Editing IPCC:AR6/WGII/Chapter-17 (section)

== 17.4 Enabling and Catalysing Conditions for Adaptation and Risk Management ==

<div id="17.4.1" class="h2-container"></div>

<span id="introduction-1"></span>
=== 17.4.1 Introduction ===

<div id="h2-8-siblings" class="h2-siblings"></div>

The WGII AR5 identified—with ''high confidence'' —a range of factors that could enable or limit planning and implementation of adaptation options and potentially their effectiveness ( [[#Klein--2014|Klein et al., 2014]] ; [[#Mimura--2014|Mimura et al., 2014]] ; [[#Noble--2014|Noble et al., 2014]] ). These included governance, finance, knowledge and capacity as enabling factors, as well as cultural, social, political and economic differences that influence individual and collective willingness and capability to act. The AR6 Special Reports (specifically, [[#de%20Coninck--2018|de Coninck et al., 2018]] ; [[#Roy--2018|Roy et al., 2018]] ; Collins et al., 2019; [[#Hurlbert--2019|Hurlbert et al., 2019]] ) reinforced the AR5 findings, further noting that the transitions needed for climate resilient development would need to be supported by radical shifts in governance, knowledge development, technology application, finance and economics, and social norms.

This section builds on the AR5 and AR6 Special Reports by reviewing new evidence on three key enablers identified in the AR5: governance, finance and knowledge. The focus is on assessing new evidence on (i) understanding of these enabling conditions, (ii) how they have changed on the ground and (iii) whether these conditions have enabled progress on adaptation and risk management. The section also addresses an emerging related topic: the role of catalysing conditions and actors in accelerating action on climate change adaptation, such as litigation on failure to adapt, understandings of urgency, and the aftermath of extreme weather events. While enabling conditions are necessary for action, they are not by their presence enough; catalysing conditions emerge when game-changing circumstances become present, such as when a high-profile extreme weather event occurs or when a champion drives change in an organisation.

<div id="17.4.2" class="h2-container"></div>

<span id="enabling-condition-1-governance"></span>
=== 17.4.2 Enabling Condition 1: Governance ===

<div id="h2-9-siblings" class="h2-siblings"></div>

Governance is an inclusive concept of the range of means for deciding, managing, implementing and monitoring climate change responses. It can involve contributions of various levels of government (global, international, regional, sub-national and local) along with those from the private sector, of non-governmental organisations and of civil society. The importance of supportive governance arrangements is re-iterated widely across regional and sectoral chapters in this report, in multiple different contexts ( ''very high confidence'' ).

<div id="17.4.2.1 " class="h3-container"></div>

<span id="legal-policy-and-regulatory-instruments"></span>
==== 17.4.2.1 Legal, Policy and Regulatory Instruments ====

<div id="h3-20-siblings" class="h3-siblings"></div>

<div id="17.4.2.1.1" class="h4-container"></div>

<span id="climate-legislation"></span>
===== 17.4.2.1.1 Climate legislation =====

<div id="h4-10-siblings" class="h4-siblings"></div>

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

National climate change laws are important for transposing ratified international commitments into domestic regimes, such as the Paris Agreement and the Convention on Biodiversity, as well as voluntary agreements such as the Sendai Framework for Disaster Risk Reduction. In turn, the enactment of domestic laws can yield useful experiences and foster engagements that positively influence and support the development of international commitments ( [[#Townshend--2013|Townshend and Matthews, 2013]] ; [[#Mehling--2015|Mehling, 2015]] ). Strong and consistent regulatory frameworks also support the flow of climate finance to developing countries that have such frameworks ( [[#Nachmany--2017|Nachmany et al., 2017]] ). The successful implementation of national and sub-national climate change and related policies and strategies are often contingent upon the underlying legislative framework empowering, mandating or guiding their review, implementation and enforcement ( [[#Averchenkova--2017|Averchenkova and Matikainen, 2017]] ; [[#Scotford--2017|Scotford et al., 2017]] ) ( ''medium confidence'' ).

Existing legal systems also pose potential barriers to adaptation, as described in [[IPCC:Wg2:Chapter:Chapter-9|Chapter 9]] (Africa) and [[IPCC:Wg2:Chapter:Chapter-8|Chapter 8]] (Poverty, Livelihoods and Sustainable Development). Laws may reinforce governance arrangements and regulations that do not support responses to climate change, and exacerbate existing vulnerabilities and inequalities (Craig, 2010; [[#Arnold--2013|Arnold and Gunderson, 2013]] ; [[#Wenta--2019|Wenta et al., 2019]] ). In such cases, laws may require review and revision or replacement, and at the same be written in ways that foster adaptive management (Craig, 2010; [[#Ruhl--2010|Ruhl, 2010]] ; [[#Cosens--2017|Cosens et al., 2017]] ).

Even though there is no agreed definition of or typology for climate change laws ( [[#Mehling--2015|Mehling, 2015]] ), studies have tended to classify climate change laws as being ‘framework’ or ‘sectoral’ (see Table 17.5 for examples). Framework laws offer a comprehensive, unifying basis for climate change policy, addressing multiple aspects or areas of climate change mitigation or adaptation (or both) in a holistic and overarching manner ( [[#Townshend--2011|Townshend et al., 2011]] ; [[#Fankhauser--2014|Fankhauser et al., 2014]] ; [[#Nachmany--2015|Nachmany et al., 2015]] ; [[#Clare--2017b|Clare et al., 2017b]] ); they are powerful levers for setting national and sub-national agendas, creating climate change institutional structures, enabling policy implementation and driving the passage of additional sectoral legislation and regulations ( [[#Clare--2017b|Clare et al., 2017b]] ). Prior to 2010, national framework laws tended to have a mitigation focus, while more recent laws or amendments thereto have an increased adaptation focus ( [[#Rumble--2019b|Rumble, 2019b]] ). No evidence indicates whether general or specific framework laws yield better outcomes; however, reviews of more recent examples of framework laws in Africa suggest a trend towards more specificity in the required content of adaptation strategies and duties ( [[#Rumble--2019b|Rumble, 2019b]] ).

A sectoral approach to climate change legislation grafts climate-related provisions into existing laws, such as environmental impact assessment, flood insurance and infrastructure planning, collectively creating an aggregated legal landscape ( [[#Townshend--2011|Townshend et al., 2011]] ; [[#Gerrard--2012|Gerrard and Fischer, 2012]] ; [[#Nachmany--2015|Nachmany et al., 2015]] ; [[#Scotford--2017|Scotford et al., 2017]] ; [[#Rumble--2019a|Rumble, 2019a]] ). This approach is particularly relevant to adaptation challenges which intersect with numerous bodies of law that are dedicated to other societal concerns ( [[#Gerrard--2012|Gerrard and Fischer, 2012]] ). However, integrating such considerations can be challenging in certain areas of law, particularly those relating to property rights, water rights and endangered species protection ( [[#Gerrard--2012|Gerrard and Fischer, 2012]] ). The incorporation of adaptive management principles (including monitoring, periodic evaluation, and response modification) within existing laws can enhance their enabling role and foster greater resilience ( [[#Godden--2012|Godden, 2012]] ; [[#Arnold--2013|Arnold and Gunderson, 2013]] ; [[#McDonald--2014|McDonald and Styles, 2014]] ).

The legal regime for adaptation is too embryonic for assessment of good practice design and content, although similarities can be seen in the framework laws and draft bills across several countries. Some studies highlight the importance of domestic ‘whole of legal system’ analysis prior to development of modifying law. This can identify the range of existing legislative instruments that can directly intersect with climate change, along with related contextual factors such as national circumstances, governance frameworks, and political and economic realities as well as national administrative culture ( [[#Scotford--2017|Scotford et al., 2017]] ). This helps any new climate change laws to be absorbed into, and harmonise with, the established legal system of each country ( [[#Scotford--2017|Scotford et al., 2017]] ). Efforts are underway to assist countries in such assessments and the identification of areas for legislative reform, for example through the Commonwealth and UN Environment’s Law and Climate Change Toolkit. Similarly, databases such as the Grantham Research Institute on Climate Change and the Environment and the Sabin Center on Climate Change Law are expanding the knowledge base of national climate legislation developments.

'''Table 17.5 |''' Selected examples of framework and sectoral law approaches adopted by different nations that represent a variety of regional contexts.

{| class="wikitable"
|-
! Example

! Legal approach

! Description

! References

|-
| United Kingdom Climate Change Act 2008

| Framework

| Provides for development of climate change impact 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.

| Averchenkova et al. (2021)

|-
| Kenya Climate Change Act 2016

| Framework

| Modelled on the United Kingdom Climate Change Act. Provides for development of climate change impact 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.

| [[#Rumble--2019b|Rumble (2019b)]]

|-
| Mexican General Law on Climate Change 2012

| Framework

| Imposes positive duties upon government to implement ‘adaptation actions’—conservation, sustainable use and rehabilitation of beaches and coasts; water programmes for watersheds; the establishment of protected areas and biological corridors; the development of risk atlases; human settlement and urban development programmes; and prevention programmes targeting diseases exacerbated by climate change. Includes development of economic instruments, including fiscal incentives, credits, bonds, civil liability insurance and market-based instruments.

| Averchenkova and Guzman Luna (2018)

|-
| New Zealand Exclusive Economic Zone and Continental Shelf (Environmental Effects) Act 2012

| Sectoral

| Incorporates adaptive management principles by regulating the issuance of marine consents with conditions allowing change based on ecological change and indicators.

| [[#Godden--2012|Godden (2012)]]

|-
| Seychelles Conservation and Climate Adaptation Trust of Seychelles Act 18 of 2015

| Sectoral

| Provides for the establishment of a dedicated trust fund for conservation measures and climate change adaptation measures.

| [[#Etongo--2021|Etongo et al. (2021)]]

|-
| Commonwealth of Dominica Climate Resilience Act 16 of 2018

| Sectoral

| Promotes disaster recovery and resilience building. Establishes the Dominica Climate Resilience Policy Board and sets out its functions and duties. Requires the development of a Climate Resilience and Recovery Plan.

| [[#Government%20of%20the%20Commonwealth%20of%20Dominica--2018|Government of the Commonwealth of Dominica (2018)]]

|-
| Swedish National Strategy for Climate Change Adaptation (Government Proposition 2017/18:163)

| Sectoral

| Amends Sweden’s Planning and Building Act (2010: 900) by requiring municipalities to assess the risk of damage to the built environment from climate risks as well as how such risks may change in the future; requires detailed plans for measures to address land permeability when issuing a land permit; adopts the Swedish National Climate Strategy into law.

| [[#Government%20of%20Sweden--2017|Government of Sweden (2017)]]

|-
| Argentinian Glaciers Preservation Law N 32.016 (2010)

| Sectoral

| Provides for minimum budgets to protect the national glacial water sources that supply the Mendoza oasis. Establishes that all of Argentina’s glaciers and its periglacial environment are to be protected, irrespective of size.

| [[#Warner--2019|Warner et al. (2019)]]

|-
| Netherlands Delta Act on Water Safety and Fresh Water Supply

| Sectoral

| Protects the Netherlands from risks such as sea level rise and extreme rainfall. Establishes a Delta Programme to secure fresh water supply and address climate risks/sea level rise; a Delta Fund to operate the programme and a commissioner.

| [[#Van%20Alphen--2016|Van Alphen (2016)]]

|}

<div id="17.4.2.1.2" class="h4-container"></div>

<span id="climate-change-policies-strategies-and-plans"></span>
===== 17.4.2.1.2 Climate change policies, strategies and plans =====

<div id="h4-11-siblings" class="h4-siblings"></div>

Climate change policies and plans are important in the translation of national commitments and legal requirements into specific on the ground strategies and guidelines, which enable actions across multiple spheres and scales of government and non-government institutions and actors.

Substantial developments in adaptation policy have occurred since AR5 ( ''high confidence'' ). Perhaps the most significant is the NDCs required under the Paris Agreement, where 184 out of 197 parties to the UNFCCC have already submitted their first plans ( [[#UNDP%20and%20UNFCCC--2019|UNDP and UNFCCC, 2019]] ). The NDCs have allowed countries to articulate their priorities and ambition with respect to climate action, and it has been suggested that these can in turn lead to cascading policies (and laws) that drive and enable adaptation and climate risk management. Analysis of the first NDCs submitted in the lead-up to and after the Paris Agreement showed that adaptation priorities were more often articulated by developing countries and least developed countries, while developed countries and emerging economies focused mostly on mitigation (Pauw et al., 2019). As of 2019, over 90 developing nations are at various stages of preparing National Adaptation Plans and 112 nations have indicated their intention to revise their NDCs for the 2020 update ( [[#UNDP%20and%20UNFCCC--2019|UNDP and UNFCCC, 2019]] ).

Several other international agreements, including the Sendai Framework for Disaster Risk Reduction and the UN Agenda 2030 Sustainable Development Goals, have had significant impacts on the adaptation and risk-management decision-making processes. For example, the Sendai Framework articulates the need for improved understanding of disaster risk in all its dimensions of exposure, vulnerability and hazard characteristics; accountability for disaster risk management; preparedness to ‘Build Back Better’; recognition of stakeholders and their roles; mobilisation of risk-sensitive investment to avoid the creation of new risk resilience of health infrastructure, cultural heritage and workplaces; strengthening of international cooperation and partnership; and risk-informed donor policies and programmes, including financial support and loans from international financial institutions.

Specific adaptation policies have been formulated at national, regional/state and local levels across 68 countries and 136 coastal cities ( [[#Olazabal--2019a|Olazabal et al., 2019a]] ). At the national level, the quantity and complexity of adaptation policies have increased since AR5, with most policies coming into force since 2009 ( [[#Nachmany--2018|Nachmany and Setzer, 2018]] ). Adaptation is addressed in the executive climate policies of at least 170 countries ( [[#Nachmany--2019a|Nachmany et al., 2019a]] ). Documented sub-national adaptation policies are more prevalent in developed countries and emerging economies, as compared with low- and middle-income ones ( [[#Olazabal--2019b|Olazabal et al., 2019b]] ). For example, by 2017, 26% of large and medium-sized European cities had an adaptation plan or a joint adaptation–mitigation plan in place ( [[#Reckien--2018a|Reckien et al., 2018a]] ).

Adaptation policies often comprise multiple goals and instruments, which develop over time, especially where jurisdiction over policy issues is shared among agencies or levels of government ( [[#Río--2013|Río and Howlett, 2013]] ). The increase in the number and complexity of policy instruments across geared towards adaptation raises questions of coherence and alignment between the selected policy mixes and their effectiveness ( [[#England--2018|England et al., 2018]] ; [[#Ranabhat--2018|Ranabhat et al., 2018]] ; [[#Lesnikowski--2019|Lesnikowski et al., 2019]] ).

Evaluation of national adaptation plans (NAPs) has only recently been undertaken. [[#Woodruff--2019|Woodruff and Regan (2019)]] compared national adaptation plans from 38 countries and concluded that most were strong in identifying vulnerabilities and identifying potential adaptation options but were weaker in articulating implementation pathways and monitoring of progress; plans written by multi-agency teams were nearly always of higher quality. [[#Garschagen--2021|Garschagen et al. (2021)]] showed that, while most NAPs consider future changes in climate hazard, many do not consider how vulnerability and exposure might change, concluding that this limits the potential effectiveness of the plans. Morgan et al. (2019) showed that NAPs that are consistent with the Paris Agreement can enable development pathways that promote synergies between environmental, social and economic goals.

