Editing IPCC:AR6/WGI/Chapter-12 (section)

== 12.6 Climate Change Information in Climate Services ==

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Climate services are a significantly evolving source of climate change information to support adaptation, mitigation and risk management decisions. As an evolving field, there are multiple definitions of climate services ( [[#Brasseur--2016|Brasseur and Gallardo, 2016]] ). The Global Framework for Climate Services defines a climate service as the provision of climate information to assist decision-making. The service includes appropriate engagement from users and providers, is based on scientifically credible information and expertise, has an effective access mechanism, and responds to user needs ( [[#Hewitt--2012|Hewitt et al., 2012]] ).

The AR5 WGII introduced climate services as bridging the generation and application of climate knowledge, also describing their history and concepts ( [[#Jones--2014|Jones et al., 2014]] ). Since then, this transdisciplinary field has been growing rapidly ( [[#Brasseur--2016|Brasseur and Gallardo, 2016]] ; [[#Hewitt--2020a|Hewitt et al., 2020a]] ), with the social sciences in particular pointing out knowledge requirements for co-design and co-development of climate services ( [[#Larosa--2019|Larosa and Mysiak, 2019]] ; [[#Daniels--2020|Daniels et al., 2020]] ; [[#Steynor--2020|Steynor et al., 2020]] ). Climate services differ from more research-driven vulnerability, impacts, and adaptation research in their orientation towards decision support ( [[#Stone--2005|Stone and Meinke, 2005]] ; [[#Ruane--2016|Ruane et al., 2016]] ; [[#Golding--2019|Golding et al., 2019]] ), but overlaps exist ( [[#Bruno%20Soares--2019|Bruno Soares and Buontempo, 2019]] ). Climate services are often targeted at building resilience to climate-related hazards from near real-time to seasonal and multi-decadal time horizons, to inform adaptation to climate variability and change ( [[#Hewitt--2012|Hewitt et al., 2012]] ), widely recognized as an important challenge for sustainable development and risk management ( [[#Moss--2010|Moss et al., 2010]] ; [[#Jones--2014|Jones et al., 2014]] ; [[#Vaughan--2018|Vaughan et al., 2018]] ). This section focuses largely on climate change time scales (past, present and future), which are the focus of AR6 WGI.

This section introduces the current climate services landscape, assesses climate service practices and products related to climate change information and associated challenges. Cross-Chapter Box 12.2 provides concrete examples of climate services. The section builds on the introduction to climate services in [[IPCC:Wg1:Chapter:Chapter-1#1.2.3.3|Section 1.2.3.3]] and the assessment of regional climate information construction – including storylines – discussed in Sections 10.3.4.2, 10.5.3 and Cross-Chapter Box 10.3. The ( [[IPCC:Wg1:Chapter:Atlas|Atlas]] supports the provision of climate information across WGs by providing interactive maps and further details to the material made publicly accessible for use in climate services. WGII (Chapter 17) further elaborates on climate services as enablers for climate risk management.

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=== 12.6.1 Context of Climate Services ===

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The idea of climate services is not new and has its roots in meteorology and climatology ( [[#Larosa--2019|Larosa and Mysiak, 2019]] ). It can be traced back to the late 1970s and the US National Climate Program Act of 1978 ( [[#Henderson--2016|Henderson, 2016]] ). The development of the Global Framework for Climate Services (GFCS) after the World Climate Conference-3 in Geneva brought international attention and renewed impetus to the climate services field ( [[#Hewitt--2012|Hewitt et al., 2012]] ). As a result, large investments have been made globally and regionally in the development of user-driven climate services. WMO has created Regional Climate Centres (RCCs) to facilitate climate service development by regional and national providers ( [[#Hewitt--2020a|Hewitt et al., 2020a]] ). The European Union declared its ambition to stimulate ‘the creation of a community of climate services application developers and users that matches supply and demand for climate information and prediction’, giving primacy to climate services that are user-driven and science-informed ( [[#Lourenço--2016|Lourenço et al., 2016]] ), thus embracing concepts of co-design, co-development and co-evaluation of climate services ( [[#Street--2016|Street, 2016]] ). Diverse and action-driven international initiatives allowed climate services to progressively shift from mitigation towards adaptation ( [[#Larosa--2019|Larosa and Mysiak, 2019]] ). Opportunities for the development of climate services have emerged through the 2015 Agendas (Paris Agreement, Sustainable Development Goals and Sendai Framework), Nationally Determined Contributions, National Adaptation Plans, Multilateral Development Banks and Task Force on Climate-related Financial Disclosure (see [[IPCC:Wg1:Chapter:Chapter-1#1.2.2|Section 1.2.2]] ).

