Climate Adaptation Modelling
- Open Access
- 2022
- Open Access
- Book
- Editors
- Claus Kondrup
- Paola Mercogliano
- Assist. Prof. Francesco Bosello
- Jaroslav Mysiak
- Enrico Scoccimarro
- Angela Rizzo
- Rhian Ebrey
- Marleen de Ruiter
- Ad Jeuken
- Paul Watkiss
- Book Series
- Springer Climate
- Publisher
- Springer International Publishing
About this book
This open access book focuses on an issue only marginally tackled by this literature: the still existing gap between adaptation science and modelling and the possibility to effectively access and exploit the information produced by policy making at different levels, international, national and local. To do so, the book presents the proceedings of a high-level expert workshop on adaptation modelling, integrated with main results from the “Study on Adaptation Modelling” (SAM-PS) commissioned by the European Commission's Directorate-General for Climate Action (DG CLIMA) and implemented by the CMCC Foundation – Euro-Mediterranean Centre on Climate Change, in collaboration with the Institute for Environmental Studies (IVM), Deltares, and Paul Watkiss Associates (PWA).
What is the latest development in adaptation modelling? Which tools and information are available for adaptation assessment? How much are they practically usable by the policy community? How their uptake by practitioners can be improved? What are the major research gaps in adaptation modelling that needs to be covered in the next future? How? This book addresses these questions presenting the results of a study on adaptation modelling commissioned by the European Commission's Directorate-General for Climate Action (DG CLIMA) enriched by the outcomes of a high-level expert workshop on adaptation also part of the research. This book aspires to provide a useful support to academics, policy makers and practitioners in the field of adaptation to orient them in the expanding adaptation modelling assessment literature and suggest practical ways for its application.
This book, mainly addressed to academics, policy makers and practitioners in the field of adaptation, aims to providing orientation in the large and expanding methodological/quantitative literature, presenting novelties, guiding in the practical application of adaptation assessments and suggesting lines for future research. This open access book focuses on an issue only marginally tackled by this literature: the still existing gap between adaptation science and modelling and the possibility to effectively access and exploit the information produced by policy making at different levels, international, national and local. To do so, the book presents the proceedings of a high-level expert workshop on adaptation modelling, integrated with main results from the “Study on Adaptation Modelling” (SAM-PS) commissioned by the European Commission's Directorate-General for Climate Action (DG CLIMA) and implemented by the CMCC Foundation – Euro-Mediterranean Centre on Climate Change, in collaboration with the Institute for Environmental Studies (IVM), Deltares, and Paul Watkiss Associates (PWA).
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Table of Contents
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Challenges for Adaptation Modelling
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Frontmatter
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Chapter 1. Modelling the Cost and Benefits of Adaptation. A Targeted Review on Integrated Assessment Models with a Special Focus on Adaptation Modelling
- Open Access
Download PDF-versionThe chapter delves into the use of Integrated Assessment Models (IAMs) for modelling the cost and benefits of adaptation to climate change. It begins by distinguishing between cross-sectoral optimization models (POMs) and economic assessment models (PEMs) according to their objectives. The evolution of IAMs is traced through 'generations' of models, each enhancing our understanding of climate change and economic policy. The chapter then focuses on the challenges of adaptation modelling, including the complexity of sector-specific measures, uncertain benefits, and varying adaptation capabilities across regions. It provides an overview of how adaptation is incorporated into IAMs, both explicitly and implicitly, and discusses the need for more detailed and harmonized approaches to better capture the variety of adaptation possibilities. The chapter concludes with recommendations for future research, emphasizing the importance of improving adaptation modelling to better fit the heterogeneity of measures.AI Generated
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AbstractThis paper gives a targeted review on Integrated Assessment Models (IAMs) with a focus on damage functions and adaptation modelling. -
Chapter 2. Cross-Sectoral Challenges for Adaptation Modelling
- Open Access
Download PDF-versionThe chapter 'Cross-Sectoral Challenges for Adaptation Modelling' delves into the intricacies of economic modelling for climate adaptation, focusing on the GRACE model. This model, a global computable general equilibrium framework, enables the assessment of cross-sectoral and cross-regional interactions, revealing the importance of adaptation measures in mitigating climate change impacts. The chapter explores case studies in the forestry sector and heat stress adaptation, demonstrating the model's capability to integrate local insights with macroeconomic analyses. It also discusses the challenges and opportunities in bridging the gap between bottom-up and top-down approaches, emphasizing the need for interdisciplinary studies and stakeholder involvement to enhance the accuracy and consistency of climate impact assessments. By highlighting the potential for proactive adaptation and the limitations of current modelling techniques, the chapter offers a nuanced perspective on the future of climate adaptation research.AI Generated
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AbstractSocioeconomic studies on adaptation based on bottom-up approaches have been focusing mainly on local impacts of weather-related variations, thereby neglecting potential remote impacts. There is little knowledge about challenges that relate to the global and long-term character of climate change. By contrast, impact assessment studies using top-down approaches, such as multi-region, multi-sector computable general equilibrium (CGE) models, provide a consistent framework to capture potential remote impacts, which occur through cross-sectoral and cross-regional interactions. Here we present main findings of our economic impact assessments of climate change and adaption modelling. Furthermore, we discuss the challenges for incorporating adaptation measures and policies into macroeconomic models. -
Chapter 3. Climate Services Supporting Adaptation Modelling
- Open Access
Download PDF-versionThe chapter delves into the European Research and Innovation Roadmap for Climate Services, emphasizing the critical role of climate services in informing climate action. It discusses the Roadmap's definition of climate services, which includes data transformation, projections, forecasts, and other relevant information. The text also explores the three main research and innovation challenges identified by the Roadmap: enabling market growth, building the market framework, and enhancing the quality and relevance of climate services. It highlights the accomplishments and gaps in these areas, drawing from various stakeholder assessments and recommendations. The chapter concludes by stressing the need for a systematic assessment of remaining and emerging challenges to ensure that climate services effectively support climate actions as outlined in initiatives like the European Green Deal and EU Horizon Europe missions.AI Generated
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AbstractInformation and knowledge resources to support climate action (climate services) have been the subject of investments by European and national funding agencies and by the private sector in response to a growing demand and requirements to support climate-related actions. The extent to which the current state of these resources are consistent with and attributable to these investments still requires further assessment. There have been efforts to continue to inform such investments and to stimulate the climate service market. These to some degree identified remaining and emerging gaps, including those intending to support enhancing the breadth, quality and relevance of products and services, the infrastructure supporting the climate service public and private market domains and the factors enabling market growth. The criticality of realising the benefits from the availability and use of this intelligence is increasing and evolving as Europe and the rest of the world call for a transition to a climate-resilient and a low-carbon society and economy. To realise and sustain this potential, there is the need for a systematic assessment of the impacts of previous investments and of where and what type of investments could enhance the impacts in terms of informing action—exploring and identifying shared pathways to enable the development and use of climate services. -
Chapter 4. Impact-Oriented Climate Information Selection
- Open Access
