114636c70505768e2551b2671c
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"[...] as a central pivot point between the identification of key climate \r risks (Chapter 16) and the means to integrate and leverage action on \r climate risk decision-making into the broader requirements of climate \r resilient development pathways (Chapter 18). This section introduces \r the main entry points on decision-making that have framed this \r assessment (Sections  17.1.1.1-17.1.1.5), as well as the key terms \r used to frame this assessment and its organisation in this chapter \r (Section 17.1.2)."


id: 1d387f9bffcd7e7ca3c9800ea29fcca
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"Since AR5, significant advances have been made in regard to the \r understanding of the drivers of decision-making and contexts in which \r climate risk decision-making takes place. Climate risk decision-making \r generally, and adaptation specifically, has been a focus within the IPCC \r special reports in the sixth assessment cycle. An overall goal of climate \r risk management is to eliminate or reduce the risk to levels that are \r socio-politically and economically acceptable. Risk management to an \r acceptable level may not be feasible because of limits or barriers to \r adaptation. Future potential risks are a more complex matter given \r the need to define time scales and spatial extent, and uncertainties. \r In the IPCC Special Report on Global Warming of 1.5degC (SR1.5) (IPCC, \r 2018a), the risks associated with climate-related impacts were found \r to be higher under emission scenarios above 1.5degC, raising awareness \r [...]"


id: d1159173aa7f32da300bcaf9b8256a3a
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"[...] for the need to limit the impacts of warming through the acceleration \r of climate mitigation and both incremental and transformational \r adaptation (IPCC, 2018a)."


id: c92b284a7d6feefd8d3034e9e889452d
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"A central framing point is the connection between climate risk \r decision-making and adaptation. Adaptation for human systems in \r this report is introduced in Chapter 1 and defined in the Glossary \r as 'the process of adjustment to actual or expected climate and its \r effects, in order to moderate harm or exploit beneficial opportunities'. \r In natural systems, adaptation is the process of adjustment to actual \r climate and its effects; human intervention may facilitate adjustment \r to expected climate and its effects (see IPCC 6th Assessment Report \r [AR6] Glossary [Annex II]). In this chapter, we consider adaptations \r that may be implemented by people, whether they be to support \r human, managed, or natural systems, and the processes and factors \r that underpin adaptation in these diverse settings. Different types of \r adaptation have been distinguished in Chapter 1, including anticipatory \r versus reactive, autonomous versus planned, and incremental versus \r [...]"


id: 19f176e8ac569baf35d3f3e2761bbccd
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"[...] transformational (IPCC WGII glossaries; Chapters 16-18). These \r dichotomies and interactions are assessed here. Implementation \r of adaptation through iterative risk management decision-making \r emphasises that anticipating and responding to climate change does \r not consist of a single set of judgements at a single point in time, but \r rather an ongoing cycle of assessment, action, reassessment, learn and \r response (Chapter 1)."


id: 554d2798cdc546ffd1b2fcffac0766a6
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"Another significant advance is that, instead of cataloguing decision\u0002making strategies, the literature has now evolved to the point \r where adaptation progress, effectiveness and efficiency can be more \r meaningfully assessed through increased monitoring and evaluation \r capacity, although the ability to measure success and effectiveness \r is not fully developed and is hampered by lack of data, agreed \r methods and terms, and time to fully evaluate adaptation actions \r (see Sections 17.3.3 and 17.5, Cross-Chapter Box PROGRESS in this \r Chapter). The ambition to describe effectiveness and success illustrates \r further maturation of the literature on climate risk decision-making \r as a system process. Overall, the process of climate risk decision\u0002making remains dynamic, and the chapter attempts to assess a variety \r of proactive management approaches being developed and tested \r to address adverse, diverse and complex risks in a wide range of \r [...]"


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"[...] developing and developed country contexts (Figure 17.1). The chapter \r provides a synthesis of how these new approaches are reflected in the \r sectoral and regional chapters and cross-chapter papers of this report \r (Chapters 2-15; Cross-Chapter Papers 1-7). Specifically, the goal is to \r provide a line of sight between the sectoral and regional chapters and \r cross-chapter papers' decision-making assessment to sections in this \r chapter. This synthesis also helps to present the varying and context\u0002driven character of adaptation strategies now in practice and being \r considered."


id: 61b16d357b7d5f3459e647602f302a15
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"Since AR5, there has been an increasing ambition for adaptation, \r signalled by growing attention to the adaptation gaps and deficits, \r which call for extensive and intensive levels of action (Chen et al., 2016; \r UNEP, 2017; Tompkins et  al., 2018; Valente and Veloso-Gomes, 2020; \r UNEP, 2021a), as well as increased attention to co-benefits between \r climate risk reduction and other benefits, such as equity and biodiversity \r conservation (Colloff et  al., 2017, Section  17.5.1; Smith et  al., 2020). \r Climate risk decision-making as an object of study has emerged in a more \r central location within the literature as adaptation moves from planning \r into the realm of practice. The broad sense of urgency (summarised in \r Wilson and Orlove, 2019; Wilson and Orlove, 2021) shows growth of the \r term 'urgency' in both scholarly publications and the popular press since \r 2014, building on earlier increases starting around 2005, and a dramatic \r [...]"


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"[...] spike of the terms 'climate crisis' and 'climate emergency'. Paralleling \r this call for more extensive and rapid action is the emergence of the term \r 'transformational' adaptation and decision-making. Transformational \r adaptation (defined and deeply examined in Chapters 1 and 16 and \r Section 17.2) highlights efforts that involve large-scale, systemic change \r (Wilson et al., 2020) and involves 'adapting to climate change resulting \r in significant changes in structure or function that go beyond adjusting \r existing practices including approaches that enable new ways of \r decision-making on adaptation' (IPCC, 2018a). The complex relationship \r between incremental adaptation and transformational adaptation is \r presented and reviewed in Section 17.2. Furthermore, the literature since \r the AR5 report has moved beyond the question of limits and barriers \r to adaptation as relevant aspects for decision-making to additionally \r [...]"


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"[...] assessing drivers of change, with increasing focus devoted to more \r nuanced and differentiated contexts for action."


id: c0a7e8efde8dfc6d1532fcf5c466d2f2
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"In AR6 (Chapter 16 and cross-chapter papers), over 100 key risks \r have been identified across regions and sectors, which have the \r potential to manifest into severe impacts that are relevant to the \r interpretation of UNFCCC Article 2, specifically on the objective \r to avoid dangerous anthropogenic interference with the climate \r system. These risks are likely2\r  to become more severe under higher \r warming scenarios and social-ecological conditions that yield high \r exposure and vulnerability to the associated climate-related hazards. \r In this report, these key risks have been grouped into categories \r represented by eight overarching risks (called Representative Key \r Risks, RKRs) relating to: (1) coastal socio-ecological systems; (2) \r terrestrial and ocean ecosystems; (3) critical physical infrastructure, \r networks and services; (4) living standards; (5) human health; (6) \r food security; (7) water security; and (8) peace and human mobility \r [...]"


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"[...] (Chapter 16). Decision-making options for managing these risks, such \r as selecting the relevant adaptation options to implement, require an \r assessment of the local context in which these impacts are likely to \r be experienced, as well as the local to global collective implications \r of those actions (Sections 17.2 and 17.5)."


id: 5d3b56f1448e73ec080a3db31cff79
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"However, a wealth of information has recently become available on how success and effectiveness of adaptation could be assessed, \r defined or investigated in certain settings (Patt and Schroter, 2008; Morecroft Michael et al., 2019; Tubi and Williams, 2021) or across \r a larger set of adaptations (Hegger et al., 2012; Eriksen et al., 2015; Gajjar et al., 2019a; Owen, 2020; Singh et al., 2021). Accordingly, \r successful adaptation is understood as effective adaptation, in that it reduces climate impacts, vulnerabilities and risk, and additionally \r balances synergies and trade-offs across diverse objectives, perspectives, expectations and values (Eriksen et al., 2015; Juhola et al., 2016; \r Gajjar et al., 2019a; Owen, 2020; Singh et al., 2021). Across this report, four factors are identified as enabling conditions of successful \r adaptation, which include a focus on recognitional, procedural and distributional justice as well as flexible and strong institutions that \r [...]"


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"dimension of climate change, as described in Chapter 8, vulnerability, \r inequality and poverty influence these portfolios of adaptation and \r transformational change. Particularly for change where residual risks \r remain that may lead to exceeding the limits of adaptation, increasingly \r transformational adaptation and policy innovation will be important. \r Section  17.2.1 assesses options for climate risk management from \r around the world that reduce, manage or retain climate-related risks \r and assesses their contribution to reducing vulnerability and exposure, \r how they are governed, and the benefits to humans and ecosystems. \r Section 17.2.2 presents portfolios of risk management, including the \r design principles and observed variations across the globe, before it \r discusses the need and potential for transformational adaptation to \r complement incremental adaptation, for which we present evidence \r across the report for selected adaptation options and some key risks. \r [...]"


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"[...] The Cross-Chapter Box LOSS in this Chapter synthesises recent literature \r and assesses key strands of the international policy dialogue on Loss \r and Damage, which discusses options that help to deal with impacts \r and residual risks in vulnerable countries."


id: 5f07251d824f629bcd942b8f64ba925b
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"Figure 17.1 |  Schematic representation of the climate risk management decision-making process as introduced in Chapter 1 (Figure 1.6) and the key \r elements of this chapter that address additional aspects of this process. In Chapter 17, climate risk management (middle box) is framed as the iterative response (i.e., \r what society could do and how it could be done) to the climate risks described in Chapter 16, with outcomes (ideally reduced risk) that can support (or perhaps hinder) climate \r resilient development, as assessed in Chapter 18. Decision makers from diverse contexts sit at the centre of the climate risk decision-making process and interact with and drive \r these processes as they play out. The main sections of Chapter 17 (bottom panel of boxes) address a wide range of issues (keywords in bottom panel) that manifest at one or more \r [...]"


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"[...] stages of climate risk management processes, illustrated by icons for section numbers and Cross-Chapter Boxes in the interactive risk management process."


id: c290d1bf5e3edcd7bfa2d863a1a13cc2
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"To coordinate between a suite of applicable risk management \r interventions, the concept of risk layering has been discussed and used in \r (financial) risk governance of disaster risk management (Mechler et al., \r 2006; Cummins and Mahul, 2009; Clarke and Mahul, 2011) and climate \r risk management (Lal et al., 2012; Mechler et al., 2014; Herron et al., \r 2015; Schafer et al., 2016; Mechler and Deubelli, 2021). Incremental \r risk prevention and preparedness as well as risk financing occurs \r within national systems. Over the years, regional cooperation, such as \r through the regional sovereign insurance pools in the Caribbean, the \r Pacific and Africa, but also transboundary risk management elsewhere \r have become more important (medium confidence) (see Martinez-Diaz \r et al., 2019). Also, with risks increasingly experienced as severe and \r existential (Boyd et al., 2017), global governance and solidarity have \r been invoked (see Linnerooth-Bayer et al., 2019; Pill, 2021), largely as \r [...]"


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"[...] part of the policy discourse on Loss and Damage (Mechler et al., 2019) \r with further momentum provided by discussions on the global goal of \r adaptation and recognition of climate risk as transboundary (Benzie \r and Persson, 2019; Cross-Chapter Box  INTERREG in Chapter 16). \r Transformational risk management has emerged where incremental \r and in situ adaptation is not effective in managing risks, such as for \r managed or strategic retreat for communities facing severe coastal \r and riverine flooding (Siders et al., 2019). Transformation has not been \r well documented, including as to its governance (Section 17.2.2.5)."