<div id="17.4.2.1.3" class="h4-container"></div>

<span id="impact-of-legal-and-policy-instruments"></span>
===== 17.4.2.1.3 Impact of legal and policy instruments =====

<div id="h4-12-siblings" class="h4-siblings"></div>

Commitment to act, and guidance on how to do so, from international and national governance levels can drive national and sub-national adaptation ( [[#Reckien--2013|Reckien et al., 2013]] ; [[#Heidrich--2016|Heidrich et al., 2016]] ; [[#Reckien--2018a|Reckien et al., 2018a]] ). For example, more local plans have been developed in European countries where it is obligatory for local municipalities to develop climate change plans ( [[#Reckien--2018a|Reckien et al., 2018a]] ). Local government have also drawn on non-binding national climate frameworks, as well as international frameworks (such as European law) or international networks (such as Global Covenant of Mayors for Climate and Energy) to guide their actions ( [[#Reckien--2013|Reckien et al., 2013]] ; [[#De%20Gregorio%20Hurtado--2015|De Gregorio Hurtado et al., 2015]] ; [[#Reckien--2015|Reckien et al., 2015]] ; [[#Heidrich--2016|Heidrich et al., 2016]] ; [[#Reckien--2018a|Reckien et al., 2018a]] ).

However, a national framework is not always sufficient to trigger climate change action on the lower level, in particular when the national guiding document fails to clearly formulate how it should be used and ‘translated down’ to lower governance levels ( [[#De%20Gregorio%20Hurtado--2015|De Gregorio Hurtado et al., 2015]] ). Guidance on how to apply a national framework at lower governance levels can assist in their uptake.

In the case of climate change legislation, research on the impact of adaptation laws is limited, save for a few studies ( [[#Averchenkova--2017|Averchenkova and Matikainen, 2017]] ), because many framework laws, particularly those with more of an adaptation focus, have only been published recently ( [[#Rumble--2019b|Rumble, 2019b]] ). Reviews of the implementation of the risk assessment and adaptation components of the UK’s Climate Change Act 2008 suggest that they had a weaker implementation record compared with mitigation provisions ( [[#Fankhauser--2018|Fankhauser et al., 2018]] ), potentially because implementation of adaptation is more complex as compared with mitigation as shown for the local level ( [[#Reckien--2019|Reckien et al., 2019]] ). However, the UK Act is considered to have made action on climate change more predictable, more structured and more evidence based ( [[#Averchenkova--2021|Averchenkova et al., 2021]] ).

There are numerous examples of regulatory and project-based innovations by local governments. Their impact, however, is uneven, with much depending on the implementation capacity of local governments and other socio-institutional barriers, including those relating to mandate and joint project implementation, cross-departmental working, planning cycles, concerns relating to legal liability and compensation, political appetite and cost ( [[#Godden--2012|Godden, 2012]] ; [[#Taylor--2016a|Taylor, 2016a]] ). Notwithstanding implementation challenges, evidence is emerging that overarching framework laws play a foundational and distinctive role in supporting effective climate governance, including adaptation governance ( [[#Fankhauser--2018|Fankhauser et al., 2018]] ), and are drivers of subsequent activity ( [[#Townshend--2011|Townshend et al., 2011]] ; [[#Fankhauser--2014|Fankhauser et al., 2014]] ; [[#Clare--2017b|Clare et al., 2017b]] ), especially when formulated with clear guidance for all related actors, including lower level of governance ( [[#De%20Gregorio%20Hurtado--2015|De Gregorio Hurtado et al., 2015]] ). This may explain the rapid increase in both local and national climate change laws, now with an increased emphasis on regulatory provisions to increase resilience and reduce vulnerability.

<div id="17.4.2.1.4" class="h4-container"></div>

<span id="regulations-and-standards"></span>
===== 17.4.2.1.4 Regulations and standards =====

<div id="h4-13-siblings" class="h4-siblings"></div>

The presence and articulation of regulations and standards that address climate risk, such as building codes and land use zoning are key enabling factors for effective decision-making ( [[#Kim--2020|Kim et al., 2020]] ). Regulations and standards provide a framework for common understanding of when and under what conditions action should be taken specifically in relation to the construction and maintenance of the built environment, infrastructure and environmental and social practice ( [[#Grynning--2020|Grynning et al., 2020]] ). Regulations and standards for climate action emerge primarily from two settings: first, as an addition or augmentation to existing regulations and standards that emerged initially to address existing potential climate extremes and stresses (e.g., size of culverts in response to maximum rainfall and runoff conditions); and second, new regulations and standards that were developed in direct response to new or emergent climate risks (e.g., regulations in response to new presence of mean monthly high tide flooding) ( [[#Qiao--2018|Qiao et al., 2018]] ). Commonly agreed upon social norms and conventions also can be described as regulatory and providing a set of standards.

The regional and sectoral chapters of this report provide significant evidence of how regulations and standards enhance or hinder opportunities for climate risk management and adaptation. Relevant regulations and standards are especially evident in the oceans and coastal domains ( [[IPCC:Wg2:Chapter:Chapter-3|Chapter 3]] and CCP2, in cities and infrastructure (Chapter 6), and the water (Chapter 4) and food sectors (Chapter 5). Europe and North and South America (Chapters 12, 13 and 14) have the most frequent documented occurrences of examples of regulations and standards. Regulations and standards focused on building codes to protect against extreme event and loss, water regulations and agreements to protect water supply and lessen drought impacts, and health codes to limit heat exposure are the most frequent examples of such practices. Deficiencies of regulations and standards have been noted with respect to their capacity to manage species migrating from climate change, and to provide opportunities for transformative adaptation. The evidence from the sectors and chapters illustrate that more comprehensive regulations and standards lead to positive adaptation outcomes.

<div id="17.4.2.1.5" class="h4-container"></div>

<span id="environmental-and-social-governance"></span>
===== 17.4.2.1.5 Environmental and social governance =====

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

Environmental and social governance refers to voluntary or non-legally required actions taken by participating parties to achieve a commonly defined goal ( [[#Bodin--2017|Bodin, 2017]] ; [[#DeCaro--2017|DeCaro et al., 2017]] ; [[#Partzsch--2020|Partzsch, 2020]] ). While not explicitly described in the sectoral and regional chapters of this report, the maintenance and exercise of environmental and social governance decision-making strategies do enable adaptation practice and have become especially important when formal legal and policy regimes are not yet present. As formal regulation promotes clear and common understanding of climate risks and mechanisms to develop context specific appropriate solutions, voluntary code-making and self-regulation can forestall the need for legal action or can function as precursors to the formulation and implementation of legislation, laws and regulations.

Social and environmental governance has long been presented within climate risk decision-making, although more typically in the domain of climate mitigation ( [[#Wright--2016|Wright and Nyberg, 2016]] ; [[#Vandenbergh--2017|Vandenbergh and Gilligan, 2017]] ). Corporate climate decision-making emphasises the importance of profit motives in shaping decisions; however, reputational factors as appropriate environmental stewards can also be important when linked to sensitivity of other stakeholders such as investors, lenders, customers and employees ( [[#Vandenbergh--2017|Vandenbergh and Gilligan, 2017]] ). [[#Pulver--2011|Pulver (2011)]] notes that climate issues influence corporate decision-making more strongly in organisations that are networked with other organisations that also consider these issues and through direct experience with climate-related events and associated organisational learning.

Since AR5, more case studies of social and environmental governance within the domain of climate adaptation have become evident, especially within the context of adaptive management experimentation ( [[#Vella--2016|Vella et al., 2016]] ; [[#Beunen--2019|Beunen and Patterson, 2019]] ; [[#Blühdorn--2019|Blühdorn and Deflorian, 2019]] ). Environmental and social governance strategies for climate adaptation are diverse and reflect context-specific conditions of the decision-making process, including the role of the state, the individual and private interests, formality/informality, social responsibility, sources of financing, and transparency. Environmental and social governance enables the testing and definition of implementation solutions, enhancing the opportunities for defining successful adaptation ( [[#Surminski--2013|Surminski, 2013]] ). Several models and approaches to adaptive governance to promote adaptation and resilience in response to extreme weather events have been observed. These include polycentric and multilayered institutions, participation and collaboration, self-organisation and networks, and learning and innovation ( [[#Djalante--2011|Djalante et al., 2011]] ).

The effectiveness of social and environmental governance varies by sector. For example, in the private business sector, Aragòn-Correa et al. (2019) assess the effects of mandatory and voluntary regulatory pressure on firms’ environmental strategies. In summary, they find that analyses of the effects of voluntary pressure demonstrate that by themselves they are unlikely to bring about significant improvement in environmental outcomes. Professional organisations, however, have made progress in addressing sectoral standards relative to the adaptation process. This includes the development of new industry guidelines, codes, standards and specifications, in addition to the implementation of infrastructure inventories that incorporate evaluation of vulnerabilities and identification of priority at-risk areas (Chapter 14). Voluntary pressures by themselves are not likely to result in positive outcomes and instead should be coupled with mandatory regulatory pressure to achieve the environmental response desired ( [[#Bianco--2020|Bianco, 2020]] ).

Since AR5, another key development in environmental and social governance has been the establishment of the Task Force on Climate-related Financial Disclosures (TCFD), which aimed to develop guidelines for companies to voluntarily report the financial implications of two broad categories of climate risk: the transition risks of shifting to a lower-carbon economy and the physical risks of climate change itself ( [[#TCFD--2017|TCFD, 2017]] ). As of 2019, ~1340 companies with a market capitalisation of USD 12.6 trillion and financial institutions responsible for assets of USD 150 trillion have expressed support for the TCFD ( [[#TCFD--2020|TCFD, 2020]] ). An analysis of reports to the TCFD in 2016 showed that 83% of companies report on physical risks of climate change, and of these, 82% reported on strategies to adapt to some of the identified risks ( [[#Goldstein--2019|Goldstein et al., 2019]] ). The same analysis also noted that: (i) the total of estimates of assets at risk were two orders of magnitude lower than generally accepted estimates of total financial risk; (ii) a minority of companies consider risks outside of their own operations or in their value chains; (iii) most underestimate or do not estimate the costs of adaptation; and (iv) many assume linear impacts and responses, neglecting the potential for tipping points or acceleration in risk and potentially transformative adaptation requirements. At this stage, TCFD has influenced many companies’ thinking and comprehension of physical climate risk, but it appears too early to assess whether this has driven substantive responses to manage these risks.

<div id="17.4.3" class="h2-container"></div>

<span id="enabling-condition-2-finance"></span>
=== 17.4.3 Enabling Condition 2: Finance ===

<div id="h2-10-siblings" class="h2-siblings"></div>

Finance has long been recognised as an important enabling and catalysing factor for adaptation, climate resilient development and climate risk management. In Chapter 17, financing for adaptation and climate risk management is covered in the extended Cross-Chapter Box, Financing for Adaptation and Resilience (FAR), below. The Cross-Chapter Box aims to highlight key emerging evidence on financing of adaptation, covering both public and private sources and instruments. Climate finance is also covered in a dedicated chapter in the WGIII Report (WGIII AR6 [[IPCC:Wg2:Chapter:Chapter-15|Chapter 15]] (Kreibiel et al., 2022)), and readers should refer to this chapter for a more comprehensive assessment of this subject from both a mitigation and adaptation perspective.

<div id="17.4.4" class="h2-container"></div>

<span id="enabling-condition-3-knowledge-and-capacity"></span>
=== 17.4.4 Enabling Condition 3: Knowledge and Capacity ===

<div id="h2-11-siblings" class="h2-siblings"></div>

<div id="17.4.4.1" class="h3-container"></div>

<span id="overview-of-knowledge-systems"></span>
==== 17.4.4.1 Overview of Knowledge Systems ====

<div id="h3-21-siblings" class="h3-siblings"></div>

AR5 emphasised the importance of knowledge systems as an enabling condition for decision-making, as did earlier ARs, all of which include a focus on the policy relevance of knowledge ( [[IPCC:Wg2:Chapter:Chapter-1#1.1.4|Section 1.1.4]] ). First introduced in IPCC reports in AR4, the term ‘knowledge system’ is used extensively in AR5 and the SRs. The discussion below follows a widely cited definition of knowledge systems as sets of interacting ‘agents, practices and institutions that organize the production, transfer and use of knowledge’ ( [[#Cornell--2013|Cornell et al., 2013]] : 61). This definition emphasises the social nature of knowledge and the importance of the link between knowledge and action, rather than presenting knowledge simply as information about past, present and future states of the world which can be of use to decision makers.

This definition of knowledge systems indicates the importance of capacity—the ability and the motivation to use knowledge for action—since capacity is an important feature which allows knowledge systems to function. Capacity is a necessary enabling condition for knowledge to be put to use in adaptation activities ( ''high confidence'' ), as shown across sectors such as water ( [[IPCC:Wg2:Chapter:Chapter-4#4.5.2|Section 4.5.2]] ), food security (Sections 5.12.3, 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 across regions, including Africa (Sections 9.13.1, 9.14.5), Asia (Sections 10.3.6, 10.4.4) and North America ( [[IPCC:Wg2:Chapter:Chapter-14#14.4|Section 14.4.5]] ).

Some research on knowledge systems retains the earlier attention to information as a resource for decision makers. A major focus, discussed elsewhere in this chapter, has been increasing the precision about the certainty, likelihood and confidence with which certain statements are made in relation to underlying evidence (see Cross-Chapter Box DEEP in this Chapter). This topic, which was first introduced in AR4, advanced significantly in AR5 ( [[#Mach--2017|Mach et al., 2017]] ).

In addition to these characteristics of information, the social and organisational aspects of knowledge systems have also been the subject of recent research. One strand of this discussion emphasises the distinctiveness of different knowledge systems, often focusing on three types of knowledge: scientific, Indigenous and local, and the latter are two sometimes grouped as ‘traditional’ knowledge (see Cross-Chapter Box INDIG in Chapter 18). This strand emphasises the specific forms of knowledge production and circulation in each type. Another strand of discussion emphasises the networks of interactions between different groups. This strand follows the influential ‘Knowledge systems for sustainable development’ ( [[#Cash--2003|Cash et al., 2003]] ), which was cited in Chapters 2, 7 and 8 in WGII AR5; [[#Cash--2003|Cash et al. (2003)]] emphasise the usability and acceptability of scientific knowledge, and highlight the relations between knowledge producers and users. The discussion in [[#17.4.4|Section 17.4.4]] on knowledge as an enabling factor integrates these two strands of discussion of knowledge systems.

It was well established in AR5 and SRs that a component of knowledge systems for good climate decision-making is the production of ‘information on climate, its impacts, potential risks, and vulnerability’ which can ‘be integrated into an existing or proposed decision-making context’ ( [[#Jones--2014|Jones et al., 2014]] : 200). Also important are two other components of knowledge: of response options and knowledge of other enabling conditions, particularly governance and finance, which were mentioned less frequently and more indirectly in AR5 and SR1.5, SROCC and SRCCL. Decision makers assess the feasibility of different alternatives (see Cross-Chapter Box FEASIB) and develop strategies for the implementation and modification of the alternative, requiring a level of knowledge of the governance, policy and finance landscapes at national ( [[#Tanner--2019|Tanner et al., 2019]] ; [[#Lopes--2020|Lopes et al., 2020]] ; [[#Roberts--2020|Roberts et al., 2020]] ) and international scales ( [[#Woodruff--2018|Woodruff, 2018]] ).

