This session brings together researchers and practitioners working across climate science, impacts and risk assessment, and social sciences to advance the development and application of climate risk storylines and scenarios. We welcome contributions that span the full chain from physical climate modelling and event attribution to the co-production of narratives with stakeholders, and the use of scenarios in real-world decision contexts.
We invite abstracts that address, among others:
a) Physical and impact-based climate storylines, including past events, attribution studies, and plausible future extremes
b) Development and use of socioeconomic scenarios, including qualitative narratives and their quantification
c) Methods for integrating quantitative and qualitative knowledge, and linking climate and non-climate risk drivers
d) Conceptual models and frameworks for combining hazards, exposure, vulnerability and response
e) Applications of storylines and scenarios for stress testing, impact and risk assessment, early warning systems, adaptation planning and policy support
f) Participatory and co-production approaches that enhance relevance, robustness and uptake for decision-making
By bridging physical modelling, socioeconomic pathways and stakeholder-driven approaches, this session aims to strengthen the role of storylines and scenarios as actionable tools for managing climate risks in a rapidly changing world.
Orals: Mon, 4 May, 14:00–15:45 | Room 2.24
Climate change is increasingly encountered through extreme events - floods, droughts, heatwaves, storms - that appear as brute physical facts. Yet such events only become intelligible through stories. They are narrated as crises, risks, injustices, or failures of preparedness; they are woven into accounts of resilience, responsibility, and adaptation. These storylines do not merely describe climate change; they actively construct what it is, who it concerns, and what can be done. This article develops a social-scientific framework for analysing and co-creating climate storylines, arguing that they are foundational to how climate change is understood, governed, and lived.
The article conceptualises storylines as social practices through which shared realities are produced. Narratives are not neutral representations; they organise meaning, shape identities, and delimit horizons of action. In the context of climate change, storylines stabilise interpretations of slow onset and extreme climate events and render others marginal or unthinkable. They distribute agency and responsibility and produce subjects such as the “resilient community” or the “adaptive citizen.”
The article reviews dominant storylines in climate science - such as resilience, adaptation, crisis, justice, and risk management - and shows how they organise climate change as a particular kind of problem. Despite their growing prominence, storylines are largely treated as neutral, factual devices for organising physical processes under uncertainty. This leaves a critical gap: storylines are not only representations of events, but narrative constructions that actively produce meaning, social roles, and political horizons. By bringing social-science perspectives to the analysis of climate science storylines, this article makes these constitutive and political dimensions explicit.
Building on recent work in climate science, the article treats storylines as a bridge between physical processes and social meaning. Following Shepherd et al. (2017), a storyline is understood as “a physically self-consistent unfolding of past events, or of plausible future events or pathways,” for which no a priori probability is assigned. Rather than predicting what will happen, storylines trace how particular constellations of drivers, events, and impacts might plausibly unfold. This event-oriented mode of representation aligns scientific knowledge with how people experience risk and imagine futures. Reframed as social practices, storylines show how identical climatic “facts” can be woven into divergent realities and political projects.
Building on this synthesis, the article proposes a typology of four ideal-typical climate storylines: (1) the managerial-risk storyline, which frames extremes as calculable hazards; (2) the resilience storyline, which emphasises adaptation and responsibilities subjects; (3) the crisis-emergency storyline, which constructs climate change as rupture; and (4) the justice-political storyline, which situates extremes within histories of inequality and structural power. These storylines may rely on the same observable facts, yet they produce distinct understandings of what is happening, who is responsible, and how society should respond.
Rather than offering a definitive classification, the typology functions as an analytical heuristic. It demonstrates how climate change is not a single object awaiting interpretation, but a multiplicity produced through narrative, opening space for alternative imaginaries and political possibilities in a changing world.
How to cite: Maybom, C. and Boyd, E.: A social science typology of climate change storylines , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21680, https://doi.org/10.5194/egusphere-egu26-21680, 2026.