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"limited resources, and adaptation investments are more likely to \r include structural measures to reduce exposure, complemented by \r vulnerability-reducing measures and insurance protection (medium \r confidence). While this typology is not universally representative of \r high-income areas (within or between countries), expensive exposure\u0002reduction measures tend to be easier to implement in high-income \r countries. For example, flood protection is largest in countries with \r larger amounts of public spending and least amounts of corruption \r (Scussolini et al., 2016). It is seen as more economically efficient to \r invest in expensive protection measures in wealthy regions, under \r different scenarios of sea level rise and river flooding, although these \r calculations have equity and justice implications (Peduzzi, 2017; Lincke \r and Hinkel, 2018). After flood events happen in regions with high \r levels of protection, damages are comparatively limited, and people \r [...]"


id: 547bbea876f0fee1652d9e0595d05d01
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"[...] tend to continue living in close proximity to the protected river (Mard \r et al., 2018). In contrast, flood displacement is higher in low-income \r countries (Kakinuma et al., 2020)."


id: 8035857096dcfea1667245ce1d2fa86a
created_at: 2023-04-19 13:23:04
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content:
"Several studies and many government planning documents reference \r how people can benefit from a changed climate, beyond reducing \r risks. For example, several regions are expecting an increase in \r visitors to eco-tourism sites or national parks with a changing climate \r (Fisichelli, 2015; Lwasa, 2015). In Europe, several national adaptation \r plans include planning for potential benefits of a changing climate, \r including reduced winter mortality and improved conditions for \r hydropower (Biesbroek et  al., 2010). Recognising the need for \r economic diversification, people working in certain industries, such as \r coastal management, perceive climate change as a factor increasing \r the need for their services (Fatoric et al., 2017). Northern countries \r are taking advantage of ice-free waters for shipping routes in the \r Arctic (Eguiluz et al., 2016; Melia et al., 2016; IPCC, 2019c). In Africa, \r opportunistic adaptation has been observed by smallholder farmers, \r [...]"


id: db026ed5aa9d1c40071b74e3f249019d
created_at: 2023-04-19 13:23:04
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"[...] to plant crops that are better suited for a changing climate (Lalou \r et  al., 2019). Similar agricultural adaptation in Pakistan has been \r associated with improved food security and reduced poverty (Ali \r and Erenstein, 2017; Rahman et  al., 2020). In each of these cases \r documenting benefits, there are also potential negative impacts on \r other populations or ecosystems, such as ecosystem impacts from \r increased Arctic shipping (Ng et al., 2018)."


id: dc48db1babcc07e3922b9f9083ae7003
created_at: 2023-04-19 13:23:04
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content:
"Consequences of conflict that exacerbate vulnerability to climate change include: displacement, loss of access to employment leading to \r illegal livelihoods, gender-based violence, lack of land tenure, low literacy, poor access to social and health services, destruction, looting \r and theft of key assets, such as houses, food stocks and livestock, among others (Jaspars and Maxwell, 2009; Chandra et al., 2017; \r Anguita Olmedo and Gonzalez Gomez del Mino, 2019). Such impacts perpetuate cycles of poverty (World Bank, 2013), making conflict\u0002affected populations more susceptible to suffer from climate-related events (Basher, 2006; Coughlan de Perez et al., 2019). For example, \r in Mindanao, Philippines, poverty is closely linked to long-standing armed conflicts; both climate change and conflict have significantly \r increased smallholder vulnerability, resulting in loss of livelihoods, financial assets, agricultural yield and the worsening of debt problems \r [...]"


id: df396b7503952ae67496dcd3e08c318f
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content:
"[...] (Chandra et al., 2017). In Colombia, displacement induced by conflict has pushed the population to live in high-risk areas such as steep \r slopes susceptible to landslides and river banks exposed to flooding (Albuja and Adarve, 2011). This conflict-induced vulnerability, with \r little adaptation activity, has in turn resulted in climate-related disasters (Kuipers, 2019; Siddiqi et al., 2019)."


id: 9e9e26a3bb7e60cc5972acb13cb50ff6
created_at: 2023-04-19 13:23:04
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"To address risks to livelihoods, conflict-sensitive livelihood programming has used vouchers to meet immediate needs, legal support \r to resolve land disputes, and disaster preparedness planning to identify safe places for displacement (Jaspars and Maxwell, 2009). \r For example, cooperation in the Philippines between Moro Islamic Liberation Front and United Nations agencies included training of \r farmers in disaster risk reduction, drought management and production of improved crop varieties to support a transition away from \r subsistence farming (Walch, 2018). In Mali, negotiations on fertilizer access and safe transport to agricultural lands were brokered by the \r International Committee of the Red Cross, and in Afghanistan, conflict-sensitive approaches have promoted ecosystem-based adaptation \r to support reforestation (Walch, 2018; Mena and Hilhorst, 2020). Despite several examples of conflict-sensitive adaptation practices, \r [...]"


id: ce70280e11ee467cafb5e543fea38f72
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"[...] little is known about the effectiveness of such efforts in reducing climate risks in these complex contexts (see Section 17.5 for further \r discussion of 'effectiveness')."


id: d3ac1c38f460758ca775c53698570a21
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
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content:
"To distinguish incremental from transformational adaptation, Lonsdale \r et  al. (2015), building on Mustelin and Handmer (2013), identify \r criteria related to framing, learning and decision-making, space and \r time, power, and type of change management. Tabara et al. (2019), \r additionally discuss transformation in light of informing climate \r pathways, strategies and solutions. Broadly considering these criteria, \r they identify 12 dimensions with additional discussion of change \r with regard to systems and dynamics, options and solutions, agency, \r and the consideration of equity (see also Chapters 1, 6, 18 for more \r discussion). In particular, the following key aspects for understanding \r the spectrum from incremental to transformational adaptation are \r of relevance: change, within or across the system; agency, single or \r heterogenous; a role for visioning and normative futures; the type of \r learning required (from first order, business-as-usual, to second order); \r [...]"


id: ceba48617a8f9f5065bb39ad095f71d1
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"Figure 17.6 organises global and regional findings for observed and \r projected health risks from heat (RKR-E) from chapters across the \r report and organises options according to findings on the potential for \r transformational change as presented in Section 17.2 and Table 17.3. \r The discussion shows that heat has become a significant health risk \r globally, incurring severe mortality and morbidity in all world regions \r with annual heat-related deaths estimated around 300,000 with \r millions affected (high confidence) (Section 9.3.1). Evidence shows that \r adaptation and risk management can be effective in reducing (relative) \r risks in developed countries, with inconclusive evidence in low-middle\u0002income states (Sections 9.2.4.1, 13.7.3, 13.6). In absolute terms, risk in \r terms of heat-related mortality and morbidity is projected to increase \r under medium and high heating scenarios in many regions, even with \r implemented adaptation. By 2050 (compared with 1961-1991 and for \r [...]"


id: 2cd32607621d550a7ae8b8153406f3e8
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"[...] a mid-range emissions scenario), an excess of 94,000 deaths yr-1 is \r projected globally as attributable to climate change (Section 9.3.1)."


id: 1730f0aaf8a401a300fc597299afc90d
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"The pathway to a decision may not be linear, depending on when and in \r what detail the decision-making or consultative group may need to be \r understanding the climate risk and its real-world context (sense-making,\r modelling), has sufficient background to analyse and explore options for \r ameliorating the risk (analysis, exploration), or is ready for interpreting \r the analyses and deciding on the requirements and strategies for \r implementing a chosen strategy (interpretation-implementation) \r (high confidence) (Figure  17.7; French et  al., 2020). The development \r of decision-support tools for climate risk management (Palutikof et al., \r 2019a; Palutikof et al., 2019b) and more generally (Papathanasiou et al., \r 2016), along with archives of experiences from practitioners (Watkiss \r and Hunt, 2013; Section 17.5; Bowyer et al., 2014; French, 2020), means \r that some aspects of the decision-making process can be circumvented \r [...]"


id: ae53edf9163252e598cd6d582b827da5
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"IPCC's first assessment of L&D in 2018 found residual risks to rise with further global warming leading to soft and hard adaptation \r limits in some natural and human systems (e.g., coral reefs, human health, coastal livelihoods) (Roy et al., 2018). Sections 8.4.5.6, 16.4 \r and 17.2 corroborate these findings concluding that, depending on mitigation and adaptation pathways, residual risks in key systems \r in many regions will create potential for negative impacts beyond adaptation limits (medium confidence). The assessment in 2018 also \r noted that there is 'not one definition of L&D'. This ambiguity has persisted, and a policy space for L&D has not clearly been delimited \r (high confidence). There is, however, coalescence in dialogue among academia, civil society and policy around a distinct set of themes \r as identified by stakeholder surveys as well as literature, methods and evidence reviews (Vanhala and Hestbaek, 2016; Boyd et al., \r [...]"


id: 8c14ea1967a3a564a7a96998fb27e664
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content:
"[...] 2017; Mechler et al., 2018; Calliari, 2019; McNamara and Jackson, 2019): risk management, limits to adaptation, existential risk, finance \r and support, including liability, compensation and litigation (Sections 8.3, 16.4; medium confidence; Figure Cross-Chapter Box LOSS.1). \r Various advisory groups have been set up with participation of policy and experts from research, civil society and practice to help inform \r the implementation of WIM workplans (UN, 2015; UN, 2019)."


id: 2d7511044985e3a52cb0fe76ceee07a2
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"There is evidence that, without strong risk management and adaptation, losses and damages will continue to affect the poorest vulnerable \r populations, potentially creating poverty traps (high confidence) (Sections 8.3, 8.4.5.6 and Tables 8.7, 17.2; Serdeczny, 2019; Tschakert \r et al., 2019; Thomas et al., 2020). Research has started to develop global inventories on losses and damages, including on intangible \r effects (Tschakert et al., 2019; Otto et al., 2020), and engaged with the practice community for data collection. Practice has provided \r guidance to report on losses and damages in countries (I)NDCs (WWF & Practical Action, 2020). Yet, systematic risk assessments of \r climate-related losses and damages including adaptation limits (see, e.g., Leal Filho and Nalau, 2018; Robinson, 2018) have remained \r scarce (Section 16.4; high confidence). Thus, many vulnerable countries lack comprehensive data at scale of risk management including \r [...]"


id: 38eec8807e78c4e2d8006eb6383ccfee
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"[...] on economic (e.g., loss of livelihood assets and infrastructure) and non-economic losses and damages (e.g., culture, health, biodiversity), \r thus hampering effective risk management (Thomas and Benjamin, 2018; Martyr-Koller et al., 2021; Singh et al. 2021). Van den Homberg \r and McQuistan (2019) propose a losses and damages inventory also to be used to monitor how technologies may shape risks as well as \r adaptation limits. While early warning and other risk reduction options as well as risk retention considerations are being discussed, L&D \r dialogue has strongly focused on risk finance for residual risks, particularly through the donor-supported provision of public insurance \r systems (Linnerooth-Bayer et al., 2019; Schafer et al., 2019; Broberg and Romera, 2020; Nordlander et al., 2020)."


id: f255767ec15988804ef11d1163f22eb4
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content:
"The role of transformation in risk management for overcoming any soft limits to adaptation is seeing emerging attention (medium \r confidence, limited evidence), and the TEG CRM has also been tasked to consider transformation. Relocation and retreat of assets \r and communities, where in situ adaptation is considered impossible, is increasingly being debated in research and practice, including \r in terms of finance and L&D implications (Section 8.4.4; Boston et al., 2021; Desai et al., 2021; Mach and Siders, 2021; van der Geest \r and van den Berg, 2021; Zickgraf, 2021). Livelihood transformation occurs where current livelihoods become unfeasible in the face \r of multiple climatic and non-climatic stressors (Section 8.3.4.1) requiring change within sectors (such as switching from cropping to \r livestock rearing (Escarcha et al., 2020) or across sectors, when farming households relocate to offer labour elsewhere (Section 9.1; Rasel \r [...]"


id: 7a1ddf7d400f373cda9e5acacef57286
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content:
"[...] et al., 2013). Biermann and Boas (2017) suggest revamping global governance systems to effectively address the protection and voluntary \r resettlement of those displaced by climate variability and change. A WIM taskforce on displacement is tasked to further advise on human \r mobility, including migration, displacement and planned relocation (UNFCCC, 2019a)."


id: c3eb0579a57b2cc776adbb82a7e8973d
created_at: 2023-04-19 13:23:04
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content:
"Figure 17.7 |  Relationships between different processes of decision-making to manage climate-related risks in the real world, noting that, when appropriate, \r some aspects may only require experience to be re-used. (1) Formulation of risks of concern and accompanying policies and objectives for managing those risks, forming \r prescriptive models for the decision maker. (2) Knowledge, understanding and observations of the real world are used to assess past and current impacts and future risks using \r descriptive models, based on the perspectives and prescriptive models arising from (1). If not well formulated from other experience, processes in (1) and (2) interact to make sense \r of the world and what needs to be done. In iterative management, (1) and (2) also form the basis for monitoring, reviewing and evaluating effectiveness of adaptations. (3) Use \r [...]"


