FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Chapter 17: Decision Making Options for Managing Risk 3 4 Coordinating Lead Authors: Mark New (South Africa), Diana Reckien (Netherlands), David Viner (United 5 Kingdom) 6 7 Lead Authors: Carolina Adler (Switzerland/Chile/Australia), So-Min Cheong (Republic of Korea), Cecilia 8 Conde (Mexico), Andrew Constable (Australia), Erin Coughlan de Perez (USA), Annamaria Lammel 9 (France), Reinhard Mechler (Austria), Ben Orlove (USA), William Solecki (USA) 10 11 Contributing Authors: Rachel Bezner Kerr (Canada), Sukaina Bharwani (United Kingdom), Robbert 12 Biesbroek (Netherlands), Laurens Bouwer (The Netherlands), Lily Burge (United Kingdom), Massimo 13 Cattino (Italy), Isabelle Cojocaru-Durand (Canada), Mauricio Dom韓guez Aguilar (Mexico), Hannah Farkas 14 (USA), Simon French (United Kingdom), Adugna Gemeda (Ethiopia), Michael Gerrard (USA), Elisabeth 15 Anne Gilmore (USA), Nicoletta Giulivi (Italy/Guatemala), Maron Greenleaf (USA), Marjolijn Haasnoot 16 (The Netherlands), Ralph Hamman (Germany), Kirstin Holsman (USA), Christian Huggel (Switzerland), 17 Margot Hurlbert (Canada), Kripa Jagannathan (India/USA), Catalina Jaime (UK/Colombia), Sirkku Juhola 18 (Finland), Zoe Klobus (USA), Carola Kloeck (Germany/France), Bettina Koelle (South Africa/Germany), 19 Robert Kopp (USA), Carolien Kraan (The Netherlands), Judy Lawrence (New Zealand), Timo Leiter 20 (Germany/United Kingdom), Robert Lempert (USA), Debora Ley (Mexico), Megan Lukas-Sithole (South 21 Africa), Katharine Mach (USA), Alexandre Magnan (France), Kathleen Miller (USA), Lionel Mok 22 (Canada), Veruska Muccione (Italy), Rupa Mukerji (India), Baysa Naran (Mongolia), (Camille Parmesan 23 (USA), Lei Pei (China), Lavinia Perumal (South Africa), Madeleine Rawlins (United Kingdom), Neha Rai 24 (United Kingdom), Britta Rennkamp (South Africa/Germany), Alexandra Rinaldi (USA), Olivia Rumble 25 (South Africa), Liane Schalatek (USA), Emma Lisa Freia Schipper (Sweden/USA), Pasang Yangjee Sherpa 26 (USA/Nepal), Sabrina Shih (USA), Roopam Shukla (India/Germany), Rachael Shwom (USA), Chandni 27 Singh (India), M. Cristina Tirado-von der Pahlen (USA/Spain), Cathy Vaughn (USA), Maria Alejandra 28 Velez (Colombia), Ivo Wallimar-Helmer (Switzerland), Charlene Watson (United Kingdom), Romain 29 Weikmans (Belgium), Andrew Jordan Wilson (USA), Katy Wilson (United Kingdom), Mark Workman 30 (United Kingdom) 31 32 Review Editors: Richard Klein (Germany/The Netherlands), Zinta Zommers (Latvia/Sierra Leone) 33 34 Chapter Scientists: Megan Lukas-Sithole (South Africa), Massimo Cattino (Italy), Lauren Arendse (South 35 Africa), Vita Karoblyte (United Kingdom), Leah Jones (USA) 36 37 Date of Final Draft: 1 October 2021 38 39 Note: TSU Compiled Version 40 41 42 Table of Contents 43 44 Executive Summary..........................................................................................................................................3 45 17.1 Objectives and Framing of the Chapter .................................................................................................7 46 17.1.1 Introduction.....................................................................................................................................7 47 17.1.2 Objectives and Key Terms...............................................................................................................9 48 Box 17.1: How is Success in Adaptation Characterised in Chapter 17? ...................................................10 49 17.1.3 Outline of the Chapter...................................................................................................................11 50 17.2 Risk Management and Adaptation Options.........................................................................................12 51 17.2.1 Adaptation Options for Climate Risk Management ......................................................................13 52 17.2.2 Combining Adaptation Options: Portfolios of Risk Management and Risk Governance.............19 53 Box 17.2: Climate Risk Management in Conflict-affected Areas...............................................................23 54 Cross-Chapter Box LOSS: Loss and Damage .............................................................................................31 55 17.3 Decision-making Processes of Risk Management and Adaptation ....................................................34 56 17.3.1 Decision-analytic Methods and Approaches ................................................................................36 57 Cross Chapter Box DEEP: Effective adaptation and decision-making under deep uncertainties .........51 Do Not Cite, Quote or Distribute 17-1 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 17.3.2 Integration Across Portfolios of Adaptation Responses ...............................................................55 2 17.4 Enabling and Catalysing Conditions for Adaptation and Risk Management ..................................55 3 17.4.1 Introduction...................................................................................................................................55 4 17.4.2 Enabling Condition 1: Governance ..............................................................................................56 5 17.4.3 Enabling Condition 2: Finance.....................................................................................................61 6 Cross-Chapter Box FINANCE: Finance for Adaptation and Resilience ..................................................62 7 17.4.4 Enabling Condition 3: Knowledge and Capacity .........................................................................70 8 17.4.5 Enabling Condition 4: Catalysing Conditions..............................................................................76 9 Box 17.3: Climate Risk Decision-Making in Settlements: From Incrementalism to Transformational 10 Adaptation ...............................................................................................................................................82 11 17.5 Adaptation Success and Maladaptation, Monitoring, Evaluation and Learning.............................83 12 17.5.1 Adaptation Success and Maladaptation........................................................................................83 13 17.5.2 Adaptation Monitoring, Evaluation & Learning ..........................................................................91 14 Cross-Chapter Box PROGRESS: Approaches and Challenges to Assess Adaptation Progress at the 15 Global Level ............................................................................................................................................96 16 BOX 17.4: The Rio Markers Methodology to Track Climate Finance ...................................................100 17 17.6 Managing and Adapting to Climate Risks for Climate Resilient Development .............................101 18 17.6.1 Need for Integrated Risk Management .......................................................................................101 19 17.6.2 Strategies for Managing a Portfolio of Climate Risks................................................................102 20 17.6.3 Mainstreaming Climate Risk Management in Support of Climate Resilient Development ........102 21 FAQ17.1: Which guidelines, instruments and resources are available for decision-makers to recognize 22 climate risks and decide on the best course of action?......................................................................103 23 FAQ17.2: What financing options are available to support adaptation and climate resilience?..........104 24 FAQ17.3: Why is adaptation planning along a spectrum from incremental to transformational 25 adaptation important in a warming world?.......................................................................................106 26 FAQ17.4: Given the existing state of adaptation, and the remaining risks that are not being managed, 27 who bears the burden of these residual risks around the world? ....................................................107 28 FAQ17.5: How do we know whether adaptation is successful? ...............................................................107 29 References......................................................................................................................................................110 30 31 Do Not Cite, Quote or Distribute 17-2 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Executive Summary 2 3 Introduction and Framing 4 5 Chapter 17 assesses the options, processes and enabling conditions for climate risk management, a key 6 component of climate resilient development. While Chapter 16 assesses the risks that society and ecosystems 7 face, and residual risks after adaptation, this chapter focuses on the "how" of climate risk management and 8 adaptation. It covers: the adaptation and risk management options that are available; the governance and 9 applicability of options in different contexts; residual risk and Loss & Damage; the methods and tools that 10 can be drawn on to support climate risk management planning and implementation; enabling conditions and 11 drivers for adaptation; the role of monitoring and evaluation for integrated risk management and tracking 12 progress, success and the risk of maladaptation; and finally, integration of risk management across sectors, 13 jurisdictions and time horizons, under dynamic conditions of environmental and societal change. 14 15 Adaptation options for managing a wide range of climate risks have been proposed, planned, or 16 implemented across all sectors and regions, with prospects for wide-ranging benefits to nearly all 17 people and ecosystems (high confidence1) {17.2.1}. Many options are widely applicable and could be 18 scaled up to reduce vulnerability or exposure for the majority of the world's population and the ecosystems 19 they depend on (high confidence). These include nature restoration (high confidence), changing diets and 20 reducing food waste (high confidence), infrastructure retrofitting (high confidence), building codes (medium 21 confidence), disaster early warning (high confidence), and cooperative governance (medium confidence). The 22 portfolio of adaptation options that could be successfully implemented varies across locations, with resource- 23 limited and conflict-affected contexts bearing large amounts of residual risk (high confidence) {17.2, 24 17.5.1}. 25 26 The majority of climate risk management and adaptation currently being planned and implemented is 27 incremental (high confidence). Transformational adaptation will become increasingly necessary at 28 higher global warming levels (medium confidence) but can be associated with significant and 29 inequitable trade-offs (medium confidence). Adaptations with some of the highest transformative potential 30 include migration (high confidence), spatial planning (medium confidence), governance cooperation (medium 31 confidence), universal access to healthcare (medium confidence) and changing food systems (medium 32 confidence). Options that tend to modify existing systems incrementally include early warning systems (high 33 confidence), insurance (medium confidence), and improved water use efficiency (high confidence) {17.2, 34 17.5.1}. 35 36 Governance, especially when inclusive and context-sensitive, is an important enabling condition for 37 climate risk management and adaptation (very high confidence). The use of formal and informal 38 governance approaches, often in polycentric arrangements of public, private and community actors, is 39 being increasingly recognised as important across many decision-making settings (high confidence) 40 {17.3.2; 17.4.2}. Public governance leadership has the largest role for social safety nets, spatial planning, and 41 building codes (high confidence) {17.2.1}. Private sector governance is important for insurance and for 42 minimizing the stressors that can negatively impact ecosystems and their functions especially in the absence 43 of public regulations or enforcement (medium confidence) {17.2.1}. Communities and individuals play the 44 largest role in governance of adaptations to farming and fishery practices and ecosystem-based adaptations 45 (medium confidence) {17.2.1}. Informal or individual-led decision-making is more common in food security 46 and livelihood related adaptations, such as changes to diets, livelihood diversification and seasonal migration 47 (high confidence) {17.2.1}. People who have experienced climate shocks are more likely to take on informal 48 adaptation measures, and in places where people are more exposed to extreme events, autonomous 49 adaptation is more common (high confidence) {17.2.1}. 50 1 In this Report, the following summary terms are used to describe the available evidence: limited, medium, or robust; and for the degree of agreement: low, medium, or high. A level of confidence is expressed using five qualifiers: very low, low, medium, high, and very high, and typeset in italics, e.g., medium confidence. For a given evidence and agreement statement, different confidence levels can be assigned, but increasing levels of evidence and degrees of agreement are correlated with increasing confidence. Do Not Cite, Quote or Distribute 17-3 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 National and international legal and policy frameworks and instruments support the planning and 2 implementation of adaptation and climate risk management across scales, especially when combined 3 with guidelines for action (medium confidence) {17.4.2}. Nationally Determined Contributions (NDCs) 4 have been drivers of national adaptation planning, with cascading effects on sectors and sub-national action, 5 especially in developing countries (high confidence) {17.4.2}. Nearly all developing countries (particularly 6 SIDS) that included an adaptation component in their NDCs consider adaptation the most urgent aspect of 7 their national climate change response (high confidence) {17.4.2}. A steady increase in national and sub- 8 national laws, policies, along with regulations that mandate reporting and risk disclosure have promoted 9 adaptation response across public agencies, private firms and community organizations (high confidence) 10 {17.4.2}. Greater adaptation is present where national climate laws and policies require adaptation action 11 from lower levels of government and include guidelines on how to do so (medium confidence) {17.4.2}. 12 13 Recognition of the critical role of financing for adaptation and resilience as an important enabler for 14 climate risk management has strengthened (high confidence). Yet, since AR5, the gap between the 15 estimated costs of adaptation and the documented (tracked) finance allocated to adaptation has 16 widened (high confidence). Estimated global and regional costs of adaptation vary widely due to differences 17 in assumptions, methods, and data; the majority of more recent estimates are higher than the figures 18 presented in AR5 (high confidence). Although the estimated cost of adaptation is higher for developed 19 countries (medium confidence), for developing countries they are much higher as a proportion of national 20 income, making the self-financing of adaptation more difficult (high confidence). A high proportion of 21 developing country NDC adaptation contributions are conditional on external financial support, underscoring 22 the crucial role of international finance to achieve adaptation efforts commensurate with climate risks (high 23 confidence) {17.4.2; Cross-Chapter Box FINANCE in this Chapter}. Developed country climate finance 24 leveraged for developing countries for mitigation and adaptation has fallen short of the 100 USD billion per 25 year Copenhagen commitment for 2020 (very high confidence) {Cross-Chapter Box FINANCE in this 26 Chapter}. Substantial opportunities exist for improving access to climate finance, as well as its impact and 27 effectiveness {17.4.2; Cross-Chapter Box FINANCE in this Chapter}. 28 29 Private sector financing for adaptation has been increasingly promoted as a response to realized 30 adaptation finance needs (high confidence). However, private sector financing of adaptation has been 31 limited, especially in developing countries (high confidence). Tracked private sector finance for climate 32 change action has grown substantially since 2015, but the proportion directed towards adaptation has 33 remained small (high confidence) {Cross-Chapter Box FINANCE in this Chapter}; in 2018 these 34 contributions were 0.05% of total climate finance and 1% of adaptation finance. A key challenge for private 35 sector financing of adaptation is demonstrating financial return on investment, as many benefits of 36 adaptation arise as avoided damages or public goods, rather than direct revenue streams (medium 37 confidence). Leveraging private finance in developing countries is often more difficult because of risk 38 (perceived and real) to investors, reducing the pool of potential investors and/or raising the cost (interest) of 39 investment (medium confidence) {17.4.3.; Cross-Chapter Box Finance in this Chapter}. 40 41 Information and knowledge on climate risk and adaptation options, derived from different knowledge 42 systems, can support risk management and adaptation decisions (high confidence) {17.4.4}. Processes, 43 such as co-production, that link scientific, Indigenous, local, practitioner and other forms of knowledge can 44 make climate risk management processes and outcomes more effective and sustainable (high confidence) 45 {17.3.2; 17.4.4}. 46 47 Climate services that provide reliable, relevant, and usable climate information for the short or long 48 term are increasingly being produced and used in climate risk management (high confidence) {17.4.4}. 49 In many regions and sectors, the utility of climate services is strengthened by sustained engagement between 50 stakeholders and experts and by co-production (medium confidence) {17.4.4; Cross-Chapter Box Climate 51 Services WGI Chapter 12}. Significant gaps remain in the evaluation of climate services, and some studies 52 indicate that climate services often do not reach the most vulnerable and more isolated people, maintaining 53 or exacerbating inequality. 54 55 Catalyzing conditions and windows of opportunity can drive shifts in motivation and adaptation 56 effort, stimulating more rapid uptake of existing and new adaptation options (medium confidence) 57 {17.4.5}. Decision-makers can take advantage of windows of opportunity to promote rapid and Do Not Cite, Quote or Distribute 17-4 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 effective responses in reactive and proactive cases {17.4.5}. Disaster events or shocks such as wildfires, 2 tropical cyclones, heatwaves or coral bleaching have catalyzing characteristics (high confidence) {17.4.5.2}. 3 Additional types of catalyzing conditions include climate litigation and the presence of individuals and 4 organizations that act as policy and decision innovators, including government and business innovators in 5 cities (medium confidence) {17.4.5.3}, stimulating action within and beyond their immediate contexts 6 (medium confidence). Litigation on failure of government and business to adapt is becoming more frequent 7 and is expected to increase as climate impact attribution science matures further (high confidence) {Cross- 8 Chapter Box LOSS in this Chapter; 17.4.5.3}. 9 10 Urgency can stimulate prompt climate risk management (high confidence). A moderate level of urgency 11 contributes to enhanced climate action, while both high and low levels of urgency can impede response (high 12 confidence) {17.4.5.1}. Well-designed communication strategies can move decision makers from low to 13 moderate levels of urgency, stimulating action. As conditions approach a crisis state, however, urgency can 14 weaken decision-making rather than support it (medium confidence) {17.4.5.1}. 15 16 Decision support tools and decision-analytic methods are available and are being applied for 17 managing climate risks in varied contexts, including where deep uncertainty is present (high 18 confidence). These tools and methods have been shown to support deliberative processes where 19 stakeholders jointly consider factors such as the rate and magnitude of change and their uncertainties, 20 associated impacts and timescales of adaptation needed along multiple pathways and scenarios of 21 future risks (high confidence) {17.3.2; Cross-Chapter Box DEEP in this Chapter}. However, 22 comparative evidence on the relative utility of different analytical methods in their use by decision makers 23 for managing climate risks is an important gap (medium confidence). Nevertheless, robust decision-making, 24 using pathway analyses to determine `no regrets' options amongst trade-offs, has been shown to be a useful 25 starting point under deep uncertainty (medium confidence). Methods for analysing options differ across geo- 26 political scales, with modeling studies being a particularly prominent method across scales from community 27 and urban to regional and national (high confidence) {17.3.1; 17.6, Cross-Chapter Box DEEP in this 28 Chapter}. 29 30 Successful adaptation and maladaptation form the opposite poles of a continuum (medium confidence). 31 The evaluation of an adaptation option and its location on this continuum are context-specific and 32 vary across time, place and evaluation perspectives (high confidence) {17.5.2}. Despite knowledge gaps, 33 adaptation options can be assessed according to several criteria, such as benefits to humans, benefits to 34 ecosystem services, benefits to equity (marginalized ethnic groups, gender, low-income populations), 35 transformational potential, and contribution to greenhouse gas emission reduction (medium confidence) 36 {17.5.1}. These factors can aid evaluation of co-benefits and trade-offs within and between adaptation 37 responses (high confidence) facilitating successful adaptation and reducing the likelihood of maladaptation 38 (medium confidence) {17.5.1}. 39 40 Adaptation options across a range of climate risk settings (Representative Key Risks) have potential 41 for some degree of maladaptation alongside varied potential for success (very high confidence) {17.5.2}. 42 Maladaptation can result from unaccounted trade-offs with low-income groups and the transformational 43 potential of adaptation (medium confidence) {17.5.2}. Success is greatest when adaptation enhances gender 44 equity (medium confidence) {17.5.2} and supports ecosystem function and services (medium confidence) 45 {17.5.2}. Among adaptation options, coastal infrastructure is an example that has particularly high risk for 46 maladaptation through trade-offs for natural system functioning and human vulnerability over time. 47 Examples of options with high potential for successful adaptation are nature restoration (medium confidence) 48 {17.5.2}, social safety nets (medium confidence) {17.5.2} and adaptations relating to changes of diets and 49 reducing food waste (medium confidence) {17.5.2}. 50 51 Monitoring and evaluation (M&E) are key for iterative climate risk management, in particular 52 tracking adaptation progress and learning about adaptation success and maladaptation (high 53 confidence). M&E application has increased since AR5 at the local, project and national level, but is 54 still at an early stage in most countries (high confidence) and underutilized as a way to assess 55 adaptation outcomes at longer timeframes (high confidence) {17.5.2}. About one-third of countries have 56 undertaken steps to develop national adaptation M&E systems, but fewer than half of these are reporting on 57 implementation (medium confidence) {17.5.2}. M&E, as well as tracking global progress on adaptation, are Do Not Cite, Quote or Distribute 17-5 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 confronted with a number of challenges (high confidence), such as a comparability in what counts as 2 adaptation and limited availability of data across scales {17.5.2; Cross-Chapter Box PROGRESS in this 3 Chapter}. The relative strength and weaknesses of different approaches and their applicability have not been 4 systematically assessed, but the diversity of approaches being used could provide a more comprehensive 5 assessment of global adaptation progress (Cross-Chapter Box PROGRESS in this Chapter). 6 7 Understanding of residual impacts and risks in vulnerable regions and implications for Loss & 8 Damage (L&D) has become increasingly relevant as the limits to adaptation are projected to be 9 reached in natural and human systems (high confidence) {17.2.2.5; Cross-Chapter Box LOSS in this 10 Chapter}. The international L&D policy debate has seen heightened attention, with some coalescence 11 around key issues, including risk management, limits to adaptation, existential risk, finance and support, 12 including liability, compensation and litigation. Advisory groups have been set up with participation of 13 policy and experts from research, civil society and practice to inform debate. Yet, the policy space and 14 concrete remit for L&D has remained vague, which renders policy formulation complex (high confidence) 15 {17.2; Cross-Chapter Box LOSS in this Chapter}. 16 17 Effective management of climate risks is dependent on systematically integrating adaptations across 18 interacting climate risks, ensuring that measures of success include factors important to climate 19 resilient development, and accounting for the dynamic nature of climate risks over time (very high 20 confidence) {17.6}. Across the Working Group II report are examples of how managing adaptations to 21 reduce climate risks can negatively or positively affect sustainable development, thereby impacting the 22 potential for climate resilient development. Climate risks can emerge at different rates and time horizons, 23 and the interactions between risks vary from region to region (very high confidence) {17.6}. The need to 24 manage these risks in an integrated manner is demonstrated by the diverse and interacting impacts of climate 25 risks on ecosystems, cities, health, and poverty and livelihoods, such as in the Water-Energy-Food nexus 26 (high confidence) {17.6}. Expertise and resources for integrated risk management varies between the 27 developed and developing countries (high confidence) {17.6}. Integrated pathways for managing climate 28 risks will be most suitable when `low regrets' anticipatory options are established jointly across sectors in a 29 timely manner, path dependencies are avoided in order to not limit future options for climate resilient 30 development, and maladaptations across sectors are avoided (high confidence) {17.6}. National Adaptation 31 Plans have potential to integrate participatory, iterative processes to monitor, review, and update adaptations 32 as knowledge, experience and resources become available {Cross-Chapter Box DEEP in this Chapter; 17.6}. 33 34 35 Do Not Cite, Quote or Distribute 17-6 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 17.1 Objectives and Framing of the Chapter 2 3 17.1.1 Introduction 4 5 Addressing the impacts and risks associated with observed and projected climate change (see Chapter 16) is 6 fundamentally and intricately tied to the decision-making options available to manage those risks. Climate 7 risk decision-making focuses on the processes needed to identify and characterise those risks, generate plans, 8 policies to reduce the likelihood and/or magnitude of adverse potential consequences, based on assessed or 9 perceived risks (derived from the definition of risk and risk management in Chapter 1). This chapter presents 10 an assessment of the evidence on climate risk decision-making as a set of processes that involve a range of 11 actors in different contexts resulting in diverse outcomes. The climate risk decision-makers and their actions 12 are the central focus of the assessment. The chapter is an assessment of the evidence of the decision-making 13 options that are available in practice, and functions as a central pivot point between the identification of key 14 climate risks (Chapter 16) and the means to integrate and leverage action on climate risk decision-making 15 into the broader requirements of climate resilient development pathways (Chapter 18). This section 16 introduces the main entry points on decision-making that have framed this assessment (Sections 17.1.1.1 to 17 17.1.1.5), as well as the key terms used to frame this assessment and its organisation in this chapter (Section 18 17.1.2). 19 20 A central framing point is the connection between climate risk decision-making and adaptation. Adaptation 21 for human systems in this report is introduced in Chapter 1 and defined in the Glossary as `the process of 22 adjustment to actual or expected climate and its effects, in order to moderate harm or exploit beneficial 23 opportunities'. In natural systems, adaptation is the process of adjustment to actual climate and its effects; 24 human intervention may facilitate adjustment to expected climate and its effects (see AR6 Glossary). In this 25 chapter, we consider adaptations that may be implemented by people, whether they be to support human, 26 managed, or natural systems, and the processes and factors that underpin adaptation in these diverse settings. 27 Different types of adaptation have been distinguished in Chapter 1, including anticipatory versus reactive, 28 autonomous versus planned, and incremental versus transformational (IPCC WGII glossaries; Chapters 16- 29 18). These dichotomies and interactions are assessed here. Implementation of adaptation through iterative 30 risk management decision-making emphasizes that anticipating and responding to climate change does not 31 consist of a single set of judgments at a single point in time, but rather an on-going cycle of assessment, 32 action, reassessment, learn, and response' (Chapter 1). 33 34 17.1.1.1 Decision-Making for Managing Climate Risks in AR6 35 36 The UN 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals (SDGs), as 37 well the UNFCCC Paris Climate Agreement, the UN Sendai Framework Disaster Risk Reduction, and the 38 UN Habitat New Urban Agenda helped push climate risk management and adaptation forward from the 39 global to the national level, from the planning stage into implementation and provides benchmarks for 40 adaptation progress. To assess adaptation progress (17.5), the interplay between top-down (institutional) and 41 bottom-up (individual/social/community) processes, multi-scale interaction (local, regional, national, and 42 international), iterative risk management, differing forms of knowledge, and equity are especially crucial 43 (particularly Sections 17.2, 17.4). Parallel to these advances is an understanding and assessment of 44 appropriate decision support tools, methods, and evaluation metrics (Section 17.3). 45 46 Since AR5, significant advances have been made in regard to the understanding of the drivers of decision- 47 making and contexts in which climate risk decision-making takes place. Climate risk decision-making 48 generally, and adaptation specifically, has been a focus within the IPCC special reports in the sixth 49 assessment cycle. An overall goal of climate risk management is to eliminate or reduce the risk to levels that 50 are to a level that is socio-politically and economically acceptable. Risk management to an acceptable 51 level may not be feasible because of limits or barriers to adaptation. Future potential risks are a more 52 complex matter given the need to define time scales and spatial extent, and uncertainties. In the Special 53 Report on the impacts of global warming of 1.5C [SR1.5] (IPCC, 2018a), the risks associated with climate- 54 related impacts were found to be higher under emission scenarios above 1.5癈, raising awareness for the 55 need to limit the impacts of warming through the acceleration of climate mitigation and both incremental and 56 transformational adaptation (IPCC, 2018a). 57 Do Not Cite, Quote or Distribute 17-7 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 The AR6 SRCCL (IPCC, 2019b) added the dimensions of pace, intensity, and scale of climate impacts and 2 adaptation or mitigation responses and adverse consequences. Relevant land-based adverse consequences 3 include those on lives, livelihoods, health and wellbeing, economic, social, and cultural assets and 4 investments, infrastructure, services (including ecosystem services), ecosystems and species. 5 6 While a generic understanding of the decision-making process has emerged from the literature, the chapter 7 assesses how these components and their dimensions interact across a range of temporal (short, long-term as 8 defined in SROCC), scalar (household to global), institutional/governance (formal, informal, bottom up, top 9 down), and magnitude (micro adaptation - small scale and macro adaptation - large scale) (Section 17.2). 10 The IPCC SRCCL placed emphasis on acknowledging co-benefits and trade-offs to avoid barriers to 11 implementation, with particular attention to land use decisions. It states that this coordination can be 12 supported by building networks of decision-makers across scales and sectors, including local stakeholders 13 from vulnerable groups, and by adopting and implementing policies in a flexible and iterative manner (IPCC, 14 2019b). 15 16 17.1.1.2 Approaches to Assess and Synthesise Options for Managing Risk 17 18 This chapter utilizes several points of departure to assess climate risk management that emerge from AR5 19 and AR6, specifically. SR Climate Change and Land, especially Chapter 7 and throughout SROCC. 20 These works provide foundational assessment of evidence on decision-making systems that connect 21 different spatial and temporal scales and diverse cultural contexts in which climate risk management takes 22 place, the varying interactions of decision-makers and their stakeholder groups, and the barriers and enablers 23 to decision making, including governance, finance, and knowledge (Section 17.4). 24 25 Another significant advance is that instead of cataloguing decision-making strategies, the literature has now 26 evolved to the point where adaptation progress, effectiveness and efficiency can be more meaningfully 27 assessed through increased monitoring and evaluation capacity. Although the ability to measure success and 28 effectiveness is not fully developed and hampered by lack of data, agreed methods and terms, and time to 29 fully evaluate adaptation actions (see Sections 17.3.3 and 17.5, Cross-Chapter Box PROGRESS in this 30 Chapter).). The ambition to describe effectiveness and success illustrates further maturation of the literature 31 on climate risk decision-making as a system process. Overall, the process of climate risk decision-making 32 remains dynamic, and the chapter attempts to assess a variety of proactive management approaches being 33 developed and tested to address adverse, diverse and complex risks in a wide range of developing and 34 developed country contexts (see Figure 17.1). The chapter provides a synthesis of how these new approaches 35 are reflected in the sectoral and regional chapters and cross-chapter papers of this report (Chapters 2-15; 36 CCPs 1-7). Specifically, the goal is to provide a line of sight between the sectoral and regional chapters and 37 cross-chapter papers' decision-making assessment to sections in this chapter. This synthesis also helps to 38 present the varying and context-driven character of adaptation strategies now in practice and being 39 considered. 40 41 17.1.1.3 Key Risks Considered in the Assessment of Climate Risk Decision-making 42 43 In AR6 (Chapter 16 and Cross-Chapter Papers), over 100 key risks have been identified across regions and 44 sectors, which have the potential to manifest into severe impacts that are relevant to the interpretation of 45 United Nations Framework Convention on Climate Change (UNFCCC) Article 2, specifically on the 46 objective to avoid dangerous anthropogenic interference with the climate system. These risks are likely2 to 47 become more severe under higher warming scenarios and social-ecological conditions that yield high 48 exposure and vulnerability to the associated climate-related hazards. In this report, these key risks have been 49 grouped into categories represented by eight overarching risks (called Representative Key Risks, RKRs) 50 relating to: 1) coastal socio-ecological systems; 2) terrestrial and ocean ecosystems; 3) critical physical 51 infrastructure, networks, and services; 4) living standards; 5) human health; 6) food security; 7) water 2 In this Report, the following terms have been used to indicate the assessed likelihood of an outcome or a result: Virtually certain 99�100% probability, Very likely 90�100%, Likely 66�100%, About as likely as not 33�66%, Unlikely 0�33%, Very unlikely 0�10%, and Exceptionally unlikely 0�1%. Additional terms (Extremely likely: 95� 100%, More likely than not >50�100%, and Extremely unlikely 0�5%) may also be used when appropriate. Assessed likelihood is typeset in italics, e.g., very likely). This Report also uses the term `likely range' to indicate that the assessed likelihood of an outcome lies within the 17-83% probability range. Do Not Cite, Quote or Distribute 17-8 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 security; and 8) peace and human mobility (see Chapter 16). Decision-making options for managing these 2 risks, such as selecting the relevant adaptation options to implement, require an assessment of the local 3 context in which these impacts are likely to be experienced, as well as the local to global collective 4 implications of those actions (see Sections 17.2 and 17.5). 5 6 17.1.2 Objectives and Key Terms 7 8 17.1.2.1 Drivers 9 10 AR5 provides a broad overview of drivers as the determinants of climate decision-making by individuals and 11 organizations, including social, institutional, and regulatory contexts, cultural values and norms, economic 12 resources and constraints, and the availability of information and of tools to process it. This chapter expands 13 the discussion of the contexts for decision-making in a number of ways (see Section 17.4), including an 14 examination of informal as well as formal decisions, an attention to emerging actors, particularly social 15 movements, and consideration of several dimensions of governance. It expands the treatment of decision 16 processes, with particular attention to framing and to the integration of multiple time frames (Sections 17.3 17 and 17.6). 18 19 Since AR5, there has been an increasing ambition for adaptation, signalled by growing attention to the 20 adaptation gaps and deficits, which call for extensive and intensive levels of action (Chen et al., 2016; 21 UNEP, 2017; Tompkins et al., 2018; Valente and Veloso-Gomes, 2020; UNEP, 2021a), as well as increased 22 attention to co-benefits between climate risk reduction and other benefits, such as equity and biodiversity 23 conservation (Colloff et al., 2017, Section 17.5.1; Smith et al., 2020). Climate risk decision-making as an 24 object of study has emerged in a more central location within the literature as adaptation moves from 25 planning into the realm of practice. The broad sense of urgency (summarized in Wilson and Orlove, 2019; 26 Wilson and Orlove, 2021), show growth of the term "urgency" in both scholarly publications and the popular 27 press since 2014, building on earlier increases starting around 2005, and a dramatic spike of the terms 28 "climate crisis" and "climate emergency." Paralleling this call for more extensive and rapid action is the 29 emergence of the term "transformational" adaptation and decision-making. Transformational adaptation 30 (defined and deeply examined in Chapter 1, Chapter 16, and Section 17.2) highlights efforts that involve 31 large-scale, systemic change (Wilson et al., 2020) and involves "adapting to climate change resulting in 32 significant changes in structure or function that go beyond adjusting existing practices including approaches 33 that enable new ways of decision-making on adaptation" (IPCC, 2018a). The complex relationship between 34 incremental adaptation and transformational adaptation is presented and reviewed in 17.2. Furthermore, the 35 literature since the AR5 report has moved beyond the question of limits and barriers to adaptation as relevant 36 aspects for decision-making to additionally assessing drivers of change, with increasing focus devoted to 37 more nuanced and differentiated contexts for action. 38 39 17.1.2.2 Enabling Conditions 40 41 AR5 extensively assessed the conditions of adaptation with a focus on the role of governance, finance, 42 knowledge, and capacity. AR6 extends this examination of adaptation and the decision-making process 43 around it by focusing on enablers. Adaptation enablers are defined as those conditions or properties that 44 specifically promote or advance the adaptation process (see Chapter 1). Enablers are positively associated 45 with likelihood that adaptation planning occurs, and strategies will be put into practice. Three broad enabling 46 conditions are presented in the chapter (Section 17.4): governance (legislation, regulation, institutions, 47 litigation), finance (needs, sources, intermediaries, instruments flows, and equity) and knowledge (capacities, 48 climate services, big data, indigenous/local knowledge, co-production, boundary organizations). As an 49 extension of enabling conditions, the chapter also examines catalysing conditions for adaptation (Section 50 17.4.5). Catalysing conditions motivate and accelerate the process of decision-making leading to more 51 frequent and potentially substantial adaptations. The chapter recognises that the relative influence of 52 enabling conditions and catalysing conditions are set within the human dimensions of climate change 53 including vulnerability, inequality, poverty, and the achievement/non-achievement of SDGs (see Figure 8.1). 54 55 17.1.2.3 Mechanisms for Decision-making 56 Do Not Cite, Quote or Distribute 17-9 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 The mechanisms and conditions for decision-making provide the basis for the chapter. AR5 provided a 2 detailed chapter on the support of climate decision-making. Chapter 2 of AR5 concluded, with high 3 confidence, that risk management provides a useful framework for most climate change decision making, 4 and that iterative risk management is most suitable in situations characterised by large uncertainties, long 5 time frames, the potential for learning over time, and the influence of both climate as well as other 6 socioeconomic and biophysical changes. Furthermore, decision support is situated at the intersection of data 7 provision, expert knowledge, and human decision-making at a range of scales from the individual to the 8 organization and institution. 9 10 The climate risk management decision-making process follows a set of general considerations. The detail of 11 each decision is often highly context specific. Climate risk decision-making is bound to the question of how 12 and under what circumstance it is appropriate to alter, reduce or transfer and retain risk. Different types of 13 risk (e.g., gradual compared with catastrophic) and conditions of risk (e.g., known versus uncertain) are 14 associated with different types of responses (e.g., incremental versus transformational). As the risk decision 15 process precedes, individuals and organizations will formally or informally utilize any number of 16 mechanisms to guide, aid, or facilitate the decision-making process. Decision-making can then take place in 17 a linear set of steps or through a complex iterative process involving reflexive and recursive steps. 18 19 17.1.2.4 Costs and Non-Monetised Loss, Benefits, Synergies, and Trade-Off 20 21 AR5 provided an extensive discussion of the costs to human and natural systems associated with climate 22 risks. It recognized the challenges which long time frames, uncertainty and the differing values held by 23 stakeholders create for the monetisation of losses. The AR6 SROCC built on the discussion of cultural 24 values--typically also difficult to monetise--through a consideration of cultural ecosystem services and 25 cultural forms of valuation, with cases from high mountain areas and polar regions (Hock et al., 2019; 26 Meredith et al., 2019; IPCC, 2019c). AR6 expands this discussion of multiple forms of valuation in several 27 ways. It considers regulation and litigation as mechanisms for promoting the consideration of both 28 monetisable and non-monetisable losses in decision-making (Cross-Chapter Box LOSS in this Chapter). 29 AR5 treated the issues of equity and justice primarily with regard to mitigation, especially in WGIII AR5 30 Chapter 3; these issues in the adaptation sphere are considered extensively in this chapter in areas such as 31 finance, governance, success of adaptation, maladaptation, and monitoring and evaluation. The discussions 32 of maladaptation and success of adaptation (Section 17.5) consider questions of synergies and trade-offs 33 across values and goals, while the consideration of decision processes and tools shows opportunities to use 34 co-benefits to promote effective decision-making, including approaches to decision-making under conditions 35 of deep uncertainty (Section 17.3; Cross-Chapter Box DEEP in this Chapter). Successful adaptation across 36 the report (as specified in Ch1) is associated with conditions when co-benefits are high and (negative) trade- 37 offs are low. 38 39 17.1.2.5 Monitoring and Evaluation 40 41 This chapter assesses the evidence of monitoring and evaluation (M&E) (see AR6 Glossary) and their 42 approaches as part of the adaptation process at the national, local, and project level as well as in global 43 assessments (17.5.2; Cross-Chapter Box PROGRESS in this Chapter). M&E can serve multiple functions, 44 e.g., to: 1) facilitate an understanding on whether and how interventions work in achieving intended 45 objectives; 2) inform ongoing and future implementation, and 3) provide information that helps to 46 substantiate upward and downward accountability (Preston et al., 2009; UNFCCC, 2010b; Pringle, 2011; 47 Spearman and McGray, 2011) (see BOX 17.1 for more discussion). This chapter also addresses the relevance 48 of iterative learning as part of the design of M&E processes, as a means by which actors and institutions 49 engaged in M&E acquire new insights on how these processes work (or not) to achieve set objectives. 50 51 52 [START BOX 17.1 HERE] 53 54 Box 17.1: How is Success in Adaptation Characterised in Chapter 17? 55 56 Whether an adaptation is considered successful is context specific. It depends on who evaluates adaptation 57 and at what time as well as on the ability to compare the outcome of adaptation with a hypothetical situation Do Not Cite, Quote or Distribute 17-10 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 without adaptation and without other parallel changes, such as development interventions (Singh et al., 2021; 2 Dilling et al., 2019a). The ability to compare the risk situation post and prior adaptation is complicated 3 through the long time-horizons at which adaptation outcomes often become apparent (see Cross-Chapter Box 4 ADAPT in Chapter 1; Section 17.5.1; Dilling et al., 2019a). 5 6 However, a wealth of information has recently become available on how success and effectiveness of 7 adaptation could be assessed, defined, or investigated in certain settings (Patt and Schr鰐er, 2008; Morecroft 8 Michael et al., 2019; Tubi and Williams, 2021) or across a larger set of adaptations (Hegger et al., 2012; 9 Eriksen et al., 2015; Gajjar et al., 2019a; Owen, 2020; Singh et al., 2021). Accordingly, successful adaptation 10 is understood as effective adaptation, in that it reduces climate impacts, vulnerabilities and risk, and 11 additionally balances synergies and trade-offs across diverse objectives, perspectives, expectations, and 12 values (Eriksen et al., 2015; Juhola et al., 2016; Gajjar et al., 2019a; Owen, 2020; Singh et al., 2021). Across 13 this report, four factors are identified as enabling conditions of successful adaptation, which include a focus 14 on recognitional, procedural, and distributional justice as well as flexible and strong institutions that seek 15 policy integration and account for long-term goals. 16 17 To operationalizable `success' in this chapter, it is characterised by the degree to which an adaptation 18 response benefits (1) human systems (number of people); (2) ecosystems or ecosystem services; (3) 19 marginalized ethnic groups, (4) women and girls, (5) and low-income populations, and can be characterised 20 as (6) transformational adaptation, and (7) contributing to greenhouse gases emission reductions (Section 21 17.5.1). Overarching to these factors are uncertainty and potential path-dependency of decisions that may 22 result in lock-in and maladaptation in the long-term, and recognition that what is successful in the near-term 23 is not necessarily successful in the long-term. 24 25 Success in adaptation is antithetical to maladaptation. Maladaptation refers to current or potential future 26 negative consequences, including failed or partially successful adaptation (or risk reduction), but also trade- 27 offs or side-effects of adaptation (see Glossary). Thus, success of adaptation and maladaptation form the 28 ends of a continuum that represents the balancing of synergies and trade-offs across regions, populations, or 29 sectors (Singh et al., 2016; Magnan et al., 2020; Schipper, 2020). Every adaptation action may be placed 30 along such a continuum reflecting the empirical evidence of adaptation practices and their assessment 31 (Section 17.5). 32 33 [END BOX 17.1 HERE] 34 35 36 17.1.3 Outline of the Chapter 37 38 The chapter is organised around the broad narrative of climate risk decision-making and management 39 (Figure 17.1), building from the assessment of risks within RKRs (Chapter 16) and options available to 40 address these risks and within a broader context of climate resilient development pathways (Chapter 18). 41 Decision-making is considered to be a reflexive and recursive process where different evidentiary threads 42 and information inputs become relevant to the understanding and assessment of factors underlying specific 43 decisions. Additionally, this is also a discursive process, whereby actors and institutions' interpretations of 44 climate risks are also key to these deliberations. 45 46 Do Not Cite, Quote or Distribute 17-11 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Figure 17.1: Schematic representation of the climate risk management decision-making process as introduced in 3 Chapter 1 (Figure 1.6) and the key elements of this Chapter that address additional aspects of this process. In Chapter 4 17, climate risk management (middle box) is framed as the iterative response (i.e., what society could do and how it 5 could be done) to the climate risks described in Chapter 16, with outcomes (ideally reduced risk) that can support (or 6 perhaps hinder) climate resilient development, Chapter 18. Decision makers from diverse contexts sit at the centre of 7 the climate risk decision making process, and interact with and drive these processes as they play out. The main 8 sections of Chapter 17 (bottom panel of boxes) address a wide range of issues (keywords in bottom panel) that manifest 9 at one or more stages of climate risk management processes, illustrated by icons for section numbers and Cross-Chapter 10 Boxes in the interactive risk management process. 11 12 13 Decision-making processes of risk management and adaptation are varied and numerous. Section 17.2 14 assesses the risk management and adaptation options already in practice. Section 17.3 assesses decision- 15 support methods and tools available for application and the effectiveness of these in supporting climate 16 decision-making across degrees of uncertainties and levels of governance and expected reach (scale) across 17 populations from households to international cooperation. Closely interlinked across the decision-making 18 process, are the enabling and catalysing conditions for decisions on adaptation and risk management (section 19 17.4). Section 17.5 synthesizes evidence on maladaptation and adaptation successes, and assesses the current 20 knowledge on M&E of adaptation, including financial accounting, to support learning on those, respectively. 21 Here, M&E is considered distinct from the tracking of financial flows related to adaptation, given that 22 financial accounting does not necessarily provide information on the implementation of adaptation measures 23 and their results (see also Section 17.2.1.2). Finally, in Section 17.6, decision-making, climate risk 24 responses, and their relevance for climate resilient development are presented, where evidence on their 25 respective contributions to facilitate actions in the adaptation solution space within a broader context for 26 development is shown (Chapter 18). Throughout the decision-making process, crucial feedback loops are 27 present that define the results of specific actions and recursive nature of climate risk management and 28 adaptation. 29 30 31 17.2 Risk Management and Adaptation Options 32 33 There has been substantial progress in risk management and adaptation responses around the world, as 34 demonstrated in the sectoral and regional chapters of this report and illustrated in Chapter 16. This section 35 presents an overview of different options available to manage risk, explaining how they are currently Do Not Cite, Quote or Distribute 17-12 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 governed and the extent to which they can be applied around the world. This section contains an assessment 2 of the ways in which different options are being combined to create adaptation portfolios, and describes how 3 incremental and transformational change is starting to be considered. Based on the human dimension of 4 climate change, as described in Chapter 8, vulnerability, inequality, and poverty influence these portfolios of 5 adaptation and transformational change. Particularly for change where residual risks remain that may lead to 6 exceeding the limits of adaptation, increasingly transformational adaptation and policy innovation will be 7 important.17.2.1 assesses options for climate risk management from around the world that reduce, manage, 8 or retain climate-related risks and assesses their contribution to reducing vulnerability and exposure, how 9 they are governed, and the benefits to humans and ecosystems. 17.2.2 presents portfolios of risk management 10 including the design principles and observed variations across the globe, before it discusses the need and 11 potential for transformational adaptation to complement incremental adaptation, for which we present 12 evidence across the report for selected adaptation options and some key risks. The Cross-Chapter Box LOSS 13 in this Chapter synthesises recent literature and assesses key strands of the international dialogue policy on 14 Loss & Damage, concerned with options that help to deal with residual impacts and risks in vulnerable 15 countries. 16 17 17.2.1 Adaptation Options for Climate Risk Management 18 19 This section assesses options for climate risk management (CRM) across common risk settings that have 20 been grouped into Representative Key Risks (RKRs). These risk management and adaptation actions target 21 the components of risk: hazards, vulnerabilities, and exposure associated with sudden or slow-onset events 22 (see Chapter 1 for more details on the definition of risk). 23 24 For each of the RKRs, three commonly discussed adaptation options are identified across the regional, 25 sectoral, and cross-chapters papers of this report. These 24 options have been selected to cover a 26 representative variety of strategies to adapt to climate change, while a particular adaptation option can be 27 relevant to many of the RKRs. For example, the adaptations listed under the RKR of "Food security" are also 28 related to the RKR on "Human health" (Ebi and Prats, 2015). See SM17.1 for more details. The list is not 29 comprehensive of all possible adaptations listed in the regional and sectoral chapters. For example, this does 30 not include adaptations by institutions who might become unable to cope with increasing pace and 31 magnitude of extreme events (see Chapter 11). 