Examples of the importance of these other two components—knowledge of response options and knowledge of enabling conditions—are provided by networks of cities, including internal institutional networks ( [[#Aylett--2015|Aylett, 2015]] ), intermunicipal networks (e.g., those supported by Local Governments for Sustainability [ICLEI] and the international United Cities and Local Governments [UCLG] network), transnational municipal networks (e.g., 100 Resilient Cities, Asian Cities Climate Change Resilience Network [ACCCRN]) and city-to-city regional transdisciplinary learning networks ( [[#Ndebele-Murisa--2020|Ndebele-Murisa et al., 2020]] ). These networks generate and exchange knowledge which can be critical to decision makers for understanding and evaluating the feasibility of different response options, identifying synergies across sectors and mainstreaming adaptation to climate change ( [[#Haupt--2020|Haupt et al., 2020]] ). However, the question of how to finance such network activities remains under-studied ( [[#Bracking--2021|Bracking, 2021]] ; See Box 17.3).

In addition to these general considerations of knowledge systems, research since AR5 has contributed to the understanding of specific types of knowledge. Scientific knowledge is thoroughly discussed in Chapter 1, especially in [[IPCC:Wg2:Chapter:Chapter-1#1.3|Section 1.3]] ‘Understanding and Evaluating Climate Risk’, which shows recent advances in the well-established IPCC categories of observation of past conditions and model-based projections of future conditions. We add here a consideration of a new area within scientific knowledge, artificial intelligence, which offers new methods for producing information that can be incorporated into knowledge systems.

Applying artificial intelligence (AI) to climate change is predominantly in the area of climate modelling and forecasting, inclusive of weather extremes ( [[#Monteleoni--2013|Monteleoni et al., 2013]] ; [[#Jones--2017|Jones, 2017]] ; [[#Huntingford--2019|Huntingford et al., 2019]] ). Recent efforts conceptualise the potential uses of AI for mitigation and adaptation ( [[#Rolnick--2019|Rolnick et al., 2019]] ; Cheong et al., 2020b) in addition to forecasting ( [[#Rolnick--2019|Rolnick et al., 2019]] ; [[#Chattopadhyay--2020|Chattopadhyay et al., 2020]] ; Cheong et al., 2020b; [[#Prabhat--2021|Prabhat et al., 2021]] ). There are very few cases to assess AI applications in these domains given that AI is a new field for climate change impact and adaptation. To this date, sectoral applications of AI relevant to climate change adaptation and risk reduction mainly have advanced in the areas of crop yields, early-warning systems and water management.

These sectoral advances using AI employ various learning techniques inclusive of supervised and unsupervised learning, multi-modal learning and transfer learning techniques to generate more accurate predictions than afforded by traditional climate projection methods (Cheong et al., 2020b; [[#Camps-Valls--2021|Camps-Valls et al., 2021]] ). AI applications use finer-resolution data such as sub-daily weather-related data, remote and wearable sensor data, text data and real-time survey data. They are fed into neural networks and semi-/unsupervised learning to configure detailed and more precise predictions of climate change impact on crop yields ( [[#Crane-Droesch--2018|Crane-Droesch, 2018]] ), early warning ( [[#Moon--2019|Moon et al., 2019]] ), impact of extreme heat on older adults ( [[#Cheong--2020a|Cheong et al., 2020a]] ), poverty in Africa ( [[#Oshri--2018|Oshri et al., 2018]] ) and multi-scale water management combining blockchain technology with remote water sensors ( [[#Lin--2018|Lin et al., 2018]] ).

Indigenous knowledge and local knowledge are thoroughly covered in SROCC ( [[#Abram--2019|Abram et al., 2019]] ; [[#IPCC--2019c|IPCC, 2019c]] ; [[#IPCC--2019d|IPCC, 2019d]] ) and in [[IPCC:Wg2:Chapter:Chapter-1#1.3.3|Section 1.3.3]] . We here add relevant points to decision-making, and an additional form of knowledge, practitioner knowledge.

Indigenous knowledge and local knowledge are gaining recognition at multiple scales ( [[#Kleiche-Dray--2016|Kleiche-Dray and Waast, 2016]] ; [[#David-Chavez--2018|David-Chavez and Gavin, 2018]] ; [[#Nakashima--2018|Nakashima et al., 2018]] ). Of note is their association with ecosystem-based adaptations, showcasing the long-term place-based knowledge of Indigenous Peoples ( [[#Johnson--2015|Johnson et al., 2015]] ; [[#Walshe--2016|Walshe and Argumedo, 2016]] ; [[#Carter--2019|Carter, 2019]] ; [[#Mazzocchi--2020|Mazzocchi, 2020]] ). These knowledges and practices can be an important enabling condition in decision-making processes, complementing scientific information by identifying impacts ( [[#Fernández-Llamazares--2017|Fernández-Llamazares et al., 2017]] ; [[#Katz--2020|Katz et al., 2020]] ), emphasising values to consider ( [[#Huambachano--2018|Huambachano, 2018]] ), offering solutions ( [[#Chanza--2016|Chanza and de Wit, 2016]] ; [[#Cuaton--2020|Cuaton and Su, 2020]] ; [[#Orlove--2020|Orlove et al., 2020]] ), guiding land use and resource management ( [[#Brondízio--2021|Brondízio et al., 2021]] ) and filling gaps in scientific knowledge ( [[#Hiwasaki--2014|Hiwasaki et al., 2014]] ; [[#Audefroy--2017|Audefroy and Sánchez, 2017]] ; [[#Makondo--2018|Makondo and Thomas, 2018]] ; [[#Son--2019|Son et al., 2019]] ; [[#Latulippe--2020|Latulippe and Klenk, 2020]] ; Wheeler et al., 2020).

Practitioner knowledge—the pragmatic, practice-based knowledge that comes from the regular exercise of craft or professional work—was also acknowledged briefly in AR5 ( [[#Jones--2014|Jones et al., 2014]] ) and treated significantly in SROCC ( [[#Abram--2019|Abram et al., 2019]] ). Practitioner knowledge resembles local knowledge in that it is acquired through participation in activities, and yet it differs from local knowledge, which is often place-based and tied directly to specific landscapes and communities. Local knowledge typically covers a variety of environmental domains. Practitioner knowledge may be shared with people in different locations and is often more focused on a narrower set of work activities. Recent calls have recommended bringing practitioners more fully into the IPCC assessment process, to promote more effective decision-making ( [[#Howarth--2018|Howarth et al., 2018]] ).

Practitioner knowledge makes significant contributions to decision-making by broadening the range of alternatives which are considered and by bringing in understandings of systems to the selection and implementation of alternatives. Such knowledge is applicable to a large number of domains, including biodiversity management ( [[#Tengö--2014|Tengö et al., 2014]] ; [[#Rathwell--2015|Rathwell et al., 2015]] ), and natural hazard risk management in urban settings, as reported in Denmark ( [[#Madsen--2019|Madsen et al., 2019]] ), the USA ( [[#Matsler--2019|Matsler, 2019]] ), Canada ( [[#Yumagulova--2019|Yumagulova and Vertinsky, 2019]] ), Mexico ( [[#Aguilar-Barajas--2019|Aguilar-Barajas et al., 2019]] ) and the Caribbean ( [[#Ramsey--2019|Ramsey et al., 2019]] ). Other contexts, all at regional scales, include watershed management in Peru ( [[#Ostovar--2019|Ostovar, 2019]] ), livestock management in Finland ( [[#Rasmus--2020|Rasmus et al., 2020]] ), agricultural adaptation in a context of water scarcity in Iran ( [[#Zarei--2020|Zarei et al., 2020]] ) and the water–energy nexus in the USA ( [[#Gim--2019|Gim et al., 2019]] ).

Literature indicates the importance of effective governance for promoting integration of local and practitioner knowledge with scientific knowledge ( ''high confidence'' ). This integration is most extensive and promotes a wider consideration of alternatives, where governance arrangements promote ongoing exchanges of information and discussion of solutions, whether through formal mechanisms such as regional committees ( [[#Gim--2019|Gim et al., 2019]] ; [[#Ostovar--2019|Ostovar, 2019]] ; [[#Rasmus--2020|Rasmus et al., 2020]] ; [[#Zarei--2020|Zarei et al., 2020]] ) or informal mechanisms such as personal networks and local discussion groups ( [[#Madsen--2019|Madsen et al., 2019]] ; [[#Yumagulova--2019|Yumagulova and Vertinsky, 2019]] ). Where such arrangements are absent, practitioner knowledge is side-lined from the formulation and implementation of decisions ( [[#Aguilar-Barajas--2019|Aguilar-Barajas et al., 2019]] ; [[#Matsler--2019|Matsler, 2019]] ; [[#Ramsey--2019|Ramsey et al., 2019]] ).

<div id="17.4.4.2" class="h3-container"></div>

<span id="co-production-and-other-composite-knowledge-systems"></span>
==== 17.4.4.2 Co-production and Other Composite Knowledge Systems ====

<div id="h3-22-siblings" class="h3-siblings"></div>

There is strong evidence that composite knowledge systems—characterised by interactions between the producers and potential users of climate change information—can help facilitate climate-related decision-making ( [[#Prokopy--2015|Prokopy and Power, 2015]] ; [[#Richards--2018|Richards, 2018]] ; [[#Ramsey--2019|Ramsey et al., 2019]] ). Several institutional forms and structures have been created to link scientific knowledge, Indigenous knowledge, and local and practitioner knowledge to climate change decision-making.

<div id="17.4.4.2.1" class="h4-container"></div>

<span id="co-production"></span>
===== 17.4.4.2.1 Co-production =====

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

The co-production of knowledge by different actors provides important avenues for exchanging and integrating climate-related knowledge in decisions made across society ( ''high confidence'' ). Though many definitions of co-production have been offered in recent years ( [[#Bremer--2017|Bremer and Meisch, 2017]] ; [[#Vincent--2018|Vincent et al., 2018]] ; [[#Bremer--2019|Bremer et al., 2019]] ; [[#Harvey--2019a|Harvey et al., 2019a]] ), most describe a set of individuals or organisations who work together to generate a set of products that entail new knowledge products and that guide action ( [[#Miller--2020|Miller and Wyborn, 2020]] ). Some major forms of co-production include action research ( [[#Baztan--2017|Baztan et al., 2017]] ; [[#Laursen--2018|Laursen et al., 2018]] ; [[#Zanocco--2018a|Zanocco et al., 2018a]] ), trans-disciplinarity ( [[#Howarth--2016|Howarth and Monasterolo, 2016]] ; [[#Wamsler--2017|Wamsler, 2017]] ; [[#Lanier--2018|Lanier et al., 2018]] ; [[#Scott--2018|Scott et al., 2018]] ; [[#Knapp--2019|Knapp et al., 2019]] ; Young et al., 2019), rapid assessment processes ( [[#Atkinson--2018b|Atkinson et al., 2018b]] ) and participatory integrated assessments ( [[#Howarth--2018|Howarth et al., 2018]] ; [[#Krkoška%20Lorencová--2018|Krkoška Lorencová et al., 2018]] ; [[#Bitsura-Meszaros--2019|Bitsura-Meszaros et al., 2019]] ; [[#Carter--2019a|Carter et al., 2019a]] ; [[#Cremades--2019|Cremades et al., 2019]] ; [[#Leitch--2019|Leitch et al., 2019]] ; [[#Martínez-Tagüeña--2020|Martínez-Tagüeña et al., 2020]] ; [[#17.3.1.3.1|Section 17.3.1.3.1]] ).

Co-production promotes iterative dialogue, experimentation, the tailoring of knowledge to context, needs and priorities, and learning, often promoting integration of Indigenous knowledge, local knowledge and practitioner knowledge with scientific knowledge ( ''high confidence'' ). It generally entails long-lasting ties and fully inclusive partnerships between different parties ( [[#Kench--2018|Kench et al., 2018]] ). Governance measures and adequate financing can act as enablers of such co-production. This integration is most extensive, and promotes a wider consideration of alternatives where governance arrangements promote ongoing exchanges of information and discussion of solutions, whether through formal mechanisms such as regional committees ( [[#Gim--2019|Gim et al., 2019]] ; [[#Ostovar--2019|Ostovar, 2019]] ; [[#Rasmus--2020|Rasmus et al., 2020]] ; [[#Zarei--2020|Zarei et al., 2020]] ) or informal mechanisms such as personal networks and local discussion groups ( [[#Madsen--2019|Madsen et al., 2019]] ; [[#Yumagulova--2019|Yumagulova and Vertinsky, 2019]] ). Where such arrangements are absent, practitioner knowledge is side-lined from the formulation and implementation of decisions ( [[#Orleans%20Reed--2013|Orleans Reed et al., 2013]] ; [[#Aguilar-Barajas--2019|Aguilar-Barajas et al., 2019]] ; [[#Matsler--2019|Matsler, 2019]] ; [[#Ramsey--2019|Ramsey et al., 2019]] ).

An important mechanism of co-production is the boundary organisation, a knowledge-producing organisation composed of individuals who reflect different disciplines or knowledge systems and who represent different activities, sectors or forms of governance ( [[#Blades--2016|Blades et al., 2016]] ; [[#Graham--2016|Graham and Mitchell, 2016]] ; [[#Guido--2016|Guido et al., 2016]] ; [[#Jeuring--2019|Jeuring et al., 2019]] ; [[#Serrao-Neumann--2020|Serrao-Neumann et al., 2020]] ; [[#Zarei--2020|Zarei et al., 2020]] ). Boundary organisations themselves can be linked into boundary chains ( [[#Lemos--2014|Lemos et al., 2014]] ; [[#Meyer--2015|Meyer et al., 2015]] ; [[#Kirchhoff--2015a|Kirchhoff et al., 2015a]] ; [[#Pretorius--2019|Pretorius et al., 2019]] ; [[#Daniels--2020|Daniels et al., 2020]] ). When individuals and organisations from different disciplinary backgrounds and missions coordinate their activities informally, the resulting ties have been termed ‘knowledge networks’ ( [[#Ziaja--2015|Ziaja and Fullerton, 2015]] ; [[#Brugger--2016|Brugger et al., 2016]] ; [[#Guido--2016|Guido et al., 2016]] ; [[#Davies--2018|Davies et al., 2018]] ; [[#Klenk--2018|Klenk, 2018]] ; [[#Muccione--2019|Muccione et al., 2019]] ; [[#Ziaja--2019|Ziaja, 2019]] ). When such networks interact with each other, the resulting associations have been called ‘communities of practice’, which can work to collectively shape information to shared contextual circumstances ( [[#Orsato--2018|Orsato et al., 2018]] ; [[#Wang--2019b|Wang et al., 2019b]] ).