Download PDF-versionThe chapter delves into the intricate process of selecting impact-oriented climate information to support adaptation to future conditions. It underscores the need for credible, relevant, and legitimate information to describe current and future climate scenarios. The text introduces two types of climate storylines: scenario storylines, which aggregate global climate change projections into stakeholder-oriented national scenarios, and risk storylines, which map climate-related shocks in a globalized world. Notably, the Dutch Climate Change Scenarios are highlighted as a case study, showcasing how complex climate projections can be condensed into four discrete narratives. The chapter also discusses the challenges and recommendations for creating credible climate information, emphasizing the role of societal practitioners and the limitations of probabilistic risk approaches in highly complex contexts. Throughout, the chapter emphasizes the importance of storylines in making uncertainty more conceivable and manageable, offering a unique perspective on climate adaptation strategies.AI Generated
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AbstractTo support climate adaptation decision-making, a picture of current and upcoming climate and socio-economic conditions is required, including an overview of intervention scenarios and their impact. In order to be actionable, this picture needs to rely on credible, relevant, and legitimate information, which implies the use of tested models and concepts, tailored to the decision context, and with transparent and understandable assumptions on boundary conditions and process representation. These criteria are challenged when the complexity of the problem is large and stakes are high. For many conditions, unforeseeable features and events with potentially large implications affect the problem at hand and contribute to the uncertainty that is not easily quantified, let alone eliminated. We explore storyline development approaches that help in selecting relevant and credible pathways and events that enrich the understanding of the risks and options at stake. We explore two categories of storylines (climate scenario storylines and climate risk storylines) by discussing use cases in which these were developed. -
Chapter 5. On the Evaluation of Climate Change Impact Models for Adaptation Decisions
- Open Access
Download PDF-versionThe chapter delves into the challenges of evaluating climate change impact models, which are crucial for informing adaptation strategies. It critiques traditional data-based validation methods, arguing that they may not adequately prepare models for future conditions. The author proposes global sensitivity analysis as a complementary approach to assess model robustness and stakeholder trust. Through case studies, the chapter demonstrates how this method can reveal the adequacy of model parameters in controlling outputs, thereby enhancing the understanding of causal links between interventions and outcomes.AI Generated
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AbstractDetailed understanding of the potential local or regional implications of climate change is required to guide decision- and policy-makers when developing adaptation strategies and designing infrastructure solutions suitable for potential future conditions. Impact models that translate potential future climate conditions into variables of interest (such as drought or flood risk) are needed to create the required causal connection between climate and impact for scenario-based analyses. Recent studies suggest that the main strategy for the validation of such models (and hence the justification for their use) still heavily relies on the comparison with historical observations. In this short paper, the author suggests that such a comparison alone is insufficient and that global sensitivity analysis provides additional possibilities for model evaluation to ensure greater transparency and better robustness of model-based analyses. Global sensitivity analysis can be used to demonstrate that the parameters defining intervention options (such as land use choices) adequately control the model output (even under potential future conditions); it can be used to understand the robustness of model outputs to input uncertainties over different projection horizons, the relevance of model assumptions, and how modelled environmental processes change with climatic boundary conditions. Such additional model evaluation would strengthen the stakeholder confidence in model projections and therefore into the adaptation strategies derived with the help of these model outputs. -
Chapter 6. Stress-Testing Adaptation Options
- Open Access
Download PDF-versionThe chapter 'Stress-Testing Adaptation Options' delves into the challenges of evaluating adaptation measures under deep uncertainty about climate variability and change. It begins by acknowledging the interconnected nature of climate change with other megatrends such as resource depletion and biodiversity loss. The authors advocate for integrated planning that avoids 'climate exceptionalism' and views adaptation through a water lens. The core of the chapter presents a robustness and resilience framework for adaptation option appraisal, emphasizing the importance of clarity about intended outcomes and understanding key vulnerabilities. The framework comprises portfolios of management options, system models, performance metrics, and appraisal criteria. The authors discuss two methods for stress-testing adaptation options: physical experiments and systems modelling. Field experiments, like the Loughborough University TEmperature Network, provide evidence-based adaptations, while systems modelling offers comprehensive, integrated risk assessment. The chapter concludes with practical recommendations for long-term monitoring and evaluation of adaptation outcomes, highlighting the need for transparency and governance structures to review evolving science.AI Generated
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AbstractThis technical contribution discusses ways of testing the performance of adaptation projects despite uncertainty about climate change. Robust decision making frameworks are recommended for evaluating project performance under a range of credible scenarios. Stress-testing options help to establish conditions under which there may be trade-offs between or even failure of project deliverables. Stress-tests may be undertaken for specified portfolios of management options, using models of the system being managed (including inputs and drivers of change), and then assessed against decision-relevant performance indicators with agreed options appraisal criteria. Field experiments and model simulations can be designed to test costs and benefits of adaptation measures. Simple rules may help to operationalize the findings of trials—such as ‘plant 1 km of trees along a headwater stream to cool summer water temperatures by 1 °C’. However, insights gained from field-based adaptation stress-testing are limited by the conditions experienced during the observation period. These may not be severe enough to represent extreme weather in the future. Model simulations overcome this constraint by applying credible climate changes within the virtual worlds of system models. Nonetheless, care must be taken to select meaningful change metrics and to represent plausible changes in boundary conditions for climate and non-climate pressures. All stress-testing should be accompanied by monitoring, evaluation and learning to benchmark benefits and confirm that expected outcomes are achieved. -
Chapter 7. Reducing and Managing Uncertainty of Adaptation Recommendations to Increase user's Uptake
- Open Access
Download PDF-versionThis chapter delves into the critical issue of uncertainty in adaptation recommendations for the agricultural sector, particularly in the context of climate change. It highlights the importance of effectively managing this uncertainty to increase the uptake of scientific recommendations by users. The authors present a multi-faceted approach that includes ensemble modeling, bias adjustment, and the use of response surfaces to understand and communicate uncertainty more effectively. A key innovation is the Ensemble Outcome Agreement (EOA) index, which provides a quantitative measure of confidence in adaptation recommendations. The chapter demonstrates the practical application of these methods through a case study on wheat adaptation in Spain, showcasing how uncertainty management can refine and enhance the reliability of adaptation strategies. By addressing the challenges posed by model errors, limited observation records, and the complex interplay of climate and agricultural systems, this chapter offers valuable insights for professionals seeking to improve the applicability of climate adaptation recommendations.AI Generated
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AbstractThere are many challenges that adaptation science faces for an effective application of the results and recommendations found. Among the most important are the estimation, management and interpretation of uncertainty. In this article, we present our approach to managing uncertainty in agricultural projections using a combination of techniques to identify uncertainties, exclude unviable outcomes, consider possible futures probabilistically, and select the most robust projections for adaptation. Through an example of the adaptation of winter wheat in Spain, we show how this approach is effective in increasing the probability of avoiding maladaptation and improving the applicability and assimilation of scientific results by users.