32 33 17.2.1.1 Adaptation Options and Their Contribution to Reduce Vulnerability and Exposure 34 35 Table 17.1 provides examples of each of these 24 adaptation options from across AR6 WGII. Detailed 36 information about sectors and regions where these adaptations are being discussed can be found in the 37 indicated chapters. Note that this list is curated to ensure a diversity of options, therefore most of the options 38 will apply to more than one RKR. 39 40 41 Do Not Cite, Quote or Distribute 17-13 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Table 17.1: Selected adaptation options per RKR, with examples of how each option can reduce vulnerability or exposure, or support risk financing. Many of the adaptation options 2 are relevant to multiple RKRs, and have been selected to be representative of the wide variety of adaptation options implemented or suggested around the world. RKR Adaptation option Examples from regional and sectoral chapters and cross-chapter papers Risk to coastal Coastal accommodation Raising of dwellings, raising of coastal roads (15.5.2), amphibious building designs (CCP2), improved drainage (11.3.5.3) socio-ecological Coastal infrastructure Seawalls, beach and shore nourishment (3.6, 15.5.1), breakwater structures (15.5.1), dikes, revetments, groynes, or tidal systems Strategic coastal retreat barriers. (6.3.4.8)., land reclamation (15.5.2) Retreating from coastal areas (3.6, Cross-Chapter Box SLR in Chapter 3, 6.3.5.1, CCP2), relocation/resettlement (CCP2) Restore/create natural areas Marine protected areas (FAQ 3.5), active restoration of coral reefs (3.6.2.3.2), ridge-to-reef management (CCP1), restoring dunes (CCP4), planting salinity-tolerant trees (4.5.2.1) Risk to terrestrial Increasing forest cover (CCP7), detect and manage forest pests (11.3.4.3) and ocean Reduce ecosystem stress Reduce pollution and eutrophication (3.3.3), reduce anthropogenic pressures on the Great Barrier Reef (Box 11.2), sustainable fisheries harvest (3.6.2), increasing connectivity between natural areas (2.6.2) ecosystems Marine habitats to protect against storm surge (3.6), agroecology (5.14.1.1), coastal and marine vegetation and reefs Ecosystem-based adaptation (6.3.3.4), vegetation corridors, greenspace, wetlands (FAQ 6.3), mangrove habitat restoration (8.5.2.2, 9.8.5.1), restoring coasts, rivers, wetlands to reduce flood risk (2.6.3, CCP1), wrban green space to reduce temperatures (2.6.3) Risks associated Infrastructure retrofitting Air conditioning (6.3.4), using thermosiphons for permafrost degradation (10.4.6.4.1), increasing rooftop albedo (for with critical Building codes reflectivity) (11.3.5.3), shading (13.A.4) physical Spatially redirect development Drainage systems (4.5.2.1), architectural and urban design regulations (6.3.4.2), infrastructure standards initiatives (CCP6), infrastructure, Chile's Sustainable Housing Construction Code (12.5.5.3) networks, and services Zoning/land use planning (6.3.2.1), spatial development planning to regulate coastal development (CCP2) Risk to living Insurance Agricultural insurance and micro-credit (4.5.2.1, 10.4.5.5), index-based insurance, market and price insurance (5.14.1.3), standards and Diversification of livelihoods flood insurance (10.5.3.2), collective insurance schemes (12.5.7.5) equity Social safety nets Combining income-generating activities within fisheries sector (3.6.2.2) Community level adaptation by Pangnirtung Inuit through diversification to stabilize income and food resources (CCP6) Food for work programmes (4.5.2.1), school feeding programmes (7.4.2.1.3), social protection programmes, such as unemployment compensation (10.5.6) Availability of health Safe drinking water infrastructure (4.5.2.1), temperature-controlled low-income housing (11.3.6.3), Health care clinics (6.4 infrastructure case study), place-specific mental health infrastructure and "nature therapy" (14.4.6.8) Risk to human Access to health care Access to healthcare services (11.3.6.3), Access to Health, Nutrition Services and Healthy Environments (water and health sanitation) (7.6), enhanced access to culturally-appropriate mental health resources; "Telemedicine" (information technologies and telecommunications for health and public health service delivery) (12.6.1.5) Disaster early warning Early warning of marine heatwaves (3.6.2.3.3) early warning for pests (5.12.5), Heat Action Plans (HAP) (7.4.2.1.2), raising public awareness through campaigns (FAQ13.3) Do Not Cite, Quote or Distribute 17-14 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report Risk to food Farm/fishery improvements Changing fishing gear or vessel power (3.6.2.2.3), change crop variety or timing (4.5.2.1, CCP5, 8.5), close productivity security gaps (5.12.5), biotechnology (5.12.5), irrigation schemes (9.12.5.3), integrated crop/livestock systems (5.10.1), relocating Food storage/distribution livestock linked to improved pasture management (13.5.2) improvements Improve transportation infrastructure and trade networks, shortened supply chains (5.12.5, 9.12.5.3), improved food storage (5.12.5, 7.4.2), local food production/chains (Cross-Chapter Box COVID in Chapter 7) Behaviour change in diets and Reduce food loss and waste (5.12.5), shifts to more plant-based diets (7.4.5.2), creating demand for organically sourced food food waste (10.5.3.2) Water capture/storage Farm ponds and revival of water bodies (4.5.2.1), rain gardens, bioswales or retention ponds (6.3.3.6), water storage tanks (10.5.3.2), multi-purpose water reservoirs and dams (CCP5) Risk to water Efficient water use/demand Precision/drip irrigation (4.5.2.1), Managed Aquifer Recharge (MAR) (9.4), cooperative policies across multiple sectors security (CCP4), changing water consumption patterns (CCP4) Efficient water Constructing irrigation infrastructure (4.5.2.1), inter-basin transfers (6.3.3.6), water reuse (13.A.3), slum/water upgrading supply/distribution (6.4.3) Seasonal/temporary mobility Fishing fleet mobility to follow species distribution (3.6.2.2.2), mobility for seasonal employment and remittances (4.5.2.1, Cross-Chapter Box MIGRATE in Chapter 7), legal/illegal labour migration (CCP3), pastoralist seasonal migrations (Cross- Chapter Box MIGRATE in Chapter 7) Risk to peace and Transboundary fishing agreements (3.6.4.1), ocean governance (3.6.2.2), collective water management (4.5.2.1), indigenous water-sharing systems (4.5.2.1), enforcing the land rights of indigenous populations (CCP7), adaptive co-management in migration Cooperative governance Arctic fisheries (CCP6), international compact on migration (Cross-Chapter Box MIGRATE in Chapter 7), policies for adaptive governance (8.5) Permanent migration Resettlement of flood-prone communities (4.5.2.1), rural-urban migration (6.1 case study), internal migration (Box 10.2), international migration and remittances (8.6.3, 14.4.7.3) 1 2 Do Not Cite, Quote or Distribute 17-15 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Of this list of adaptation options, many focus on reducing vulnerability to climate change (high confidence), 2 as vulnerability is one of the components of risk (see Chapter 1 and Chapter 8). Vulnerability is the 3 propensity or predisposition to be adversely affected, including sensitivity or susceptibility to harm and lack 4 of capacity to cope and adapt (see Chapter 1 for more details). In the world's threatened ecosystems, 5 reducing vulnerability often means reducing other non-climate negative pressures on ecosystems, such as 6 pesticide use or fishery overexploitation (see Chapter 3.3). 7 8 Vulnerability reduction is also a major focus in human systems, and this includes development of 9 investments that help people adapt to climate change. Examples include irrigation or diversifying crops. 10 Building infrastructure resilient to climate-related risks is another example; many of the structural and 11 physical adaptation options can reduce sensitivity to disasters, such as elevating houses or doing beach 12 nourishment in coastal areas (see Section 15.5 in Chapter 15). Extreme events often catalyse investment in 13 adaptation to reduce vulnerability for the future (Kreibich et al., 2017; Slav韐ov� et al., 2021). 14 15 Next to vulnerability reduction, a large number of adaptation options focus on reducing exposure to climate 16 change (high confidence). Selecting low-risk locations is the most basic example of reducing exposure; for 17 example, private companies are relocating factories to reduce flood-related disruptions to their supply chain 18 (Neise and Revilla Diez, 2019) and species are autonomously adjusting their ranges to a changing climate 19 (see Section 2.4). Land use planning or investing in resilient infrastructure can avoid exposure in rapidly 20 urbanizing areas, however, the design and enforcement of these regulations can negatively impact 21 marginalized people (Anguelovski et al., 2016). 22 23 Managed retreat is an example of exposure reduction that, while often controversial, is increasingly being 24 considered and implemented (CCP 2.2.2, Section 15.3.4; Cross-Chapter Box LOSS in this Chapter; Siders et 25 al., 2019). Examples include the US Hazard Mitigation Grant Programme, which, among other activities, has 26 helped people resettle outside of flood zones, and a "no-build zone" established in the Philippines after 27 Typhoon Haiyan (Hino et al., 2017). However, relocation is not always an option; immobility is sometimes 28 involuntary, e.g., in the case of "trapped" populations in Zambia (Nawrotzki and DeWaard, 2018; Section 29 8.2.1.3). 30 31 However, adaptation efforts can have negative impacts on ecosystems and vulnerable groups (high 32 confidence); see Table 17.2 and Section 17.5 for further information on maladaptation. While "hard" 33 structural investments have been popular to reduce exposure to climate extremes, barrier-type measures 34 provide protection only up to a certain limit, and are designed to fail in more extreme events. Given the risk 35 of catastrophe from a climate extreme overcoming a physical barrier, policy advancements in recent years 36 encourage any investment in structural measures to be complemented by "softer" vulnerability reduction 37 measures, such as accommodating building construction (Wesselink, 2016). 38 39 When it comes to "softer" vulnerability reduction initiatives, these were traditionally seen as "no regrets" 40 options for adaptation. However, subsequent studies have cautioned that notion as vulnerability is a dynamic 41 quality, and can be co-created while development or adaptation efforts are being implemented (Schipper and 42 Pelling, 2006; Tempels and Hartmann, 2014; Dilling et al., 2015). Some scholars have suggested the 43 application of a "do no harm" principle to climate change adaptation efforts (Mayer, 2016). 44 45 17.2.1.2 Governance of Adaptation Options 46 47 For each adaptation option identified for the RKRs (Table 17.1), this section presents an assessment of how 48 decisions are made and how the adaptations are being governed. The following section then covers benefits 49 to humans and ecosystems, and potential for maladaptation is covered in section 17.5. See SM17.1 for 50 more information on the assessment methods and underlying citations. 51 52 The following analysis of adaptation options provides a synthesized overview of adaptation globally, but 53 does not prescribe how important each adaptation should be in specific locations. Chapter 16 finds that the 54 "scope" and "speed" of adaptation is limited in many areas. 55 56 When it comes to decision-making, most of these 24 adaptations rely strongly on formal decision-making 57 (high confidence), which follows the procedures of a group of people rather than ad-hoc individual action. Do Not Cite, Quote or Distribute 17-16 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Formal decisions play a particularly strong role in the adaptations identified for infrastructure, early warning 2 systems, and water systems (Kolen and Helsloot, 2014; Calvello et al., 2015; Zhao et al., 2017; Belc醟ov� et 3 al., 2019; Teo et al., 2019). 4 5 In contrast, informal or individual-led decision-making is more common in several food security-related and 6 livelihood related adaptations, such as changes to diets, livelihood diversification and seasonal migration 7 (high confidence) (Li et al., 2017; Radel et al., 2018; Robinson et al., 2020). People who have experienced 8 climate shocks are more likely to take individual decisions to implement adaptation measures, and in 9 countries where people are more exposed to extreme events, autonomous adaptation is more common 10 (Koerth et al., 2017; Aerts et al., 2018b; van Valkengoed and Steg, 2019). 11 12 13 14 Figure 17.2: Governance of 24 major risk management options, grouped by relevance to the representative key risks. 15 Each option depicts the relative governance roles, between communities/individuals, private sector, and public sector. 16 The intensity of the colour refers to the level of confidence in the assessment. 17 18 19 All adaptation options can occur under a range of governance arrangements (high confidence), with cases of 20 either private, public, or community governance typically playing the dominant role, as depicted in Figure 21 17.2. Public governance is the most frequent governance type for most adaptations considered. This is 22 particularly true for social safety nets and spatial planning, where governments are often required to lead 23 adaptation efforts (high confidence) (Mesquita and Bursztyn, 2016; Hssaisoune et al., 2020; Wang et al., 24 2021). While government actors do the day-to-day management of these systems, civil society and 25 international organizations also play a role in shaping agendas and priorities of government actors (Nagle 26 Alverio et al., 2021). 27 28 The private sector plays a large role in governance of insurance, minimizing ecosystem stressors, and 29 livelihood diversification (medium confidence) (Allen et al., 2018; Mimet et al., 2020; Alam et al., 2020a). 30 While having a key role in shaping and implementing many other adaptations, the private sector is not often 31 the governing entity. Do Not Cite, Quote or Distribute 17-17 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 There are a number of adaptation options that tend to be governed by communities and individuals, including 3 adaptations to farming and fishery practices and ecosystem-based adaptations (high confidence) (Reid, 2016; 4 Basupi et al., 2019; Giffin et al., 2020; Karlsson and Mclean, 2020). In rapidly urbanizing areas of Asia and 5 Africa, individual or community-led adaptation is the norm in informal settlements that have poor 6 governance structures. Residents of Mathare slum in Nairobi have established methods to pool risks, such as 7 pooling labour to police looting during flood events and developing community health centres in churches 8 (Thorn et al., 2015). This is in addition to risk reduction measures such as building structures to withstand 9 rising water levels (Thorn et al., 2015). Residents in Bangkok have built walls around settlements, dug 10 informal drainage channels to vacant lots, and filled areas of land (Limthongsakul et al., 2017). In these 11 cases, individual-lead adaptation can have negative side-effects, such as the building of flood defences in 12 affluent communities increasing the flood impacts in less affluent regions of a city (Limthongsakul et al., 13 2017). 14 15 17.2.1.3 Benefit to Humans and Ecosystems 16 17 While some of the 24 adaptation options are specific to certain risk contexts (e.g. coastal areas, agricultural 18 production), others are more widely applicable (e.g. early warning systems, health care systems, 19 creation/restoration of natural areas). Figure 17.3 depicts which of these are most context-specific, e.g. 20 benefitting less than 1 billion people. This is contrasted with the extent to which each adaptation option is 21 beneficial to ecosystem services. Many of the more generalizable adaptations have also been shown to have 22 benefits to ecosystem services, such as nature restoration and changes to diets/food waste (medium 23 confidence). While health care systems and the establishment of health-related infrastructure can be widely 24 used as adaptation options, their design and application to-date have not generally benefited ecosystems or 25 ecosystem services (medium evidence, low agreement). 26 27 28 Table 17.2: Breadth of applicability of each adaptation option benefiting humans, i.e number of people (x axis), 29 estimated by the degree to which each adaptation can be applied across multiple contexts. The benefit of each 30 adaptation option for ecosystems and ecosystem services (y axis). See Annex A for literature underpinning each 31 assessment. This figure uses the 24 representative adaptation options from Table 17.1 and Figure 17.2. Reduce water 32 demand** 33 34 35 36 As a general method related to adaptive management, "early warnings" are the most frequently discussed 37 adaptation option to deal with a changing climate across all key risks, sectors, and regions. Early warning 38 systems are an adaptation that can benefit more than 5 billion people (high confidence). Examples range Do Not Cite, Quote or Distribute 17-18 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 from short-term disaster early warning systems to revision of sea level rise plans based on monitoring. For 2 example, the humanitarian community is investing in forecast-based financing systems to prepare for 3 extreme events (Coughlan de Perez et al., 2015; MacLeod et al., 2021). Forecasts are also used to manage 4 hydropower dams (Ahmad and Hossain, 2020), to trigger interventions before public health emergencies 5 (Chapter 7.4.2) and to alert fishermen of algal blooms in the world's oceans (Chapter 3.6.2.3.3). Table 17.3 6 provides examples of adaptations using early warning systems that have been used to address each of the key 7 risks. 8 9 In addition to immediate investments that reduce vulnerability and exposure, monitoring and early warning 10 systems allow people to take additional actions when there is an imminent event on the horizon (e.g. 11 temporary evacuation during extreme events rather than permanent migration). This allows for ongoing 12 adaptive decision making (Alessa et al., 2016; Ebi et al., 2016; Barnard et al., 2017; Haasnoot et al., 2018). 13 However, these systems are only cost-effective for forecastable and actionable hazards, and require effective 14 institutional governance (Wilkinson et al., 2018; IPCC, 2019c). 15 16 17 Table 17.3: Examples of adaptation investments and early warning system options for adaptive management for each of 18 the key risks in Chapter 16. Key risk Adaptive Early Warning Systems-based measures Risk to coastal socio-ecological systems Storm surge early warnings (15.5.7) Early warnings of water-borne disease (Ch 3.6.2.3.3) Risk to terrestrial and ocean ecosystems Fishery marine heatwave warnings and mobile fishing equipment (Ch 3.6.2.3, 13) Forecast of shifts and regime changes in ecosystems (Pace et al., 2015; Bauch et al., 2016; Burthe et al., 2016). Risks associated with critical physical Early warning for infrastructure and services (Ch 13.2.2.1, infrastructure, networks, and services 10.4.6.4.1) Risk to living standards and equity Adaptive social protection systems (Schwan and Yu, 2018; Ulrichs et al., 2019; Daron et al., 2021). Risk to human health Heat health early warning systems (Ch 7.4.2.1.2) Health and disease monitoring and outbreak prediction (Ch 7.4.2.1.1, Ch 12.5.6) Risk to food security Forecasting rainfall and droughts for seed selection (Ch 10.5.2.2.3), Food price early warnings (Ch 7.4.2.1.3) Risk to water security Early warnings for flood and drought (Ch 4.4.1, 10.5.2.2.3, 15.5.7) Risk to peace and migration Transboundary flood early warnings (Tuncok, 2015). 19 20 21 17.2.2 Combining Adaptation Options: Portfolios of Risk Management and Risk Governance 22 Do Not Cite, Quote or Distribute 17-19 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 While the above assessments underlying Figures 17.2 and 17.3 isolate specific risk management options for 2 specific risks, several adaptation measures are present in any given location, affecting the overall risk of a 3 particular place. Policymakers are charged to evaluate risk comprehensively, deciding on a variety of 4 measures that are effective, feasible, and aligned with other policy goals for a specific place, or 5 implementing a new activity because of how it complements the existing package of risk management 6 activities (Girard et al., 2015). 7 8 17.2.2.1 From Risk Prevention to Risk Financing and Risk Retention 9 10 Portfolios of adaptation options generally include actions to reduce vulnerability and exposure, 11 complemented by risk financing mechanisms that help people avoid the impacts of loss events, particularly 12 very rare ones. There is also explicit or implicit risk retention, where further risk management is not 13 desirable, cost-effective or feasible (Mechler and Deubelli, 2021). Risk financing can include a variety of 14 instruments, with insurance as the most widely known. Formal insurance uptake is less in developing and 15 emerging economies than in wealthier countries (Ali et al., 2020). To overcome some of the barriers to 16 insurance uptake, index insurance has been offered for agriculture and livestock in many developing 17 economies, with varying levels of success (Chantarat et al., 2013; Isakson, 2015; Dewi et al., 2018). In recent 18 years, regional disaster insurance pools for sovereign states have been established, such as the Caribbean 19 Catastrophe Risk Insurance Facility (CCRIF) (Iyahen and Syroka, 2018). Insurance can encourage the 20 quantitative evaluation of climate-related risks and adaptation limits, and it can incentivize risk reduction by 21 charging lower premiums for less risky situations (Sch鋐er et al., 2019). 22 23 While insurance is increasingly accepted as an adaptation option (Linnerooth-Bayer and Hochrainer-Stigler, 24 2015), positive outcomes are not guaranteed (high confidence). First, there are concerns as to whether this 25 will shift responsibility to the most vulnerable people to pay premiums (Surminski et al., 2016). There is also 26 high risk for insurance to cause maladaptation (M黮ler et al., 2017); for example, Annan and Schlenker 27 (2015) showed that insured crops were less well adapted to heat stress. To avoid this, people simultaneously 28 invest in insurance and adaptations that reduce vulnerability/exposure (medium confidence) (Surminski et al., 29 2016; Highfield and Brody, 2017; Sch鋐er et al., 2019; Reguero et al., 2020). 30 31 32 33 Figure 17.3: A graphical representation of layered risk management. Risks can be reduced or managed by risk finance 34 (insurance and other means), but some residual risk remains, particularly for high impact unavoided and unavoidable 35 risk, which is retained implicitly or explicitly. Where incremental and in situ adaptation is not effective in managing 36 risks, transformational adaptation supports systemic change. Risk management occurs in national systems and regional 37 insurance systems have stimulated regional collaboration. Particularly for high impact risks and impacts in specific 38 events, international assistance is required. Policy domains on Disaster Risk Reduction (DRR) and CCA (Climate 39 adaptation) as well as Loss&Damage overlap in their governance of risk management. Figure building on Mechler et al. 40 (2014); Cummins and Mahul (2009); Lal et al. (2012); Mechler and Deubelli (2021). Do Not Cite, Quote or Distribute 17-20 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 3 The combination of interventions that reduce risk and risk finance for residual risk (often through insurance 4 for sudden-onset events, or social protection for risks including linked to slow-onset processes) will reduce 5 collective risk to a certain level. For very extreme and potentially catastrophic events, it is often impossible 6 (or financially infeasible) to fully reduce vulnerability and exposure, and people, communities and countries 7 therefore retain requiring the ex-post management of unavoided and unavoidable residual impacts in case of 8 events. 9 10 Ex-post risk management relies on national assistance, social safety nets (Ch. 7.4.2.1.3; B閚� et al., 2012; 11 Elmi and Minja, 2019), and support from social networks as well as lending from international institutions 12 (high confidence) (Hochrainer-Stigler et al., 2014). Even in places where normalized losses have stabilized 13 in recent years with investments in adaptation, effective planning to manage losses remains necessary 14 (Jongman, 2018). Resilient recovery can support adaptation goals in periods of loss and damage (Slav韐ov� 15 et al., 2021). 16 17 To coordinate between a suite of applicable risk management interventions, the concept of risk layering has 18 been discussed and used in (financial) risk governance for disaster risk management (Mechler et al., 2006; 19 Cummins and Mahul, 2009; Clarke and Mahul, 2011) and climate risk management (Lal et al., 2012; 20 Mechler et al., 2014; Herron et al., 2015; Sch鋐er et al., 2016; Mechler and Deubelli, 2021). Incremental risk 21 prevention and preparedness as well as risk financing occur within national systems. Over the years, regional 22 cooperation, such as through the regional sovereign insurance pools in the Caribbean, Pacific, Africa, but 23 also transboundary risk management elsewhere have become more important (medium confidence) (see 24 Martinez-Diaz et al., 2019). Also, with risks increasingly experienced as severe and existential (Boyd et al., 25 2017), global governance and solidarity have been invoked (see, Linnerooth-Bayer et al., 2019; Pill, 2021), 26 largely as part of the policy discourse on Loss & Damage (Mechler et al., 2019) with further momentum 27 provided by discussions on the global goal of adaptation and recognition of climate risk as transboundary 28 (Benzie and Persson, 2019; Cross-Chapter Box INTERREG in Chapter 16). Transformational risk 29 management has emerged where incremental and in situ adaptation is not effective in managing risks, such 30 as for managed or strategic retreat for communities facing severe coastal and riverine flooding (Siders et al., 31 2019). Transformation has not been well documented including as to its governance (see 17.2.2.5). 32 33 17.2.2.2 Global Variation in Portfolios of Risk Management 34 35 While many studies assess adaptation trends by geographical region or by sector, the amount of residual risk 36 varies across countries with different income and governance structures. Vulnerability, poverty, and 37 inequality, which constitute the human dimensions of climate change, affect how these portfolios of 38 adaptation options are structured around the world (see Chapter 8). Figure 17.4 depicts several illustrative 39 "typologies" of how risk is addressed. While no country or location fits any one typology, this illustrates a 40 range of risk portfolios found in different contexts. 41 42 43 44 Figure 17.4: Several illustrative typologies for how risk has been managed. The first is "extensive protection", in which 45 the bulk of investments are made in reducing exposure, through protection up to limits (e.g. flood levees) and including Do Not Cite, Quote or Distribute 17-21 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 retreat. The second category is "Moderate investment focused on adaptive capacity", in which the bulk of investment is 2 made in reducing vulnerability (e.g. improved housing). The third category is "Little adaptation investment", in which 3 there is little investment in either reducing vulnerability or exposure, and the bulk of risk is residual, borne by the 4 population. 5 6 7 Extensive protection category 8 The first category in this typology, that of "extensive protection", requires substantial financial investment 9 (Figure 17.4). In higher-income contexts, this is often more feasible than in contexts with limited resources, 10 and adaptation investments are more likely to include structural measures to reduce exposure, complemented 11 by vulnerability-reducing measures and insurance protections (medium confidence). While this typology is 12 not universally representative of high-income areas (within or between countries), expensive exposure- 13 reduction measures tend to be easier to implement in high-income countries. For example, flood protection is 14 largest in countries with larger amounts of public spending and least amounts of corruption (Scussolini et al., 15 2016). It is seen as more economically efficient to invest in expensive protection measures in wealthy 16 regions, under different scenarios of sea level rise and river flooding, although these calculations have equity 17 and justice implications (Peduzzi, 2017; Lincke and Hinkel, 2018). After flood events happen in regions with 18 high levels of protection, damages are comparatively limited, and people tend to continue living in close 19 proximity to the protected river (Mard et al., 2018). In contrast, flood displacement is higher in low-income 20 countries (Kakinuma et al., 2020). 21 22 Risk financing, especially insurance, is also common in higher-income countries with well-developed 23 insurance markets and higher levels of insurance penetration than in lower income countries, illustrated by 24 the green bar in Figure 17.4 (high confidence) (Linnerooth-Bayer et al., 2019). Of climate-related disasters, 25 floods and storms cause the largest amount of reported economic losses, however, at least 40% of these 26 losses are uninsured, even in the regions with high insurance penetration (Baur et al., 2018). Government 27 involvement in insurance schemes is associated with higher penetration rates of the general population 28 (Paleari, 2019). While some, predominantly high income countries can make use of disaster contingency 29 funds or dedicated budget items, these do not exist or are not well endowed to adequately support relief, 30 recovery and reconstruction (Linnerooth-Bayer and Hochrainer-Stigler, 2015). To help stabilize public 31 finance in regions with little market-based insurance coverage and fiscal response mechanisms, regional 32 public insurance pools have been set up with donor assistance, e.g., in the Caribbean, Africa and the Pacific 33 for flood and droughts (Sch鋐er et al., 2016; Surminski et al., 2016; Linnerooth-Bayer et al., 2019). 34 35 Moderate investment focused on adaptive capacity 36 In contrast to the "extensive protection" scenario, many regions of the world bear greater resemblance to the 37 second typology in Figure 17.4 "moderate investment focused on adaptive capacity" (medium confidence). 38 These contexts see greater adaptation funding invested in capacity building activities to reduce vulnerability, 39 rather than structural or ecosystem-based protection measures to reduce exposure (Biagini et al., 2014). 40 Because of limited international and domestic finance for large structural investments to reduce exposure, 41 the most prevalent adaptation choices in low-income contexts are household-level vulnerability-reducing 42 measures (Koerth et al., 2017). 43 44 Lack of access to finance can be one of the reasons countries engage more readily in adaptive capacity- 45 building activities. Countries that rank highly on the Corruption Perceptions Index engage less in 46 technological solutions for risk management (Berrang-Ford et al., 2014). In addition, countries with higher 47 levels of corruption receive less adaptation aid (Betzold and Mohamed, 2017; Weiler et al., 2018). Countries 48 are more likely to receive adaptation aid if they import goods from a donor country, or are a former colony 49 of that donor (Betzold and Mohamed, 2017; Weiler et al., 2018). In countries with poor governance and 50 limited aid flows, remittances make up a substantial portion of finance available to the local population for 51 risk management (Samuwai and Hills, 2018). 52 53 Risk financing does play a large role in the "moderate investment" category; there are a variety of 54 instruments in use globally. Many countries in the Global South have created national policies and a number 55 of regional catastrophe risk insurance pools, subsidized by international assistance, which make pay-outs to 56 the national government of affected nations when an extreme event happens and have helped to build risk Do Not Cite, Quote or Distribute 17-22 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 awareness (Clarke et al., 2015; Thirawat et al., 2017). Beyond this, residual risk is often borne directly by 2 affected people (Andrianarimanana, 2015). 3 4 Little adaptation investment typology 5 In the third typology, there are limited resources for adaptation, and populations bear large amounts of 6 residual risk (depicted by the orange bar in the third typology in Figure 17.4, "little adaptation investment"). 7 Small Island Developing States can often find themselves in this situation, because small populations, small 8 economies, lack of economies of scale, subsistence livelihoods, and other challenges mean risk reduction and 9 risk financing are both costly (see Chapter 15). 10 11 Another example of this third typology are people living in conflict-affected areas. These populations are 12 highly vulnerable to the impacts of climate change (Basher, 2006; OCHA, 2011; IPCC, 2012; Zommers and 13 Singh, 2014; Marktanner et al., 2015; Walch, 2018; Eckstein et al., 2019; Peters et al., 2019). In conflict- 14 affected areas similar to the third category of "little adaptation investment", a combination of high 15 vulnerability and relatively few supports for adaptation means that there is a large amount of "residual risk", 16 in which residents cope with the impacts of extreme events on a regular basis (high confidence). For 17 example, deaths from "natural" disasters are 40% higher in areas that are undergoing armed conflict 18 (Marktanner et al., 2015) (see Box 17.2). 19 20 21 [START BOX 17.2 HERE] 22 23 Box 17.2: Climate Risk Management in Conflict-affected Areas 24 25 Consequences of conflict that exacerbate vulnerability to climate change include: displacement, loss of 26 access to employment leading to illegal livelihoods, gender-based violence, lack of land tenure, low literacy, 27 poor access to social and health services, destruction, looting and theft of key assets, such as houses, food 28 stocks and livestock, among others (Jaspars and Maxwell, 2009; Chandra et al., 2017; Anguita Olmedo and 29 Gonz醠ez G髆ez del Mi駉, 2019). Such impacts perpetuate cycles of poverty (World Bank, 2013), making 30 conflict-affected populations more susceptible to suffer from climate related events (Basher, 2006; Coughlan 31 de Perez et al., 2019). For example, in Mindanao, Philippines, poverty is closely linked to long-standing 32 armed conflicts; both climate change and conflict have significantly increased smallholder vulnerability, 33 resulting in loss of livelihoods, financial assets, agricultural yield and the worsening of debt problems 34 (Chandra et al., 2017). In Colombia, displacement induced by conflict has pushed the population to live in 35 high-risk areas such as steep slopes susceptible to landslides and river banks exposed to flooding (Albuja and 36 Adarve, 2011). This conflict-induced vulnerability, with little adaptation activity, has in turn resulted in 37 climate-related disasters (Kuipers, 2019; Siddiqi et al., 2019). 38 39 Conflict can also limit the effectiveness of adaptation measures that do exist; a study across Africa, the 40 Caribbean, and Asia concluded that poor governance can limit the effectiveness of early warning systems in 41 these regions (Lumbroso et al., 2016). Poor state services have health consequences and can limit social 42 support networks (Peters, 2018). States are unable (even if they are willing) to assist or protect citizens in 43 disasters. Non-governmental stakeholders play a large role in these contexts, but questions of long-term 44 implications and accountability remain unaddressed (Peters, 2018). 45 46 Climate risk management and adaptation in conflict-affected contexts is challenging, first, given the complex 47 and dynamic nature of vulnerability (Hilhorst, 2003; Frerks et al., 2004) and second given factors such as 48 weak or nonexistence disaster risk governance, restricted access, human rights violations, power dynamics 49 between parties in conflict, and environmental degradation, among others (Kloos et al., 2013; Marktanner et 50 al., 2015; ICRC, 2016; Quinn et al., 2017; Field and Kelman, 2018; Siddiqi, 2018). Climate can also be a 51 contributing factor to conflict (Mach et al., 2019). There is little peer-reviewed documentation available on 52 adaptation in climate-affected contexts, and what exists is narrowly focused on agriculture at the expense of 53 other sectors, such as cities, infrastructure, and humanitarian operations (Sitati et al., Accepted). 54 55 To address risks to livelihoods, conflict-sensitive livelihood programming has used vouchers to meet 56 immediate needs, legal support to resolve land disputes, and disaster preparedness planning to identify safe 57 places for displacement (Jaspars and Maxwell, 2009). For example, cooperation in the Philippines between Do Not Cite, Quote or Distribute 17-23 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Moro Islamic Liberation Front and United Nations agencies included training of farmers in disaster risk 2 reduction, drought management, and production of improved crop varieties to support a transition away from 3 subsistence farming (Walch, 2018). In Mali, negotiations on fertilizer access and safe transport to 4 agricultural lands were brokered by the International Committee of the Red Cross, and in Afghanistan, 5 conflict-sensitive approaches have promoted ecosystem-based adaptation to support reforestation (Walch, 6 2018; Mena and Hilhorst, 2020). Despite several examples of conflict-sensitive adaptation practices, little is 7 known about the effectiveness of such efforts in reducing climate risks in these complex contexts (see 8 Section 17.5 for further discussion of "effectiveness"). 9 10 [END BOX 17.2 HERE] 11 12 13 17.2.2.3 Adaptation Beyond Risk: Exploiting Opportunities 14 15 Several studies and many government planning documents reference how people can benefit from a changed 16 climate, beyond reducing risks. For example, several regions are expecting an increase in visitors to eco- 17 tourism sites or national parks with a changing climate (Fisichelli NA, 2015; Lwasa, 2015). In Europe, 18 several national adaptation plans include planning for potential benefits of a changing climate, including 19 reduced winter mortality and improved conditions for hydropower (Biesbroek et al., 2010). Recognizing the 20 need for economic diversification, people working in certain industries, such as coastal management, 21 perceive climate change as a factor increasing the need for their services (Fatori et al., 2017). Northern 22 countries are taking advantage of ice-free waters for shipping routes in the Arctic (Eguiluz et al., 2016; Melia 23 et al., 2016; IPCC, 2019e-a). In Africa, opportunistic adaptation has been observed by smallholder farmers, 24 who plant crops that are better suited for a changing climate (Lalou et al., 2019). Similar agricultural 25 adaptation in Pakistan has been associated with improved food security and reduced poverty (Ali and 26 Erenstein, 2017; Rahman et al., 2020). In each of these cases documenting benefits, there are also potential 27 negative impacts on other populations or ecosystems, such as ecosystem impacts from increased Arctic 28 shipping (Ng et al., 2018). 29 30 While adaptation is rarely focused on taking advantage of opportunities presented by a changed climate, 31 there are numerous co-benefits of adaptation opportunities, from health to reduced emissions to ecosystem 32 services (high confidence) (Watts et al., 2015; Geneletti and Zardo, 2016; Spencer et al., 2016). There is also 33 literature proposing that the actual process of adaptation planning can enable people to take advantage of 34 opportunities, including, e.g., opportunities for larger policy and governance reform (Coleman and Sandhu, 35 1965; Ernst and Preston, 2017; Brown et al., 2017a). 36 37 17.2.2.4 The Spectrum from Incremental to Transformational Adaptation [Or Maybe Measures] in Risk 38 Management Portfolios 39 40 Chapter 1.4.5 noted that transformational adaptation is increasingly being considered necessary to allow a 41 system to extend beyond its (soft) limits as incremental adaptation cannot guarantee to avoid intolerable 42 risks. Chapter 16.4 presents evidence on RKRs where a need for transformational adaptation and climate risk 43 management has been identified in order to further reduce climate risks and avoid breaching adaptation 44 limits. The following section identifies how the 24 adaptation options representative of the RKRs may 45 support incremental and transformational risk management/adaptation that can lead to small, medium, and 46 large systemic change, often as part of portfolios of options. This subsection further discusses the role of 47 transformational adaptation vis a vis incremental adaptation by reviewing evidence across chapters (see also 48 Box 17.3). The Cross Chapter Box on Loss and Damage further expands on the international debate 49 regarding the role of decision-making on incremental and transformational adaptation for dealing with 50 residual risks to address soft as well as hard adaptation limits (see Cross-Chapter Box LOSS in this Chapter). 51 52 As the literature distinguishes active transformation to shape future risks from passive and unintended 53 transformation (Lonsdale et al., 2015; Chapter 1), the section queries how to inspire actors to consider how 54 to develop or implement transformational adaptation to complement incremental adaptation/risk 55 management when and where appropriate. 56 Do Not Cite, Quote or Distribute 17-24 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 In contrast to a broadening literature on conceptualization and policy proposal, there has been little evidence 2 reported in the literature of transformational adaptation and risk management at scale of implementation 3 (high confidence) (Klein et al., 2017; Ajibade and Egge, 2019; T郻ara et al., 2019; Mechler and Deubelli, 4 2021). Deubelli and Venkateswaran (2021) review evidence on largely NGO -implemented community-level 5 adaptation for floods, heat and drought across the globe. They suggest that transformational adaptation 6 success, while multi-facetted and challenging, depends on the availability of appropriate enabling 7 environments including experiential and niche learning, alignment of transformational change objectives 8 with strategic (government or other actor's) priorities, strong bottom-up governance grounded in local 9 contexts, phased long-term program support and appropriate financing. 10 11 In order to distinguish incremental from transformational adaptation, Lonsdale et al. (2015), building on 12 Mustelin and Handmer (2013), identify criteria related to framing, learning and decision-making, space and 13 time, power, and type of change management. T郻ara et al. (2019), additionally, discuss transformation in 14 light of informing climate pathways, strategies and solutions. Broadly considering these criteria, they 15 identify twelve dimensions with additional discussion of change with regard to systems and dynamics, 16 options and solutions, agency, and the consideration of equity (see also Chapters 1, 6, 18 for more 17 discussion). In particular, the following key aspects for understanding the spectrum from incremental to 18 transformational adaptation are of relevance: change - within or across the system; agency-single or 19 heterogenous, a role for visioning and normative futures, the type of learning required (from first order, 20 business-as-usual, to second order), as well as how equity and distributional issues are explicit. 21 22 Applying these key aspects to the list of 24 adaptation options from Table 17.1, certain options are assessed 23 to be more transformational, often requiring large system changes that go beyond addressing individual risks. 24 Adaptations that are more transformative offer potential to lead to systemic change. Less transformative 25 adaptations allow people to address specific climate-related risks while maintaining existing systems (See 26 SM17.1 for more details; see also Box 17.3). 27 28 For example, several adaptations related to the RKR on risks to peace and migration, namely permanent 29 migration, and cooperative governance, require moderate to high levels of transformation (high confidence). 30 Some behavioural adaptations, such as changing diets and reducing food waste, can also require large 31 transformations in land use and food culture (medium confidence). Spatial planning, including urban zoning, 32 also tends to be more transformative (medium confidence). 33 34 On the other end of the spectrum, disaster early warning systems tend to be incremental rather than 35 transformational (high confidence), because they enable people to maintain/protect existing systems. Several 36 other adaptations allow people to maintain livelihoods and systems in the face of changing risks. For 37 example, improvements in agricultural and fishing practices can be done with moderate transformation to 38 systems (medium confidence). Similarly, insurance tends to require less transformation, as it can allow 39 people to maintain existing systems while being more resilient to climate-related shocks (medium 40 confidence). 41 42 None of the 24 adaptation options are consistently beneficial for vulnerable and marginalized groups (high 43 confidence). For each adaptation, there are examples of how it has been implemented in a way that benefits 44 poor, low-income, ethnic groups and/ or females, and other examples of implementation in different contexts 45 that have worsened the risks for those groups specifically. For example, while the goal of cooperative 46 governance can be to support the marginalized, these same marginalised groups are usually excluded from 47 participating in the design of the solutions, and many articles criticise governance results as protecting only 48 the interests of the wealthier and more powerful parties in the negotiations, especially in governance of 49 migration (Groutsis et al., 2015; Pijnenburg et al., 2018). This reinforces the need for context-specific 50 planning to ensure marginalized groups will benefit from an adaptation plan. See Table 17.4 for examples of 51 how each adaptation option can have or not have equity benefits. 52 53 54 Table 17.4: The 24 adaptation options from Table 17.1 grouped and coloured by their potential for transformation. (See 55 Appendix A for assessment methodology.) Adaptations in red tend to require small amounts of transformation, 56 adaptations in orange tend to require middling levels of transformation, and adaptations in yellow tend to require large 57 levels of transformation, or systemic change. Each option is paired with examples of how that adaptation can be done in 58 a way that does not benefit, or worsens the situation for marginalized groups, as well as an example in which that Do Not Cite, Quote or Distribute 17-25 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 adaptation has benefitted those groups. Examples of equity focus on benefits to poor, low-income, ethnic groups, or 2 females. 3 * low confidence, ** medium confidence, *** high confidence Example of the adaptation excluding or worsening the situation for marginalized Example of the adaptation benefitting Adaptation groups marginalized groups Less transformation (small systemic change) Index-based insurance policies in Mongolia The availability of capital after disaster were accessible primarily to wealthy herders events can avoid a poverty trap from Insurance** (Taylor, 2016b). disasters (Alam et al., 2020a). Accommodation strategies in Jakarta have led The mosaic restoration project provided to a false sense of security in an impoverished training for women to support local Coastal and vulnerable neighbourhood (Esteban et al., accommodation of climate changes on Yap accommodation*** 2017). (Krishnapillai, 2018). Early warning People of higher socio-economic status tend Famine and drought early warning systems systems*** to receive warnings, while marginalized have helped avoid starvation among the groups can be left out (Baudoin et al., 2016). world's most vulnerable people (Funk et al., 2019). Small farmers were unable to access supports Retrofits for water use efficiency were made to implement drip irrigation in Morocco, and available free of charge to low-income uptake was greater among wealthy farmers communities in the US (Lee and Tansel, Water use/demand*** (Jobbins et al., 2015). 2013). Construction of hard barriers increased flood Successful coastal embankments can help risk for several low-income communities in people avoid poverty traps in Bangladesh by Coastal hard protection** Bangladesh (Adnan et al., 2020). reducing exposure to flood events (Borgomeo et al., 2017). Moderate transformation (medium systemic change) Infrastructure Low-income people often do not own their Energy policy could promote solar retrofitting** homes, and there are few incentives for infrastructure in Nigeria, which can offer landlords to upgrade (Tardy and Lee, 2019). electrification in underserved regions (Ohunakin et al., 2014). Building codes in Nepal and Bangladesh Slum upgrading projects in Latin America often fail to increase resilience because many reduced the vulnerability of informal buildings are built informally (Ahmed et al., settlements by improving built infrastructure Building codes*** 2019). (Nez Collado and Wang, 2020). Farm/fishery practice** Many agriculture improvement strategies Improved crop varieties have supported the create higher workloads for women and do income of low-income farmers in Zambia not directly enfranchise them, as seen in (Khonje et al., 2015). Uganda, Ghana, and Bangladesh (Jost et al., 2015). Diversification of Diversifying livelihoods can increase A study on diversity of income sources in livelihoods* women's workloads, in a review of semi-arid Ghana indicated that diversification can Do Not Cite, Quote or Distribute 17-26 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report regions across Africa and Asia (Rao et al., make people less vulnerable to extreme 2020). events (Baffoe and Matsuda, 2017). Social safety nets** Social protection systems in Bangladesh focus Adaptive social protection can help poor on specific groups in rural areas, and they people avoid the impact of extreme events often fail to reach urban poor and other very by scaling up support at critical moments disadvantaged people (Coirolo et al., 2013). (Bowen et al., 2020). Infrastructure for The development of sanitary water Improvements to water and sanitation health*** infrastructure in Germany had less benefit in infrastructure that avoid people fetching areas with higher income inequality water is associated with improvements to (Gallardo-Albarr醤, 2020). women's health (Geere and Hunter, 2020). Increasing/improving livestock markets can Investments in large produce storage houses Food favour high-income livestock producers has supported indigenous livelihoods in the storage/distribution** (Gautier et al., 2016). face of climate change (Mugambiwa, 2018). Restoration/creation of Urban greening programmes in the US Afforestation reduced landslide risk for natural areas** avoided minority neighbourhoods or caused informal settlements in Brazil (Sandholz et displacement of people of colour al., 2018). (Anguelovski et al., 2016; Watkins et al., 2016). Minimizing ecosystem Fish quota reduction had negative economic South Africa's Working for Water stressors* impacts when done quickly (Barbeaux et al., programme employed poor people to control 2020). invasive species (van Wilgen and Wannenburgh, 2016). Ecosystem-based Payments to indigenous groups in return for Integrated water resource management is adaptation** protecting conservation land can be less than proposed in the Caribbean as a way to their original livelihoods and disadvantage maintain ecosystem services while those not receiving the payments, such as improving economic welfare (Mycoo, women (Bedelian and Ogutu, 2017). 2017). Water tariffs during the Cape Town drought City Water Forums in Nepal have focused Water negatively impacted poor households on equitable water allocation as an supply/distribution** (Millington and Scheba, 2021). adaptation (Pandey and Bajracharya, 2017). Seasonal/temporary Women tend to have greater restrictions on Indigenous communities in Guatemala use mobility** mobility than men (Lama, 2018). temporary migration to manage rainfall variability (Ruano and Milan, 2014). Most transformation (largest systemic changes needed) Spatial planning in American cities has often resulted in less green space in ethnic minority While difficult, strategic approaches to neighbourhoods (Connolly and Anguelovski, urban planning can promote inclusive Spatial planning** 2021) development (Chu et al., 2017). Diets/food waste* Low-income groups have less opportunity to Changing dietary intake during heatwaves diversify diets if certain foods become more (e.g. eating cooler foods) is seen as a low- expensive or difficult to obtain (Reynolds et cost adaptation accessible to low-income al., 2019). people in the UK (Porter et al., 2014). Health care systems** Facilities in poor communities are often Universal health coverage can be highly poorly sited and can lack capacity to support beneficial to poor people (Atun et al., 2015), Do Not Cite, Quote or Distribute 17-27 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report people during climate-related extreme events when needed for climate-related health (Codjoe et al., 2020). outcomes. Many indignous populations have been negatively affected by loss of their land when Improving water harvesting supports displaced for dam construction (Siciliano and marginalized populations in dryland areas Water capture/storage** Urban, 2017). (Bobadoye et al., 2016). Cooperative International cooperation among national International cooperation has the potential to governance** governments regarding migration can remove barriers to adaptation in informal encourage human rights abuses and increase settlements in developing countries by migration (Crawley and Skleparis, 2018). sharing knowledge and expectations (Oberlack and Eisenack, 2014). Permanent migration from small island Migration supported by social protection nations can entail a loss of identity for systems can be sustainable for poor Permanent migration*** indigenous groups (Bordner et al., 2020). populations (Schwan and Yu, 2018). Strategic coastal Muslim people faced tensions with host In several cases of post-disaster relocation, retreat*** communities when relocated in India, and community members initiated the retreat faced difficulties in terms of fishing access and there were broader benefits to society and land size (Mortreux et al., 2018). (Hino et al., 2017). 1 2 3 17.2.2.5 Incremental and Transformational Adaptation for Managing Risk in the Context of Adaptation 4 Limits 5 6 With evidence on soft and hard limits being experienced in natural and human systems including in 7 terrestrial, aquatic and marine ecosystems, coastal and island systems, agriculture, health systems, urban 8 spaces and tourism (Table 16.5, 16.4.2, medium confidence) transformation is also being considered to 9 expand the adaptation space beyond soft limits and before hard limits are being reached. As a key area of 10 advancement since AR5, this section assesses the relationship of residual risks, limits and incremental as 11 well transformational adaptation integrating the assessment of limits in 16.4 with ch.17 adaptation and risk 12 management assessment along a spectrum of adaptation change. 17.2.2.5 thus contributes to understanding 13 in which systems and regions transformational adaptation is increasingly required and considered once 14 incremental adjustments are exhausted in the context of soft and hard limits. 15 16 Assessing risk and limits requires in-depth analysis of the adaptability of human and natural systems under 17 different warming and risk levels, also considering socio-economic exposure and vulnerability drivers, 18 informed by perspectives on what breaching limits means, especially if significant change and losses and 19 damages may occur (see 16.4, 8.4). Assessments differ between natural systems (where adaptation potential 20 is often very limited; Klein et al., 2014) and human systems where incremental and transformational 21 adaptation can help to extend soft limits so that hard limits are not met or to buy time until hard limits are 22 reached with higher levels of warming. 23 24 The assessment synthesises global and regional evidence across regional and thematic report chapters along 25 a continuum from observed to projected impacts and risks, the spectrum of incremental and transformational 26 adaptation, and finally any evidence on soft and hard limits. We present regional evidence for two types of 27 salient natural and human systems and Representative Key Risks: RKR-B (risk to terrestrial and ocean 28 ecosystems), where we assess risks from marine heatwaves to coral reefs; and RKR- E (risk of heat on 29 human health as a human system). Both RKRs and systems are facing substantial (residual) risk, 30 characterised by adaptation limits and share heatwaves as the hazard, for which climate change has been 31 considered the major driver of increasing intensity and frequency (high confidence)(IPCC, 2021). The 32 assessment synthesises evidence on transformation as reported in the chapters as well as categorizes 33 identified adaptation options along an adaptation spectrum according to the criteria discussed in 17.2.2.4, Do Not Cite, Quote or Distribute 17-28 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 specifically whether adaptation leads to systems' change or only change within a system, is driven by multi- 2 scale agency and considers equity impacts specifically. 