Scientific advancements in climate services related to meteorology and climatology are still closely linked to essential climate variables ( [[#Larosa--2019|Larosa and Mysiak, 2019]] ) and benefit from consistently growing computational power, infrastructure and storage capacity to meet the demands of higher spatially and temporally resolved climate information ( [[#Buontempo--2020|Buontempo et al., 2020]] ). Climate services also focus on impact chains, providing decision makers with information on climate change with cross-sectoral impact assessments for adaptation ( [[#Jacob--2017|Jacob and Solman, 2017]] ). Today there is a diversity of climate services that involve interpretation, analysis, and communication of different sources of climate data, ideally combining different types of knowledge (scientific/technical, experiential, indigenous, etc.), to a targeted group of decision makers ( [[#Parris--2016|Parris et al., 2016]] ; [[#Olazabal--2018|Olazabal et al., 2018]] ; [[#Pezij--2019|Pezij et al., 2019]] ). [[#Jacobs--2020|Jacobs and Street (2020)]] argue that climate services should be expanded to also address societal challenges, such as system transformation, that include climate in the context of other risks and development challenges.

Climate services are undertaken in public and private sectors at global, regional, national, and local scales ( [[#Hewitt--2012|Hewitt et al., 2012]] , 2020b; [[#Cortekar--2020|Cortekar et al., 2020]] ). Intermediaries such as private sector consulting companies, national climate service providers, research organizations, government agencies or academic institutions provide climate services that translate aspects of climate research to the specific context of decision makers (see also [[IPCC:Wg1:Chapter:Chapter-10#10.5|Section 10.5]] ). The EU Roadmap for Climate Services ( [[#EC--2015|EC, 2015]] ; [[#Street--2016|Street, 2016]] ) focuses on developing a market for climate services comprising of both public and private domains. The GFCS, under the leadership of several United Nations Agencies, emphasizes the public domain by supporting national and regional capacity building and development of climate services mainly through National Meteorological and Hydrological Services ( [[#Hewitt--2012|Hewitt et al., 2012]] ; [[#Domingos--2016|Domingos et al., 2016]] ; [[#Sivakumar--2018|Sivakumar and Lucio, 2018]] ; [[#WMO--2018|WMO, 2018]] ). There are ongoing debates about the commercialization of climate services (M.S. [[#Brooks--2013|]] [[#Brooks--2013|Brooks, 2013]] ; [[#WMO--2015|WMO, 2015]] ; [[#Webber--2017|Webber and Donner, 2017]] ; [[#Hoa--2018|Hoa, 2018]] ; [[#Troccoli--2018|Troccoli et al., 2018]] ; [[#Bruno%20Soares--2019|Bruno Soares and Buontempo, 2019]] ; [[#Hewitt--2020a|Hewitt et al., 2020a]] ). Some argue that the commercialization of climate services is needed to meet the diverse needs of specific clients and to drive innovation in the field (M.S. [[#Brooks--2013|]] [[#Brooks--2013|Brooks, 2013]] ; [[#Troccoli--2018a|Troccoli, 2018a]] ). Others argue that if climate services shift incentives for climate science away from the public interest towards profit-seeking, this will result in less publicly accessible and transparent climate information and more private knowledge ( [[#Keele--2019|Keele, 2019]] ; [[#Tart--2020|Tart et al., 2020]] ).

Some climate adaptation planning already uses climate information as provided by the IPCC. However, depending on the decision context, this information may be too coarse, too broad or too disciplinary to directly inform decision-making at the scale where adaptation measures are taken ( [[#Howarth--2016|Howarth and Painter, 2016]] ; [[#Nissan--2019|Nissan et al., 2019]] ). Thus, while the IPCC’s role is clearly perceived as that of a reference – an authoritative starting point – there is a need for complementary information to translate the assessments at the national, local or sectoral level ( [[#Howarth--2016|Howarth and Painter, 2016]] ; [[#Kjellström--2016|Kjellström et al., 2016]] ; [[#van%20den%20Hurk--2018|van den Hurk et al., 2018]] ; [[#Vaughan--2018|Vaughan et al., 2018]] ). The AR6 Interactive [[IPCC:Wg1:Chapter:Atlas|Atlas]] (see Atlas.2) does provide a collection of observational data and global and regional climate projections. It is designed as a climate service towards the needs of WGI and beyond, to assess the state of the climate by offering data, maps and a level of expert analysis by aggregation of results to regions, scenarios and warming levels.

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=== 12.6.2 Assessment of Climate Services Practice and Products Related to Climate Change Information ===

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The climate services landscape is fast growing and very broad, as reflected in the vast diversity of practices and products that can be found in the peer-reviewed literature ( ''very high confidence'' ). However, a large part of climate services practices and products is published in ‘grey’ literature (i.e., non-peer reviewed or non-academic) by private consultancy and non-scientific civil organizations, many of which are not in the public domain. In addition, the respective climate service context of a specific stakeholder in a sector dictates what climate information is required and on what scales and in what format it is most usefully provided. The extent and type of engagement between scientists and users is another critical aspect of climate services (see Cross-Chapter Box 12.2, Figure 1, and [[IPCC:Wg1:Chapter:Chapter-10#10.5|Section 10.5]] ). The assessment here can thus only provide a partial and rather general representation of available practices and products in the evolving climate services field.