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Hazard, Exposure and Vulnerability Modelling
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Frontmatter
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Chapter 8. Modelling Risk Reduction Measures to Minimise Future Impacts of Storms at Coastal Areas
- Open Access
Download PDF-versionThe chapter explores the critical issue of storm impacts on coastal areas, exacerbated by climate change and increasing human occupation. It delves into the use of process-based models like XBeach and LISFLOOD to accurately simulate hazards such as erosion and flooding. The text emphasizes the importance of testing and validating disaster risk reduction (DRR) measures using these models, considering future climate scenarios. It also discusses the classification of DRR measures into exposure-reducing, pathway-obstructing, and vulnerability-reducing types, each requiring different modeling approaches. The chapter proposes a comprehensive approach to assess the effectiveness of DRR measures, including the use of an effectiveness index. It concludes by stressing the need for a more integrated use of models, climate change predictions, and DRR measures to enhance coastal management and preparedness against climate change impacts.AI Generated
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AbstractCoastal storms often cause damages and losses in occupied areas. Under climate change conditions (i.e. sea-level rise and increased frequency of extreme sea levels) and increasing human occupation, the consequences of coastal storms will be amplified if no adaptation actions are implemented. The selection of the best possible coastal management measures to reduce risks at coastal areas, considering costs, effectiveness and acceptance, will be mandatory in the future. This work presents a generic approach to model disaster risk reduction measures at coastal areas, including climate change effects. The proposed methodology is adaptable to any coastal region and can be used to test (and improve) management options at a broad number of coastal areas. It can also be used to define a timeframe for the implementation of the defined measures since not all risk reduction measures, under a climate change scenario, need to be implemented at the same time. This would help to optimise implementation costs while reducing the risk to the occupation and people. -
Chapter 9. A Model-Based Response Surface Approach for Evaluating Climate Change Risks and Adaptation Urgency
- Open Access
Download PDF-versionThe chapter introduces a model-based response surface approach designed to evaluate climate change risks and adaptation urgency, aligning with the Finnish Climate Act's mandate for regular national adaptation plans. The method involves constructing impact response surfaces (IRS) to depict the sensitivity of key indicators to climate and socioeconomic drivers, estimating the likelihood of exceeding critical impact thresholds, and simulating the effectiveness of adaptation and mitigation measures. This approach integrates stakeholder input to select relevant indicators and ensures long-term monitoring and evaluation of adaptation strategies. The chapter highlights the importance of engaging stakeholders in model co-development and emphasizes the need for improved representation of adaptation in impact models. The method is currently being tested in five sectors at a national scale in Finland, showcasing its practical application and potential for enhancing climate change risk assessments.AI Generated
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AbstractWe present a new approach to advance methods of climate change impact and adaptation assessment within a risk framework. Specifically, our research seeks to test the feasibility of applying impact models across sectors within a standard analytical framework for representing three aspects of potential relevance for policy: (i) sensitivity—examining the sensitivity of the sectors to changing climate for readily observable indicators; (ii) urgency—estimating risks of approaching or exceeding critical thresholds of impact under alternative scenarios as a basis for determining urgency of response; and (iii) response—determining the effectiveness of potential adaptation and mitigation responses. By working with observable indicators, the approach is also amenable to long-term monitoring as well as evaluation of the success of adaptation, where this too can be simulated. The approach focuses on impacts in climate-sensitive sectors, such as water resources, forestry, agriculture or human health. It involves the construction of impact response surfaces (IRSs) based on impact model simulations, using sectoral impact models that are also capable of simulating some adaptation measures. We illustrate the types of analyses to be undertaken and their potential outputs using two examples: risks of crop yield shortfall in Finland and impact risks for water management in the Vale do Gaio reservoir, Portugal. Based on previous analyses such as these, we have identified three challenges requiring special attention in this new modelling exercise: (a) ensuring the salience and credibility of the impact modelling conducted and outputs obtained, through engagement with relevant stakeholders, (b) co-exploration of the capabilities of current impact models and the need for improved representation of adaptation and (c) co-identification of critical thresholds for key impact indicators and effective representation of uncertainties. The approach is currently being tested for five sectors in Finland. -
Chapter 10. Use of Vegetation for Landslide Risk Mitigation
- Open Access
Download PDF-versionThe chapter delves into the critical issue of landslide risk management in the context of climate change, highlighting the increasing focus on Nature-Based Solutions (NBS) for mitigation. It discusses the challenges of verifying the effectiveness of NBS, particularly vegetation, in reducing landslide occurrence without causing environmental harm. The paper emphasizes the need for advanced modelling techniques to accurately predict slope stability, incorporating the complex interactions between vegetation and soil. It also explores the legislative challenges and the need for quantifiable documentation of vegetation's effects. The chapter proposes a methodological approach to include vegetation in slope stability modelling, addressing the time-dependent and species-specific parameters. It concludes with recommendations for further research and development in this crucial area of landslide risk mitigation.AI Generated
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AbstractLandslide risk management involves several activities, modelling being a required premise for most of them. Modelling of climate-induced landslides include both the analysis of the triggering process, i.e. static slope stability analysis and dynamic propagation (run-out) analysis. These analyses are vital for mapping purposes, as well as for selection of effective means to reduce the landslide risk when this exceeds a certain value of tolerance. With the prospect of increasing rainfall duration and intensity in parts of Europe, the need for further development of modelling tools is evident. In recent years, the use of Nature-Based Solutions (NBS) for mitigation of natural hazards has further demonstrated the need for developing the modelling tools. The use of vegetation as NBS is increasingly being used for erosion protection and shallow landslide mitigation. For slope stability analyses, the use of vegetation makes the modelling more complex for a number of reasons, mostly linked to the influence of vegetation on both the soil–atmosphere interaction (i.e. rainfall interception, evapotranspiration) and the soil hydro-mechanical properties. All effects that are difficult to model due to lack of knowledge and to large variations in time and space. Even though there is an increasing activity in the geotechnical environment to incorporate the effects of vegetation in the modelling for quantifying the change in slope stability (i.e. calculate slope safety factor), the status is far from being at the level of traditional landslide modelling tools. More efforts are therefore needed in the years to come to demonstrate that the use of vegetation as a viable and effective measure in landslide risk mitigation management can be verified in a more quantifiable manner. -