3 4 Figure 17.5 organises global and regional findings for observed and projected health risks from heat (RKR- 5 E) from chapters across the report and organizes options according to findings on the potential for 6 transformational change as presented in17.2 and table 17.4. The discussion shows that heat has become a 7 significant health risk globally, incurring severe mortality and morbidity in all world regions with annual 8 heat related deaths estimated around ~300 000 with millions affected (high confidence) (9.3.1). Evidence 9 shows that adaptation and risk management, can be effective in reducing (relative) risks in developed 10 countries, with inconclusive evidence in low-middle incomes states (9.2.4.1, 13.7.3, 13.6). In absolute terms, 11 risk in terms of heat-related mortality and morbidity is projected to increase under medium and high heating 12 scenarios in many regions, even with implemented adaptation. By 2050 (compared to 1961-1991 and for a 13 mid-range emissions scenario), an excess of 94,000 deaths per year is projected globally as attributable to 14 climate change (9.3.1). 15 16 Planned and implemented adaptation interventions in all regions have remained largely incremental, while 17 uptake is being intensified in some regions; options have included air conditioning (as autonomously 18 deployed), public cooling spaces, heat action plans that incorporate early warning and response and heat- 19 adapted building design (9.9.5, 11.3.6, 12.5.6.1.1,13.11.3, 13.11.3, 15.6.2). 20 21 Given increasing risks projected and already reported soft and hard limits, transformation is being considered 22 as a complement potentially leading to systemic and transformational change. Adaptation, if upgraded to also 23 consider transformational interventions, will thus help to reduce heat risks (medium-high confidence, limited 24 evidence) albeit with reduced effectiveness at higher levels of warming, particularly in regions (Africa, Asia) 25 where lethal heat waves are projected to occur almost annually towards later in the 21st (medium confidence) 26 (9.1, 10.4.7). 27 28 This may involve urban redesign using nature-based solutions (such as green roofs and infrastructure) as 29 well as rescheduling of outdoor labour or cross-sectorial coordination. Integrated approaches across 30 interdependent systems (e.g. ecosystem- based approaches and climate-sensitive urban design) are being 31 proposed. Also, it may mean bolstering social safety nets and health systems that better attend to heat 32 impacts by providing universal coverage. Societal and political transformations to reduce climate change 33 risks for vulnerable groups are considered particularly relevant in some regions (9.4.2.1.2, 9.9.5, 10.4.6.4.3, 34 12.5.3.2, 13.6.2.1, 14.6). Yet, across all regions there is limited evidence on proposed transformational 35 adaptation and very little evidence regarding implementation (high confidence). 36 37 As a consequence, studies project soft limits to be further reached as increased mortality and morbidity will 38 add stress to health systems, and labour productivity will be severely hampered impacting economic systems 39 (medium to high confidence) at medium to higher levels of global warming (7.2.4.1, 9.10, 10.4.4.4, 11.9.1, 40 13.6.2.3, 13.7.2, 13.7.4, 13.10.2.1, 13.8, 15.3.4.9). 41 42 Hard limits may be breached in some regions where critical heat tolerance thresholds are projected to be 43 surpassed at medium to higher levels of global warming, such as physiological survivability thresholds, 44 which, e.g., may render urban outdoor labour in Asia, Africa and North America infeasible (10.4.6.3.2, 14.8, 45 Box 9.1). 46 47 Do Not Cite, Quote or Distribute 17-29 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 R贩� KROPIn-rbEcosr:jeeeRmrcivtseeeknddttoiramilshkapusdamactpastnahtieoanltchomfropmlemheenatted N� oHrigthh America have increased E穟7r0op0e00 and 54 000 deaths during 2003 and 2010 A� sSihaort-term effects of high temperatures on temperatures mortality and morbidity (**** ) with heatwaves, adaptation actions have reduced heat- daily mortality and morbidity reported in impacts varying by age, gender, related mortality in parts of Southern Europe (***) several cities throughout Asia. location, and socioeconomic � Risk of heat mortality and morbidity to more than � More frequent hot days and intense heat- by conditions (**** ) triple at 3癈 compared to 1.5癈 with projected waves will increase heat-related risks and 贩� Transformational adaptation � Warming projected to increase heat- 90'000 deaths in 2100 (***) deaths in Asia (**) Soft limit (to incremental adaptation) related mortality (**** ) and � Air cooling, heat warning and response systems, � Urban technological solutions (e.g. smart Hard limit morbidity (**) building interventions, but largely incremental cities, early warning systems);and � Air conditioning&cooling stations adaptation (***) behavioural adaptation growing from � Transformational, long-term � Increasing use and plans for NBS in urban spaces; initial stages but unevenly distributed adaptation action to increase large scale system transformations needed due to across large and small cities (**) resilience such as through redesign of adaptation limits in Southern Europe (**) involving � Transformational adaptation largely Global urban space (***) strong behavioural change combined with large lacking, some incipient in larger cities, incl. � Available (incremental) adaptation portfolios of preventive and planning options NBS � Heat is a significant health risk due to options unable to protect human � Above 3癈 limits to the adaptation potential of � Heat stress likely to approach critical widespread urbanization, demographic changes and increase in hot weather (***) health under high-emission scenarios people and existing health systems, particularly in health thresholds in West and South Asia (***) Southern and Eastern Europe and with health under medium warming scenario, and in 323,000 estimated heat-related deaths and 13 � Hard limits to adaptation may be systems under pressure(***) some other regions such as East Asia under million heat-related DALYs in 2019 � Temperature-related mortality expected to reached for rural and urban outdoor high warming (***) labor towards end of century (**) increase under medium and high heating scenarios even with adaptation. By 2050 (compared to 1961-1991) an excess of 94,000 A� uHsetarat-lraesliaated deaths have increased with a deaths per year attributable to climate change projected due to heat for medium warming. � Implementation of heat warning systems has third attributable to climate change in Australia (***) reduced relative mortality risk in developed � Increase in heat-related mortality and countries (***), unclear trends in low-middle income countries. Multi-sectoral integrated morbidity for people and wildlife in Australia (***) approach beneficial incl. heat early warning � Urban cooling, education to reduce heat and response systems targeting vulnerable groups (***) stress, heatwave early-warning systems, Longer term building standards that improve � urban planning and design, insulation/cooling. Current levels of including Nature based solutions (NBS) to reduce urban heat island effects. Improved adaptation largely incremental and reactive inconsistent with rising risks (*** ) basic protection for outdoor work incl. work 贩 NBS and well-resourced primary health care rescheduling to cooler times of the day (***) Fundamental limits include thermal threshold, � Some regions with heat stress conditions A� fCrliicmaate variability impacting the health of some individuals and communities are already approaching upper limits of labour tens of millions of Africans through exposure productivity (***) to extreme heat. Heat extremes (hot days reaching their psycho-social adaptation limits Thresholds of survivability (***) � approached (***) and hot nights) increased in frequency since WG I Detection and attribution statement 1980 (***) 贩 Hot extremes (including heatwaves) have � Increasing temperatures will cause tens of Small Islands thousands of additional deaths under become more frequent and more intense moderate and high global warming scenarios, across most land regions since the 1950s (*****) particularly in North, West and Central Africa � Disproportionate health risks associated with Human-induced (***) � climate change is the main � Cooling stations, limited evidence of pro- changes in temperature. Heatwaves cause injuries driver of these changes (***) and deaths � Every additional 0.5癈 of global warming C贩 eHSniegtanratiflsictaarnendstsSinaocuhrteehaaslAtehms cienorniicncaeternns(i*ty*,*) active climate change adaptation in African � Heat-related mortality and risks of occupational heat cities, (***) causes clearly discernible increases in the � Urgent need for improved societal and stress in small island states projected to increase with intensity and frequency of heatwaves (*** ) higher temperatures. Higher temperatures also can frequency and duration of heatwaves political transformations to reduce climate affect productivity of outdoor workers. (***), strong increases in heat-related change risks for vulnerable groups (**). � Limited evidence reported. early warning mortality in urban areas Deployment considered necessary of NBS and Focus on early warning and response systems; integrating climate services into � with demonstrated health, ecological, health decision-making systems; public uptake and surveillance systems for heat waves; economic and social co-benefits. Confidence: political, institutional, and financial � Morbidity and mortality will escalate with � buy in; improving health data collection systems * low barriers limit feasibility to date (***) further global warming, placing additional � No evidence if transformational adaptation. ** medium � NBS proposed to be combined with strain on health and economic systems (***) Reduced habitability of small islands through a *** high Under high warming scenarios annual compounding of key risks including from heat-related **** very high community engagement and � health stress for warming of 1.5 � degrees (***) ***** virtually certain integration of diverse knowledge to exceedance of deadly heat thresholds in foster transformational adaptation North, West and Central Africa (***) � No limits for health risk discussed 2 3 Figure 17.5: Understanding the spectrum of incremental to transformational planned adaptation for managing climate 4 related heat risk to health including associated soft and hard adaptation limits (RKR-E). Evidence from regional and 5 thematic chapters. The figure from the WG I Atlas shows the change in extreme hot days (above 35oC) across regions 6 for a medium-term scenario and medium global warming relative to 1850-1900. See table SI 17.2.2.5 RKR E. 7 8 9 Marine heatwaves have affected tropical coral reefs, which are analysed as part of RKR-B (see SM17.4). 10 Coral reefs across the tropic have recently seen massive bleaching events (such as for the Great Barrier reefs) 11 (very high confidence) Risks are projected to be further exacerbated by increases in intensity, frequency and 12 duration of marine heatwaves (high confidence) as well as impacts from extreme events such as tropical 13 cyclones (low to medium confidence) (3.4.2). 14 15 Although there is some evidence of autonomous natural thermal adaptation, as indicated by the presence of 16 stress tolerant symbionts adapted to higher thermal thresholds observed in the Persian/Arabian Gulf. Yet, 17 there is low confidence (with limited evidence, low agreement) that enhanced thermal tolerance can be 18 maintained over time (Ch.3 Box 5) as the adaptability in natural system is considered very limited and risk 19 are driven by water temperature. Evidence suggests that already at further warming of 1.5C coral reefs are 20 put at large risk (very high confidence) (3.4.2.1). 21 22 Planned adaptation can help to buy some limited time including through recovery and restoration efforts that 23 target resistant coral populations and interventions to culture heat-tolerant algal symbionts as well as by 24 setting up marine protected areas. Under higher warming levels, transformation has been proposed as 25 possibly complementing available management approaches with high-risk interventions, including enhanced 26 corals and reef shading, which may help to sustain some coral reef systems beyond 1.5癈 of global warming. 27 Modelling has shown, however, that the effectiveness of such high-risk interventions declines beyond 2癈 of 28 global warming (Figure 3.23, 3.4.2.1) (medium confidence). 29 30 Already for limited warming beyond 1.5癈 for mid-century with increasing intensity and frequency of 31 marine heatwaves hard limits are projected to become manifest in terms of widespread decline and loss of 32 structural integrity (very high confidence) (3.4.2.1), including for the two largest such systems, the Great 33 Barrier Reef and the Mesoamerican coral reef (11.3.2, Box 11.2, Table 11.14, 12.4). 34 35 In terms of planned adaptation options that would provide benefits to populations, evidence suggest these are 36 very limited, uncertain and bring along substantial risks to people, culture and ecosystems (3.5.2. Cross- 37 Chapter Box SLR). Concurrent with the loss of coral reefs important ecosystem services, including to Do Not Cite, Quote or Distribute 17-30 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 fishery, tourism and coastal protection would be lost. Transformational adaptation, while requiring to make 2 difficult choices, is being discussed to help overcome soft limits through livelihood diversification for 3 alternative income sources, assisted migration and planned relocation of communities dependent on the 4 services provided by the reef ecosystem (medium confidence) (3.5.2). 5 6 7 [START CROSS-CHAPTER BOX LOSS HERE] 8 9 Cross-Chapter Box LOSS: Loss and Damage 10 11 Authors: Reinhard Mechler (17), Adelle Thomas (16), Christian Huggel [MR1] (12), Emily Boyd (8), 12 Veruska Muccione (13), Ivo Wallimann-Helmer (CA), Laurens Bouwer (CA), Sirkku Juhola (CA), Chandni 13 Singh (10), Carolina Adler (17), Kris Ebi (7), Patricia Pinho (8), Rawshan Ara Begum (1), Adugna Woyessa 14 (9), Johanna Nalau (15), Katja Frieler (16), Richard Jones (WG I), Riyanti Djalante (8), Rosa Perez (18), 15 Tabea Lissner (4), Anita Wreford (11), Mark Pelling (6), Francois Gemenne (8), Nick Simpson (9), Doreen 16 Stabinsky (WG III) 17 18 An intensifying dialogue 19 20 This Cross-Chapter Box offers an assessment of the growing literature on Loss & Damage. Capitalised letter 21 `Loss and Damage' (L&D) has been used to refer to political negotiation under the UNFCCC. Research has 22 used lowercase `losses and damages' for residual effects from (observed) impacts and (projected) risks (see 23 Glossary). 24 25 Dialogue around L&D issues started with a proposal for insurance and compensation by the Alliance of 26 Small Island States (AOSIS) (INC, 1991) and has intensified over recent years with suggestions made to 27 consider complements to adaptation in order to manage residual impacts and risks `beyond adaptation' in 28 vulnerable developing countries (1.4.5). L&D was formally recognized in 2013 at COP19 through the 29 Warsaw International Mechanism on Loss and Damage (UNFCCC, 2013), governed by an Executive 30 Committee (ExCom), to advance knowledge, foster dialogue as well as enhance action and support. Article 8 31 of the Paris Agreement provided a permanent legal basis for the WIM (UN, 2015). 32 33 IPCC's first assessment of L&D in 2018 found residual risks to rise with further global warming leading to 34 soft and hard adaptation limits in some natural and human systems (e.g., coral reefs, human health, coastal 35 livelihoods (Roy et al., 2018). Sections 8.4.5.6, 16.4 and 17.2 corroborate these findings concluding that, 36 depending on mitigation and adaptation pathways residual risks in key systems in many regions will create 37 potential for negative impacts beyond adaptation limits (medium confidence). The assessment in 2018 also 38 noted that there is "not one definition of L&D." This ambiguity has persisted and a policy space for L&D has 39 not clearly been delimited (high confidence). There is, however, coalescence in dialogue among academia, 40 civil society and policy around a distinct set of themes as identified by stakeholder surveys as well as 41 literature, methods and evidence reviews (Vanhala and Hestbaek, 2016; Boyd et al., 2017; Mechler et al., 42 2018; Calliari, 2019; McNamara and Jackson, 2019): risk management, limits to adaptation, existential risk, 43 finance and support including liability, compensation and litigation (8.3, 16.4; medium confidence; Figure 44 Cross-Chapter Box LOSS.1). Various advisory groups have been set up with participation of policy and 45 experts from research, civil society and practice to help inform the implementation of WIM workplans (UN, 46 2015; UN, 2019). 47 48 Do Not Cite, Quote or Distribute 17-31 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Figure Box Cross-Chapter Box LOSS.1: Charting out the L&D discursive and policy space. The figure shows key 3 discursive strands relevant for L&D including their interrelationships with and distinction from adaptation. The figure 4 also identifies expert groups set up under the WIM and showcases the scale of responses discussed, a focus on ex ante 5 risk management and ex post attention to losses and damages as well as contributions by climate change and other 6 stresses for the themes. Adapted from Boyd et al. (2017) and building on Vanhala and Hestbaek (2016), Mechler et al. 7 (2018), McNamara and Jackson (2019), and Calliari (2019). 8 9 10 Risk management 11 12 An increasing body of research has focussed on the role of climate risk management (8.3; 16.4 and 17.2; 13 high confidence) (Birkmann and Welle, 2015; Gall, 2015; van der Geest and Warner, 2015; Mechler and 14 Schinko, 2016; Boyd et al., 2017; IPCC, 2018b; IPCC, 2019b; Boda et al., 2020; Broberg and Romera, 15 2020). A technical advisory group on comprehensive risk management (TEG CRM) advises the WIM 16 ExCom while other expert groups focus on slow-onset events and non-economic L&D (UNFCCC, 2019a). 17 18 There is evidence that, without strong risk management and adaptation, losses and damages will continue to 19 affect the poorest vulnerable populations potentially creating poverty traps (high confidence) (8.3; 8.4.5.6 20 and Table 8.7; 17.2; Serdeczny, 2019; Tschakert et al., 2019; Thomas et al., 2020). Research has started to 21 develop global inventories on losses and damages including on intangible effects (Tschakert et al., 2019; 22 Otto et al., 2020) and engaged with the practice community for data collection. Practice has provided 23 guidance to report on losses and damages in countries' (I)NDCs (WWF & Practical Action, 2020). Yet, 24 systematic risk assessments of climate-related losses and damages including adaptation limits (see, e.g. Leal 25 Filho and Nalau, 2018; Robinson, 2018) have remained scarce (16.4; high confidence). Thus many 26 vulnerable countries lack comprehensive data at scale of risk management including on economic (e.g. loss 27 of livelihood assets and infrastructure), and non-economic losses and damages (e.g. culture, health, 28 biodiversity) thus hampering effective risk management (Thomas and Benjamin, 2018; Martyr-Koller et al., 29 2021; Singh et al. 2021). van den Homberg and McQuistan (2019) propose a losses and damages inventory 30 also to be used to monitor how technologies may shape risks as well as adaptation limits. While early 31 warning and other risk reduction options as well as risk retention considerations are being discussed, L&D 32 dialogue has strongly focussed on risk finance for residual risks, particularly through the donor-supported 33 provision of public insurance systems (Linnerooth-Bayer et al., 2019; Sch鋐er et al., 2019; Broberg and 34 Romera, 2020; Nordlander et al., 2020). 35 36 Transformation 37 Do Not Cite, Quote or Distribute 17-32 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 The role of transformation in risk management for overcoming any soft limits to adaptation is seeing 2 emerging attention (medium confidence, limited evidence), and the TEG CRM has also been tasked to 3 consider transformation. Relocation and retreat of assets and communities, where in situ adaptation is 4 considered impossible, is increasingly being debated in research and practice, including in terms of finance 5 and L&D implications (8.4.4; Boston et al., 2021; Desai et al., 2021; Mach and Siders, 2021; van der Geest 6 and van den Berg, 2021; Zickgraf, 2021). Livelihood transformation occurs where current livelihoods 7 become unfeasible in the face of multiple climatic and non-climatic stressors (8.3.4.1) requiring change 8 within sectors (such as switching from cropping to livestock rearing (Escarcha et al., 2020) or across sectors, 9 when farming households relocate to offer labour elsewhere (9.1; Rasel et al., 2013). Biermann and Boas 10 (2017) suggest revamping global governance systems to effectively address the protection and voluntary 11 resettlement of those displaced by climate variability and change. A WIM taskforce on displacement is 12 tasked to further advise on human mobility, including migration, displacement and planned relocation 13 (UNFCCC, 2019a). 14 15 The existential dimension 16 17 There has been less and often implicit discussion on the existential dimension of climate-related risk as 18 pertaining to L&D (medium confidence).McNamara and Jackson (2019) infer an existential dimension from 19 notions of inevitability and irreversibility associated with migration and relocation of communities 20 (Eckersley, 2015; Mayer, 2017; McNamara et al., 2018), socio-cultural impacts linked to glacial retreat (Jurt 21 et al., 2015), as well as adverse psychological and intersubjective effects (Herington, 2017; Adams et al., 22 2021). Many SIDS in their NDCs refer to sea level rise in particular posing existential threats, and call for 23 enhanced international support for L&D (Thomas and Benjamin, 2017). 24 25 Finance and support 26 27 International support and finance, including compensation for losses and damages, have been in the spotlight 28 from the beginning of the dialogue (high confidence), starting with AOSIS' proposal (INC, 1991). Recent 29 work has focussed on finance sources, such as solidarity-based donor and other support for experienced 30 losses and damages and climate-induced displacement as well as questions of compensation and litigation 31 (Roberts et al., 2017; Gewirtzman et al., 2018; Mechler and Deubelli, 2021; Robinson et al., 2021). A 32 selection of finance options has also been explored such as donor-supported insurance systems with built-in 33 risk reduction provisions (Gewirtzman et al., 2018) as well as roles for social protection (Aleksandrova and 34 Costella, 2021). International policy and donors have provided technical assistance for insurance-related 35 options such as (Insuresilience Global Partnership, 2018). 36 37 As national and donor-related funding for impacts and risk management remains limited (Sch鋐er and 38 K黱zel, 2019; 17.2; Serdeczny, 2019) even at current global warming, many highly exposed developing 39 countries remain financially constrained in their capacity to attend to residual impacts and risk management 40 needs (Linnerooth-Bayer and Hochrainer-Stigler, 2015; Roberts et al., 2017; UNEP, 2021a) (high 41 confidence). Discussion on options for the risk retention layer `beyond adaptation" are likely to see further 42 attention as the dialogue proceeds. 43 44 Although there is no explicit mandate regarding L&D, about a quarter of the Green Climate Fund's approved 45 projects explicitly refer to L&D while 16% of projects have thematic links to L&D across their main project 46 activities (Kempa et al., 2021). Any estimate of L&D finance needs and spending, however, remains highly 47 speculative, as long as its exact remit including in relation to adaptation has not been clarified politically 48 (medium evidence, high agreement) (Markandya and Gonz醠ez-Eguino, 2019). 49 50 Liability and compensation, implying legally defined reimbursement of losses and damages attributable to 51 climate change, remain contentious in L&D dialogue (high confidence). In half of the academic and grey 52 literature surveyed by McNamara and Jackson (2019), compensation is mentioned. Studies have laid out 53 responsibility principles, such as historical responsibility based on the polluter pays principle, beneficiary 54 pays, as well as ability to pay. Discussions on compensation are closely linked to justice and equity 55 scholarship which has studied compensatory, distributive and procedural equity considerations for burden 56 sharing (Roser et al., 2015; Wallimann-Helmer, 2015; Huggel et al., 2016; Boran, 2017; Page and Heyward, Do Not Cite, Quote or Distribute 17-33 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2017; Roberts et al., 2017; Shockley and Hourdequin, 2017; Wallimann-Helmer et al., 2019; Garcia-Portela, 2 2020). 3 4 Litigation and liability are linked and a growing research body has examined the role of litigation and 5 international law for the L&D context finding that litigation risks for governments and business may increase 6 as the science, particularly on attribution matures further (Mayer, 2016; Banda and Fulton, 2017; WGI 7 CWGB Attribution, 8.2.1.2); Marjanac and Patton, 2018; James et al., 2019; Simlinger and Mayer, 2019; 8 Wewerinke-Singh and Salili, 2019; Toussaint and Martinez Blanco, 2020) (high agreement, medium 9 evidence). 10 11 Outlook 12 13 The WIM has been reviewed twice as to its delivery on its key functions. As an outcome of the second 14 review in 2019, an expert group on Action and Support has been set up to further discuss issues pertaining to 15 finance, technology and capacity-building and a Santiago Network for Technical Assistance will be 16 established to consider providing technical support directly to developing countries (UNFCCC, 2019b). 17 Overall, the L&D dialogue under the WIM supported by an increasing body of research has made important 18 advances with regard to the two functions of knowledge generation and coordination; however, less so on 19 action and support (medium confidence) (Calliari et al., 2020). Resolution on the last item will need 20 additional attention as, despite the coalescence of themes, the L&D dialogue continues to proceed across 21 interlinked yet contested discussion strands. 22 23 [END CROSS-CHAPTER BOX LOSS HERE] 24 25 26 17.3 Decision-making Processes of Risk Management and Adaptation 27 28 AR5 (Chambwera et al., 2014; Jones et al., 2014; Klein et al., 2014; Kunreuther et al., 2014; Mimura et al., 29 2014) represented a significant step forward in focusing attention on how decision-making may facilitate 30 effective and robust responses to climate risks remaining after mitigation measures have been taken, 31 following recognition of these needs in AR4, including the diverse contexts that face decision-makers (Klein 32 et al., 2007). 33 34 AR5 (Jones et al., 2014; Kunreuther et al., 2014) recognised that the decision-making procedures are as 35 important to consider in managing risks as are the options for responding to climate change, mostly because 36 the procedures can themselves constrain the choices of actions, which could, in turn, lead to constrained 37 pathways which are undesirable. It emphasised the importance of iterative risk management because risk 38 and adaptation are dynamic. It also identified that (i) risk assessments, decision-support tools, early warning 39 systems, accounting for uncertainty and delivering no-regret options by examining trade-offs are important, 40 (ii) integration across different governance portfolios is needed due to potential conflict of different actions 41 between portfolios, and (iii) planning, implementation and decision-making, including the use of methods, 42 are dependent on local context. 43 44 Since AR5, the IPCC special reports have provided assessed the value of integrated assessment processes for 45 assessing trade-offs and synergies (IPCC, 2018a), adaptive management and governance, the roles of formal 46 and informal decision making (IPCC, 2019b), and the importance of developing policy and governance 47 options for risk management, including managing disasters, enhancing resilience, addressing decision- 48 relevant uncertainties, and being prepared for abrupt change and extreme events (IPCC, 2019c) 49 50 Chapter 16 has shown that climate risks vary greatly from small to large, local to regional, uncertain to 51 deeply uncertain. The plethora of risks means there are many types of decisions, and many forms of 52 analyses and processes that may be drawn on. Decisions can differ according to whether they are strategic, 53 tactical or operational; whether there are one or many decision makers, from a domestic setting to national 54 governments; the level of uncertainty present; the time available to take the decision; and many more factors 55 (Chapter 1; Section 17.1). 56 Do Not Cite, Quote or Distribute 17-34 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 The pathway to a decision may not be linear, depending on when and in what detail the decision-making or 2 consultative group may need to be understanding the climate risk and its real world context (sense-making, 3 modelling), has sufficient background to analyse and explore options for ameliorating the risk (analysis, 4 exploration), or is ready for interpreting the analyses and deciding on the requirements and strategies for 5 implementing a chosen strategy (interpretation-implementation) (high confidence) (Figure 17.6; French et 6 al., 2020). The development of decision-support tools for climate risk management (Palutikof et al., 2019a; 7 Palutikof et al., 2019b) and more generally (Papathanasiou et al., 2016) along with archives of experiences 8 from practitioners (Watkiss and Hunt, 2013; Section 17.5; Bowyer et al., 2014; French, 2020a) means that 9 some aspects of the decision-making process can be circumvented or at least streamlined as that experience 10 is re-used (high confidence). 11 12 No single approach to decision making best suits an individual climate risk across any adaptation context 13 (Richards et al., 2013), although there is now a greater awareness of the methods and approaches that are 14 available and their requirements for best practice (Hurlbert et al., 2019) (high confidence). This section aims, 15 firstly, to assess the factors that people responsible for organising and facilitating decision-making may wish 16 to consider in choosing the methods and approach for them to make decisions in their context. It also 17 assesses existing experience in analysing the utility of methods for climate risk decision-making. The 18 second part then assesses progress in integrating decision-making across a portfolio of risks. 19 20 Processes and methods to facilitate decision-making, from problem recognition to implementing a solution, 21 have evolved in many contexts, disciplines and applications over the last century (high confidence). As a 22 result, decision-making terminology has a vast number of synonyms that are not compiled here. For clarity, 23 the term `decision-analytic methods' refers to procedures or tools that may be used by decision-makers to 24 help develop, analyse and contrast alternative actions/adaptations; `approaches' refers to processes that may 25 be undertaken by decision-makers to facilitate the development of proposed actions/adaptations; `decision- 26 support tools' refers to software or procedures that facilitate the use of knowledge and data (Papathanasiou et 27 al., 2016). 28 29 30 31 32 Figure 17.6: Relationships between different processes of decision-making to manage climate-related risks in the real 33 world, noting that, when appropriate, some aspects may only require experience to be re-used. 1. Formulation of risks 34 of concern and accompanying policies and objectives for managing those risks, forming prescriptive models for the 35 decision maker. 2. Knowledge, understanding and observations of the real world are used to assess past and current 36 impacts and future risks using descriptive models, based on the perspectives and prescriptive models arising from (1). 37 If not well formulated from other experience, processes in (1) and (2) interact to make sense of the world and what Do Not Cite, Quote or Distribute 17-35 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 needs to be done. In iterative management, (1) and (2) also form the basis for monitoring, reviewing, and evaluating 2 effectiveness of adaptations. 3. Use of decision-support and decision-analytic tools to appraise costs and benefits of 3 different options for ameliorating future risks. The double-headed arrow indicates where two-way interactions occur 4 between different activities (likely to be iterative, feedback and non-linear processes) � modelling and assessments are 5 repeated and revised in tandem with the planning and evaluation of options, based on interactions with the policy- 6 makers and stakeholders. 4. The decision-maker, which may be a group of people, interacts with the evaluation of 7 options (two-way interaction) and interprets the efficacy of the options and the implications for the real world, 8 ultimately choosing one or more actions to satisfy the policy objectives to manage the risks. 5. Implementation of the 9 actions in the real world, which may be once-only actions or instigation of a feedback management system that enables 10 ongoing adjustments to meet objectives. 11 12 13 17.3.1 Decision-analytic Methods and Approaches 14 15 Different classes of decision-analytic methods have been variously presented in IPCC reports since AR4 but 16 without a summary assessment of their capacity to deal with different contexts of the decision maker. 17 `Communities-of-practice' are developing tool-boxes to support analysing and making of decisions generally 18 (French, 2020a). These communities of decision analysts can act like broad-based statisticians to advise on 19 matching methods to the climate risk and its context, before individual decision specialists are consulted. 20 Some scientific literature is presenting guides for choosing different methods, tools and approaches (Shi et 21 al., 2019). This sub-subsection provides a summary guide for policy analysts and decision-makers to help 22 identify the classes of decision-analytic methods that may be suitable for their context for managing climate 23 risks. It focuses on decision-analytic methods, noting that decision-support tools will underpin many of these 24 methods by organising information (Bourne et al., 2016; Papathanasiou et al., 2016; Ceccato et al., 2018; 25 Ha遝 and Kind, 2018) or support modelling (Papathanasiou et al., 2016; Kwakkel, 2017; Gardiner et al., 26 2018), sometimes with a particular decision-analytic process in mind (Hadka et al., 2015; Torresan et al., 27 2016; Tonmoy et al., 2018). 28 29 17.3.1.1 Factors to Consider in Selecting Methods to Facilitate Decision-Making 30 31 The choice of methods and approaches to decision-making for climate risks (next section) will depend on (i) 32 the cognitive needs of the deliberations, otherwise considered to be the phase in developing a decision, (ii) 33 the types of models and modelling available to facilitate the deliberations, (iii) the degree of uncertainty 34 surrounding the choices, and the (iv) context of a choice (high confidence) (Richards et al., 2013; Jones et 35 al., 2014; Shi et al., 2019; French, 2021). 36 37 17.3.1.1.1 Cognitive phases of decision making 38 The decision process often involves overlapping and iterative development of the components leading 39 toward a decision, resulting in the blurring of stages but involving different phases of cognitive activity 40 (Figure 17.6; Holtzman, 1989; French, 2015; French, 2020a). Framing the problem (Orlove et al., 2020), by 41 modelling its relationships with the human and natural systems and eliciting objectives, values and scope of 42 the problem from stakeholders, is a precursor to analyses of options but may be returned to whenever a phase 43 of `sense-making and modelling' is required (high confidence) (Ackermann, 2012; Keeney, 2012; Slotte and 44 H鋗鋖鋓nen, 2014; Abbas and Howard, 2015; Marttunen et al., 2017; Korhonen and Wallenius, 2020; 45 French, 2021). 46 47 The cognitive phase of 'analysing and exploring' uses models and existing data and/or knowledge services 48 as available to explore the relevance/efficacy of adaptations to ameliorate risk or to meet other adaptation 49 objectives, as well as possible flow-on effects of those actions (Section 17.3.1.4). Sensitivity and robustness 50 analyses can be useful if conditions are favourable to supplement the decision analysis, setting bounds on 51 some of the residual uncertainty (high confidence) (Borgonovo and Plischke, 2016; Ferretti et al., 2016). 52 Validation of models and verification of data (Tittensor et al., 2018) are becoming highlighted as important 53 steps in this phase or in the sense-making phase, particularly in their capacity to understand and test 54 decision-makers and stakeholders' perceptions (medium confidence). Randomisation methods, Bayesian 55 methods, interval methods, MCDA, DMDU and economic and financial approaches (e.g., Real Options 56 Analysis) are tools of choice in this phase (high confidence) (Table 17.5) (Abbas and Howard, 2015; 57 Bendoly and Clark, 2016; Borgonovo and Plischke, 2016; Iooss and Saltelli, 2017; Korhonen and Wallenius, Do Not Cite, Quote or Distribute 17-36 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2020; Saltelli et al., 2020). Decision-support tools in the provision of data and/or modelling methods are 2 regularly used in this and the sense-making phase (high confidence) (17.3.1.2). 3 4 The phase of interpreting the analyses to make decisions on climate adaptation followed by implementation 5 are the least described in the literature (Figure 17.7). Decision process management tools and methods for 6 communicating choices, outcomes and implementation are expected to be used to provide support in this 7 phase, particularly for understanding whether the advice is fit-for-purpose, and the efficacy of choices are 8 clear (low confidence) (Spetzler et al., 2016). 9 10 17.3.1.1.2 Types and capacity of models to support decision making 11 `Descriptive models' of socio-biophysical systems and their responses to different drivers (Argyris and 12 French, 2017; French and Argyris, 2018; Saltelli et al., 2020) and `prescriptive models', which capture the 13 beliefs, values and objectives of decision-makers and stakeholders (Parnell et al., 2013; Keisler et al., 2014; 14 French and Argyris, 2018), provide the foundations of sense making (high confidence) and thereby 15 influencing the options and choices available in the phase of analysis and exploration (medium confidence) 16 (Gorddard et al., 2016). 17 18 Socio-biophysical models may be qualitative network models, statistical models or dynamic mathematical 19 models (Melbourne-Thomas et al., 2017). Qualitative network modelling can help assess the nature and 20 consequences of the interactions, as well as facilitating understanding of possible structures to be used in 21 dynamic models for assessing long term adaptation options (Reckien et al., 2013; Reckien, 2014; Reckien 22 and Luedeke, 2014; Symstad et al., 2017). These approaches help articulate the direct and indirect effects of 23 fixed, long-term engineering or structural adaptations. Dynamic stochastic modelling (Fulton and Link, 24 2014; Ianelli et al., 2016) has been used to assess short to medium term interactions of more dynamic and 25 variable sectors, such as those with annual adjustments and management of water, agriculture, land and 26 marine uses (Holsman et al., 2019; Hollowed et al., 2020; Bahri et al., 2021). On a longer timeframe, 27 scenarios are used to test long term interactions but often with less variability and chance (Giupponi et al., 28 2013; Adam et al., 2014; Rosenzweig et al., 2017). 29 30 Many sensitivity analyses based on scenarios, including procedures to randomise across model uncertainty, 31 relate to descriptive dynamic mathematical models with the user of the models characterised as an objective 32 observer (Borgonovo and Plischke, 2016; Ferretti et al., 2016; Symstad et al., 2017; French, 2020a). 33 Bayesian approaches enable these descriptive analyses to take account of the subjective choices in model 34 construction and implementation (Abbas and Howard, 2015; Sperotto et al., 2017; J鋑er et al., 2018; 35 Sperotto et al., 2019; French, 2020a). Organising descriptive analyses and deciding on a suitable option 36 across a diversity of opinions amongst stakeholders use prescriptive processes, which can be supported with 37 prescriptive modelling tools (Williamson and Goldstein, 2012; Gelman et al., 2013; Abbas and Howard, 38 2015; Dias et al., 2018; Phan et al., 2019; Hanea et al., 2021). These approaches are subjective, in that they 39 are constrained or directed by the particular views and emphases of the decision-making group (Gorddard et 40 al., 2016). Not all tools are appropriate for all these activities. 41 42 Decision-makers will be better able to choose decision-analytic methods when they have an understanding of 43 the types, scale and breadth of uncertainties around the climate risk (high confidence) (Symstad et al., 2017). 44 The Cynefin framework (Snowden, 2002; French, 2013) is a policy-driven framework that broadly 45 categorises the decision context of uncertainty within which decision makers and policy analysts may find 46 themselves (medium confidence) (Hurlbert et al., 2019; Helmrich and Chester, 2020). As Cynefin has helped 47 frame previous IPCC presentations on contexts of uncertainty (Hurlbert et al., 2019) and has a community of 48 practice to consult on its use (French, 2020a), it is used here, also because it considers the uncertainty in 49 knowledge around cause and effect in general terms, rather than specifically focussing on uncertainty in 50 formal models. Helmrich and Chester (2020) show how Cynefin can be used to frame climate adaptation 51 decision making in the infrastructure sector. 52 53 The Cynefin contexts relate to how well the system is understood for knowing precisely the outcomes of 54 actions that may be taken - range from known, knowable, complex to chaotic. If a context is known or 55 knowable, then it will be possible to build sophisticated models and make sound predictions. If the context is 56 complex and chaotic the outcomes of actions will be less predictable, no matter how complex the models 57 may be, although more complex dynamic models may be useful to test `what if' scenarios in these cases Do Not Cite, Quote or Distribute 17-37 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 (Marchau et al., 2019). Under complex and chaotic circumstances an ensemble of models and approaches 2 may be needed to help categorise a satisfactory `solution space' across the broad knowledge of relationships 3 and dependencies, but will need to have iterative processes to update and refine adaptations as knowledge 4 improves (Marchau et al., 2019). 5 6 17.3.1.1.3 Uncertainty and attitudes to risk 7 Uncertainty does not just relate to what might happen given climate drivers or adaptations, but also about 8 how much one values potential consequences (Butler et al., 2016; Beven et al., 2018a; Cross-Chapter Boc 9 DEEP; Beven et al., 2018b; French, 2020a) (high confidence); the balance between how particular decision 10 analyses address uncertainties relating to the external world (descriptive models) and those relating to the 11 values driving the decision making (prescriptive models) is important (Butler et al., 2016). Some analyses 12 partially ignore uncertainties relating to the former in order to focus on conflicts in the values held by 13 different stakeholders and help structure debate (Korhonen and Wallenius, 2020; French, 2020a), while 14 others build very sophisticated models of the external world to predict potential consequences, but in doing 15 so lose transparency and risk becoming untrustworthy black boxes to many stakeholders (low confidence) 16 (Peterson and Thompson, 2020). 17 18 Much of the readily-available literature on how uncertainties affect decision-making relates to the 19 uncertainty in the biophysical models, with a recognition that the choice of tools will be influenced by the 20 types of uncertainty to be addressed (Le Cozannet et al., 2017; Symstad et al., 2017; Beven et al., 2018a; 21 Beven et al., 2018b; Durbach and Stewart, 2020b; French, 2020a). While terminology varies amongst 22 disciplines, three types of uncertainty are important in understanding assessments of the future from 23 descriptive models � epistemic (uncertainty in model construction relating to the lack of knowledge about 24 the system being represented), analytic (the degree to which a model fits observations, and its accuracy), and 25 stochastic (the natural variability or randomness in the system). The probability of an event arising in the 26 future is determined from all three uncertainties, noting that stochastic uncertainty is a property of the system 27 rather than a limitation of research (Le Cozannet et al., 2017; Beven et al., 2018a; Beven et al., 2018b). 28 29 Uncertainty in what constitutes a risk of concern is increasingly identified as important to consider when 30 managing risk (Chapter 16; Butler et al., 2016; Prober et al., 2017; French et al., 2020; Reis and Shortridge, 31 2020). The uncertainty here arises from what is an acceptable risk. Acceptability relates to the value or 32 importance of the consequence, which may include moral and ethical uncertainties (Prober et al., 2017), as 33 well as how ambiguous the understanding of the consequence may be between different groups (Beven et al., 34 2018a; Beven et al., 2018b). The development of strategies to ameliorate risk will benefit from considering 35 these two uncertainties in specifying the risk to be managed (Prober et al., 2017; French et al., 2020) because 36 they can help set boundaries on a required likelihood of success, rather than simply casting stakeholders or 37 decision-makers as risk averse or risk tolerant, and can help identify and accept pathways of success 38 (Gregory et al., 2012). This can be important when decisions need to be made well in advance of the actions 39 needing to take effect, such as for many climate risks (Chapter 1; Chapter 16; Section 17.2.3; Cross-Chapter 40 Box DEEP in this Chapter). 41 42 Elicitation methods help reduce these uncertainties (high confidence) (Butler et al., 2016; Prober et al., 2017; 43 Symstad et al., 2017; Beven et al., 2018b). In addition, informal decision processes can assist in developing 44 consensus in approaches and outcomes (Orlove et al., 2020). 45 46 17.3.1.2 Decision Analytic Methods Used in Decision-Making and Climate Risk Management 47 48 Entities making decisions (countries, regions, organisations and individuals) select methods that best suit 49 them in their context (F黱fgeld et al., 2018; Shi et al., 2019; French, 2020a) (high confidence). 50 Classes of tools (Watkiss and Hunt, 2013; French, 2020a) include Bayesian methods, Interval methods, 51 decision making under deep uncertainty (DMDU; see Cross-Chapter Box DEEP in this Chapter), cost- 52 benefit analyses, multicriteria decision analysis, elicitation and general decision support tools (Table 17.5). A 53 summary guide for policy analysts and decision-makers is presented in Table 17.5 to help identify the classes 54 of decision-analytic methods that may be suitable for their context for managing climate risks. The table 55 summarises how well the methods address the Cynefin context, phase of decision making, the types of 56 uncertainties that exist through the decision-making process and the resources required. As terminology may 57 vary between disciplines and research groups, suitable references to better explain the methods within the Do Not Cite, Quote or Distribute 17-38 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 class are provided. Also, there may be overlap between the classes as individual methods are often paired 2 with other methods to address specific requirements and approaches (Buurman and Babovic, 2016; Haasnoot 3 et al., 2019). In that respect, these methods are referred to in the next section discussing advances in the 4 different approaches to managing climate risks. 5 6 Case studies in Table 17.5 describe the utility of classes of decision-analytic tools to facilitate decisions 7 about climate adaptations (SM 17.2). These case studies are presented in Figure 17.7 according to the type of 8 decision-making body and mapped according to their contribution to a decision outcome relative to the 9 geopolitical scale of the actions being assessed. The effectiveness of these methods and tools in Table 17.5 in 10 the context of climate change adaptation (Box 17.1) has yet to be evaluated. 11 12 13 Table 17.5: Characteristics of the main approaches to decision analysis with respect to their Cynefin context, the 14 manner in which they can be used to address different uncertainties, where they may be used in different cognitive 15 phases of the decision-making process, the resources required, and some case studies for further exploring how they 16 might be used. Numbers in square brackets after references in Case Studies refer to the references plotted in Figure 17 17.7. Bayesian Methods (Keeney and Raiffa, 1993; Smith, 2010; Gelman et al., 2013; Reilly and Clemen, 2013; Abbas and Howard, 2015; Sperotto et al., 2017; Marchau et al., 2019) A structured approach to assembling information around the consequences of choices, either by modelling, analysis of multiple scenarios or by structuring deliberation; Underpinned by a theoretical base, coherent assumptions and powerful computational methods; Can use both observational data and expert knowledge, weighting them appropriately; Same approaches as in Artificial Intelligence algorithms. Biases (information, stakeholders, decision- makers) can be made explicit. Traditionally, Bayesian methods computationally identify an `optimal' decision, based on maximising the expected utility across a number of specified requirements, represented as functions. Examples include the general application of decision network models (Richards et al., 2013; Sperotto et al., 2017), the use of decision network analyses based on elicitation to choose adaptations to coastal management in a lagoonal area in Italy (Catenacci and Giupponi, 2013) and coastal community in UK (J鋑er et al., 2018); combination of economic models and decision models to assess research and development priorities (Baker and Solak, 2011); combining outputs from models, observations and opinions in a decision framework for assessing climate impacts on water nutrient loads in Italy (Sperotto et al., 2019) and a general review for water resource management (Phan et al., 2019); combining results from different dynamic models to assess human mortality from ozone in the USA (Alexeeff et al., 2016), assessing adaptive capacity of surf lifesaving in Australia (Richards et al., 2016), and assessing urban flood risks in Denmark (舠tr鰉 et al., 2014). Cognitive Phase Resources required Case Studies Sense-making and Analysing and Interpreting and Implementing Modelling Exploring Construction of Bayesian updating Use of graphical Bayesian decision (Alexeeff et al., 2016) [1], (舠tr鰉 hierarchical models, and expected utility models (decision trees, analytic models can be et al., 2014) [2], (Baker and Solak, belief nets (Sperotto analysis, belief nets and applied with increasing 2011) [3], (Catenacci and et al., 2017; Phan et supplemented by influence diagrams) complexity and Giupponi, 2013) [4], (J鋑er et al., al., 2019), decision robustness and and sensitivity plots sophistication to any 2018) [5], (Phan et al., 2019) [6], trees (Keeney and sensitivity analyses can help make given problem. (Richards et al., 2013 )[7], Raiffa, 1993) and (Rios Insua, 1999; transparent and explain Coherence between (Richards et al., 2016) [8], influence diagrams Rios Insua and reasoning for strategy different levels of (Sperotto et al., 2017) [9], (Keeney and Raiffa, Ruggeri, 2000; to stakeholders and sophistication can be (Sperotto et al., 2019) [10] 1993; Reilly and French et al., 2009; implementers (Bendoly maintained. Thus, the Clemen, 2013), Smith, 2010; Reilly and Clark, 2016) and resources can be tailored supplemented by and Clemen, 2013; provide for auditable to the time and support many soft elicitation Abbas and Howard, building of consensus. available for the techniques help build 2015). analysis. The most models for sophisticated analyses quantitative analysis are computationally (Gelman, 2003; demanding. Bendoly and Clark, 2016) Do Not Cite, Quote or Distribute 17-39 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report Uncertainties Ambiguity Cynefin context Knowable Complex Chaotic Value Known Stochastic, (Prescriptive Epistemic, Modelling) Analytical (Descriptive Modelling) All can be Uncertainties Any stochastic Epistemic More exploratory Formal uncertainties modelled resolved or reduced uncertainties updated via analysis (Gelman, modelling Bayesian probabilistically, by discussion, then modelled statistics/machine 2003) to impossible. learning, then perhaps values modelled by probabilistically; remaining understand Much stochastic supplemented by multi-attribute otherwise, uncertainties behaviours with exploratory modelled sensitivity values and utilities deterministic probabilistically. less complex work to identify Full Bayesian analysis (Rios (Keeney, 1992; modelling with decision modelling Bayesian potential causes possible (French et Insua, 1999; Keeney and Raiffa, sensitivity al., 2009; Smith, modelling and effects. 