User needs and decision-making contexts are very diverse and there is no ‘one size fits all’ solution to climate services ( ''very high confidence'' ) ( [[#Hewitt--2017b|Hewitt et al., 2017b]] ; K. [[#Vincent--2018b|]] [[#Vincent--2018|Vincent et al., 2018]] b ). In many cases this requires recognizing that stakeholders make decisions through a combination of scientific information and additional values ( [[#Vanderlinden--2017|Vanderlinden et al., 2017]] ; [[#Parker--2019|Parker and Lusk, 2019]] ; see also Sections [[IPCC:Wg1:Chapter:Chapter-1#1.2.3|1.2.3]] and [[IPCC:Wg1:Chapter:Chapter-10#10.5|10.5.4]] ). The emerging climate service literature may clarify some features of climate information requested by users, for instance climatic impact-driver identification and prioritization through stakeholder engagement; the specification of thresholds for various regions/sectors; the types of metrics (magnitude/intensity, frequency, duration, timing, spatial extent) that are of primary interest; and decision support systems where informatics allow stakeholders to custom-make impact-relevant thresholds and then query databases to understand current and future characteristics ( [[#Bachmair--2016|Bachmair et al., 2016]] ; [[#Buontempo--2020|Buontempo et al., 2020]] ). However, users also ask for capacity building activities related to basic knowledge in climate change sciences and climate-related risks ( [[#De%20Bruin--2020|De Bruin et al., 2020]] ; [[#Sultan--2020|Sultan et al., 2020]] ).

Since AR5 and SROCC (Chapter 2) there has been considerable progress in understanding climate information user needs ( [[#Baztan--2017|Baztan et al., 2017]] ; [[#Golding--2017a|Golding et al., 2017a]] , b, 2019; [[#Bruno%20Soares--2018a|Bruno Soares et al., 2018a]] ; [[#Hewitt--2018|Hewitt and Golding, 2018]] ; [[#Singh--2018|Singh et al., 2018]] ; [[#Sivakumar--2018|Sivakumar and Lucio, 2018]] ; [[#Bessembinder--2019|Bessembinder et al., 2019]] ; [[#Hewitt--2020b|Hewitt et al., 2020b]] ; [[#Sultan--2020|Sultan et al., 2020]] ; Y. [[#Wang--2020|]] [[#Wang--2020|Wang et al., 2020]] ), better facilitation of user engagement ( [[#Buontempo--2014|Buontempo et al., 2014]] , 2018; [[#Buontempo--2018|Buontempo and Hewitt, 2018]] ) and an appreciation from climate scientists of the need to involve communication specialists and social scientists to support the co-design and co-development process that is fundamental to a successful climate service ( [[#Buontempo--2014|Buontempo et al., 2014]] ; [[#Gregow--2016|Gregow et al., 2016]] ; [[#Damm--2020|Damm et al., 2020]] ).

Climate services require user engagement and can take various forms in which climate information and data are delivered or communicated to the users ( ''very high confidence'' ). Different levels of user engagement exist, which can range from passive engagement to interactive group activities, to focused relationships between climate service provider and users. These result in different types of climate service products including websites, capacity building, and co-design of tailored climate indices (Cross-Chapter Box 12.2, Figure 1; [[#Hewitt--2017a|Hewitt et al., 2017a]] ). The fundamental basis for climate service development is the co-production process between climate service provider and user ( [[#Valiela--2006|Valiela, 2006]] ; [[#Briley--2015|Briley et al., 2015]] ; [[#Golding--2017a|Golding et al., 2017a]] ; K. [[#Vincent--2018a|]] [[#Vincent--2018|Vincent et al., 2018]] a ; [[#Bruno%20Soares--2019|Bruno Soares and Buontempo, 2019]] ; [[#Schipper--2019|Schipper et al., 2019]] ), which can be very resource intensive ( [[#Buontempo--2018|Buontempo et al., 2018]] ; [[#Falloon--2018|Falloon et al., 2018]] ; [[#Kolstad--2019|Kolstad et al., 2019]] ) and varies strongly from case to case ( [[#Reinecke--2015|Reinecke, 2015]] ; [[#Bremer--2019|Bremer et al., 2019]] ; [[#Goodess--2019|Goodess et al., 2019]] ; [[#Jung--2019|Jung and Schindler, 2019]] ). Climate services scholars and practitioners can better facilitate and embrace the knowledge co-production process if it is recognized as a multi-faceted phenomenon with several dimensions (e.g., constitutive, interactional, institutional, pedagogical, empowerment) ( [[#Kruk--2017|Kruk et al., 2017]] ; [[#Knaggård--2019|Knaggård et al., 2019]] ; [[#Weichselgartner--2019|Weichselgartner and Arheimer, 2019]] ).

Information moves from ‘useful’ to ‘usable’ only when users effectively incorporate this information into a decision process ( [[#Lemos--2012|Lemos et al., 2012]] ; [[#Bruno%20Soares--2016|Bruno Soares and Dessai, 2016]] ; [[#Prokopy--2017|Prokopy et al., 2017]] ; see also WGII, Chapter 17). Climate services include a range of knowledge brokerage activities such as: identifying knowledge needs; dissemination of knowledge; coordinating and networking; compiling and translating; building capacity through informed decision-making; analysing, evaluating and developing policy; and personal consultation (e.g., [[#De%20Bruin--2020|De Bruin et al., 2020]] ). When analysing four European climate services, [[#Reinecke--2015|Reinecke (2015)]] found that different climate services emphasized different knowledge brokerage activities.