There is extensive evidence that co-production can generate useful climate knowledge ( [[#Djenontin--2018|Djenontin and Meadow, 2018]] ; [[#Bisbal--2019|Bisbal, 2019]] ; [[#Ryan--2019|Ryan and Bustos, 2019]] ; [[#Hewitt--2020|Hewitt et al., 2020]] ; [[#Jack--2020|Jack et al., 2020]] ; [[#Lavorel--2020|Lavorel et al., 2020]] ; [[#Ruiz-Mallén--2020|Ruiz-Mallén, 2020]] ) and that it can increase the likelihood that knowledge will be used in decision-making ( [[#Vogel--2016|Vogel et al., 2016]] ; [[#Prokopy--2017|Prokopy et al., 2017]] ; [[#Skelton--2017|Skelton et al., 2017]] ; [[#Sylvester--2020|Sylvester and Brooks, 2020]] ). Co-production is not without its costs, since it requires more time, money, facilitation expertise and personal commitment from participants than more conventional modes of knowledge production ( [[#Lemos--2018|Lemos et al., 2018]] ; [[#Sletto--2019|Sletto et al., 2019]] ; [[#Wamsler--2019|Wamsler et al., 2019]] ; [[#Blair--2020|Blair et al., 2020]] ). Some research has shown ways to decrease the costs of co-production for participants, such as funding and time to enable and sustain interactions and to build trust and legitimacy, or to create boundary organisations ( [[#Young--2016|Young et al., 2016]] ; [[#Klenk--2017|Klenk et al., 2017]] ).

Co-production is supported by project cycles that provide for the involvement of stakeholders from the outset ( [[#Daly--2019|Daly and Dilling, 2019]] ; [[#Brady--2020|Brady and Leichenko, 2020]] ); flexible research agendas that do not assume a climate related question ( [[#Daniels--2020|Daniels et al., 2020]] ); support for interactivity and reflexivity ( [[#Araujo--2020|Araujo et al., 2020]] ); and institutionalising incentives which address the different values, norms, perceptions and work patterns of scientists, policymakers and civil society representatives ( [[#Cvitanovic--2015|Cvitanovic et al., 2015]] ; [[#Vincent--2015|Vincent et al., 2015]] ; Bruno [[#Soares--2016|Soares and Dessai, 2016]] ; [[#Singh--2017|Singh et al., 2017]] ; [[#Djenontin--2018|Djenontin and Meadow, 2018]] ; [[#Norström--2020|Norström et al., 2020]] ; [[#Turnhout--2020|Turnhout et al., 2020]] ). Certain roles, such as policy entrepreneurs ( [[#Tanner--2019|Tanner et al., 2019]] ), embedded researchers ( [[#Pretorius--2019|Pretorius et al., 2019]] ) and knowledge brokers ( [[#Cvitanovic--2015|Cvitanovic et al., 2015]] ), can facilitate co-production.

<div id="17.4.4.2.2" class="h4-container"></div>

<span id="climate-services"></span>
===== 17.4.4.2.2 Climate services =====

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

Climate services (refer to CWG Box on Climate Services) can be important enablers of climate risk management, provided they are credible, relevant and usable ( ''high confidence'' ), and will become increasingly important as human influence on weather and climate extremes grows across all regions (Chapter 11; [[#Fischer--2021|Fischer et al., 2021]] ; [[#IPCC--2021|IPCC, 2021]] ). Climate services are more effective and more widely used when they are tailored to specific decisions and decision makers ( ''high confidence'' ). Sustained iterative engagement between climate information users, producers and translators can improve the quality of the information and the decision-making and avoid maladaptation ( ''medium confidence'' ).

Historically, climate services have been organised by climate information providers, based in meteorological, hydrological and agricultural faculties and services, serving to improve through climate risk management, including the use of historical information, monitoring, seasonal forecasts and long-term climate projections ( [[#Hewitt--2012|Hewitt et al., 2012]] ; [[#Blome--2017|Blome, 2017]] ; [[#Bessembinder--2019|Bessembinder et al., 2019]] ; [[#Vaughan--2019b|Vaughan et al., 2019b]] ).

Recent research on climate services shows that transdisciplinary knowledge co-production is a key enabler, starting to shift emphasis from the creation of climate services ''products'' to climate services ''processes'' ( [[#Vincent--2018|Vincent et al., 2018]] ; [[#Carter--2019b|Carter et al., 2019b]] ; [[#Daniels--2020|Daniels et al., 2020]] ), potentially increasing uptake and sustainability ( [[#Norström--2020|Norström et al., 2020]] ). This shift is a result of the recognition of benefits which a co-production approach can offer, in addition to the provision of information; these additional benefits include building confidence, capacities, learning, knowledge, social capital, institutional capacity, stakeholder relationships, social networks, beneficial management practices and strengthened institutions (Bruno [[#Soares--2016|Soares and Dessai, 2016]] ; [[#Djenontin--2018|Djenontin and Meadow, 2018]] ; [[#Bremer--2019|Bremer et al., 2019]] ).

Cross-Chapter Box 12.2 in WGI AR6, ‘Climate information for climate services’, shows that users are widely distributed across civil society. Relevant users of climate services include humanitarian organisations ( [[#Coughlan%20de%20Perez--2014|Coughlan de Perez and Mason, 2014]] ; [[#Harvey--2019b|Harvey et al., 2019b]] ), government offices ( [[#Mahon--2019|Mahon et al., 2019]] ), international agencies ( [[#Perkins--2019|Perkins and Nachmany, 2019]] ) and the private sector ( [[#Beckett--2016|Beckett, 2016]] ; [[#Hudson--2019|Hudson et al., 2019]] ). Climate services currently exist at local, national, regional and international scales, at time scales which range from sub-seasonal to decadal and longer ( [[#White--2017|White et al., 2017]] ; [[#Hewitt--2020|Hewitt et al., 2020]] ) and in a range of different sectors (Bruno [[#Soares--2019|Soares and Buontempo, 2019]] ). Agriculture is the sector with the largest number of examples ( [[#Zebiak--2015|Zebiak et al., 2015]] ; [[#Burke--2016|Burke and Emerick, 2016]] ; [[#Cliffe--2016|Cliffe et al., 2016]] ; [[#Haigh--2018|Haigh et al., 2018]] ; [[#Buontempo--2020|Buontempo et al., 2020]] ); others include health ( [[#Ghebreyesus--2010|Ghebreyesus et al., 2010]] ; [[#Ballester--2016|Ballester et al., 2016]] ), forestry ( [[#Caurla--2020|Caurla and Lobianco, 2020]] ), fisheries ( [[#Busch--2016|Busch et al., 2016]] ), disaster risk reduction ( [[#Street--2019|Street et al., 2019]] ) and water resources management ( [[#van%20Vliet--2015|van Vliet et al., 2015]] ; [[#Golding--2019|Golding et al., 2019]] ). Evaluations of the extent to which climate services are accessed, used and deliver benefits to decision makers remain in an initial stage ( [[#Perrels--2020|Perrels, 2020]] ), though studies suggest that these contributions vary widely depending on context. A review of evaluation of weather and climate agricultural services in Africa, for instance, found that most farmers use climate services when they are available , but that on-farm outcomes varied, with some farmers experiencing yield losses and others gains upward of 60% ( [[#Vaughan--2019a|Vaughan et al., 2019a]] ). Other studies express concern that large climate service projects have run for decades at significant expense, without adequate evaluation ( [[#Gerlak--2020|Gerlak et al., 2020]] ).

Recent reviews ( [[#Carr--2018|Carr and Onzere, 2018]] ; [[#Hewitt--2020|Hewitt et al., 2020]] ) provide evidence that the use of climate services is affected by (a) the quality, reliability and skill of the climate information ( [[#Zebiak--2019|Zebiak, 2019]] ); (b) the fit, tailoring and contextualisation of that information with respect to the specific decision-making needs of particular users ( [[#Clarkson--2019|Clarkson et al., 2019]] ); (c) the mode and method by which the service is communicated ( [[#Golding--2017|Golding et al., 2017]] ); and (d) the characteristics of the users themselves, including the users’ access to resources that would allow them to alter their decisions based on the information provided ( [[#Clarkson--2019|Clarkson et al., 2019]] ).

A related literature characterises the extent to which the development, reach and effectiveness of climate services is affected by factors that can be termed ‘climate service governance’ ( [[#Stegmaier--2020|Stegmaier et al., 2020]] ). Elements of this governance include the arrangements by which those parties engage with each other ( [[#Vaughan--2016|Vaughan et al., 2016]] ; [[#Daniels--2020|Daniels et al., 2020]] ) and the financial arrangements, and associated responsibilities, which support the service ( [[#Lourenço--2015|Lourenço et al., 2015]] ; Bruno [[#Soares--2019|Soares and Buontempo, 2019]] ). Though governance varies by context, evidence suggests that engaging a range of experts and potential users in the co-design and co-production of climate services increases the use and utility of services ( [[#Lemos--2014|Lemos et al., 2014]] ; [[#Pope--2017|Pope et al., 2017]] ; [[#Masuda--2018|Masuda et al., 2018]] ; [[#Harvey--2019b|Harvey et al., 2019b]] ). However, some studies warn that, even with broad and inclusive participation, power differentials can create barriers to co-production, reducing the usefulness of information products ( [[#Alexander--2020|Alexander et al., 2020]] ) and the neglect of non-meteorological sources of information which may also possess useful predictive power ( [[#Coughlan%20de%20Perez--2019|Coughlan de Perez et al., 2019]] ).

A small but growing number of papers consider the business models that support climate services, including, for instance, the role of open data ( [[#Iturbide--2019|Iturbide et al., 2019]] ; [[#Chimani--2020|Chimani et al., 2020]] ), the standards or institutional mandates by which users come to understand the credibility and legitimacy of certain services (Bruno [[#Soares--2019|Soares and Buontempo, 2019]] ), and the role of public–private partnerships ( [[#Cortekar--2020|Cortekar et al., 2020]] ). While the commercialisation of climate services holds significant promise that more and more specifically targeted services will be provided, there is not yet agreement on which business models best support this in different contexts. There is also concern that commercialisation of climate services may disadvantage under-resourced actors at the expense of wealthier or more powerful ones ( [[#Webber--2017|Webber, 2017]] ; [[#Webber--2017|Webber and Donner, 2017]] ; [[#Cortekar--2020|Cortekar et al., 2020]] ). It has been noted that some climate services, such as weather forecasts and early warnings, are an example of a public good, best provided by public agencies ( ''high confidence'' ) ( [[#Sutter--2013|Sutter, 2013]] ; [[#Kitchell--2016|Kitchell, 2016]] ; [[#Hansen--2018|Hansen et al., 2018]] ).

<div id="17.4.4.2.3" class="h4-container"></div>

<span id="capacity-and-motivation-within-knowledge-systems"></span>
===== 17.4.4.2.3 Capacity and motivation within knowledge systems =====

<div id="h4-17-siblings" class="h4-siblings"></div>

Knowledge of climate change influences decision-making not only by providing information but also by increasing the motivation to act and by promoting behaviour change. Evidence from many sectors (including water ( [[IPCC:Wg2:Chapter:Chapter-4#4.5.2|Section 4.5.2]] ), ocean and coastal ecosystems ( [[IPCC:Wg2:Chapter:Chapter-3#3.6.2|Section 3.6.2]] ), and agriculture ( [[IPCC:Wg2:Chapter:Chapter-5#5.4.2|Section 5.4.2]] ) and regions (including Africa [Section 9.8.4], Asia [Section 10.4.6] and North America [Section 10.4.5] shows that building capacity (e.g., adaptive capacity, institutional capacity, education/training in human capacity) can support adaptation and limited governance capacity can constrain it ( ''high confidence'' ). An emerging area of research examines the contribution of building capacity within public and technical organisations and agencies to draw on Indigenous knowledge and local knowledge ( [[#Adger--2017|Adger et al., 2017]] ; [[#Hochman--2017|Hochman et al., 2017]] ; Bacud, 2018). A number of factors influence the effect of knowledge on motivation and behaviour change, including values and education.

Decision makers who shape options for managing climate risk can evaluate stakeholders’ capacities and motivations to participate in the implementation process of these options. Stakeholder engagement in climate change risk management supports successful adaptation ( [[#Gray--2014|Gray et al., 2014]] ; [[#Elsawah--2015|Elsawah et al., 2015]] ; [[#Siders--2017|Siders, 2017]] ; [[#Giordano--2020|Giordano et al., 2020]] ). Research in psychology and related fields shows that the cognitive mechanisms by which individuals and organisations process climate information influence this capacity, motivation and engagement ( [[#Grothmann--2005|Grothmann and Patt, 2005]] ; [[#Grothmann--2013|Grothmann et al., 2013]] ; [[#Masud--2016|Masud et al., 2016]] ; [[#Nelson--2016|Nelson et al., 2016]] ; [[#Takahashi--2016|Takahashi et al., 2016]] ; [[#Hügel--2020|Hügel and Davies, 2020]] ; [[#Grothmann--2021|Grothmann and Michel, 2021]] ).

The perception of climate change as a major threat that requires action has increased since AR5, reflecting both the growth of information about climate change and the processing of that information ( [[#Lee--2015|Lee et al., 2015]] ; [[#Fagan--2019|Fagan and Huang, 2019]] ). Global social movements play an important role in raising public awareness of climate urgency ( [[#Thackeray--2020|Thackeray et al., 2020]] ). Climate change concern plays an important role in decision-making outcomes which entail public participation ( [[#Lammel--2015|Lammel, 2015]] ; [[#Chiang--2018|Chiang, 2018]] ; [[#van%20Valkengoed--2019|van Valkengoed and Steg, 2019]] ; Arıkan and Günay, 2020). Nonetheless, public risk perception varies sharply on spatial and temporal scales, reflecting environmental changes, social influences ( [[#Kousser--2018|Kousser and Tranter, 2018]] ; [[#Rousseau--2020|Rousseau and Deschacht, 2020]] ), economic capacities (Arıkan and Günay, 2020) and culture ( [[#Noll--2020|Noll et al., 2020]] ), as well as individual characteristics ( [[#van%20Valkengoed--2019|van Valkengoed and Steg, 2019]] ). The importance of values and norms is demonstrated by recent research which highlights how intrinsic motivation (altruistic, self-transcendental and eco-centric values) ( [[#Corner--2014|Corner et al., 2014]] ; [[#Braito--2017|Braito et al., 2017]] ; [[#Xiang--2019|Xiang et al., 2019]] ; [[#Bouman--2020|Bouman et al., 2020]] ) and extrinsic social motivation (e.g., economic gains and social desirability) ( [[#van%20Valkengoed--2019|van Valkengoed and Steg, 2019]] ) can drive action.

Recent research shows the importance of education as a predictor of risk perception, motivation and action. Education level is the strongest predictor of public awareness of climate change risk in a study across 119 countries of public awareness of climate change risk ( [[#Lee--2015|Lee, 2015]] ), though this relationship varies in different nations, and is influenced by mediating variables ( [[#Muttarak--2015|Muttarak and Chankrajang, 2015]] ; [[#Blennow--2016|Blennow et al., 2016]] ) ( [[#Ballew--2020|Ballew et al., 2020]] ). Knowledge and awareness of climate change are correlated with the motivation to undertake action on climate change ( [[#Hornsey--2017|Hornsey and Fielding, 2017]] ). The integration of climate science in educational curricula has been shown to be effective ( [[#Hess--2019|Hess and Maki, 2019]] ; [[#Molthan-Hill--2019|Molthan-Hill et al., 2019]] ), including approaches such as integration of the complex system approach ( [[#Jacobson--2017|Jacobson et al., 2017]] ), experiential climate change education ( [[#Siegner--2018|Siegner, 2018]] ), including climate games ( [[#O’Garra--2021|O’Garra et al., 2021]] ; [[#Pfirman--2021|Pfirman et al., 2021]] ), massive open online courses and informal science learning centres ( [[#Geiger--2017|Geiger et al., 2017]] ).