Chapter 11. Modelling to Evaluate Climate Resilience of Crop Rotations Under Climate Change
- Open Access
Download PDF-versionThe chapter delves into the critical role of crop rotations in enhancing climate resilience in agriculture, a sector highly vulnerable to climate change. It highlights the significance of diversified crop sequences in optimizing resource use efficiency, reducing greenhouse gas emissions, and mitigating the impacts of extreme weather events. The text also explores the complexities and uncertainties in current modelling approaches, emphasizing the need for more sophisticated models that can simulate long-term effects and interactions between multiple crops and management practices. The chapter concludes with recommendations for improving model capabilities to better assess and adapt to climate change, ensuring sustainable and resilient agricultural systems.AI Generated
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AbstractDiversification of crop rotations is considered as an option to increase the resilience of European crop production under climate change. Although crop rotation design and management has been identified as an important measure to adapt to and mitigate climate change, most studies on climate change impact or adaptation so far use single-year simulations and/or single crop assessments. Crop response to various management options within a growing season is generally taken into account by most crop models. However, if simulations neglect processes and fluxes between growing seasons and potential carry-over effects related to agronomic management, the long-term sustainability of adaptation and mitigation strategies cannot be properly evaluated. Therefore, the integrated assessment of impacts, adaptation and mitigation options under current and future climatic conditions requires a continuous long-term analysis of crop sequences to take into account carry-over effects as in real conditions. The present paper provides information on crop rotation aspects, which should be considered in modelling, presents the current state of modelling for climate impact assessment, address points of uncertainty and missing aspects in modelling and draws an outlook on potential future developments with special emphasis on crop rotations. In conclusion, crop models require suitable experimental data to parameterize additional crops, which were so far not sufficiently investigated to cope with multiple opportunities in crop rotations. -
Chapter 12. Dynamic Flood Risk Modelling in Human–Flood Systems
- Open Access
Download PDF-versionThe chapter 'Dynamic Flood Risk Modelling in Human–Flood Systems' delves into the critical importance of understanding and managing flood risk in the context of climate change. It begins by highlighting the significant global impact of floods, with over 2 billion people affected between 1998-2017, and the expected increase in risk due to climate change and urbanization. The authors emphasize the dynamic nature of flood risk, encompassing hazard, exposure, and vulnerability, and the need for integrated systems approaches to manage these components effectively. The chapter then explores empirical data-driven knowledge, including trend analyses of flood damage data and the innovative paired event concept, which allows for detailed case study analyses of risk and its drivers. It also discusses state-of-the-art modelling approaches, such as stylized models, system-of-systems models, and agent-based models, each offering unique insights into human-flood interactions. The chapter concludes with recommendations for advancing large-scale flood risk assessments by incorporating more detailed and comprehensive data and process-based modelling systems. Throughout, the chapter emphasizes the importance of understanding and quantifying the temporal dynamics of flood risk to enhance climate change adaptation and flood risk management.AI Generated
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AbstractEffective flood risk management is highly relevant for advancing climate change adaptation. It needs to be based on risk modelling that considers the dynamics, complex interactions and feedbacks in human–flood systems. In this regard, we review recent advancements in understanding, quantifying and modelling changes in risk and its drivers. A challenge for integrating human behaviour in dynamic risk assessments and modelling is the combined consideration of qualitative and quantitative data. Advancements in this respect are (1) the compilation and analysis of comprehensive qualitative and quantitative data on flood risk changes in case studies following the paired event concept; (2) the integration of qualitative and quantitative data into socio-hydrological models using Bayesian inference; and (3) the coupling of hydrological flood risk models with behaviour models in socio-hydrological modelling systems. We recommend to further develop these approaches and use more such process-based, dynamic modelling also for large-scale flood risk analyses. These approaches are increasingly feasible due to significant improvements in computational power and data science. -
Chapter 13. Climate-Fit.City: Urban Climate Data and Services
- Open Access
Download PDF-versionThe chapter 'Climate-Fit.City: Urban Climate Data and Services' delves into the innovative Climate-Fit.City service, which aims to help cities adapt to climate change by translating scientific urban climate data into practical information. It begins by outlining the vulnerability of urban areas to climate change impacts and the need for cross-sectorial adaptation processes. The methodology behind Climate-Fit.City is detailed, showcasing how it integrates climate data to address specific local challenges. The chapter also presents various sector-specific services, such as active mobility, building energy, and emergency planning, which are co-designed with urban end users. Notably, the chapter highlights the socio-economic impacts of these services, demonstrating their potential to improve public services, reduce climate-related deaths, and support evidence-based urban policies. Throughout, the chapter emphasizes the integrated nature of Climate-Fit.City, which uses a common data set to streamline multiple services and engage various urban actors, overcoming traditional silos in climate adaptation.AI Generated
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AbstractThe Climate-fit.City service (https://www.climate-fit.city) provides the best available scientific urban climate data and information for public and private end users operating in cities. Within the Climate-fit.City H2020 project, the benefits of urban climate information for end user communities was demonstrated, considering services in diverse domains (Climate and Health, Building Energy, Emergency Planning, Urban Planning, Active Mobility, Tourism and Cultural Heritage) to improve decision-making and to help end users to better address the consequences of climate change at the local scale. The socio-economic impact assessment performed in the Climate-fit.City project has demonstrated that, in all the cases, there are actual and potential added values in terms of public service effectiveness, economic impacts, policy innovation and social impacts. Further impact was also revealed in terms of raising awareness by end users, policymakers and the general public about climate change. These diversified impacts offer a variegated landscape of sub-areas and stakeholders that are touched upon by each climate service. -
