# The value of structured expert judgment to help assess climate adaptation

Alexandre K Magnan, Jia Li, Adèle Tanguy, Stéphane Hallegatte, Christophe Buffet

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## To cite this version:

Alexandre K Magnan, Jia Li, Adèle Tanguy, Stéphane Hallegatte, Christophe Buffet. The value of structured expert judgment to help assess climate adaptation. Climate Risk Management, 2025, 47, pp.100692. 10.1016/j.crm.2025.100692. hal-05310175

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Submitted on 12 Oct 2025

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# The value of structured expert judgment to help assess climate adaptation

Alexandre K. Magnan<sup>a,b,c,*</sup>, Jia Li<sup>d</sup>, Adèle Tanguy<sup>a</sup>, Stéphane Hallegatte<sup>d</sup>, Christophe Buffet<sup>e</sup>

## ARTICLE INFO

**Keywords:**

Climate change adaptation

Assessment methods

Structured expert judgment

## ABSTRACT

While climate change continues to accelerate and associated risks are expected to become more intense and complex than previously anticipated, climate adaptation policies and projects remain short-sighted and single hazard-focused, limited in scale, limited in addressing the root causes of exposure and vulnerability, and poorly monitored. Understanding whether societies are on track to adapt or on a pathway towards higher risks is essential but raises many methodological challenges. Assessment methods based on quantitative indicators have been prominent up to now, but they show limitations especially relating to the difficulty of identifying statistical data that capture the complex nature of adaptation and are relevant across contexts. This Perspective paper discusses the case of structured expert judgment methods to assess adaptation status based on a wider range of information (quantitative and qualitative, published and non-published, etc.), therefore offering complementary, alternative methods to assess progress.

Upward and accelerating trends in global warming pose an important question: are societies on track to adapt or on a pathway towards higher risks? Recent analyses conclude that the necessary shift in the scale of climate adaptation has not yet happened at the global level and that there is still little evidence of effective risk reduction in relation to implemented responses (Berrang-Ford et al., 2021; O'Neill et al., 2022; UNEP, 2023). Assessing what shapes adaptation on the ground (e.g., effective planning and action, capacities, long-term vision, finance) faces challenges relating to the difficulty of identifying indicators that both capture the multifaceted nature of adaptation and are relevant across contexts.

Acknowledging the limitations of methods solely relying on statistics and quantitative indicators, this Perspective paper calls for a wider panel of information to be integrated through the development of alternative, but complementary, assessment frameworks. In particular, it dives into the case of Structured Expert Judgment methods (SEJ). While it builds especially on our own experience with three SEJ approaches —the Global Adaptation Progress Tracker (GAP-Track), the Country Adaptation and Resilience Readiness Diagnostic (A&R Diagnostic), and the Resilience Rating System (RRS) (see Supplementary Material SM1-SM3)—its development and conclusions apply to other SEJ methods such as the IPCC multidimensional feasibility assessment developed under the Sixth Assessment Cycle to assess the feasibility of adaptation and mitigation options (Singh et al., 2020). SEJ demonstrate some added-value

<footnote><sup>a</sup> Cawthron Institute, Whakatu-Nelson, Aotearoa, New Zealand</footnote>

<footnote><sup>b</sup> UMR LIENSs 7266, La Rochelle University-CNRS, La Rochelle, France</footnote>

<footnote><sup>c</sup> World Adaptation Science Programme, United Nations Environment Programme (Secretariat), Nairobi, Kenya</footnote>

<footnote><sup>d</sup> The World Bank, Washington, DC, USA</footnote>

<footnote><sup>e</sup> French Development Agency, Paris, France</footnote>

<footnote>* Corresponding author at: Cawthron Institute, Nelson, New Zealand.</footnote>

<footnote>E-mail address: alexandre.magnan@cawthron.org.nz (A.K. Magnan).</footnote>
in that they allow assembling multiple types of information, hence supporting a more comprehensive understanding of adaptation; delivering results in relatively short periods of time; and help framing and assessing adaptation consistently across scales, stakeholders, and types of interventions (e.g. from projects to policies). SEJ methods could therefore play a decisive role in informing decision-making processes, for example the five-year cycle of the Global Stocktake (GST) aimed at tracking adaptation progress/gaps under the United Nations Framework Convention on Climate Change (UNFCCC). SEJ approaches are part of the solution to assess progress towards the Global Goal on Adaptation, and must be fully considered in the two-year work programme on indicators that was decided in Dubai in 2023 (UNFCCC, 2023a). They could also be pivotal to the revision of the 1994 IPCC Technical Guidelines for assessing climate change impacts and adaptations (Carter et al., 1994), as decided during the IPCC 60th Plenary session in January 2024.<fnref n="1" />