Attention to behavioural change of individuals has grown since AR5, including cases which address both adaptation and mitigation (e.g., dietary changes, modification of buildings, transport alternatives) ( [[#Azadi--2019|Azadi et al., 2019]] ; [[#Fischer--2019|Fischer, 2019]] ; [[#Willett--2019|Willett et al., 2019]] ; [[#Sharifi--2020|Sharifi, 2020]] ; [[#Sharifi--2021|Sharifi, 2021]] ). The interventions to promote behavioural change can be bottom-up, initiated by individuals, communities, non-governmental organisations or the private sector, or top-down, coming from governments at various levels ( [[#Robertson--2015|Robertson and Barling, 2015]] ; [[#Stern--2016|Stern et al., 2016]] ). They are supported by a number of mechanisms, including education, information strategies, and campaigns, financial incentives, regulatory processes and legislation ( [[#Rosenow--2017|Rosenow et al., 2017]] ; [[#Creutzig--2018|Creutzig et al., 2018]] ; [[#Carlsson--2019|Carlsson et al., 2019]] ). These behavioural changes contribute significantly to effective risk management.

<div id="cross-chapter-box-finance:-finance-for-adaptation-and-resilience" class="h2-container box-container"></div>

'''Cross-Chapter Box FINANCE: Finance for Adaptation and Resilience'''
<div id="h2-22-siblings" class="h2-siblings"></div>

Authors: Mark New (South Africa), Madeleine Rawlins (UK), David Viner (UK), Charlene Watson (UK), Lily Burge (UK), Lionel Mok (Canada), Lauren Arendse (South Africa), Vita Karoblyte (UK), Liane Schalatek (USA), Neha Rai (UK), Baysa Naran (Mongolia), So-Min Cheong (Republic of Korea), Nicoletta Giulivi (Italy/Guatemala).

'''Introduction'''
This Cross-Chapter Box reports on: (i) new evidence on the finance needed for adaptation and resilience, and uncertainties in these estimates; (ii) the emerging public and private climate finance architecture; (iii) the status of financing for AR, including sources, total flows, regional and sectoral distributions; (iv) equity considerations; (iv) opportunities and challenges for financing adaptation and resilience during and after the coronavirus disease 2019 (COVID-19) pandemic. This Cross-Chapter Box does not focus on finance for mitigation, which is covered in WGIII [[IPCC:Wg2:Chapter:Chapter-15|Chapter 15]] (Kreibiel et al., 20122), nor the economic damages of climate change or financial aspects of Loss and Damage, which are covered in Cross-Working Group Box ECONOMIC (Chapter 16) and Cross-Chapter Box LOSS (this chapter), respectively.

Successive reports of the IPCC ( [[#Vellinga--2001|Vellinga et al., 2001]] ; [[#Mimura--2008|Mimura et al., 2008]] ; [[#Yohe--2008|Yohe et al., 2008]] ; [[#Klein--2014|Klein et al., 2014]] ) and the AR6 Special Reports have noted the importance of finance as an enabler for adaptation, across both developed and developing nations. While the UNFCCC and the UNFCCC has yet to arrive at a formally agreed definition of climate finance, numerous overlapping have been suggested and reported (e.g., [[#Falconer--2014|Falconer and Stadelmann, 2014]] ; [[#UNFCCC--2014|UNFCCC, 2014]] ; [[#Roberts--2017|Roberts and Weikmans, 2017]] ; [[#Munira--2021|Munira et al., 2021]] ). However, there is wide agreement across these definitions that climate finance refers to financial resources devoted to addressing climate change, both mitigation and adaptation to current and projected climate change, and that these resources can come from both public and private sources (high confidence). Climate finance includes, but in most definitions is not restricted to, international financial flows to developing countries. Finance can be delivered through a range of instruments including grants, concessional and non-concessional debt, and internal budget reallocations (high confidence) (Watson and Schalatek, 2019). Adaptation and resilience are often used interchangeably in climate finance discussions, although adaptation is a process, while resilience (to climate risk) is the ability to progress towards desired outcomes in the face of impacts from a changing climate ( [[IPCC:Wg2:Chapter:Chapter-1#1.2.1|Section 1.2.1]] ).

Box Cross-Chapter Box FINANCE.1 | The 100 Billion Climate Finance Commitment to Developing Countries

At the 16th session of the Conference of the Parties (COP16) in Copenhagen in 2009, developed country parties to the UNFCCC committed to a goal of jointly mobilising USD 100 billion yr −1 by 2020 to address the climate change needs of developing countries ( [[#UNFCCC--2009|UNFCCC, 2009]] ). This was in response to a threat by developing countries to walk out of the negotiations, as they perceived developed country support to be lagging and lacking in ambition ( [[#Roberts--2021|Roberts et al., 2021]] ). The commitment was formalised in the Cancun Agreements (Decision 1/CP.16) in 2010 and was re-affirmed as a key element of the Paris Agreement in 2015 (Article 9, paragraph 4). At the 26th session of the Conference of the Parties (COP26) in 2021, formal deliberations will begin on a new climate finance goal to be adopted in 2025; the current USD 100 billion target will serve as the annual minimum until 2025 ( [[#Chhetri--2020|Chhetri et al., 2020]] ).

The ‘100 Billion’ does not represent the total need to respond to climate change in developing countries, nor the global cost across all countries, as is sometimes interpreted in the literature and media. As shown below in this Cross-Chapter Box, the estimated cost of adaptation for developing countries ranges from 15 to 411 billion USD yr −1 for climate change impacts out to 2030, with the majority of estimates being well above 100 billion.

Proposed sources for the developed country commitment included ‘ ''a wide variety of sources, public and private, bilateral and multilateral, including alternative sources of finance'' ’ and several instruments including grants and loans. Nonetheless, there remain differences of opinion on the types of finance that should count towards this goal, with several issues identified ( ''high confidence'' ) ( [[#Bodnar--2015|Bodnar et al., 2015]] ; [[#Bhattacharya--2020|Bhattacharya et al., 2020]] ; [[#Roberts--2021|Roberts et al., 2021]] ), including: (i) counting non-grant finance, such as market and concessional loans (public and private), where developing countries ultimately have to repay the investment; (ii) what is counted as ‘climate’ by different funders, especially when climate is not the prime objective; (iii) the extent to which some funds are ‘new and additional’ rather than a repurposing of development finance.

Progress towards the 100 Billion target has shown an upward trend over the last several years ( ''high confidence'' ), but will fall short in 2020, even when the most generous criteria are included ( ''high confidence'' ). In 2017/2018, the most recent year for which data have been comprehensively analysed, estimates using different (but overlapping) data sources and methods were in the range 48–75 billion USD yr −1 , compared with 45–75 in 2015/2016 and 41–52 in 2013/2014 ( [[#Carty--2020|Carty et al., 2020]] ; SM17.3; [[#CPI--2020|CPI, 2020]] ; [[#OECD--2020|OECD, 2020]] ; [[#UNFCCC--2020|UNFCCC, 2020]] ). The distribution between adaptation and mitigation has remained strongly weighted towards mitigation, although the proportion allocated to adaptation has increased from 17–25% in 2013/2014 to 19–30% in 2017/2018 ( ''high confidence'' ). One analysis that excludes debt repayments indicates that the debt-adjusted flows are about half the total flows reported above, of which circa 31–33% was for adaptation between 2015/2016 and 2017/2018 ( [[#Carty--2020|Carty et al., 2020]] ).

'''Adaptation finance needs'''
Estimates of global, regional or national finance needs for adaptation and resilience vary depending on both analysis approach, the level of climate change, and the geographic and sectoral scope of analysis ( ''high confidence'' ) ( [[#UNEP--2016|UNEP, 2016]] ; [[#Chapagain--2020|Chapagain et al., 2020]] ; [[#UNEP--2020|UNEP, 2020]] ). Recent estimates have adopted one of main approaches: (i) aggregation of individual case studies, along with scaling to generate global or regional costs; (ii) analysis of NDC adaptation cost estimates ( [[#Weischer--2016|Weischer et al., 2016]] ; [[#Hallegatte--2018|Hallegatte et al., 2018]] ); (iii) integrated assessment model simulation of impacts and adaptation costs ( [[#Markandya--2019|Markandya and González-Eguino, 2019]] ; [[#Chapagain--2020|Chapagain et al., 2020]] ).

All approaches suffer from limitations that can cause both over- and underestimates, including incomplete coverage of sectors and risks; inability to account for autonomous/unreported adaptation; incorrect cost estimations; soft and hard limits to adaptation; balance between adaptation, mitigation and residual cost; benefits and co-benefits on cost; and learning and innovation as climate change progresses ( [[#UNEP--2020|UNEP, 2020]] ). Global or developing region estimates based on scaling NDC data is particularly uncertain, as most NDCs did not specify how the costs were calculated. Also, scaling from a relatively small set of NDCs with costs to the global scale is not particularly robust, indicating a need for more transparency and better guidance for calculating adaptation costs ( [[#Watkiss--2015|Watkiss et al., 2015]] ; [[#Zhang--2016|Zhang and Pan, 2016]] ; [[#Hallegatte--2018|Hallegatte et al., 2018]] ; [[#African%20Development%20Bank--2019|African Development Bank, 2019]] ).

Most estimates of adaptation cost in the literature are for developing countries. [[#Chapagain--2020|Chapagain et al. (2020)]] assessed various estimates of adaptation for developing countries, under different emissions scenarios for 2030 and 2050. The median estimates (and range) from these studies are 127 (15–411) and 295 (47–1088) billion USD yr −1 for climate change impacts out to 2030 and 2050, respectively (see SM17.3). All but one study report adaptation costs higher than the 70–100 billion estimated in 2010 by the World Bank ( [[#World%20Bank--2010|World Bank, 2010]] ).

[[File:579274329b4732502644012235f255b5 IPCC_AR6_WGII_Figure_17_Cross-Chapter_Box_FINANCE_1.png]]

'''Figure Cross-Chapter Box FINANCE.1 |''' '''Comparison of recent studies that estimated developing country adaptation costs in billion USD (in 2005 prices) yr''' '''−1''' ''', for 2030 and 2050.''' Figure based on [[#Chapagain--2020|Chapagain et al. (2020)]] . Major studies are [[#World%20Bank--2010|World Bank (2010)]] , [[#Chapagain--2020|Chapagain et al. (2020)]] , [[#UNEP--2016|UNEP (2016)]] , [[#Baarsch--2015|Baarsch et al. (2015)]] and [[#Markandya--2019|Markandya and González-Eguino (2019)]] . The solid-coloured bars are based on RCP2.6, and patterned bars are based on RCP 8.5; the width of the bars indicates the range of estimates (maximum and minimum) produced in each study.

The cost of adaptation for developed countries is rarely reported; most literature either reports a global cost or developing country costs, or costs for a specific country or sector. [[#Baarsch--2015|Baarsch et al. (2015)]] , using an Integrated Assessment Model (IAM), report adaptation annual costs (2012 prices) in 2030 (and 2050) as 272 (660) billion globally and 205 (521) in developing countries only under the RCP2.6 scenario, indicating that developed country costs are around 25% (21%) of total cost.

In addition to global estimated adaptation costs, there are many studies that have focused on specific regions, countries or sectors, such as estimated adaptation cost for coastal environments, water-related infrastructure, urban infrastructure, agriculture and energy ( [[#UNEP--2014|UNEP, 2014]] ; [[#Watkiss--2015|Watkiss et al., 2015]] ; [[#UNEP--2016|UNEP, 2016]] ). Examples of such estimates are reported in various chapters in this report and summarised in SM17.3.

Estimating the benefit of adaptation, in terms of damage avoided, remains challenging. For example, [[#Ricke--2018|Ricke et al. (2018)]] show that the social cost of carbon (monetary damage per tCO 2 emitted) varies by up to two orders of magnitude depending on country, socioeconomic scenario, damage function, total greenhouse gases (GHG) forcing, and local climate change. In addition, non-monetary benefits such as cultural identity, sacred places, human health and lives are often ignored ( [[#Tschakert--2017|Tschakert et al., 2017]] ; [[#Serdeczny--2019|Serdeczny, 2019]] ; see also Cross-Working Group Box ECONOMIC in Chapter 16; Cross-Chapter Box LOSS, this Chapter). Recent case studies and global level analyses continue to support the conclusion in IPCC AR5 WGII [https://www.ipcc.ch/report/ar6/wg2/chapter/chapter-17 Chapter 17] ( [[#Chambwera--2014|Chambwera et al., 2014]] ) that the benefits of adaptation generally remain larger than the costs ( ''medium confidence'' ), but the cost–benefit ratio varies widely by context and assumptions ( [[#OECD--2015|OECD, 2015]] ; [[#Global%20Commission%20on%20Adaptation--2019|Global Commission on Adaptation, 2019]] ; [[#WRI--2019|WRI, 2019]] )

'''The climate finance landscape'''
The adaptation and resilience finance landscape spans multiple sources, intermediaries, instruments and recipients, operating across global to sub-national scales ( [[#Buchner--2019|Buchner et al., 2019]] ; [[#Carter--2020|Carter, 2020]] ; [[#Watson--2021|Watson and Schalatek, 2021]] ). Public finance is provided by national and sub-national governments and distributed directly by government or intermediaries such as development finance institutions and climate funds, either nationally or internationally. Private finance comes from five main sources: commercial financial institutions (banks), institutional investors (including asset managers, insurance companies and pension funds), other private equity (venture capital and infrastructure funds), non-financial corporations such as renewable energy or water companies, and individual households and communities. Across these different sources, the main instruments used are grants, concessional debt, market debt, internal budget allocation, insurance, as well as personal savings in households ( ''high confidence'' ). Public and private sources of funding can be blended into a single instrument, for example for insurance where public funds provide capital for both sovereign catastrophe instruments and micro-insurance ( [[#Jarzabkowski--2019|Jarzabkowski et al., 2019]] ) or for concessional loans. Similarly, public finance is often ultimately derived from commercial debt instruments such as bonds.

'''International public climate finance'''
International public climate finance flows are realised through bilateral and multi-lateral channels ( [[#Watson--2021|Watson and Schalatek, 2021]] ) where contributions to these channels are received from Annex II and non-Annex I countries ( [[#UNFCCC%20SCF--2018|UNFCCC SCF, 2018]] ; [[#Buchner--2019|Buchner et al., 2019]] ). Annex II countries contribute as part of their commitments in the Paris Agreement, while non-Annex I countries commit climate finance through these channels on a voluntary basis ( [[#Pickering--2015|Pickering et al., 2015]] ; [[#Roberts--2017|Roberts and Weikmans, 2017]] ; [[#Egli--2019|Egli and Stünzi, 2019]] ). Bilateral intermediaries include development cooperation agencies and national development banks. These institutions often have long-standing development-cooperation experience, and offer climate change projects, facilities and financial instruments based on their differing mandates, structures and priorities ( [[#Atteridge--2009|Atteridge et al., 2009]] ; [[#Buchner--2019|Buchner et al., 2019]] ).