2010; Abbas and Rios Insua and 1993; Gregory et analysis. Value Howard, 2015). support by Little if any Ruggeri, 2000; al., 2012). Residual functions tend to sensitivity and complex Iooss and uncertainties be used more than robustness analysis. Saltelli, 2017). explored via utility functions studies (Rios Deep sensitivity analysis. (Keeney and Insua, 1999; uncertainties can Raiffa, 1993; French, 2003). be investigated Goodwin and Scenario focused via scenarios Wright, 2014). decision analysis (French, 2020a). to cope with deep uncertainties (French, 2020a). Careful deliberations to construct values and utilities. (Keeney and Raiffa, 1993; Gregory et al., 2012). Decision-making under deep uncertainty (DMDU) (Hallegatte et al., 2012; Weaver et al., 2013; Marchau et al., 2019; Workman et al., 2021) Deep uncertainty relates to circumstances in which data are too sparse, experts in too much disagreement or time is too short to model the uncertainty. As such, DMDU methods are focused on working in the Cynefin Complex Space context. Approaches emphasise robustness ("no regrets" options) and the use of scenarios, and often link well with scenario-focused robust Bayesian studies (Cross-Chapter Box DEEP in this Chapter). DMDU studies draw in many other approaches to decision analysis, using them to identify robust rather than optimal strategies, as in Robust Decision Making (RDM). DMDU analyses can help decision makers to think contingently and build a more wide- ranging recognition of the risks. They often integrate with other classes of tools. Examples include RDM for hydro-power design using down-scaled climate data in sub-Saharan Africa (Taner et al., 2017), RDM for water management in California, USA (Lempert and Groves, 2010), the Colorado River, USA, and for international climate investment strategies (Groves et al., 2019), use of decision-scaling (Brown et al., 2019), comparison of RDM and Info-gap methods (Hall et al., 2012) and review of using climate modelling in RDM (Weaver et al., 2013). Cognitive Phase Resources required Case Studies Sense-making and Analysing and Interpreting and Modelling Exploring Implementing Some of the simpler Many Bayesian or DMDU with its Some of the simpler (Brown et al., DMDU tools MCDA tools can be emphasis on robustness models do not require 2019) [11], (Groves complement soft used here but with encourages substantial resources, et al., 2019) [12], Do Not Cite, Quote or Distribute 17-40 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report elicitation tools and DMDU's additional contingency planning but the application of (Hall et al., 2012) can help to identify emphasis on in implementation with parallel sophisticated [13], (Lempert and relevant scenarios robustness and the careful monitoring to analyses in several Groves, 2010), and help formulate exploration of identify emerging scenarios can be [14], (Taner et al., problems. several/many risks. computationally 2017) [15], scenarios. demanding. Also, the (Weaver et al., emphasis on discussion 2013) [16] of robustness can be demanding on the time of problem-owners, experts and stakeholders. Uncertainties Cynefin context Stochastic, Ambiguity Known Knowable Complex Chaotic Epistemic, Value Analytical (Descriptive (Prescriptive Modelling) Modelling) Methods are Some DMDU Deep uncertainty is Deep uncertainty is The complex and Deep designed for deep epistemic methods draw on absent but the absent but the chaotic spaces are uncertainties uncertainties. Some can deal MCDA methods principles and principles of home to deep are rife in the with stochastic uncertainties. and thus consider processes of decision making uncertainties. chaotic Analytical uncertainties ambiguity and decision making may be used. DMDU tools and contexts. seldom accounted for. value uncertainties. may be used. more particularly DMDU In any case, processes are emphases on DMDU methods relevant here. The robustness and support wide emphasis on possible deliberation with robustness is very scenarios can stakeholders. relevant. The stimulate tools themselves creative are relatively discussions of simply structured ill understood but are effective at issues. stimulating discussion. Decision Process Management (Raz and Micheal, 2001; Dalkir, 2005; Burstein and W. Holsapple, 2008; Jashapara, 2011; Bonczek et al., 2014; Sauter, 2014; Holsapple et al., 2019) A range of tools and techniques to help manage the decision-making process and support risk management and the implementation of the chosen strategy. Some tools organise data and analyses, often being built on a geographic information system, known as decision support tools. Others manage processes, organising workflows. Some have inevitably expanded in function to support decision-making itself, even though their primary focus might be on, say, implementation and monitoring risks. Such tools are closely related to knowledge management systems; knowledge management processes and decision process management differ more in terminology than in substance. Examples include tools for agriculture (Biehl et al., 2017), evaluating and comparing CMIP climate models (Parding et al., 2020), development of action cycles (Park et al., 2012), and decision support systems across a range of sectors and decision-group applications (Papathanasiou et al., 2016). Cognitive Phase Resources required Case Studies Sense-making and Analysing and Interpreting and Modelling Exploring Implementing Process, project, Tools help structure Project management Decision process (Biehl et al., tools plan management tools 2017)[17], knowledge elicitation decision-making implementation and can reduce resources (Papathanasiou et and risk management processes and ensure Do Not Cite, Quote or Distribute 17-41 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report tools help identify how timely involvement of risk management tools needed in the al., 2016), [18], identify what to decision-making (Parding et al., to structure decision- problem owners, monitor during process. However, 2020) [19], (Park implementation. this assumes that the et al., 2012) [20] making processes. stakeholders, and Knowledge tools are already management tools installed on local Decision process tools experts. Knowledge maintain audit trail and information systems track reasoning for and that the analysis can capture details for management tools can choices made during team is experienced implementation in using them. implementation and capture details for Otherwise, resource is needed to document process for implementation and understand and train in the use of the audit trail. document process for tools. audit trail. Uncertainties Cynefin context Stochastic, Ambiguity Known Knowable Complex Chaotic Epistemic, Value Analytical (Descriptive (Prescriptive Modelling) Modelling) Not designed to Not usually Simple project Project Project Project address addressed, since management tools management and uncertainties ambiguities and may be sufficient risk management management and management involved in the value uncertainties here. tools apply easily decision itself, will be addressed in here. risk management and risk but may handle the decision making project risks in itself, but may use tools may be management the decision those values in risk process, management of used but tools may be especially implementation. implementation. attention needs used but to be paid to attention risks that are needs to be complex in paid to risks nature with little that are knowledge of complex in precise nature with relationships little between cause knowledge of and effects. precise relationships between cause and effects. Economic and Financial Methods (Howell et al., 2001; Pearce et al., 2006; Boardman et al., 2017; Atkinson et al., 2018a; Hurlbert et al., 2019) Stem from economic theory and accounting practices: e.g. cost-benefit analysis, which seeks to price out all aspects of the consequence of a strategy, portfolio analysis, or real options theory, which seeks to value financial investments allowing for their risks and the contingent buying and selling. Such methods are perceived as objective when dealing with tangibles, but are more controversial in their valuing of intangibles. Since these methods model uncertainties with probabilities and then work with expectations, they share much in common with Bayesian methods. However, many applications of cost-benefit analysis omit any detailed treatment of uncertainty. Examples examine the economic costs and benefits of adaptation pathways for storm water infrastructure in Singapore (Manocha and Babovic, 2017), and a coastal mega city, Los Angeles in the USA (de Ruig et al., 2019) Cognitive Phase Resources required Case Studies Sense-making and Analysing and Interpreting and Modelling Exploring Implementing Do Not Cite, Quote or Distribute 17-42 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report In themselves, these These tools focus Since CBA methods do Cost benefit analysis (de Ruig et al., methods do not for complex projects is 2019) [21], support sense-making mainly on analysis not emphasise the a major undertaking (Manocha and and modelling, with much data Babovic, 2017) though discussions of and evaluating the analysis of uncertainties collection needed to [22] how to value impacts, value outcomes. Real both tangible and costs and benefits of and risks, they are less options also require intangible can be data on risks and catalytic in various options. suited for use in uncertainties. Both understanding the may have high issues. They are not designed developing and computational needs. to be used communicating an interactively so are implementation plan. more often deployed Real options with their and communicated via emphasis on reports than contingency are much interactive workshops. more suited (Fischhoff, 2015). Uncertainties Cynefin context Stochastic, Ambiguity Known Knowable Complex Chaotic Epistemic, Value Analytical (Descriptive (Prescriptive Modelling) Modelling) Cost-benefit These methods Although CBA and The methods may The recognition Formal methods usually reduce all value many financial be applied to of the need to modelling deal with and preference methods work in evaluate complex treat deep impossible. uncertainty via information to theory, the projects but CBA uncertainties Much expectations financial complexity makes tends to 'average using real options exploratory with little equivalents. The it seldom worth the out' rather than has been work to attention to key issue is to find effort. analyse uncertainty. investigated identify probability a market in which (Hallegatte et al., potential distributions; all outcomes may 2012; Buurman causes and real options be valued and Babovic, effects. Little methods tend to financially. 2016). if any complex treat uncertainty Modern CBA analysis. in much more methods use much sophisticated more subtle ways. Both techniques for this methods, when than those applied applied fully in the last century have many (Bedford et al., points of contact 2005; Saarikoski et with Bayesian al., 2016). methods (Neely and de Neufville, 2001; Bedford et al., 2005) Interval Methods (Shafer, 1976; Pedrycz et al., 2011) Because of concerns that the statistical accuracy of some data is unknown, and that decision-makers and experts cannot make numerical judgements accurately, analyses have been suggested which work with ranges of values in categories (intervals) as their inputs. While avoiding accuracy issues, weakening the arithmetic may result in other foundational assumptions not being met, including some basic principles of rationality. Different types of uncertainty can often be confused, and the analyses can contradict basic probability theory. Interval models of semantics and imprecision can be useful in exploring ambiguity and value uncertainty, though modelling rather than resolving such uncertainties does not necessary help in decision-making. Some interval methods can be thought of more as sensitivity techniques applied to other decision analytic approaches. Typical approaches here relate to the fuzzy or possibility theory, and evidential reasoning. Do Not Cite, Quote or Distribute 17-43 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report Examples include using fuzzy methods to. assessing climate adaptations in ports in China (Yang et al., 2018), water supply vulnerability in South Korea (Kim and Chung, 2013) and resilience of the Nile River delta (Batisha, 2015); and evidential reasoning in an environmental impact assessment for flood mitigation in Manila Philippines (Gilbuena et al., 2013). Cognitive Phase Resources required Case Studies Sense-making and Analysing and Interpreting and Implementing Modelling Exploring The emphasis on If there is substantial The emphasis on Many methods are rather (Batisha, 2015) [23], simple in application and (Gilbuena et al., 2013) modelling data available, then linguistic require only moderate [24], (Kim and Chung, resources, but they may 2013) [25], (Yang et al., ambiguity may even the simplest of uncertainty may in face issues in scaling up 2018) [26] to major complex help structure a these methods can some cases it may problems. model initially, produce useful mask some of the but the lack of results. But with issues (French, structures to small quantities of 1995). model and data, their data explore complex analysis may be too interdependencies inefficient. may inhibit the Evidential reasoning ability to build a MCDA can be valid insightful on the representation of preference side. the issues. Uncertainties Cynefin context Stochastic, Ambiguity Known Knowable Complex Chaotic Epistemic, Value Analytical (Descriptive (Prescriptive Modelling) Modelling) There are issues of Some Methods can be Since the methods The recognition of the The ability to operational definition of methods can applied here often capture rather need to treat deep deal with quantities in some methodologies. be simplistic without major than explore and uncertainties using real ambiguity may Some simpler interval methods with issue, possibly resolve ambiguity options has been be helpful in have no concept of conditionality so quantities not because the and value investigated poorly cannot model learning effectively, being simple, uncertainties, they (Hallegatte et al., understood but there are some very sophisticated operationally repetitive can hide issues. 2012; Buurman and situations, but theories of evidence that can. Interval defined. The nature of the Also, the lack, in Babovic, 2016). the emphasis methods can also provide sensitivity evidential problem allows some cases, of on capturing analyses for Bayesian and reasoning access to much operational ambiguity may MCDA methods (Shafer, 1976; Rios approach to data and the definitions may ultimately Insua, 1990). MCDA possibility of mean that some slow the allows tuning the quantification is building of exploration methods to the dubious. Evidential understanding. of the application. reasoning methods relative can help analyse weights on conflicting different objectives (French, criteria or 1995; Xu, 2012). between levels in criteria (Xu, 2012; Zhang et al., 2017). Do Not Cite, Quote or Distribute 17-44 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report Multi-Criteria Decision Analysis (MCDA): Full ranking and optimal seeking (Bell et al., 2001; Belton and Stewart, 2002; Bouyssou et al., 2006; Zopounidis and Pardalos, 2010; Tzeng and Huang, 2011; Velasquez and Hester, 2013; Kumar et al., 2017) Covers many approaches: indeed, Bayesian, DMDU and interval methods are sometimes considered MCDA. Some MCDA seek an optimal or best strategy; others form partial rankings, eliminating weak strategies but not discriminating fully between the better ones. Many MCDA methods eschew dealing with uncertainties and focus on modelling and exploring conflicting objectives and balancing these. MCDA techniques are especially useful in working with senior decision-makers in setting policy and broad objectives, and in processes of stakeholder engagement. Examples include ranking adaptation and mitigation priorities at a national level in the Netherlands (de Bruin et al., 2009), Lithuania (Streimikiene and Balezentis, 2013) and Bangladesh (Haque, 2016), in the forestry sector in Nicaragua (Guill閚 Bola駉s et al., 2018); and in emissions trading in the European Union (Konidari and Mavrakis, 2007). Cognitive Phase Resources required Case Studies Sense-making and Analysing and Interpreting and Modelling Exploring Implementing There is growing Emphasis is Use of graphical The more exploratory (de Bruin et al., experience in usually on models and sensitivity methods can be quite light 2009) [27], (Guill閚 combining soft analysing and plots can help explain in terms of computational Bola駉s et al., 2018) elicitation with tools exploring, reasoning for strategy resource, but require [28], (Haque, 2016) to formulate resolving to stakeholders and interactions with decision [29], (Konidari and problems (Marttunen conflicting implementers makers and stakeholders in Mavrakis, 2007) et al., 2017). Many objectives. (Bendoly and Clark, workshops. Methods with [30], (Streimikiene MCDA tools MCDA Methods 2016). use complex stochastic and Balezentis, 2013) naturally encourage come into their mathematical [31] discussion and own at this stage programming can be deliberation on of the process. computationally developing Sensitivity tools demanding and require appropriate value and intuitive substantial data. structures. However, graphical displays exploration and exist for many of formulation of the methods stochastic and (Gunawan and epistemological Azarm, 2005; uncertainties is less Boardman et al., developed (Durbach 2017). and Stewart, 2020a). Uncertainties Cynefin context Stochastic, Ambiguity Known Knowable Complex Chaotic Epistemic, Value Analytical (Descriptive (Prescriptive Modelling) Modelling) These methods Many methods Usually in the If the objective Methods can Formal tend to focus on here use multi- known context, the function is not well explore modelling balancing and attribute value objective function understood, then conflicting impossible. resolving functions and is well understood; these methods can objectives, but Much conflicting focus on using but in cases where be useful and can be seldom are able to exploratory objectives and weights to it is not, extended to address deep work to include little or no explore different interactive multi- stochastic epistemic identify analysis of emphases on objective programming, but uncertainties, potential stochastic and conflicting programming can epistemic unless combined causes and epistemic objectives. One offer a way uncertainties are not with scenarios effects. Little uncertainties. very popular forward (Klamroth really addressed (Stewart et al., if any complex Interactive method is AHP et al., 2018). 2013; Marchau et analysis. Do Not Cite, Quote or Distribute 17-45 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report methods that use (Saaty, 1980) (Gutjahr and al., 2019; Pichler, 2016). Durbach and complex objective though this has Stewart, 2020a). functions do need issues in scaling to consider up to evaluate convergence more than a criteria for handful of analytic policies. uncertainties. Multi-Criteria Decision Analysis (MCDA): Partial ranking (Roy, 1996; Bell et al., 2001; Belton and Stewart, 2002; Bouyssou et al., 2006; Behzadian et al., 2010; Zopounidis and Pardalos, 2010; Tzeng and Huang, 2011; Bouyssou and others, 2012; De Smet and Lidouh, 2012; Velasquez and Hester, 2013; Figueira et al., 2016; Govindan and Jepsen, 2016) Examples include developing criteria for assessing climate protection strategies and applying these to retrofitting a school to manage climate risks in Germany (Markl-Hummel and Geldermann, 2014); evaluating outranking approaches for managing heat stress in a large city in Australia (El-Zein and Tonmoy, 2015); using MCDA to manage the interactions of climate change with tourism in Greece (Michailidou et al., 2016); and identifying priorities to manage droughts and floods in agriculture in Bangladesh (Xenarios and Polatidis, 2015). Cognitive Phase Resources required Case Studies Sense-making and Analysing and Interpreting and Modelling Exploring Implementing Graphical representations ELECTRE and The analysis of If an outranking (El-Zein and dominance can algorithm is essentially Tonmoy, 2015) of partial orders are useful PROMETHEE provide a sound combinatorial in its [32], (Markl- footing for building approach, then for Hummel and in model formulation, and implementations of risk registers to aid complex problems there Geldermann, implementation. may be computational 2014) [33], the emphasis on exploring outranking Understanding the problems. Some of the (Michailidou et kernel of consensus methods may require al., 2016) [34], what can be said approaches have can also aid less interaction with (Xenarios and communication. decision-makers and Polatidis, 2015) objectively about many tools for stakeholders if they can deduce many partial [35] dominance relations can exploring partial relations from objective data. build a kernel of relations and consensus between analysing decision-makers and agreements and the stakeholders. reasoning behind these. Uncertainties Cynefin context Stochastic, Epistemic, Ambiguity Known Knowable Complex Chaotic Analytical Value (Descriptive Modelling) (Prescriptive Modelling) Modelling of all Partial ranking or Usually in the Since epistemic Outranking methods Formal forms of uncertainty outranking known context, modelling including epistemic methods seek, the objective uncertainties are may be combined impossible. uncertainty is not the first of all, to function is well Much primary objective of identify understood; but not fully with scenarios to exploratory these methods. dominance when it is not, work to Stochastic uncertainty between options outranking addressed, these explore and analyse identify may be included as and preference methods can potential probability relations that can identify a partial methods can only decisions under deep causes and distributions but there be agreed ranking without effects. is no formalism for somewhat need too many help in relation to uncertainty (Hyde et Little if any conflicting al., 2003; Durbach, objectives, but 2014). robustness to uncertainties will need addressing Do Not Cite, Quote or Distribute 17-46 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report learning to address objectively. Thus, interactions with (Hyde et al., complex 2003). analysis. epistemic first they problem-owners. uncertainties (Hyde et eliminate al., 2003; Behzadian suboptimal et al., 2010; Gerv醩io alternatives and Sim鮡s da Silva, before seeking a 2012). fuller ranking. Ambiguity and value uncertainty may also be quantified (Behzadian et al., 2010; Figueira et al., 2016; Govindan and Jepsen, 2016). Soft Elicitation (Rosenhead and Mingers, 2001; Shaw et al., 2006; Shaw et al., 2007; Ackermann, 2012; Bendoly and Clark, 2016) Also known as problem structuring, it is the process of asking problem owners, experts and stakeholders for the knowledge, perceptions, beliefs, uncertainties and values that a model needs to embody before being populated with numbers. Methods here help in problem formulation, structuring understanding: e.g. cognitive maps, soft operational research diagrams, soft systems, prompts such as PESTLE and other qualitative tools (Prober et al., 2017; Symstad et al., 2017). The output of soft elicitation can lead to the building of sophisticated quantitative models (Symstad et al., 2017); and can also structure communications and deliberations with stakeholders. Exploratory data analysis and visual analytics are also relevant. Soft elicitation has enormous advantages in setting the frame for communication between all parties (Prober et al., 2017); there are many cases in which the clarity brought by framing the issues well has obviated the need for formal quantitative analysis. Examples include Adaptation Pathway planning and elicitation on managing a national park in the USA (Symstad et al., 2017), poverty alleviation in a province in Indonesia (Butler et al., 2016), woodland landscapes in Australia (Prober et al., 2017), as well as general considerations for contested adaptations (Bosomworth et al., 2017). Cognitive Phase Resources required Case Studies Sense-making and Analysing and Interpreting and Modelling Exploring Implementing Soft elicitation tools Soft elicitation is not The results of soft Physical resources (Bosomworth et provide much support relevant to quantitative elicitation provide the requirements are al., 2017) [36], to sense-making, analysis and evaluation dimensions for relatively slight: (Butler et al., formulating problems per se, but can support communication by sometimes post-its 2016) [37], and identifying the exploration of identifying the issues and a white board can (Prober et al., relevant issues to be residuals to understand that are important to be sufficient, though 2017) [38], addressed (Shaw et al., the quality of the stakeholders and modern visual (Symstad et al., 2006; Shaw et al., models and detect building understanding analytics can require 2017) [39] 2007; Ackermann, further factors to be in those implementing substantial computing 2012). addressed. the policies. resource. However, the demands on the time of problem- owners, stakeholders and experts can be significant Uncertainties Cynefin context Stochastic, Ambiguity Known Knowable Complex Chaotic Epistemic, Value Analytical Do Not Cite, Quote or Distribute 17-47 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report (Descriptive (Prescriptive Modelling) Modelling) Soft elicitation There are tools to Usually problems Problems falling Many soft Soft falling into known tools are catalyse deliberations contexts are well- into knowable space elicitation tools elicitation understood and available to and help problem- there is little need are usually well were developed tools and to elicit or elicit problem- owners and structure models structured and for complex processes can to perform owners' and stakeholders clarify analyses. problem owners' contexts: 'wicked' be used to experts' their meanings and values are also well problems with catalyse perceptions of contextualise their understood. deep creative these values to the specific However, there may uncertainties: thinking uncertainties issues being be a need to explore e.g., soft systems, about poorly and, more considered (Keeney, error structures in cognitive maps understood particularly, 1992). preparation to and similar tools contexts. dependences estimate parameters to elicit and in the models perceptions of independences (Gelman, 2003; relationships between them. Steed et al., 2013; between entities Exploratory data Fekete and Primet, and problem- analysis is also 2016). owners' and relevant (Steed stakeholder's et al., 2013; values (Keeney, Bendoly and 1992; Rosenhead Clark, 2016). and Mingers, 2001) 1 2 3 4 Figure 17.7: Decision-analytic tools used across different geo-political scales and how they contributed to decision 5 outcomes. Points comprise the type of decision-making body (C = Community; G = Government; B = 6 Business/Industry; F = Finance; N = NGO; A = All categories) coupled with the reference number in square brackets, 7 which correspond to numbered references in the case studies of Table 17.5. Colours of the points correspond to the Do Not Cite, Quote or Distribute 17-48 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 class of decision-analytic tool as presented in Table 17.3: Bayesian (red), DMDU (Decision Making under Deep 2 Uncertainty) (brown), Decision Process Management (dark blue), Economic and Financial Methods (purple), Interval 3 Methods (light blue), MCDA � full ranking (light green) or partial ranking (dark green), Soft Elicitation (Black). 4 5 6 Many published studies on the utility of decision-analytic methods in managing climate risks are theoretical 7 and therefore it is difficult to find studies on p the value of analytic methods for underpinning final decisions 8 on climate risk adaptation. Bayesian, Deep Uncertainty and elicitation methods and tools to support decision 9 making were the most easily located classes of methods to be used in different contexts (Figure 17.6) while 10 the other classes were more oriented towards government processes. This result highlights a key gap at 11 present in the need to have real world experiences published and mapped for their utility for different tasks, 12 thereby creating a resource for policy-makers to identify suitable tools, such as in emerging communities-of- 13 practice of decision practitioners (Watkiss and Hunt, 2013; Street et al., 2019; French, 2020a). 14 15 17.3.1.3 Approaches to Support Decision-making 16 17 The common approaches presented here are not undertaken in isolation and are often combined throughout, 18 or applied at different stages of, a decision process, as illustrated in Figure 17.6. 19 20 17.3.1.3.1 Role of informal processes 21 Informal decision-making pervades decision-making in all contexts (high confidence) (Orlove et al., 2020); 22 decisions relating to climate change are affected not only by rational processes but also by many informal, 23 often behavioural responses to the situation, some of which may not require formal processes. Informal 24 processes were officially studied in only a few of the publications contributing to Figure 17.7, but all of the 25 studies have hints to informal decision-making that pervades all levels of governance. Although there are not 26 many concrete studies, citing roles of study participants can lead to a perception of a disconnect between the 27 process and the outcome that resulted (see Section 17.5.1 for enablers of success). 28 29 Generally, while governance requirements may define the processes of formal deliberations and decision- 30 making, informal deliberations will carry on in parallel, supported by social media, and these informal 31 deliberations may be used to affect the outcome of the formal processes. Stakeholders may feel excluded 32 from the formal deliberations either by governance structures or because they do not agree with their 33 representatives. Conflicting value systems may cause some stakeholders to feel side-lined, particularly if 34 some of the key decision-makers are perceived holding different personal views and interests or to have 35 engaged in political horse-trading, which connect independent decisions. There may be emotional responses, 36 driven by poor comprehension of risk and probabilistic information, and potential for group biases or 37 insularity of participants (Engler et al., 2019). Well-designed decision processes recognise the informal and 38 seek to gain information from it without introducing bias (medium confidence) (French and Argyris, 2018). 39 40 17.3.1.3.2 Stakeholder engagement 41 Stakeholder engagement has become increasingly part of climate-relevant decision processes (Orlove et al., 42 2020). The degree of stakeholder engagement ranges from instructive, consultative to cooperative that are 43 equivalent to information exchange, influence, and partners in decision-making (Sen, 2000; Cattino and 44 Reckien, in press). Since the AR5, climate change adaptation and resilience literature has seen an increase in 45 participatory approaches that deepen engagement and overcome challenges, as well as making some 46 assessments of their effectiveness (Newton Mann et al., 2017; Wamsler, 2017; Esteve et al., 2018), including 47 structured interactions among different types of stakeholders, the use of place-based boundary organizations 48 to strengthen the interactions and heighten the awareness of the institutional context. A higher degree of 49 public participation can lead to more transformational adaptation as well as to higher ambition for local 50 mitigation (medium confidence) (17.4.4.2; Cattino and Reckien, in press). Challenges to stakeholder 51 participation are access to state-of-the-art science, capacity to recognize and respond to non-reliable or false 52 climate science information, and the removal of cognitive and other biases (high confidence) (Gorddard et 53 al., 2016; Engler et al., 2019; Fulton, 2021). 54 55 Participatory and elicitation approaches, where the concerns and involvement of a broader range of interest 56 groups and stakeholders are taken into account, can improve the effectiveness of decision-making (medium 57 confidence) (Gregory et al., 2012; Cvitanovic et al., 2019). Participatory planning includes a variety of co- Do Not Cite, Quote or Distribute 17-49 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 generative strategies and approaches (e.g., qualitative scenario or adaptation pathway development) through 2 which goals and objectives, knowledge, and strategy implementation and evaluation can be decided 3 collaboratively between practitioners, policymaking, local interests and groups, and scientists (Butler et al., 4 2016; Prober et al., 2017; Symstad et al., 2017). Specifically, for climate change adaptation, these decision- 5 making strategies can incorporate expert, indigenous and local knowledge (high confidence) (Cross-Chapter 6 Box INDIG; Gustafson et al., 2016). The challenge will be to bring together these different actors, as 7 stakeholders tend to act within rather than among systems and procedures, and it is important that platforms 8 are developed to integrate data effectively (Rizzo et al., 2020). Furthermore, reflexive and iterative risk 9 management may further ensure acceptance by participating groups. 10 11 Bayesian Methods are increasingly used in advancing approaches for decision-making and support in climate 12 adaptation (Sperotto et al., 2017), by being able to include stakeholder and decision-maker perceptions and 13 biases (Dias et al., 2018; Engler et al., 2019; Phan et al., 2019; Fulton, 2021) in a transparent modelling 14 environment, thereby facilitating consensus and impartiality (medium confidence) (Catenacci and Giupponi, 15 2013; Gelman and Hennig, 2017). Increasing computational efficiency means that these methods can enable 16 different approaches to be addressed and different descriptive and prescriptive models to be included within 17 a single probabilistic environment, which also can be updated in iterative processes (high confidence) (Table 18 17.5; Sperotto et al., 2017; Phan et al., 2019). 19 20 17.3.1.3.3 Scenario analyses 21 Scenarios are described in SR1.5 (IPCC, 2018a) and SRCCL (IPCC, 2019b) as a description of how the 22 future may develop based on a coherent and internally consistent set of assumptions about key driving forces 23 (e.g. rate of technological change, prices) and relationships. Scenarios are neither predictions nor forecasts 24 but are used to provide narratives and trajectories equipped with alternate outcomes. SR1.5 and the SRCCL 25 describe a range of scenarios methods and how scenarios are used to guide risk management decision 26 making. Scenario analysis includes a range of potential future conditions from low end, mid-range, to high- 27 end projections. Scenarios can also include a temporal component from short term, medium term and long 28 term, as defined in the SROCC (IPCC, 2019c). 29 30 Scenarios and pathways, combined with elicitation methods, are becoming widely used to assess adaptation 31 and resilience strategies (high confidence) (Butler et al., 2016; Prober et al., 2017; Symstad et al., 2017; 32 Lawrence et al., 2019; Phan et al., 2019; Sperotto et al., 2019; Haasnoot et al., 2020a). They can support the 33 consideration of a wide range of alternative possible futures (Catenacci and Giupponi, 2013; J鋑er et al., 34 2018), enabling identification of potential path dependencies caused by adaptation options (high confidence) 35 (Pretorius, 2017; Haasnoot et al., 2020a). They can also increase the willingness of stakeholders to consider 36 costly actions, by placing them within broader sequences of action (limited evidence) (Barnett et al., 2014). 37 The development, consideration and understanding of scenarios can be enhanced by using visualisation tools 38 to better display storylines, enabling the discussion of alternative futures by participants in decision-making 39 processes (limited evidence) (Winters et al., 2016). 40 41 17.3.1.3.4 Evaluating trade-offs, robust decision making, and deep uncertainty 42 Trade-offs are pervasive in decision-making for climate change adaptation, including between adaptation 43 and mitigation, economic/social and environmental cost including distributional/equity considerations, 44 affordability and risk reduction, short and long-term consequences, and spatial variations (Borgomeo et al., 45 2016; Hudson et al., 2016; Gil et al., 2018; Landauer et al., 2019). 46 47 Trade-offs are often directly compared in cost-benefit analyses which require rigorous estimation of the 48 monetized costs and benefits, where monetization is feasible and values uncontested (such as for 49 infrastructure) (high confidence) (de Ruig et al., 2019; Table 17.5). Other tools can be employed, such as 50 cost-effectiveness analysis and multi-criteria analysis in order to draw stakeholders into the process (Posner, 51 2004; Matheny, 2007; Mechler and Schinko, 2016). Stakeholder participation in measuring costs and 52 benefits and in the modelling can aid the process (Doukas and Nikas, 2020). 53 54 Logic trees include a range of decision protocols and multi-criteria rules, either based on quantitative or 55 qualitative categories (Roncoli et al., 2016), often termed multi-criteria analyses. The concept of the logic 56 tree has been increasingly applied in climate risk decision-making contexts (Nikas et al., 2018). 57 Do Not Cite, Quote or Distribute 17-50 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Since the AR5, robust decision-making methods are increasingly used to account for deep uncertainty in 2 many climate related risks (high confidence) (Marchau et al., 2019; Table 17.5), particularly when decisions 3 need to be made well in advance of when the adaptations need to be implemented (Cross-Chapter Box.5 in 4 SROCC Chapter 1; Cross-Chapter Box DEEP in this Chapter). Reducing risk and building resilience under 5 the context of these types of wicked problems require asking "what if" questions about the future, remain 6 flexible in the face of uncertainty, and seek out policies that provide good outcomes no matter what the 7 future climate might bring (high confidence) (17.6; e.g. Larson et al., 2015; Bhave et al., 2016; Bhave et al., 8 2018). In these cases, trade-offs can be assessed and options can be prioritized through iterative decision- 9 making processes, such as multi-criteria decision-making, robust decision-making, and dynamic adaptation 10 pathway planning (high confidence) (Table 17.5; Kwakkel et al., 2014; Kwakkel et al., 2016; Shortridge et 11 al., 2016; Lawrence and Haasnoot, 2017; Haasnoot et al., 2019; Lempert, 2019; Roelich and Giesekam, 12 2019; Haasnoot et al., 2020a). They can address limitations of data-intensive robust decision-making in 13 developing countries (Daron, 2015), can use proxy data to enable the use of robust decisions in data scarce 14 contexts (Shortridge and Guikema, 2016; Ahmad et al., 2019), incorporate multiple-objectives into robust 15 decision making (Singh et al., 2015), and pathway development supplemented by real options analysis 16 (Buurman and Babovic, 2016; Smet, 2017; Haasnoot et al., 2019; Lawrence et al., 2019). Often, there are 17 close synergies between the application of these methods and using scenario analyses (Workman et al., 18 2021). 19 20 21 [START CROSS CHAPTER BOX DEEP HERE] 22 23 Cross Chapter Box DEEP: Effective adaptation and decision-making under deep uncertainties 24 25 Authors: Carolina Adler, Robert Lempert, Andrew Constable, Marjolijn Haasnoot, Judy Lawrence, 26 Katharine J. Mach, Simon French, Robert Kopp, Camille Parmesan, Mauricio Dom韓guez Aguilar, Elisabeth 27 A. Gilmore, Rachel Bezner Kerr, Adugna Gemeda, Cristina Tirado-von der Pahlen, Debora Ley, Rupa 28 Mukerji. 29 30 Decision relevant uncertainties for managing climate risk 31 32 Adaptation decision-making can benefit from assessments that support planning for both `what is most 33 likely' as well as for stress-testing adaptation options over a range of scenarios (Sections 11.7 and 17.3; 34 Cross-Chapter Box.5 in SROCC Chapter 1). This Cross-Chapter Box summarises how deep uncertainties 35 (Section 1.2; IPCC, 2019a) can be assessed in decision-making and addressed practically for adaptation. 36 The concept of deep uncertainty has evolved in IPCC assessments, expanding beyond a focus on reducing 37 uncertainty, to also considering a range of tools and approaches that guide robust and timely decisions to 38 address climate risks. Deep uncertainty is defined as circumstances where experts or stakeholders do not 39 know or cannot agree on one or more of the following: (1) appropriate conceptual models that describe 40 relationships among drivers in a system; (2) the probability distributions used to represent uncertainty about 41 variables and parameters; and/or (3) how to weigh and value desirable alternative outcomes (Cross-Chapter 42 Box.5 in Chapter 1; Lempert et al., 2003; IPCC, 2019a; IPCC, 2019c). 43 44 Decisions by individuals, households, the private sector, governments, and public-private partnerships are 45 generally made with partial or uncertain information. This is also the case for adaptation and development 46 decisions where there is often deep uncertainty about the impacts and the societal conditions, preferences and 47 priorities, and responses over time. Under such conditions, decision-makers employ decision processes and 48 scientific information differently from situations where most decision-relevant information is available, 49 uncontested, and confidently characterized with single joint probability distribution. Assuming scientific 50 information is certain, when it is not, is a barrier to effective communication of risks and to successful 51 decisions under uncertainty, increasing the potential for failure and regret of investments, lost opportunities, 52 and transfers of costs to future generations (Sarewitz and Byerly, 2000; Marchau et al., 2019; Sections 11.7 53 and 17.6). 54 55 Addressing deep uncertainty is contextual as it depends on the decision options available, outcomes at stake, 56 and the available scientific information (Box 1.1. in Marchau et al., 2019). The IPCC uncertainty guidance 57 note (Mastrandrea et al., 2010) addresses only the latter (see also Mastrandrea and Mach, 2011; Section Do Not Cite, Quote or Distribute 17-51 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 1.3.4). Deep uncertainty is generally more salient when policy-relevant statements have low confidence or 2 lack relevant data or information, or in cases where significant uncertainty contributes to disagreements and 3 disputes (Sriver et al., 2018). Recent work has also included moral uncertainty (MacAskill et al., 2020) by 4 evaluating the outcomes of alternative strategies with analyses organized around different perspectives on 5 the appropriate principles of justice (Ciullo et al., 2020; Section 17.3; Jafino et al., 2021; Lempert and 6 Turner, 2021). 7 8 To better communicate deep uncertainty, WGI AR6 complements projections of likely global mean sea-level 9 change, driven by processes in which there is at least medium confidence, with projections that incorporate 10 ice-sheet processes in which there is low confidence (Section 9.6.3 in Fox-Kemper et al., 2021). The latter 11 are accompanied by storylines to highlight the physical processes that would generate extreme outcomes 12 (Box 9.4 in Fox-Kemper et al., 2021). These low-confidence projections and storylines are useful because 13 the likelihood of high-end (> 1.5 m) global mean sea level (GMSL) rise in the 21st century is difficult to 14 determine but important to consider in coastal settings (e.g., CCP2; Cross-Chapter Box SLR in Chapter 3). 15 High-end GMSL rise by 2100 could be caused by earlier-than-projected disintegration of marine ice shelves, 16 the abrupt, widespread onset of Marine Ice Sheet Instability and Marine Ice Cliff Instability around 17 Antarctica, or faster-than-projected changes in the surface mass balance and dynamical ice loss from 18 Greenland (Box TS.4 in Arias et al., 2021; Box 9.4 in Fox-Kemper et al., 2021). In a low-likelihood, high- 19 impact storyline and a high CO2 emissions scenario, such processes could in combination contribute more 20 than one additional meter of sea level rise by 2100 (Box TS.4 in Arias et al., 2021; Section 9.6.3 and Box 9.4 21 in Fox-Kemper et al., 2021). Other hazards assessed in WGI AR6 that address similar aspects that are 22 relevant for decision-making under deep uncertainty, include drought (Section 8.4.1.6 in Douville et al., 23 2021; Section 11.6.5 in Seneviratne et al., 2021), flood (Section 8.4.1.5 in Douville et al., 2021); (Section 24 11.5.5 in Seneviratne et al., 2021), wildfire weather (days) (Section 11.8.3 and Box 11.2 in Seneviratne et al., 25 2021), among others. 26 27 Approaches and information requirements for managing deep uncertainty 28 29 Many approaches are available for evaluating robust decisions under conditions of deep uncertainty 30 (Sections 17.3 and 11.7; Box 11.5 in Chapter 11). The majority use multiple scenarios to stress-test 31 adaptation options and explore how alternative adaptation pathways might evolve under a range of different 32 conditions (Swanson). Approaches differ in terms of their focus, types of strategies best addressed, and data 33 and other resources required (Marchau et al., 2019). 34 35 "Low regret" options are one simple and common approach to deep uncertainty (Sections 17.3 and 17.6) 36 expected to perform well over a wide range of scenarios and represent one example of robust strategies. 37 However, such options will generally be insufficient for adaptive responses to adapt over long timeframes 38 and to avoid lock-in of investments (Section 11.7; Box 11.5 in Chapter 11). 39 40 "Adaptation pathways" provide another approach for addressing deep uncertainty and staging decisions over 41 time (Haasnoot et al., 2013), by linking the choice of near-term adaptation actions with predetermined future 42 thresholds. Observation of such thresholds trigger subsequent actions in the planning or implementation 43 stages of adaptation strategies. Adaptation pathways can begin with low-regret, near-term actions that aim to 44 create and preserve future options to adjust if and when necessary. Alternative pathways can be explored and 45 evaluated to design an adaptive plan with short-term actions and long-term options. 46 47 Climate resilient development (CRD), and the pathways to it, can also involve decision making under deep 48 uncertainty. Literature assessed in sectoral and regional chapters of this report present several examples of 49 potential risks to achieving development goals under climate change, at global as well as national and local 50 levels (high confidence) (Chapter 18). Achieving CRD depends on negotiation, contestation, and 51 reconciliation of trade-offs among diverse actors, who in turn value preferred outcomes differently with 52 respect to associated climate risks and uncertainties, hence the prospect for deep uncertainty to manifest 53 (Section 18.5). Deep uncertainty also characterizes the development process itself, given that fundamental 54 changes and disruptions are part of the transformational changes required to shift towards CRDPs. 55 The "keeping options open" approach, plans by using a series of sequential decisions and actions in the near- 56 term to avoid closing off potentially promising future options (Rosenhead, 2001; Section 2.6), or by using 57 real options, take near-term actions that create currently unavailable options in the future (Kwakkel, 2020). Do Not Cite, Quote or Distribute 17-52 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Deep uncertainty approaches use a wide range of storylines as scenarios to test low regret options and to 2 provide information relevant for potential thresholds for use in adaptation pathways (Haasnoot et al., 2013; 3 Box 11.4; Box 11.6; Sections 11.7; 17.3). 4 5 Deep uncertainty approaches enhance the value of monitoring to detect signals of change in a timely manner 6 (medium confidence). Actionable warning can come from climate signals, and socio-economic 7 indicators/signposts, including drivers of change, vulnerability, and impacts, best suited for timely, reliable 8 and convincing signals for decision making that anticipate future changes and the need for adaptation or the 9 potential to seize opportunities (Hermans et al., 2017; Haasnoot et al., 2018; Stephens et al., 2018; 10 Oppenheimer et al., 2019). For early warning signals to be decision-relevant, they need to have institutional 11 connectivity to enable action (Haasnoot et al., 2018; Sections 1.4; 11.4; 11.7; Table 11.18) (medium 12 confidence). 13 14 Examples and case studies from across the WGII report 15 16 There are diverse examples of the practical application of deep uncertainty methods across different climate 17 change hazards in many regions of the world. For instance, low-regret options have been used to address the 18 impacts and risks of landslides and debris flows in mountains (Section CCP5.2.6). Their frequency and 19 magnitude are already widely experienced (Section CCP5.2.6) and projected to increase (Section 20 CCP5.3.2.1). However, managing these associated risks also requires joint consideration of projected 21 vulnerabilities and exposure of people and infrastructure, including the multiple and dynamic non-climate 22 related factors that are relevant for how the impacts manifest in context, such as population growth and land 23 use planning (CCP5.2.6). Here, context-specific deliberative processes are used that include scenarios to 24 guide and specify preventive measures with higher effectiveness than protective (infrastructure) measures 25 could achieve alone. Low-regret adaptation involves raising awareness and accounting for long planning 26 horizons to address the uncertainties associated with such risks, for instance in mountain regions, including 27 education (Sections CCP5.4.1; CCP5.2.6), with co-benefits such as addressing changes in water availability 28 for supply and demand (CCP5.4.1). 29 30 Adaptation pathways have been used to address SLR and changes in extreme rainfall through flood risk and 31 management (Cross-Chapter Box SLR in Chapter 3; CCP2; Sections 13.2, 11.3 and 11.7): for example, 32 adaptive plans in the Netherlands (Van Alphen, 2016; Bloemen et al., 2019), climate resilient development 33 in Bangladesh (Hossain et al., 2018; Zevenbergen et al., 2018), adaptive spatial pathways for infrastructure 34 retreat and for flood risk management in New Zealand (Lawrence et al., 2019a; Kool et al., 2020) and 35 adaptive strategies such as in the cities of London (Ranger et al., 2013; Hall et al., 2019), New York 36 (Rosenzweig and Solecki, 2014), and Los Angeles (Aerts et al., 2018a). This approach is mainstreamed into 37 guidance documents such as the Climate Risk Informed Decision Analysis (CRIDA) (Mendoza et al., 2018), 38 national guidance and policy briefs to address coastal hazards and sea-level rise planning in New Zealand 39 (Lawrence et al., 2018; Lawrence et al., 2019b), planning for sea-level rise in California (OCP, 2018), and 40 synthesis documents by the government of Canada on marine coasts (Lemmen et al., 2016). Furthermore, 41 examples from the United Kingdom, New Zealand and The Netherlands point to the development of 42 monitoring plans to detect signals for climate adaptation (Stephens et al., 2017; Haasnoot et al., 2018; 43 Bloemen et al., 2019). 44 45 Climate smart planning, with a focus on keeping options open, can play a role in reducing species extinction 46 rates (Sections 2.5; 2.6). When and where and for whom particular irreversible impacts will occur is deeply 47 uncertain, for example the extinction of a species. Even at the lowest emissions scenarios, some local species 48 will become extinct, but estimates of extinction risk are highly uncertain, typically varying by factors of 2-3 49 even for one species (Section 2.5) (medium confidence). Risks of species' extinctions are lowered by 50 reducing emissions but keeping options open for as long as possible and avoiding irreversible actions are key 51 to developing a climate-resilient adaptive pathway so that real-time climate-driven changes can inform 52 actions. Nature-based solutions (NBS) are emerging as key players for mitigation. With smart planning, NBS 53 offer approaches that not only provide substantial mitigation, but also considerable adaptation benefit to 54 biodiversity, and human health and well-being. Done poorly, such projects can result in large negative 55 impacts on humans and nature. An NBS climate-sensitive decision framework leading to "win-win" 56 solutions for mitigation and adaptation is shown in Figure 1 Cross-Chapter Box NATURAL in Chapter 2 Do Not Cite, Quote or Distribute 17-53 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 (see also Sections 2.4.2.5, 2.5, 2.6, 5.4.4.4, and 5.14.1; Cross-Chapter Box ILLNES in Chapter 2; Cross- 2 Chapter Box COVID in Chapter 7). 3 4 In view of these multiple and diverse examples, it is evident that the application of deep uncertainty methods 5 is enabling decisions to be made in a timely manner that avoid foreseeable and undesirable outcomes and 6 take opportunities as they arise (high confidence). 7 8 Prospects for adaptation decision-making 9 10 Deep uncertainty is increasingly salient for decision-making as recognition of climate-related risks and 11 related uncertainties has increased (high confidence). These risks can compound and cascade to become new 12 risks, increasing the breadth, frequency and severity of climate change impacts and the consequently 13 increasing scale and scope of adaptation (high confidence) (Cross-Chapter Box Extremes in Chapter 2; 14 Sections 1.3.1.2, 2.3, 2.5, 2.6, 11.5, 11.7, and CCP5.3.1). Waiting until uncertainties are resolved (if they 15 ever can) may leave little or no time to adapt. The lead-time for planning and implementation of adaptation 16 can take decades (Haasnoot et al., 2020b; Cross-Chapter Box SLR in Chapter 3) and socio-economic 17 developments can lock-in undesirable pathways where underlying vulnerabilities and exposure, such as 18 poverty, conflict, and their associated displacement of people, remain unaddressed (Sections 5.13.4; 19 16.5.2.3.8; Cross-Chapter Box Migrate in Chapter 7). 20 21 Overall, there is growing evidence that effective implementation of strategies developed for deeply uncertain 22 problems require adequate mandates and funding frameworks, preparedness and disaster response plans, and 23 monitoring and evaluation of the strategy outcomes, against how the future unfolds (medium confidence). 24 Collaborative and adaptive governance arrangements, and education and awareness raising, promote learning 25 environments for community engagement, and are essential for the effective implementation of robust 26 adaptation plans (medium confidence) (Sections 5.14.1; 17.3 and 11.7). 27 28 [END CROSS CHAPTER BOX DEEP HERE] 29 30 31 17.3.1.3.5 Adaptive feedback management 32 Iterative decision making requires that the implementation of adaptations are reviewed to determine whether 33 the adaptation effectively achieved the objectives, and whether adjustments or additional actions were 34 required (17.5). Adaptive feedback management is an approach to managing dynamic climate risks by 35 designing a field monitoring program to provide data to an assessment procedure which in turn advises on 36 what adjustments need to be made to a `control action', all of which are part of the adaptation to be 37 implemented (Hurlbert et al., 2019; Figure 17.6). Adaptive feedback management is more able to account for 38 the dynamic nature of risk and the future emergence of unforeseen risks because of the active design of how 39 to adjust the management approach (Dickey-Collas, 2014). 40 41 Adaptive feedback management is important for managing climate risks that fall within the Cynefin context 42 of chaos, relying on observations and indicators to learn about the system and to trigger actions (medium 43 confidence) (Helmrich and Chester, 2020). It has been a valued approach for managing wildfish fisheries in 44 many oceans (high confidence) (Fulton et al., 2019; Hollowed et al., 2020; Bahri et al., 2021), and is 45 important for responding to the challenges of climate change (high confidence) (Holsman et al., 2019; 46 Hollowed et al., 2020; Bahri et al., 2021). 47 48 While the benefits of investment in data and assessments can outweigh the costs of implementation (low 49 confidence) (Fulton et al., 2019), the implementation may take time when resources are limited, particularly 50 in developing nations, where low-cost approaches will be needed for deciding on pathways for adaptation 51 (Bhave et al., 2016; Shortridge et al., 2016). 52 53 Iterative decision making and adaptive feedback management meet when the feedback management 54 procedure is reviewed in total for its effectiveness in one of the review and adjustment iterations. At present, 55 a common approach for assessing different adaptation options and their interaction is by using, e.g., 56 scenarios in dynamic models (Adam et al., 2014; Girard et al., 2015). An emerging field in adapting fisheries 57 to climate change is to embed the decision-making system in the scenario models in order to assess the Do Not Cite, Quote or Distribute 17-54 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 capability of feedback management (decision-making, monitoring and capacity for adjustment of the options 2 over time) to achieve satisfactory trade-offs amongst the objectives of the different stakeholders (medium 3 confidence) (Melbourne-Thomas et al., 2017; Holsman et al., 2019; Hollowed et al., 2020). This method can 4 enable prospective evaluation of future whole-of-management scenarios described in this chapter. 5 6 17.3.2 Integration Across Portfolios of Adaptation Responses 7 8 In recent years, methods for simultaneously considering multiple societal and sectoral objectives, climate 9 risks and adaptation options have been emerging, often termed `integrated' approaches (Hadka et al., 2015; 10 Garner et al., 2016; Rosenzweig et al., 2017; Giupponi and Gain, 2017a; Stelzenmuller et al., 2018; Marchau 11 et al., 2019). Different decision-making approaches can be complementary (Kwakkel et al., 2016) and 12 multiple approaches will be needed to manage risks across sectors, in space and over short to long time 13 scales (see Section 17.6). 14 15 Higher level integration was first presented in SREX (Burton et al., 2012; Lal et al., 2012; O'Brien et al., 16 2012) and includes concepts of planning, coordination and mainstreaming (Lal et al., 2012), consideration of 17 cross-scale dynamics and nested vulnerabilities (Klein et al., 2014), as well as decision-making across 18 governments and sectors (Denton et al., 2014; Mimura et al., 2014). 19 20 Since AR5, recognition of the importance of using integrated adaptation to improve climate risk 21 management across the nexus between many sectors and across regions has increased (high confidence) 22 (Harrison et al., 2016; Challinor et al., 2018). This was highlighted in the Special Report on Climate Change 23 and Land (Hurlbert et al., 2019); advanced planning and integration of adaptation responses are needed over 24 many levels (medium confidence) (G鰌fert et al., 2019; Section 17.6; Woodruff and Regan, 2019). The 25 complexity of managing this nexus may be compounded by the potential for antagonistic or synergistic 26 effects among and between climate impacts, and changes arising from local sectoral activities and 27 independent adaptation responses to those risks (high confidence) (Crain et al., 2008; Piggott et al., 2015; 28 Adger et al., 2018; Brown et al., 2018; Stelzenmuller et al., 2018; Simpson et al., 2021), such as the cross- 29 sectoral demands for freshwater (Xue et al., 2015; Azhoni et al., 2018). Integrated adaptation will also help 30 facilitate management of new and emerging risks, help identify when response plans may need to be changed 31 in light of the dynamics of risk over time, and help identify solutions that are less likely to constrain future 32 options for adapting to future needs (Wise et al., 2016). 33 34 Implicit to managing cross-sectoral interactions, including the nexus concept, is that the interlinkages 35 between multiple sectors are systemic, and therefore solutions to challenges arising from any one sector can 36 only be satisfactorily addressed by considering the connections to other sectors at the same time (Wichelns, 37 2017). Challenges for integrated adaptation include: (1) to sufficiently capture the complexities between the 38 nexus dimensions (Weitz et al., 2017); (2) to adequately consider the time, costs and challenges of 39 coordination and cooperation (Wichelns, 2017); (3) to consider the political economy in which progress 40 toward more integrated solutions could take place, not only account for technological requirements(Leck and 41 Roberts, 2015); (4) to obtain sufficient temporal or spatial data to capture the interactions between natural 42 and social processes (Shannak et al., 2018); (5) to connect these considerations to decision-making and 43 policy processes in order to gain insights into the conditions for collaboration and coordination across 44 sectors, including external dynamics and political and cognitive factors determining change (Weitz et al., 45 2017); and (6) to develop a coherent framework against which to assess results and observations (Crain et 46 al., 2008; Wichelns, 2017). 