id: 765c7ad201f2b61e28e55bef170bf2da
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index: climate_gpt_v2
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content:
"[...] of decision-support and decision-analytic tools to appraise costs and benefits of different options for ameliorating future risks. The double-headed arrow indicates where two-way \r interactions occur between different activities (likely to be iterative, feedback and nonlinear processes); modelling and assessments are repeated and revised in tandem with the \r planning and evaluation of options, based on interactions with the policymakers and stakeholders. (4) The decision maker, which may be a group of people, interacts with the \r evaluation of options (two-way interaction) and interprets the efficacy of the options and the implications for the real world, ultimately choosing one or more actions to satisfy the \r policy objectives to manage the risks. (5) Implementation of the actions in the real world, which may be once-only actions or instigation of a feedback management system that \r enables ongoing adjustments to meet objectives."


id: d094a69e6f23bb8d92f633cdcc88546e
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content:
"to support analysing and making of decisions generally (French, \r 2020). These communities of decision analysts can act like broad\u0002based statisticians to advise on matching methods to the climate risk \r and its context, before individual decision specialists are consulted. \r Some scientific literature is presenting guides for choosing different \r methods, tools and approaches (Shi et al., 2019). This sub-subsection \r provides a summary guide for policy analysts and decision makers \r to help identify the classes of decision-analytic methods that may \r be suitable for their context for managing climate risks. It focuses \r on decision-analytic methods, noting that decision-support tools will \r underpin many of these methods by organising information (Bourne \r et  al., 2016; Papathanasiou et  al., 2016; Ceccato et  al., 2018; Hasse \r and Kind, 2018) or support modelling (Papathanasiou et  al., 2016; \r Kwakkel, 2017; Gardiner et  al., 2018), sometimes with a particular \r [...]"


id: 8ead603e41cbe2e6489d9b410210ce14
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content:
"[...] decision-analytic process in mind (Hadka et al., 2015; Torresan et al., \r 2016; Tonmoy et al., 2018)."


id: 21f438ff7b9fc34fbc17b4cebaecd283
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content:
"The cognitive phase of 'analysing and exploring' uses models and \r existing data and/or knowledge services as available to explore the \r relevance/efficacy of adaptations to ameliorate risk or to meet other \r adaptation objectives, as well as possible flow-on effects of those \r actions (Section  17.3.1.4). Sensitivity and robustness analyses can \r be useful if conditions are favourable to supplement the decision \r analysis, setting bounds on some of the residual uncertainty (high \r confidence) (Borgonovo and Plischke, 2016; Ferretti et  al., 2016). \r Validation of models and verification of data (Tittensor et al., 2018) are \r becoming highlighted as important steps in this phase or in the sense\u0002making phase, particularly in their capacity to understand and test \r decision makers and stakeholders' perceptions (medium confidence). \r Randomisation methods, Bayesian methods, interval methods, multi\u0002criteria decision analysis (MCDA), decision-making under deep \r [...]"


id: 5aebc09a88c625464272608753e38007
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content:
"[...] uncertainty (DMDU) and economic and financial approaches (e.g., Real \r Options Analysis) are tools of choice in this phase (high confidence) \r (Table  17.4) (Abbas and Howard, 2015; Bendoly and Clark, 2016; \r Borgonovo and Plischke, 2016; Iooss and Saltelli, 2017; Korhonen and \r Wallenius, 2020; Saltelli et  al., 2020). Decision-support tools in the \r provision of data and/or modelling methods are regularly used in this \r and the sense-making phase (high confidence) (Section 17.3.1.2)."


id: 33bfb4547bc0359540f2a4bdf4c34750
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content:
"Many sensitivity analyses based on scenarios, including procedures \r to randomise across model uncertainty, relate to descriptive dynamic \r mathematical models with the user of the models characterised as an \r objective observer (Borgonovo and Plischke, 2016; Ferretti et al., 2016; \r Symstad et al., 2017; French, 2020). Bayesian approaches enable these \r descriptive analyses to take account of the subjective choices in model \r construction and implementation (Abbas and Howard, 2015; Sperotto \r et  al., 2017; Jager et  al., 2018; Sperotto et  al., 2019; French, 2020). \r Organising descriptive analyses and deciding on a suitable option \r across a diversity of opinions among stakeholders use prescriptive \r processes, which can be supported with prescriptive modelling tools \r (Williamson and Goldstein, 2012; Gelman et  al., 2013; Abbas and \r Howard, 2015; Dias et al., 2018; Phan et al., 2019; Hanea et al., 2021). \r These approaches are subjective, in that they are constrained or \r [...]"


id: f666ccc5c734cb147b1a6112c6328478
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"[...] directed by the particular views and emphases of the decision-making \r group (Gorddard et al., 2016). Not all tools are appropriate for all these \r activities."


id: 24f3d50fd846e6d770f88e37de3344e7
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content:
"Decision makers will be better able to choose decision-analytic methods \r when they have an understanding of the types, scale and breadth of \r uncertainties around the climate risk (high confidence) (Symstad et al., \r 2017). The Cynefin framework (Snowden, 2002; French, 2013) is a \r policy-driven framework that broadly categorises the decision context \r of uncertainty within which decision makers and policy analysts may \r find themselves (medium confidence) (Hurlbert et al., 2019; Helmrich \r and Chester, 2020). As Cynefin has helped frame previous IPCC \r presentations on contexts of uncertainty (Hurlbert et al., 2019) and has \r a community of practice to consult on its use (French, 2020), it is used \r here, also because it considers the uncertainty in knowledge around \r cause and effect in general terms, rather than specifically focusing on \r uncertainty in formal models. Helmrich and Chester (2020) show how \r Cynefin can be used to frame climate adaptation decision-making in \r [...]"


id: 7864a8a144c4d162a8a4c39c4281b83d
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content:
"Uncertainty does not just relate to what might happen given climate \r drivers or adaptations, but also to how much one values potential \r consequences (Butler et al., 2016; Beven et al., 2018a; Cross-Chapter \r Boc DEEP; Beven et  al., 2018b; French, 2020) (high confidence);\r the balance between how particular decision analyses address \r uncertainties relating to the external world (descriptive models) and \r those relating to the values driving the decision-making (prescriptive \r models) is important (Butler et  al., 2016). Some analyses partially \r ignore uncertainties relating to the former in order to focus on conflicts \r in the values held by different stakeholders and help structure debate \r (Korhonen and Wallenius, 2020; French, 2020), while others build \r very sophisticated models of the external world to predict potential \r consequences, but in doing so lose transparency and risk becoming \r untrustworthy black boxes to many stakeholders (low confidence) \r [...]"


id: 4ebbff0598d4bf5eb56c6c47bdfdb9db
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content:
"Classes of tools (Watkiss and Hunt, 2013; French, 2020) include \r Bayesian methods, interval methods, decision-making under deep \r uncertainty (DMDU; see Cross-Chapter Box  DEEP in this Chapter), \r cost-benefit analyses, multi-criteria decision analysis, elicitation and \r general decision support tools (Table  17.4). A summary guide for \r policy analysts and decision makers is presented in Table 17.4 to help \r identify the classes of decision-analytic methods that may be suitable \r for their context for managing climate risks. The table summarises how \r well the methods address the Cynefin context, the phase of decision\u0002making, the types of uncertainties that exist through the decision\u0002making process and the resources required. As terminology may vary \r between disciplines and research groups, suitable references to better \r explain the methods within the class are provided. Also, there may be \r overlap between the classes as individual methods are often paired \r [...]"


id: f807ac3af230c9def42a7bcc46681548
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content:
"[...] with other methods to address specific requirements and approaches \r (Buurman and Babovic, 2016; Haasnoot et al., 2019). In that respect, \r these methods are referred to in the next section discussing advances \r in the different approaches to managing climate risks."


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"Much of the readily available literature on how uncertainties affect \r decision-making relates to the uncertainty in the biophysical models, \r with a recognition that the choice of tools will be influenced by \r the types of uncertainty to be addressed (Le Cozannet et  al., 2017; \r Symstad et al., 2017; Beven et al., 2018a; Beven et al., 2018b; Durbach \r and Stewart, 2020b; French, 2020). While terminology varies among \r disciplines, three types of uncertainty are important in understanding \r assessments of the future from descriptive models: epistemic \r (uncertainty in model construction relating to the lack of knowledge \r about the system being represented), analytic (the degree to which a \r model fits observations, and its accuracy) and stochastic (the natural \r variability or randomness in the system). The probability of an event \r arising in the future is determined from all three uncertainties, noting \r that stochastic uncertainty is a property of the system rather than a \r [...]"


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"[...] limitation of research (Le Cozannet et al., 2017; Beven et al., 2018a; \r Beven et al., 2018b)."


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"Uncertainty in what constitutes a risk of concern is increasingly identified \r as important to consider when managing risk (Chapter 16; Butler et al., \r 2016; Prober et al., 2017; French et al., 2020; Reis and Shortridge, 2020). \r The uncertainty here arises from what is an acceptable risk. Acceptability \r relates to the value or importance of the consequence, which may \r include moral and ethical uncertainties (Prober et  al., 2017), as well \r as how ambiguous the understanding of the consequence may be \r between different groups (Beven et al., 2018a; Beven et al., 2018b). The \r development of strategies to ameliorate risk will benefit from considering \r these two uncertainties in specifying the risk to be managed (Prober \r et al., 2017; French et al., 2020) because they can help set boundaries on a \r required likelihood of success, rather than simply casting stakeholders or \r decision makers as risk averse or risk tolerant, and can help identify and \r [...]"


id: 5c24a32b2b944c48f95c234be3c38b7d
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"[...] accept pathways of success (Gregory et al., 2012). This can be important \r when decisions need to be made well in advance of the actions needing \r to take effect, such as for many climate risks (Chapter 1; Chapter 16; \r Section 17.2.3; Cross-Chapter Box DEEP in this Chapter)."


id: ab7da04089ea262efed1233051743f0b
created_at: 2023-04-19 13:23:04
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"Stakeholder engagement has become increasingly part of climate\u0002relevant decision processes (Orlove et  al., 2020). The degree of \r stakeholder engagement ranges from instructive and consultative to \r cooperative, which are equivalent to information exchange, influence \r and partners in decision-making (Sen, 2000; Cattino and Reckien, \r in press). Since the AR5, climate change adaptation and resilience \r literature has seen an increase in participatory approaches that deepen \r engagement and overcome challenges, as well as making some \r assessments of their effectiveness (Newton Mann et al., 2017; Wamsler, \r 2017; Esteve et  al., 2018), including structured interactions among \r different types of stakeholders and the use of place-based boundary \r organisations to strengthen the interactions and heighten the awareness \r of the institutional context. A higher degree of public participation can \r lead to more transformational adaptation as well as to higher ambition \r [...]"


id: 6c9549931ac6e6fb1f329fa1457ab4ba
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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"[...] for local mitigation (medium confidence) (Section  17.4.4.2; Cattino \r and Reckien, in press). Challenges to stakeholder participation are \r access to state-of-the-art science, capacity to recognise and respond \r to non-reliable or false climate science information, and the removal \r of cognitive and other biases (high confidence) (Gorddard et al., 2016; \r Engler et al., 2019; Fulton, 2021)."


id: b28228c129d17f898ab270400037a194
created_at: 2023-04-19 13:23:04
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"Scenarios and pathways, combined with elicitation methods, are \r becoming widely used to assess adaptation and resilience strategies (high \r confidence) (Butler et al., 2016; Prober et al., 2017; Symstad et al., 2017; \r Lawrence et al., 2019; Phan et al., 2019; Sperotto et al., 2019; Haasnoot \r et al., 2020a). They can support the consideration of a wide range of \r alternative possible futures (Catenacci and Giupponi, 2013; Jager et al., \r 2018), enabling identification of potential path dependencies caused \r by adaptation options (high confidence) (Pretorius, 2017; Haasnoot \r et  al., 2020a). They can also increase the willingness of stakeholders \r to consider costly actions, by placing them within broader sequences \r of action (limited evidence) (Barnett et  al., 2014). The development, \r consideration and understanding of scenarios can be enhanced by using \r visualisation tools to better display storylines, enabling the discussion of \r [...]"


id: 27a5364e5c0e7019d6020528ecae3580
created_at: 2023-04-19 13:23:04
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"[...] alternative futures by participants in decision-making processes (limited \r evidence) (Winters et al., 2016)."