Multi-lateral channels include the UNFCCC financial mechanisms, such as the Green Climate Fund, and the multi-lateral development banks (MDBs), such as the World Bank. Both pool contributor resources before committing such resources for climate change projects and programmes. Funding through multi-lateral channels promotes recipient country engagement in the governance and prioritisation of funding decisions, with concurrent processes in the multi-laterals often existing to support country ownership of funded climate action ( [[#Ciplet--2013|Ciplet et al., 2013]] ; [[#Ha--2016|Ha et al., 2016]] ).

There are five multi-lateral climate change funds of the UNFCCC and Paris Agreement financial mechanisms. There are further multi-lateral climate change funds that are not governed by the UNFCCC or Paris Agreement, the largest of which is the World Bank governed Climate Investment Funds ( [[#Watson--2021|Watson and Schalatek, 2021]] ). Some of the major multi-lateral climate change funds have been established with a specific focus on adaptation, while some bilateral donors have thematic or sectoral priorities. Multi-lateral climate change funds operate through accredited implementing entities. These have historically been multi-lateral in nature, such as the development banks, but recent years have seen a rise in the accreditation of national and regional institutions ( [[#UNFCCC%20SCF--2018|UNFCCC SCF, 2018]] ). In addition to programming funds from external sources, such as through the multi-lateral climate change funds, the MDBs also raise and programme their own climate finance ( [[#UNFCCC%20SCF--2018|UNFCCC SCF, 2018]] ; [[#MDBs--2019|MDBs, 2019]] ).

Several major multi-lateral climate change funds work through grant-only programmes, whereas others include concessional loan, equity and guarantee instruments. The broader suite of instruments used by the MDBs includes grant, investment loan, equity, guarantee, line of credit, policy-based financing and results-based financing ( [[#MDBs--2019|MDBs, 2019]] ).

Public funding of a concessional nature that flows from Annex II to non-Annex I countries supports research and capacity building and can also facilitate private finance flows into climate action, with the intention to avoid creating a high debt burden in developing countries, in response to climate impacts for which they have little historic responsibility ( [[#Watson--2016|Watson, 2016]] ; [[#Carter--2020|Carter, 2020]] ; [[#Schalatek--2020|Schalatek, 2020]] ). Less concessional public finance flows include other official flows that are not developmental in nature and can be trade related, including, for example, export credits.

Critiques of the public climate finance architecture are aimed at the overlapping mandates of the institutions programming climate finance, particularly the multi-lateral climate funds, and the challenges in accessing funding ( [[#Nakhooda--2014|Nakhooda et al., 2014]] ; [[#Amerasinghe--2017|Amerasinghe et al., 2017]] ; [[#Pickering--2017|Pickering et al., 2017]] ). However, Pickering et al. (2017) further note that institutional fragmentation of climate finance could result in more flexibility, resilience and innovation. There have also been important governance changes leveraged by some of these funds and instruments, such as integration of gender considerations into projects ( [[#Schalatek--2020|Schalatek, 2020]] ).

'''Private financing of adaptation and resilience'''
There is an increasing focus on the role of the private sector to support large-scale financing of adaptation and resilience ( [[#UNEP--2016|UNEP, 2016]] ; [[#UNEP--2018|UNEP, 2018]] ). To date, it has been difficult to track adaptation and resilience finance within the private sector ( [[#UNEP--2016|UNEP, 2016]] ) as it is either not disclosed or not easily identifiable, since it is often built into capital and operating expenditure and is not a standalone investment. Several private mechanisms are emerging as important sources of climate finance (Gupta et al., 2014; [[#Eccles--2018|Eccles and Krzus, 2018]] ; [[#Miller--2019|Miller et al., 2019]] ).

'''''Green, social impact and resilience bonds''''' are similar to traditional bonds—fixed-income financial instruments raised on commercial markets by companies, governments or financial institutions—but the proceeds are used to fund activities that have positive environmental, social or climate benefit ( [[#Tuhkanen--2020|Tuhkanen, 2020]] ). Green bonds align to voluntary principles, such as the Green Bond Principles set out by the International Capital Market Association, the Climate Bonds Initiative’s Climate Resilience Principles ( [[#Sartzetakis--2020|Sartzetakis, 2020]] ). Given the voluntary nature and lack of standardisation of green bond principles, there are concerns around their additionality, and there is also a lack of data on how green bonds contribute to a scaling up of green projects ( [[#Dupre--2018|Dupre et al., 2018]] ).

Green bond annual issuance reached 260 billion in 2019 ( [[#CBI--2020|CBI, 2020]] ), but as of 2018, only 3–5% (USD 12 billion) of green bond total proceeds can be explicitly traced to climate-resilience-related efforts ( [[#CBI--2019|CBI, 2019]] ). Examples of AR focused bonds include those issued by Fiji in 2017, dedicating 91% of spending to adaptation and resilience ( [[#Shukla--2017|Shukla and Peyraud, 2017]] ; [[#Ministry%20of%20Economy--2019|Ministry of Economy, 2019]] ), and by the European Bank for Reconstruction and Development’s 2019 Climate Resilience Bond for USD 700 million to finance climate-resilient infrastructure, commercial operations, agriculture or ecological systems ( [[#EBRD--2019|EBRD, 2019]] ).

'''''Dedicated investment vehicles''''' are equity funds that are created to invest in products and services that enhance resilience and reduce risks. An example is the Climate Resilience and Adaptation Finance and Technology Transfer Facility that is proposed as a USD 500 million private equity fund to invest in companies providing climate resilience solutions for developing countries. Initial funding has been provided by donors ( [[#Miller--2019|Miller et al., 2019]] ).

'''''Balance sheet finance''''' occurs when an entity directly invests in resilience and adaptation rather than as a separate project. This source of funding may be from exiting reserves, re-allocation from other budget lines, or via external commercial finance, but the investment is financed by the firm rather than as a separate project (Gupta et al., 2014; [[#Buchner--2019|Buchner et al., 2019]] ).

'''''Insurance''''' can play an important role in managing residual climate risks at any given level of adaptation, but insurers can also be important r risk assessment and risk reduction as part of any insurance package ( [[#Jarzabkowski--2019|Jarzabkowski et al., 2019]] ; [[IPCC:Wg2:Chapter:Chapter-11#11.3.8.3|Section 11.3.8.3]] ). While traditional indemnity insurance is important for repair and rebuilding of damaged property and infrastructure, parametric insurance has become increasingly popular for supporting rapid post-disaster responses such as drought, hurricane damage and flooding. Examples include sovereign insurance facilities such as African Risk Capacity and the Caribbean Catastrophe Risk Insurance Facility ( [[#Broberg--2019|Broberg, 2019]] ) as well as weather-index insurance targeted at individuals, especially in agriculture ( [[#Greatrex--2015|Greatrex et al., 2015]] ; [[#Isakson--2015|Isakson, 2015]] ; [[#Surminski--2016|Surminski et al., 2016]] ; [[#Jensen--2017|Jensen and Barrett, 2017]] ; [[#Fischer--2019|Fischer, 2019]] ). The role of insurance as a climate risk management option, as well as limitations, is covered in more depth in [[#17.2|Section 17.2]] and Cross-Chapter Box LOSS (this chapter).

'''Mainstreaming physical climate risks and resilience in the private sector'''
The data on tracked climate finance and green bond issuance for adaptation and resilience both show a substantial gap between the adaptation needs and the finance deployed. Scaling up these instruments is unlikely to close this gap given the challenges with financing adaptation projects, particularly from the private sector. There is therefore a need for more systematic action to manage climate risks and mainstream climate change considerations ( [[#Miller--2019|Miller et al., 2019]] ).

The financial case for mitigation investment can often be demonstrated through revenues from, for example, the sale of renewable electricity. On contrast, the benefits from investment in adaptation and resilience are typically considered in terms of avoided losses and cost benefit ratios. For example, the [[#Global%20Commission%20on%20Adaptation--2019|Global Commission on Adaptation (2019)]] estimates that the overall rate of return on investments in improved resilience is very high, with benefit–cost ratios ranging from 2:1 to 10:1, and in some cases even higher.

The private sector is becoming increasingly aware of the need to assess physical climate risks to avoid the long-term risks to assets and enhance climate resilience. The task force on climate-related financial disclosures (TCFD) is likely to create additional pressure from investors for companies to identify, manage and reduce risks from climate change ( [[#Eccles--2018|Eccles and Krzus, 2018]] ; [[#ERM%20and%20CBEY--2018|ERM and CBEY, 2018]] ; [[#Tuhkanen--2020|Tuhkanen, 2020]] ).

A key factor for the impact of the TCFD on mainstreaming of physical climate risks and demonstrating the case for investment in adaptation and resilience will be how investors systematically incorporate physical climate risks, adaptation and resilience into their investment decisions. The Coalition for Climate Resilient Investment ( [[#DFID--2019|DFID et al., 2019]] ) was established to look at this from the private sector viewpoint and is working to systematically incorporate resilience into cash flow modelling and asset valuation practices, so that investors may quantify the investment in resilience for an asset and the benefits associated with reduced costs and more reliable revenue streams.

'''Recent trends in climate finance flows'''
Considerable progress has been made in tracking climate finance since AR5, but substantial gaps remain, especially regarding domestic public finance and private sector balance sheet investment in adaptation ( [[#17.5.1|Section 17.5.1.5]] ; [[#CPI--2020|CPI, 2020]] ; [[#Richmond--2020|Richmond et al., 2020]] ). The best documented information comes from international climate funds, which provide detail at the project level. Most bilateral and multi-lateral investment institutions report on whether debt, grants and other instruments are for climate projects, but with less detail. Private finance is harder to track, as reporting is voluntary; even for green bonds, where certification identifies the range of sectors a bond aims to cover, reporting of how the bond is spent is infrequent.

The Climate Policy Initiative (CPI) has been tracking climate finance since 2009, allowing for trends to be assessed; however, trends reported are a function of both real changes in finance and changes in methods and information sources ( [[#Richmond--2020|Richmond et al., 2020]] ). Total climate finance tracked by CPI has increased from USD 364 billion yr −1 in 2010/2011 to 579 billion in 2017/2018 (SM17.3). Tracked finance remained relatively constant from 2010/2011 to 2013/2014 but has increased steeply in more recent years. The proportion of finance allocated to adaptation has remained small throughout, between 4% and 8% ( ''high confidence'' ); a further 1–2% of global finance has been classified as ‘multiple-objectives’. The large majority of tracked adaptation finance is from public sources ( ''high confidence'' ), with only 2% coming from private sources in 2017/2018 ( [[#CPI--2020|CPI, 2020]] ). This is at least partly because of the difficulty in demonstrating financial (as opposed to public good and avoided damages) return on investment for adaptation.

The majority of the most recently (2017/18) tracked adaptation and multiple-objective finance was supplied through public donors, largely through grants, concessional and non-concessional instruments (Figure FAR.1). Most finance (44.1%) was spent transregionally (allocated in specific projects to recipients in more than a single region). For regionally specific funding, Sub-Saharan Africa and South Asia, along with the Latin America and Caribbean region, received the largest gross amounts, although Oceania has received the greatest per-capita funding. The largest proportion of AR funding has been allocated to increasing the resilience of infrastructure, energy and the built environment, followed by agriculture, forestry and natural management, and then water and wastewater.

Across financial instruments, Sub-Saharan Africa received the highest relative proportion through grants (38%), followed by the Latin America and Caribbean region (23%), with other non-Organisation for Economic Co-operation and Development (OECD) regions receiving between 16% and 10% (SM17.3). Concessional debt as a proportion of the regional total varies from 84% in South Asia to as low as 29% in Latin America and Caribbean, which has the highest proportion of non-concessional debt (48%).

[[File:49c2c94a5683c22f964bcc423661fc9d IPCC_AR6_WGII_Figure_17_Cross-Chapter_Box_FINANCE_2.png]]

'''Figure Cross-Chapter Box FINANCE.2 |''' '''The flow and distribution of globally tracked adaptation and resilience finance in 2018 from different sources, through different instruments into different sectors and regions.''' Each strand shows the relative proportion of finance flowing from one category to another (for example, from private or public sources to different instruments). Categories from left to right are: (a) whether the finance is solely for adaptation or for adaptation and other objectives, including mitigation (multiple objectives); (b) whether the finance comes from public or private sources; (c) the financing instrument; (d) the broad sectoral allocation; (e) the geographical distribution of funding (proportion of total in % and per-capita allocation). Based on data collated by [[#CPI--2020|CPI (2020)]] .

'''The importance of public and private finance for adaptation and resilience'''
Adaptation finance provided by international public mechanisms remains the core source of tracked flows in support of adaptation and resilience to developing countries ( [[#Micale--2018|Micale et al., 2018]] ; [[#UNEP--2018|UNEP, 2018]] ), although these public funds alone are insufficient to meet rapidly growing needs and constitute only a minority share of all public climate finance flows ( [[#UNEP--2016|UNEP, 2016]] ; [[#Global%20Commission%20on%20Adaptation--2019|Global Commission on Adaptation, 2019]] ).

Public mechanisms can play a role in leveraging private sector finance for adaptation by addressing real and perceived regulatory, cost and market barriers through blended finance approaches, public–private partnerships or innovative financial instruments and structuring in support of private sector requirements for risk management and guaranteed investment returns ( [[#Pillay--2017|Pillay et al., 2017]] ; [[#Miller--2019|Miller et al., 2019]] ).

There is growing agreement on the sectors (such as infrastructure, agriculture or water management) and approaches (contingency finance or insurance) where private sector adaptation investments alone, or leveraged by public mechanisms, might be best targeted, such as by reducing the risk of providing financial services for adaptation investments to domestic micro-, small and medium enterprises or agricultural smallholders, many of them women ( [[#Biagini--2013|Biagini and Miller, 2013]] ; [[#Chambwera--2014|Chambwera et al., 2014]] ; [[#Pauw--2016|Pauw et al., 2016]] ; [[#Global%20Commission%20on%20Adaptation--2019|Global Commission on Adaptation, 2019]] ; [[#Miller--2019|Miller et al., 2019]] ; [[#Resurrección--2019|Resurrección et al., 2019]] ; [[#Richmond--2020|Richmond et al., 2020]] ). A remaining open question is how to allocate limited public adaptation funds in a way that is equitable, effective and efficient between mobilising private investments and safeguarding adequate financial support for necessary adaptation efforts, such as the provision of public goods, which the private sector will not invest in ( [[#Fankhauser--2011|Fankhauser and Burton, 2011]] ; [[#Abadie--2013|Abadie et al., 2013]] ; [[#Baatz--2018|Baatz, 2018]] ; [[#Omari-Motsumi--2019|Omari-Motsumi et al., 2019]] ).

Many adaptation interventions in the most vulnerable countries, communities and people provide no adequate financial return on investments and can therefore can only be funded with highly concessional public finance. Grant support is most appropriate for measures such as capacity building, planning, public policy and regulatory reforms, disaster risk management and response, community engagement or support for social safety nets, and for addressing social vulnerabilities, including poverty or gender inequality, which constrain adaptation ( [[#Grasso--2010a|Grasso, 2010a]] ; [[#Pillay--2017|Pillay et al., 2017]] ; [[#Agrawal--2019|Agrawal et al., 2019]] ; [[#Buchner--2019|Buchner et al., 2019]] ).