There are various types of climate service providers and products related to key sectors and regions, such as those described in Sections 12.3 and 12.4 ( [[#Hewitt--2017b|Hewitt et al., 2017b]] ). For instance, studies have described sectoral climate services in support of agriculture ( [[#Falloon--2018|Falloon et al., 2018]] ; [[#Hansen--2019|Hansen et al., 2019]] ), health ( [[#Jancloes--2014|Jancloes et al., 2014]] ; [[#Lowe--2017|Lowe et al., 2017]] ), tourism ( [[#Morin--2018|Morin et al., 2018]] ; [[#Damm--2020|Damm et al., 2020]] ; [[#Matthews--2021|Matthews et al., 2021]] ), energy ( [[#Troccoli--2018b|Troccoli, 2018b]] ; [[#Goodess--2019|Goodess et al., 2019]] ; [[#Soret--2019|Soret et al., 2019]] ), disaster risk reduction ( [[#Golding--2019|Golding et al., 2019]] ; [[#Street--2019|Street et al., 2019]] ), water ( [[#van%20den%20Hurk--2016|van den Hurk et al., 2016]] ; [[#Vano--2018|Vano et al., 2018]] ), ocean and coastal ecosystems ( [[#Weisse--2015|Weisse et al., 2015]] ; [[#Le%20Cozannet--2017|Le Cozannet et al., 2017]] ), cities ( [[#Rosenzweig--2014|Rosenzweig and Solecki, 2014]] ; [[#Rosenzweig--2015|Rosenzweig et al., 2015]] ; [[#Gidhagen--2020|Gidhagen et al., 2020]] ), and cultural heritage ( [[#ICOMOS--2019|ICOMOS, 2019]] ). Many countries (including almost every country in Europe – see Atlas.8.2) have established a climate service centre, which follow different practices of user engagement and provide different products (e.g., [[#Kjellström--2016|Kjellström et al., 2016]] ; [[#Skelton--2017|Skelton et al., 2017]] ; [[#Kolstad--2019|Kolstad et al., 2019]] ). Climate services in other countries may be distributed across agencies and programmes, although these are often not centrally coordinated ( [[#Parris--2016|Parris et al., 2016]] ). One of the key pillars of the GFCS is the Climate Services Information System (CSIS), which is the principal mechanism through which information about past, present and future climate is archived, analysed, modelled, exchanged and processed for users ( [[#Hewitt--2020a|Hewitt et al., 2020a]] ). Some national governments also have organized national climate projections to be used for official planning (e.g., [[#EEA--2018|EEA, 2018]] ). A list of available national products (e.g., observational datasets) and projections can be found in the [[IPCC:Wg1:Chapter:Atlas|Atlas]] (e.g., Atlas.1.4).

Figure 12.12 maps a general categorization of practices and products that have emerged from reviewing climate service literature and user interviews ( [[#Visscher--2020|Visscher et al., 2020]] ). The categories range from very generic products or expert analysis focused particularly on climate information (climate-centric approaches) to more integrated products that include shared open-source products and capacity building as well as tailored products that treat climate information as part of a larger decision-making context (climate-inclusive approaches). Three specific examples that elaborate in more detail on specific practices and products related to those general categories are provided in Cross-Chapter Box 12.2.

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[[File:c4d63952d748298ec4b3de32e7bb1a12 IPCC_AR6_WGI_Figure_12_12.png]]

'''Figure 12.12''' '''|''' '''Illustration of different types of climate services.''' Products, for instance, can focus only on climate-related information or can be designed to integrate climate information with other decision-relevant context (vertical axis) and they can be very generic in terms of relevance to a wide range of sectors or stakeholders or customized to fit the needs of a specific sector or stakeholder (horizontal axis). Figure adapted from [[#Visscher--2020|Visscher et al. (2020)]] .

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=== 12.6.3 Challenges ===

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Climate services set new scientific challenges to physical climate research ( ''high confidence'' ). Over at least the last decade, for instance, many questions have appeared in terms of optimal estimation of changes and uncertainties from projections of model ensembles, ensemble optimization, or adjustment of model biases while preserving essential information on trends and cross-variable, time and space consistencies, downscaling information at the local scale ( [[#Benestad--2017|Benestad et al., 2017]] ; [[#Hewitt--2017b|Hewitt et al., 2017b]] ; [[#Marotzke--2017|Marotzke et al., 2017]] ; [[#Hewitt--2018|Hewitt and Lowe, 2018]] ; [[#Knutti--2019|Knutti, 2019]] ; see also [[IPCC:Wg1:Chapter:Chapter-10#10.5|Section 10.5]] ). Other challenges related to climate services are the inter-operability of data ( [[#Giuliani--2017|Giuliani et al., 2017]] ), access to data (open/FAIR Guiding principles; [[#Wilkinson--2016|Wilkinson et al., 2016]] ; [[#Georgeson--2017|Georgeson et al., 2017]] ), format of data (including moving away from percentile-based probabilistic forecasts (e.g., [[#Haines--2019|Haines, 2019]] )) and funding mechanisms ( [[#Bruno%20Soares--2019|Bruno Soares and Buontempo, 2019]] ).