id: ccd856015007eb3a90f86cf55e0a1bbf
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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"Participatory and elicitation approaches, where the concerns and \r involvement of a broader range of interest groups and stakeholders are \r taken into account, can improve the effectiveness of decision-making \r (medium confidence) (Gregory et  al., 2012; Cvitanovic et  al., 2019). \r Participatory planning includes a variety of co-generative strategies \r and approaches (e.g., qualitative scenario or adaptation pathway \r development) through which goals and objectives, knowledge and \r strategy implementation and evaluation can be decided collaboratively \r between practitioners, policymaking, local interests and groups, \r and scientists (Butler et al., 2016; Prober et al., 2017; Symstad et al., \r 2017). Specifically, for climate change adaptation, these decision\u0002making strategies can incorporate expert, Indigenous and local \r knowledge (high confidence) (Cross-Chapter Box  INDIG; Gustafson \r et  al., 2016). The challenge will be to bring together these different \r [...]"


id: c9162e63f95b83b65998e6b7db06bba2
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"[...] actors, as stakeholders tend to act within rather than among systems \r and procedures, and it is important that platforms are developed to \r integrate data effectively (Rizzo et  al., 2020). Furthermore, reflexive \r and iterative risk management may further ensure acceptance by \r participating groups."


id: 62e5828ac14e608a6db782c0df3ff6b7
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
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"Since the AR5, robust decision-making methods are increasingly used \r to account for deep uncertainty in many climate-related risks (high \r confidence) (Marchau et al., 2019; Table 17.4), particularly when decisions \r need to be made well in advance of when the adaptations need to be \r implemented (Cross-Chapter Box.5 in SROCC Chapter 1; Cross-Chapter \r Box DEEP in this Chapter). Reducing risk and building resilience under \r the context of these types of wicked problems require asking 'what if' \r questions about the future, remaining flexible in the face of uncertainty \r and seeking out policies that provide good outcomes no matter what the \r future climate might bring (high confidence) (Section 17.6; e.g., Larson \r et al., 2015; Bhave et al., 2016; Bhave et al., 2018). In these cases, trade\u0002offs can be assessed and options can be prioritised through iterative \r decision-making processes, such as multi-criteria decision-making, \r [...]"


id: 45139244bdd676b56afff00fbb60c685
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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"[...] robust decision-making and dynamic adaptation pathway planning \r (high confidence) (Table 17.4; Kwakkel et al., 2014; Kwakkel et al., 2016; \r Shortridge et al., 2016; Lawrence and Haasnoot, 2017; Haasnoot et al., \r 2019; Lempert, 2019; Roelich and Giesekam, 2019; Haasnoot et  al., \r 2020a). They can address limitations of data-intensive robust decision\u0002making in developing countries (Daron, 2015), use proxy data to enable \r the use of robust decisions in data-scarce contexts (Shortridge and \r Guikema, 2016; Ahmad et al., 2019), incorporate multiple-objectives into \r robust decision-making (Singh et al., 2015), and supplement pathway \r development with real options analysis (Buurman and Babovic, 2016; \r Smet, 2017; Haasnoot et al., 2019; Lawrence et al., 2019). Often, there \r are close synergies between the application of these methods and using \r scenario analyses (Workman et al., 2021)."


id: c555ef06d198353253ec4bce5cb655a5
created_at: 2023-04-19 13:23:04
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"Since AR5, recognition of the importance of using integrated adaptation \r to improve climate risk management across the nexus between many \r sectors and across regions has increased (high confidence) (Harrison \r et al., 2016; Challinor et al., 2018). This was highlighted in the Special \r Report on Climate Change and Land (Hurlbert et al., 2019); advanced \r planning and integration of adaptation responses are needed over \r many levels (medium confidence) (Gopfert et al., 2019; Section 17.6; \r Woodruff and Regan, 2019). The complexity of managing this nexus \r may be compounded by the potential for antagonistic or synergistic \r effects among and between climate impacts, and changes arising from \r local sectoral activities and independent adaptation responses to those \r risks (high confidence) (Crain et al., 2008; Piggott et al., 2015; Adger \r et al., 2018; Brown et al., 2018; Stelzenmuller et al., 2018; Simpson \r et al., 2021), such as the cross-sectoral demands for freshwater (Xue \r [...]"


id: d8bae9b0992a3c3cd0498d7d4a840a2b
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"[...] et al., 2015; Azhoni et al., 2018). Integrated adaptation will also help \r facilitate management of new and emerging risks, help identify when \r response plans may need to be changed in light of the dynamics of risk \r over time, and help identify solutions that are less likely to constrain \r future options for adapting to future needs (Wise et al., 2016)."


id: 91d39fea404ad31dd8fc1c26aec465e3
created_at: 2023-04-19 13:23:04
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"To better communicate deep uncertainty, WGI AR6 complements projections of likely global mean sea level change, driven by processes \r in which there is at least medium confidence, with projections that incorporate ice-sheet processes in which there is low confidence\r (Section  9.6.3 in Fox-Kemper et  al., 2021). The latter are accompanied by storylines to highlight the physical processes that would \r generate extreme outcomes (Box 9.4 in Fox-Kemper et al., 2021). These low confidence projections and storylines are useful because the \r likelihood of high-end (>1.5 m) global mean sea level (GMSL) rise in the 21st century is difficult to determine but important to consider \r in coastal settings (e.g., Cross-Chapter Paper 2; Cross-Chapter Box SLR in Chapter 3). High-end GMSL rise by 2100 could be caused by \r earlier-than-projected disintegration of marine ice shelves, the abrupt, widespread onset of marine ice sheet instability and marine ice \r [...]"


id: 4303e368da0fe248fe1b44b86f89e847
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"[...] cliff instability around Antarctica, or faster-than-projected changes in the surface mass balance and dynamical ice loss from Greenland \r (Box TS.4 in Arias et al., 2021; Box 9.4 in Fox-Kemper et al., 2021). In a low-likelihood, high-impact storyline and a high CO2 emissions \r scenario, such processes could in combination contribute more than one additional metre of sea level rise by 2100 (Box TS.4 in Arias et al., \r 2021; Section 9.6.3 and Box 9.4 in Fox-Kemper et al., 2021). Other hazards assessed in WGI AR6 that address similar aspects relevant \r for decision-making under deep uncertainty include drought (Section 8.4.1.6 in Douville et al., 2021; Section 11.6.5 in Seneviratne et al., \r 2021), flood (Section 8.4.1.5 in Douville et al., 2021; Section 11.5.5 in Seneviratne et al., 2021) and wildfire weather (days) (Section 11.8.3 \r and Box 11.2 in Seneviratne et al., 2021), among others."


id: 95c18cb2e3f40fcd1457f970fd0ef519
created_at: 2023-04-19 13:23:04
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"There are diverse examples of the practical application of deep uncertainty methods across different climate change hazards in many \r regions of the world. For instance, low-regret options have been used to address the impacts and risks of landslides and debris flows \r in mountains (Section CCP5.2.6). Their frequency and magnitude are already widely experienced (Section CCP5.2.6) and projected to \r increase (Section CCP5.3.2.1). However, managing these associated risks also requires joint consideration of projected vulnerabilities \r and exposure of people and infrastructure, including the multiple and dynamic non-climate-related factors that are relevant for how the \r impacts manifest in context, such as population growth and land use planning (CCP5.2.6). Here, context-specific deliberative processes \r are used that include scenarios to guide and specify preventive measures with higher effectiveness than protective (infrastructure) \r [...]"


id: 24af6ac12a9ff609288f10e0061efe61
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"[...] measures could achieve alone. Low-regret adaptation involves raising awareness and accounting for long planning horizons to address \r the uncertainties associated with such risks, for instance in mountain regions, including education (Sections CCP5.4.1; CCP5.2.6), with \r co-benefits such as addressing changes in water availability for supply and demand (CCP5.4.1)."


id: 237da895d277d17f4b663fb44da25ee6
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"Adaptation pathways have been used to address SLR and changes in extreme rainfall through flood risk and management (Cross-Chapter \r Box SLR in Chapter 3; CCP2; Sections 13.2, 11.3 and 11.7): for example, adaptive plans in the Netherlands (Van Alphen, 2016; Bloemen \r et al., 2019), climate resilient development in Bangladesh (Hossain et al., 2018; Zevenbergen et al., 2018), adaptive spatial pathways for \r infrastructure retreat and for flood risk management in New Zealand (Lawrence et al., 2019a; Kool et al., 2020) and adaptive strategies such \r as in the cities of London (Ranger et al., 2013; Hall et al., 2019), New York (Rosenzweig and Solecki, 2014) and Los Angeles (Aerts et al., \r 2018a). This approach is mainstreamed into guidance documents such as the Climate Risk Informed Decision Analysis (CRIDA) (Mendoza \r et al., 2018), national guidance and policy briefs to address coastal hazards and sea level rise planning in New Zealand (Lawrence et al., \r [...]"


id: 37959b07657fc27b88f892889486b1c3
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"[...] 2018; Lawrence et al., 2019b), planning for sea level rise in California (OCP, 2018) and synthesis documents by the government of Canada \r on marine coasts (Lemmen et al., 2016). Furthermore, examples from the UK, New Zealand and the Netherlands point to the development \r of monitoring plans to detect signals for climate adaptation (Stephens et al., 2017; Haasnoot et al., 2018; Bloemen et al., 2019)."


id: 36cb1efafda984b0ad2757e9d8268e44
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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content:
"Climate-smart planning, with a focus on keeping options open, can play a role in reducing species extinction rates (Sections 2.5, 2.6). \r When and where and for whom particular irreversible impacts will occur is deeply uncertain, for example the extinction of a species. Even \r at the lowest emissions scenarios, some local species will become extinct, but estimates of extinction risk are highly uncertain, typically \r varying by factors of two to three even for one species (Section 2.5) (medium confidence). Risks of species' extinctions are lowered by \r reducing emissions, but keeping options open for as long as possible and avoiding irreversible actions are key to developing a climate\u0002resilient adaptive pathway so that real-time climate-driven changes can inform actions. Nature-based solutions (NBS) are emerging as \r key players for mitigation. With smart planning, NBS offer approaches that not only provide substantial mitigation, but also considerable \r [...]"


id: dc51aba0a24dc8e121721e0183afb95e
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"[...] adaptation benefit to biodiversity, and human health and well-being. Done poorly, such projects can result in large negative impacts on \r humans and nature. An NBS climate-sensitive decision framework leading to 'win-win' solutions for mitigation and adaptation is shown \r in Figure 1 Cross-Chapter Box NATURAL in Chapter 2 (see also Sections 2.4.2.5, 2.5, 2.6, 5.4.4.4 and 5.14.1; Cross-Chapter Box ILLNES in \r Chapter 2; Cross-Chapter Box COVID in Chapter 7)."


id: 6d1cc8c77a0aa7546c87d225c6d520e6
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"Implicit to managing cross-sectoral interactions, including the nexus \r concept, is that the interlinkages between multiple sectors are systemic, \r and therefore solutions to challenges arising from any one sector can \r only be satisfactorily addressed by considering the connections to other \r sectors at the same time (Wichelns, 2017). Challenges for integrated \r adaptation include: (1) to sufficiently capture the complexities between \r the nexus dimensions (Weitz et al., 2017); (2) to adequately consider the \r time, costs and challenges of coordination and cooperation (Wichelns, \r 2017); (3) to consider the political economy in which progress towards \r more integrated solutions could take place, not only accounting for \r technological requirements (Leck and Roberts, 2015); (4) to obtain \r sufficient temporal or spatial data to capture the interactions between \r natural and social processes (Shannak et  al., 2018); (5) to connect \r [...]"


id: b3920276b183405149dcb873b3078d36
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"[...] these considerations to decision-making and policy processes in order \r to gain insights into the conditions for collaboration and coordination \r across sectors, including external dynamics and political and cognitive \r factors determining change (Weitz et al., 2017); and (6) to develop a \r coherent framework against which to assess results and observations \r (Crain et al., 2008; Wichelns, 2017)."


id: 9a6978fa982922ba790c2d01f0278ac9
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"Even though there is no agreed definition of or typology for climate \r change laws (Mehling, 2015), studies have tended to classify climate \r change laws as being 'framework' or 'sectoral' (see Table  17.5 for \r examples). Framework laws offer a comprehensive, unifying basis \r for climate change policy, addressing multiple aspects or areas of \r climate change mitigation or adaptation (or both) in a holistic and \r overarching manner (Townshend et al., 2011; Fankhauser et al., 2014; \r Nachmany et al., 2015; Clare et al., 2017b); they are powerful levers \r for setting national and sub-national agendas, creating climate change \r institutional structures, enabling policy implementation and driving \r the passage of additional sectoral legislation and regulations (Clare \r et al., 2017b). Prior to 2010, national framework laws tended to have a \r mitigation focus, while more recent laws or amendments thereto have \r an increased adaptation focus (Rumble, 2019b). No evidence indicates \r [...]"