47 48 49 17.4 Enabling and Catalysing Conditions for Adaptation and Risk Management 50 51 17.4.1 Introduction 52 53 The WGII AR5 identified - with high confidence - a range of factors that could enable or limit planning and 54 implementation of adaptation options and potentially their effectiveness (Klein et al., 2014; Mimura et al., 55 2014; Noble et al., 2014). These included governance, finance, knowledge and capacity as enabling factors, 56 as well as cultural, social, political and economic differences that influence individual and collective 57 willingness and capability to act. The AR6 SRs (specifically, de Coninck et al., 2018; Roy et al., 2018; Do Not Cite, Quote or Distribute 17-55 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Collins et al., 2019; Hurlbert et al., 2019) reinforced the AR5 findings, further noting that the transitions 2 needed for climate resilient development would need to be supported by radical shifts in governance, 3 knowledge development, technology application, finance and economics, and social norms. 4 5 This section builds on the AR5 and AR6 SRs by reviewing new evidence on three key enablers identified in 6 the AR5: governance, finance and knowledge. The focus is on assessing new evidence on (i) understanding 7 of these enabling conditions, (ii) how they have changed on the ground, and (iii) whether these conditions 8 have enabled progress on adaptation and risk management. The section also addresses an emerging related 9 topic, the role of catalysing conditions and actors in accelerating action on climate change adaptation, such 10 as litigation on failure to adapt, understandings of urgency, and the aftermath of extreme weather events. 11 While enabling conditions are necessary for action, they are not by their presence enough; catalyzing 12 conditions emerge when game-changing circumstances become present, such as when a high-profile extreme 13 weather event occurs or when a champion drives change in an organisation. 14 15 17.4.2 Enabling Condition 1: Governance 16 17 Governance is an inclusive concept of the range of means for deciding, managing, implementing, and 18 monitoring climate change responses. It can involve the contributions of various levels of government 19 (global, international, regional, sub-national and local) along with those from the private sector, of 20 nongovernmental organisations, and of civil society. The importance of supportive governance 21 arrangements is reiterated widely across regional and sectoral chapters in this report, in multiple different 22 contexts (very high confidence). 23 24 17.4.2.1 Legal, Policy and Regulatory Instruments 25 26 17.4.2.1.1 Climate legislation 27 Legal systems play an important governance role in facilitating responses to climate change across all levels 28 of society (high confidence) (Ruhl, 2010; McDonald and Styles, 2014; Mehling, 2015). Laws can facilitate 29 climate action in multiple ways, including through: (i) mandating and guiding the behaviour of governance 30 structures and actors, (ii) fostering coordination between different levels of government, (iii) enforcing 31 climate responses, (iv) its symbolic value as well as (iv) aligning scientific evidence and societal norms 32 (Mehling, 2015; Scotford et al., 2017). Laws also can embed climate change planning within the 33 administrative structure of a state rendering policy less vulnerable to revocation (Scotford et al., 2017). 34 Extensive revision to laws has occurred in the last decade: a survey of 164 countries showed that over 1200 35 climate-related national laws and policies have been published with approximately 44% being acts of 36 parliament (Nachmany et al., 2017). 37 38 National climate change laws are important for transposing ratified international commitments into domestic 39 regimes, such as the Paris Agreement and the Convention on Biodiversity, as well as voluntary agreements 40 such as the Sendai Framework for Disaster Risk Reduction. In turn, the enactment of domestic laws can 41 yield useful experiences and foster engagements that positively influence and support the development of 42 international commitments (Townshend and Matthews, 2013; Mehling, 2015). Strong and consistent 43 regulatory frameworks also support the flow of climate finance to developing countries that have such 44 frameworks (Nachmany et al., 2017). The successful implementation of national and sub-national climate 45 change and related policies and strategies are often contingent upon the underlying legislative framework 46 empowering, mandating or guiding their review, implementation and enforcement (Averchenkova and 47 Matikainen, 2017; Scotford et al., 2017) (medium confidence). 48 49 Existing legal systems also pose potential barriers to adaptation, as described in Chapter 9 (Africa) and 50 Chapter 8 (Poverty, Livelihoods and Sustainable Development). Laws may reinforce governance 51 arrangements and regulations state that do not support responses to climate change, and exacerbate existing 52 vulnerabilities and inequalities (Craig, 2010; Arnold and Gunderson, 2013; Wenta et al., 2019). In such cases 53 laws may require review and revision or replacement, and at the same be written in ways that foster adaptive 54 management (Craig, 2010; Ruhl, 2010; Cosens et al., 2017). 55 56 Even though there is no agreed definition of or typology for climate change laws (Mehling, 2015), studies 57 have tended to classify climate change laws as being `framework' or `sectoral' (see Table 17.6 for Do Not Cite, Quote or Distribute 17-56 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 examples). Framework laws offer a comprehensive, unifying basis for climate change policy, addressing 2 multiple aspects or areas of climate change mitigation or adaptation (or both) in a holistic and overarching 3 manner (Townshend et al., 2011; Fankhauser et al., 2014; Nachmany et al., 2015; Clare et al., 2017b); they 4 are powerful levers for setting national and sub-national agendas, creating climate change institutional 5 structures, enabling policy implementation, and driving the passage of additional sectoral legislation and 6 regulations (Clare et al., 2017b). Prior to 2010, national framework laws tended to have a mitigation focus 7 while more recent laws or amendments thereto have an increased adaptation focus (Rumble, 2019b). No 8 evidence indicates whether general or specific framework laws yield better outcomes; however, reviews of 9 more recent examples of framework laws in Africa suggest a trend towards more specificity in the required 10 content of adaptation strategies and duties (Rumble, 2019b). 11 12 A sectoral approach to climate change legislation grafts climate-related provisions into existing laws, such as 13 environmental impact assessment, flood insurance and infrastructure planning, collectively creating an 14 aggregated legal landscape (Townshend et al., 2011; Gerrard and Fischer, 2012; Nachmany et al., 2015; 15 Scotford et al., 2017; Rumble, 2019a). This approach is particularly relevant to adaptation challenges which 16 intersect with numerous bodies of law that are dedicated to other societal concerns (Gerrard and Fischer, 17 2012). However, integrating such considerations can be challenging in certain areas of law, particularly those 18 relating to property rights, water rights and endangered species protection (Gerrard and Fischer, 2012). The 19 incorporation of adaptive management principles (including monitoring, periodic evaluation, and response 20 modification) within existing laws can enhance their enabling role and foster greater resilience (Godden, 21 2012; Arnold and Gunderson, 2013; McDonald and Styles, 2014). 22 23 The legal regime for adaptation is too embryonic for assessment of good practice design and content, 24 although similarities can be seen in the framework laws and draft bills across several countries. Some studies 25 highlight the importance of domestic `whole of legal system' analysis prior to developing of modifying law. 26 This can identify the range of existing legislative instruments that can directly intersect with climate change, 27 along with related contextual factors such as national circumstances, governance frameworks, and political 28 and economic realities as well as national administrative culture (Scotford et al., 2017). This helps any new 29 climate change laws to be absorbed into, and harmonise with, the established legal system of each country 30 (Scotford et al., 2017). Efforts are underway to assist countries in such assessments and the identification of 31 areas for legislative reform, for example through the Commonwealth and UN Environment's Law and 32 Climate Change Toolkit. Similarly, databases such as the Grantham Research Institute on Climate Change 33 and the Environment and the Sabin Center on Climate Change Law are expanding the knowledge base of 34 national climate legislation developments. 35 36 37 Table 17.6: Selected examples of framework and sectoral law approaches adopted by different nations that represent a 38 variety of regional contexts. Example Legal Description References Approach United Kingdom Framework Provides for development of climate change impact (Averchenkova Climate Change Act reports and programmes for adaptation. Dedicated et al., 2021) 2008 institutional structure with advisory body, adaptation planning provision, reporting/information obligations, climate change mainstreaming, climate change trusts, or financial arrangements. Kenya Climate Change Framework Modelled on the United Kingdom Climate Change Act. (Rumble, Act 2016 Provides for development of climate change impact 2019b) reports and programmes for adaptation. Dedicated institutional structure with advisory body, adaptation planning provision, reporting/information obligations, climate change mainstreaming, climate change trusts, or financial arrangements. Do Not Cite, Quote or Distribute 17-57 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report Mexican General Law Framework Imposes positive duties upon government to implement (Averchenkova on Climate Change "adaptation actions" - conservation, sustainable use and and Guzman 2012 rehabilitation of beaches and coasts; water programmes Luna, 2018) for watersheds; the establishment of protected areas and biological corridors; the development of risk atlases; human settlement and urban development programmes; and prevention programs targeting diseases exacerbated by climate change. Includes development of economic instruments including fiscal incentives, credits, bonds, civil liability insurance, market-based instruments. New Zealand Sectoral Incorporates adaptive management principles by (Godden, 2012) Exclusive Economic regulating the issuance of marine consents with Zone and Continental conditions allowing change based on ecological change Shelf (Environmental and indicators. Effects) Act 2012 Seychelles Sectoral Provides for the establishment of a dedicated trust fund (Etongo et al., Conservation and for conservation measures and climate change 2021) Climate Adaptation adaptation measures. Trust of Seychelles Act 18 of 2015 Commonwealth of Sectoral Promotes disaster recovery and resilience building. (Government of Dominica Climate Establishes the Dominica Climate Resilience Policy the Resilience Act 16 of Board and sets out its functions and duties. Requires the Commonwealth 2018 development of a Climate Resilience and Recovery of Dominica, Plan. 2018) Swedish National Sectoral Amends Sweden's Planning and Building Act (2010: (Government of Strategy for Climate 900) by requiring Municipalities to assess the risk of Sweden, 2017) Change Adaptation damage to the built environment from climate risks well (Government as how such risks may change in the future; requires Proposition detailed plans for measures to address land permeability 2017/18:163) when issuing a land permit; adopts the Swedish National Climate Strategy into law. Argentinian Glaciers Sectoral Provides for minimum budgets to protect the national (Warner et al., Preservation Law N glacial water sources that supply the Mendoza oasis. 2019) 32.016 (2010) Establishes that all of Argentina's glaciers and its periglacial environment are to be protected, irrespective of size. Netherlands Delta Act Sectoral Protects the Netherlands from risks such as sea level rise (Van Alphen, on Water Safety and and extreme rainfall. Establishes a Delta Programme to 2016) Fresh Water Supply secure fresh water supply and address climate risks/sea level rise; a Delta Fund to operate the Programme and a Commissioner. 1 2 3 17.4.2.1.2 Climate change policies, strategies and plans 4 Climate change policies and plans are important in the translation of national commitments and legal 5 requirements into specific on the ground strategies and guidelines, which enable actions across multiple 6 spheres and scales of government and non-government institutions and actors. 7 8 Substantial developments in adaptation policy have occurred since AR5 (high confidence). Perhaps the most 9 significant is the Nationally Determined Contributions (NDCs) required under the Paris Agreement, where 10 184 out of 197 parties to the UNFCCC have already submitted their first plans (UNDP and UNFCCC, 2019). 11 The NDCs have allowed countries to articulate their priorities and ambition with respect to climate action 12 and it has been suggested that these can in turn lead to cascading policies (and laws) that drive and enable 13 adaptation and climate risk management. Analysis of the first NDCs submitted in the lead up to and after the Do Not Cite, Quote or Distribute 17-58 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Paris Agreement showed that adaptation priorities were more often articulated by developing countries and 2 least developed countries, while developed countries and emerging economies focused mostly on mitigation 3 (Pauw et al., 2019). As of 2019, over 90 developing nations are at various stages of preparing National 4 Adaptation Plans and 112 nations have indicated their intention to revise their NDCs for the 2020 update 5 (UNDP and UNFCCC, 2019). 6 7 Several other international agreements including the Sendai Framework for Disaster Risk Reduction and the 8 UN Agenda 2030 Sustainable Development Goals have had significant impacts on the adaptation and risk- 9 management decision-making processes. For example, the Sendai Framework articulates the need for 10 improved understanding of disaster risk in all its dimensions of exposure, vulnerability and hazard 11 characteristics; accountability for disaster risk management; preparedness to "Build Back Better"; 12 recognition of stakeholders and their roles; mobilization of risk-sensitive investment to avoid the creation of 13 new risk resilience of health infrastructure, cultural heritage and workplaces; strengthening of international 14 cooperation and partnership, and risk-informed donor policies and programs, including financial support and 15 loans from international financial institutions. 16 17 Specific adaptation policies have been formulated at national, regional/state and local levels across 68 18 countries and 136 coastal cities (Olazabal et al., 2019a). At the national level, the quantity and complexity of 19 adaptation policies have increased since AR5, with most policies coming into force since 2009 (Nachmany 20 and Setzer, 2018). Adaptation is addressed in the executive climate policies of at least 170 countries 21 (Nachmany et al., 2019a). Documented sub-national adaptation policies are more prevalent in developed 22 countries and emerging economies, as compared with low- and middle-income ones (Olazabal et al., 2019b). 23 For example, by 2017 26% of large and medium-sized European cities had an adaptation plan or a joint 24 adaptation-mitigation plan in place (Reckien et al., 2018a). 25 26 Adaptation policies often comprise multiple goals and instruments, which develop over time, especially 27 where jurisdiction over policy issues is shared among agencies or levels of government (R韔 and Howlett, 28 2013). The increase in the number and complexity of policy instruments across geared towards adaptation 29 raises questions of coherence and alignment between the selected policy mixes and their effectiveness 30 (England et al., 2018; Ranabhat et al., 2018; Lesnikowski et al., 2019). 31 32 Evaluation of national adaptation plans (NAPs) has only recently been undertaken. Woodruff and Regan 33 (2019) compared national adaptation plans from 38 countries and concluded that most were strong in 34 identifying vulnerabilities and identifying potential adaptation options but were weaker in articulating 35 implementation pathways and monitoring of progress; plans written by multi-agency teams were nearly 36 always of higher quality. Garschagen et al. (2021) showed that while most NAPs consider future changes in 37 climate hazard, many do not consider how vulnerability and exposure might change, concluding that this 38 limits the potential effectiveness of the plans. Morgan et al. (2019) showed that NAPs that are consistent 39 with the Paris Agreement can enable development pathways that promote synergies between environmental, 40 social, and economic goals. 41 42 17.4.2.1.3 Impact of legal and policy instruments 43 Commitment to act, and guidance on how to do so, from international and national governance levels can 44 drive national and sub-national adaptation (Reckien et al., 2013; Heidrich et al., 2016; Reckien et al., 2018a). 45 For example, more local plans have been developed in European countries where it is obligatory for local 46 municipalities to develop climate change plans (Reckien et al., 2018a). Local government have also drawn 47 on non-binding national climate frameworks, as well as international frameworks (such as European law) or 48 international networks (such as Global Covenant of Mayors for Climate and Energy) to guide their actions 49 (Reckien et al., 2013; De Gregorio Hurtado et al., 2015; Reckien et al., 2015; Heidrich et al., 2016; Reckien 50 et al., 2018a). 51 52 However, a national framework is not always sufficient to trigger climate change action on the lower level, 53 in particular when the national guiding document fails to clearly formulate how it should be used and 54 "translated down" to lower governance levels (De Gregorio Hurtado et al., 2015). Guidance on how to apply 55 a national framework at lower governance levels can assist in their uptake. 56 Do Not Cite, Quote or Distribute 17-59 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 In the case of climate change legislation, research on the impact of adaptation laws is limited, save for a few 2 studies (Averchenkova and Matikainen, 2017), because many framework laws, particularly those with more 3 of an adaptation focus, have only been published recently (Rumble, 2019b). Reviews of the implementation 4 of the risk assessment and adaptation components of the UK's Climate Change Act 2008 suggest that they 5 had a weaker implementation record compared to mitigation provisions (Fankhauser et al., 2018), potentially 6 because implementation of adaptation is more complex as compared to mitigation as shown for the local 7 level (Reckien et al., 2019). However, the UK Act is considered to have made action on climate change more 8 predictable, more structured and more evidence-based (Averchenkova et al., 2021). 9 10 There are numerous examples of regulatory and project-based innovations by local governments. Their 11 impact, however, is uneven, with much depending on the implementation capacity of local governments and 12 other socio-institutional barriers, including those relating to mandate and joint project implementation, cross- 13 departmental working, planning cycles, concerns relating to legal liability and compensation, political 14 appetite and cost (Godden, 2012; Taylor, 2016a). Notwithstanding implementation challenges, evidence is 15 emerging that overarching framework laws play a foundational and distinctive role in supporting effective 16 climate governance, including adaptation governance (Fankhauser et al., 2018) and are drivers of subsequent 17 activity (Townshend et al., 2011; Fankhauser et al., 2014; Clare et al., 2017b), especially when formulated 18 with clear guidance for all related actors, including lower level of governance (De Gregorio Hurtado et al., 19 2015). This may explain the rapid increase in both local and national climate change laws, now with an 20 increased emphasis on regulatory provisions to increase resilience and reduce vulnerability. 21 22 17.4.2.1.4 Regulations and standards 23 The presence and articulation of regulations and standards that address climate risk, such as building codes 24 and land use zoning are key enabling factors for effective decision-making (Kim et al., 2020). Regulations 25 and standards provide a framework for common understanding of when and under what conditions action 26 should be taken specifically in relation to the construction and maintenance of the built environment, 27 infrastructure and environmental and social practice (Grynning et al., 2020). Regulations and standards for 28 climate action emerge primarily from two settings. First, as an addition or augmentation to existing 29 regulations and standards that emerged initially to address existing potential climate extremes and stresses 30 (e.g. size of culverts in response to maximum rainfall and runoff conditions). And second, new regulations 31 and standards that were developed in direct response to new or emergent climate risks (e.g. regulations in 32 response to new presence of mean monthly high tide flooding) (Qiao et al., 2018). Commonly agreed upon 33 social norms and conventions also can be described as regulatory and providing a set of standards. 34 35 The regional and sectoral chapters of this report provide significant evidence of how regulations and 36 standards enhance or hinder opportunities for climate risk management and adaptation. Relevant regulations 37 and standards are especially evident in the oceans and coastal domains (Chapter 3 and CCP2, in cities and 38 infrastructure (Chapter 6), and the water (Chapter 4) and food sectors (Chapter 5). Europe and North and 39 South America (Chapters 12, 13 and 14) have the most frequent documented occurrences of examples of 40 regulations and standards. Regulations and standards focused on building codes to protect against extreme 41 event and loss, water regulations and agreements to protect water supply and lessen drought impacts, and 42 health codes to limit heat exposure are the most frequent examples of such practices. Deficiencies of 43 regulations and standards have been noted with respect to their capacity to manage species migrating from 44 climate change, and to provide opportunities for transformative adaptation. The evidence from the sectors 45 and chapters illustrate that more comprehensive regulations and standards lead to positive adaptation 46 outcomes. 47 48 17.4.2.1.5 Environmental and social governance 49 Environmental and social governance refers to voluntary or non-legally required actions taken by 50 participating parties to achieve a commonly defined goal (Bodin, 2017; DeCaro et al., 2017; Partzsch, 2020). 51 While not explicitly described in the sectoral and regional chapters of this report, the maintenance and 52 exercise of environmental and social governance decision-making strategies do enable adaptation practice 53 and have become especially important when formal legal and policy regimes are not yet present. As formal 54 regulation promotes clear and common understanding of climate risks and mechanisms to develop context 55 specific appropriate solutions, voluntary code-making and self-regulation can forestall the need for legal 56 action or can function as precursors to the formulation and implementation of legislation, laws, and 57 regulations. Do Not Cite, Quote or Distribute 17-60 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Social and environmental governance long has been presented within climate risk decision-making, although 3 more typically in the domain of climate mitigation (Wright and Nyberg, 2016; Vandenbergh and Gilligan, 4 2017). Corporate climate decision-making emphasizes the importance of profit motives in shaping decisions 5 however reputational factors as appropriate environmental stewards also can be important when linked to 6 sensitivity of other stakeholders such as investors, lenders, customers, and employees (Vandenbergh and 7 Gilligan, 2017). Pulver (2011) notes that climate issues influence corporate decision-making more strongly 8 in organizations that are networked with other organizations that also consider these issues and through 9 direct experience with climate-related events and associated organizational learning. 10 11 Since AR5, more case studies of social and environmental governance within the domain of climate 12 adaptation have become evident, especially within the context of adaptive management experimentation 13 (Vella et al., 2016; Beunen and Patterson, 2019; Bl黨dorn and Deflorian, 2019). Environmental and social 14 governance strategies for climate adaptation are diverse and reflect context specific conditions of the 15 decision-making process including the role of the state, the individual and private interests, 16 formality/informality, social responsibility, sources of financing, and transparency. Environmental and social 17 governance enables the testing and definition of implementation solutions, enhancing the opportunities for 18 defining successful adaptation (Surminski, 2013). Several models and approaches to adaptive governance to 19 promote adaptation and resilience in response to extreme weather events have been observed. These include 20 polycentric and multi-layered institutions, participation and collaboration, self-organization and networks, 21 and learning and innovation (Djalante et al., 2011). 22 23 The effectiveness of social and environmental governance varies by sector. For example, in the private 24 business sector, Arag騨-Correa et al. (2019) assess the effects of mandatory and voluntary regulatory 25 pressure on firms' environmental strategies. In summary, they find that analyses of the effects of voluntary 26 pressure demonstrate that by themselves they are unlikely to bring about significant improvement in 27 environmental outcomes. Professional organisations, however, have made progress in addressing sectoral 28 standards relative to the adaptation process. This includes the development of new industry guidelines, 29 codes, standards, specifications, in addition to the implementation of infrastructure inventories that 30 incorporate evaluation of vulnerabilities and identification of priority at-risk areas (Chapter 14). Voluntary 31 pressures by themselves are not likely to result in positive outcomes and instead should be coupled with 32 mandatory regulatory pressure to achieve the environmental response desired (Bianco, 2020). 33 34 Since AR5, another key development in environmental and social governance has been the establishment of 35 the Task Force on Climate-related Financial Disclosures (TCFD), which aimed to develop guidelines for 36 companies to voluntarily report the financial implications of two broad categories of climate risk: the 37 transition risks of shifting to a lower-carbon economy and the physical risks of climate change itself (TCFD, 38 2017). As of 2019, ~1,340 companies with a market capitalization of USD12.6 trillion and financial 39 institutions responsible for assets of USD 150 trillion have expressed support for the TCFD (TCFD, 2020). 40 An analysis of reports to the TCFD in 2016 showed that 83% of companies report on physical risks of 41 climate change, and of these 82% reported on strategies to adapt to some of the identified risks (Goldstein et 42 al., 2019). The same analysis also noted that: (i) the total of estimates of assets at risk were two orders of 43 magnitude lower than generally accepted estimates of total financial risk; (ii) a minority of companies 44 consider risks outside of their own operations or in their value chains; (iii) most underestimate or do not 45 estimate the costs of adaptation; and (iv) many assume linear impacts and responses, neglecting the potential 46 for tipping points or acceleration in risk and potentially transformative adaptation requirements. At this 47 stage, TCFD has influenced many companies' thinking and comprehension of physical climate risk, but it 48 appears too early to assess whether this has driven substantive responses to manage these risks. 49 50 17.4.3 Enabling Condition 2: Finance 51 52 Finance has long been recognised as an important enabling and catalysing factor for adaptation, climate 53 resilient development and climate risk management. In Chapter 17, financing for adaptation and climate risk 54 management is covered in the extended cross chapter box, Financing for Adaptation and Resilience (FAR), 55 below. The Cross-Chapter Box aims to highlight key emerging evidence on financing of adaptation, 56 covering both public and private sources and instruments. Climate finance is also covered in a dedicated Do Not Cite, Quote or Distribute 17-61 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 chapter in the WGIII Report (WGIII AR6 Chapter 15), and readers should refer to this Chapter for a more 2 comprehensive assessment of this subject from both a mitigation and adaptation perspective. 3 4 5 [START CROSS-CHAPTER BOX FINANCE HERE] 6 7 Cross-Chapter Box FINANCE: Finance for Adaptation and Resilience 8 9 Authors: Mark New, Madeleine Rawlins, David Viner, Charlene Watson, Lily Burge, Lionel Mok, Lauren 10 Arendse, Vita Karoblyte, Liane Schalatek and Neha Rai and Baysa Naran, So-Min Cheong, Nicoletta 11 Giulivi. 12 13 Introduction 14 This Cross-Chapter Box reports on: (i) new evidence on the finance needed for adaptation and resilience, and 15 uncertainties in these estimates; (ii) the emerging public and private climate finance architecture; (iii) the 16 status of financing for AR, including sources, total flows, regional and sectoral distributions, (iv) equity 17 considerations; (iv) opportunities and challenges for financing adaptation and resilience during and after the 18 COVID-19 pandemic. This Cross-Chapter Box does not focus on finance for mitigation, which is covered in 19 WGIII Chapter 15, nor the economic damages of climate change or financial aspects of Loss and Damage, 20 which are covered in Cross-Working Group Box ECONOMIC (Chapter 16) and Cross-Chapter Box LOSS 21 (this chapter), respectively. 22 23 Successive reports of the IPCC (Vellinga et al., 2001; Mimura et al., 2008; Yohe et al., 2008; Klein et al., 24 2014) and the AR6 Special Reports have noted the importance of finance as an enabler for adaptation, across 25 both developed and developing nations. While various definitions for climate finance have been suggested, 26 and the UNFCCC has yet to have an agreed definition, the IPCC (see Glossary) defines climate financing as 27 "the financial resources devoted to addressing climate change by all public and private actors from global to 28 local scales, including international financial flows to developing countries to assist them in addressing 29 climate change. [It] aims to reduce net greenhouse gas emissions and/or to enhance adaptation and increase 30 resilience to the impacts of current and projected climate change. Finance can come from private and public 31 sources, channelled by various intermediaries, and is delivered by a range of instruments, including grants, 32 concessional and non-concessional debt, and internal budget reallocations". Adaptation and resilience are 33 often used interchangeably in climate finance discussions, although adaptation is a process while resilience 34 (to climate risk) is the ability to progress towards desired outcomes in face of impacts from a changing 35 climate (see Section 1.2.1). 36 37 [START BOX CROSS-CHAPTER BOX FINANCE.1 HERE] 38 39 Box Cross-Chapter Box FINANCE.1: The 100 Billion Climate Finance Commitment to Developing 40 Countries 41 42 At COP16 in Copenhagen in 2009, developed country Parties to the UNFCCC committed to a goal of jointly 43 mobilizing USD 100 billion per year by 2020 to address the climate change needs of developing countries 44 (UNFCCC, 2009). This was in response to a threat by developing countries to walk out of the negotiations, 45 as they perceived developed country support to be lagging and lacking in ambition (Roberts et al., 2021). 46 The commitment was formalized in the Cancun Agreements (Decision 1/CP.16) in 2010 and was reaffirmed 47 as a key element of the Paris Agreement in 2015 (Article 9, paragraph 4). At COP26 in 2021, formal 48 deliberations will begin on a new climate finance goal to be adopted in 2025; the current USD 100 billion 49 target will serve as the annual minimum until 2025 (Chhetri et al., 2020). 50 51 The "100 Billion" does not represent the total need to respond to climate change in developing countries, nor 52 the global cost across all countries, as is sometimes interpreted in the literature and media. As shown below 53 in this Cross-Chapter Box, the estimated cost of adaptation for developing countries ranges 15-411 billion 54 USD per year for climate change impacts out to 2030, with the majority of estimates being well above 100 55 billion. 56 Do Not Cite, Quote or Distribute 17-62 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Proposed sources for the developed country commitment included "a wide variety of sources, public and 2 private, bilateral and multilateral, including alternative sources of finance" and several instruments 3 including grants and loans. Nonetheless, there remain differences of opinion on the types of finance that 4 should count towards this goal, with several issues identified (high confidence) (Bodnar et al., 2015; 5 Bhattacharya et al., 2020; Roberts et al., 2021), including: (i) counting non-grant finance, such as market and 6 concessional loans (public and private), where developing countries ultimately have to repay the investment; 7 (ii) what is counted as "climate" by different funders, especially when climate is not the prime objective; (iii) 8 the extent to which some funds are "new and additional" rather than a repurposing of development finance. 9 10 Progress towards the 100 Billion target has shown an upward trend over the last several years (high 11 confidence), but will fall short in 2020, even when the most generous criteria are included (high confidence). 12 In 2017/18, the most recent year for which data have been comprehensively analysed, estimates using 13 different (but overlapping) data sources and methods were in the range 48-75 billion USD per year, 14 compared to 45-75 in 2015/16 and 41-52 in 2013/14 (Carty et al., 2020; SM17.3; CPI, 2020; OECD, 2020; 15 UNFCCC, 2020). The distribution between adaptation and mitigation has remained strongly weighted 16 towards mitigation, although the proportion allocated to adaptation has increased from 17-25% in 2013/14 to 17 19-30% in 2017/18 (high confidence). One analysis that excludes debt repayments indicates that the debt- 18 adjusted flows are about half the total flows reported above, of which circa 31-33 % was for adaptation 19 between 2015/16 and 2017/18 (Carty et al., 2020). 20 21 [END BOX CROSS-CHAPTER BOX FINANCE.1 HERE] 22 23 Adaptation Finance Needs 24 25 Estimates of global, regional, or national finance needs for adaptation and resilience vary depending on both 26 analysis approach, the level of climate change, and the geographic and sectoral scope of analysis (high 27 confidence) (UNEP, 2016; Chapagain et al., 2020; UNEP, 2020). Recent estimates have adopted one of main 28 approaches: (i) aggregation of individual case studies, along with scaling to generate global or regional costs; 29 (ii) analysis of NDC adaptation cost estimates (Weischer et al., 2016; Hallegatte et al., 2018); (iii) integrated 30 assessment model simulation of impacts and adaptation costs (Markandya and Gonz醠ez-Eguino, 2019; 31 Chapagain et al., 2020). 32 33 All approaches suffer from limitations that can cause both over and underestimates, including incomplete 34 coverage of sectors and risks, inability to account for autonomous/unreported adaptation; incorrect cost 35 estimations; soft and hard limits to adaptation; balance between adaptation, mitigation, and residual cost; 36 benefits and co-benefits on cost; and learning and innovation as climate change progresses (UNEP, 2020). 37 Global or developing region estimates based on scaling NDC data is particularly uncertain, as most NDCs 38 did not specify how the costs were calculated. Also, scaling from a relatively small set of NDCs with costs to 39 the global scale is not particularly robust, indicating a need for more transparency and better guidance for 40 calculating adaptation costs (Watkiss et al., 2015b; Zhang and Pan, 2016; Hallegatte et al., 2018; AfDB, 41 2019). 42 43 Most estimated of adaptation cost in the literature are for developing countries. Chapagain et al. (2020) 44 assessed various estimates of adaptation for developing countries, under different emissions scenarios for 45 2030 and 2050. The median estimates (and range) from these studies are 127 (15-411) and 295 (47-1088) 46 billion USD per year for climate change impacts out to 2030 and 2050, respectively (see SM17.3). All but 47 one study report adaptation costs higher than the 70-100 billion estimated in 2010 by the World Bank (World 48 Bank, 2010). 49 50 The cost of adaptation for developed countries is rarely reported; most literature either reports a global cost 51 or developing country costs, or costs for a specific country or sector. Baarsch et al. (2015), using an IAM, 52 report adaptation annual costs (2012 prices) in 2030 (and 2050) as 272 (660) billion globally and 205 (521) 53 in developing countries only under the RCP2.6 scenario, indicating that developed country costs are around 54 25 (21) % of total cost. 55 56 Do Not Cite, Quote or Distribute 17-63 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Figure Cross-Chapter Box FINANCE.1: Comparison of recent studies that estimated developing country 2 adaptation costs in billion USD (in 2005 prices) per year, for 2030 and 2050. Figure based on Chapagain et al. (2020). 3 Major studies are World Bank (2010), Chapagain et al. (2020), UNEP (2016), Baarsch et al. (2015) and Markandya and 4 Gonz醠ez-Eguino (2019). The solid-coloured bars are based on RCP2.6 and pattern-bars are based on RCP 8.5; the 5 width of the bars indicates the range of estimates (maximum and minimum) produced in each study. 6 7 8 In addition to global estimated adaptation costs, there are many studies that have focused on specific regions, 9 countries, or sectors, such as estimated adaptation cost for coastal environments, water related infrastructure, 10 urban infrastructure, agriculture, energy (UNEP, 2014; Watkiss et al., 2015b; UNEP, 2016). Examples of 11 such estimates are reported in various chapters in this report and summarised in SM17.3. 12 13 Estimating the benefit of adaptation, in terms of damage avoided, remains challenging. For example, Ricke 14 et al. (2018) show that the social cost of carbon (monetary damage per tCO2 emitted) varies by up to two 15 orders of magnitude depending on country, socio-economic scenario, damage function, total GHG forcing, 16 and local climate change. In addition, non-monetary benefits such as cultural identity, sacred places, human 17 health and lives are often ignored (Tschakert et al., 2017; Serdeczny, 2019; see also Cross-Working Group 18 Box ECONOMIC in Chapter 16; Cross-Chapter Box LOSS, this chapter). Recent case studies and global 19 level analyses continue to support the conclusion in IPCC AR5 WGII Chapter 17 (Chambwera et al., 2014) 20 that the benefits of adaptation generally remain larger than the costs (medium confidence), but the cost- 21 benefit ratio varies widely by context and assumptions (OECD, 2015; Global Commission on Adaptation, 22 2019; WRI, 2019) 23 24 The Climate Finance Landscape 25 26 The adaptation and resilience finance landscape spans multiple sources, intermediaries, instruments, and 27 recipients, operating across global to sub-national scales (Buchner et al., 2019; Carter, 2020; Watson and 28 Schalatek, 2021). Public finance is provided by national and subnational governments and distributed 29 directly by government or intermediaries such as development finance institutions and climate funds, either 30 nationally or internationally. Private finance comes from five main sources: commercial financial 31 institutions (banks), institutional investors (including asset managers, insurance companies, and pension 32 funds), other private equity (venture capital and infrastructure funds), non-financial corporations such as 33 renewable energy or water companies, individual households and communities. Across these different 34 sources, the main instruments used are grants, concessional debt, market debt, internal budget allocation, 35 including personal savings in households, and insurance. Public and private sources of funding can be 36 blended into a single instrument, for example for insurance where public funds provide capital for both 37 sovereign catastrophe instruments and microinsurance (Jarzabkowski et al., 2019) or for concessional loans. 38 Similarly, public finance is often ultimately be derived from commercial debt instruments such as bonds. 39 40 International public climate finance 41 Do Not Cite, Quote or Distribute 17-64 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 International public climate finance flows are realised through bilateral and multilateral channels (Watson 2 and Schalatek, 2021) where contributions to these channels are received from Annex II and non-Annex I 3 countries (UNFCCC SCF, 2018; Buchner et al., 2019). Annex II countries contribute as part of their 4 commitments in the Paris Agreement, while non-Annex I countries commit climate finance through these 5 channels on a voluntary basis (Pickering et al., 2015; Roberts and Weikmans, 2017; Egli and St黱zi, 2019). 6 Bilateral intermediaries include development cooperation agencies and national development banks. These 7 institutions often have long standing development-cooperation experience, and offer climate change projects, 8 facilities and financial instruments based on their differing mandates, structures and priorities (Atteridge et 9 al., 2009; Buchner et al., 2019). 10 11 Multilateral channels include the UNFCCC financial mechanisms, such as the Green Climate Fund, and the 12 multilateral development banks (MDBs), such as the World Bank. Both pool contributor resources before 13 committing such resources for climate change projects and programmes. Funding through multilateral 14 channels promotes recipient country engagement in the governance and prioritisation of funding decisions, 15 with concurrent processes in the multilaterals often existing to support country ownership of funded climate 16 action (Ciplet et al., 2013; Ha et al., 2016). 17 18 There are five multilateral climate change funds of the UNFCCC and Paris Agreement financial 19 mechanisms. There are further multilateral climate change funds that are not governed by the UNFCCC or 20 Paris Agreement, the largest of which is the World Bank governed Climate Investment Funds (Watson and 21 Schalatek, 2021). Some of the major multilateral climate change funds have been established with a specific 22 focus on adaptation, while some bilateral donors have thematic or sectoral priorities. Multilateral climate 23 change funds operate through accredited implementing entities. These have historically been multilateral in 24 nature, such as the development banks, but recent years have seen a rise in the accreditation of national and 25 regional institutions (UNFCCC SCF, 2018). In addition to programming funds from external sources, such 26 as through the multilateral climate change funds, the MDBs also raise and programme their own climate 27 finance (UNFCCC SCF, 2018; MDBs, 2019). 28 29 Several major multilateral climate change funds work through grant-only programmes, whereas others 30 include concessional loan, equity and guarantee instruments. The broader suite of instruments used by the 31 MDBs includes grant, investment loan, equity, guarantee, line of credit, policy-based financing and results- 32 based financing (MDBs, 2019). 33 34 Public funding of a concessional nature that flows from Annex II to non-Annex I countries supports research 35 and capacity building and can also facilitate private finance flows into climate action, with the intention to 36 avoid creating a high debt burden in developing countries, in response to climate impacts for which they 37 have little historic responsibility (Watson, 2016; Carter, 2020; Schalatek, 2020). Less concessional public 38 finance flows include other official flows that are not developmental in nature and can be trade related, 39 including for example export credits. 40 41 Critiques of the public climate finance architecture are aimed at the overlapping mandates of the institutions 42 programming climate finance, particularly the multilateral climate funds, and the challenges in accessing 43 funding (Nakhooda et al., 2014; Amerasinghe et al., 2017; Pickering et al., 2017). However, Pickering et al. 44 (2017) further note that institutional fragmentation of climate finance could result in more flexibility, 45 resilience and innovation. There have also been important governance changes leveraged by some of these 46 funds and instruments, such as integration of gender considerations into projects (Schalatek, 2020). 47 48 Private financing of adaptation and resilience 49 50 There is an increasing focus on the role of the private sector to support large-scale financing of adaptation 51 and resilience (UNEP, 2016; UNEP, 2018). To date it has been difficult to track adaptation and resilience 52 finance within the private sector (UNEP, 2016)as it is either not disclosed or not easily identifiable, since it is 53 often built into capital and operating expenditure and is not a standalone investment. Several private 54 mechanisms are emerging as important sources of climate finance (Gupta et al., 2014; Eccles and Krzus, 55 2018; Miller et al., 2019). 56 Do Not Cite, Quote or Distribute 17-65 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Green, social impact and resilience bonds are similar to traditional bonds - fixed-income financial 2 instruments raised on commercial markets by companies, governments or financial institutions - but the 3 proceeds are used to fund activities that have positive environmental, social or climate benefit (Tuhkanen, 4 2020). Green bonds align to voluntary principles, such as the Green Bond Principles set out by the 5 International Capital Market Association, the Climate Bonds Initiative's Climate Resilience Principles 6 (Sartzetakis, 2020)Given the voluntary nature and lack of standardization of green bond principles, there are 7 concerns around their additionality and there is also a lack of data on how green bonds contribute to a scaling 8 up of green projects (Dupre et al., 2018). 9 10 Green bond annual issuance reached 260 billion in 2019 (CBI, 2020) but, as of 2018, only 3-5% (USD 12 11 billion) of green bond total proceeds can be explicitly traced to climate resilience related efforts (CBI, 2019). 12 Examples of AR focused bonds include those issued by Fiji in 2017, dedicating 91% of spending to 13 adaptation and resilience (Shukla and Peyraud, 2017; Ministry of Economy, 2019), and by the European 14 Bank for Reconstruction and Development's 2019 Climate Resilience Bond for USD 700 million to finance 15 climate resilient infrastructure, commercial operations, agriculture or ecological systems (EBRD, 2019). 16 17 Dedicated investment vehicles are equity funds that are created to invest in products and services that 18 enhance resilience and reduce risks. An example is the Climate Resilience and Adaptation Finance and 19 Technology Transfer Facility that is proposed as a USD 500 million private equity fund to invest in 20 companies providing climate resilience solutions for developing countries. Initial funding has been provided 21 by donors (Miller et al., 2019). 22 23 Balance sheet finance occurs when an entity directly invests in resilience and adaptation rather than as a 24 separate project. This source of funding may be from exiting reserves, reallocation from other budget lines, 25 or via external commercial finance, but the investment is financed by the firm rather than as a separate 26 project (Gupta et al., 2014; Buchner et al., 2019). 27 28 Insurance can play an important role in managing residual climate risks at any given level of adaptation, but 29 insurers can also be important r risk assessment and risk reduction as part of any insurance package 30 (Jarzabkowski et al., 2019; Chapter 11.3.8.3). While traditional indemnity insurance is important for repair 31 and rebuilding of damaged property and infrastructure, parametric insurance has become increasingly 32 popular for supporting rapid post-disaster responses such as drought, hurricane damage and flooding. 33 Examples include sovereign insurance facilities such as African Risk Capacity and the Caribbean 34 Catastrophe Risk Insurance Facility (Broberg, 2019) as well as weather-index insurance targeted at 35 individuals, especially in agriculture (Greatrex et al., 2015; Isakson, 2015; Surminski et al., 2016; Jensen and 36 Barrett, 2017; Fischer, 2019). The role of insurance as a climate risk management option, as well as 37 limitations, is covered in more depth in Section 17.2 and Cross-Chapter Box LOSS (this Chapter). 38 39 Mainstreaming physical climate risks and resilience in the private sector 40 41 The data on tracked climate finance and green bond issuance for adaptation and resilience both show a 42 substantial gap between the adaptation needs and the finance deployed. Scaling up these instruments is 43 unlikely to close this gap given the challenges with financing adaptation projects, particularly from the 44 private sector. There is therefore a need for more systematic action to manage climate risks and mainstream 45 climate change considerations (Miller et al., 2019). 46 47 The financial case for mitigation investment can often be demonstrated through revenues from, for example, 48 the sale of renewable electricity. On contrast, the benefits from investment in adaptation and resilience are 49 typically considered in terms of avoided losses and cost benefit ratios. For example, the Global Commission 50 on Adaptation (2019) estimates that the overall rate of return on investments in improved resilience is very 51 high, with benefit-cost ratios ranging from 2:1 to 10:1, and in some cases even higher. 52 53 The private sector is becoming increasingly aware of the need to assess physical climate risks to avoid the 54 long-term risks to assets and enhance climate resilience. The task force on climate-related financial 55 disclosures (TCFD) is likely to create additional pressure from investors for companies to identify, manage 56 and reduce risks from climate change (Eccles and Krzus, 2018; ERM and CBEY, 2018; Tuhkanen, 2020). 57 Do Not Cite, Quote or Distribute 17-66 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 A key factor for the impact of the TCFD on mainstreaming of physical climate risks and demonstrating the 2 case for investment in adaptation and resilience will be how investors systematically incorporate physical 3 climate risks, adaptation, and resilience into their investment decisions. The Coalition for Climate Resilient 4 Investment (DFID et al., 2019) was established to look at this from the private sector viewpoint and is 5 working to systematically incorporate resilience into cash flow modelling and asset valuation practices, so 6 that investors may quantify the investment in resilience for an asset and the benefits associated with reduced 7 costs and more reliable revenue streams. 8 9 Recent trends in climate finance flows 10 11 Considerable progress has been made in tracking climate finance since AR5, but substantial gaps remain, 12 especially regarding domestic public finance and private sector balance sheet investment in adaptation 13 (Section 17.5.1.5; CPI, 2020; Richmond et al., 2020). The best documented information comes from 14 international climate funds, which provide detail at the project level. Most bilateral and multilateral 15 investment institutions report on whether debt, grants and other instruments are for climate projects, but with 16 less detail. Private finance is harder to track, as reporting is voluntary; even for green bonds, where 17 certification identifies the range of sectors a bond aims to cover, reporting of how the bond is spent is 18 infrequent. 19 20 The Climate Policy Initiative (CPI) has been tracking climate finance since 2009, allowing for trends to be 21 assessed; however, trends reported are a function of both real changes in finance and changes in methods and 22 information sources (Richmond et al., 2020). Total climate finance tracked by CPI has increased from USD 23 364 billion per year in 2010/11 to 579 billion in 2017/18 (SM17.3). Tracked finance remained relatively 24 constant from 2010/11 to 2013/14 but has increased steeply in more recent years. The proportion of finance 25 allocated to adaptation has remained small throughout, between 4 and 8% (high confidence); a further 1-2% 26 of global finance has been classified as "multiple-objectives". The large majority of tracked adaptation 27 finance is from public sources (high confidence), with only 2% coming from private sources in 2017/18 28 (CPI, 2020). This is at least partly because of the difficulty in demonstrating financial (as opposed to public 29 good and avoided damages) return on investment for adaptation. 30 31 The majority of the most recently (2017/18) tracked adaptation and multiple-objective finance was supplied 32 through public donors, largely through grants, concessional and non-concessional instruments (Figure 33 FAR.1). Most finance (44,1%) was spent transregionally (allocated in specific projects to recipients in more 34 than a single region). For regionally specific funding, Sub-Saharan Africa, South Asia, along with the Latin 35 America & Caribbean region, received the largest gross amounts, although Oceania has received the greatest 36 per-capita funding. The largest proportion of AR funding has been allocated to increasing the resilience of 37 infrastructure, energy, and the built environment, followed by agriculture, forestry, and natural management, 38 and then water and wastewater. 39 40 Across financial instruments, sub-Saharan Africa received the highest relative proportion through grants 41 (38%), followed by the Latin America & Caribbean region (23%), with other non-OECD regions receiving 42 between 16 and 10% (SM17.3). Concessional debt as a proportion of the regional total varies from 84% in 43 South Asia to as low as 29% in Latin America & Caribbean, which has the highest proportion of non- 44 concessional debt (48%). 45 Do Not Cite, Quote or Distribute 17-67 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Figure Cross-Chapter Box FINANCE.2: The flow and distribution of globally tracked adaptation and resilience 3 finance in 2018 from different sources, through different instruments into different sectors and regions. Each strand 4 shows the relative proportion of finance flowing from one category to another (for example from private or public 5 sources to different instruments). Categories from left to right are: (a) whether the finance is solely for adaptation or for 6 adaptation and other objectives, including mitigation (multiple objectives); (b) whether the finance comes from public 7 or private sources; (c) the financing instrument; (d) the broad sectoral allocation; (e) the geographical distribution of 8 funding (proportion of total in % and per-capita allocation). Based on data collated by CPI (2020). 9 10 11 The importance of public and private finance for adaptation and resilience 12 13 Adaptation finance provided by international public mechanisms remains the core source of tracked flows in 14 support of adaptation and resilience to developing countries (Micale et al., 2018; UNEP, 2018), although 15 these public funds alone are insufficient to meet rapidly growing needs and constitute only a minority share 16 of all public climate finance flows (UNEP, 2016; Global Commission on Adaptation, 2019). 17 18 Public mechanisms can play a role in leveraging private sector finance for adaptation by addressing real and 19 perceived regulatory, cost and market barriers through blended finance approaches, public-private 20 partnerships or innovative financial instruments and structuring in support of private sector requirements for 21 risk management and guaranteed investment returns (Pillay et al., 2017; Miller et al., 2019). 