Understanding and modelling of weather and climate extremes is of great relevance for climate services and is continuing to set challenges for research, such as modelling changes in impact-relevant threshold exceedance and return periods for a variety of extremes ( [[#Maraun--2015|Maraun et al., 2015]] ; [[#Sillmann--2017|Sillmann et al., 2017]] ; [[#Hewitt--2021|Hewitt et al., 2021]] ; [[#Schwingshackl--2021|Schwingshackl et al., 2021]] ; see also Chapter 11). Extreme event attribution has also been used in context of climate services ( [[#Philip--2020|Philip et al., 2020]] ) as it is of interest to some stakeholder groups ( [[#Sippel--2015|Sippel et al., 2015]] ; [[#Marjanac--2018|Marjanac and Patton, 2018]] ; [[#Jézéquel--2019|Jézéquel et al., 2019]] , 2020). The usefulness or applicability of available extreme event attribution methods ( [[IPCC:Wg1:Chapter:Chapter-11#11.2.4|Section 11.2.4]] and Cross-Working Group Box on Attribution in Chapter 1) for assessing climate-related risks remains subject to debate ( [[#Shepherd--2016|Shepherd, 2016]] ; [[#Mann--2017|Mann et al., 2017]] ; [[#Lloyd--2018|Lloyd and Oreskes, 2018]] ).

The design of climate services involves addressing certain key challenges, such as a domain challenge where users, tasks and data may be unknown; or an informational challenge related to the use and adoption of novel and complex scientific data ( [[#Christel--2018|Christel et al., 2018]] ). This includes challenges in the uptake of climate information in terms of coordinated delivery of data, information, expertise and training by public research institutes, the inclusion of climate change adaptation in public and private regulation, and uncertainties and confidence in climate projections ( [[#Cavelier--2017|Cavelier et al., 2017]] ). Quality control and quality assurance are still weak elements in the development of climate service products ( [[#Jacob--2020|Jacob, 2020]] ). Quality criteria or standards (that go beyond good practice) will have to be developed and agreed ( [[#Baldissera%20Pacchetti--2021|Baldissera Pacchetti et al., 2021]] ). These challenges reflect the dilemma that exists at the interface between the climate modelling community and climate services regarding: (i) the purposes of the models for climate research versus service development; (ii) the gap between the spatial and temporal scales of the models versus the scales needed in applications; and (iii) tailoring climate model results to real-world applications ( [[#Benestad--2017|Benestad et al., 2017]] ; [[#Hackenbruch--2017|Hackenbruch et al., 2017]] ; [[#van%20den%20Hurk--2018|van den Hurk et al., 2018]] ).

Climate services require a sustained engagement between scientists, service providers and users that is often hindered by limited resources for the co-design and co-production process ( ''high confidence'' ). There are recurring challenges related to successful climate service applications: (i) climate services are not visible and are poorly understood by ‘end users’ ( [[#Weichselgartner--2019|Weichselgartner and Arheimer, 2019]] ); (ii) data can be of unknown or poor quality, data formats can be hard to access or process, and it can be difficult to utilize data disseminated from large databases (e.g., [[IPCC:Wg1:Chapter:Chapter-1#1.5.4|Section 1.5.4]] ) without appropriate user guidance; (iii) users are unsure how to choose from available climate services to meet their needs ( [[#Rössler--2019|Rössler et al., 2019]] ); (iv) building trust between climate service users and providers ( [[#Baztan--2020|Baztan et al., 2020]] ); (v) the lack of understanding of users and their contexts by the climate science and service community ( [[#Porter--2017|Porter and Dessai, 2017]] ); (vi) the difficulty in scaling up services ( [[#Tall--2014|Tall et al., 2014]] ; [[#van%20Huysen--2018|van Huysen et al., 2018]] ); (vii) the lack of trained scientists skilled at conducting societally relevant research ( [[#Rozance--2020|Rozance et al., 2020]] ).

Challenges also arise in determining the effectiveness and added value of climate services, particularly in terms of providing quantitative estimates of economic benefits and making a business case for climate services ( [[#Bruno%20Soares--2017|Bruno Soares, 2017]] ). The market for climate services is still in its infancy ( [[#Cavelier--2017|Cavelier et al., 2017]] ; [[#Bruno%20Soares--2018b|Bruno Soares et al., 2018b]] ; [[#Tall--2018|Tall et al., 2018]] ; [[#Damm--2020|Damm et al., 2020]] ). One form of value may be determined by a particular user community’s willingness to pay ( [[#Acquah--2011|Acquah and Onumah, 2011]] ; [[#Ouédraogo--2018|Ouédraogo et al., 2018]] ; [[#Antwi-Agyei--2021|Antwi-Agyei et al., 2021]] ), which however cannot reflect the value of climate services as a public good and for society as a whole ( [[#Hewitt--2012|Hewitt et al., 2012]] ). Literature is only recently emerging on the socio-economic benefits of weather and climate services ( [[#Vaughan--2019|Vaughan et al., 2019]] ). Early studies and guidelines from the WMO focus on cost–benefit ratios ( [[#Perrels--2013|Perrels et al., 2013]] ; [[#WMO--2015|WMO, 2015]] ). Issues related to demand-driven versus supply-driven climate services ( [[#Lourenço--2016|Lourenço et al., 2016]] ; [[#Street--2016|Street, 2016]] ; [[#Daniels--2020|Daniels et al., 2020]] ), public versus private climate services ( [[#Hewitt--2020a|Hewitt et al., 2020a]] ) and business models for climate services ( [[#Hoa--2018|Hoa, 2018]] ) have been raised. A large share of climate services documented in peer-reviewed literature is currently provided in non-market frameworks (e.g., public service obligations and research and development grants) ( [[#Hoa--2018|Hoa, 2018]] ; [[#Kolstad--2019|Kolstad et al., 2019]] ; [[#Cortekar--2020|Cortekar et al., 2020]] ).