# 1. The need for alternative approaches to assess adaptation

Assessing climate adaptation efforts, whatever the scale considered, refers to understanding the adequacy of current strategies, instruments and interventions to match specific adaptation needs, and their effectiveness in terms of actual climate risk reduction (Gao Christiansen, 2023). This requires consideration of a broad range of information relating to both outcomes (e.g., evidence of risk reduction and resilience) and processes and capacities (e.g., policy instruments, governance, social dynamics, financing tools). This in turn raises three major framing and methodological issues.

First, adaptation goals, baselines, and targets are not always clearly defined or quantifiable, leaving open the question: progress/ gaps against what? At the international level, for example, despite recent progress towards clarifying global targets<fnref n="2" /> (by ~ 2030) under the Global Goal on Adaptation (UNFCCC, 2023b), these targets are still very qualitative and the question remains open about how to assess and track progress against them. In 2023, the Global Goal on Adaptation decision text addressed this question through the launch of a two-year work programme on developing quantified elements for those targets and indicators for measuring related progress (Art. 39). The term “indicator” is however poorly defined, so that it remains open to interpretation and often understood as quantitative metrics (Magnan, 2023), which leads to the second major issue.

Key challenges are about identifying sets of indicators and metrics to capture adaptation comprehensively (e.g. not only GDP- or income-related aspects), and that can be informed with reliable data and tracked over time for monitoring progress and gaps. While quantitative indicators are useful to measure aspects such as poverty rates or some impact-related processes (e.g. %/ha of deforestation), they are not well suited to include hard-to-quantify drivers of adaptation such as risk perceptions, community cohesion, power relations and governance mechanisms, to name a few. At a project level also, not all characteristics can be described through quantitative indicators (e.g. improved knowledge). This all points to the fact that complementary methods relying on different metric bases are needed to expand our understanding of adaptation processes and outcomes (AC, 2021; OECD-IEA, 2022; AC-LEG, 2023).

As a third issue, the fact that climate impacts and vulnerability are highly heterogeneous by location and socio-demographic strata even within the same location, raises the challenge of identifying metrics applicable across scales and systems, as well as the question: adaptation progress/gaps for who?

# 2. Benefits and limitations of structured expert judgments to assess adaptation

SEJ have a long history in practice (Morgan, 2014; Mach et al., 2017, 2019; Majszak & Jebeile, 2023). They consist of assessing a given issue, often highly complex, uncertain and presenting data gaps (e.g. nuclear safety, climate risks and adaptation levels), based on a set of metrics or questions that can be informed with a scoring system, by a group of people having knowledge or recognized expertise on the issue,<fnref n="3" /> and a wide diversity of types and sources of information. As any other method, SEJ have both benefits and limitations.

## 2.1. What structured expert judgment can do

There is a general misunderstanding about quantitative indicator-based frameworks: while they are seen as “objective” and traceable because they rely on statistics, datasets and numbers, they are not impartial. The relevance of any purely quantitative indicator depends on whether numerical information exists to inform it. Yet, not everything that shapes climate adaptation and adaptive capacity on the ground can be readily captured and aggregated quantitatively, as illustrated by states and trends in risk perceptions and governance mechanisms. This represents important biases and carries the risk of constraining the insights from overly quantitative indicator-driven assessments. What we argue here is not that such assessments are useless, but rather that they cannot be considered self-sufficient to inform policy decisions, and that complementary approaches are needed to understand climate adaptation in a more comprehensive way. SEJ methods proceed from that, with five main characteristics helping to move the above multifaceted problem forward.