The increasing complexity of the risk landscape, exacerbated by social, environmental, and climate changes, makes understanding, managing, and communicating multi- and systemic risk events crucial. In recent years, the concept of storylines has gained attention in academic and policy circles as a way to communicate and understand complex risk scenarios. While the existing literature highlights the potential of storylines for framing and contextualising risks, systemic- and multi-risk considerations remain fragmented and often overlooked. Addressing this complexity requires innovative frameworks that integrate diverse perspectives and account for the dynamic and interdependent nature of risks.
This study presents two storylines developed for the Veneto Region under the EU-funded MYRIAD-EU project with a threefold objective: facilitate discussion with stakeholders, raise awareness on multi- and systemic risks, and identify key current/future multi- and systemic risks, to further support the development of forward-looking disaster risk management (DRM) pathways towards greater resilience.
The storylines, co-created with key local stakeholders through a participatory process, includes the region’s main characteristics, geography and climate, socio-economic context, risk profile, the analysis of a baseline past event, and a description of plausible future scenarios and expected key risks. Qualitative analysis of interviews and focus group discussions with core stakeholders was conducted to identify a benchmark event with multi- and systemic risk characteristics that had a significant impact on the region in recent years. The Vaia storm of 27-30 October 2018, the largest storm ever recorded in Italy, which also impacted Austria, France, and Switzerland, was chosen. This storm has been recognised as an extreme hydrometeorological event characterized by multiple hazards with cascading effects that caused severe cross-sectoral impacts and whose frequency and intensity will likely be influenced by climate change. Information shared by stakeholders, supplemented by results from a scientific literature review contributed to the characterization of the event and its impact chains across sectors. Counterfactuals to develop the storylines and identify future plausible scenarios were chosen based on the discussion with stakeholders, scientific literature, quantitative analyses, studies and policy documents, including the Regional Strategy for Climate Change Adaptation (SRACC). The final output of the study was visualised using ArcGIS StoryMap web-based tool.
This study illustrates how the integration of quantitative and qualitative analyses can be effectively employed to co-develop risk storylines, offering a valuable approach to both scientific inquiry and policy engagement.
How to cite: Casartelli, V., Salpina, D., Marengo, A., Ferrario, D. M., Mysiak, J., and Torresan, S.: Back to the future: leveraging event-based participatory storylines for mixed-method risk assessments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12075, https://doi.org/10.5194/egusphere-egu26-12075, 2026.
In early October 2024, Atlantic tropical cyclone Kirk followed an unusual trajectory. Rather than moving westward with the trade winds, it turned northward and then eastward toward Europe. Kirk made landfall in France, producing strong wind gusts, heavy rainfall, localized flooding, widespread treefall, and multiple fatalities.
This presentation
We assess the potential consequences had Kirk made landfall in the Netherlands instead of France. Using a modelling-to-impact framework, ECMWF forecasts are dynamically downscaled with the convection-permitting HCLIM43-AROME model at 2.5 km resolution. Model output is analysed using relevant impact indicators and translated into damage cost estimates. Sensitivity experiments further show that a Netherlands-impacting Kirk responds strongly to sea-surface temperature (SST) conditions: warmer SSTs substantially intensify the storm and dramatically increase estimated damages.
Why it matters
Climate change preparedness commonly relies on CMIP6 GCM projections, combined with some form of regional downscaling (e.g. CORDEX). However, most GCMs do not adequately resolve storms like Kirk, and their projected changes are therefore largely absent. However examples like Kirk (2024) show that former tropical cyclones can already reach the Netherlands in today's climate. Combined with other recent European cases (e.g. Ophelia in 2017) and high-resolution future projections suggesting an increased likelihood of early-autumn landfalls, this highlights the need to consider such plausible but underrepresented extremes in preparedness planning.
Plausible
One week prior to landfall, ECMWF ensemble forecasts showed large uncertainty in Kirk’s track, with potential landfall locations ranging from Portugal to Ireland. Forecast intensities also varied widely. For several days, a scenario in which Kirk passed through the English Channel and impacted the Dutch coast remained plausible. Although this did not occur, examining such a scenario provides valuable insight into societal preparedness for rare but credible, potentially climate-fueled extremes. We argue that preparing for such events, even if not yet realized, is both relevant and necessary.