Access to adequate adaptation grant finance is further constrained because several public mechanisms provide grants only for the additional costs of adaptation measures compared with a development baseline in the absence of climate impacts. Calculating the incremental costs of adaptation measures imposes additional time and resource burden on the most vulnerable recipients, who are often faced with data gaps or technical capacity constraints ( [[#Chambwera--2014|Chambwera et al., 2014]] ; GCF, 2018; [[#UNEP--2018|UNEP, 2018]] ; [[#Omari-Motsumi--2019|Omari-Motsumi et al., 2019]] ).

An exact delineation of respective costs for adaptation and development components is difficult and might be unsuitable as many adaptation measures are intrinsically linked to development. It may also prevent realising necessary synergies between both components ( [[#McGray--2007|McGray et al., 2007]] ; [[#Smith--2011|Smith et al., 2011]] ; [[#Denton--2014|Denton et al., 2014]] ; [[#Resch--2017|Resch et al., 2017]] ; [[#Micale--2018|Micale et al., 2018]] ).

'''Equality and fairness in climate finance'''
Climate finance literature recognises that poor and least developed households, communities and countries are most affected and marginalised by climate change, and least responsible for its causes, but receive relatively little financial support for adaptation (Chapters 15, 8; [[#Olsson--2014|Olsson et al., 2014]] ; [[#Rozenberg--2015|Rozenberg and Hallegatte, 2015]] ; [[#Hallegatte--2016|Hallegatte et al., 2016]] ; [[#Rai--2017|Rai and Fisher, 2017]] ; [[#Shakya--2017|Shakya and Byrnes, 2017]] ).

While the gap between current financial flows to developing countries and their adaptation needs (see Box Cross-Chapter Box FINANCE.1) is a major factor undermining equity and fairness in financing, several other factors that can also affect fair and just financing in developing countries have been identified in recent literature ( [[#Klein--2014|Klein et al., 2014]] ; [[#Colenbrander--2018|Colenbrander et al., 2018]] ; [[#Mfitumukiza--2019|Mfitumukiza et al., 2019]] ; [[#Khan--2019a|Khan et al., 2019a]] ; [[#Doshi--2020|Doshi and Garschagen, 2020]] ). First, financing is skewed in favour of mitigation, and therefore towards fast-growing upper- and middle-income countries offering the biggest gains in emission reductions, especially in Southeast Asia, but also in Sub-Saharan Africa ( [[#Rai--2016|Rai et al., 2016]] ). Further, as much of current finance uses debt-based instruments, mitigation projects are further preferred as returns are more assured ( [[#Lee--2018|Lee and Hong, 2018]] ; [[#Carty--2020|Carty et al., 2020]] ).

Second, the requirement of many funders for readiness and fiduciary capacity means that least developed countries (LDCs) have been less able to access finance, despite many support mechanisms being offered. Additionally, geopolitical preferences of some countries mean that some developing countries are preferred to others for bilateral funding ( [[#Doshi--2020|Doshi and Garschagen, 2020]] ). This is exacerbated for private sector investment, where lower credit ratings make finance more expensive, and increasing understanding of exposure to physical climate risks could lead to ‘capital flight’ from most vulnerable countries ( [[#Global%20Commission%20on%20Adaptation--2019|Global Commission on Adaptation, 2019]] ; [[#Miller--2019|Miller et al., 2019]] ; [[#Cooper--2020|Cooper, 2020]] ).

Third, within climate-vulnerable countries, very little is channelled to local communities who need it most; the few analyses available suggest that less than 10% of total climate finance supports decentralised actions ( [[#Rai--2016|Rai et al., 2016]] ; [[#Soanes--2017|Soanes et al., 2017]] ). Reasons include: (i) lack of consideration of procedural equity in programme design ( [[#Grasso--2010b|Grasso, 2010b]] ; [[#Wang--2018|Wang and Gao, 2018]] ; [[#Venn--2019|Venn, 2019]] ; [[#Khan--2019a|Khan et al., 2019a]] ); (ii) finance being managed by multi-lateral implementers, rather than agencies that are closer to local communities; (iii) the higher transaction costs of decentralised projects in low-income communities reduce their attractiveness to funders as well as the ability of local organisations to meet the fiduciary standards ( [[#Fonta--2018|Fonta et al., 2018]] ; [[#Omari-Motsumi--2019|Omari-Motsumi et al., 2019]] ).

It has been proposed that, as middle-income countries can leverage mitigation finance from the private sector, targeting scarce public finance towards LDCs and SIDS may be necessary to ensure sufficient funds reach these countries ( [[#Steele--2015|Steele, 2015]] ). Matching domestic climate spending with international support is one way to ensure LDCs get the funds they need ( [[#Grasso--2010b|Grasso, 2010b]] ; [[#Bird--2014|Bird, 2014]] ). Targeting specific marginalised communities and women within countries can also help make climate finance more effective and fairer, such as the Asian Development Bank’s efforts to make lending portfolios more inclusive and pro-poor ( [[#ADB--2018|ADB, 2018]] ).

'''Post-COVID recovery packages, debt relief and finance for adaptation and resilience'''
Recent literature has highlighted the opportunity that COVID recovery packages offer for environmentally sustainable, low-carbon and climate-resilient economic growth ( [[#Forster--2020|Forster et al., 2020]] ; [[#Hepburn--2020|Hepburn et al., 2020]] ; [[#Hanna--2021|Hanna et al., 2021]] ). Assessment of whether this is indeed happening is limited, although the few available studies suggest that that this opportunity is not being realised in many nations ( [[#O’Callaghan--2021|O’Callaghan and Murdock, 2021]] ; VIVID [[#Economics--2021|Economics, 2021]] ). One study of the Group of Twenty (G20) and 10 other nations suggested that stimulus packages would have net negative environmental impact in two-thirds of these countries (VIVID [[#Economics--2021|Economics, 2021]] ), while another showed that around half of G20 recovery investment targeted at energy has had gone towards fossil fuels, rather than to cleaner energy sources ( [[#Dibley--2021|Dibley et al., 2021]] ).

Concerns have also been raised about the interactions between debt service, COVID economic recession and post-COVID recovery in developing countries ( [[#Simmons--2021|Simmons et al., 2021]] ; [[#Volz--2021|Volz et al., 2021]] ). Debt service grows as a proportion of national budget during recession, reducing scope for investment in recovery, is a self-reinforcing cycle. It has been suggested that linking debt relief to Paris-aligned objectives can act as an additional source of climate finance ( [[#Fenton--2014|Fenton et al., 2014]] ). The G20 has begun addressing this debt crisis through its Debt Service Suspension Initiative and the Common Framework for Debt Treatments ( [[#IMF--2020|IMF, 2020]] ). It has been suggested that these initiatives could be expanded to prioritise climate-focused debt-relief instruments and to include more countries ( [[#Steele--2020|Steele and Patel, 2020]] ; [[#Volz--2021|Volz et al., 2021]] ). If debt relief is used to invest in national instrument for green and inclusive recovery, national ownership of the use of the finance can occur, avoiding some of the negative connotations of historical debt restructuring ( [[#Volz--2021|Volz et al., 2021]] ).

<div id="17.4.5" class="h2-container"></div>

<span id="enabling-condition-4-catalysing-conditions"></span>
=== 17.4.5 Enabling Condition 4: Catalysing Conditions ===

<div id="h2-12-siblings" class="h2-siblings"></div>

A clear difference between enabling conditions and catalysing conditions is emerging in the climate mitigation literature ( [[#Hermwille--2019|Hermwille et al., 2019]] ; [[#Michaelowa--2021|Michaelowa et al., 2021]] ), with some examples in the adaptation literature as well ( [[#Madsen--2019|Madsen et al., 2019]] ; [[#Booysen--2019a|Booysen et al., 2019a]] ; [[#Bolorinos--2020|Bolorinos et al., 2020]] ). Though enabling conditions are necessary pre-conditions that allow response options to be formulated and implemented, their presence alone does not guarantee that these response options will occur in a timely fashion or at a scale commensurate with the risk, or even that they will occur at all. Catalysing conditions address this deficit in advancing action. They serve to overcome the inertia that often operates as a barrier to action and motivate individuals and organisations to initiate or accelerate action. Different forms of catalysing conditions, described below, lead individuals and organisations to weigh more seriously the costs of delaying action or keeping action at low levels. Catalysing conditions focus the attention of individuals and organisations on particular risks, leading actors to augment their decision-making processes and to allocate financial and social resources to respond to those risks. This attention and deliberation can lead to more frequent and potentially substantial adaptations, whether through more extensive action on existing forms of adaptation or through the adoption of entirely new adaptations ( [[#Bolorinos--2020|Bolorinos et al., 2020]] ).

The first two catalysing conditions described below address the costs of delaying action. Urgency increases the awareness of individuals and organisations of such costs, while windows of opportunity, including extreme events, are time-bound periods during which certain actions are possible, but after which they are more difficult or impossible. The other two conditions stimulate new forms or levels of action by promoting or directing step changes from one policy or management regime to another ( [[#Solecki--2017|Solecki et al., 2017]] ). Litigation over adaptation issues, for example, can open new lines of action or close off old ones, while catalysing agents advance action through a variety of means (e.g., communicating the urgency of climate action, revising agendas for action, expanding coalitions which undertake action). As detailed below, these four catalysing conditions can operate together as well as separately to promote more prompt and extensive adaptations.

<div id="17.4.5.1" class="h3-container"></div>

<span id="urgency"></span>
==== 17.4.5.1 Urgency ====

<div id="h3-23-siblings" class="h3-siblings"></div>

Urgency can catalyse action for individuals and organisations. A moderate level of urgency serves as an important driver of climate action, but both high and low levels of urgency impede response ( ''high confidence'' ). [[#Wilson--2021|Wilson and Orlove (2021)]] review 5 experimental and 20 observational papers that examine the relationship between urgency and levels of response in climate decision-making, across a range of settings: from individuals and households to communities, managed ecosystems, sub-national regions and international river basin. Urgency in the papers is defined primarily through objective and subjective time pressure, including the recognition of the costs of delaying action and the importance of using windows of opportunity during which new forms and higher levels of response are possible. All the experimental papers and all but three of the observational papers provide support for an inverted U-shaped relationship between urgency and response intensity (including motivation and action), with higher levels of response at intermediate levels of urgency and lower levels of response at low or high levels of urgency (Figure 17.9). The general shape of this relationship also is supported for other decision domains by a well-established line of research within psychology ( [[#Heitz--2014|Heitz, 2014]] ; [[#Zakay--2014|Zakay, 2014]] ; [[#Prem--2017|Prem et al., 2017]] ).

<div id="_idContainer044" class="Figure"></div>

[[File:f7cac68a574d51efb5c3b0e62d9f4bae IPCC_AR6_WGII_Figure_17_009.png]]

'''Figure 17.9 |''' '''A moderate level of urgency serves as an important driver of climate action, but both high and low levels of urgency impede response (derived from [[#Wilson--2021|Wilson and Orlove, 2021]] ).'''

The synthesis of the studies on urgency offers two central lessons for policymakers, community groups and others involved in addressing climate change. First, greater levels of response to climate change-induced challenges can be motivated by communication strategies that move decision makers from low to moderate levels of urgency ( ''high confidence'' ). In the case of drought, a number of studies show that urgent messages promote water conservation, especially when these messages are repeated, perceived as trustworthy and linked to concrete suggestions for action ( [[#Gonzales--2017|Gonzales and Ajami, 2017]] ; [[#Joubert--2019|Joubert and]] [[#Ziervogel--2019|Ziervogel, 2019]] ; [[#Kam--2019|Kam et al., 2019]] ; [[#Booysen--2019a|Booysen et al., 2019a]] ; [[#Booysen--2019b|Booysen et al., 2019b]] ; [[#Bolorinos--2020|Bolorinos et al., 2020]] ). These effects are also demonstrated in experimental studies of adaptation planning in contexts including European flood preparations ( [[#Madsen--2019|Madsen et al., 2019]] ; [[#Pot--2019|Pot et al., 2019]] ) and Pacific Island coastal planning ( [[#Donner--2014|Donner and Webber, 2014]] ).

Second, very high levels of urgency are a barrier to effective action ( ''medium confidence'' ) because last-minute actions to reduce risk during crises can create haste and panic, often leading to insufficient deliberation. In these cases, decision makers fail to consider a full range of alternative actions, make rash choices and poorly mobilise available resources ( [[#Asfaw--2019|Asfaw et al., 2019]] ; [[#Robins--2019|Robins, 2019]] ; [[#Gee--2020|Gee, 2020]] ). Given that climate decision makers in many regions and sectors are experiencing greater pressure to act, this finding suggests the existence of windows for planning and action during which climate risks have led to moderate levels of urgency, but before these risks have resulted in urgency exceeding some upper threshold ( [[#17.4.5.2|Section 17.4.5.2]] ).

In addition, these studies point to potential weaknesses as well as strengths in strategic communication to modulate urgency. Such messages may instead lead to lower levels of response if they induce very high levels of urgency ( [[#Asfaw--2019|Asfaw et al., 2019]] ), though this effect may be somewhat mitigated by messages that simultaneously increase recipients’ sense of self-efficacy or they are experienced in the specific risk domain discussed in the messages ( [[#Bodin--2019|Bodin et al., 2019]] ). Future research on the relationships between urgency and effective risk management could help refine the measurement of urgency, how the relationship varies in different contexts, the role of different forms of messaging about urgency and action ( [[#Fesenfeld--2021|Fesenfeld and Rinscheid, 2021]] ), and the effects of urgency on decision-making by high-level decision makers within polities and by climate social movements.

<div id="17.4.5.2" class="h3-container"></div>

<span id="windows-of-opportunity"></span>
==== 17.4.5.2 Windows of Opportunity ====

<div id="h3-24-siblings" class="h3-siblings"></div>

Windows of opportunity are time-bounded periods during which conditions are present for advancing and often accelerating climate adaptation strategies. They can act as significant catalysing conditions for climate action and are connected to a range of possible outcomes from small incremental shifts to larger-scale more profound transformation adaptations ( [[#Novalia--2020|Novalia and Malekpour, 2020]] ).

Windows can open because of extreme weather events ( [[#Birkmann--2008|Birkmann and Fernando, 2008]] ), political shifts, such as new institutions, new laws and regulations, and presence of a new policy entrepreneur or new policies ( [[#Haasnoot--2013|Haasnoot et al., 2013]] ; [[#Bell--2015|Bell and Morrison, 2015]] ), relevant and achievable policy goals, and emergence of new knowledge ( [[#Abunnasr--2013|Abunnasr et al., 2013]] ), and close after the initial causes recede and become less efficacious. They also serve as focusing events whereby a coalition of groups address specific policy questions or response options ( [[#Rudel--2019|Rudel, 2019]] ). Recognising that windows of opportunity often catalyse action does not mean that action outside such windows is insignificant or impossible.