<footnote n="1">¹ https://www.ipcc.ch/meeting-doc/ipcc-60/; this work is expected to be developed in conjunction with the Working Group II report to the 7th Assessment Cycle, and will be published as a separate product.</footnote>

<footnote n="2">² GGA targets are organised around themes (water, food, health, ecosystems and biodiversity, infrastructure, poverty and livelihoods, and cultural heritage; Art. 9) and policy cycle stages (risk assessment, planning, implementation, and monitoring and evaluation; Art. 10).</footnote>

<footnote n="3">³ “Experts” can be scientists, decision-makers, representatives of traditional communities and/or of the civil society, etc. Defining who is an “expert” essentially relies on the specific nature of the SEJ exercise in terms of the topic and the geographical and social context of analysis.</footnote>
(1) *Bring together multiple types of information* — The scoring system base of SEJ allows assembling information of various natures and referring to a diversity of adaptation dimensions—including processes, outputs and outcomes—, hence offering a more comprehensive framework to measure adaptation progress. SEJ draws from both quantitative and qualitative information, from sources ranging from existing databases and scientific or grey literature, to unpublished material such as indigenous knowledge and the experience and knowledge that the experts² accumulated through time. Scoring systems offer a coherent, universal metric system to describe/translate these multiple types of information, and help experts with various backgrounds to speak the same language, therefore overcoming some of the limitations of quantitative indicator-based systems.

(2) *Describe adaptation in a more complex way* — Scoring systems allow creating a common metric (e.g. 0–4 scale in GAP-Track, 1–3 scale in A&R Diagnostic, C-A + scale in RRS; see SM1, SM2 and SM3, respectively) across multiple adaptation parameters, from risk knowledge to planning, action, capacities, and evidence of risk reduction and/or development outcomes, among others. This represents a ground-breaking improvement compared to quantitative indicator-based frameworks in that this helps describe adaptation in a more comprehensive way, as well as raises awareness among a diversity of stakeholders about the importance of considering multiple adaptation dimensions *together*. This point aligns with the “system transitions” approach developed during the IPCC Sixth Assessment Cycle, aimed at moving beyond siloed approaches focusing, for example, on independent sectors.<fnref n="4" /> The GAP-Track, the A&R diagnostic and RRS promote multi-dimensional, or whole-of-society approaches. The GAP-Track applies to local geographies and is framed by six overarching questions reflecting core physical and human dimensions of adaptation (Magnan et al., 2023): knowledge about current and future climate risks, short- to medium-term planning, action, capacities, evidence towards reducing climate risks, and long-term pathway strategising. The A&R diagnostic applies at the country level and considers dimensions relating to rapid and inclusive development, adaptation of firms and people, land use and protection of critical public assets and services, people’s capacity to cope with and recover from shocks, macroeconomic and fiscal risks, and governance structure and continuous monitoring (Hallegatte et al., 2020). RRS focuses on the project level and considers a rating system for both the resilience of investments (i.e., the adequacy of investments and measures implemented against the climate vulnerability profile of the targeted geography or sector in the face of current and future climate risks) and the resilience building *through* the investments (e.g., consistency of resilience-oriented outcomes with broader development objectives and with the aim to support transformational changes transcending the immediate project boundaries and outputs) (World Bank, 2021).

(3) *Reflect the diversity of context specificities* — There is a need to inject a grounded, local perspective into more global pictures. The GAP-Track rationale, for example, states that while adaptation is widely described as primarily a local-scale issue that needs to consider the local drivers of climate risk, vulnerability and adaptation, adaptation assessments at the global scale still exclusively rely on national-level statistics. This raises the question of the relevance of national averages to properly reflect the diversity of what is happening on the ground, where most of the impacts and adaptive capacities materialise. The GAP-Track shows that getting a sense of the local perspective in global analyses is technically doable: its assessment matrix considers local case studies that are partly described with individual synthetic aggregated scores that are then aggregated to inform a global picture. The A&R diagnostic has been undertaken for 44 countries and economies which advances understanding of countries A&R readiness at the global scale while capturing country priorities and contexts (World Bank 2024a). A similar rationale applies to RRS, as describing all investments and projects using a consistent scoring system allows for an aggregated vision of resilience attributes and performance of project-based adaptation across sectors (e.g. health, water, agriculture, energy, transport, natural resources management), geographies, and project portfolios (World Bank 2024b). In the end, SEJ allow injecting a real-world perspective (local case studies, individual projects) into higher-level processes such as national policies or multilateral banks strategies, and the GST.