22 23 There is growing agreement on the sectors (such as infrastructure, agriculture or water management) and 24 approaches (contingency finance or insurance) where private sector adaptation investments alone, or 25 leveraged by public mechanisms, might be best targeted, such as by reducing the risk of providing financial 26 services for adaptation investments to domestic micro-, small-, and medium enterprises or agricultural 27 smallholders, many of them women (Biagini and Miller, 2013; Chambwera et al., 2014; Pauw et al., 2016; 28 Global Commission on Adaptation, 2019; Miller et al., 2019; Resurrecci髇 et al., 2019; Richmond et al., 29 2020). A remaining open question is how to allocate limited public adaptation funds in a way that is 30 equitable, effective and efficient between mobilizing private investments and safeguarding adequate financial 31 support for necessary adaptation efforts, such as the provision of public goods, which the private sector will 32 not invest in (Fankhauser and Burton, 2011; Abadie et al., 2013; Baatz, 2018; Omari-Motsumi et al., 2019). 33 34 Many adaptation interventions in the most vulnerable countries, communities and people provide no 35 adequate financial return on investments and can therefore can only be funded with highly concessional 36 public finance. Grant support is most appropriate for measures such as capacity building, planning, public 37 policy and regulatory reforms, disaster risk management and response, community engagement or support Do Not Cite, Quote or Distribute 17-68 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 for social safety nets, and for addressing social vulnerabilities, including poverty or gender inequality, which 2 constrain adaptation (Grasso, 2010a; Pillay et al., 2017; Agrawal et al., 2019; Buchner et al., 2019). 3 Access to adequate adaptation grant finance is further constrained because several public mechanisms 4 provide grants only for the additional costs of adaptation measures compared to a development baseline in 5 the absence of climate impacts. Calculating the incremental costs of adaptation measures imposes additional 6 time and resource burden on the most vulnerable recipients, who are often faced with data gaps or technical 7 capacity constraints (Chambwera et al., 2014; GCF, 2018; UNEP, 2018; Omari-Motsumi et al., 2019). 8 An exact delineation of respective costs for adaptation and development components is difficult and might 9 be unsuitable as many adaptation measures are intrinsically linked to development. It may also prevent 10 realizing necessary synergies between both (McGray et al., 2007; Smith et al., 2011; Denton et al., 2014; 11 Resch et al., 2017; Micale et al., 2018). 12 13 Equality and fairness in climate finance 14 15 Climate finance literature recognises that poor and least developed households, communities, and countries 16 are most affected and marginalized by climate change, and least responsible for its causes, but receive 17 relatively little financial support for adaptation (Chapter 15; Chapter 8; Olsson et al., 2014; Rozenberg and 18 Hallegatte, 2015; Hallegatte et al., 2016; Rai and Fisher, 2017; Shakya and Byrnes, 2017). 19 20 Several factors affecting fair and just financing in developing countries have been identified in recent 21 literature (Klein et al., 2014; Colenbrander et al., 2018; Mfitumukiza et al., 2019; Khan et al., 2019a; Doshi 22 and Garschagen, 2020). First, financing is skewed in favour of mitigation, and therefore towards fast- 23 growing upper- and middle-income countries offering the biggest gains in emission reductions, especially in 24 Southeast Asia, but also in Sub-Saharan Africa (Rai et al., 2016). Further, as much of current finance uses 25 debt-based instruments, mitigation projects are further preferred as returns are more assured (Lee and Hong, 26 2018; Carty et al., 2020). 27 28 Second, the requirement of many funders for readiness and fiduciary capacity means that LDCs have been 29 less able to access finance, despite many support mechanisms being offered. Additionally, geopolitical 30 preferences of some countries mean that some developing countries are preferred to others for bilateral 31 funding (Doshi and Garschagen, 2020). This is exacerbated for private sector investment, where lower credit 32 ratings make finance more expensive, and increasing understanding of exposure to physical climate risks 33 could lead to `capital flight' from most vulnerable countries (Global Commission on Adaptation, 2019; 34 Miller et al., 2019; Cooper, 2020). 35 36 Third, within climate-vulnerable countries, very little is channelled to local communities who need it most; 37 the few analyses available suggest that less than 10% of total climate finance supports decentralized actions 38 (Rai et al., 2016; Soanes et al., 2017). Reasons include: (i) lack of consideration of procedural equity in 39 programme design (Grasso, 2010b; Wang and Gao, 2018; Venn, 2019; Khan et al., 2019a); (ii) finance being 40 managed by multilateral implementers, rather than agencies that are closer to local communities; (iii) the 41 higher transaction costs of decentralized projects in low-income communities reduce their attractiveness to 42 funders as well as the ability of local organisations to meet the fiduciary standards (Fonta et al., 2018; 43 Omari-Motsumi et al., 2019). 44 45 It has been proposed that, as middle-income countries can leverage mitigation finance from the private 46 sector, targeting scarce public finance towards LDCs and SIDS may be necessary to ensure sufficient funds 47 reach these countries (Steele, 2015). Matching domestic climate spending with international support is one 48 way to ensure LDCs get the funds they need (Grasso, 2010b; Bird, 2014). Targeting specific marginalized 49 communities and women within countries can also help make climate finance more effective and fairer, such 50 as the Asian Development Bank's efforts to make lending portfolios more inclusive and pro-poor (ADB, 51 2018). 52 53 Post-COVID recovery packages, debt relief and finance for adaptation and resilience 54 55 Recent literature has highlighted the opportunity that COVID recovery packages offer for environmentally 56 sustainable, low carbon and climate resilient economic growth (Forster et al., 2020; Hepburn et al., 2020; 57 Hanna et al., 2021). Assessment of whether this is indeed happening is limited, although the few available Do Not Cite, Quote or Distribute 17-69 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 studies suggest that that this opportunity is not being realised in many nations (O'Callaghan and Murdock, 2 2021; VIVID Economics, 2021). One study of the G20 and 10 other nations suggested that stimulus 3 packages would have net negative environmental impact in two thirds of these countries (VIVID Economics, 4 2021), while another showed that around half of G20 recovery investment targeted at energy has had gone 5 towards fossil fuels, rather than to cleaner energy sources (Dibley et al., 2021). 6 7 Concerns have also been raised about the interactions between debt service, COVID economic recession and 8 post COVID recovery in developing countries (Simmons et al., 2021; Volz et al., 2021). Debt service grows 9 as a proportion of national budget during recession, reducing scope for investment in recovery, is a self- 10 reinforcing cycle. It has been suggested that linking debt-relief to Paris-aligned objectives can act as an 11 additional source of climate finance (Fenton et al., 2014). The G20 has begun addressing this debt crisis 12 through its Debt Service Suspension Initiative and the Common Framework for Debt Treatments (IMF, 13 2020). It has been suggested that these initiatives could be expanded to prioritize climate-focused debt-relief 14 instruments and to include more countries (Steele and Patel, 2020; Volz et al., 2021). If debt-relief is used to 15 invest in national instrument for green and inclusive recovery, national ownership of the use of the finance 16 can occur, avoiding some of the negative connotations of historical debt restructuring (Volz et al., 2021). 17 18 [END CROSS-CHAPTER BOX FINANCE HERE] 19 20 21 17.4.4 Enabling Condition 3: Knowledge and Capacity 22 23 17.4.4.1 Overview of Knowledge Systems 24 25 AR5 emphasized the importance of knowledge systems as an enabling condition for decision making, as did 26 earlier ARs, all of which include a focus on the policy-relevance of knowledge (Section 1.1.4) First 27 introduced in IPCC reports in AR4, the term "knowledge system" is used extensively in AR5 and the SRs. 28 The discussion below follows a widely-cited definition of knowledge systems as sets of interacting "agents, 29 practices and institutions that organize the production, transfer and use of knowledge" (Cornell et al., 2013: 30 61). This definition emphasizes the social nature of knowledge and the importance of the link between 31 knowledge and action, rather than presenting knowledge simply as information about past, present and future 32 states of the world which can be of use to decision-makers. 33 34 This definition of knowledge systems indicates the importance of capacity--the ability and the motivation to 35 use knowledge for action--since capacity is an important feature which allows knowledge systems to 36 function. Capacity is a necessary enabling condition for knowledge to be put to use in adaptation activities 37 (high confidence), as shown across sectors such as water (Section 4.5.2), food security (Sections 5.12.3, 38 5.14.3), cities and settlements (Sections 6.4.2, 6.4.4) and health and well-being (Sections 7.1.3, 7.2.6), and 39 across regions, including Africa (Sections 9.13.1, 9.14.5), Asia (Sections 10.3.6, 10.4.4) and North America 40 (Section 14.4.5). 41 42 Some research on knowledge systems retains the earlier attention to information as a resource for decision- 43 makers. A major focus, discussed elsewhere in this chapter, has been increasing the precision about the 44 certainty, likelihood, and the confidence with which certain statements are made in relation to underlying 45 evidence (See Cross-Chapter Box DEEP in this Chapter). This topic, which was first introduced in AR4, 46 advanced significantly in AR5 (Mach et al., 2017). 47 48 In addition to these characteristics of information, the social and organizational aspects of knowledge 49 systems have also been the subject of recent research. One strand of this discussion emphasizes the 50 distinctiveness of different knowledge systems, often focusing on three types of knowledge: scientific, 51 Indigenous, and local, and the latter two sometimes grouped as "traditional" knowledge (See Cross-Chapter 52 Box INDIG in Chapter 18). This strand emphasizes the specific forms of knowledge production and 53 circulation in each type. Another strand of discussion emphasizes the networks of interactions between 54 different groups. This strand follows the influential "Knowledge systems for sustainable development" (Cash 55 et al., 2003), which was cited in Chapter 2, 7 and 8 in WGII AR5; Cash et al. (2003) emphasizes the usability 56 and acceptability of scientific knowledge, and underscores the relations between knowledge producers and Do Not Cite, Quote or Distribute 17-70 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 users. The discussion in 17.4.4 on knowledge as an enabling factor integrates these two strands of discussion 2 of knowledge systems. 3 4 It was well established in AR5 and SRs that a component of knowledge systems for good climate decision- 5 making is the production of "information on climate, its impacts, potential risks, and vulnerability" which 6 can "be integrated into an existing or proposed decision-making context" (Jones et al., 2014: 200). Also 7 important are two other components of knowledge: of response options and knowledge of other enabling 8 conditions, particularly governance and finance, which were mentioned less frequently and more indirectly 9 in AR5 and SR1.5, SROCC and SRLAND. Decision-makers assess the feasibility of different alternatives 10 (see Cross-Chapter Box FEASIB) and develop strategies for the implementation and modification of the 11 alternative, requiring a level of knowledge of the governance, policy and finance landscapes at national 12 (Tanner et al., 2019; Lopes et al., 2020; Roberts et al., 2020) and international scales (Woodruff, 2018). 13 14 Examples of the importance of these other two components--knowledge of response options and knowledge 15 of enabling conditions--are provided by networks of cities, including internal institutional networks (Aylett, 16 2015), intermunicipal networks (e.g., those supported by ICLEI- Local Governments for Sustainability and 17 the international United Cities and Local Governments (UCLG) network), transnational municipal networks 18 (e.g. 100 Resilient Cities, Asian Cities Climate Change Resilience Network (ACCCRN), and city to city 19 regional transdisciplinary learning networks (Ndebele-Murisa et al., 2020). These networks generate and 20 exchange knowledge which can be critical to decision-makers for understanding and evaluating the 21 feasibility of different response options, identifying synergies across sectors, and mainstreaming adaptation 22 to climate change (Haupt et al., 2020). However, the question of how to finance such network activities 23 remains under-studied (Bracking, 2021; See Box 17.3). 24 25 In addition to these general considerations of knowledge systems, research since AR5 has contributed to the 26 understanding of specific types of knowledge. Scientific knowledge is thoroughly discussed in Chapter 1, 27 especially in Section 1.3 Understanding and Evaluating Climate Risk, which shows recent advances in the 28 well-established IPCC categories of observation of past conditions and model-based projections of future 29 conditions. We add here a consideration of a new area within scientific knowledge, artificial intelligence, 30 which offers new methods for producing information that can be incorporated into knowledge systems. 31 32 Applying Artificial Intelligence (AI) to climate change is predominantly in the area of climate modelling and 33 forecasting, inclusive of weather extremes (Monteleoni et al., 2013; Jones, 2017; Huntingford et al., 2019). 34 Recent efforts conceptualize the potential uses of AI for mitigation and adaptation (Rolnick et al., 2019; 35 Cheong et al., 2020b) in addition to forecasting (Rolnick et al., 2019; Chattopadhyay et al., 2020; Cheong et 36 al., 2020b; Prabhat et al., 2021). There are very few cases to assess AI applications in these domains given 37 that AI is a new field for climate change impact and adaptation. To this date, sectoral applications of AI 38 relevant to climate change adaptation and risk reduction mainly have advanced in the areas of crop yields, 39 early warning system, and water management. 40 41 These sectoral advances using AI employ various learning techniques inclusive of supervised and 42 unsupervised learning, multimodal learning and transfer learning techniques to generate more accurate 43 predictions than afforded by traditional climate projection methods (Cheong et al., 2020b; Camps-Valls et 44 al., 2021). AI applications use finer resolution data such as sub-daily weather-related data, remote and 45 wearable sensor data, text data, and real-time survey data. They are fed into neural networks and 46 semi/unsupervised learning to configure detailed and more precise predictions of climate change impact on 47 crop yields (Crane-Droesch, 2018), early warning (Moon et al., 2019), impact of extreme heat on older 48 adults (Cheong et al., 2020a), poverty in Africa (Oshri et al., 2018), and multi-scale water management 49 combining blockchain technology with remote water sensors (Lin et al., 2018). 50 51 Indigenous knowledge and local knowledge are thoroughly covered in SROCC (Abram et al., 2019; IPCC, 52 2019c; IPCC, 2019e-b) and in Section 1.3.3. We here add relevant points to decision making, and an 53 additional form of knowledge, practitioner knowledge. 54 55 Indigenous knowledge and local knowledge are gaining recognition at multiple scales (Kleiche-Dray and 56 Waast, 2016; David-Chavez and Gavin, 2018; Nakashima et al., 2018). Of note is their association with 57 ecosystem-based adaptations, showcasing the long-term place-based knowledge of Indigenous peoples Do Not Cite, Quote or Distribute 17-71 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 (Johnson et al., 2015; Walshe and Argumedo, 2016; Carter, 2019; Mazzocchi, 2020). These knowledges and 2 practices can be an important enabling condition in decision making processes, complementing scientific 3 information by identifying impacts (Fern醤dez-Llamazares et al., 2017; Katz et al., 2020), emphasizing 4 values to consider (Huambachano, 2018), offering solutions (Chanza and de Wit, 2016; Cuaton and Su, 5 2020; Orlove et al., 2020), guiding land use and resource management (Brond韟io et al., 2021) and filling 6 gaps in scientific knowledge (Hiwasaki et al., 2014; Audefroy and S醤chez, 2017; Makondo and Thomas, 7 2018; Son et al., 2019; Latulippe and Klenk, 2020; Wheeler et al., 2020a). 8 9 Practitioner knowledge--the pragmatic, practice-based knowledge that comes from the regular exercise of 10 craft or professional work--was also acknowledged briefly in AR5 (Jones et al., 2014) and treated 11 significantly in SROCC (Abram et al., 2019). Practitioner knowledge resembles local knowledge in that it is 12 acquired through participation in activities, and yet it differs from local knowledge, which is often place- 13 based and tied directly to specific landscapes and communities. Local knowledge typically covers a variety 14 of environmental domains. Practitioner knowledge may be shared with people in different locations and is 15 often more focused on a narrower set of work activities. Recent calls have recommended bringing 16 practitioners more fully into the IPCC assessment process, to promote more effective decision-making 17 (Howarth et al., 2018). 18 19 Practitioner knowledge makes significant contributions to decision-making by broadening the range of 20 alternatives which are considered and by bringing in understandings of systems to the selection and 21 implementation of alternatives. Such knowledge is applicable to a large number domains, including 22 biodiversity management (Teng� et al., 2014; Rathwell et al., 2015), and natural hazard risk management in 23 urban settings, as reported in Denmark (Madsen et al., 2019), the US (Matsler, 2019), Canada (Yumagulova 24 and Vertinsky, 2019), Mexico (Aguilar-Barajas et al., 2019), and the Caribbean (Ramsey et al., 2019). Other 25 contexts, all at regional scales, include watershed management in Peru (Ostovar, 2019), livestock 26 management in Finland (Rasmus et al., 2020), agricultural adaptation in a context of water scarcity in Iran 27 (Zarei et al., 2020), and the water-energy nexus in the US (Gim et al., 2019). 28 29 Literature indicates the importance of effective governance for promoting integration of local and 30 practitioner knowledge with scientific knowledge (high confidence). This integration is most extensive, and 31 promotes a wider consideration of alternatives, where governance arrangements promote ongoing exchanges 32 of information and discussion of solutions, whether through formal mechanisms such as regional committees 33 (Gim et al., 2019; Ostovar, 2019; Rasmus et al., 2020; Zarei et al., 2020) or informal mechanisms such as 34 personal networks and local discussion groups (Madsen et al., 2019; Yumagulova and Vertinsky, 2019). 35 Where such arrangements are absent, practitioner knowledge is side-lined from the formulation and 36 implementation of decisions (Aguilar-Barajas et al., 2019; Matsler, 2019; Ramsey et al., 2019). 37 38 17.4.4.2 Co-production and Other Composite Knowledge Systems 39 40 There is strong evidence that composite knowledge systems � characterized by interactions between the 41 producers and potential users of climate change information -- can help facilitate climate-related decision 42 making (Prokopy and Power, 2015; Richards, 2018; Ramsey et al., 2019). Several institutional forms and 43 structures have been created to link scientific knowledge, Indigenous knowledge, and local and practitioner 44 knowledge, to climate change decision making. 45 46 17.4.4.2.1 Co-production 47 The co-production of knowledge by different actors provides important avenues for exchanging and 48 integrating climate-related knowledge in decisions made across society (high confidence). Though many 49 definitions of co-production have been offered in recent years (Bremer and Meisch, 2017; Vincent et al., 50 2018; Bremer et al., 2019; Harvey et al., 2019a), most describe a set of individuals or organizations who 51 work together to generate a set of products that entail new knowledge products and that guide action (Miller 52 and Wyborn, 2020). Some major forms of co-production include action research (Baztan et al., 2017; 53 Laursen et al., 2018; Zanocco et al., 2018a), trans-disciplinarity (Howarth and Monasterolo, 2016; Wamsler, 54 2017; Lanier et al., 2018; Scott et al., 2018; Knapp et al., 2019; Young et al., 2019a); rapid assessment 55 processes (Atkinson et al., 2018b); and participatory integrated assessments (Howarth et al., 2018; Krkoska 56 Lorencov� et al., 2018; Bitsura-Meszaros et al., 2019; Carter et al., 2019a; Cremades et al., 2019; Leitch et 57 al., 2019; Mart韓ez-Tag黣馻 et al., 2020; Section 17.3.1.3.1). Do Not Cite, Quote or Distribute 17-72 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Co-production promotes iterative dialogue, experimentation, the tailoring of knowledge to context, needs 3 and priorities, and learning, often promoting integration of Indigenous knowledge, local knowledge and 4 practitioner knowledge with scientific knowledge (high confidence). It generally entails long-lasting ties and 5 fully inclusive partnerships between different parties (Kench et al., 2018). Governance measures and 6 adequate financing can act as enablers of such co-production. This integration is most extensive, and 7 promotes a wider consideration of alternatives where governance arrangements promote ongoing exchanges 8 of information and discussion of solutions, whether through formal mechanisms such as regional committees 9 (Gim et al., 2019; Ostovar, 2019; Rasmus et al., 2020; Zarei et al., 2020) or informal mechanisms such as 10 personal networks and local discussion groups (Madsen et al., 2019; Yumagulova and Vertinsky, 2019). 11 Where such arrangements are absent, practitioner knowledge is side-lined from the formulation and 12 implementation of decisions (Orleans Reed et al., 2013; Aguilar-Barajas et al., 2019; Matsler, 2019; Ramsey 13 et al., 2019). 14 15 An important mechanism of co-production is the boundary organization, a knowledge-producing 16 organization comprised of individuals who reflect different disciplines or knowledge systems and who 17 represent different activities, sectors or forms of governance (Blades et al., 2016; Graham and Mitchell, 18 2016; Guido et al., 2016; Jeuring et al., 2019; Serrao-Neumann et al., 2020; Zarei et al., 2020). Boundary 19 organizations themselves can be linked into boundary chains (Lemos et al., 2014; Meyer et al., 2015; 20 Kirchhoff et al., 2015a; Pretorius et al., 2019; Daniels et al., 2020). When individuals and organizations from 21 different disciplinary backgrounds and missions coordinate their activities informally, the resulting ties have 22 been termed `knowledge networks' (Ziaja and Fullerton, 2015; Brugger et al., 2016; Guido et al., 2016; 23 Davies et al., 2018; Klenk, 2018; Muccione et al., 2019; Ziaja, 2019). When such networks interact with 24 each other, the resulting associations have been called "communities of practice," which can work to 25 collectively shape information to shared contextual circumstances (Orsato et al., 2018; Wang et al., 2019b). 26 27 There is extensive evidence that co-production can generate useful climate knowledge (Djenontin and 28 Meadow, 2018; Bisbal, 2019; Ryan and Bustos, 2019; Hewitt et al., 2020; Jack et al., 2020; Lavorel et al., 29 2020; Ruiz-Mall閚, 2020) and that it can increase the likelihood that knowledge will be used in decision- 30 making (Vogel et al., 2016; Prokopy et al., 2017; Skelton et al., 2017; Sylvester and Brooks, 2020). Co- 31 production is not without its costs, since it requires more time, money, facilitation expertise and personal 32 commitment from participants than more conventional modes of knowledge production (Lemos et al., 2018; 33 Sletto et al., 2019; Wamsler et al., 2019; Blair et al., 2020). Some research has shown ways to decrease the 34 costs of co-production for participants, such as funding and time to enable and sustain interactions and to 35 build trust and legitimacy, or to create boundary organizations (Young et al., 2016; Klenk et al., 2017). 36 37 Co-production is supported by project cycles that provide for the involvement of stakeholders from the 38 outset (Daly and Dilling, 2019; Brady and Leichenko, 2020); flexible research agendas that do not assume a 39 climate related question (Daniels et al., 2020); support for interactivity and reflexivity (Araujo et al., 2020), 40 and, institutionalizing incentives which address the different values, norms, perceptions and work patterns of 41 scientists, policy-makers and civil society representatives (Cvitanovic et al., 2015; Vincent et al., 2015; 42 Bruno Soares and Dessai, 2016; Singh et al., 2017; Djenontin and Meadow, 2018; Norstr鰉 et al., 2020; 43 Turnhout et al., 2020). Certain roles, such as policy entrepreneurs (Tanner et al., 2019), embedded 44 researchers (Pretorius et al., 2019) and knowledge brokers (Cvitanovic et al., 2015), can facilitate co- 45 production. 46 47 17.4.4.2.2 Climate services 48 Climate services (refer to CWG Box on Climate Services) can be important enablers of climate risk 49 management, provided they are credible, relevant and usable (high confidence), and will become 50 increasingly important as human influence on weather and climate extremes grows across all regions 51 (Chapter 11; Fischer et al., 2021; IPCC, 2021). Climate services are more effective and more widely used 52 when they are tailored to specific decisions and decision-makers (high confidence). Sustained iterative 53 engagement between climate information users, producers and translators can improve the quality of the 54 information and the decision-making and avoid maladaptation (medium confidence). 55 56 Historically, climate services have been organized by climate information providers, based in 57 meteorological, hydrological, and agricultural faculties and services, serving to improve through climate risk Do Not Cite, Quote or Distribute 17-73 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 management, including the use of historical information, monitoring, seasonal forecasts, and long-term 2 climate projections (Hewitt et al., 2012; Blome, 2017; Bessembinder et al., 2019; Vaughan et al., 2019b). 3 4 Recent research on climate services shows that transdisciplinary knowledge co-production is a key enabler, 5 starting to shift emphasis from the creation of climate services products to climate services processes 6 (Vincent et al., 2018; Carter et al., 2019b; Daniels et al., 2020), potentially increasing uptake and 7 sustainability (Norstr鰉 et al., 2020). This shift is a result of the recognition of benefits which a co- 8 production approach can offer, in addition to the provision of information; information; these additional 9 benefits include building confidence, capacities, learning, knowledge, social capital, institutional capacity, 10 stakeholder relationships, social networks, beneficial management practices, and strengthened institutions 11 (Bruno Soares and Dessai, 2016; Djenontin and Meadow, 2018; Bremer et al., 2019). 12 13 Cross-Chapter Box 12.2 in WGI AR6, Climate information for climate services, shows that users are widely 14 distributed across civil society. Relevant users of climate services include humanitarian organizations 15 (Coughlan de Perez and Mason, 2014; Harvey et al., 2019b), government offices (Mahon et al., 2019), 16 international agencies (Perkins and Nachmany, 2019), and the private sector (Beckett, 2016; Hudson et al., 17 2019). Climate services currently exist at local, national, regional, and international scales, at time scales 18 which range from sub-seasonal to decadal and longer (White et al., 2017; Hewitt et al., 2020) and in a range 19 of different sectors (Bruno Soares and Buontempo, 2019). Agriculture is the sector with the largest number 20 of examples (Zebiak et al., 2015; Burke and Emerick, 2016; Cliffe et al., 2016; Haigh et al., 2018; 21 Buontempo et al., 2020); others include health (Ghebreyesus et al., 2010; Ballester et al., 2016), forestry 22 (Caurla and Lobianco, 2020), fisheries (Busch et al., 2016), disaster risk reduction (Street et al., 2019), and 23 water resources management (van Vliet et al., 2015; Golding et al., 2019). Evaluations of the extent to which 24 climate services are accessed, used, and deliver benefits to decision makers remain in an initial stage 25 (Perrels, 2020), though studies suggest that these contributions vary widely depending on context. A review 26 of evaluation of weather and climate agricultural services in Africa, for instance, found that most farmers use 27 climate services when they are available , but that on-farm outcomes varied, with some farmers 28 experiencing yield losses and others gains upward of 60% (Vaughan et al., 2019a). Other studies express 29 concern that large climate service projects have run for decades at significant expense, without adequate 30 evaluation at all (Gerlak et al., 2020). 31 32 Recent reviews (Carr and Onzere, 2018; Hewitt et al., 2020) provide evidence that the use of climate services 33 is affected by (a) the quality, reliability and skill of the climate information (Zebiak, 2019); (b) the fit, 34 tailoring and contextualization of that information with respect to the specific decision-making needs of 35 particular users (Clarkson et al., 2019); (c) the mode and method by which the service is communicated 36 (Golding et al., 2017); and (d) the characteristics of the users themselves � including the users' access to 37 resources that would allow them to alter their decisions based on the information provided (Clarkson et al., 38 2019). 39 40 A related literature characterizes the extent to which the development, reach and effectiveness of climate 41 services is affected by factors that can be termed `climate service governance' (Stegmaier et al., 2020). 42 Elements of this governance include the arrangements by which those parties engage with each other 43 (Vaughan et al., 2016; Daniels et al., 2020) and the financial arrangements, and associated responsibilities, 44 which support the service (Louren鏾 et al., 2015; Bruno Soares and Buontempo, 2019). Though governance 45 varies by context, evidence suggests that engaging a range of experts and potential users in the co-design and 46 co-production of climate services increases the use and utility of services (Lemos et al., 2014; Pope et al., 47 2017; Masuda et al., 2018; Harvey et al., 2019b). However, some studies warn that even with broad and 48 inclusive participation, power differentials can create barriers to co-production reducing the usefulness 49 information products (Alexander et al., 2020) and the neglect of non-meteorological sources of information 50 which may also possess useful predictive power (Coughlan de Perez et al., 2019). 51 52 A small but growing number of papers consider the business models that support climate services, 53 including, for instance, the role of open data (Iturbide et al., 2019; Chimani et al., 2020), the standards or 54 institutional mandates by which users come to understand the credibility and legitimacy of certain services 55 (Bruno Soares and Buontempo, 2019), and the role of public-private partnerships (Cortekar et al., 2020). 56 While the commercialization of climate services holds significant promise that more and more specifically 57 targeted services will be provided, there is not yet agreement on which business models best support this in Do Not Cite, Quote or Distribute 17-74 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 different contexts. There is also concern that commercialization of climate services may disadvantage under- 2 resourced actors at the expense of wealthier or more powerful ones (Webber, 2017; Webber and Donner, 3 2017; Cortekar et al., 2020). It has been noted that some climate services, such as weather forecasts and early 4 warnings, are an example of a public good, best provided by public agencies (high confidence) (Sutter, 2013; 5 Kitchell, 2016; Hansen et al., 2018). 6 7 17.4.4.2.3 Capacity and motivation within knowledge systems 8 Knowledge of climate change influences decision-making not only by providing information but also by 9 increasing the motivation to act and by promoting behaviour change. Evidence from many sectors (including 10 water (4.5.2), ocean and coastal ecosystems (3.6.2), and agriculture (5.4.2) and regions (including Africa 11 (9.8.4), Asia (10.4.6), and North America (10.4.5) show that building capacity (e.g. adaptive capacity, 12 institutional capacity, education/training in human capacity) can support adaptation and limited governance 13 capacity can constrain it (high confidence). An emerging area of research examines the contribution of 14 building capacity within public and technical organizations and agencies to draw on Indigenous knowledge 15 and local knowledge (Adger et al., 2017; Hochman et al., 2017; Bacud, 2018). A number of factors influence 16 the effect of knowledge on motivation and behaviour change, including values and education. 17 18 Decision-makers who shape options for managing climate risk can evaluate stakeholders' capacities and 19 motivations to participate in the implementation process of these options. Stakeholder engagement in climate 20 change risk management supports successful adaptation (Gray et al., 2014; Elsawah et al., 2015; Siders, 21 2017; Giordano et al., 2020). Research in psychology and related fields shows that the cognitive mechanisms 22 by which individuals and organizations process climate information influence this capacity, motivation and 23 engagement (Grothmann and Patt, 2005; Grothmann et al., 2013; Masud et al., 2016; Nelson et al., 2016; 24 Takahashi et al., 2016; H黦el and Davies, 2020; Grothmann and Michel, 2021). 25 26 The perception of climate change as a major threat that requires action has increased since AR5, reflecting 27 both the growth of information about climate change and the processing of that information (Lee et al., 2015; 28 Fagan and Huang, 2019). Global social movements play an important role in raising public awareness of 29 climate urgency (Thackeray et al., 2020). Climate change concern plays an important role in decision- 30 making outcomes which entail public participation (Lammel, 2015; Chiang, 2018; van Valkengoed and Steg, 31 2019; Arikan and G黱ay, 2020). Nonetheless, public risk perception varies sharply on spatial and temporal 32 scales, reflecting environmental changes, social influences (Kousser and Tranter, 2018; Rousseau and 33 Deschacht, 2020), economic capacities (Arikan and G黱ay, 2020) and culture (Noll et al., 2020), as well as 34 individual characteristics (van Valkengoed and Steg, 2019). The importance of values and norms is 35 demonstrated by recent research which highlights how intrinsic motivation (altruistic, self-transcendental and 36 ecocentric values) (Corner et al., 2014; Braito et al., 2017; Xiang et al., 2019; Bouman et al., 2020) and 37 extrinsic social motivation (e.g., economic gains and social desirability) (van Valkengoed and Steg, 2019) 38 can drive action. 39 40 Recent research shows the importance of education as a predictor of risk perception, motivation and action. 41 Education level is the strongest predictor of public awareness of climate change risk in a study across 119 42 countries of public awareness of climate change risk (Lee, 2015), though this relationship varies in different 43 nations, and is influenced by mediating variables (Muttarak and Chankrajang, 2015; Blennow et al., 2016) 44 (Ballew et al., 2020). Knowledge and awareness of climate change are correlated with the motivation to 45 undertake action on climate change (Hornsey and Fielding, 2017). The integration of climate science in 46 educational curricula has been shown to be effective (Hess and Maki, 2019; Molthan-Hill et al., 2019), 47 including approaches such as integration of the complex system approach (Jacobson et al., 2017), 48 experiential climate change education (Siegner, 2018), including climate games (O'Garra et al., 2021; 49 Pfirman et al., 2021), massive open online courses , and informal science learning centres (Geiger et al., 50 2017). 51 52 Attention to behavioural change of individuals has grown since AR5, including cases which address both 53 adaptation and mitigation (e.g. dietary changes, modification of buildings, transport alternatives) (Azadi et 54 al., 2019; Fischer, 2019; Willett et al., 2019; Sharifi, 2020; Sharifi, 2021). The interventions to promote 55 behavioural change can be bottom-up, initiated by individuals, communities, non-governmental 56 organizations or the private sector, or top-down, coming from governments at various levels (Robertson and 57 Barling, 2015; Stern et al., 2016). They are supported by a number of mechanisms, including education, Do Not Cite, Quote or Distribute 17-75 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 information strategies, and campaigns, financial incentives, regulatory processes and legislation (Rosenow et 2 al., 2017; Creutzig et al., 2018; Carlsson et al., 2019). These behavioural changes contribute significantly to 3 effective risk management. 4 5 17.4.5 Enabling Condition 4: Catalysing Conditions 6 7 A clear difference between enabling conditions and catalysing conditions is emerging in the climate 8 mitigation literature (Hermwille et al., 2019; Michaelowa et al., 2021), with some examples in the adaptation 9 literature as well (Madsen et al., 2019; Booysen et al., 2019a; Bolorinos et al., 2020). Though enabling 10 conditions are necessary preconditions that allow response options to be formulated and implemented, their 11 presence alone does not guarantee that these response options will occur in a timely fashion or at a scale 12 commensurate with the risk, or even that they will occur at all. Catalysing conditions address this deficit in 13 advancing action. They serve to overcome the inertia that often operates as a barrier to action and motivate 14 individuals and organizations to initiate or accelerate action. Different forms of catalyzing conditions, 15 described below, lead individuals and organizations to weigh more seriously the costs of delaying action or 16 keeping action at low levels. Catalysing conditions focus the attention of individuals and organizations on 17 particular risks, leading actors to augment their decision-making processes and to allocate financial and 18 social resources to respond to those risks. This attention and deliberation can lead to more frequent and 19 potentially substantial adaptations, whether through more extensive action on existing forms of adaptation or 20 through the adoption of entirely new adaptations (Bolorinos et al., 2020). 21 22 The first two catalysing conditions described below address the costs of delaying action. Urgency increases 23 the awareness of individuals and organizations of such costs, while windows of opportunity, including 24 extreme events, are time-bound periods during which certain actions are possible, but after which they are 25 more difficult or impossible. The other two conditions stimulate new forms or levels of action by promoting 26 or directing step changes from one policy or management regime to another (Solecki et al., 2017). Litigation 27 over adaptation issues, for example, can open new lines of action or close off old ones, while catalysing 28 agents advance action through a variety of means (e.g., communicating the urgency of climate action, 29 revising agendas for action, expanding coalitions which undertake action). As detailed below, these four 30 catalysing conditions can operate together as well as separately to promote more prompt and extensive 31 adaptations. 32 33 17.4.5.1 Urgency 34 35 Urgency can catalyse action for individuals and organizations. A moderate level of urgency serves as an 36 important driver of climate action, but both high and low levels of urgency impede response (high 37 confidence). Wilson and Orlove (2021) review five experimental and twenty observational papers that 38 examine the relationship between urgency and levels of response in climate decision-making, across a range 39 of settings: from individuals and households, to communities, managed ecosystems, sub-national regions and 40 international river basin. Urgency in the papers is defined primarily through objective and subjective time 41 pressure, including the recognition of the costs of delaying action and the importance of using windows of 42 opportunity during which new forms and higher levels of response are possible. All the experimental papers 43 and all but three of the observational papers provide support for an inverted U-shaped relationship between 44 urgency and response intensity (including motivation and action), with higher levels of response at 45 intermediate levels of urgency and lower levels of response at low or high levels of urgency (Figure 17.8). 46 The general shape of this relationship also is supported for other decision domains by a well-established line 47 of research within psychology (Heitz, 2014; Zakay, 2014; Prem et al., 2017). 48 49 Do Not Cite, Quote or Distribute 17-76 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Figure 17.8: A moderate level of urgency serves as an important driver of climate action, but both high and low levels 3 of urgency impede response [derived from Wilson and Orlove (2021)]. 4 5 6 The synthesis of the studies on urgency offers two central lessons for policy makers, community groups, and 7 others involved in addressing climate change. First, that greater levels of response to climate change-induced 8 challenges can be motivated by communication strategies that move decision makers from low to moderate 9 levels of urgency (high confidence). In the case of drought, a number of studies show that urgent messages 10 promote water conservation, especially when these messages are repeated, perceived as trustworthy, and 11 linked to concrete suggestions for action (Gonzales and Ajami, 2017; Joubert and Ziervogel, 2019; Kam et 12 al., 2019; Booysen et al., 2019a; Booysen et al., 2019b; Bolorinos et al., 2020). These effects are also 13 demonstrated in experimental studies of adaptation planning in contexts including European flood 14 preparations (Madsen et al., 2019; Pot et al., 2019), and Pacific Island coastal planning (Donner and Webber, 15 2014). 16 17 Second, very high levels of urgency are a barrier to effective action (medium confidence), because last- 18 minute actions to reduce risk during crises can create haste and panic, often leading to insufficient 19 deliberation. In these cases, decision-makers fail to consider a full range of alternative actions, make rash 20 choices and poorly mobilize available resources (Asfaw et al., 2019; Robins, 2019; Gee, 2020). Given that 21 climate decision makers in many regions and sectors are experiencing greater pressure to act; this finding 22 suggests the existence of windows for planning and action during which climate risks have led to moderate 23 levels of urgency, but before these risks have resulted in urgency exceeding some upper threshold (see 24 17.4.5.2). 25 26 In addition, these studies point to potential weaknesses as well as strengths in strategic communication to 27 modulate urgency. Such messages may instead lead to lower levels of response if they induce very high 28 levels of urgency (Asfaw et al., 2019), though this effect may be somewhat mitigated by messages that 29 simultaneously increase recipients' sense of self-efficacy or they are experienced in the specific risk domain 30 discussed in the messages (Bodin et al., 2019). Future research on the relationships between urgency and 31 effective risk management could help refine the measurement of urgency, how the relationship varies in 32 different contexts, the role of different forms of messaging about urgency and action (Fesenfeld and 33 Rinscheid, 2021), as well as the effects of urgency on decision-making by high-level decision-makers within 34 polities and by climate social movements. 35 36 17.4.5.2 Windows of Opportunity 37 Do Not Cite, Quote or Distribute 17-77 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Windows of opportunity are time-bounded periods during which conditions are present for advancing and 2 often accelerating climate adaptation strategies. They can act as significant catalysing conditions for climate 3 action and are connected to a range of possible outcomes from small incremental shifts to larger scale more 4 profound transformation adaptations (Novalia and Malekpour, 2020). 5 6 Windows can open because of extreme weather events (Birkmann and Fernando, 2008), political shifts, such 7 as new institutions, new laws and regulations, and presence of a new policy entrepreneur or new policies 8 (Haasnoot et al., 2013; Bell and Morrison, 2015), relevant and achievable policy goals, and emergence of 9 new knowledge (Abunnasr et al., 2013), and close after the initial causes recede and become less efficacious. 10 They also serve as focusing events whereby a coalition of groups address specific policy questions or 11 response options (Rudel, 2019). Recognizing that windows of opportunity often catalyze action does not 12 mean that action outside such windows is insignificant or impossible. 13 14 Extreme events such as disasters often act as proximate drivers of windows of opportunity (Birkmann and 15 Fernando, 2008; McSweeney and Coomes, 2011). Climate disasters in a specific location become significant 16 windows for new debate, policymaking and financing (McSweeney and Coomes, 2011). Extreme events also 17 can facilitate change at locations distant from the most impacted site when remote actors gain perspective on 18 their own risks (Friedman et al., 2019; Solecki et al., 2019). Factors that facilitate extreme events driving 19 proactive as opposed to reactive responses include access to relevant risk and vulnerability data, pre-existing 20 experience with similar events, and appropriate governance (Brown et al., 2017a). Page and Dilling (2020) 21 find that worldview or ideology plays a central role in sense-making and in shaping what organizational 22 decision-makers `see' in terms of acceptable actions in response to an extreme event. 23 24 Significant variation is present across the mix and intensity of conditions that promotes action through a 25 window of opportunity. Capacity to respond to is a function of the presence of enabling conditions as well as 26 tools and methods to aid decision-making (Shi et al., 2015). Political activism provides windows of 27 opportunity for climate adaptation (Lauer and Eguavoen, 2016; see also 17.4.5.3.1). 28 29 Sudden shifts in institutions and legal framework can also catalyse climate action. For example, the year 30 2015 included a series of international frameworks such as the Sendai Framework for Disaster Risk 31 Reduction 2015-2030 (van Niekerk et al., 2020; Hofmann, 2021), the 2030 Agenda for Sustainable 32 Development, which established the Sustainable Development Goals (Sanchez Rodriguez et al., 2018), and 33 the Paris Climate Agreement, which dramatically enhanced the promotion and implementation of altered the 34 conditions under which climate adaptation occurred. 35 36 17.4.5.3 Climate Litigation on Adaptation 37 38 Litigation for loss and damage from climate change was first noted as a potential motivator for emissions 39 reduction in AR4 and AR5 noted that litigation was pending but not tested and that while legal systems were 40 beginning to define the boundaries of responsibility for climate change, it was `unclear liability exists'. The 41 SR1.5 (IPCC, 2018a) reported, with high confidence, that litigation risks of government and business had 42 increased and the SRCCL (IPCC, 2019b) noted that recent developments in climate attribution improve the 43 ability to detect human influence on climate and broaden liability. 44 45 Since AR5 there has been growing recognition of the potential of litigation for failure to take measures to 46 adapt to climate change to drive climate risk management (Banda and Fulton, 2017; Peel et al., 2017; 47 Bouwer, 2018). Litigation cases on adaptation and loss and damage comprise about one third of those 48 covered in the literature (Setzer and Vanhala, 2019a). Reasons for this growth are: (i) the growing gap 49 between projected climate change impacts and current adaptation efforts (Stezer and Byrnes, 2019) and (ii) 50 expanded legal duty of government, business, and others to manage foreseeable harms (Marjanac and Patton, 51 2018). Climate change litigation is expanding geographically into the Americas, Asia (and the Pacific 52 region), and Europe with several cases brought in low- and middle-income countries (Stezer and Byrnes, 53 2019) (See Table 17.7). 54 55 Lawsuits against private entities contribute to articulating climate change as a legal and financial risk 56 (medium confidence) (Peel and Osofsky, 2015; Ganguly et al., 2018; McCormick et al., 2018; Peel and Do Not Cite, Quote or Distribute 17-78 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Osofsky, 2018). Even if unsuccessful, Estrin (2016) concludes they are important in underlining the high 2 level of public concern. 3 4 Climate-related, legal, financial disclosure requirements are improving investment decision making of 5 corporations as well as augmenting ex post liability for failure to consider climate change risk in decision 6 making. Organizations are required to disclose governance around climate related risks (impact of climate 7 change on businesses, products, services, supply or value chain, adaptation and mitigation activities, 8 investment in research and development and operations). This functions as a vehicle for identifying 9 climate-related risk and the organization's resilience strategy taking into consideration different climate- 10 related scenarios including a 2癈 or lower scenario (Sarra, 2018). Institutions such as the G20 (Carney, 11 2019), the American Bar Association (Brammer and Chakrabarti, 2019), the European Commission (Zadek, 12 2018) have adopted or endorsed these standards. 13 14 15 Table 17.7: Examples of types of climate-related litigation Litigation Type Detail and Examples Supporting Literature Challenge government Challenging government or administrative planning (Banda and Fulton, decisions for not considering decisions for failure to consider, or adequately address, 2017; Peel et al., climate change risks climate change in relation to developing and protecting 2017; Bouwer, 2018; coastal zones, water stressed regions, flood prone areas, or Clarke and Hussain, decisions affecting endangered species whose habitat is at 2018) risk. For example, the Victorian Civil and Administrative Tribunal in Australia rejected a planned housing project in a coastal area, citing the risks from climate change (Gippsland Coastal Bd. v. South Gippsland Sc & Ors (No2), 2008). Petitions to act Constitutional petitions to force governments to take (Banda and Fulton, adaptation measures. As an example, in Leghari v. 2017; Ashgar Leghari Pakistan a farmer initiated public interest litigation against v. Federation of federal and provincial governments for failure to develop Pakistan, April 2015; climate change resilience through adaptation to floods, Ashgar Leghari v. droughts and other impacts because it violated his rights to Federation of life and dignity. The High Court of Lahore found for Mr. Pakistan, September Leghari and created a commission to develop and 2015) implement a wide range of adaptation actions. Regulatory proceedings Environmental groups and city and state officials (Consolidated Edison intervened in the application of the electric utility serving Co., 2019) Failure to act by public New York City, Consolidated Edison Company, to the authorities New York State Public Service Commission for a rate increase. The intervenors argued that the company was not Failure by private sector to adequately preparing for flooding, heat waves and other consider climate change climate-related impacts. As a result, the Commission directed the company to undertake a study of its vulnerability to climate change, and write and implement a plan to address these risks. Liability of public authorities for failure to undertake (Banda and Fulton, necessary adaptation actions to avoid damage to life or 2017; Peel et al., property especially where statutory framework is proven 2017; Bouwer, 2018) ineffective or out of step with international commitments; in some areas these are class action suits. An example is private lawsuits for failure of a built environment to consider adaptation needs in a built environment (energy efficiency works, overheating because of increased temperatures). Examples include: (i) A citizen suit against ExxonMobil (Benjamin, 2017; for failure to adapt Everett Terminal to the impacts of Stezer and Byrnes, Do Not Cite, Quote or Distribute 17-79 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report adaptation in their business climate change including increased precipitation, sea level 2019; Street and Jude, practice rise and storm surges occurring with increasing frequency; 2019; Wasim, 2019; (ii) A citizen suit against. Shell Oil Products US alleging Conservation Law Shell failed to incorporate climate risks in its investment in Foundation v. Exxon a bulk storage and fuel terminal in Rhode Island, USA; Mobil Corporation, (iii) Shareholder action against ExxonMobil for failure to 2021) report climate risks or complying with recommendations to do so and for issuing misleading corporate disclosure relied on by investors; (iv) A suit brought an NGO, the Conservation Law Foundation, against Exxon Mobil alleging that the company had taken insufficient precautions to protect a major oil tank farm near Boston, USA, from coastal storms that are worsened by climate change, creating a danger of an oil spill into Boston Harbour. The U.S. Court of Appeals for the First Circuit ruled in 2021 that the lawsuit could proceed, and that the NGO could attempt to make out its case that Exxon Mobil should take greater precautions.; (v) Government and citizen claims for public nuisance against fossil fuel companies for the costs of adaptation such as infrastructure to protect against sea level rise. Youth public trust claims Government inter-generational liability for inadequate (Schneider et al., climate change mitigation and adaptation efforts. Our 2017; Bouwer, 2018) Children's Trust (a non-profit organization) and others brought an action against the United States and several executive branch individuals in 2015 claiming damages for their loss of the environment and the defendant's failure to preserve a habitable climate system. Similarly, a public trust claim could be brought in a coastal town for failure to adapt to climate change. Human rights claims Human rights may be a powerful tool for organizing and (Hall and Weiss, unifying adaptation decision making, especially for the 2012; Peel and most vulnerable, through enforcement mechanisms of Osofsky, 2018; Setzer progressive realization as well as ex post liability (see and Vanhala, 2019b; Chapter 8). For example, a persons' right to food implores Stezer and Byrnes, state parties to take necessary actions to alleviate hunger 2019) caused by climate change; during natural and other disasters rights to water, and life are impacted; sea-level rise and storm surges impact many coastal settlements and the right to adequate housing and an adequate standard of living. This is in part due to increasing acceptance of the impact of climate change on health, livelihoods, shelter and fundamental rights. 1 2 3 17.4.5.4 Catalysing Agents 4 5 Individuals and organizations often serve as catalysing agents of climate risk decision-making. They promote 6 greater levels of new forms of climate action by communicating the urgency of climate action and by 7 developing coalitions which undertake action. Agents include individuals, organisations or collectives, or 8 multiple organizations linked together. 9 10 17.4.5.4.1 Social movements and other mobilizations 11 Recent studies of climate-related social movements show that they can act as catalysing agents which 12 promote action to manage climate-related risks (medium confidence). However, these studies use varying 13 definitions of climate movements within the broader context of environmental movements. A prominent 14 topic of research is the rapidity and the large scale of the proliferation of these movements around the world, 15 primarily in urban settings but also in rural and Indigenous contexts (Claeys and Delgado Pugley, 2017). Do Not Cite, Quote or Distribute 17-80 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 These movements usually focus on climate mitigation but sometimes include adaptation. Their social bases 3 include groups which had not previously been active in climate politics, notably children and youth, as well 4 as sectors with long traditions of environmental activism, such as women and Indigenous peoples (see Cross- 5 Chapter Boxes GENDER and INDIG in Chapter 18). Much of the literature on youth movements traces the 6 emergence of the movements themselves (Sanson et al., 2019; Treichel, 2020), their framings of climate 7 change as a social justice issue (Holmberg and Alvinius, 2019) and their presence in demonstrations and on 8 social media (Boulianne et al., 2020). Climate action catalysed by youth and other climate movements 9 include visible international events such as the signing of Declaration on Children, Youth, and Climate 10 Action at COP25 in Madrid 2019 (Han and Ahn, 2020), as well as national efforts, including lawsuits, and 11 local events such as in tree-planting and waste reduction initiatives (Bandura and Cherry, 2019). 