Extreme events such as disasters often act as proximate drivers of windows of opportunity ( [[#Birkmann--2008|Birkmann and Fernando, 2008]] ; [[#McSweeney--2011|McSweeney and Coomes, 2011]] ). Climate disasters in a specific location become significant windows for new debate, policymaking and financing ( [[#McSweeney--2011|McSweeney and Coomes, 2011]] ). Extreme events also can facilitate change at locations distant from the most impacted site when remote actors gain perspective on their own risks ( [[#Friedman--2019|Friedman et al., 2019]] ; [[#Solecki--2019|Solecki et al., 2019]] ). Factors that facilitate extreme events driving proactive as opposed to reactive responses include access to relevant risk and vulnerability data, pre-existing experience with similar events, and appropriate governance ( [[#Brown--2017a|Brown et al., 2017a]] ). [[#Page--2020|Page and Dilling (2020)]] find that worldview or ideology plays a central role in sense-making and in shaping what organisational decision makers ‘see’ in terms of acceptable actions in response to an extreme event.

Significant variation is present across the mix and intensity of conditions that promote action through a window of opportunity. Capacity to respond to is a function of the presence of enabling conditions as well as tools and methods to aid decision-making (Shi et al., 2015). Political activism provides windows of opportunity for climate adaptation ( [[#Lauer--2016|Lauer and Eguavoen, 2016]] ; see also [[#17.4.5.3|Section 17.4.5.3.1]] ).

Sudden shifts in institutions and legal framework can also catalyse climate action. For example, the year 2015 included a series of international frameworks such as the Sendai Framework for Disaster Risk Reduction 2015–2030 ( [[#van%20Niekerk--2020|van Niekerk et al., 2020]] ; [[#Hofmann--2021|Hofmann, 2021]] ), the 2030 Agenda for Sustainable Development, which established the Sustainable Development Goals ( [[#Sanchez%20Rodriguez--2018|Sanchez Rodriguez et al., 2018]] ), and the Paris Climate Agreement, which dramatically enhanced the promotion and implementation of altered the conditions under which climate adaptation occurred.

<div id="17.4.5.3" class="h3-container"></div>

<span id="climate-litigation-on-adaptation"></span>
==== 17.4.5.3 Climate Litigation on Adaptation ====

<div id="h3-25-siblings" class="h3-siblings"></div>

Litigation for Loss and Damage from climate change was first noted as a potential motivator for emissions reduction in AR4, and AR5 noted that litigation was pending but not tested and that, while legal systems were beginning to define the boundaries of responsibility for climate change, it was ‘unclear liability exists’. The SR1.5 ( [[#IPCC--2018a|IPCC, 2018a]] ) reported, with ''high confidence'' , that litigation risks of government and business had increased, and the SRCCL ( [[#IPCC--2019b|IPCC, 2019b]] ) noted that recent developments in climate attribution improve the ability to detect human influence on climate and broaden liability.

Since AR5 there has been growing recognition of the potential of litigation for failure to take measures to adapt to climate change to drive climate risk management ( [[#Banda--2017|Banda and Fulton, 2017]] ; [[#Peel--2017|Peel et al., 2017]] ; [[#Bouwer--2018|Bouwer, 2018]] ). Litigation cases on adaptation and loss and damage account for about one-third of those covered in the literature ( [[#Setzer--2019|Setzer and Vanhala, 2019]] ). Reasons for this growth are: (i) the growing gap between projected climate change impacts and current adaptation efforts ( [[#Stezer--2019|Stezer and Byrnes, 2019]] ) and (ii) expanded legal duty of government, business and others to manage foreseeable harms ( [[#Marjanac--2018|Marjanac and Patton, 2018]] ). Climate change litigation is expanding geographically into the Americas, Asia (and the Pacific region) and Europe, with several cases brought in low- and middle-income countries ( [[#Stezer--2019|Stezer and Byrnes, 2019]] ) (Table 17.6).

Lawsuits against private entities contribute to articulating climate change as a legal and financial risk ( ''medium confidence'' ) ( [[#Peel--2015|Peel and Osofsky, 2015]] ; [[#Ganguly--2018|Ganguly et al., 2018]] ; [[#McCormick--2018|McCormick et al., 2018]] ; [[#Peel--2018|Peel and Osofsky, 2018]] ). Even if unsuccessful, [[#Estrin--2016|Estrin (2016)]] concludes they are important in underlining the high level of public concern.

Climate-related, legal, financial disclosure requirements are improving investment decision-making of corporations as well as augmenting ''ex post'' liability for failure to consider climate change risk in decision-making. Organisations are required to disclose governance around climate-related risks (impact of climate change on businesses, products, services, supply or value chain, adaptation and mitigation activities, investment in research and development and operations). This functions as a vehicle for identifying climate-related risk and the organisation’s resilience strategy taking into consideration different climate- related scenarios including a 2°C or lower scenario ( [[#Sarra--2018|Sarra, 2018]] ). Institutions such as the G20 ( [[#Carney--2019|Carney, 2019]] ), the American Bar Association ( [[#Brammer--2019|Brammer and Chakrabarti, 2019]] ) and the European Commission ( [[#Zadek--2018|Zadek, 2018]] ) have adopted or endorsed these standards.

'''Table 17.6 |''' Examples of types of climate-related litigation.

{| class="wikitable"
|-
! Litigation type

! Detail and examples

! Supporting literature

|-
| Challenge government decisions for not considering climate change risks

| Challenging government or administrative planning decisions for failure to consider, or adequately address, climate change in relation to developing and protecting coastal zones, water-stressed regions, flood-prone areas or decisions affecting endangered species whose habitat is at 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 &amp; Ors (No2), 2008).

| [[#Banda--2017|Banda and Fulton (2017)]] ; Peel et al. (2017); [[#Bouwer--2018|Bouwer (2018)]] ; [[#Clarke--2018|Clarke and Hussain (2018)]]

|-
| Petitions to act

| Constitutional petitions to force governments to take adaptation measures. As an example, in Leghari v. Pakistan a farmer initiated public interest litigation against federal and provincial governments for failure to develop climate change resilience through adaptation to floods, droughts and other impacts because it violated his rights to life and dignity. The High Court of Lahore found for Mr. Leghari and created a commission to develop and implement a wide range of adaptation actions.

| [[#Banda--2017|Banda and Fulton (2017)]] ; Ashgar Leghari v. Federation of Pakistan (April 2015); Ashgar Leghari v. Federation of Pakistan (September 2015)

|-
| Regulatory proceedings

| Environmental groups and city and state officials intervened in the application of the electric utility serving New York City, Consolidated Edison Company, to the New York State Public Service Commission for a rate increase. The intervenors argued that the company was not adequately preparing for flooding, heatwaves and other 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.

| [[#Consolidated%20Edison%20Co.--2019|Consolidated Edison Co. (2019)]]

|-
| Failure to act by public authorities

| Liability of public authorities for failure to undertake necessary adaptation actions to avoid damage to life or property, especially where statutory framework is proven 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).

| [[#Banda--2017|Banda and Fulton (2017)]] ; Peel et al. (2017); [[#Bouwer--2018|Bouwer (2018)]]

|-
| Failure by private sector to consider climate change adaptation in their business practice

| Examples include: (i) a citizen suit against ExxonMobil for failure to adapt Everett Terminal to the impacts of climate change including increased precipitation, sea level rise and storm surges occurring with increasing frequency; (ii) a citizen suit against Shell Oil Products US alleging Shell failed to incorporate climate risks in its investment in a bulk storage and fuel terminal in Rhode Island, USA; (iii) shareholder action against ExxonMobil for failure to 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.

| [[#Benjamin--2017|Benjamin (2017)]] ; [[#Stezer--2019|Stezer and Byrnes (2019)]] ; [[#Street--2019|Street and Jude (2019)]] ; [[#Wasim--2019|Wasim (2019)]] ; [[#Conservation%20Law%20Foundation%20v.%20Exxon%20Mobil%20Corporation--2021|Conservation Law Foundation v. Exxon Mobil Corporation (2021)]]

|-
| Youth public trust claims

| Government inter-generational liability for inadequate climate change mitigation and adaptation efforts. Our Children’s Trust (a non-profit organisation) and others brought an action against the USA 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 by the governments’ affirmative actions that actively cause and worsen the climate crisis. Similarly, a public trust claim could be brought in a coastal town for failure to adapt to climate change.

| Schneider et al. (2017); [[#Bouwer--2018|Bouwer (2018)]]

|-
| Human rights claims

| Human rights may be a powerful tool for organising and unifying adaptation decision-making, especially for the most vulnerable, through enforcement mechanisms of progressive realisation as well as ''ex post'' liability (Chapter 8). For example, a persons’ right to food implores state parties to take necessary actions to alleviate hunger 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.

| [[#Hall--2012|Hall and Weiss (2012)]] ; [[#Peel--2018|Peel and Osofsky (2018)]] ; [[#Setzer--2019|Setzer and Vanhala (2019)]] ; [[#Stezer--2019|Stezer and Byrnes (2019)]]

|}

<div id="17.4.5.4" class="h3-container"></div>

<span id="catalysing-agents"></span>
==== 17.4.5.4 Catalysing Agents ====

<div id="h3-26-siblings" class="h3-siblings"></div>

Individuals and organisations often serve as catalysing agents of climate risk decision-making. They promote greater levels of new forms of climate action by communicating the urgency of climate action and by developing coalitions which undertake action. Agents include individuals, organisations or collectives, or multiple organisations linked together.

<div id="17.4.5.4.1" class="h4-container"></div>

<span id="social-movements-and-other-mobilisations"></span>
===== 17.4.5.4.1 Social movements and other mobilisations =====

<div id="h4-18-siblings" class="h4-siblings"></div>

Recent studies of climate-related social movements show that they can act as catalysing agents which promote action to manage climate-related risks ( ''medium confidence'' ). However, these studies use varying definitions of climate movements within the broader context of environmental movements. A prominent topic of research is the rapidity and the large scale of the proliferation of these movements around the world, primarily in urban settings but also in rural and Indigenous contexts ( [[#Claeys--2017|Claeys and Delgado Pugley, 2017]] ).

These movements usually focus on climate mitigation but sometimes include adaptation. Their social bases include groups which had not previously been active in climate politics, notably children and youth, as well as sectors with long traditions of environmental activism, such as women and Indigenous Peoples (see Cross-Chapter Boxes GENDER and INDIG in Chapter 18). Much of the literature on youth movements traces the emergence of the movements themselves ( [[#Sanson--2019|Sanson et al., 2019]] ; [[#Treichel--2020|Treichel, 2020]] ), their framings of climate change as a social justice issue ( [[#Holmberg--2019|Holmberg and Alvinius, 2019]] ) and their presence in demonstrations and on social media ( [[#Boulianne--2020|Boulianne et al., 2020]] ). Climate action catalysed by youth and other climate movements include visible international events such as the signing of Declaration on Children, Youth, and Climate Action at COP25 in Madrid 2019 ( [[#Han--2020|Han and Ahn, 2020]] ), as well as national efforts, including lawsuits, and local events such as in tree-planting and waste reduction initiatives ( [[#Bandura--2019|Bandura and Cherry, 2019]] ).

A recent review examines 2743 cases around the world of mobilisations for environmental justice causes ( [[#Scheidel--2020|Scheidel et al., 2020]] ); roughly half the cases occurred between 1970 and 2007, and half between 2008 and 2019. Of these environmental mobilisations, 17% are directly related to climate and energy, and others are related to climate-sensitive issues (15% for biomass and land use, 14% for water management). This study reports the proportion of positive outcomes for different strategies, defined as meeting the goals of the movements, which generally align with climate adaptation and sustainable resource management. These rates vary from 10% for negotiated solutions to 34% for court decisions. It notes the corresponding higher rates of failure, as well as the costs borne by the movements, which include criminalisation (20% of cases), violence (18%) and assassination (13%). These costs are significantly higher for Indigenous communities that engage in these mobilisations.

At a global scale, climate movements succeeded in pressing for the greater recognition of the importance of Indigenous knowledge within international agreements ( [[#Tormos-Aponte--2018|Tormos-Aponte and García-López, 2018]] ) but did not achieve the major reforms of climate finance which they sought ( [[#Khan--2019a|Khan et al., 2019a]] ); these differing outcomes reflect the sensitivity of the issues and the formation of coalitions which supported or opposed the movements. At national and local scales, one review of US cases reports limited effectiveness of climate movements because of the ability of governmental agencies to co-opt them ( [[#Pulido--2016|Pulido et al., 2016]] ), while another review in Pakistan shows a number of successes, because the movements were able to build alliances with other public sector and community groups ( [[#Shawoo--2020|Shawoo and McDermott, 2020]] ).

<div id="17.4.5.4.2" class="h4-container"></div>

<span id="policy-leaders-and-entrepreneurs"></span>
===== 17.4.5.4.2 Policy leaders and entrepreneurs =====

<div id="h4-19-siblings" class="h4-siblings"></div>

Policy leaders, often described as policy entrepreneurs within the scholarly literature, are individuals in positions of leadership who set agendas and build coalitions to drive decision-making processes, and hence can function as catalysers of climate adaptation ( [[#Petridou--2020|Petridou and Mintrom, 2020]] ). Political leaders who have taken on climate change as a key policy issue function as policy entrepreneurs at international, national and sub-national levels. City officials, including mayors and other executives, often play the role of climate policy entrepreneurs, while the absence of effective leadership negatively affects adaptation success ( [[#Becker--2019|Becker and Kretsch, 2019]] ). Such entrepreneurs can be important forces for change in both reactive contexts following an extreme or focusing event and in proactive context. They can be effective especially in contexts where they navigate and link together formal and informal networks of complex climate governance systems ( [[#Tanner--2019|Tanner et al., 2019]] ). Their capacity to act has been increased when they and their institutions are embedded within partnership networks ( [[#Bellinson--2019|Bellinson and Chu, 2019]] ). It is in these contexts that the leadership and position of a policy entrepreneur becomes even more catalytic when operating at the interface of formal and informal networks ( [[#Mintrom--2019|Mintrom, 2019]] ; [[#Stone--2019|Stone, 2019]] ).

Sub-national actors and city officials including mayors and other executives are among the individuals most often described and assessed as climate policy entrepreneurs ( [[#Kalafatis--2017|Kalafatis and Lemos, 2017]] ). City-level climate policy entrepreneurs often operate using their own experience, connections and persistence to address issues of importance to their constituency. Climate risk concerns are often inherently local, and in turn local decision makers perceive it as being appropriate to engage. Conversely, the absence of effective leadership negatively affects adaptation success ( [[#Kalafatis--2017|Kalafatis and Lemos, 2017]] ; [[#Becker--2019|Becker and Kretsch, 2019]] ). Urban climate policy entrepreneurs operate in four key spheres of policy development and implementation: attention and support seeking strategies; linking strategies (e.g., coalition building); relational management strategies (e.g., networking and trusting building); and arena strategies including timing ( [[#Brouwer--2018|Brouwer and Huitema, 2018]] ). The presence and operation of urban climate policy entrepreneurs is positively associated in settings with multiple jurisdictions and across differing spatial scales ( [[#Kalafatis--2017|Kalafatis and Lemos, 2017]] ; [[#Renner--2018|Renner and Meijerink, 2018]] ). It is in these contexts that their capacity to operate simultaneously at the interface of multiple networks is particularly valuable for promoting climate action. Urban climate policy entrepreneurs can directly engage with a range of constituent groups and offer and promote climate adaptation strategies that can have direct impact on the daily lives of these residents and their interests.

<div id="17.5" class="h1-container"></div>

<span id="adaptation-success-and-maladaptation-monitoring-evaluation-and-learning"></span>