id: 9b03a70f4f413d2e574626290cbd0d70
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"[...] whether general or specific framework laws yield better outcomes; \r however, reviews of more recent examples of framework laws in Africa \r suggest a trend towards more specificity in the required content of \r adaptation strategies and duties (Rumble, 2019b)."


id: 69909216ac61e424a0f7bd87aba690a7
created_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
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content:
"Legal systems play an important governance role in facilitating \r responses to climate change across all levels of society (high \r confidence) (Ruhl, 2010; McDonald and Styles, 2014; Mehling, 2015). \r Laws can facilitate climate action in multiple ways, including through: \r (i) mandating and guiding the behaviour of governance structures \r and actors, (ii) fostering coordination between different levels of \r government, (iii) enforcing climate responses, (iv) its symbolic value \r and (iv) aligning scientific evidence and societal norms (Mehling, 2015; \r Scotford et al., 2017). Laws also can embed climate change planning \r within the administrative structure of a state, rendering policy less \r vulnerable to revocation (Scotford et  al., 2017). Extensive revision \r to laws has occurred in the last decade: a survey of 164  countries \r showed that over 1200 climate-related national laws and policies have \r been published, with approximately 44% being acts of parliament \r [...]"


id: 318fa59d7fffc98da478df57d4c9aed5
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"A sectoral approach to climate change legislation grafts climate-related \r provisions into existing laws, such as environmental impact assessment, \r flood insurance and infrastructure planning, collectively creating an \r aggregated legal landscape (Townshend et  al., 2011; Gerrard and \r Fischer, 2012; Nachmany et  al., 2015; Scotford et  al., 2017; Rumble, \r 2019a). This approach is particularly relevant to adaptation challenges \r which intersect with numerous bodies of law that are dedicated to other \r societal concerns (Gerrard and Fischer, 2012). However, integrating such \r considerations can be challenging in certain areas of law, particularly \r those relating to property rights, water rights and endangered species \r protection (Gerrard and Fischer, 2012). The incorporation of adaptive \r management principles (including monitoring, periodic evaluation, and \r response modification) within existing laws can enhance their enabling \r [...]"


id: ba3f3f6064c88be42e8bb591ec0188ee
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"[...] role and foster greater resilience (Godden, 2012; Arnold and Gunderson, \r 2013; McDonald and Styles, 2014)."


id: 61d83ea55aa8b2d5b7faaa2e5afd1c8f
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updated_at: 2023-04-19 13:23:04
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content:
"Substantial developments in adaptation policy have occurred since \r AR5 (high confidence). Perhaps the most significant is the NDCs \r required under the Paris Agreement, where 184 out of 197 parties \r to the UNFCCC have already submitted their first plans (UNDP and \r UNFCCC, 2019). The NDCs have allowed countries to articulate their \r priorities and ambition with respect to climate action, and it has \r been suggested that these can in turn lead to cascading policies (and \r laws) that drive and enable adaptation and climate risk management. \r Analysis of the first NDCs submitted in the lead-up to and after the \r Paris Agreement showed that adaptation priorities were more often \r articulated by developing countries and least developed countries, \r while developed countries and emerging economies focused mostly on \r mitigation (Pauw et al., 2019). As of 2019, over 90 developing nations \r are at various stages of preparing National Adaptation Plans and 112 \r [...]"


id: a62a5db30e245f11bd2c1061e30fc1da
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updated_at: 2023-04-19 13:23:04
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content:
"[...] nations have indicated their intention to revise their NDCs for the 2020 \r update (UNDP and UNFCCC, 2019)."


id: 6359368e03d2ae3bddf91a24abc450c2
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updated_at: 2023-04-19 13:23:04
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content:
"as shown for the local level (Reckien et al., 2019). However, the UK Act \r is considered to have made action on climate change more predictable, \r more structured and more evidence based (Averchenkova et al., 2021).\r There are numerous examples of regulatory and project-based \r innovations by local governments. Their impact, however, is uneven, with \r much depending on the implementation capacity of local governments \r and other socio-institutional barriers, including those relating to mandate \r and joint project implementation, cross-departmental working, planning \r cycles, concerns relating to legal liability and compensation, political \r appetite and cost (Godden, 2012; Taylor, 2016a). Notwithstanding \r implementation challenges, evidence is emerging that overarching \r framework laws play a foundational and distinctive role in supporting \r effective climate governance, including adaptation governance \r (Fankhauser et  al., 2018), and are drivers of subsequent activity \r [...]"


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content:
"[...] (Townshend et al., 2011; Fankhauser et al., 2014; Clare et al., 2017b), \r especially when formulated with clear guidance for all related actors, \r including lower level of governance (De Gregorio Hurtado et al., 2015). \r This may explain the rapid increase in both local and national climate \r change laws, now with an increased emphasis on regulatory provisions \r 17.4.2.1.4 Regulations and standards\r The presence and articulation of regulations and standards that \r address climate risk, such as building codes and land use zoning \r are key enabling factors for effective decision-making (Kim et  al., \r 2020). Regulations and standards provide a framework for common \r understanding of when and under what conditions action should be \r taken specifically in relation to the construction and maintenance of \r the built environment, infrastructure and environmental and social \r practice (Grynning et al., 2020). Regulations and standards for climate \r [...]"


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"[...] action emerge primarily from two settings: first, as an addition or \r augmentation to existing regulations and standards that emerged \r initially to address existing potential climate extremes and stresses \r (e.g., size of culverts in response to maximum rainfall and runoff \r conditions); and second, new regulations and standards that were \r developed in direct response to new or emergent climate risks (e.g., \r regulations in response to new presence of mean monthly high tide \r flooding) (Qiao et al., 2018). Commonly agreed upon social norms and \r conventions also can be described as regulatory and providing a set \r of standards."


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"There are numerous examples of regulatory and project-based \r innovations by local governments. Their impact, however, is uneven, with \r much depending on the implementation capacity of local governments \r and other socio-institutional barriers, including those relating to mandate \r and joint project implementation, cross-departmental working, planning \r cycles, concerns relating to legal liability and compensation, political \r appetite and cost (Godden, 2012; Taylor, 2016a). Notwithstanding \r implementation challenges, evidence is emerging that overarching \r framework laws play a foundational and distinctive role in supporting \r effective climate governance, including adaptation governance \r (Fankhauser et  al., 2018), and are drivers of subsequent activity \r (Townshend et al., 2011; Fankhauser et al., 2014; Clare et al., 2017b), \r especially when formulated with clear guidance for all related actors, \r including lower level of governance (De Gregorio Hurtado et al., 2015). \r [...]"


id: 38d9c428f4e79020087579d109b19e29
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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"[...] This may explain the rapid increase in both local and national climate \r change laws, now with an increased emphasis on regulatory provisions \r to increase resilience and reduce vulnerability."


id: d094806af33366fb2d237648c01f6d59
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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content:
"The regional and sectoral chapters of this report provide significant \r evidence of how regulations and standards enhance or hinder \r opportunities for climate risk management and adaptation. Relevant \r regulations and standards are especially evident in the oceans and \r coastal domains (Chapter 3 and CCP2, in cities and infrastructure \r (Chapter 6), and the water (Chapter 4) and food sectors (Chapter 5). \r Europe and North and South America (Chapters 12, 13 and 14) have \r the most frequent documented occurrences of examples of regulations \r and standards. Regulations and standards focused on building codes \r to protect against extreme event and loss, water regulations and \r agreements to protect water supply and lessen drought impacts, and \r health codes to limit heat exposure are the most frequent examples \r of such practices. Deficiencies of regulations and standards have been \r noted with respect to their capacity to manage species migrating \r [...]"


id: 45ce1403f54dc63f70fb2bb1bf8d7f0a
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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content:
"[...] from climate change, and to provide opportunities for transformative \r adaptation. The evidence from the sectors and chapters illustrate \r that more comprehensive regulations and standards lead to positive \r adaptation outcomes."


id: 43795485ba3c577fd9b542b0017fe504
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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content:
"The effectiveness of social and environmental governance varies \r by sector. For example, in the private business sector, Aragon-Correa \r et al. (2019) assess the effects of mandatory and voluntary regulatory \r pressure on firms' environmental strategies.  In summary, they find \r that analyses of the effects of voluntary pressure demonstrate that by \r themselves they are unlikely to bring about significant improvement \r in environmental outcomes. Professional organisations, however, \r have made progress in addressing sectoral standards relative to the \r adaptation process. This includes the development of new industry \r guidelines, codes, standards and specifications, in addition to the \r implementation of infrastructure inventories that incorporate evaluation \r of vulnerabilities and identification of priority at-risk areas (Chapter 14). \r Voluntary pressures by themselves are not likely to result in positive \r outcomes and instead should be coupled with mandatory regulatory \r [...]"


id: d3aab4e344bdacd65a653a0c546ea90b
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
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content:
"Since AR5, another key development in environmental and social \r governance has been the establishment of the Task Force on Climate\u0002related Financial Disclosures (TCFD), which aimed to develop guidelines \r for companies to voluntarily report the financial implications of two \r broad categories of climate risk: the transition risks of shifting to a \r lower-carbon economy and the physical risks of climate change \r itself (TCFD, 2017). As of 2019,  ~1340 companies with a market \r capitalisation of USD 12.6 trillion and financial institutions responsible \r for assets of USD 150 trillion have expressed support for the TCFD \r (TCFD, 2020). An analysis of reports to the TCFD in 2016 showed that \r 83% of companies report on physical risks of climate change, and of \r these, 82% reported on strategies to adapt to some of the identified \r risks (Goldstein et al., 2019). The same analysis also noted that: (i) the \r total of estimates of assets at risk were two orders of magnitude lower \r [...]"


id: 2ede4487bf5c04fdf7291c83ed0beba6
created_at: 2023-04-19 13:23:04
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content:
"[...] than generally accepted estimates of total financial risk; (ii) a minority \r of companies consider risks outside of their own operations or in their \r value chains; (iii) most underestimate or do not estimate the costs \r of adaptation; and (iv) many assume linear impacts and responses, \r neglecting the potential for tipping points or acceleration in risk and \r potentially transformative adaptation requirements.  At this stage, \r TCFD has influenced many companies' thinking and comprehension \r of physical climate risk, but it appears too early to assess whether this \r has driven substantive responses to manage these risks."


id: 24a999dc11b826c383692dacb99145b4
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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content:
"Examples of the importance of these other two components--\r knowledge of response options and knowledge of enabling \r conditions--are provided by  networks of cities, including internal \r institutional networks (Aylett, 2015), intermunicipal networks (e.g., \r those supported by Local Governments for Sustainability [ICLEI] \r and the international United Cities and Local Governments [UCLG] \r network), transnational municipal networks (e.g., 100 Resilient Cities, \r Asian Cities Climate Change Resilience Network [ACCCRN]) and city\u0002to-city regional transdisciplinary learning networks (Ndebele-Murisa \r et al., 2020). These networks generate and exchange knowledge which \r can be critical to decision makers for understanding and evaluating the \r feasibility of different response options, identifying synergies across \r sectors and mainstreaming adaptation to climate change (Haupt et al., \r 2020). However, the question of how to finance such network activities \r [...]"


id: 37aa2e41bbdceaed167b9edb0ac7240
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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content:
"Successive reports of the IPCC (Vellinga et al., 2001; Mimura et al., 2008; Yohe et al., 2008; Klein et al., 2014) and the AR6 Special Reports \r have noted the importance of finance as an enabler for adaptation, across both developed and developing nations. While the UNFCCC \r and the UNFCCC has yet to arrive at a formally agreed definition of climate finance, numerous overlapping have been suggested and \r reported (e.g., Falconer and Stadelmann, 2014; UNFCCC, 2014; Roberts and Weikmans, 2017; Munira et al., 2021). However, there is \r wide agreement across these definitions that climate finance refers to financial resources devoted to addressing climate change, both \r mitigation and adaptation to current and projected climate change, and that these resources can come from both public and private \r sources (high confidence). Climate finance includes, but in most definitions is not restricted to, international financial flows to developing \r [...]"