Chapter 14. Weather and Climate Services to Support a Risk-Sharing Mechanism for Adaptation of the Agricultural Sector. A Theoretical Example for Drought-Prone Areas
- Open Access
Download PDF-versionThis chapter delves into the critical role of weather and climate services in facilitating risk-sharing mechanisms for the agricultural sector, particularly in adapting to climate change. It emphasizes the vulnerability of agriculture to climate-related risks and the necessity of risk-sharing to achieve Sustainable Development Goals, such as reducing hunger. The chapter introduces weather-based index insurance (WII) as a viable adaptation strategy, explaining how it redistributes risk between farmers and insurance companies. The model developed in this study simulates the dynamics of aggregate demand for WII under different forecast conditions, demonstrating that perfect forecasts can lead to steady growth in insured farmers, while imperfect forecasts may result in stable or decreasing numbers. The analysis also considers the economic impact of WII on farmers' income and the potential effects of climate change on future droughts. The chapter concludes with recommendations for implementing WII projects and the importance of considering climate change effects in future models.AI Generated
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AbstractSharing the burden of adaptation is key for the agricultural sector in developing countries. For the agricultural sector in developing countries, the losses will go from 3% under 1.5 °C scenario to 7% under 2 °C scenario (Masson-Delmotte et al. 2018). This anticipated information on possible climate change-driven challenges possesses a big load in farmers management that might ex-ante stop investing because of the negative consequences of the scenarios presented. This situation could be even worse in subsistence farming system totally dependent on the yields. Crop insurances can be a good way to overcome some of the losses. In this paper, we present weather-based insurance schemes (WII), which are based on weather index objectively determined for the specific agricultural region, and therefore the individual loss assessment, which makes insurances too expensive, is not necessary. We present the results of decisions based on perfect and imperfect weather forecasts and conclude by offering insights in the difference of decision-making if a perfect forecast might be available or not and the consequences for farmers income. -
Chapter 15. Recent Innovations in Flood Hazard Modelling Over Large Data Sparse Regions
- Open Access
Download PDF-versionThe chapter delves into the critical role of flood hazard modelling in flood risk management, emphasizing the need for accurate data in regions lacking sufficient information. It discusses the four key components of global flood models (GFM)—terrain elevation models, extreme flow estimation methods, river network definitions, and inundation simulation models—and highlights recent advancements in each. The text also addresses ongoing data needs, modelling uncertainties, and opportunities for improvement over the next decade. Notably, it reviews the impact of error removal processes in digital terrain modelling and the potential of high-resolution satellite data for more accurate flood simulations. The chapter concludes with an assessment of the current state of global flood modelling, emphasizing the challenges and variability in model accuracy.AI Generated
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AbstractThis opinion piece summarises recent progress in the development of global flood models (GFMs) in support of flood impact modelling and identifies potential areas for model improvement over the next 5–10 years. In many parts of the world, flood hazard data are absent or lack the accuracy and precision required for most practical applications, including climate change impact assessment. With the hydrological cycle expected to intensify due to climate change, better modelling of flood hazard is needed as a prerequisite to understanding how flood risk might change in the future with climate. The past decade has seen substantial advances in the modelling of flood inundation in data scarce areas along with the emergence of global flood models that could form the foundation of global impact assessments. In summarising these advances, four key themes emerge linked to topography, extreme flow estimation, river network parameterisation and numerical modelling of inundation. Progress in each of these themes will be needed to deliver the next generation of global flood hazard data.
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Sectoral Models for Impact and Adaptation Assessment
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Frontmatter
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Chapter 16. A New Modelling Approach to Adaptation-Mitigation in the Land System
- Open Access
Download PDF-versionThis chapter delves into the intricate relationship between food production systems and climate change, highlighting the significant role of land use in both adaptation and mitigation. It introduces the Land System Modular Model (LandSyMM), a cutting-edge tool that couples dynamic global vegetation models, climate system emulators, and socio-economic land-use models to simulate the complex interplay between natural systems and human activities. By representing both bottom-up adaptation dynamics and top-down mitigation policies, LandSyMM offers a unique perspective on the potential trade-offs and synergies between climate change adaptation and mitigation strategies. The chapter also discusses the limitations of current models and the need for more detailed spatial resolution to capture location-specific responses to climate change. Furthermore, it explores the potential impacts of autonomous decisions by land managers and farmers, emphasizing the importance of understanding these dynamics to inform effective policy-making. The chapter concludes by highlighting the potential of LandSyMM to address the gap in understanding climate change adaptation-mitigation and to inform policymakers on the trade-offs between different policy options.AI Generated
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AbstractClimate change, growing populations and economic shocks are adding pressure on the global agricultural system’s ability to feed the world. In addition to curbing the emissions from fossil fuel use, land-based actions are seen as essential in the effort to mitigate climate change, but these tend to reduce areas available for food production, thereby further increasing this pressure. The actors of the food system have the capacity to respond and adapt to changes in climate, and thereby reduce the negative consequences, while potentially creating additional challenges, including further greenhouse gas emissions. The food system actors may respond autonomously based on economic drivers and other factors to adapt to climate change, whereas policy measures are usually needed for mitigation actions to be implemented. Much research and policy focus has been given to land-based climate change mitigation, but far less emphasis has to date been given to the understanding of adaptation, or the interaction between adaptation and mitigation in the land use and food system. Here, we present an approach to better understand and plan these interactions through modelling. Climate change adaptation and mitigation strategies and the impacts on the global food system and socio-economic development can be simulated over long-term predictions, thanks to the new combination of multiple models into the Land System Modular Model (LandSyMM). LandSyMM takes into account the impacts in changes in climate (i.e. temperature, precipitation, atmospheric greenhouse gas concentrations) and land management on crop yields with its implications for land allocation, food security and trade. This new coupled model integrates, over fine spatial scale, the interactions between commodities consumption, land use management, vegetation and climate into a worldwide dynamic economic system. This study offers an outline description of the LandSyMM as well as the perspectives of uses for climate adaptation assessment. -