12 13 A recent review examines 2743 cases around the world of mobilizations for environmental justice causes 14 (Scheidel et al., 2020); roughly half the cases occurred between 1970 and 2007, and half between 2008 and 15 2019. Of these environmental mobilizations, 17% are directly related to climate and energy, and others are 16 related to climate-sensitive issues (15% for biomass and land use, 14% for water management). This study 17 reports the proportion of positive outcomes for different strategies, defined as meeting the goals of the 18 movements, which generally align with climate adaptation and sustainable resource management. These 19 rates vary from 10% for negotiated solutions to 34% for court decisions. It notes the corresponding higher 20 rates of failure, as well as the costs borne by the movements, which include criminalization (20% of cases), 21 violence (18%) and assassination (13%). These costs are significantly higher for Indigenous communities 22 that engage in these mobilizations. 23 24 At a global scale, climate movements succeeded in pressing for the greater recognition of the importance of 25 Indigenous knowledge within international agreements (Tormos-Aponte and Garc韆-L髉ez, 2018) but did 26 not achieve the major reforms of climate finance which they sought (Khan et al., 2019a); these differing 27 outcomes reflect the sensitivity of the issues and the formation of coalitions which supported or opposed the 28 movements. At national and local scales, one review of US cases reports limited effectiveness of climate 29 movements because of the ability of governmental agencies to coopt them (Pulido et al., 2016), while 30 another review in Pakistan shows a number of successes, because the movements were able to build alliances 31 with other public sector and community groups (Shawoo and McDermott, 2020). 32 33 17.4.5.4.2 Policy leaders and entrepreneurs 34 Policy leaders, often described as policy entrepreneurs within the scholarly literature, are individuals in 35 positions of leadership who set agendas and build coalitions to drive decision-making processes, and hence 36 can function as catalysers of climate adaptation (Petridou and Mintrom, 2020). Political leaders who have 37 taken on climate change as a key policy issue function as policy entrepreneurs at international, national and 38 sub-national levels. City officials including mayors and other executives often play the role of climate policy 39 entrepreneurs, while the absence of effective leadership negatively affects adaptation success (Becker and 40 Kretsch, 2019). Such entrepreneurs can be important forces for change in both reactive contexts following an 41 extreme or focusing event and in proactive context. They can be effective especially in contexts where they 42 navigate and link together formal and informal networks of complex climate governance systems (Tanner et 43 al., 2019). Their capacity to act has been increased when they and their institutions are embedded within 44 partnership networks (Bellinson and Chu, 2019). It is in these contexts that the leadership and position of a 45 policy entrepreneur becomes even more catalytic when operating at the interface of formal and informal 46 networks (Mintrom, 2019; Stone, 2019). 47 48 Sub-national actors and city officials including mayors and other executives are among the individuals most 49 often described and assessed as climate policy entrepreneurs (Kalafatis and Lemos, 2017). City level climate 50 policy entrepreneurs often operate using their own experience, connections, and persistence to address issues 51 of importance to their constituency. Climate risk concerns are often inherently local and in turn local 52 decision-makers perceive it being appropriate to engage. Conversely, the absence of effective leadership 53 negatively affects adaptation success (Kalafatis and Lemos, 2017; Becker and Kretsch, 2019). Urban climate 54 policy entrepreneurs operate in four key spheres of policy development and implementation: attention and 55 support seeking strategies; linking strategies (e.g., coalition building); relational management strategies (e.g., 56 networking and trusting building); and arena strategies including timing (Brouwer and Huitema, 2018). The 57 presence and operation of urban climate policy entrepreneurs is positively associated in settings with Do Not Cite, Quote or Distribute 17-81 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 multiple jurisdictions and across differing spatial scales (Kalafatis and Lemos, 2017; Renner and Meijerink, 2 2018). It is these contexts that their capacity to operate simultaneously at the interface of multiple networks 3 is particularly valuable for promoting climate action. Urban climate policy entrepreneurs can directly engage 4 with a range of constituent groups and offer and promote climate adaptation strategies that can have direct 5 impact on the daily lives of these residents and their interests. 6 7 8 [START BOX 17.3 HERE] 9 10 Box 17.3: Climate Risk Decision-Making in Settlements: From Incrementalism to Transformational 11 Adaptation 12 13 Cities are important sites of experimentation where the integration and management of adaptation decision- 14 making complexity often takes place. These actions provide early evidence of what aspects of complex 15 climate risk management decision-making functions well, but also what does not work (Revi et al., 2020). 16 Cities are seen as locales where case examples of transformative adaptation can be examined (Rosenzweig 17 and Solecki, 2018; Vermeulen et al., 2018). Cities act as testbeds of how to integrate climate response into 18 issues of equity, health, resource allocation, and sustainability in ways that utilize innovative use of new and 19 emerging decision-support tools, methods and protocols. 20 21 Risk management has been an integral part of the community development and settlement building process. 22 Three key sets of drivers influence risk management decision-making in cities (Solecki et al., 2017). These 23 include 1) root � i.e., cultural norms and social traditions; 2) context � i.e., policy and governance conditions 24 and 3) proximate � i.e., extreme events. Settlements have developed informal and formal strategies including 25 climate protection levels to respond to local conditions of climate risk and hazards. In formal contexts, these 26 strategies are contextualized in local climate change action plans (Araos et al., 2016a; Stults and Woodruff, 27 2017; Reckien et al., 2018a; Singh et al., 2021) and defined around a set of evaluation tools and methods and 28 building codes, standards, and regulations (see discussion in 17.4.4). 29 30 Climate change has begun to alter the environmental baseline of cities changing their risk and hazard 31 profiles. In recent years, national and local risk management can benefit from assessments of current 32 decision-making strategies and from evaluations of opportunities for change in risk management policy. 33 These changes can be adjustments of existing policies or transitions to a new policy for current (i.e., 34 conditions already experienced by getting worse) or emerging risks (i.e., conditions not previously or widely 35 experienced but now increasingly present). 36 37 With increasing impacts of climate change, settlements of all sizes are considering how to make their 38 communities more resilient to climate risk (see Cross-Working Group Box URBAN in Chapter 6; Araos et 39 al., 2016a; Araos et al., 2017; Reckien et al., 2018a). In many settlements demands for heightened resiliency 40 are being coupled with opportunities to enhance the social and economic equity and quality of life of 41 residents. Transformational adaptation (transformational, as being outcome-oriented; Vermeulen et al., 2018) 42 and associated adjustments to the urban risk management decision-making requires an integration of climate 43 resiliency pathways and conditions of sustainable development (Mendizabal et al., 2018). At the same time, 44 growing conflict is present between requirements for greater resiliency and continued economic 45 development, in particular in low-income environments (Ahenkan et al., 2020). Cities and their residents 46 have the capacity to transform their own governance and decision-making systems (Birkmann et al., 2014; 47 Chu, 2018; Romero-Lankao et al., 2018). Furthermore, cities have recognized the opportunity and demand to 48 transform in order to be more ambitious (Mendizabal et al., 2018) and more successful, more equitable 49 (Reckien et al., 2018b) and better able to connect the climate action to the sustainable development process 50 (Singh et al., 2021). 51 52 In some cases, transformational adaptation is associated with large-scale, top-down, formal decision 53 processes leading to significant policy shifts. For coastal cities this might include actions to build massive 54 flood protection systems (as opposed to simple increase of existing structures) (Albers et al., 2015; Hinkel et 55 al., 2018; Ajibade, 2019; see also Section 2.3.5, Cross-Chapter Paper 2) or policies to encourage managed 56 retreat from increasing at risk locations (Hino et al., 2017; Rulleau and Rey-Valette, 2017). In more extreme 57 instances, the relocation of cities is presented as a possibility, such as planned for the city of Jakarta Do Not Cite, Quote or Distribute 17-82 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 (Garschagen et al., 2018b). However, acceptability of top-down approaches to relocation are usually low and 2 bottom-up drivers of relocation are important, especially to avoid inequitable outcomes (Mach and Siders, 3 2021). Intensity of extreme events and changing risk perceptions and expectations of property prices have 4 been identified as important behavioural drivers of voluntary relocation (de Koning et al., 2019; de Koning 5 and Filatova, 2020). Yet, when not supported by equitable public adaptation policies, the transformational 6 adaptation left to the influence of autonomous adaptation and market institutions alone leads to climate 7 gentrification low-income households are priced out from the hazard-free zones (de Koning and Filatova, 8 2020). 9 10 These circumstances also have revealed potential advances in decision-making by encouraging greater 11 participation, more effective generation and use of information and data, and more prominent inclusion of 12 questions of social and economic equity (Ziervogel et al., 2017; Reckien et al., 2018b; Solecki et al., In 13 Press). Adaptation planning and decision-making, in general, within cities has increasingly focused on 14 actively engaging residents in participatory and neighbourhood scale co-production processes (Broto et al., 15 2015; Sarzynski, 2015; Wamsler, 2017; Foster et al., 2019). However, engaging residents in risk 16 management and adaptation has not always led to transformative decision-making and resiliency, but can at 17 times also reinforce existing maladaptive systems (D'Alisa and Kallis, 2016). 18 19 Now increasing amounts of data are being collected via surveys or in participatory settings next to advanced 20 methods, such as using citizen science, big data and AI, to integrate these social dimensions of climate 21 adaptation decisions in cities in formal models (Abebe et al., 2019; Taberna et al., 2020). Linking to social 22 data on individual decisions, risk perceptions, social norms, and governmental policy, advanced social 23 models trace and quantify how adaptation in cities evolve and would cumulatively induce transformational 24 change. Although wider application of these models is outstanding there is opportunity to simulate and learn 25 from the integration of social and behavioural data with political and cultural norms (de Koning and 26 Filatova, 2020). 27 28 Although non-urban areas could in many instances act in the same way as urban areas, the density of people, 29 assets, infrastructure, and economical values drives cities to act as testbeds, implement adaptation, and strive 30 for resiliency. Cities are showcases for the larger environmental systems of governments that also support 31 mitigation ambition of national actors and are therefore demanding to be recognized as valuable actors in the 32 international negotiations, highlighting their contribution in emissions reductions (Chan et al., 2015; Hale, 33 2016), e.g., in the preparation for the first Global Stocktake of the Paris Agreement in 2023 (see Cross- 34 Chapter Box PROGRESS in this Chapter). 35 36 [END BOX 17.3 HERE] 37 38 39 17.5 Adaptation Success and Maladaptation, Monitoring, Evaluation and Learning 40 41 17.5.1 Adaptation Success and Maladaptation 42 43 17.5.1.1 The Adaptation-Maladaptation Continuum 44 45 As evidence on adaptation implementation grows (Berrang-Ford et al., 2021; Eriksen et al., 2021), there is a 46 need to examine the outcomes of adaptation (Ford et al., 2011) for effectiveness, adequacy, justice/ equity in 47 both outcomes and process, as well as synergies and trade-offs with mitigation, ecosystem functioning, and 48 other societal goals. There is also a growing recognition of the observed and potential negative consequences 49 of some adaptation interventions, often referred to as maladaptation (Juhola et al., 2016; Magnan et al., 2016; 50 Schipper, 2020; Eriksen et al., 2021). This section advances a new framing to allow for an improved 51 assessment of the potential positive or negative outcomes of adaptation options, therefore allowing 52 navigation of the adaptation-maladaptation continuum. 53 54 17.5.1.1.1 Defining and assessing success in adaptation vis a vis maladaptation 55 The highly contextual nature of adaptation, a multitude of applied definitions of adaptation (e.g cost 56 effectiveness versus outcomes), its overlaps with development interventions, and the long time horizons over 57 which outcomes accrue, deter a universal definition of adaptation success (Dilling et al., 2019a; section Do Not Cite, Quote or Distribute 17-83 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 17.5.1.2; Owen, 2020; Singh et al., 2021). Moser and Boykoff (2013), Olazabal et al. (2019b), and Sherman 2 and Ford (2013) suggest criteria against which successful adaptation could potentially be tracked. The 3 literature is converging to suggest that successful adaptation broadly refers to actions and policies that 4 effectively and substantially reduce climate vulnerability, and exposure to and/or impacts of climate risk 5 (Noble et al., 2014; Juhola et al., 2016), while creating synergies to other climate-related goals, increasing 6 co-benefits to non-climate-related goals (such as current and future economic, societal, and other 7 environmental goals) and minimize trade-offs (Grafakos et al., 2019) across diverse objectives, perspectives, 8 expectations, and values (Eriksen et al., 2015; Gajjar et al., 2019a; Owen, 2020) (high confidence). 9 10 Maladaptation refers to current or potential negative consequences of adaptation-related responses that lead 11 to an increase in the climate vulnerability of a system, sector, or group (Barnett and O'Neill, 2010) by 12 exacerbating or shifting vulnerability or exposure now or in the future (Antwi-Agyei et al., 2014; Noble et 13 al., 2014; Juhola et al., 2016; Magnan et al., 2020) and eroding sustainable development (Juhola et al., 2016). 14 Conceptually, maladaptation differs from `failed' or `unsuccessful' adaptation (Schipper, 2020), which 15 "describes a failed adaptation initiative not producing any significant detrimental effect" (Magnan et al., 16 2016: 648). Several frameworks have been proposed to explain and better assess maladaptation (Hallegatte, 17 2009; Barnett and O'Neill, 2010; Magnan, 2014; Magnan et al., 2016; Gajjar et al., 2019b). In order to limit 18 the risk of maladaptation, a common focus of these frameworks is on intentionally avoiding negative 19 consequences of adaptation interventions, anticipating detrimental lock-ins and path dependence, and 20 minimizing spatio-temporal trade-offs. 21 22 The adaptation literature challenges the simplistic dichotomy of interventions being either successful or 23 maladaptive (e.g. Moser and Boykoff, 2013; Singh et al., 2016; Magnan et al., 2020; Schipper, 2020). There 24 is no clear cut boundary between these two categories; rather, successful adaptation and maladaptation need 25 to be considered the two ends of a continuum of risk management strategies (Figure 17.9) emphasising that: 26 27 no options are "bad" or "good" a priori with respect to reducing climate risk/vulnerability. 28 positive and negative outcomes of adaptation depend on local context specificities (including the 29 presence/ absence of enabling conditions [1]), how adaptation is planned and implemented, who is judging the 30 outcomes (i.e. adaptation decision-maker, planner, implementer or recipient) and when adaptation outcomes 31 are assessed. 32 ex ante assessment of where options fall on the continuum can help anticipate maladaptive outcomes. 33 34 Along the adaptation-maladaptation continuum, adaptation options can score high or low on different 35 outcome criteria identified in this section as: benefits to the number of people, benefits to ecosystem 36 services, equity outcomes (for marginalized ethnic groups, gender, low-income populations), 37 transformational potential and contribution to GHG emission reduction (see SM 17.1 for full descriptions). 38 Importantly, the outcome of the assessment, and consequently location of a given adaptation option along 39 this continuum, is dynamic, depending on multiple components including changes in the characteristics of 40 climate hazards and the effects of iterative risk management. Unfortunately, this temporal dimension is 41 understudied in the literature (including studying thresholds or speed), preventing advances on this specific 42 point. 43 44 Do Not Cite, Quote or Distribute 17-84 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Figure 17.9: Successful adaptation and maladaptation are conceptualised as the two end points of a continuum, with 3 adaptation options being located along the continuum based on outcome criteria (how they benefit humans and 4 ecosystems; how they contribute to or hinder equity goals; whether they enable transformative change to climatic risks, 5 and synergies and trade-offs with climate mitigation). As indicated in SM 17.1 and figure 17.9, adaptation options 6 might rate largely positive and slightly negative across outcome criteria (tending towards successful adaptation), while 7 other adaptation options might have small positive aspects and larger negative ones across different outcome criteria 8 (tending towards maladaptation). The figure draws on Singh et al. (2016); Magnan et al. (2020), and Schipper (2020). 9 10 11 17.5.1.1.2 Empirical evidence on success of adaptation vis a vis maladaptation 12 Although the empirical evidence on current and potential successful adaptation and maladaptation remains 13 small and fragmented (Magnan et al., 2020; Berrang-Ford et al., 2021; see Section 17.3.2 in this Chapter), 14 the above framing allows for moving a step further in assessing the potential contribution of a wide range of 15 adaptation-related options to success or maladaptation. 16 17 According to an assessment (Figure 17.10; see SM 17.1 for full descriptions) of maladaptation-relevant 18 outcome dimensions, here called criteria, i.e. benefits to people, benefits to ecosystem services, benefits to 19 equity (marginalized ethnic groups, gender, low-income populations), transformational potential, and 20 contribution to GHG emission reduction, no option is located at one or the other end of the adaptation- 21 maladaptation continuum (Figure 17.10, right panel), showing that all options have some maladaptation 22 potential, i.e. trade-offs (very high confidence). This is also shown by the wide confidence bars of most 23 options (right panel) signifying that most adaptation can be done in a way that involves a higher or a lower 24 risk of maladaptation (medium confidence; see also Table 17.2). The option of `coastal infrastructure' 25 signifies the highest risk for maladaptation. While it can be an efficient adaptation option in highly densely 26 populated areas (Oppenheimer et al., 2019; CCP2.3), it has potential tradeoffs for natural system functioning 27 and human vulnerability over time. The option most widely associated with successful adaptation is `nature 28 restoration', closely followed by `social safety nets' and options relating to `farm/ fishery practices', and 29 `diets/ food waste' (high confidence). 30 31 Some options show the dominant influence of certain criteria (Figure 17.10, central panel rows). For 32 example, `availability of health infrastructure' and `access to health care' are dominated by the criterion 33 `greenhouse gas emissions'. Similarly, `spatial planning' carries a high risk of disadvantages to marginalized 34 ethnic and low-income groups. This means that these adaptations could be transformed into successful 35 adaptations more easily than others, if attention is paid to the dominant criterion. For example, if healthcare 36 could be provided with low GHG emissions it would move closer towards successful adaptation (high 37 confidence). For other options, the criteria's influence is more evenly distributed, as illustrated for the Do Not Cite, Quote or Distribute 17-85 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 `diversification of livelihoods' and the three options to address climate risks to peace and mobility, denoting 2 multiple entry points to reduce the risk of maladaptive outcomes for these options. 3 4 Some criteria score highly across a number of options (Figure 17.10, central panel columns), showing that 5 many adaptations do not pay attention to different trade-offs. For example, particular attention should be 6 paid to prioritising benefits to low-income groups and leveraging the transformational potential of adaptation 7 (having the largest number of large circles), i.e. many evaluated options become maladaptive by 8 exacerbating the vulnerability of low-income groups and by fortifying the status-quo (medium confidence). 9 On the contrary, most evaluated adaptation options are widely applicable across populations (benefits to 10 humans), and deliver ecosystem services, while some also respect gender equity (largest number of small 11 bubbles across options), through these criteria a number of adaptation options contribute to a higher potential 12 for successful adaptation (high confidence). 13 14 Do Not Cite, Quote or Distribute 17-86 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Figure 17.10: The potential contribution of 24 adaptation-related options to maladaptation and successful 3 adaptation. The figure builds on evidence provided in the underlying sectoral and regional chapters and the Cross- 4 Chapter Papers (SM17.1) to map 24 adaptation options identified as relevant to the eight Representative Key Risks (see 5 Ch16.5) onto the adaptation-maladaptation continuum. It assesses the potential contribution of each of these adaptation 6 options to successful adaptation and the risk of maladaptation. The figure permits a review of options in multiple ways: 7 a) Looking at adaptation options (first column) one can see which adaptation options score highest across the criteria 8 (the central rows). Results by options show which ones carry the highest risk of maladaptation (=largest circles per 9 row). b): Looking at criteria (top centre) one can see which criteria seem to be most influential to contribute to Do Not Cite, Quote or Distribute 17-87 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 maladaptation outcomes (=largest circles per central column). c) The panel on the right: Merging the scores of each 2 adaptation option across criteria helps highlighting whether the options are likely to end up as successful adaptation or 3 maladaptation. 4 5 6 The results displayed in Figure 17.10 are not rigorous predictions but illustrate the maladaptive potential of 7 options based on a synthesis of literature from underlying WGII chapters and cross-chapter papers. This 8 leads to findings for general situations, potentially obscuring critical contextual specificities which can 9 mediate successful adaptation or maladaptation outcomes. In a certain context, Figure 17.10 will appear 10 different. Moreover, the analysis is based on a static interpretation of adaptation outcomes, while risk and 11 risk reduction are dynamic. The current, underlying literature does not help understanding the temporal 12 dimension of the options, their flexibility or risk of lock-in, and related potential contribution to long-term 13 maladaptation or successful adaptation. The added value of the analysis lies in the approach to assess the 14 potential contribution to maladaptation or successful adaptation (via the seven criteria at the top of the 15 figure), rather than in the final results themselves. This overview illustrates how in a particular context and 16 for particular groups of people, adaptation options and their location on the adaptation-maladaptation 17 continuum can be assessed for a set of outcome dimensions, focuses on assessing potential contributions per 18 and across criteria, as well as per and across options (critical information to support the identification of 19 adaptation pathways; Cross-Chapter Box DEEP in this Chapter). 20 21 17.5.1.1.3 Enabling successful adaptation and pre-empting maladaptation 22 Considering evidence on enabling successful adaptation in the sectoral (Chapters 2-8) and regional chapters 23 (9-15), four conditions stand out as particularly key to enabling adaptation success: recognitional equity and 24 justice, including the integration of Indigenous and local communities and knowledge; procedural equity and 25 justice; distributive equity and justice; and flexible and strong institutions that seek integration of climate 26 risk management with other policies and address long-term risk reduction goals (Table 17.8). For a wider 27 discussion of enablers for adaptation and climate risk management, see Section 17.4. 28 29 Recognitional equity and justice: Recognitional justice focuses on inclusion and agency, i.e. examining 30 who is recognised as a legitimate actor and how their rights, needs and interests are acknowledged and 31 incorporated into action (Singh et al., 2021). 32 33 A global assessment of 1682 papers on adaptation responses yields that low-income groups (high agreement, 34 37% of 1682 articles), women (medium agreement, 20% articles), Indigenous peoples (10%), the elderly 35 (8%), youths (5%), racial and ethnic minorities (4%), and migrants (4%) were the most frequently 36 considered groups in adaptation responses. Individuals with disabilities are the least considered, with only 37 1% of articles including this group. There is a category of "other" capturing characteristics of social 38 disadvantage that are distinct from the categories above. This includes, for example, spatially marginalized 39 populations (e.g., groups relegated to flood-prone or cyclone-prone areas) and groups marginalized due to 40 marital status or assets (education, farm size, and land tenure) (Araos, in press). 41 42 Procedural equity and justice: Participation is employed to enable procedures that aim to redress power 43 imbalances, which are assumed to be the root causes of vulnerability (i.e. the reasons that lead certain people 44 and places to be differentially vulnerable to climate risks) (Tschakert and Machado, 2012; Shackleton et al., 45 2015; Schlosberg et al., 2017; Ziervogel et al., 2017). However, participation is often constrained by gender 46 (Cross-Chapter Box GENDER, Ch 18), social status, unequal citizenship (as concerns education, access to 47 information, finance and media) (Wallimann-Helmer et al., 2019), entrenched political interests (Shackleton 48 et al., 2015; Chu et al., 2017), power dynamics (Rusca et al., 2015; Taylor and Bhasme, 2018; Kita, 2019; 49 Omukuti, 2020; Taylor and Bhasme, 2020), or institutional shortcomings (Nightingale, 2017, in Nepal), 50 which allow the most powerful access to funding and reinforce marginalisation of the powerless (Schipper et 51 al., 2014; Khatri, 2018; McNamara et al., 2020). Vulnerability is also sometimes used as a pretext to exclude 52 groups from participation, often because vulnerable groups do not own land, lack legal status, time, or the 53 ability to commit labour or material inputs for adaptation, all drivers of vulnerability in the first place 54 (Nyantakyi-Frimpong and Bezner Kerr, 2015; Camargo and Ojeda, 2017; Nagoda and Nightingale, 2017; 55 Nightingale, 2017; Thomas and Warner, 2019; Mikulewicz, 2020). 56 57 Reporting from the global assessment of equity considerations in adaptation, procedural equity and justice, 58 was slightly more often mentioned (~52%) than not (~48) (medium agreement). However, the robustness of Do Not Cite, Quote or Distribute 17-88 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 the evidence on inclusion of vulnerable and marginalized groups in the planning of adaptation responses is 2 low (63%) (high agreement). Only for ~6% of the articles that provide evidence for inclusion of vulnerable 3 groups the robustness of evidence is high (low agreement). Globally, the category of low-income (~25%) 4 and women (~13%) are most often included, although the robustness remains low. Most of the robust 5 evidence comes from Africa and Asia, where adaptation responses mostly focus on low-income and women 6 groups in the food (28%) and poverty (32%) sectors (medium agreement). With regards to other vulnerability 7 categories, such as disabled populations, almost negligible evidence was found for the inclusion of this 8 group, globally. There is also little reporting of procedural equity in community-based or ecosystem-based 9 responses (Araos, in press). 10 11 Distributive equity and justice: Attention to distributional equity and justice aims to ensure that adaptation 12 interventions do not exacerbate inequities (Atteridge and Remling, 2018) and that the benefits and burdens of 13 interventions are distributed fairly (Tschakert et al., 2013; Reckien et al., 2017; Reckien et al., 2018b; Pelling 14 and Garschagen, 2019). 15 16 A global assessment of 1682 papers on adaptation (Araos, in press) finds that about 60% of articles 17 mentioned at least one vulnerable group being involved in the implementation of adaptation or targeted by it 18 (medium confidence). Low-income groups (high agreement, 37% of 1682 articles) and women (medium 19 agreement, 20% articles) are the most frequently mentioned. Particularly in sectors and regions that 20 incorporated coping measures in their adaptation response (Poverty, Food, Africa, Asia, Central & South 21 America), these groups are prevalent. In sectors where responses were more strategic or planned, such as in 22 cities, terrestrial and water, a larger proportion of articles (51%, 47% and 47% of articles respectively) 23 vulnerable groups were not frequently included in the response (medium agreement). There was also a stark 24 difference in inclusion of marginalized and vulnerable groups between high-income and low-income 25 countries regions, with the majority of the responses from Australia, Europe and North America, not 26 including marginalized groups (high agreement with 70%, 69% & 55% of articles respectively), showing the 27 need for increasing attention in particular on a cross-sectoral and cross-regional relation (Araos, in press). 28 29 Flexible and strong institutions: There is medium confidence that flexible institutions can enable adoption 30 of new adaptation measures or course-correct established ones based on ongoing monitoring and evaluation, 31 which is key to avoiding potential maladaptation (e.g. Granberg and Glover, 2014, in Australia; Magnan et 32 al., 2016; Torabi et al., 2018; Gajjar et al., 2019a, in India). Cross-sectoral, cross-jurisdictional and cross- 33 spatial institutional frameworks enable successful adaptation by improving the ability of societies to respond 34 to changes in their environment in a timely manner. The latter points to the vital role of monitoring and 35 evaluation, as the tool to detect change in risk and vulnerability, together with environmental or societal 36 conditions determining risk and the effectiveness, efficiency, adequacy, or success of adaptation responses. 37 38 39 Table 17.8: Key factors that enable successful adaptation. The evidence and examples draw on the underlying sectoral 40 and regional chapters as well as a synthesis of adaptation literature. Enablers What this Key characteristics Examples and traceability enables Recognitional Pluralising the - Focuses on inclusion and agency, i.e., who is - Co-production of knowledge justice ambit of who is recognised as a legitimate actor and how their and inclusion of Indigenous and 'counted' as rights, needs and interests are acknowledged local knowledge (Loboguerrero vulnerable, and incorporated into adaptation (Chu and et al., 2018; Dannenberg et al., drawing on Michael, 2018; Singh et al., 2021). 2019, Cross-Chapter Box ILK; multiple - Acknowledges how differential vulnerability Ziervogel et al., 2019). knowledge to climate change stems from historical and - Co-production of knowledge systems structural inequalities, which can unevenly and inclusion of marginalized distribute adaptation benefits, especially for groups across sectors, see e.g., in the poorest and the most marginalized the health sector (Ch 7), food (Tschakert and Machado, 2012; Shackleton et systems (Ch 5) and fire al., 2015; Schlosberg et al., 2017; Ziervogel et management (Ch 12). al., 2017; Eriksen et al., 2021). - Informs more equitable adaptation priorities (Ziervogel et al., 2017), legitimizes adaptation Do Not Cite, Quote or Distribute 17-89 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report actions (Myers et al., 2018; Ellis and Tschakert, 2019), supports inclusion of marginalized groups (Chu and Michael, 2018) (medium confidence). Procedural Differential - Ensures that processes of representation and - Participation of multiple justice participation participation in adaptation planning, stakeholders enables co- and power for prioritisation and implementation are inclusive production of adaptation Distributive more inclusive (Holland, 2017; Reckien et al., 2017; Reckien strategies and devolution of justice adaptation et al., 2018b) (medium confidence). decision-making (Ziervogel, planning and - Enable adaptations to advance more quickly 2019) and often, even if not implementation and generate higher levels of wellbeing (e.g. always (D'Alisa and Kallis, Dannenberg et al., 2019 comparing cases of 2016), a higher level of strategic retreat), while also benefiting poorer transformational adaptation (and households (Chu and Michael, 2018). more ambitious local mitigation - Higher participation can enable more goals) (Cattino and Reckien, in legitimate outcomes, greater awareness about press). societal problems addressed, larger - Participatory processes can willingness for community cooperation, and have more equitable outcomes as increased individual behavioural change evidenced in informal (Burton and Mustelin, 2013). settlements (Ziervogel, 2019, - Participation in design and implementation South Africa), small farmers of adaptation projects can be a critical element (Loboguerrero et al., 2018, for avoiding maladaptive outcomes (Taylor, Colombia); migrants (Gajjar et 2015; Nightingale, 2017; Forsyth, 2018; al., 2019b, India), and Mikulewicz, 2019). deliberative dialogues (Ojha and et al., 2019). - But participation does not always address unequal power relations (e.g. Buggy and McNamara, 2016; Karlsson et al., 2017). Delivering - Ensures that adaptation interventions do not - Women and men have very adaptation for exacerbate inequities (Atteridge and Remling, different access to mobile vulnerable 2018) and that the benefits and burdens of phones, entailing lower groups and interventions are distributed fairly (Tschakert responsiveness with climate correcting et al., 2013; Reckien et al., 2017; Reckien et services among women (Partey structural al., 2018b; Pelling and Garschagen, 2019). et al., 2020, across Africa). vulnerabilities - However, low levels of commitment to - Slow progress on prioritizing distributive justice, e.g. when justice is one of distributional and procedural many goals of adaptation instead of the prime justice limits the expansion of one, are insufficient to promote equitable adaptation funding to poorest distribution of benefits and harms (medium and most vulnerable social evidence, high agreement) (Anguelovski et al., groups and nations (Khan et al., 2016; Pulido et al., 2016; Weinstein et al., 2019a). 2019; Shawoo and McDermott, 2020). - Focussing only on distributive justice alone is less effective than a holistic integration of recognitional and procedural justice (limited evidence, medium agreement); e.g., only including poor households as recipients provides benefits to wealthier households, in sectors such as insurance for herders in Mongolia (Taylor, 2016b), urban water supply in Malawi (Rusca et al., 2017), informal urban settlements in Kenya (Pelling and Garschagen, 2019), and Do Not Cite, Quote or Distribute 17-90 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report forest management in Cambodia (Work et al., 2019). Flexible and Seeks policy - Institutional flexibility allows a society to - Capacity building of adaptation strong integration, respond quickly to the demands of a changing funders, planners, and institutions dynamic risk environment by developing new institutions or implementers and reorienting management, adjusting existing ones quickly (Davis, 2010); existing institutions to make and account for possibly avoiding lock-ins and addressing decisions under uncertainty, long-term future climate risks (very high evidence, high institute long-term climate risk goals agreement) (Levi-Faur, 2012; Sherman and management that goes beyond Ford, 2013; Boyd and Juhola, 2015; Magnan typical political/ planning cycles, et al., 2016). and develop learning - Stability (and familiarity) is often desired in mechanisms between sectors, governance arrangements and balancing the actors, and projects needed need for stability with goals of flexibility, (Moser and Boykoff, 2013; without causing rigidity is key (Craig et al., Granberg and Glover, 2014 in 2017, in USA; Ch 11). This is possible Australia; Boyd and Juhola, through deliberate, consultative changes that 2015 in cities; Ziervogel, 2019 build awareness, develop shared norms, rules, in Africa and; Olazabal et al., and goals, and develop inclusive decision- 2019b in India; Ch 3 Oceans; Ch making processes (Ch 3). 10; Ch 11; Ch 12). - Flexible institutions enable adoption of new adaptation measures or course-correct based on ongoing M&E (e.g. Granberg and Glover, 2014 in Australia; Magnan et al., 2016; Torabi et al., 2018; Gajjar et al., 2019a in India) (medium evidence, high agreement). - Sectoral or spatial policy integration (Chu et al., 2017; section 17.6; Hino et al., 2017; Robinson and Wren, 2020); integration of jurisdictional frameworks of different agencies (Poesch et al., 2016; Ch 5; Ch 9); and adaptive and flexible legal systems, which disaggregate socio-ecological systems into smaller components (Arnold and Gunderson, 2013; Wenta et al., 2019) are key enablers. 1 2 3 17.5.2 Adaptation Monitoring, Evaluation & Learning 4 5 17.5.2.1 Purpose of Monitoring and Evaluation 6 7 Adaptation responses have been observed in every region and across a wide variety of sectors (Ch16.3), but 8 little evidence exists of their outcomes in terms of climate risk reduction (high confidence) (Ch 1.4.3; Ford 9 and Berrang-Ford, 2016; Tompkins et al., 2018; Berrang-Ford et al., 2021; Eriksen et al., 2021; UNEP, 10 2021a). To advance on that, the Paris Agreement is encouraging countries to engage in "Monitoring and 11 evaluating and learning from adaptation plans, policies, programmes and actions" (UN, 2015, Article 7.9d). 12 Monitoring and Evaluation (M&E) is the systematic process of collecting, analyzing and using information 13 to assess the progress of adaptation and evaluate its effects--e.g., risk reduction outcomes, co-benefits and 14 trade-offs--mostly during and after implementation (AR6 Glossary). Distinctions between monitoring and 15 evaluation typically view monitoring as a continuous process of tracking implementation and informing 16 management to allow for corrective action including in situations of deep uncertainty (see Cross-Chapter Do Not Cite, Quote or Distribute 17-91 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Box DEEP in this Chapter) while evaluation is described as a more comprehensive assessment of 2 achievements, unintended effects and lessons learned carried out at certain point in time (OECD, 2002). 3 Monitoring and evaluation is an important part of the adaptation process (Figure 1.9). It can help to generate 4 information on adaptation success or maladaptive outcomes. 5 6 M&E of adaptation is undertaken for different purposes, including: (1) understanding whether responses 7 have achieved their intended objectives and contributed to a reduction in climate risks and vulnerability or to 8 an increase of adaptive capacity and resilience, (2) informing ongoing implementation and future responses, 9 and (3) providing upward and downward accountability (Preston et al., 2009; UNFCCC, 2010a; Pringle, 10 2011; Spearman and McGray, 2011). M&E is also commonly linked to learning (section 17.5.2.7). By 11 continuously monitoring implementation, e.g., to assess whether adaptation is on track or needs to be 12 accelerated-- M&E can aid decision-making under uncertainty. Adaptation M&E is distinct from tracking 13 financial flows related to adaptation since financial accounting does not provide information on 14 implementation and outcomes (17.5.2.5; Adaptation Partnership, 2012; World Bank Independent Evaluation 15 Group, 2012). 16 17 17.5.2.2 Adaptation M&E Approaches 18 19 Adaptation M&E can be conducted for various purposes and in a wide variety of different contexts ranging 20 from the local to the global level (McKenzie Hedger et al., 2008; UNFCCC, 2010a; Spearman and McGray, 21 2011). The context and specific purpose of M&E determine what information needs to be generated, and 22 together with the available resources also determine the suitability of particular approaches and methods 23 (Leiter, 2016; Leiter, 2017). Several frameworks and approaches have been proposed for M&E of adaptation 24 and climate resilience (Bours et al., 2014d; Schipper and Langston, 2015; Adaptation Committee, 2016; 25 ODI, 2016; Cai et al., 2018; Gregorowski et al., 2018) including sector-specific ones for agriculture (FAO, 26 2017; FAO, 2019a; FAO, 2019b), health (Ebi et al., 2018), ecosystem-based adaptation (Donatti et al., 2018; 27 Donatti et al., 2020; GIZ, 2020a) and cities (section 6.4.6). 28 29 Adaptation M&E generally seeks to answer whether implementation is taking place and what effects it has 30 (figure 17.11). Accordingly, M&E can focus on the processes, activities and outputs or on their outcomes 31 and ultimate impacts (Harley et al., 2008; Pringle, 2011; Ford et al., 2013). Most of the available guidance 32 for the development of adaptation M&E systems is aimed at the household, local or project level (Pringle, 33 2011; Villanueva, 2012; Olivier et al., 2013; CARE, 2014; BRACED, 2015; Leiter, 2016; Jones, 2019b) with 34 only limited guidance for national or cross-sectoral M&E systems (Price-Kelly et al., 2015) or frameworks 35 that are applicable at different scales (Brooks et al., 2014). The available guidebooks take users through a 36 series of steps which are synthesized in Figure 17.11. 37 38 39 17-92 Total pages: 156 Do Not Cite, Quote or Distribute FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Figure 17.11: Adaptation M&E and learning as part of the adaptation process (based on Hammill et al., 2014a; Price- 2 Kelly et al., 2015; Leiter, 2016). This figure shows the main steps involved in developing an adaptation M&E system 3 where the context informs the purpose of M&E which in turn determines the information needs. To achieve the M&E 4 purposes, the chosen approach and data sources need to be able to generate the needed information which needs to be 5 communicated in a suitable way to the target audiences. 6 7 8 The majority of adaptation M&E efforts have so far focused on processes and outputs rather than on 9 achieved outcomes, e.g. climate risks, vulnerability, well-being or development (Droesch et al., 2008; GIZ 10 and Adelphi, 2014; UNDP Cambodia, 2014; Fawcett et al., 2017) (high confidence) or use a combination 11 thereof (Brooks et al., 2011; Brooks et al., 2014). Newly emerging approaches include perception-based 12 measurements and the use of data collected via mobile phones (Jones et al., 2018; Jones, 2019a), which can 13 be collected frequently (Clare et al., 2017a; Knippenberg et al., 2019; Jones and Ballon, 2020). Such 14 advances call into question the common reliance on "objective" indicators defined from an external 15 perspective. Instead, they suggest that multiple complementary approaches combined with higher frequency 16 data collection produce a more elaborate picture of the effects of adaptation and resilience responses (Jones 17 and d'Errico, 2019; Knippenberg et al., 2019; Singh et al., 2019; Jones, 2019a; see Cross-Chapter Box 18 PROGRESS in this Chapter) (medium confidence). 19 20 Central to designing, monitoring and evaluating adaptation responses is outlining how activities are expected 21 to lead to intended objectives, e.g., via a theory of change (Bours et al., 2014c; Oberlack and al., 2019). 22 Theories of change or similar change models provide a basis to decide what to measure but more attention 23 needs to be paid to how theories of change are constructed and who is involved (Mason and Barnes, 2007; 24 Forsyth, 2018). Participatory approaches can support understanding how climate risks affect the respective 25 population, how these risks interact with social and cultural processes, and how responses could most 26 effectively address climate risks (Conway et al., 2019). Inclusive M&E systems can facilitate ownership and 27 enhance the meaningfulness and usability of the generated information (CARE, 2014; Faulkner et al., 2015). 28 Meaningfulness is not associated with a particular approach or method but depends on whether the chosen 29 M&E design fits the M&E purpose and the information needs of the intended audience (Fisher et al., 2015; 30 Leiter, 2017). Effective communication of M&E findings and feedback into decision making processes is 31 essential to achieve the respective M&E purpose and facilitate learning (section 17.5.2.7). 32 33 17.5.2.3 Adaptation Indicators and Indices 34 35 A set of all-purpose and globally applicable standard indicators that could comprehensively measure 36 adaptation does not exist (high confidence) (IPCC, 2014a; Leiter and Pringle, 2018). A wide variety of 37 indicators have been used to assess adaptation and its results (CARE, 2010; Harvey et al., 2011; Lamhauge 38 et al., 2013; Brooks et al., 2014; Hammill et al., 2014b; M鋕inen et al., 2018; HM Government, 2019). 39 Literature has also noted unrealistic expectations of what indicators can accomplish. For instance, decisions 40 involving competing political interests would not be adequately informed through simple indicators; and 41 learning requires knowledge of how and why change has happened, something that indicators often do not 42 capture (Hinkel, 2011; Bours et al., 2014d). Indicators can also become misguided incentives and might steer 43 attention away from what matters (Leiter and Pringle, 2018; Hallegatte and Engle, 2019; Klonschinski, 44 2021). Surveys, scorecards, interviews and focus groups are alternative methods of gaining insights on 45 adaptation progress (Brooks et al., 2014; Porter et al., 2015; Das, 2019; McNamara et al., 2020). 46 47 The difficulties of assessing adaptation and an emphasis on short-term results have contributed to the 48 common practice of relying on easily quantifiable indicators rather than assessing actual changes, i.e. 49 outcomes and impacts (World Bank Independent Evaluation Group, 2012; Fisher et al., 2015). In fact, 50 indicators used by international climate funds largely measure outputs which provide little evidence of the 51 actual effectiveness of adaptation, i.e. its outcomes and impacts (GCF Independent Evaluation Unit, 2018; 52 Leiter et al., 2019; Pauw et al., 2020). 53 54 Indices, the combination of multiple indicators into a single score, are common products of risk and 55 vulnerability assessments to compare countries or other entities, often in the form of rankings or maps 56 (Preston et al., 2011; Reckien, 2018; de Sherbinin and et al., 2019). They can indicate changes in 57 vulnerability over time within their respective conceptualisation of vulnerability or risk. The construction of 58 indices including indicator selection, their weighting, normalisation and data sources have a profound impact Do Not Cite, Quote or Distribute 17-93 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 on their scores (Reckien, 2018). Research has consistently found large discrepancies between country 2 vulnerability rankings (Brooks et al., 2005; Eriksen and Kelly, 2007; Leiter et al., 2017b; Visser et al., 2020). 3 Reviews of vulnerability and resilience indices identified "substantial conceptual, methodological and 4 empirical weaknesses" (F黶sel, 2010: 8) and a widespread lack of validation (Cai et al., 2018). Using 5 countries as a unit of analysis also masks significant subnational variation (Otto et al., 2015; 6 Mohammadpour et al., 2019). Individual indices therefore "fail to convene a robust guidance for policy 7 makers" (Muccione et al., 2017: 4) and should not present the sole basis for policy decisions (Brooks et al., 8 2005; Leiter and Pringle, 2018). Due to their limitations (Singh et al., 2017), the OECD suggests that indices 9 are primarily used for "initiating discussion and stimulating public interest" (OECD, 2008: 13). 10 11 17.5.2.4 Empirical Evidence of National Adaptation M&E Systems 12 13 Tracking the implementation of national adaptation plans is essential for understanding their effectiveness, 14 i.e. the progress made in addressing climate risks, and can support assessing the success of adaptation and 15 the risk of maladaptation. Over 60 countries have developed or started developing national adaptation M&E 16 systems, although less than half are yet reporting on implementation (Leiter, 2021b; Table 17.9). Country- 17 specific adaptation M&E systems vary considerably regarding their legal mandate, purpose, content, 18 involved actors and types of reporting (Hammill et al., 2014a; EEA, 2015; Leiter, 2015; Leiter et al., 2017a; 19 EEA, 2020). In most cases, they focus primarily on monitoring implementation rather than assessing 20 outcomes, although some are linked to national climate risk or vulnerability assessments (e.g. in Germany 21 and the United Kingdom) (EEA, 2018). At least 15 countries have published evaluations of national 22 adaptation plans which help inform the development of successive adaptation plans or strategies (Table 23 17.9). Nevertheless, there is only limited empirical evidence of the ability of M&E systems to facilitate 24 action or increase the level of ambition of revised policies. More research is needed to determine the quality 25 of national adaptation M&E systems and how well they support the policy cycle. 26 27 Under the Paris Agreement countries are encouraged to provide information on adaptation including its 28 adequacy and effectiveness (M鰄ner et al., 2017; Adaptation Committee, 2021). National adaptation M&E 29 systems can inform both national as well as international reporting and contribute to the global stocktake (see 30 Cross-Chapter Box PROGRESS in this Chapter; Craft and Fisher, 2015; Leiter et al., 2017a). Guidance for 31 and examples of national adaptation progress assessments are provided by Price-Kelly et al. (2015); Brooks 32 et al. (2014); Brooks et al. (2019); EEA (2015); GIZ (2017); Karani (2018); and van R黷h and Sch鰊thaler 33 (2018). Global assessments of adaptation progress have so far often focused on adaptation planning and, to a 34 lesser extent, implementation whilst evidence of the collective effect of adaptation globally remains limited 35 (high confidence) (UNEP, 2021a; Cross-Chapter Box PROGRESS in this Chapter). 36 37 38 Table 17.9: Countries in different stages of developing or operating a national adaptation M&E system as of 1 August 39 2021 (Source: Leiter (2021b). Countries can appear twice if they have published both a progress report and an 40 evaluation. National adaptation M&E system Stage Definition Country Under Early stage Tangible steps have been undertaken to Benin, Cook Islands, Jordan, Paraguay, develop- develop a national adaptation M&E Sri Lanka, Uganda system, for example a stocktake of ment relevant existing data sources and engagement with stakeholders on the objectives of the M&E system Advanced Details of the adaptation M&E system Albania, Bulgaria, Cameroon, Canada, stage have been developed, including, for Colombia, Ethiopia, Fiji, Grenada, instance, institutional arrangements, Indonesia, Moldova, Morocco, indicators and data sources, but it has not Mozambique, Nauru, Peru, Rwanda, yet been applied Senegal, St.Lucia, St. Vincent and the Grenadines, Suriname, Thailand, Togo, Tonga, Turkey, Vietnam Do Not Cite, Quote or Distribute 17-94 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report In Adaptation A progress report on the implementation Austria, Belgium (Flanders), Brazil, operation progress of the national adaptation plan or Burkina Faso, Cambodia, Chile, Cyprus, report strategy has been published France, Germany, Japan, Kenya, Kiribati, published Lithuania, Mexico, Netherlands (Delta Programme), Norway, Portugal, Slovakia, Spain, South Africa, South Korea, Switzerland, United Kingdom Evaluation An evaluation of the implementation of Belgium, Cambodia, Chile, Czech published the national adaptation plan or strategy Republic, Finland, France, Germany, Ireland, Mexico, Netherlands, has been undertaken and published. Philippines, South Korea, Spain, Switzerland, United Kingdom 1 2 3 17.5.2.5 Challenges of Assessing Adaptation 4 5 To date, literature has largely focused on aspects prior to implementation such as assessments of climate 6 vulnerability and risks or appraisals of adaptation options (Sietsma et al., 2021; Cross-Chapter Box 7 Adaptation). To understand adaptation progress, the assessment of implemented adaptation actions and their 8 outcomes requires more attention (very high confidence) (Cross-Chapter Box PROGRESS in this Chapter). 9 10 Outcomes on risk reduction are typically expressed in ways that are specific to the respective sector or 11 context (e.g., as agricultural yields, health benefits or reduced water stress) highlighting that "adaptation has 12 no common reference metrics in the same way that tonnes of GHGs or radiative forcing values are for 13 mitigation" (IPCC, 2014a: 856). Assessments of adaptation progress therefore need to specify what they are 14 measuring and how they are measuring it. The way adaptation is conceptualised, e.g. as a continuum 15 between successful adaptation and maladaptation (Section 17.1.1) and the way adaptation is framed, e.g. as a 16 technical challenge or a political process (Juhola et al., 2011; Bassett and Fogelman, 2013; Eriksen et al., 17 2015), shape the understanding of progress and its subsequent measurement (Singh et al., 2021). 18 19 Furthermore, people can be differently affected even in the same location due to, amongst others, differential 20 vulnerability amongst the population (Reckien and Petkova, 2019; Thomas et al., 2019). Different views and 21 values can also affect what it means to adapt (Few et al., 2021). Assessments of adaptation progress therefore 22 need to be transparent and reflective about how they define and measure adaptation and account for 23 culturally and geographic contingent concepts of what it means to adapt in light of the global diversity of 24 livelihoods and concepts. 25 26 The lack of knowledge on adaptation progress is associated with further measurement challenges including 27 that avoided impacts are difficult to measure and that risk levels change over time, meaning what is effective 28 today may not be effective in the future (Brooks et al., 2011; Pringle, 2011; Spearman and McGray, 2011; 29 Villanueva, 2012; Bours et al., 2014a). Moreover, adaptation is embedded in complex political and social 30 realities where power and politics shape outcomes and where simplistic views of how adaptation would take 31 place may be ill-conceived (Nightingale, 2017; Mikulewicz, 2018; Mikulewicz, 2020). In practice this means 32 that theories of change of adaptation projects may miss important causes of risks and could subsequently 33 lead to inaccurate assessments (Forsyth, 2018). Measuring adaptation is therefore a matter of understanding 34 drivers of vulnerability and risk and of designing responses and M&E systems accordingly (UNFCCC, 35 2019a, section V). 