id: 8e49bde71f0183f0ab0b9ccbe3cd7711
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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content:
"[...] countries. Finance can be delivered through a range of instruments including grants, concessional and non-concessional debt, and \r internal budget reallocations (high confidence) (Watson and Schalatek, 2019). Adaptation and resilience are often used interchangeably \r in climate finance discussions, although adaptation is a process, while resilience (to climate risk) is the ability to progress towards desired \r outcomes in the face of impacts from a changing climate (Section 1.2.1)."


id: e38b19b2e376cc44619e2f3389b6da98
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 37326
content:
"The adaptation and resilience finance landscape spans multiple sources, intermediaries, instruments and recipients, operating across \r global to sub-national scales (Buchner et al., 2019; Carter, 2020; Watson and Schalatek, 2021). Public finance is provided by national \r and sub-national governments and distributed directly by government or intermediaries such as development finance institutions \r and climate funds, either nationally or internationally. Private finance comes from five main sources: commercial financial institutions \r (banks), institutional investors (including asset managers, insurance companies and pension funds), other private equity (venture capital \r and infrastructure funds), non-financial corporations such as renewable energy or water companies, and individual households and \r communities. Across these different sources, the main instruments used are grants, concessional debt, market debt, internal budget \r [...]"


id: 59a35f5306bd073929cffefda380989c
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 13010
content:
"[...] allocation, insurance, as well as personal savings in households (high confidence). Public and private sources of funding can be blended \r into a single instrument, for example for insurance where public funds provide capital for both sovereign catastrophe instruments and \r micro-insurance (Jarzabkowski et al., 2019) or for concessional loans. Similarly, public finance is often ultimately derived from commercial \r debt instruments such as bonds."


id: 298ed0218af742b6986ea9c3a1d25f25
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 4534
content:
"The Climate Policy Initiative (CPI) has been tracking climate finance since 2009, allowing for trends to be assessed; however, trends \r reported are a function of both real changes in finance and changes in methods and information sources (Richmond et al., 2020). Total \r climate finance tracked by CPI has increased from USD 364 billion yr-1 in 2010/2011 to 579 billion in 2017/2018 (SM17.3). Tracked finance \r remained relatively constant from 2010/2011 to 2013/2014 but has increased steeply in more recent years. The proportion of finance \r allocated to adaptation has remained small throughout, between 4% and 8% (high confidence); a further 1-2% of global finance has \r been classified as 'multiple-objectives'. The large majority of tracked adaptation finance is from public sources (high confidence), with \r only 2% coming from private sources in 2017/2018 (CPI, 2020). This is at least partly because of the difficulty in demonstrating financial \r [...]"


id: fd927fd53a9e91cbc4be535ebf638e51
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 41963
content:
"There is growing agreement on the sectors (such as infrastructure, agriculture or water management) and approaches (contingency \r finance or insurance) where private sector adaptation investments alone, or leveraged by public mechanisms, might be best targeted, \r such as by reducing the risk of providing financial services for adaptation investments to domestic micro-, small and medium enterprises \r or agricultural smallholders, many of them women (Biagini and Miller, 2013; Chambwera et  al., 2014; Pauw et  al., 2016; Global \r Commission on Adaptation, 2019; Miller et al., 2019; Resurreccion et al., 2019; Richmond et al., 2020). A remaining open question is how \r to allocate limited public adaptation funds in a way that is equitable, effective and efficient between mobilising private investments and \r safeguarding adequate financial support for necessary adaptation efforts, such as the provision of public goods, which the private sector \r [...]"


id: a70c343526a5ae0567a21267cacaa9c9
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 26599
content:
"[...] will not invest in (Fankhauser and Burton, 2011; Abadie et al., 2013; Baatz, 2018; Omari-Motsumi et al., 2019)."


id: 7b99483fa1f948061fd3391e81130e24
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 18954
content:
"Concerns have also been raised about the interactions between debt service, COVID economic recession and post-COVID recovery in \r developing countries (Simmons et al., 2021; Volz et al., 2021). Debt service grows as a proportion of national budget during recession, \r reducing scope for investment in recovery, is a self-reinforcing cycle. It has been suggested that linking debt relief to Paris-aligned \r objectives can act as an additional source of climate finance (Fenton et al., 2014). The G20 has begun addressing this debt crisis through \r its Debt Service Suspension Initiative and the Common Framework for Debt Treatments (IMF, 2020). It has been suggested that these \r initiatives could be expanded to prioritise climate-focused debt-relief instruments and to include more countries (Steele and Patel, 2020; \r Volz et al., 2021). If debt relief is used to invest in national instrument for green and inclusive recovery, national ownership of the use of \r [...]"


id: b919593f2b23cb2713a8dddcfe605688
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
vector_id: 29768
content:
"[...] the finance can occur, avoiding some of the negative connotations of historical debt restructuring (Volz et al., 2021)."


id: 41b801c9530bb60efe100deddd8c2106
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 8758
content:
"Indigenous knowledge and local knowledge are gaining recognition \r at multiple scales (Kleiche-Dray and Waast, 2016; David-Chavez and \r Gavin, 2018; Nakashima et  al., 2018). Of note is their association \r with ecosystem-based adaptations, showcasing the long-term \r place-based knowledge of Indigenous Peoples (Johnson et al., 2015; \r Walshe and Argumedo, 2016; Carter, 2019; Mazzocchi, 2020). These \r knowledges and practices can be an important enabling condition in \r decision-making processes, complementing scientific information  by \r identifying impacts (Fernandez-Llamazares et  al., 2017; Katz et  al., \r 2020), emphasising values to consider (Huambachano, 2018), offering \r solutions (Chanza and de Wit, 2016; Cuaton and Su, 2020; Orlove \r et al., 2020), guiding land use and resource management (Brondizio \r et al., 2021) and filling gaps in scientific knowledge (Hiwasaki et al., \r 2014; Audefroy and Sanchez, 2017; Makondo and Thomas, 2018; Son \r [...]"


id: 5f8eb0265e2f83e8e92226515436a9cd
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 14118
content:
"The co-production of knowledge by different actors provides important \r avenues for exchanging and integrating climate-related knowledge \r in decisions made across society (high confidence). Though many \r definitions of co-production have been offered in recent years (Bremer \r and Meisch, 2017; Vincent et  al., 2018; Bremer et  al., 2019; Harvey \r et  al., 2019a), most describe a set of individuals or organisations \r who work together to generate a set of products that entail new \r knowledge products and that guide action (Miller and Wyborn, 2020). \r Some major forms of co-production include action research (Baztan \r et  al., 2017; Laursen et  al., 2018; Zanocco et  al., 2018a), trans\u0002disciplinarity (Howarth and Monasterolo, 2016; Wamsler, 2017; Lanier \r et al., 2018; Scott et al., 2018; Knapp et al., 2019; Young et al., 2019), \r rapid assessment processes (Atkinson et al., 2018b) and participatory \r integrated assessments (Howarth et  al., 2018; Krkoska Lorencova \r [...]"


id: 1309a4848971621d3b706e27db1af39
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
vector_id: 560
content:
"[...] et  al., 2018; Bitsura-Meszaros et  al., 2019; Carter et  al., 2019a; \r Cremades et  al., 2019; Leitch et  al., 2019; Martinez-Taguena et  al., \r 2020; Section 17.3.1.3.1)."


id: bebe90773498ce76234167430daab88
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 30824
content:
"Co-production promotes iterative dialogue, experimentation, \r the tailoring of knowledge to context, needs and priorities, and \r learning, often promoting integration of Indigenous knowledge, local \r knowledge and practitioner knowledge with scientific knowledge \r (high confidence). It generally entails long-lasting ties and fully \r inclusive partnerships between different parties (Kench et al., 2018). \r Governance measures and adequate financing can act as enablers of \r such co-production. This integration is most extensive, and promotes \r a wider consideration of alternatives where governance arrangements \r promote ongoing exchanges of information and discussion of solutions, \r whether through formal mechanisms such as regional committees \r (Gim et  al., 2019; Ostovar, 2019; Rasmus et  al., 2020; Zarei et  al., \r 2020) or informal mechanisms such as personal networks and local \r discussion groups (Madsen et  al., 2019; Yumagulova and Vertinsky, \r [...]"


id: 1274baeee48f7a9cb9c8645a705bdc13
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 448
content:
"[...] 2019). Where such arrangements are absent, practitioner knowledge \r is side-lined from the formulation and implementation of decisions \r (Orleans Reed et al., 2013; Aguilar-Barajas et al., 2019; Matsler, 2019; \r Ramsey et al., 2019)."


id: 21d5f5f62fbcdbc04915424fafc3bf81
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 3171
content:
"can be termed 'climate service governance' (Stegmaier et al., 2020). \r Elements of this governance include the arrangements by which those \r parties engage with each other (Vaughan et al., 2016; Daniels et al., \r 2020) and the financial arrangements, and associated responsibilities, \r which support the service (Lourenco et  al., 2015; Bruno Soares and \r Buontempo, 2019). Though governance varies by context, evidence \r suggests that engaging a range of experts and potential users in the \r co-design and co-production of climate services increases the use and \r utility of services (Lemos et al., 2014; Pope et al., 2017; Masuda et al., \r 2018; Harvey et al., 2019b). However, some studies warn that, even \r with broad and inclusive participation, power differentials can create \r barriers to co-production, reducing the usefulness of information \r products (Alexander et al., 2020) and the neglect of non-meteorological \r sources of information which may also possess useful predictive power \r [...]"


id: e743777bf18ae308b49cc9e1de1c610e
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 37981
content:
"Cross-Chapter Box 12.2 in WGI AR6, 'Climate information for climate \r services', shows that users are widely distributed across civil society. \r Relevant users of climate services include humanitarian organisations \r (Coughlan de Perez and Mason, 2014; Harvey et  al., 2019b), \r government offices (Mahon et  al., 2019), international agencies \r (Perkins and Nachmany, 2019) and the private sector (Beckett, 2016; \r Hudson et al., 2019). Climate services currently exist at local, national, \r regional and international scales, at time scales which range from sub\u0002seasonal to decadal and longer (White et al., 2017; Hewitt et al., 2020) \r and in a range of different sectors (Bruno Soares and Buontempo, \r 2019). Agriculture is the sector with the largest number of examples \r (Zebiak et  al., 2015; Burke and Emerick, 2016; Cliffe et  al., 2016; \r Haigh et  al., 2018; Buontempo et  al., 2020); others include  health \r (Ghebreyesus et al., 2010; Ballester et al., 2016), forestry (Caurla and \r [...]"


id: 6f589d21d923c4520f26de0b7979d81c
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
vector_id: 16849
content:
"[...] Lobianco, 2020), fisheries (Busch et al., 2016), disaster risk reduction \r (Street et al., 2019) and water resources management (van Vliet et al., \r 2015; Golding et al., 2019). Evaluations of the extent to which climate \r services are accessed, used and deliver benefits to decision makers \r remain in an initial stage (Perrels, 2020), though studies suggest \r that these contributions vary widely depending on context. A review \r of evaluation of weather and climate agricultural services in Africa, \r for instance, found that most farmers use climate services when they \r are available , but that on-farm outcomes varied, with some farmers \r experiencing yield losses and others gains upward of 60% (Vaughan \r et al., 2019a). Other studies express concern that large climate service \r projects have run for decades at significant expense, without adequate \r evaluation (Gerlak et al., 2020)."


id: a749054cfa4fa7ef247fcfa5ff2188e4
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 26648
content:
"A small but growing number of papers consider the business models \r that support climate services, including, for instance, the role of \r open data (Iturbide et al., 2019; Chimani et al., 2020), the standards \r or institutional mandates by which users come to understand the \r credibility and legitimacy of certain services (Bruno Soares and \r Buontempo, 2019), and the role of public-private partnerships \r (Cortekar et al., 2020). While the commercialisation of climate services \r holds significant promise that more and more specifically targeted \r services will be provided, there is not yet agreement on which business \r models best support this in different contexts. There is also concern \r that commercialisation of climate services may disadvantage under\u0002resourced actors at the expense of wealthier or more powerful ones \r (Webber, 2017; Webber and Donner, 2017; Cortekar et  al., 2020). It \r has been noted that some climate services, such as weather forecasts \r [...]"


id: f764835d98812b518ae539d56116afe3
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 40900
content:
"[...] and early warnings, are an example of a public good, best provided by \r public agencies (high confidence) (Sutter, 2013; Kitchell, 2016; Hansen \r et al., 2018)."