Chapter 17. Water Resource System Modelling for Climate Adaptation
- Open Access
Download PDF-versionThe chapter explores the critical role of water resource system modelling in climate adaptation, focusing on the use of simulation models to predict hydrologic, socioeconomic, and environmental consequences. It delves into decision analysis methods under uncertainty, emphasizing the importance of flexibility and robustness in water management. The text also discusses the application of these models in real-world scenarios, such as in London's water security planning, and highlights the expanding boundaries of water resource system modelling through technological advancements and institutional innovations. The chapter concludes with recommendations for the wider adoption of these approaches in the face of intensifying climate change impacts.AI Generated
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AbstractMethods and models for water resource system simulation, risk analysis, and decision analysis provide powerful tools for dealing with the challenge of climate change in the water sector. These models enable learning about the complex behaviour of river basins, testing of alternative adaptation decisions, exploration of uncertainties, and navigation of trade‐offs. This paper briefly describes recent advances in decision analysis and simulation modelling for climate adaptation in the water sector. These advances are now relatively mature and are increasingly being applied by practitioners. -
Chapter 18. A Top-Down Meets Bottom-Up Approach for Climate Change Adaptation in Water Resource Systems
- Open Access
Download PDF-versionThis chapter delves into the complex challenge of adapting water resource systems to climate change, highlighting the need for flexible and dynamic adaptation policies. It introduces a unique framework that merges top-down and bottom-up approaches, addressing the cascade of uncertainties in climate projections and incorporating local vulnerabilities and stakeholder perspectives. The framework is illustrated through case studies in the Orb and Jucar basins, demonstrating how to develop future demand scenarios and adaptation portfolios. The chapter also emphasizes the importance of equity in cost allocation and the use of hydroeconomic models for selecting cost-efficient adaptation strategies. By integrating these elements, the proposed approach offers a systematic method for supporting the selection of adaptation measures at the basin scale, ensuring economic efficiency, environmental sustainability, social acceptability, and robustness.AI Generated
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AbstractThe adaptation to the multiple facets of climate/global change challenges the conventional means of water system planning. Numerous demand and supply management options are often available, from which a portfolio of adaptation measures needs to be selected in a context of high uncertainty about future conditions. A framework is developed to integrate inputs from the two main approaches commonly used to plan for adaptation. The proposed “top–down meets bottom–up” approach provides a systematic and practical method for supporting the selection of adaptation measures at river basin level by comprehensively integrating the goals of economic efficiency, social acceptability, environmental sustainability, and adaptation robustness. The top-down approach relies on the use of a chain of models to assess the impact of global change on water resources and its adaptive management over a range of climate projections. Future demand scenarios and locally prioritized adaptation measures are identified following a bottom-up approach through a participatory process with the relevant stakeholders and experts. Cost-effective combinations of adaptation measures are then selected using a hydro-economic model at basin scale. The resulting adaptation portfolios are climate checked to define a robust program of measures based on trade-offs between adaptation costs and reliability. Valuable insights are obtained on the use of uncertain climate information for selecting robust, reliable, and resilient water management portfolios. Finally, cost allocation and equity implications are analyzed through the comparison of economically rational results (cooperative game theory) and the application of social justice principles. -
Chapter 19. Advances in Climate Adaptation Modeling of Infrastructure Networks
- Open Access
Download PDF-versionThe chapter discusses the increasing necessity of climate adaptation for infrastructure networks due to the escalating impacts of climate change. It introduces a hybrid top-down and bottom-up methodology for evaluating network vulnerabilities, risks, and adaptation strategies. This approach integrates climate hazard information with spatial network data to assess direct and indirect vulnerabilities and quantify risks. Case studies from New Zealand, Great Britain, Tanzania, Vietnam, and Argentina illustrate the methodology's practical application, demonstrating the significance of network interdependencies and the economic benefits of climate resilience investments. The chapter also highlights the development of open-source tools for risk assessment and adaptation planning, emphasizing the need for improved data collection and sharing to enhance the accuracy and effectiveness of these models.AI Generated
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AbstractAs the adverse effects of climate change are increasingly becoming unavoidable, calls for improving climate adaptation assessments have gathered interest at the global scale. Infrastructure policymakers and practitioners are now interested in understanding climate vulnerabilities and risks that capture the systemic nature of failure propagation seen across interconnected networks. This would help inform adaptation planning objectives meant to improve systemic resilience. This paper presents recent technical methodological and tool-based advances made in climate vulnerability, risk, and adaptation modeling of large-scale infrastructure networks. These methodologies adopt a bottom-up approach that focuses on creating data-rich representations of infrastructure network attributes, resource flows, and socio-economic indicators that are all used for quantifying direct and indirect risks to network assets exposed to extreme climate hazards at multiple scales. Insights from different case studies are presented to show how such methodologies have been used in practice for informing different policy needs. The paper concludes by identifying the existing gaps and future opportunities for such bottom-up infrastructure network vulnerability, risk, and adaptation assessment methodologies. -
Chapter 20. Navigating Deep Uncertainty in Complex Human–Water Systems
- Open Access
Download PDF-versionThis chapter delves into the pressing issue of water scarcity and flood risk exacerbated by climate change, population growth, and wealth distribution shifts. It argues that standard decision-making under deep uncertainty is inadequate and advocates for robustness through avoidance of unfavorable contingencies and adaptive policies that can handle unpredictable events. The research surveys recent advances in (socio-)hydrology and (institutional) economics, highlighting the need for better integration to address deep uncertainty. It proposes a modular hierarchy for multi-system ensembles to sample uncertainty and a longitudinal accounting of public transaction costs to strengthen adaptive robustness. The chapter concludes with recommendations for future scientific work, emphasizing interdisciplinary research, longitudinal data analysis, and stakeholder integration to inform robust water policies.AI Generated