Dutch National Climate Scenarios
The Netherlands has a long-standing tradition of developing national climate scenarios, most recently updated in October 2023. These scenarios provide change factors, gridded fields, and time series used by stakeholders to stress-test applications across sectors. They are based on CMIP6 projections and derived through resampling of EC-Earth/RACMO GCM/RCM simulations. Due to resolution limitations, however, storms like Kirk are not well represented and are therefore largely absent from these scenarios. The present analysis of a Netherlands-impacting Kirk forms part of a KNMI report published in December 2025, which presents nine storyline cases of plausible extreme events in the current climate.
How to cite: de Vries, H. and Fonseca Cerda, M. D. S.: Are our societies prepared for today's climate-fueled extremes? A case study of hurricane Kirk (2025), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12976, https://doi.org/10.5194/egusphere-egu26-12976, 2026.
Climate scenarios for impact assessment and policy targets are generally drawn from Integrated Assessment Model databases, which explore diverse but ad-hoc futures, making it difficult to inform the effectiveness of individual policy measures. Pre-defined climate target objectives also tend to cluster scenarios around common thresholds, such as 1.5 or 2 degrees, failing to sample the full space of Paris-compatible climate futures. Finally, some scenario exercises provide only near-term futures, making them difficult to reconcile with end-of-century warming targets.
To address these issues, we present FLEX (Framework for Long-term EXtensions), a toolkit that allows scenarios to be indefinitely extended by defining a concise list of properties (e.g. net-zero timing, methane policy and carbon removal assumptions), using storylines to generate self-consistent, harmonised emissions trajectories. We show how FLEX can be used to explore trade-offs and uncertainties in near-term policy outcomes, varying net-zero timing, non-CO2 contributions, and CDR deployment.
We have used FLEX to define the extensions for CMIP7's ScenarioMIP experiment, to explore long-term (post-2100) policy-relevant questions where IAM-based projections are unavailable. The design explores long-term commitments to policies and provides boundary conditions for slow-responding processes such as ice-sheets and permafrost loss. FLEX is used to produce extensions that continue the narratives defined in each of the ScenarioMIP members, exploring a range of climate stabilisation levels, reversibility, and tipping point risks. We provide FLEX as open-source software compatible with existing scenario processing tools.
How to cite: Mittal, S., Sanderson, B., Sandstad, M., Kikstra, J., Nicholls, Z., and Zecchetto, M.: Introducing FLEX: a simplified framework for future scenario exploration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7062, https://doi.org/10.5194/egusphere-egu26-7062, 2026.
The development of scenarios is an essential part of many natural hazard risk analyses and assessments. Scenarios help to understand and quantify risks, identify the range of plausible consequences, and examine emerging future developments. Scenarios support informed decision-making, and the requirements to them depend on the type of decisions one wants to support. One example is the quantification of risks for the purpose of prioritizing investments, where the interest lies mainly within the expected overall losses and not the spatial distribution of the damages. By contrast, the spatial and temporal distribution of expected damage is of vital importance for tasks such as stress testing response capacities or risk mapping for spatial planning and response planning.
In data-scarce environments, where hazard and damage-forming processes are not well understood or documented, it is challenging to develop and validate models for comprehensive hazard and risk analysis. In practice, risk estimates are frequently based on a few plausible scenarios; however, it has been shown that the risk can be significantly underestimated or overestimated depending on the number and choice of scenarios that are considered (Ward et al., 2011). With the aim of developing recommendations on robust scenario selection, we structure common decision-making problems according to the demands they place on scenario selection methodologies. Using the example of an alpine catchment we illustrate constraints of some common methodologies. Based on a systematic investigation of influencing factors of the risk estimate, we propose systems of identifying scenarios for different decision-making contexts.