36 37 The importance of context and the dependence on viewpoints make comparative assessments of adaptation 38 across nations, regions or responses challenging. Comparison requires a consistent conceptualisation of 39 adaptation, comparable units of analysis and access to relevant datasets (Ford et al., 2015; Ford and Berrang- 40 Ford, 2016). Comparative adaptation policy assessments to date often lack clarity in concepts and 41 explanatory variables (Dupuis and Biesbroek, 2013; Biesbroek R, 2018a). The trade-off between 42 standardisation and context-specificity also complicates attempts to aggregate adaptation progress across 43 scales to the national or global level (Leiter and Pringle, 2018; Cross-Chapter Box PROGRESS in this 44 Chapter). 45 Do Not Cite, Quote or Distribute 17-95 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 [START CROSS-CHAPTER BOX PROGRESS HERE] 3 4 Cross-Chapter Box PROGRESS: Approaches and Challenges to Assess Adaptation Progress at the 5 Global Level 6 7 Authors: Matthias Garschagen, Timo Leiter, Robbert Biesbroek, Alexandre K. Magnan, Diana Reckien, 8 Mark New, Lea Berrang-Ford, So Min Cheong, Lisa Schipper, Robert Lempert 9 10 This Cross-Chapter Box responds to a growing demand for assessing global climate change adaptation 11 progress, which currently faces the challenge of lacking consensus on how adaptation progress at this level 12 can be tracked (high confidence). The box therefore assesses the rationale and methodological approaches 13 for understanding adaptation progress globally across sectors and regions. It discusses strengths and 14 weaknesses of existing approaches and sources of information, with a view towards informing the first 15 Global Stocktake of the Paris Agreement in 2023. 16 17 Rationale for assessing adaptation progress at the global level 18 19 Global assessments of adaptation are expected to help answer key questions of climate policy (Ford et al., 20 2015; UNEP, 2017; Adaptation Committee, 2021) (low evidence, high agreement,), including: Do the 21 observed, collective investments in adaptation lead humanity to being better able to avoid or reduce the 22 negative consequences from climate change? Where is progress being made and what gaps remain in the 23 global adaptation response to climate risks? 24 25 Whilst more than 170 countries have policies that address adaptation (Nachmany et al., 2019b; 17.4.2), very 26 few have operational frameworks to track and evaluate implementation and results (Leiter, 2021a; 17.5.2.4). 27 In Europe, for example, most countries have adopted a national adaptation plan or strategy, but only few are 28 tracking whether ambitions are realised (EEA, 2020; 13.11.2). Moreover, climate risks are interconnected 29 across scales, regions and sectors (Eakin et al., 2009; Challinor et al., 2017; Cross-Chapter Box INTERREG 30 in Chapter 16; Hedlund et al., 2018) (high confidence), complicating causal attribution. National assessments 31 of progress usually do not assess private sector and non-governmental adaptation and barely account for 32 climate risks that transcend across borders, for example through supply chains or shared ecosystems (EEA, 33 2018; Benzie and Persson, 2019). In addition, adaptation action in one place or time can potentially lead to 34 negative effects elsewhere (externalities) (Magnan and Ribera, 2016; Atteridge and Remling, 2018; 17.5.1). 35 Hence, determining the collective adequacy and effectiveness (see Figure 1.7 in Chapter 1) of adaptation 36 responses is different from simple aggregates of national and sub-national information (UNEP, 2017). 37 38 Assessing global progress on adaptation is therefore of high relevance to the scientific community, to policy 39 makers and other actors. Global assessments serve different information needs than local assessments and 40 their meaningfulness depends on the chosen approaches and their limitations. Aggregated global assessments 41 of adaptation progress are therefore not meant to substitute place-specific ones but to complement them to 42 enhance the knowledge base on adaptation beyond actions by or within individual countries. The Paris 43 Agreement stipulates a Global Stocktake to be undertaken every five years to assess the collective progress 44 towards its long-term goals including on adaptation (UNFCCC, 2015, Article 14). Yet very few scientific 45 studies have addressed the adaptation-specific aspects of the Global Stocktake (Craft and Fisher, 2018; 46 Tompkins et al., 2018) and there are different views and options on how assessing global progress could take 47 place (high confidence). 48 49 Considerations in designing global adaptation assessments 50 51 A number of key considerations for the design of global adaptation assessment approaches are discussed in 52 the literature (Ford and Berrang-Ford, 2016; Berrang-Ford et al., 2017). Some of these involve trade-offs, 53 e.g. global applicability vs. context-specificity, for which there is no simple solution. Design considerations 54 directly depend on the objectives of global adaptation assessments, which can differ between actors and can 55 include e.g. providing transparency, enabling accountability, understanding effectiveness, or guiding policy 56 development (Section 17.5.2.1). The underlying objectives determine the suitability of approaches and the 57 data requirements. Do Not Cite, Quote or Distribute 17-96 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Comparability 3 Global assessments may have the objective to compare adaptation over time and across sectors and regions 4 (Ford et al., 2015). Such comparison requires a consistent definition of concepts (Hall, 2017; Berrang-Ford 5 et al., 2019) and the identification of variables that are both generic enough to be applicable from one context 6 to another and specific enough to illustrate national circumstances. To date, finding such balance has proven 7 to be challenging (Dupuis and Biesbroek, 2013). The context-dependence of adaptation outcomes poses 8 limits for meaningful comparisons. Even people exposed to the same climate hazard may be differentially 9 affected due to varying levels of vulnerability and resilience (Jones et al., 2018; Thomas et al., 2019), 10 meaning that perceptions on adaptation outcomes can also differ (Jones and d'Errico, 2019). 11 12 Aggregation 13 The aggregation of data from local or regional to global scales can take different forms ranging from 14 qualitative synthesis to quantitative aggregation which may involve condensing a diverse set of variables into 15 a single score (Leiter, 2015; 17.5.2.3). In contrast to climate change mitigation, adaptation does not have a 16 global reference metric against which adaptation levels could be assessed to identify progress or gaps. 17 Experience from the Global Environment Facility, for example, has shown that mechanical aggregation 18 based on standardized indicators fails to capture what makes the greatest difference on the ground (Chen and 19 Uitto, 2014). 20 21 Results: Input, process, output or outcome 22 Adaptation progress at any spatial scale can in principle be assessed in terms of input (e.g. resources spent), 23 process (i.e. the way adaptation is organized), output (i.e. adaptation capacities and actions) and outcomes 24 (i.e. actual changes induced) (Section 17.5.2.2). Due to the challenges inherent in measuring adaptation 25 outcomes (Sections 16.3, 17.5.1 and 17.5.2.5), most global assessments to date have focused on outputs, e.g. 26 whether countries have adopted adaptation plans (Berrang-Ford et al., 2021; UNEP, 2021a) (high 27 confidence). Understanding the effectiveness of adaptation responses globally requires a way to 28 conceptualize and capture outcomes, for example in terms of effective climate risk reduction, whilst avoiding 29 simplifications that mask maladaptation at the global level, e.g. where climate risks are shifted to other 30 countries, sectors or population groups (Cross-Chapter Box INTERREG in Chapter 16, Section 17.5.1). 31 32 Data 33 Global assessments typically require global availability of consistent data, be it quantitative or qualitative, 34 which has proven to be a constraining factor for attempts to assess global adaptation (high confidence). For 35 example, many countries face difficulties in reporting adequately on progress in implementing the Sendai 36 Framework and risk-related SDGs (UNDRR, 2019: vi). The availability of data also influences which 37 variables can be eventually selected in an assessment. This limitation can affect the ability to meet the initial 38 objectives and lead to biases in the framing and interpretation of assessment outcomes. For some variables, 39 an alternative to relying on nationally provided data can be to develop new global datasets (Magnan and 40 Chalastani, 2019), or utilising data from Earth Observation (Andries et al., 2018). Adaptation is hence faced 41 with a dilemma between globally available yet generic data and regionally or locally more detailed yet 42 patchy data (high confidence). 43 44 Assessment of existing approaches to assess adaptation progress at the global level 45 46 Only few global assessments of adaptation progress across sectors have been undertaken to date (high 47 confidence). They focus, for example, on whether countries have progressed their adaptation policies and 48 actions over time (Lesnikowski et al., 2015; Nachmany et al., 2019b), the extent of implemented adaptation 49 globally (Leiter, 2021a; Leiter, 2021b), and the type and actors of responses (Berrang-Ford et al., 2021), 50 evidence for reduced vulnerability to climate-related hazards (Formetta and Feyen, 2019; UNDRR, 2019) or 51 adaptation planning in cities across the globe (Araos et al., 2016a; Reckien et al., 2018a; Olazabal et al., 52 2019a). Each of these assessments draw on different approaches and data, and all have particular potential 53 but also limitations (Table Cross-Chapter Box PROGRESS.1) (high confidence). The application of differing 54 approaches shows that there is no single `best' approach or data source to assess global progress on 55 adaptation (high confidence). Existing global assessments have provided valuable insights into the extent and 56 types of responses and their level of planning and implementation (16.3.2.4). They do, however, not provide 57 comprehensive and robust answers so far on whether climate risk and vulnerability have been reduced Do Not Cite, Quote or Distribute 17-97 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 (Berrang-Ford et al., 2021) (high confidence). As a result, combining different approaches and integrating 2 data on climate risk levels, policy measures, implemented actions and their effects on climate risk reduction 3 is currently regarded the most robust approach (Berrang-Ford et al., 2019) (medium evidence, high 4 agreement). 5 6 7 Table Cross-Chapter Box PROGRESS.1: Key approaches and data sources used for global adaptation assessments. Approach / Data source Potential added-value Limitations Systematic assessment of adaptation Provides an indication of the Not a representative sample; biased responses reported in academic literature status, trends and gaps in towards responses published in (e.g. systematic reviews, evidence synthesis, adaptation responses scientific literature; excludes grey meta-analysis, large-n comparative studies) literature; some topics and regions Examples: not well covered; challenges in Berrang-Ford, 2011 #188}, Global terms of comparability and Adaptation Mapping Initiative (Berrang- aggregation; inconsistency in Ford et al., 2021) definitions and use of concepts; English language bias Self-reported progress documents by Context-specific information; May only be available every few years; content is sensitive to countries (e.g. National Communications, official government documents political and policy changes; possible bias towards positive Biennial Transparency Reports or domestic enable assessments of national examples; challenges in terms of comparability and aggregation; progress and evaluation) progress inconsistency in definitions and use of concepts Examples: (Gagnon-Lebrun and Agrawala, 2007; Lesnikowski et al., 2015; Lesnikowski et al., 2016; Leiter, 2021a) Self-reported information from the private Provides an indication of the Sample biased towards larger sector (e.g. information on actions taken in status, trends and gaps in companies; challenges in terms of response to climate risks within the context adaptation responses by the comparability and aggregation; of climate-related financial disclosure or in private sector; complements potential inconsistencies in company reports). information published in the definitions and use of concepts Examples: scientific literature; could enable (Committee on Climate Change, 2017; better understanding of supply Street and Jude, 2019; UNFCCC, 2021), chain risks responses reported under Climate-related Financial Disclosure Project documents and evaluations (e.g. Detailed information on context, Actual implementation can differ from climate funds or implementing intended or achieved results and from what was proposed; organisations) activities fragmented picture of Examples: local/regional actions; results may (Leiter, 2021b); (Eriksen et al., 2021) be challenging to aggregate; challenges in terms of comparability and aggregation; inconsistency in definitions and use of concepts Existing global data sets of mostly Comparable information based Global data availability constrains quantitative indicators on globally defined indicators indicator choice; reporting burden Examples: for new indicators; trade-off United Nations (UN, 2016a; UN, 2016b; between global applicability and UN, 2019; UNDRR, 2019) national circumstances; usefulness and meaningfulness of global indicators is contested (Leiter and Pringle, 2018; Lyytim鋕i et al., 2020; Pauw et al., 2020). Tracking financial flows Comparable data on financial No information about implementation of measures and Examples: flows directed at adaptation; their adaptation effect (Eriksen et al, 2021), i.e. it tracks inputs, not (CPI, 2019), (OECD, 2018a), (MDBs, 2019) standardised methodologies (e.g. OECD RIO markers; climate Do Not Cite, Quote or Distribute 17-98 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report finance tracking method of outputs or outcomes; inconsistency multilateral development banks; in what gets counted as adaptation chapter 17.5.2.6; Cross-Chapter finance (Donner et al., 2016; Doshi Box FINANCE in this Chapter) and Garschagen, 2020); evidence of over-reporting (Michaelowa and Michaelowa, 2011; Weikmans et al., 2017) 1 2 3 Conclusion -- Combining approaches for assessing adaptation progress at the global level 4 5 Understanding to what extent the world is on track to adapt to climate change impacts and risks globally is a 6 pressing question in scientific and policy communities, especially in light of the Global Stocktake under the 7 Paris Agreement. Important considerations for a robust assessment framework (e.g. consistency), as well as 8 the associated scientific challenges (e.g. aggregation, externalities, breath vs. depth of data) and the role of 9 underlying objectives (e.g. on the contested issue of comparability) are increasingly understood (high 10 confidence). There is also a growing and diverse body of information on adaptation progress, although most 11 assessments of global progress undertaken to date focus on processes and outputs (e.g. policies and plans) 12 rather than outcomes (i.e. risk reduction). A variety of approaches and data sources are employed, such as 13 systematic reviews of observed adaptation, formal communications by Parties to the UNFCCC, and project 14 documents to international funding agencies. Novel approaches, including big data tools (Ford et al., 2016; 15 Biesbroek et al., 2020), are also being explored but still have to prove their practical value. Each approach 16 and source of information can contribute additional knowledge, but also demonstrates limitations, so that 17 there is no single `best' approach (high confidence). Yet to date, the international community has not 18 sufficiently explored the relative strengths and weaknesses of different approaches and their applicability, 19 and therefore their potential synergies in complementing each other. Triangulated assessments have only 20 rarely been applied (high confidence) due to multiple conceptual and methodological challenges, despite 21 their potential for increasing the robustness of knowledge. One overarching conclusion of this Cross-Chapter 22 Box therefore is that the combination of different approaches will provide a more comprehensive picture of 23 global adaptation progress than is currently available from individual approaches (low evidence, high 24 agreement). 25 26 [END CROSS-CHAPTER BOX PROGRESS HERE] 27 28 29 17.5.2.6 Tracking Adaptation Finance 30 31 Adaptation finance tracking is capturing the financial flows associated with adaptation. It can indicate how 32 much is being spent on adaptation, where funds are going to, and whether spending matches allocated 33 budgets. Thus, adaptation finance tracking can provide useful information for decision making, but it does 34 not provide information on the achievements resulting from the invested funds. Accordingly, it can 35 complement, but not substitute, M&E of actions and outcomes. Adaptation finance tracking can be applied 36 domestically (Guzm醤 et al., 2017; Guzm醤 et al., 2018) as well as internationally, for instance by developed 37 countries to report on the goal to mobilize US$100 billion a year by 2020 in climate finance (UNFCCC SCF, 38 2018). Data on adaptation finance can be used alongside information on planning and implementation to 39 assess adaptation progress (UNEP, 2021a). 40 41 Tracking adaptation finance requires defining what counts as adaptation. Different definitions can lead to 42 large variations in the estimated amount of adaptation finance (Donner et al., 2016; Hall, 2017). A further 43 challenge is how to account for adaptation that is mainstreamed, i.e. where adaptation-specific investments 44 form only part of a larger programme or budget line, or where actions contribute to adaptation without being 45 labelled as adaptation. These challenges limit the direct comparability between adaptation and mitigation 46 finance (UNFCCC, 2019a). In fact, tracking adaptation finance differs from tracking mitigation finance since 47 activities cannot be a-priori assumed to constitute adaptation but instead have to be assessed for their linkage 48 to climate risks in a particular context (MDBs & IDFC, 2018). Methods for adaptation finance tracking 49 continue to be further developed aiming at better comparability and completeness (Richmond and 50 Hallmeyer, 2019; Richmond et al., 2021). Do Not Cite, Quote or Distribute 17-99 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Various methods are used to track adaptation finance, which makes comparisons between adaptation finance 3 figures challenging (UNFCCC SCF, 2018; Weikmans and Roberts, 2019). For example, multilateral 4 development banks use a different methodology than countries do under the OECD Development Assistance 5 Committee (DAC) (see Box 17.4; MDBs, 2019). One of the differences concerns the treatment of partially 6 adaptation-relevant projects, namely whether only parts or the full amount of a given project volume are 7 counted as adaptation finance (see e.g. MDBs, 2019). Under the OECD DAC methodology, countries often 8 use a fixed percentage (e.g., 50% of the total project value) whereas the MDB methodology attempts for a 9 project-specific estimation of the adaptation-relevant proportion (MDBs & IDFC, 2018). Another aspect is 10 whether tracking distinguishes between financial instruments, e.g., grants or loans. Different accounting 11 rules can lead to large differences in reported amounts of adaptation finance and to a lack of comparability 12 between providers (Weikmans and Roberts, 2019). Studies identified an over-reporting (i.e., counting non- 13 adaptation related finance) by a factor of two to three, which suggests the need for a more consistent and 14 transparent accounting system (Weikmans et al., 2017; CARE, 2021). 15 16 Good coverage of adaptation finance data exists around international public finance flows, predominantly 17 official development assistance flows from OECD DAC members and from multilateral development banks. 18 Less data exists around domestic public finance and private finance flows to adaptation activities, but data 19 sources continue to be further expanded e.g. through climate change expenditure tagging and city-level data 20 (Weikmans et al., 2017; UNFCCC SCF, 2018; Richmond et al., 2021). Recent estimates of adaptation 21 finance are provided in UNFCCC SCF (2018); Macquarie et al. (2020); and in Cross-Chapter Box FAR. 22 23 24 [START BOX 17.4 HERE] 25 26 BOX 17.4: The Rio Markers Methodology to Track Climate Finance 27 28 The OECD Development Assistance Committee (DAC) introduced a methodology to track the amount of 29 bilateral official development assistance (ODA) that is targeting climate change mitigation and/or adaptation. 30 It distinguishes whether activities have adaptation as a "principal" objective (score "2"), as a "significant" 31 objective (score "1"), or as not targeting it (score "0") (OECD, 2016). The associated project value is 32 counted in full, in part, or not counted as adaptation finance, respectively. Countries count the volume of 33 partial adaptation projects (score "1") to a different extent which limits comparability and can lead to over- 34 reporting (OECD, 2019a). The first data on this "adaptation marker" became available in 2012 for the 35 financial flows of 2010. It forms the basis for developed countries' reporting to the UNFCCC Secretariat on 36 their financial commitments towards developing countries (Weikmans and Roberts, 2019). 37 38 While a guidebook with requirements for adaptation as a principle or significant objective has been 39 developed (OECD, 2016), several studies have shown that OECD DAC donors tend to overestimate the 40 number of activities in their portfolio that genuinely have adaptation objectives (Michaelowa and 41 Michaelowa, 2011; Weikmans et al., 2017; CARE, 2021). Hence, the amount of adaptation finance from 42 public sources may be lower than reported. The use of just three categories leads to a broad range of the 43 extent of adaptation being concentrated in the middle category ("significant objective"). Accordingly, the 44 category "principle objective adaptation" provides a more robust predictor of the relevance of an activity to 45 adaptation (Donner et al., 2016). 46 47 [END BOX 17.4 HERE] 48 49 50 17.5.2.7 Evaluation and Learning 51 52 Most adaptation M&E frameworks and tools proposed to date refer to monitoring rather than evaluation 53 (high confidence) (Adaptation Committee, 2016). Evaluations are envisioned to go beyond monitoring by 54 examining how and why results have been achieved and what could be improved (Brousselle and Buregeya, 55 2018; V鋒鋗鋕i and Verger, 2019). Evaluations of adaptation outcomes are still rare, particularly 56 quantitative impact evaluations (Weldegebriel and Prowse, 2013; Das, 2019; B閚� et al., 2020). Impact 57 evaluations of adaptation need to address several methodological as well as practical challenges (Dinshaw et Do Not Cite, Quote or Distribute 17-100 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 al., 2014; Fisher et al., 2015; B閚� et al., 2017; Puri et al., 2020). Different types of evaluations are 2 appropriate for different evaluation questions (Silvestrini et al., 2015). Evaluations of the available evidence 3 of effective adaptation in particular topics or sectors have emerged more recently, for instance on 4 mainstreaming (Runhaar et al., 2018) and agricultural climate services (Vaughan et al., 2019a). Impact 5 evaluations of capacity building measures are important because capacity building is assumed to lead to 6 adaptation, but its actual effects are seldom examined (Mortreux and Barnett, 2017; Alpizar F and 7 Meiselman, 2019). If well designed and utilised for learning, evaluations can play an important role in 8 improving adaptation responses (Hild閚, 2011). 9 10 Learning requires information about how and why change occurred and what experiences have been made 11 (Feinstein, 2012). M&E is frequently associated with learning, but it is rarely made explicit how learning is 12 supposed to take place (Armitage et al., 2008; Baird et al., 2015; Borras and H鴏und, 2015). The design of 13 adaptation M&E systems can support learning by gathering relevant information and disseminating it in a 14 way that is accessible and effectively linked to decision making processes (Spearman and McGray, 2011; 15 Villanueva, 2012; Fisher et al., 2015). Options include institutionalised feedback mechanisms, peer learning 16 and knowledge sharing events, a learning culture and ways to gather in-depth insights beyond indicators 17 (ibid; Oswald and Taylor, 2010). Since AR5, adaptation programmes and funds such as the BRACED 18 programme, the Adaptation Fund, the Climate Investment Funds and the Green Climate Fund have created 19 knowledge-sharing units and provide resources to support learning activities(BRACED, 2015; Roehrer and 20 Kouadio, 2015; Adaptation Fund, 2016; Leavy et al., 2018; CIF, 2020; Puri et al., 2020), but there is little 21 information about their longer-term effectiveness. 22 23 24 17.6 Managing and Adapting to Climate Risks for Climate Resilient Development 25 26 Actions to ameliorate a climate risk have consequences beyond the immediate effects on exposure or 27 vulnerability to a hazard. They may aim to combat many risks, could adversely interact with other risks and 28 actions, or may be nested within a suite of actions across many risks. Some actions may have negative 29 consequences for climate resilient development. In this broader context, the effectiveness of adaptations for 30 supporting climate resilient development is now better articulated (Box 17.1). Importantly, adaptations need 31 to be designed to not only combat current and future climate risks, but also ensuring that they do not lock in 32 undesirable pathways in the future as risks develop and change (very high confidence) (17.2, 17.3.1, 17.5). 33 Effective management of climate risks will therefore be dependent on satisfactorily managing current 34 climate risks (Box 17.1, 17.2, 17.5), coupled with assessing prognoses for future climate risks, and 35 developing responses in advance for reducing those risks to tolerable residual levels (very high confidence) 36 (1.4, 1.6, 16.6, 17.2, Box 16.1; e.g. water risks - 4.7.1). The dynamic nature of risk (Viner et al., 2019; 37 Simpson et al., 2021; 16.3, 16.6) also means that the contribution of current adaptations to ameliorating 38 future risks needs to be regularly reviewed (high confidence) (17.5.2). Across the Working Group II report 39 are examples of how managing adaptations to ameliorate climate risks can negatively or positively affect 40 sustainable development, thereby impacting the potential for climate resilient development discussed in 41 Chapter 18. Drawing on the assessment of sectoral and regional chapters in this report, this section examines 42 three broad components for orienting decision-making for climate adaptation towards climate resilient 43 development. 44 45 17.6.1 Need for Integrated Risk Management 46 47 The complex, interacting and compounding nature of climate risks means that single risks cannot be 48 managed in isolation (very high confidence) (16.5, Figure 16.11; 17.3.2; Nhamo et al., 2018), including 49 accounting for potential risks arising from adaptations (Simpson et al., 2021). Regional examples of needs 50 for cross-sectoral integrated management include the water-energy-food nexus in Africa (10.5.1), Asia 51 (10.6.3), Australasia (11.6), Europe (13.2.2) and North America (Table 14.8), and ecosystem-oriented 52 adaptations and/or nature-based solutions, in Africa (9.6.5), Asia (10.4.2), Australasia (Box 11.4, 11.3.5), 53 Central and South America (12.5.1), Europe (13.3.2), North America (14.6.1, Box14.3) and Small Islands 54 (15.5.4). The cross-sectoral interactions within humans systems, including impacts on cities, settlements and 55 infrastructure, are reflected in those subjects as well as for health in Africa (9.10.2), Asia (10.4.5), 56 Australasia (11.3.6), Central & South America (12.5.6), Europe (13.7.2), North America (14.6.1), and Small Do Not Cite, Quote or Distribute 17-101 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Islands (15.6.2), and poverty and livelihoods in Africa (9.11.3), Asia (10.4.5, 10.5), Australasia (11.4), 2 Central & South America (12.5.7), Europe (13.8.2), North America (14.6.1), and Small Islands (15.3.4). 3 These examples demonstrate that the emergence of climate risks can be at different rates, different time 4 horizons, and the interactions between risks vary from region to region (very high confidence). The need to 5 manage these risks in an integrated manner is readily identified in the Water-Energy-Food nexus (Box 9.5). 6 However, in terms of climate resilient development, the need for integration is demonstrated by the diverse 7 and interacting impacts of climate risks on ecosystems (2.7, 3.6), cities (6.2.3, 6.2.4, Box 6.2, 6.3), health 8 (7.4), and poverty and livelihoods (8.6). 9 10 17.6.2 Strategies for Managing a Portfolio of Climate Risks 11 12 Since WG2 AR5, new methods for simultaneously considering multiple societal and sectoral objectives, 13 climate risks and adaptation options have emerged (17.3.2; Adam et al., 2014; Hadka et al., 2015; Garner et 14 al., 2016; Rosenzweig et al., 2017; Giupponi and Gain, 2017a; Stelzenmuller et al., 2018; Marchau et al., 15 2019), including methods for accounting for different sources of uncertainty and types of risk (17.3.1; 16 Giupponi and Gain, 2017a). Different decision-making approaches can be complementary (high confidence) 17 (17.3.1; Kwakkel et al., 2016) and multiple approaches will likely be necessary in managing the risks across 18 sectors, over different spatial scales, and over short to long time scales (medium confidence) (Cross-Chapter 19 Box PROGRESS in this Chapter; Girard et al., 2015; Rouillard and Spray, 2016). 20 21 Deciding on which adaptations to adopt when managing climate risks inevitably needs examination of trade- 22 offs in outcomes (very high confidence) (17.3.1, 17.5.1; Cross-Chapter Box FEASIB in Chapter 18). A 23 current difficulty with integrated assessments is to develop a set of metrics that are appropriately scaled for 24 the different sectors or outcomes to be compared (e.g., 12.5.2.6; 17.3.1; 17.5.2; Cross-Chapter Box 25 PROGRESS in this Chapter). For climate resilient development, dimensions of poverty, equity, justice, and 26 health need to be factored into analyses (Box 17.1, 17.5), many of which are difficult to quantify (high 27 confidence) (18.2.4). Moreover, uncertainties on the interactions within and between sectors can make trade- 28 off analyses uneven in their precision across sectors and uncertain as to the outcome of an implemented 29 adaptation (medium confidence) (4.7.2, 17.4, 17.5). 30 31 Expertise and resources for using tools and approaches for integrated risk management varies between the 32 developed and developing countries (high confidence) (e.g. 4.7.2). Exploration of adaptation scenarios can 33 be derived from Earth System Models (high confidence) (e.g. 4.7.1.2, 11.7.3.1). However, the feasibility of 34 possible adaptations and the degree to which they are likely to be effective (Box 17.1) will require further 35 exploration as success will depend on appropriate enabling conditions including institutional support and 36 capacity, available financial resources and knowledge, and suitable conditions for stakeholder participation 37 (high confidence) (17.4). The current levels of uncertainty surrounding the effectiveness of many adaptation 38 options (17.5.2; Cross-Chapter Box PROGRESS in this Chapter) means that decision-making approaches 39 applicable to deep uncertainty (Cross-Chapter Box DEEP in this Chapter; 17.3.1) will apply in many if not 40 most cases (medium confidence). An early step in identifying suitable integrated pathways for managing 41 climate risks, establish `no regrets' anticipatory options in a timely manner, and avoiding path dependencies, 42 is to jointly map the steps for adapting to sectoral risks, and determine suitable ways to avoid maladaptations 43 arising (high confidence) (17.3.1, Cross-Working Group Box URBAN in Chapter 6 and Cross-Chapter 44 Boxes DEEP in this Chapter). The application of Dynamic Adaptive Pathway planning has been successfully 45 used in this way in Australasia (11.7.3) and Europe (13.6.2.2, 13.10.2) (Lawrence et al., 2019a; Haasnoot et 46 al., 2020a). Current experience suggests that synergies between sectors can save resources and effort (limited 47 evidence) (13.11.2). Iterative processes can then enhance adaptation programs by including more detailed 48 modelling and updated knowledge as the experience is acquired (17.3.1). 49 50 17.6.3 Mainstreaming Climate Risk Management in Support of Climate Resilient Development 51 52 This chapter has assessed and detailed a number of decision-making tools (17.3) and enabling mechanisms 53 and catalysing conditions (17.4) that could be used in mainstreaming the management of climate risk and 54 adaptation in the sustainable development of communities, different sectors and nations. Since AR5, the 55 challenges facing the management of climate risks have been articulated (Adger et al., 2018; 56 Balasubramanian, 2018) and greater clarity on the steps that could be taken to better mainstream adaptation 57 has been developed (high confidence) (Cuevas, 2016; Giupponi and Gain, 2017a; Gomez-Echeverri, 2018; Do Not Cite, Quote or Distribute 17-102 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 Sanchez Rodriguez et al., 2018). Nevertheless, the choice of decision processes is recognized as being 2 dependent on a variety of local factors influencing development (Ayers et al., 2014; Szabo et al., 2016). 3 4 Adaptation strategies or plans, some of which incorporate elements of climate resilient development, have 5 been developed in many jurisdictions from local (Cuevas, 2016; Araos et al., 2016a; Reckien et al., 2018a; 6 G鰌fert et al., 2019) to provincial/state (Warnken and Mosadeghi, 2018) to national governments (Markolf 7 et al., 2015; CSIRO, 2018; Warnken and Mosadeghi, 2018; Brown et al., 2018a; Table 17.9). National 8 Adaptation Plans have been a requirement under the UNFCCC and establish the general approach taken by 9 nations for adapting to climate change (Woodruff and Regan, 2019). Integrated risk assessments and 10 adaptation processes are being developed but with much less experience evident in their implementation 11 (high confidence) (Wise et al., 2014; Woodruff and Stults, 2016; Brown et al., 2018a). 12 13 National Adaptation Plans (NAPs) submitted to the UNFCCC have been reviewed for quality by Woodruff 14 and Regan (2019). In their review, Woodruff & Regan used a number of indicators grouped within 15 established "quality principles". They found that the plans were more oriented at the strategic level or at the 16 level of specific projects rather than identifying methods for resolving cross-sectoral or cross-jurisdictional 17 interactions or issues (medium confidence). A key recommendation from their review and supported by other 18 studies (e.g. Abutaleb et al., 2018) is that plans would be improved greatly by having inputs from multiple 19 government agencies and multiple sectors (medium confidence), which could provide the basis for planning 20 and review of integrated adaptation. Also, the plans need greater attention to implementation (9.4.1, 11.8, 21 13.11.2), and the identification of metrics by which success (17.5.1) and performance can be measured 22 (Cross-Chapter Box PROGRESS in this Chapter), a common issue for adaptation planning generally (e.g. 23 12.5.2.6, 17.5). 24 25 Hence, satisfactorily managing intersecting climate risks in different settings, of which RKRs provide 26 examples, is central to achieving sustainable development (high confidence) (16.6.4), requiring integrated 27 risk management within and across regions, jurisdictions, sectors and ecosystems (high confidence) (more 28 cross references please CCP5.4.2; CCP5.4.3). Iterative processes will enable measuring progress and 29 updating adaptation at a satisfactory rate, in order to account for the different needs within regions and across 30 sectors at different times (high confidence). The degree to which equity and justice will be achieved will 31 be determined by the participatory processes in deciding on suitable adaptation options, the investment in the 32 adaptation processes and the coordination and collaboration built amongst institutions and people across 33 regions (high confidence). 34 35 36 [START FAQ17.1 HERE] 37 38 FAQ17.1: Which guidelines, instruments and resources are available for decision-makers to recognize 39 climate risks and decide on the best course of action? 40 41 Guidelines, instruments, and resources to identify options for managing risks, and support decisions on the 42 most suitable course of actions to take, can be collectively referred to as decision-support frameworks. These 43 can include data services, decision-support tools, processes for making decisions and methods for monitoring 44 and evaluating progress and success. Data services enable the identification, location and timing of risks that 45 could manifest with negative impacts, as well as potential opportunities. Often, these are termed `climate 46 services' and assist with mapping hazards and how they are changing. Decision-support tools range from 47 qualitative approaches to determine overlap of areas of concern with those hazards in the future, to more 48 quantitative and dynamic simulation approaches that enable dynamic stress-testing of adaptation options and 49 strategies to determine if proposed plans for adapting to the future could be successful. An important 50 consideration is whether options for risk management or capitalisation on opportunities will limit options and 51 flexibility for responding to unforeseen events in the future. If these options have a negative effect on other 52 areas of concern, then they could be identified in these planning scenarios as maladaptations, and therefore 53 avoided. 54 55 A great challenge for decision-makers is how to choose effective options when the future is 56 uncertain. Uncertainty can arise not just in the statistical error of the magnitude of risk but also in the nature 57 and consequence of risk from uncertainty about mechanisms that link areas of concern to hazards, Do Not Cite, Quote or Distribute 17-103 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 uncertainty in the decision processes itself and so on. Methods are available to help develop no-regret 2 options, commonly referred to as "decision making under conditions of deep uncertainty". 3 Decision-support frameworks are most successful when they are iterative, integrative, and consultative. 4 Rather than a single decision be made, and an action taken, there are processes for making the best decision 5 possible then monitoring progress toward delivering a successful outcome. Given a set of suitable indicators 6 with regular monitoring, decisions can be revised, updated, or changed as the future unfolds and foundations 7 for the original decision tested. This is important because climate responses need to be initiated well in 8 advance of them being needed due to the time required to implement suitable responses. These forward- 9 looking approaches allow errors to occur and corrections made before problems arise. They also enable 10 action to be taken without having to wait for the circumstances to arise, which if this were to occur could 11 result in only limited reactions being available and the outcomes then dependent upon recovery from events 12 rather than proactive planning and avoidance of events. Integrated approaches to risk management are 13 available to help manage portfolios of interacting risks, including the potential for compounding and 14 cascading risks when climate-related events arise. 15 16 Managing uncertainty with forward-looking processes needs to be more deliberative and oriented towards 17 building trust in a collaborative process. Building relationships through informal, bottom-up processes 18 enables this to occur. Top-down planning processes are important for ensuring the management of risks and 19 opportunities do not end up with maladaptations and that the approaches are equitable and proportional to 20 that which is needed to manage the risks. 21 22 [END FAQ17.1 HERE] 23 24 25 [START FAQ17.2 HERE] 26 27 FAQ17.2: What financing options are available to support adaptation and climate resilience? 28 29 What do we mean by "climate finance"? 30 The UNFCCC has no formally agreed definition of climate finance. The current IPCC definition is: "the 31 financial resources devoted to addressing climate change by all public and private actors from global to 32 local scales, including international financial flows to developing countries to assist them in addressing 33 climate change" (see Annex I: Glossary). 34 35 What needs to be financed? 36 Financial resources might be needed for a range of adaptation and resilience building activities. These 37 include research, education and capacity building; development of laws, regulations, and standards; 38 provision of climate services and other information; reducing the vulnerability of existing assets, activities, 39 and services; and ensuring future development - such as new infrastructure, settlements, health services and 40 business activities - is climate resilient. Finance is also needed to recover and rebuild from the damage of 41 climate hazards that cannot be completely avoided through adaptation. Adaptation actions can be undertaken 42 by many different actors, alone or in partnership, including national and sub-national governments, public 43 and private utilities, businesses of varying size, communities, households, and individuals. 44 45 46 Table FAQ17.2.1 Examples of adaptation and resilience activities that might need to be financed Training of agricultural extension officers so that their A new urban development requires higher standards (and advice to small-holder farmers can support up-front costs) for buildings, roads, stormwater systems, implementation of climate adapted agriculture. water re-use and to be resilient to expected changes in Additional financial support is needed for the costs of heavy rainfall, runoff, temperature, and water supply farmers transitioning to climate resilient agricultural reliability. practices. A water utility requires capital expenditure to increase A catastrophe risk insurance facility is established to supply through a desalination plant and to reduce leakage provide post-disaster (drought, hurricane, flooding, pest from its reticulation system in response to a scenario of outbreaks) recovery finance to national governments. Do Not Cite, Quote or Distribute 17-104 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report reduced surface water availability and an increase in The facility requires capital to be able to underwrite the customers. insurance products it offers. 1 2 3 How much finance is needed? 4 The amount of adaptation finance depends on global, regional, and local factors, including: the amount and 5 timing of global warming, how this translates into impacts and adaptation needs across the world; the levels 6 of adaptation already in place; the type of risk being adapted to; and the adaptation options being chosen, 7 including whether the adaptation required is incremental or transformational. 8 9 The most mentioned figure for finance need is the developed countries commitment to provide USD 100 10 billion per year by 2020 to support developing countries efforts in mitigation and adaptation. Negotiations 11 will start in 2021 on updating this amount for 2025. While sometimes thought to represent the actual cost of 12 responding to climate change in developing countries, this is not the case. More recent estimates of the 13 global cost of adaptation by 2030 across developed and developing countries range between about USD 80- 14 300 billion per year. 15 16 What types of finance are available? 17 Four main types (or instruments) of finance are currently being used to support adaptation. These different 18 types are not mutually exclusive; grants can be combined with loans to provide blended finance. 19 20 21 Table FAQ17.2.2 The main instruments through which adaptation is being financed Grants provide finance without any repayment Concessional loans require partial repayment of the requirements. Most grants for adaptation have been finance provided. These involve either capital provided by multilateral funds such as the Green Climate repayment coupled to below market interest rates or Fund or a fund managed by a single OECD country such capital repayment only. Concessional finance is almost as Germany's International Climate Initiative. Some entirely provided through multilateral development countries have national climate or environment funds banks such as the World Bank. This finance is that provide grants for their own climate adaptation particularly important for developing countries where actions. Grants are also provided by philanthropic market interests are high due to poor credit ratings or foundations and sometimes by companies as part of their other risk factors, or where the return on investment is environmental and social responsiveness mandate. too low make a commercial loan viable. Non-concessional loans (or debts) are commercial Budget reallocation does not require raising of new instruments, where capital repayment and market interest finance; rather it involves moving funds already secured rates apply. These may be provided through away from other purposes towards adaptation. In development banks or private banks. Green bonds are a government, this might involve reallocation towards relatively new form of market loan, designed to meet flood defence. In the private sector a company might climate and other environmental sustainability criteria in move budget from marketing, research and development, terms of how the proceeds are used. In recent years or perhaps dividends, towards increasing the climate green bonds have offered better interest than ordinary resilience of operation, infrastructure or their value bonds due to oversubscription by investors who are chain. looking to move towards environmentally sustainable investment portfolios. 22 23 24 Where are different types of finance most useful? 25 Grants are useful for a range of adaptation actions where it is hard to generate a financial return. These 26 include capacity building activities, piloting new adaptation innovations, high risk investment settings, or 27 projects where there are considerable non-financial benefits. In contrast loans and other debt instruments can 28 often support larger investments, for example for scaling out of successful pilot projects or for building 29 adaptation and resilience into general development investment. To date, a large proportion of international 30 climate finance for adaptation in developing countries, especially in sub-Saharan Africa and Oceania has 31 been grant led, sourced from OECD public funds, indicating that in many instances financing via loans is 32 either considered too risky by the commercial investment sector or it has been hard to demonstrate sufficient 33 return on investment. 34 Do Not Cite, Quote or Distribute 17-105 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 3 Figure FAQ17.2.1. The distribution of adaptation finance across different regions and different types of finance in 4 2015-2016, as tracked the Climate Policy Initiative. The size of each circle represents the amount of finance, with 5 amount in billions USD superimposed. Based on data tracked by the Climate Policy Initiative. 6 7 8 [END FAQ17.2 HERE] 9 10 11 [START FAQ17.3 HERE] 12 13 FAQ17.3: Why is adaptation planning along a spectrum from incremental to transformational 14 adaptation important in a warming world? 15 16 In a warming world, incremental adaptation, i.e. proven standard measures of adaptation, will not always 17 suffice to adjust to the negative impacts from climate change leading to substantial residual risks and, in 18 some cases, the breaching of adaptation limits; transformational adaptation, involving larger system-wide 19 change (as compared to in system change), will increasingly be necessary as a complement for helping 20 individuals and communities to cope with climate change. As an example of incremental adaptation, a 21 farmer may decide to use drought-tolerant crops to deal with increasing occurrences of heatwaves. With 22 further warming and increases in heat waves and drought, however, the impacts of climate change may 23 necessitate the consideration of system-wide change, such as moving to an entirely new agricultural system 24 in areas where the climate is no longer suitable for current practices; or switching to livestock rearing. Where 25 on-site adaptation becomes infeasible and pull factors exist, the farming households may decide to seek 26 employment in other sectors, which may also lead to migration for work. As another example, physical 27 protection through sea walls to stop coastal flooding is a proven adaptation measure. With further projected 28 flooding due to increasing sea level rise attributable to climate change transformational city planning, that 29 would systemically change how flood water is managed throughout the whole city requiring deeper 30 institutional, structural, and financial support, may become necessary. Also, the deliberate relocation of 31 settlements (managed retreat) is seeing attention in the face of increasingly severe coastal or riverine 32 flooding in some regions. While transformational adaptation is increasingly being considered in theory and 33 planning, implementation is only beginning to see attention. 34 35 [END FAQ17.3 HERE] 36 37 38 [START FAQ17.4 HERE] 39 Do Not Cite, Quote or Distribute 17-106 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 FAQ17.4: Given the existing state of adaptation, and the remaining risks that are not being managed, 2 who bears the burden of these residual risks around the world? 3 4 A warming climate brings along increasing risks, part of which can be reduced or insured. What remains is 5 called residual risks and needs to be retained by households, the private and public sectors. People living in 6 conflict-affected areas benefit only marginally from adaptation investments by governments, private sector, 7 or other institutions. These people bear most of the changing climate risks themselves. Higher-income 8 countries generally have invested heavily in structural adaptation to make sure people are not exposed to 9 extreme events (e.g. dykes) and have developed a variety of private or public insurance systems to finance 10 the risk of the most rare or extreme events. In other, middle or lower-income countries, these very extreme 11 events are less likely to be insured, and the impacts are borne by the most vulnerable people. Absent risk 12 reduction or insurance, coping with residual risks generally means reducing consumption (e.g. food) or 13 drawing down assets (selling machinery, houses etc), which all can bring along longer-term adverse 14 developmental implications. Adaptation investments in low-income countries tend to focus more heavily on 15 increasing capacity and reducing vulnerability; people remain exposed to the changing climate risks, and 16 bear the burden of reacting and responding. 17 18 [END FAQ17.4 HERE] 19 20 21 [START FAQ17.5 HERE] 22 23 FAQ17.5: How do we know whether adaptation is successful? 24 25 Adaptation aims to reduce exposure and vulnerability to climate change by responding to dynamic and 26 multi-scalar combinations of climatic risks. What might be seen as successful at one scale or at one point in 27 time might not be at another, particularly if climate risks continue to rise. Moreover, the benefits of 28 adaptation interventions may not reach all intended beneficiaries or everyone affected by climate impact and 29 risk, causing different people to have different views on how successful adaptation has been. 30 31 There is, therefore, no universal way to measure adaptation success, but there is high agreement that success 32 is associated with a reduction of climate risks and vulnerabilities (for humans and ecosystems) and an 33 equitable balancing of synergies and trade-offs across diverse objectives, perspectives, expectations, and 34 values. Adaptation that is successful is also commonly expected to be inclusive of different socio-economic 35 groups, especially the most vulnerable, and to be based on flexible and integrative planning processes that 36 take into account different climate scenarios. 37 38 Conceptually, the opposite of successful adaptation is maladaptation, i.e. when adaptation responses produce 39 unintended negative side effects such as exacerbating or shifting vulnerability, increasing risk for certain 40 people or ecosystems, or increasing greenhouse gas emissions. Among the adaptation options assessed in this 41 report (Figure FAQ 17.5.1), physical infrastructure along coasts (e.g., sea walls) has the highest risk for 42 maladaptation over time through negative side-effects on ecosystem functioning and coastal livelihood 43 opportunities. However, such adaptations may appear valuable in the short and even longer term for already 44 densely populated urban coasts, demonstrating that an adaptation can be differently judged based on the 45 context it is implemented in (Figure FAQ 17.5.1). Many other adaptation options have a larger potential to 46 contribute to successful adaptation (Figure FAQ17.5.1), such as nature restoration, providing social safety 47 nets, and changing diets/ minimizing food waste. 48 49 Do Not Cite, Quote or Distribute 17-107 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 2 Figure FAQ17.5.1: Contribution of adaptation options to potentially successful adaptation and to the risk of 3 maladaptation. Note: A similar figure is part of Ch17.5.2. 4 5 6 Assessments of adaptation need to be transparent about how they are measuring success. Monitoring and 7 Evaluation (M&E) can be used to track progress and evaluate success and to identify if course corrections 8 during adaptation implementation are needed to achieve the envisaged objectives. Given the diversity of 9 adaptation actions and contexts, no one-size-fits-all approach to M&E and no common reference metrics for 10 adaptation exist. To date, assessments of progress of adaptation have often focused on processes and outputs 11 (i.e. actions taken, such as adaptation plans adopted) that are easier to measure than the effects of these 12 actions in terms of long-term reduction of risks and vulnerabilities. However, knowledge about the outcomes 13 in terms of reducing climate risk, impact and vulnerability is critically required to know if adaptation has 14 been successful. 15 16 Tracking progress, in particular outcomes and impacts of adaptation, involves a number of challenges. First, 17 in order to determine progress over time, risk and vulnerability assessments need to be repeated at least once 18 after starting an adaptation process. This is rarely done, as it demands resources that are usually not factored 19 into the adaptation response. Second, attributing changes in climate risks and vulnerabilities to the adaptation 20 response is often difficult due to other influencing factors, such as socio-economic development over time. 21 Expected causal relationships between responses and their outcomes should already be outlined during the 22 adaptation planning phase, for example by mapping the way from activities to outcomes, and they should be 23 monitored during implementation. Third, as adaptation can occur in multiple forms and target multiple 24 temporal and spatial scales, the engagement of a diversity of stakeholders is vital to understand how Do Not Cite, Quote or Distribute 17-108 Total pages: 156 FINAL DRAFT Chapter 17 IPCC WGII Sixth Assessment Report 1 responses enable adaptation and adaptation success across vulnerable groups. Though, stakeholder 2 engagement can be time intensive and costly, in particular when reaching out to populations that are usually 3 not part of policy and planning processes it can support evaluating co-benefits and trade-offs of adaptation 4 responses. Consideration and analysis of co-benefits and trade-offs along with a focus on short, medium, and 5 long time horizons of adaptation goals, which is usually possible through flexible and strong institutions, 6 facilitate successful adaptation and reduce the likelihood of maladaptation. 7 8 [END FAQ 17.5 HERE] 9 10 11 Do Not Cite, Quote or Distribute 17-109 Total pages: 156