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AbstractComplex human–water systems are deeply uncertain. Policymakers are not aware of all possible futures (deep uncertainty type 2), while the probability of those futures that can be identified ex-ante is typically unknown (deep uncertainty type 1). In this context, standard decision-making based on a complete probabilistic description of future conditions and optimization of expected performance is no longer appropriate; instead, priority should be given to robustness, through the identification of policies that are (i) insensitive to foreseeable changes in future conditions (classical robustness that addresses deep uncertainty type 1) and (ii) adaptive to unforeseen contingencies (adaptive robustness that addresses deep uncertainty type 2). This research surveys recent advances in (socio-)hydrology and (institutional) economics toward robust decision-making. Despite significant progress, integration among disciplines remains weak and allows only for a fractioned understanding and partial representation of uncertainty. To bridge this gap, I will argue that science needs to further underpin the development and integration of two pieces of ex-ante information: (1) a modeling hierarchy of human–water systems to assess policy performance under alternative scenarios and model settings, so as to navigate deep uncertainty type 1 and (2) a longitudinal accounting and analysis of public transaction costs to navigate deep uncertainty type 2. -
Chapter 21. Cascading Transitional Climate Risks in the Private Sector—Risks and Opportunities
- Open Access
Download PDF-versionThe chapter discusses the significance of transitional climate risks in the private sector, emphasizing the need for robust risk assessment and management. It explains the different types of transitional risks as outlined by the Task Force on Climate-Related Financial Disclosures (TCFD) and highlights the opportunities these risks present for companies. The methods for assessing GHG emissions, including Scope 1, 2, and 3 emissions, are explored in detail. The chapter also discusses the challenges and complexities of accurate GHG emission reporting and the importance of harmonized accounting methods. It concludes with recommendations for enhancing transparency and collaboration in the private sector to effectively manage transitional climate risks.AI Generated
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AbstractAdaptation to climate change poses two recognized significant types of risks to the private sector; (1) physical risks and (2) transitional risks. As markets respond to climate-related policies and shifting demands from customers and investors, opportunities as well as risks are presented. A very recent and important policy development is the European Green Deal suggesting the EU to reduce its emissions from 40 to 55% by 2030, and aiming to enable European countries to meet their Paris Agreement targets. The shift required for this transition highlights the challenges in terms of adapting business models and decision-making tools, while also providing opportunities for innovation and development in the private sector. In order to reach Paris Agreement goals, science-based targets need to be adopted to measure and manage emissions, specifically focussing on Scope 3 emissions embedded in the value chain in the private sector. Methods and guidances are considered, with the ultimate goal being a harmonized methodology to create a detailed emissions inventory and risk disclosure of a company’s operations. It is suggested that Environmentally Extended Input–Output models initially be used as a screening tool, in order to identify emission dense sectors. Process-based LCA inventory data, collected through collaboration and transparency throughout the value chain, can then be applied to increase the resolution of the decision-making tool. -
Chapter 22. Climate Change Adaptation in Insurance
- Open Access
Download PDF-versionThe chapter delves into the crucial role of insurance in climate change adaptation, highlighting the need for innovative solutions beyond traditional risk transfer. It presents three key examples where insurers can significantly contribute to adaptation: incentivizing risk reduction measures in property insurance, promoting proactive management of business interruption risks, and improving creditworthiness through adaptation measures. These practices not only help in transferring risk but also in directly reducing avoidable damages, making insurance a vital tool in building resilience against climate change. The chapter underscores the importance of integrating prevention measures into insurance products and emphasizes the need for advanced risk assessment models to support risk-based pricing. It concludes by stressing the necessity for collaboration among public and private stakeholders to ensure that risks remain insurable in the face of climate change.AI Generated
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AbstractIn this paper, we show three examples of how insurers can contribute to climate change adaptation, through insurers’ underwriting and pricing practice. In the context of climate change, there is a clear need to go beyond traditional risk transfer products. Including risk reduction measures in an insurance product has the advantage of helping to better adapt to climate change by not only transferring the risk but by directly reducing avoidable damages when an event strikes, which as a result contributes to build a more resilient society. -
Chapter 23. Climate Change Adaptation and Societal Transformation: What Are the Public Health Challenges?
- Open Access
Download PDF-versionThe chapter delves into the intricate relationship between climate change, societal transformation, and public health, highlighting the European Commission's Horizon Europe Missions as a pivotal initiative. It underscores the necessity of integrating health into climate adaptation strategies, drawing parallels with the COVID-19 pandemic's impact on behavioral change. The text introduces systems thinking approaches and behavioral change models as crucial tools for designing effective interventions. It emphasizes the importance of research in delivering evidence-based policies and outlines key strategies for adaptation, such as enhancing early warning systems and promoting sustainable lifestyles. The chapter concludes by recommending a systematic approach to intervention design, monitoring, and evaluation to achieve societal transformation and mitigate climate change's health impacts.AI Generated
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AbstractBehavioural change with societal transformation has been the key processes whereby hand and respiratory hygiene, social distancing and self-isolation that citizens across the world have been asked to implement to respond to the global COVID-19 pandemic. Is it possible to use such societal transformation approaches to change our behaviour for climate change adaptation? The European Commission (EC) funded research and innovation programmes that will be launched from 2021 will mobilise investment and EC’s wide efforts to achieve measurable and time-bound goals on issues that affect citizens’ daily lives. These programmes are based around five missions, one of which is the Mission on Adaptation to climate change including societal transformation. This will provide an opportunity to build evidence-informed assessment and design of interventions and should use a systems approach to determine and deploy the most cost-effective mix of public health behaviour change policy options according to the Nuffield Intervention Ladder and the Behaviour Change Wheel. This will maximise the likelihood of delivering societal transformation actions through ambitious but realistic research and innovation activities to help deliver planetary health programmes for Europe more widely.