Other challenges related to governance and dealing with complex systems are sometimes acknowledged but less well described in the climate services domain ( [[#Hewitt--2020a|Hewitt et al., 2020a]] ). Importantly, decision contexts are strongly rooted in past practice (which often does not even make optimal use of past climate information), stakeholder experience, and history. Even important emerging concepts of co-production, entry points, and champions do not always fall naturally into these realities without significant effort. The social sciences have an important role in helping understand and tackle these challenges ( [[#Bruno%20Soares--2019|Bruno Soares and Buontempo, 2019]] ).

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Cross-Chapter Box 12.2 | Climate Services and Climate Change Information

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'''Contributing Authors:''' Suraje Dessai (United Kingdom/Portugal), Jana Sillmann (Norway/Germany), Carlo Buontempo (United Kingdom/Italy), Cecilia Conde (Mexico), Aida Diongue-Niang (Senegal), Francisco J. Doblas-Reyes (Spain), Christopher Jack (South Africa), Richard Jones (United Kingdom), Benjamin Lamptey (Niger/Ghana), Xianfu Lu (United Kingdom/China), Douglas Maraun (Austria/Germany), Ben Orlove (United States of America), Roshanka Ranasinghe (Netherlands/Sri Lanka/Australia), Alex C. Ruane (United States of America), Anna Steynor (South Africa), Bart van den Hurk (Netherlands), Robert Vautard (France)

Climate services involve the provision of climate information in such a way as to assist decision-making. The service needs to have appropriate engagement from users and providers; be based on scientifically credible information and expertise; have an effective access mechanism; and meet the users’ needs ( [[#Hewitt--2012|Hewitt et al., 2012]] ). Predominantly, climate services are targeted at informing and enabling risk management in adaptation to climate variability and change ( [[#Jones--2014|Jones et al., 2014]] ; [[#Vaughan--2018|Vaughan et al., 2018]] ). [[IPCC:Wg1:Chapter:Chapter-1|Chapter 1]] introduces climate services in a broader context of interaction between science and society, including how climate information can be tailored and co-produced for greatest utility in specific contexts. [[IPCC:Wg1:Chapter:Chapter-10|Chapter 10]] assesses the key foundations for the generation of climate information about regional climate change. Chapters 11, 12 and [[IPCC:Wg1:Chapter:Atlas|Atlas]] comprehensively assess regional climate change information. The Interactive [[IPCC:Wg1:Chapter:Atlas|Atlas]] gives access to various repositories of quantitative climate information. In WGII, Chapter 17 assesses climate services in the context of climate risk management.

Cross-Chapter Box 12.2

Climate service contexts are diverse and complex. They can be characterized using different factors such as sectors, regions, purposes, time horizons, data sources, level of processing of climate data, background knowledge, type of climate service providers, as well as the nature of the interactions between providers, users and other stakeholders ( [[#Bessembinder--2019|Bessembinder et al., 2019]] ). To illustrate the wide diversity of climate change information in climate services, a useful categorization is by user –provider engagement of climate services (Cross-Chapter Box 12.2, Figure 1). One broad category includes ‘websites and web tools’ which generally focuses on data and information provision ( [[#Hewitson--2017|Hewitson et al., 2017]] ). Websites are generally able to reach many users, but engagement is passive through one-way transfer of information. The second broad category involves ‘interactive group activities’, such as workshops, meetings and interactive forums, which create a stronger dialogue between climate service providers and decision makers. Multi-way communication and regular interaction enable building of trust, co-learning and co-production of products and services. The third broad category involves ‘focused relationships’ which are tailored, targeted and address very specific needs of the user. Effective engagement arises from an iterative process between the provider and user to ensure the user’s needs are being addressed appropriately ( [[#Hewitt--2017a|Hewitt et al., 2017a]] ).

The diversity of climate services practices and products is illustrated here using three case studies each representing one of the broad categories of user –provider engagement (Cross-Chapter Box 12.2, Figure 1).

[[File:9b57b8c914bd9465a29be2fb3e0f3af2 IPCC_AR6_WGI_CCBox_12_2_Figure_1.png]]

'''Cross-Chapter Box 12.2, Figu'''

'''re 1 |'''

'''Schematic of three broad categories of engagement between users and providers of climate services.''' Figure adapted from [[#Hewitt--2017a|Hewitt et al. (2017a)]] .
'''Case study 1: Websites and web tools'''
The Copernicus Climate Change Service (C3S) provides free and open access to climate data, tools and information through a website. It also includes demonstration projects that show how C3S data can be used in practice through case studies, training sessions and workshops ( [[#Thepaut--2018|Thepaut et al., 2018]] ). A large audience of the service is composed of intermediate users, loosely defined as the community of operators in one of the intermediate steps between the primary producers of climate data and the ultimate beneficiaries.