References:
Ward, P. J., H. de Moel, und J. C. J. H. Aerts. „How are flood risk estimates affected by the choice of return-periods?“ Natural Hazards and Earth System Sciences 11 (Dezember 2011): 3181–95. https://doi.org/10.5194/nhess-11-3181-2011.
How to cite: Hoffmann, A. and Straub, D.: Developing recommendations for producing scenarios for natural hazard risk analysis in data-scarce environments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17349, https://doi.org/10.5194/egusphere-egu26-17349, 2026.
This paper introduces a structured expert elicitation to develop narrative descriptions of political futures for the Shared Socioeconomic Pathways (SSPs). The SSPs are scenarios widely used to explore how alternative futures affect the challenges for mitigation and adaptation. Despite the central role of political dimensions (e.g. institutional inclusiveness, institutional effectiveness, and peace) in shaping development trajectories and the feasibility of climate action, the SSPs do not systematically incorporate political features. Political development is often non-linear and relationships between political dimensions and climate action are contested. Expert elicitation provides a transparent approach to link available empirical evidence as well as evaluate the degree of confidence and assess the conditionality of the relationships. Preliminary findings from the elicitations highlight that institutional effectiveness is a consistent differentiator of climate action. High state capacity, low corruption, and credible enforcement reduce challenges to mitigation and adaptation, while weaker institutions and armed conflict substantially increase them.
How to cite: Gilmore, E., Rudolfsen, I., and Buhaug, H.: Integrating Political Futures in the Shared Socioeconomic Pathways: An Expert Elicitation Approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10133, https://doi.org/10.5194/egusphere-egu26-10133, 2026.
limate risk assessments (CRAs) are increasingly used to inform adaptation planning, climate finance, and development decisions. However, existing CRA frameworks vary widely in how they define risk, operationalise assessment methods, and account for adaptation limits and loss and damage. This working paper reviews major global, regional, national, and multilateral CRA frameworks through the lens of Small Island Developing States (SIDS), with a particular focus on their suitability for identifying residual risks, adaptation limits, and economic and non-economic loss and damage.
The paper compares selected frameworks, including ISO 14091, the GIZ Climate Risk Management framework, the EU Climate Risk Assessment Manual, the CLIMAAX framework, the Asian Development Bank’s Climate Risk Management Framework, and national applications in Pacific SIDS - against a common set of criteria. These include alignment with the IPCC AR6 risk framing; treatment of hazards, exposure, and vulnerability; methodological approaches; integration of loss and damage; use of disaggregated data; and relevance for climate finance and policy. It finds that while most frameworks align with the IPCC AR6 risk concept and robustly assess climate risks, few explicitly address adaptation limits or systematically integrate loss and damage, particularly non-economic losses. Where loss and damage is considered, it is typically confined to post-disaster accounting or implicitly embedded within damage estimates, without clear identification of residual risk or intolerable impacts. Thresholds for intolerable risk, mechanisms for distinguishing avoidable from unavoidable impacts, and methods for incorporating community-defined risk tolerance remain largely absent.
Building on this analysis, the paper identifies practical entry points for integrating loss and damage into existing CRA processes and highlights key methodological and institutional gaps relevant for SIDS. The findings directly inform the design of the Building Our Pacific Response to Loss and Damage (BOLD) initiative by supporting the development of context-appropriate, policy-relevant tools for assessing climate risks and unavoidable losses, strengthening national decision-making, and improving access to loss and damage finance.
How to cite: Khan, M. S., Ijaz, S., Irfan, K., Rehman, M., Saeed, M., Pringle, P., Serdeczny, O., and Saeed, F.: Integrating Loss and Damage into Climate Risk Assessment Frameworks: Evidence, Methodological Gaps, and a Pathway for Pacific Small Island Developing States, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20919, https://doi.org/10.5194/egusphere-egu26-20919, 2026.