(4) *Enhance consistency in the way adaptation is framed* — SEJ bottom-up approaches highlight that framing and assessing adaptation in a consistent way across scales, projects and stakeholders is doable. For example, the GAP-Track that aggregates local case studies and the A&R diagnostic that describes country-level adaptation efforts, are designed to understand progress and gaps at the global level, through an aggregation exercise. The framing used to assess individual projects in the RRS can also be used to organise a cross-project perspective, for example to answer whether the investment portfolios of a given financial institution promotes action that adequately addresses climate risks to a given sector, and contributes to building broader system resilience across multiple sectors. Accordingly, SEJ can be powerful vehicles to allow various levels of adaptation decision-making and stakeholders to address the same questions, base discussions on similar framings and metrics and, ultimately, highlight adaptation priorities transcending scales, intervention types and sectors. Said differently, SEJ are suitable tools to support grounded collective decisions across scales despite apparent data gaps and varying context-specificities. Global initiatives under the UNFCCC and the IPCC could benefit from SEJ approaches to enhance the consistency and interoperability of their assessments, and further bring national institutions' and scientists' perspectives together.

(5) *Deliver results in relatively short periods of time* — While the development of new, SEJ-related databases may require time to be completed, the GAP-Track, the A&R Diagnostic and the RRS show that a lot of information is already available, but underused. The scientific literature on adaptation is also sharply growing and offers a major source of local-scale and project-based information (Berrang-Ford et al., 2021). The challenge here is essentially to gather existing but scattered information and knowledge into a more synthetic information level. Encouraging is that for the GAP-Track for example, the methodological

<footnote n="4">⁴ And though siloed approaches can make sense in the case of the assessment of adaptation efforts within a specific sector.</footnote>
development and a first application —to coastal adaptation (Magnan et al., 2023)— only took a year and a half. Similarly, it generally takes two months to complete a RRS assessment for a given project, and three-six months to conduct an A&R assessment for a given country. Noteworthy is that in the case of the World Bank Group assessments, the development of clear frameworks, rating criteria and building capacity and expertise of teams have all helped facilitate more efficient implementation of the methods and hence accelerate the learning process.

## 2.2. *Key limitations and ways to overcome them*

SEJ are not silver bullet methods to assess climate adaptation. Our experience with the GAP-Track, the A&R Diagnostic and the RRS indicates that major limitations refer to the choice of the information involved by one particular expert group to decide about scores, which raises the questions of both the “representativeness” of the outcomes (which “truth” do they reflect? Aren’t they inherently expert group-specific?) and the replicability of these outcomes over time with changing expert groups. These biases can however be minimised, if not eliminated.

First, the SEJ assessment architecture must rely on a very clear definition and precise description of each score level for each assessment question/dimension, in order to support experts when selecting the most relevant information and deciding on specific scores, as well as to enhance shared understanding of the assessment bases by the experts. This makes an expert judgment “structured”, together with laying foundations for consistency across various assessments by different expert groups, both at a given time and over time. For an example of score description, see section 7.2 of the online *Supplementary Information* of the GAP-Track paper by Magnan et al. (2023).

Second, it is critical to implement multiple iterations of assessment by individual experts, as well as organise group-level exchanges on a regular basis (see SM1-SM3) to share information on the material used by experts and their respective experience with scoring. While it is important to minimise the risk of each expert being influenced by others, it is equally important that collective discussions occur to clarify areas of disagreement —while not trying to systematically harmonise scores.

Third, as done in the GAP-Track especially, confidence levels can be associated with each score (individual and group-level) to help minimise the influence of individual and collective value judgment or cultural bias (e.g. westernised vision of risk or capacities), and hence nuance the interpretation of the final results.

## 2.3. *Towards tracking progress and gaps over time*

The extent to which SEJ help track adaptation progress/gaps over time remains a debated question. SEJ are limited in providing purely quantified information, for example on the precise number of people at risk of being affected by marine flooding. This can be seen as a weakness from the perspective of comparing outcomes across countries or projects, and conducting regular quantitative assessments to track trends in progress/gaps. To take the examples of the GAP-Track and the RRS, they neither consider a specific baseline (i.e. a given past level of adaptation or resilience) nor future benchmarks (i.e. adaptation targets under various warming scenarios), but rather take a snapshot of where a locality or a project stands today. This leaves a question open: beyond the snapshot, where does the locality or the project locate along the adaptation trend? However, we argue that implementing approaches such as the GAP-Track, the A&R Diagnostic and the RRS on a regular basis could help provide useful information on progress, and therefore be used as Monitoring, Evaluation & Learning tools to increase ambition and performance over time. For example, if a country is rated as “emerging” today (yellow or score 2 in case of A&R diagnostic) for climate risk assessment, a target could be to reach the “established” level (green or score 3) in 5 years. In parallel of increasing the ambition, the rating criteria could be refined (e.g., risk assessment of x, y, z) to understand how to move from the “emerging” to “established” levels, hence offering continued improvement of Monitoring, Evaluation and Learning.