id: a7ebf1b526ac364a6f4ff79d1cabdc93
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 26754
content:
"Knowledge of climate change influences decision-making not only by \r providing information but also by increasing the motivation to act and \r by promoting behaviour change. Evidence from many sectors (including \r water (Section 4.5.2), ocean and coastal ecosystems (Section 3.6.2), and \r agriculture (Section 5.4.2) and regions (including Africa [Section 9.8.4], \r Asia [Section 10.4.6] and North America [Section 10.4.5] shows that \r building capacity (e.g., adaptive capacity, institutional capacity, \r education/training in human capacity) can support adaptation and \r limited governance capacity can constrain it (high confidence). An \r emerging area of research examines the contribution of building \r capacity within public and technical organisations and agencies to draw \r on Indigenous knowledge and local knowledge (Adger et  al., 2017; \r Hochman et al., 2017; Bacud, 2018). A number of factors influence the \r effect of knowledge on motivation and behaviour change, including \r [...]"


id: f27662533423afb1afe9dea90a4a4427
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 40048
content:
"A clear difference between enabling conditions and catalysing \r conditions is emerging in the climate mitigation literature (Hermwille \r et  al., 2019; Michaelowa et  al., 2021), with some examples in the \r adaptation literature as well (Madsen et  al., 2019; Booysen et  al., \r 2019a; Bolorinos et  al., 2020). Though enabling conditions are \r necessary pre-conditions that allow response options to be formulated \r and implemented, their presence alone does not guarantee that \r these response options will occur in a timely fashion or at a scale \r commensurate with the risk, or even that they will occur at all. \r Catalysing conditions address this deficit in advancing action. They \r serve to overcome the inertia that often operates as a barrier to action \r and motivate individuals and organisations to initiate or accelerate \r action. Different forms of catalysing conditions, described below, lead \r individuals and organisations to weigh more seriously the costs of \r [...]"


id: 561c7251cc82fbd9526da605dbddb9c3
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 12423
content:
"[...] delaying action or keeping action at low levels. Catalysing conditions \r focus the attention of individuals and organisations on particular risks, \r leading actors to augment their decision-making processes and to \r allocate financial and social resources to respond to those risks. This \r attention and deliberation can lead to more frequent and potentially \r substantial adaptations, whether through more extensive action on \r existing forms of adaptation or through the adoption of entirely new \r adaptations (Bolorinos et al., 2020)."


id: 1815311259b9b5e14fcac08f878290a3
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 1447
content:
"The perception of climate change as a major threat that requires action \r has increased since AR5, reflecting both the growth of information \r about climate change and the processing of that information (Lee \r et al., 2015; Fagan and Huang, 2019). Global social movements play \r an important role in raising public awareness of climate urgency \r (Thackeray et al., 2020). Climate change concern plays an important \r role in decision-making outcomes which entail public participation \r (Lammel, 2015; Chiang, 2018; van Valkengoed and Steg, 2019; Arikan \r and Gunay, 2020). Nonetheless, public risk perception varies sharply \r on spatial and temporal scales, reflecting environmental changes, \r social influences (Kousser and Tranter, 2018; Rousseau and Deschacht, \r 2020), economic capacities (Arikan and Gunay, 2020) and culture (Noll \r et al., 2020), as well as individual characteristics (van Valkengoed and \r Steg, 2019). The importance of values and norms is demonstrated by \r [...]"


id: 1ab071931d07154d938c018881cd8dfd
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 1899
content:
"[...] recent research which highlights how intrinsic motivation (altruistic, \r self-transcendental and eco-centric values) (Corner et al., 2014; Braito \r et  al., 2017; Xiang et  al., 2019; Bouman et  al., 2020) and extrinsic \r social motivation (e.g., economic gains and social desirability) (van \r Valkengoed and Steg, 2019) can drive action."


id: ab07c387122bc591ebf542c983b1ac45
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updated_at: 2023-04-19 13:23:04
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vector_id: 27313
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"Recent research shows the importance of education as a predictor of \r risk perception, motivation and action. Education level is the strongest \r predictor of public awareness of climate change risk in a study across \r 119 countries of public awareness of climate change risk (Lee, 2015), \r though this relationship varies in different nations, and is influenced \r by mediating variables (Muttarak and Chankrajang, 2015; Blennow \r et al., 2016) (Ballew et al., 2020). Knowledge and awareness of climate \r change are correlated with the motivation to undertake action on \r climate change (Hornsey and Fielding, 2017). The integration of climate \r science in educational curricula has been shown to be effective (Hess \r and Maki, 2019; Molthan-Hill et al., 2019), including approaches such \r as integration of the complex system approach (Jacobson et al., 2017), \r experiential climate change education (Siegner, 2018), including climate \r [...]"


id: 97e070ae5bb041c98e75f7286e09a9a4
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
vector_id: 23934
content:
"[...] games (O'Garra et al., 2021; Pfirman et al., 2021), massive open online \r courses and informal science learning centres (Geiger et al., 2017)."


id: d52ac91019517775d30d26f6f8f6db76
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 34826
content:
"Urgency can catalyse action for individuals and organisations. A \r moderate level of urgency serves as an important driver of climate \r action, but both high and low levels of urgency impede response \r (high confidence). Wilson and Orlove (2021) review 5 experimental \r and 20 observational papers that examine the relationship between \r urgency and levels of response in climate decision-making, across a \r range of settings: from individuals and households to communities, \r managed ecosystems, sub-national regions and international river \r basin. Urgency in the papers is defined primarily through objective \r and subjective time pressure, including the recognition of the costs of \r delaying action and the importance of using windows of opportunity \r during which new forms and higher levels of response are possible. \r All the experimental papers and all but three of the observational \r papers provide support for an inverted U-shaped relationship between \r [...]"


id: c492c5c4e38f005c64716475ac8d28cc
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
vector_id: 31895
content:
"Policy leaders, often described as policy entrepreneurs within the \r scholarly literature, are individuals in positions of leadership who set \r agendas and build coalitions to drive decision-making processes, and \r hence can function as catalysers of climate adaptation (Petridou and \r Mintrom, 2020). Political leaders who have taken on climate change \r as a key policy issue function as policy entrepreneurs at international, \r national and sub-national levels. City officials, including mayors and \r other executives, often play the role of climate policy entrepreneurs, \r while the absence of effective leadership negatively affects adaptation \r success (Becker and Kretsch, 2019). Such entrepreneurs can be \r important forces for change in both reactive contexts following an \r extreme or focusing event and in proactive context. They can be effective \r especially in contexts where they navigate and link together formal and \r [...]"


id: 5f2f2b38a524c7c2ea88ac36f391ff50
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
vector_id: 14051
content:
"[...] informal networks of complex climate governance systems (Tanner et al., \r 2019). Their capacity to act has been increased when they and their \r institutions are embedded within partnership networks (Bellinson and \r Chu, 2019). It is in these contexts that the leadership and position of a \r policy entrepreneur becomes even more catalytic when operating at the \r interface of formal and informal networks (Mintrom, 2019; Stone, 2019)."


id: 5dd8485a38b77b1a62bfacd1b2b83dfa
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 13811
content:
"The highly contextual nature of adaptation, a multitude of applied \r definitions of adaptation (e.g., cost effectiveness versus outcomes), \r its overlaps with development interventions, and the long time \r horizons over which outcomes accrue, deter a universal definition \r of adaptation success (Dilling et al., 2019; Section 17.5.1.2; Owen, \r 2020; Singh et al., 2021). Moser and Boykoff (2013), Olazabal et al. \r (2019b) and Sherman and Ford (2013) suggest criteria against which \r successful adaptation could potentially be tracked. The literature \r is converging to suggest that successful adaptation broadly refers \r to actions and policies that effectively and substantially reduce \r climate vulnerability, and exposure to and/or impacts of climate risk \r (Noble et  al., 2014; Juhola et  al., 2016), while creating synergies \r to other climate-related goals, increasing benefits to non-climate\u0002related goals (such as current and future economic, societal and \r [...]"


id: 462b15e374a109cf340b746de05e8076
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 9567
content:
"[...] other environmental goals) and minimise trade-offs (Grafakos et al., \r 2019) across diverse objectives, perspectives, expectations and \r values (Eriksen et al., 2015; Gajjar et al., 2019a; Owen, 2020) (high \r confidence)."


id: aa30e3ebae3507fbd5ea8338a145bb5
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 27167
content:
"Sub-national actors and city officials including mayors and other \r executives are among the individuals most often described and assessed \r as climate policy entrepreneurs (Kalafatis and Lemos, 2017). City-level \r climate policy entrepreneurs often operate using their own experience, \r connections and persistence to address issues of importance to their \r constituency. Climate risk concerns are often inherently local, and in \r turn local decision makers perceive it as being appropriate to engage. \r Conversely, the absence of effective leadership negatively affects \r adaptation success (Kalafatis and Lemos, 2017; Becker and Kretsch, \r 2019). Urban climate policy entrepreneurs operate in four key spheres \r of policy development and implementation: attention and support \r seeking strategies; linking strategies (e.g., coalition building); relational \r management strategies (e.g., networking and trusting building); and \r arena strategies including timing (Brouwer and Huitema, 2018). The \r [...]"


id: 8530f68d29694ac1abe4be0774dd89c5
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 20575
content:
"[...] presence and operation of urban climate policy entrepreneurs is positively \r associated in settings with multiple jurisdictions and across differing \r spatial scales (Kalafatis and Lemos, 2017; Renner and Meijerink, 2018). "


id: f7252c8e8b49f23ac75664216b703257
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 40852
content:
"With increasing impacts of climate change, settlements of all sizes are considering how to make their communities more resilient \r to climate risk (see Cross-Working Group Box  URBAN in Chapter 6; Araos et  al., 2016a; Araos et  al., 2017; Reckien et  al., 2018a). \r In many settlements, demands for heightened resiliency are being coupled with opportunities to enhance the social and economic \r equity and quality of life of residents. Transformational adaptation (transformational, as being outcome-oriented; Vermeulen et al., 2018) \r and associated adjustments to the urban risk management decision-making require an integration of climate resiliency pathways and \r conditions of sustainable development (Mendizabal et al., 2018). At the same time, growing conflict is present between requirements \r for greater resiliency and continued economic development, in particular in low-income environments (Ahenkan et al., 2020). Cities and \r [...]"


id: 36efde1fe5d2aefa8b2409a1669663eb
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 6890
content:
"[...] their residents have the capacity to transform their own governance and decision-making systems (Birkmann et al., 2014; Chu, 2018; \r Romero-Lankao et al., 2018). Furthermore, cities have recognised the opportunity and demand to transform in order to be more ambitious \r (Mendizabal et al., 2018) and more successful, more equitable (Reckien et al., 2018b) and better able to connect the climate action to the \r sustainable development process (Singh et al., 2021)."


id: 7f23f3f9ab353a778d1fe946044f9ebe
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 19521
content:
"In some cases, transformational adaptation is associated with large-scale, top-down, formal decision processes leading to significant \r policy shifts. For coastal cities, this might include actions to build massive flood protection systems (as opposed to simple increase of \r existing structures) (Albers et al., 2015; Hinkel et al., 2018; Ajibade, 2019; see also Section 2.3.5, Cross-Chapter Paper 2) or policies \r to encourage managed retreat from increasing at risk locations (Hino et al., 2017; Rulleau and Rey-Valette, 2017). In more extreme \r instances, the relocation of cities is presented as a possibility, such as planned for the city of Jakarta (Garschagen et al., 2018b). However, \r acceptability of top-down approaches to relocation are usually low, and bottom-up drivers of relocation are important, especially to avoid \r inequitable outcomes (Mach and Siders, 2021). Intensity of extreme events and changing risk perceptions and expectations of property \r [...]"


id: 778b606e995a5c06a78ca9a268eb6319
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 18235
content:
"[...] prices have been identified as important behavioural drivers of voluntary relocation (de Koning et al., 2019; de Koning and Filatova, 2020). \r Yet, when not supported by equitable public adaptation policies, the transformational adaptation left to the influence of autonomous \r adaptation and market institutions alone leads to climate gentrification low-income households are priced out from the hazard-free \r zones (de Koning and Filatova, 2020)."