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Adaptation Modelling and Policy Action
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Frontmatter
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Chapter 24. The Roles of Climate Risk Dynamics and Adaptation Limits in Adaptation Assessment
- Open Access
Download PDF-versionThe chapter delves into the critical roles of climate risk dynamics and adaptation limits in the assessment of adaptation measures. It emphasizes the need to capture the dynamic nature of risk, which is influenced by changes in climate, exposure, and vulnerability. Additionally, the chapter highlights the importance of understanding the hard and soft limits of adaptation to inform decision-making for both adaptation and mitigation. By integrating future dynamics of exposure and vulnerability, the chapter offers a more reliable basis for evaluating adaptation measures and ensuring their effective implementation.AI Generated
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AbstractThe performance of adaptation measures depends on their robustness against various possible futures, with varying climate change impacts. Such impacts are driven by both climatic as well as non-climatic drivers. Risk dynamics are then important, as the avoided risk will determine the benefits of adaptation actions. It is argued that the integration of information on changing exposure and vulnerability is needed to make projections of future climate risk more realistic. In addition, many impact and vulnerability studies have used a top-down rather a technical approach. Whether adaptation action is feasible is determined by technical and physical possibilities on the ground, as well as local capacities, governance and preference. These determine the hard and soft limits of adaptation. Therefore, it is argued that the risk metrics outputs alone are not sufficient to predict adaptation outcomes, or predict where adaptation is feasible or not; they must be placed in the local context. Several of the current climate risk products would fall short of their promise to inform adaptation decision-making on the ground. Some steps are proposed to improve adaptation modelling in order to better incorporate these aspects. -
Chapter 25. Climate Impact Chains—A Conceptual Modelling Approach for Climate Risk Assessment in the Context of Adaptation Planning
- Open Access
Download PDF-versionThe chapter introduces the 'Climate Impact Chains' framework, a conceptual modelling approach designed to assess climate risks in the context of adaptation planning. Developed by Eurac Research, this methodology has been applied in various national climate risk assessments worldwide. It involves a participatory process to identify and understand the root causes of climate risks, integrating local data and knowledge. The framework considers hazards, exposure, and vulnerability, and can be operationalized using models, indicators, and qualitative approaches. It supports early identification of adaptation demands and fosters targeted discussions on adaptation options. The chapter highlights the advantages of this approach, including its transparency, ability to compare different units, and potential for integrating a hybrid quantitative/qualitative methodology. It also discusses challenges and future research directions, emphasizing the need for value-based risk assessments and validation of hybrid methods.AI Generated
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AbstractIn this paper we present a conceptual framework for a climate risk assessment based on the so-called impact chains. The method follows a general assessment framework consistent with the IPCC AR5 concept on climate risk. This framework has been developed by Eurac Research within the context of various projects with the German Environment Agency and the German Gesellschaft für Internationale Zusammenarbeit (German Corporation for International Cooperation)—GIZ. It has been applied in almost twenty national climate risk assessments worldwide (e.g., Burundi, Bangladesh, Thailand, Vietnam, Madagascar) and has been perceived as (1) an appropriate means for risk analysis, (2) a useful tool for communication of complex cause-effect relationships in climate change impacts and risks, and (3) a great approach to identify entry points for adaptation measures. For an operational risk assessment, impact chains serve as a basis for the selection of appropriate models, indicators or guide more qualitative, expert-based assessments. -
Chapter 26. Operationalizing Climate Proofing in Decision/Policy Making
- Open Access
Download PDF-versionThe chapter discusses the integration of climate change modelling and expert knowledge into decision-making processes for climate proofing. It highlights the challenges posed by deep uncertainty and the need for robust solutions that perform well across a wide range of future scenarios. The proposed methodological framework involves six main steps, including stakeholder engagement, scenario analysis, and multi-criteria analysis combined with uncertainty analysis. The approach aims to enhance the resilience and adaptation of systems by identifying the most robust solutions, which are those that perform best under various plausible future conditions. Applications of this framework in various contexts, such as regional planning and private investments, demonstrate its practical value in supporting effective climate change adaptation strategies.AI Generated
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AbstractThe purpose of this work is to present an operational approach to include consideration of global change drivers (climatic, economic, social, etc.) in support to the design of local policies or investment plans. In both cases decision/policy makers typically have sets of plausible solutions and decisions to be taken in terms of choices among sets of plausible solutions with the best knowledge about the future dynamics of endogenous and exogenous system variables. The ambition is to identify the preferable solution(s) (in terms of technical performances, acceptance by stakeholders, cost–benefit ratio, etc.) in a medium term perspective, (e.g., 10–40 years), with current knowledge about the problem and under the effect of important sources of uncertainty (both aleatory and epistemic). Common to most decision contexts in a medium term perspective typical of both investment decisions and adaptation policies is the prevalence of economic signals in the shorter term and of climatic signals in the longer term. Models play a fundamental role in both cases, but they rarely cover the whole set of variables needed for decision making and the outcomes usually require integration of qualitative expert knowledge or simply subjective judgements. Multi-criteria analysis coupled with uncertainty analysis can contribute with methodologically sound and operational solutions. This paper elaborates on a series of recent cases with the ambition to extract common elements for a general methodological framework. -
Chapter 27. Adaptation Modelling: A JPI Climate Perspective
- Open Access
Download PDF-versionThe chapter delves into the Joint Programming Initiative 'Connecting Climate Knowledge for Europe' (JPI Climate), an EU-led effort to connect research, funders, and performers across Europe. It outlines JPI Climate's vision to facilitate a low-emission, climate-resilient society and its mission to align strategies and resources at national and European levels. Key projects such as ERA4CS and AXIS are highlighted, focusing on enhancing climate services and promoting cross-boundary research. The chapter also discusses future developments, including the establishment of Knowledge Hubs on climate neutrality and sea-level rise, and the anticipated European Facility for Climate Change. These initiatives aim to fill critical knowledge gaps and support the implementation of the Paris Agreement and the UN Sustainable Development Goals.AI Generated
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AbstractThe Joint Programming Initiative “Connecting Climate Knowledge for Europe” (JPI Climate) is a pan-European intergovernmental initiative gathering European countries to jointly coordinate climate research and fund new transnational research initiatives that provide useful climate knowledge and services for post-COP21 Climate Action. The main objective of JPI Climate is to bring together existing and developing new excellent scientific knowledge that is needed to assist practitioners to adequately transform society towards climate resilience and consequently providing integrated climate knowledge and decision support services for societal innovation. To date, JPI Climate has mobilised more than 100 million EUR in research investments and has provided access to knowledge and expertise across Europe and beyond. Some of the key projects from JPI Climate include “European Research Area for Climate Services” (ERA4CS), designed to boost the development of efficient climate services, “Assessment of Cross(X)-sectoral climate Impacts and pathways for Sustainable transformation” (AXIS), which aims to promote cross-boundary, cross-community research with the overall goal to improve coherence, integration and robustness of climate impact research and connect it to societal needs, and “Enabling Societal Transformation in the Face of Climate Change” (SOLSTICE), bringing together the Social Sciences and Humanities communities to enable and accelerate positive transformation in the face of climate change. The current development of JPI Climate Knowledge Hubs and the potential establishment of a European Facility for Climate Change (EFCC) will further establish JPI Climate as a key player in European climate change research and will actively inform and support the implementation of relevant national, European and international climate strategies and policies.
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28. Correction to: The Roles of Climate Risk Dynamics and Adaptation Limits in Adaptation Assessment
- Open Access
- Title
- Climate Adaptation Modelling
- Editors
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Claus Kondrup
Paola Mercogliano
Assist. Prof. Francesco Bosello
Jaroslav Mysiak
Enrico Scoccimarro
Angela Rizzo
Rhian Ebrey
Marleen de Ruiter
Ad Jeuken
Paul Watkiss
- Copyright Year
- 2022
- Publisher
- Springer International Publishing
- Electronic ISBN
- 978-3-030-86211-4
- Print ISBN
- 978-3-030-86210-7
- DOI
- https://doi.org/10.1007/978-3-030-86211-4
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