Using SEJ for the purpose of tracking progress over time however may raise the above-mentioned concerns about changing assessment and interpretation biases due especially to changing expert groups. While associating detailed narratives to each score (see section 2.2) helps minimize this issue, there are also encouraging signs from the IPCC experience. Since 2001, expert judgments have been developed to assess the five “Reasons for Concern” that illustrate aggregated, cross-system and global-scale climate risks (Zommers et al., 2020). From one assessment to another, the expert groups are not the same but follow a similar procedure of identifying risk transitions against temperature thresholds (including justifying each transition), rely on the same material (i.e. the scientific literature), and build upon previous assessments and score justifications. So that in the end, global trends can be highlighted for the five “Reasons for Concern”. IPCC results show for example that risk level transitions occur at lower global warming levels from one report to another (O'Neill et al., 2022).

# 3. Conclusion

This Perspective paper argues that because of their different characteristics, quantitative indicator-based and structured expert judgment (SEJ) methods should be seen as complementary to inform adaptation status and trends, whatever the scale and theme considered. To date, however, SEJ remain poorly included in the panel of assessment frameworks supporting decision-making on climate adaptation, under the assumptions that they are not as objective as quantitative methods and/or are more data-constrained, and time- and resource-intensive. Science and practice however discredit such assumptions. In the context of the UNFCCC GST, this calls for a broadening of the panel of approaches to be used to assess and track adaptation at the global level, as already emphasised by some of the UNFCCC constituted bodies (AC, 2021; AC-LEG, 2023). While there is a traditional focus in the UNFCCC arena of using
national-level quantitative indicators to inform country-driven reporting documents such as the Nationally-Determined Contributions and Adaptation Communications, there is increasing recognition in this context that measuring and aggregating non-state actions is critically needed, as shown for example with the UNFCCC Race2Resilience Metrics Framework.<fnref n="5" /> In that vein, external-to-UNFCCC scientific and bi-/multi-lateral cooperation stakeholders could play a role by being vehicles for SEJ-based knowledge to be developed. One remaining open question is, however, how to establish and sustain such a multi-method approach.

### CRediT authorship contribution statement

**Alexandre K. Magnan:** Writing – review & editing, Writing – original draft, Supervision, Conceptualization. **Jia Li:** Writing – review & editing, Writing – original draft, Conceptualization. **Adèle Tanguy:** Writing – review & editing. **Stéphane Hallegatte:** Writing – review & editing. **Christophe Buffet:** Writing – review & editing.

### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Appendix A. Supplementary material

Supplementary data to this article can be found online at https://doi.org/10.1016/j.crm.2025.100692.

### Data availability

No data was used for the research described in the article.

### References

AC, 2021. Approaches to reviewing the overall progress made in achieving the global goal on adaptation — Technical paper. Adaptation Committee, UNFCCC. https://unfccc.int/sites/default/files/resource/AC_TP GlobalGoalOnAdaptation.pdf.

AC-LEG, 2023. Methodologies for reviewing the adequacy and effectiveness of adaptation and support. Reference paper. Adaptation Committee and Least Developed Countries Expert Group, UNFCCC. https://unfccc.int/documents/633175.

Berrang-Ford, L., et al., 2021. A systematic global stocktake of evidence on human adaptation to climate change. Nature Clim. Chang. 11, 989–1000. https://doi.org/10.1038/s41558-021-01170-y.

Carter, T.R., Parry, M., Harasawa, H., Nishioka, S. (Eds.), 1994. IPCC Technical Guidelines for assessing climate change impacts and adaptations. University College London (UK) and National Institute for Environmental Studies (Japan). https://www.ipcc.ch/report/ipcc-technical-guidelines-for-assessing-climate-change-impacts-and-adaptations-2/.

Gao, J., Christiansen, L., eds., 2023. Perspectives: Adequacy and Effectiveness of Adaptation in the Global Stocktake. Copenhagen: UNEP Copenhagen Climate Centre. https://unepcc.org/wp-content/uploads/2023/02/perspectives-adequacy-and-effectiveness-of-adaptation-in-the-global-stocktake-web.pdf.