To address this audience, the strategy of C3S is to provide free and open access climate data and tools such as historical observations (both satellite and ground-based), climate data records relevant for a number of Essential Climate Variables ( [[#Bojinski--2014|Bojinski et al., 2014]] ), global and regional reanalyses, climate monitoring bulletins, seasonal predictions, as well as both global (a selection of simulations from the Coupled Model Intercomparison Project, CMIP; [[#Taylor--2012|Taylor et al., 2012]] ; [[#Eyring--2016|Eyring et al., 2016]] ) and regional climate projections from the Coordinated Regional Downscaling Experiment (Euro- and Med-CORDEX; [[#Jacob--2014|Jacob et al., 2014]] ; [[#Ruti--2016|Ruti et al., 2016]] ). A number of indices for various sectors can be calculated through cloud-based tools. For instance, in order to address the specific needs of key sectoral users, climate impact indicators for common variables such as ‘heating degree days’ can be calculated by the users and made available to others ( [[#Buontempo--2020|Buontempo et al., 2020]] ). All this material is quality controlled following a standardized, transparent and traceable framework.

C3S also facilitates the tailoring process, by providing a series of working open-source, cloud-based demonstrators which show how climate data can be transformed into actionable information to meet specific user requirements. This tailoring process covers the chain between the definition of key indicators all the way to the user interface. The definition and production of C3S products involve scientists that produced and assessed the data. A variety of potential users are involved in the definition of indicators and other products.

Through its quality assurance process and demonstrators, C3S provides a basic evaluation of all climate data; it provides access, and it encourages the users to develop their own case-specific analysis within the C3S infrastructure. Trustworthiness and relevance of such an analysis are substantially strengthened through a distillation process, co-designed by the user and data provider, and drawing upon multiple lines of evidence and process-based evaluation of model fitness ( [[IPCC:Wg1:Chapter:Chapter-10#10.5|Section 10.5]] ).

'''Case study 2: Interactive group activities'''
Science-application engagement is extremely challenging, especially in critically important but complex contexts such as rapidly growing cities in developing nations ( [[#Culwick--2017|Culwick and Patel, 2017]] ). The publicly funded Future Resilience for African CiTies And Lands (FRACTAL) project was conceived and designed in response to extensive and strong evidence and experience that useful and useable climate services require strong mutual relationships across the science-application interface that can be built using supportive processes and structures ( [[#Taylor--2017|]] [[#Taylor--2017|A. Taylor et al., 2017]] ).

Informed by this understanding, FRACTAL was grounded in a very reflexive and context-guided approach with city decision-making at its core ( [[#Taylor--2017|]] [[#Taylor--2017|A. Taylor et al., 2017]] ). Representatives from selected southern African cities were included in the proposal design and, throughout the project, a core principle was to allow the city partners to lead and guide the process.

Two important elements were deployed in FRACTAL: ‘embedded researchers’ and ‘learning labs’. Embedded researchers were seconded into the municipality and served as the essential connection for the learning process within each city ( [[#Steynor--2020|Steynor et al., 2020]] ). Learning labs ( [[#Arrighi--2016|Arrighi et al., 2016]] ) were interactive structures in which participants from academia, local city government and councils, state-owned enterprises, communities and community development institutions, and others could interact. Embedded researchers and learning labs were the backbone of ongoing learning processes within each city and resulted in more focused small-group dialogues, capacity development and training processes, and within-city research and engagement activities. Each learning lab focused initially on identifying ‘burning issues’ without a requirement that they involve strong climate linkages. However, with the overarching focus on resilience, discussions evolved in that direction and the burning issues identified often centred around water in peri-urban areas, for example in Windhoek, Namibia ( [[#Scott--2018|Scott et al., 2018]] ).

The learning labs also introduced and developed the concept of Climate Risk Narratives (CRNs) as a process and product to generate and integrate climate and socio-economic information relevant to adaptation and resilience (see Cross-Chapter Box 12.2, Figure 2, and Box 10.2 on storylines) ( [[#Jack--2020|Jack et al., 2020]] ). The first CRNs were informed primarily by climate evidence, but also included some tentative socio-economic impact elements gleaned from literature and other studies. Their content was intentionally provocative and designed to promote debate and discussion, and subsequent iteration. Many participants noted that this was the first time that various important conversations across governance structures and disciplinary areas had occurred around what climate change may actually mean. This demonstrates the engagement value of CRNs as a key element in an iterative co-production process to ensure important details are included correctly, such as the local context, terms and names as well as providing reality checks on the impacts and societal responses ( [[#Jack--2020|Jack et al., 2020]] ).

Cross-Chapter Box 12.2

This case study emphasizes the positive contributions of the fit, tailoring and contextualization of climate information with respect to the specific decision-making needs of particular users ( [[IPCC:Wg1:Chapter:Chapter-10#10.5|Section 10.5]] ; AR6 WGII Section 17.4.4.2.2), the importance of participatory planning for risk management in urban areas (AR6 WGII Sections 6.3.3.3 and 6.4.2) and the importance of networks and organizations which link researchers, policymakers and end-users to promote adaptation in African cities (AR6 WGII Box 9.4). Upscaling this type of interactive activity to cater for the large number of user demands remains a challenge.