id: 2fd1b0974bf0ea2c1d89e3b21eb43fd3
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 5668
content:
"According to an assessment (Figure  17.11; see SM 17.1 for full \r descriptions) of maladaptation-relevant outcome dimensions, here \r called criteria, that is, benefits to people, benefits to ecosystem services, \r benefits to equity (marginalised ethnic groups, gender, low-income \r populations), transformational potential and contribution to GHG \r emission reduction, no option is located at one or the other end of \r the adaptation-maladaptation continuum (Figure  17.11, right panel), \r showing that all options have some maladaptation potential, that \r is, trade-offs (very high confidence). This is also shown by the wide \r confidence ranges of most options (right panel) signifying that most \r adaptation can be done in a way that involves a higher or a lower risk of \r maladaptation (medium confidence; see also Figure 17.3). The option of \r 'coastal infrastructure' signifies the highest risk for maladaptation. While \r [...]"


id: f64a4c381f4a2f916da652ea25d0ac9d
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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content:
"[...] it can be an efficient adaptation option in highly densely populated areas \r (Oppenheimer et al., 2019; CCP2.3), it has potential trade-offs for natural \r system functioning and human vulnerability over time. The options most \r widely associated with successful adaptation are 'nature restoration', \r 'social safety nets', 'change of farm/fishery practice' and 'change of \r diets/reducing food waste' (high confidence)."


id: 2b1911dd55497b1086ff07607ba61554
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 4823
content:
"leads to findings for general situations, potentially obscuring critical \r contextual specificities which can mediate successful adaptation or \r maladaptation outcomes. In a certain context, Figure 17.11 will appear \r different. Moreover, the analysis is based on a static interpretation of \r adaptation outcomes, while risk and risk reduction are dynamic. The \r current, underlying literature does not help understanding the temporal \r dimension of the options, their flexibility or risk of lock-in, and related \r potential contribution to long-term maladaptation or successful \r adaptation. The added value of the analysis lies in the approach to \r assess the potential contribution to maladaptation or successful \r adaptation (via the seven criteria at the top of the figure), rather \r than in the final results themselves. This overview illustrates how, in \r a particular context and for particular groups of people, adaptation \r [...]"


id: e6160ff153bef7b552baf6fb291114c5
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 37775
content:
"[...] options and their location on the adaptation-maladaptation continuum \r can be assessed for a set of outcome dimensions, focusing on assessing \r potential contributions per and across criteria as well as per and across \r options (critical information to support the identification of adaptation \r pathways; Cross-Chapter Box DEEP in this Chapter)."


id: d83a4164342883a3c415c4094fbaea03
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
vector_id: 35345
content:
"Figure 17.11 |  The potential contribution of 24 adaptation-related options to maladaptation and successful adaptation. The figure builds on evidence provided \r in the underlying sectoral and regional chapters and the Cross-Chapter Papers (SM17.1) to map 24 adaptation options identified as relevant to the eight Representative Key Risks \r (see Section 16.5) onto the adaptation-maladaptation continuum. It assesses the potential contribution of each of these adaptation options to successful adaptation and the risk of \r maladaptation. The figure permits a review of options in multiple ways: (a) looking at adaptation options (first column), one can see which adaptation options score highest across \r the criteria (the central rows). Results by options show which ones carry the highest risk of maladaptation (largest circles per row); (b): looking at criteria (top centre), one can see \r [...]"


id: b7b487673114aaf4940393723d471e40
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
vector_id: 29537
content:
"[...] which criteria seem to be most influential to contribute to maladaptation outcomes (largest circles per central column); (c) panel on the right: merging the scores of each adaptation \r option across criteria helps highlight whether the options are likely to end up as successful adaptation or maladaptation."


id: 9d274ef294e5680c8734adf396decae9
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 24888
content:
"A global assessment of 1682 papers on adaptation (Araos et al., 2021) \r finds that about 60% of articles mentioned at least one vulnerable \r group being involved in the implementation of adaptation or targeted \r by it (medium confidence). Low-income groups (high agreement, 37% \r of 1682 articles) and women (medium agreement, 20% articles) are \r the most frequently mentioned. Particularly in sectors and regions that \r incorporated coping measures in their adaptation response (poverty, \r food, Africa, Asia, Central and South America), these groups are \r prevalent. In sectors where responses were more strategic or planned, \r such as in cities, terrestrial and water, in a larger proportion of articles \r (51%, 47% and 47% of articles, respectively) vulnerable groups were \r not frequently included in the response (medium agreement). There \r was also a stark difference in inclusion of marginalised and vulnerable \r groups between high-income and low-income countries or regions, \r [...]"


id: 858348aece9fbffcf1886c900626660e
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
vector_id: 20629
content:
"[...] with the majority of the responses from Australia, Europe and North \r America, not including marginalised groups (high agreement with \r 70%, 69% and 55% of articles, respectively), showing the need for \r increasing attention in particular on a cross-sectoral and cross-regional \r relation (Araos et al., 2021)."


id: 8ba41353ffd0ca6044a6fce18ba04c57
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 21738
content:
"Procedural equity and justice: Participation is employed to enable \r procedures that aim to redress power imbalances, which are assumed \r to be the root causes of vulnerability (i.e., the reasons that lead certain \r people and places to be differentially vulnerable to climate risks) \r (Tschakert and Machado, 2012; Shackleton et al., 2015; Schlosberg et al., \r 2017; Ziervogel et al., 2017). However, participation is often constrained \r by gender (Cross-Chapter Box GENDER in Chapter 18), social status, \r unequal citizenship (as concerns education, access to information, \r finance and media) (Wallimann-Helmer et  al., 2019), entrenched \r political interests (Shackleton et  al., 2015; Chu et  al., 2017), power \r dynamics (Rusca et  al., 2015; Taylor and Bhasme, 2018; Kita, 2019; \r Omukuti, 2020; Taylor and Bhasme, 2020) or institutional shortcomings \r (Nightingale, 2017, in Nepal), which allow the most powerful access \r to funding and reinforce marginalisation of the powerless (Schipper \r [...]"


id: b8b3ce7bedf8e5cf6b7d247239d1ca12
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
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index: climate_gpt_v2
vector_id: 29701
content:
"[...] et al., 2014; Khatri, 2018; McNamara et al., 2020). Vulnerability is also \r sometimes used as a pretext to exclude groups from participation, \r often because vulnerable groups do not own land and lack legal status, \r time or the ability to commit labour or material inputs for adaptation, \r all drivers of vulnerability in the first place (Nyantakyi-Frimpong and \r Bezner Kerr, 2015; Camargo and Ojeda, 2017; Nagoda and Nightingale, \r 2017; Nightingale, 2017; Thomas and Warner, 2019; Mikulewicz, 2020)."


id: bf1e0e58d71c6a6e2f136de9060af138
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 30902
content:
"Reporting from the global assessment of equity considerations in \r adaptation, procedural equity and justice was slightly more often \r mentioned (~52%) than not (~48%) (medium agreement). However, the \r robustness of the evidence on inclusion of vulnerable and marginalised \r groups in the planning of adaptation responses is low (63%) (high \r agreement). Only for ~6% of the articles that provide evidence for \r inclusion of vulnerable groups was the robustness of evidence high (low \r agreement). Globally, the categories of low income (~25%) and women \r (~13%) are most often included, although the robustness remains \r low. Most of the robust evidence comes from Africa and Asia, where \r adaptation responses mostly focus on low-income and women groups \r in the food (28%) and poverty (32%) sectors (medium agreement). With \r regard to other vulnerability categories, such as disabled populations, \r almost negligible evidence was found for the inclusion of this group, \r [...]"


id: 6fc136bf9de9228dda44fdffe3eb899d
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 16917
content:
"[...] globally. There is also little reporting of procedural equity in community\u0002based or ecosystem-based responses (Araos et al., 2021)."


id: ceb5742a91b56245f15973d44347e738
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 33704
content:
"Adaptation responses have been observed in every region and across \r a wide variety of sectors (Section 16.3), but little evidence exists of \r their outcomes in terms of climate risk reduction (high confidence) \r (Section  1.4.3; Ford and Berrang-Ford, 2016; Tompkins et  al., 2018; \r Berrang-Ford et al., 2021; Eriksen et al., 2021; UNEP, 2021a). To advance \r on that, the Paris Agreement is encouraging countries to engage in \r 'Monitoring and evaluating and learning from adaptation plans, \r policies, programmes and actions' (UN, 2015, Article 7.9d). Monitoring \r and evaluation (M&E) is the systematic process of collecting, analysing \r and using information to assess the progress of adaptation and evaluate \r its effects--for example, risk reduction outcomes, co-benefits and \r trade-offs--mostly during and after implementation (AR6 Glossary, \r Annex II). Distinctions between monitoring and evaluation typically \r view monitoring as a continuous process of tracking implementation \r [...]"


id: 2eb552f03caa378fff9d74e5b485ac69
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 5496
content:
"[...] and informing management to allow for corrective action including \r in situations of deep uncertainty (see Cross-Chapter Box DEEP in this \r Chapter), while evaluation is described as a more comprehensive \r assessment of achievements, unintended effects and lessons learned "


id: 9227ffab221defacd33bc2766e58a583
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 22931
content:
"Central to designing, monitoring and evaluating adaptation responses \r is outlining how activities are expected to lead to intended objectives, \r for example, via a theory of change (Bours et al., 2014c; Oberlack and \r al., 2019). Theories of change or similar change models provide a basis \r to decide what to measure, but more attention needs to be paid to \r how theories of change are constructed and who is involved (Mason \r and Barnes, 2007; Forsyth, 2018). Participatory approaches can support \r understanding how climate risks affect the respective population, \r how these risks interact with social and cultural processes, and how \r responses could most effectively address climate risks (Conway et al., \r 2019). Inclusive M&E systems can facilitate ownership and enhance \r the meaningfulness and usability of the generated information \r (CARE, 2014; Faulkner et al., 2015). Meaningfulness is not associated \r with a particular approach or method but depends on whether the \r [...]"


id: cf8489c79163ab504bc815cd587373bf
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 33871
content:
"[...] chosen M&E design fits the M&E purpose and the information needs \r of the intended audience (Fisher et al., 2015; Leiter, 2017). Effective \r communication of M&E findings and feedback into decision-making \r processes is essential to achieve the respective M&E purpose and \r facilitate learning (Section 17.5.2.7)."


id: deca7b4b71d59ab50ecd0b6ef7d59af9
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 36462
content:
"A set of all-purpose and globally applicable standard indicators that \r could comprehensively measure adaptation does not exist (high \r confidence) (IPCC, 2014; Leiter and Pringle, 2018). A wide variety of \r indicators have been used to assess adaptation and its results (CARE, \r 2010; Harvey et al., 2011; Lamhauge et al., 2013; Brooks et al., 2014; \r Hammill et al., 2014b; Makinen et al., 2018; HM Government, 2019). \r Literature has also noted unrealistic expectations of what indicators \r can accomplish. For instance, decisions involving competing political \r interests would not be adequately informed through simple indicators; \r and learning requires knowledge of how and why change has \r happened, something that indicators often do not capture (Hinkel, \r 2011; Bours et  al., 2014b). Indicators can also become misguided \r incentives and might steer attention away from what matters (Leiter \r and Pringle, 2018; Hallegatte and Engle, 2019; Klonschinski, 2021). \r [...]"


id: d0e3126686cedb65ee8fc0f8ecf74518
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 34098
content:
"[...] Surveys, scorecards, interviews and focus groups are alternative \r methods of gaining insights on adaptation progress (Brooks et  al., \r 2014; Porter et al., 2015; Das, 2019; McNamara et al., 2020)."


id: f876a1d4d01e9bad2fd0e084f93a99ba
created_at: 2023-04-19 13:23:04
updated_at: 2023-04-19 13:23:04
content_type: text
index: climate_gpt_v2
vector_id: 41072
content:
"Indices, the combination of multiple indicators into a single score, are \r common products of risk and vulnerability assessments to compare \r countries or other entities, often in the form of rankings or maps \r (Preston et al., 2011; Reckien, 2018; de Sherbinin and et al., 2019). They \r can indicate changes in vulnerability over time within their respective \r conceptualisation of vulnerability or risk. The construction of indices, \r including indicator selection, their weighting, normalisation and \r data sources, has a profound impact on their scores (Reckien, 2018). \r Research has consistently found large discrepancies between country \r vulnerability rankings (Brooks et  al., 2005; Eriksen and Kelly, 2007; \r Leiter et al., 2017b; Visser et al., 2020). Reviews of vulnerability and \r resilience indices identified 'substantial conceptual, methodological \r and empirical weaknesses' (Fussel, 2010: 8) and a widespread lack \r [...]"