Hallegatte, S., Rentschler, J., Rosenberg, J., 2020. Adaptation Principles — A guide for designing strategies for climate change adaptation and resilience. World Bank, Washington, DC. https://openknowledge.worldbank.org/server/api/core/bitstreams/339b0abf-bd8a-5ca8-9f9a-bc1dd51315df/content.

Mach, K.J., et al., 2017. Unleashing expert judgment in assessment. Glob. Environ. Chang. 44, 1–14. https://doi.org/10.1016/j.gloenvcha.2017.02.005.

Mach, K.J., et al., 2019. Climate as a risk factor for armed conflict. Nature 571, 193–197. https://doi.org/10.1038/s41586-019-1300-6.

Magnan, A.K., et al., 2023. Status of global coastal adaptation. Nature Clim. Chang. 13, 1213–1221. https://doi.org/10.1038/s41558-023-01834-x.

Magnan A.K., 2023. Robust framework for Global Goal on Adaptation needed, no time to waste. IIS SDG Knowledge Hub, online 11 October 2023. https://sdg.iisd.org/commentary/guest-articles/robust-framework-for-global-goal-on-adaptation-needed-no-time-to-waste/.

Majszak, M., Jebeile, J., 2023. Expert judgment in climate science: How it is used and how it can be justified. Stud. Hist. Phil. Sci. 100, 32–38. https://doi.org/10.1016/j.shpsa.2023.05.005.

Morgan, G., 2014. Use (and abuse) of expert elicitation in support of decision making for public policy. PNAS 111, 7176–7184. https://doi.org/10.1073/pnas.1319946111.

O'Neill, B.C. et al., 2022. Key risks across sectors and regions. In: Pörtner, H.O. (Ed.), Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, pp. 2411–2538. https://www.ipcc.ch/report/ar6/wg2/.

OECD-IEA, 2022. Adaptation in the global stocktake: options to deliver on its mandate. Climate Change Expert Group, paper No. 2022(4). https://issuu.com/oecd/publishing/docs/adaptation-in-the-gst-ccxg.

Singh, C., et al., 2020. Assessing the feasibility of adaptation options: methodological advancements and directions for climate adaptation research and practice. Clim. Chang. 162, 255–277. https://doi.org/10.1007/s10584-020-02762-x.

UNEP, 2023. The Adaptation Gap Report 2023: Underfinanced, underprepared. United National Environmental Programme, Nairobi. https://www.unep.org/resources/adaptation-gap-report-2023.

UNFCCC (2023a). Outcome of the first global stocktake. Draft decision -/CMA.5. Referenced as FCCC/PA/CMA/2023/L.17. https://unfccc.int/sites/default/files/resource/cma2023_L17_adv.pdf.

UNFCCC (2023b). Matters relating to adaptation in Draft decision -/CMA.5. Glasgow–Sharm el-Sheikh work programme on the global goal on adaptation referred to in decision 7/CMA.3. Referenced as FCCC/PA/CMA/2023/L.18. https://unfccc.int/sites/default/files/resource/cma2023_L18_adv.pdf.

<footnote n="5">⁵ https://racetozero.unfccc.int/wp-content/uploads/2021/11/202111_R2R_Metrics_framework.pdf, and https://climatechampions.unfccc.int/resilience-metrics/.</footnote>
World Bank (2021). To be completed Resilience Rating System: a methodology for building and tracking resilience to climate change. World Bank, Washington, DC. https://documents1.worldbank.org/curated/en/701011613082635276/pdf/Summary.pdf.

World Bank (2024a). Rising to the Challenge: Success Stories and Strategies for Achieving Climate Adaptation and Resilience. World Bank, Washington DC. https://openknowledge.worldbank.org/entities/publication/89bc5293-7879-40b1-a726-9782aa79c4a2.

World Bank (2024b). Resilience Rating System: A Methodology for Building and Tracking Resilience to Climate Change - Synthesizing Key Lessons from IDA19 Piloting. World Bank, Washington DC. https://openknowledge.worldbank.org/entities/publication/35040b7a-9ac1-45b8-b95c-2757dea2f2c9.

Zommers, Z., et al., 2020. Burning embers: towards more transparent and robust climate-change risk assessments. Nat. Rev. Earth Environ. 1, 516–529. https://doi.org/10.1038/s43017-020-0088-0.