[[File:2635486ac58ac406ff5417aa417692de IPCC_AR6_WGI_CCBox_12_2_Figure_2.png]]

'''Cross-Chapter Box 12.2, Figure 2'''

'''|'''

'''Climate Risk Narrative infographic developed through the FRACTAL Windhoek Learning Lab process.''' Figure adapted from [[#Jack--2020|Jack et al. (2020)]] .
'''Case study 3: Focused relationships'''
This broad category involves one-to-one engagement between a provider and a user with very specific needs. One such user is the Asian Development Bank (ADB), which has committed to making all its investments climate resilient by implementing a climate risk management framework ( [[#ADB--2014|ADB, 2014]] , 2018; [[#Lu--2019|Lu, 2019]] ). The climate risk management framework mandates all climate-sensitive investment projects undertake a climate risk and adaptation assessment, to identify material risks of a changing climate to the proposed project and potential adaptive measures to be incorporated into project design, implementation, maintenance and/or monitoring. Typically, loan project processing teams procure consulting services for a bespoke climate risk and adaptation assessment (CRA) for a specific project. The user –provider engagement is highly targeted and goal-oriented. An example of such a focused user –provider engagement is the CRA carried out as part of an investment project in Vietnam, the Water Efficiency Improvement in Drought-Affected Provinces (WEIDAP) project.

In the wake of the El Niño-induced 2015–2016 severe drought, which caused major damage to agricultural land in the Central Highlands of Vietnam, the WEIDAP project was initiated to improve water productivity of irrigated agriculture. Proposed project interventions include a package of both ‘soft’ (e.g., policy, institutional and capacity building, on-farm water efficiency practices) and ‘hard’ (modernized irrigation schemes) activities. To ensure that the project delivers expected benefits under a changing climate, consultants were recruited to carry out a detailed CRA, working as part of the overall project processing team. Through extensive consultations with the rest of the project team and review of literature including relevant climate projections, the CRA consultants chose to construct three broad climate scenarios for the 2050s (a time frame appropriate for the lifetime of the irrigation schemes being proposed under the project): a warm-and-wet, a hot-and-wet, and a hotter future. Outputs from a selection of CMIP5 models were analysed under these three scenarios, to derive changes in temperature, rainfall and potential evapotranspiration, which in turn were used as inputs to hydrological, crop and agro-economics models to assess the impacts of climate change on the overall project performance. Table 1 presents the summary of the key parameters under the three scenarios. Recommendations from the CRA included (largely minor) refinements and additional activities for drought planning, detailed engineering design of the relevant project components (such as access roads, river crossings and foundations), and support for poorer farmers who may not be able to afford access to water and climate-resilient technologies.

This case study illustrates that climate information distillation including a sustained iterative engagement between climate information users, producers and translators can improve the quality of the information and the decision-making ( [[IPCC:Wg1:Chapter:Chapter-10#10.5|Section 10.5]] ; WGII Section 17.4.4.2.2).

'''Cross-Chapter Box 12.2, Table'''

'''1 |'''

'''Summary of annual province-level changes in temperature, precipitation and evapotranspiration under the three broad scenarios in southern Vietnam.''' Scenario 1: warm-and-wet; Scenario 2: hot-and-wet; Scenario 3: hotter. Source: Table 3 in [[#ADB--2020|ADB (2020)]] .
{| class="wikitable"
|-
| rowspan="3"| '''Item'''

| colspan="15"| '''Province and Scenario Number'''

|-
| colspan="3"| '''B''' '''ì''' '''nh Thu''' '''â''' '''n'''

| colspan="3"| '''Ð''' '''ă''' '''´''' '''k L''' '''ă''' '''´''' '''k'''

| colspan="3"| '''Ð''' '''ă''' '''´''' '''k N''' '''ô''' '''ng'''

| colspan="3"| '''Khánh H''' '''ò''' '''a'''

| colspan="3"| '''Ninh Thu''' â '''n'''

|-
| '''1'''

| '''2'''

| '''3'''

| '''1'''

| '''2'''

| '''3'''

| '''1'''

| '''2'''

| '''3'''

| '''1'''

| '''2'''

| '''3'''

| '''1'''

| '''2'''

| '''3'''

|-
| '''ΔT (°C)'''

| 1.1

| 1.8

| 2.6

| 1.1

| 1.5

| 2.0

| 1.2

| 2.1

| 2.7

| 1.1

| 1.8

| 2.6

| 1.1

| 1.5

| 2.6

|-
| '''ΔP (%)'''

| 28

| –12

| 4

| 8

| 17

| –8

| 8

| –8

| 7

| 3

| –10

| 7

| 27

| 1

| 5

|-
| '''ΔPET (%)'''

| 3

| 6

| 8

| 4

| 5

| 7

| 4

| 7

| 9

| 3

| 6

| 8

| 3

| 5

| 8

|}

ΔT = change in temperature; ΔP = change in precipitation; ΔPET = change in potential evapotranspiration.

Note: Colour scale indicates significance of changes for the water balance.

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