Europe’s 2025 heatwave transformed the phrase “sleepwalking to drought” from a warning into reality. Climate adaptation is shaped not only by hydrological change but also by deep uncertainty in climate models, governance pathways, and social priorities. We compare three place-based art-science collaborations in the UK, Germany, and Canada to explore how co-creative methods make climate uncertainty legible, discussable, and actionable for water decision-making.
Drawing on social impact theory from engineering design, particularly frameworks that foreground well-being, inequality, demographics, and identity, we treat adaptation as a social process shaped by power, culture, and participation, not merely a technical challenge. Across cases, community-created drama functions as a boundary method, translating abstract or contested knowledge into shared interpretive spaces.
In the UK, community theatre engages intergenerational groups to frame drought adaptation as lived experience. Co-created scripts transform hydrological abstractions into narratives of care, identity, and solidarity. They highlight who acts under scarcity and uncertainty, how priorities are negotiated, and how resilience is socially distributed. In Germany, groundwater recharge modelling faces sharply diverging climate projections that depart from historical observations. Ensemble outputs from bias-corrected simulations feed into a converge-diverge “double diamond” process, where dramaturgical methods help communities interpret uncertainty, cluster extremes, and co-develop water strategies with international partners. In Canada, uncertainty centres on competing development pathways: upstream high-emission energy production versus large-scale freshwater delta restoration. Co-created scripts and boundary objects surface tensions between economic value and environmental and cultural continuity, underscoring the need to move beyond accessibility toward institutional responsiveness.
Methodologically, we argue that co-created dramaturgical practices operate as social infrastructure for climate adaptation, enabling collective problem framing, ethical engagement with uncertainty, and action across competing demands. Rather than reducing uncertainty, these approaches render it governable, supporting resilience and prosilience in water-stressed futures.
Art’s role is both connective and resistant, linking hydrology and social science while guarding against tokenisation. In the UK, the aim is co-benefit: resilience that strengthens local capacity while addressing questions of place, class, and heritage. In Germany, water discussions pair knowledge creation with action through plural stories and datasets, synthesising priorities, prototyping solutions, and refining strategies. For Canada, the call is for active restoration within and beyond the river delta. Local communities champion internal restoration through channel clearing and cultural burning, while upstream restoration requires large-scale partnerships and willingness to sacrifice economic value for environmental and cultural continuity.
Across cases, key tensions include disciplinary silos, limited resources, and the risk of optics over substance. We show that co-designed hydrological modelling, paired with iterative and accessible feedback loops, enables appropriately scaled analytical depth and ethical engagement with uncertainty. These methods foster shared climate dramaturgy for resilient and prosilient water futures.
How to cite: Chun, K. P., Mendieta, T., Hartmann, A., Strickert, G., Bradford, L., Leipold, S., Berridge, S., and McEwen, L.: Drought Uncertainty: Co-creating Climate Adaptation in Canada, the UK and Germany , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15086, https://doi.org/10.5194/egusphere-egu26-15086, 2026.
A central challenge in climate change adaptation is the temporal mismatch between short-term planning and long-term changing risks. Most strategies focus on ex-post adaptation to current climate impacts rather than on anticipatory strategies that address future risks. This challenge is particularly difficult for systemic climate risks related to interconnected hazards, such as floods and droughts. Flood and drought risks, and their adaptation solutions, are usually analysed in isolation, overlooking their coupled dynamics within hydrological cycles and possible win-wins for adaptation to hydrological extremes. A key tool used in adaptation planning are climate change scenarios. These represent structured narratives about plausible futures, and can help to understand future hazards, supporting the exploration of future risk trajectories linked to hydrological extremes. However, effective adaptation planning for systemic risks at the local level requires downscaled climate projections and locally contextualised socioeconomic trajectories to effectively co-develop adaptation options with local actors. This study addresses this need by co-creating scenario narratives based on hybrid localized Shared Socioeconomic Pathway–Representative Concentration Pathway (SSP-RCP) projections and introduces an approach to explore systemic future risk landscapes of interconnected hazards.
We coupled downscaled RCP2.6 and RCP8.5 scenarios with localized SSP1 and SSP5 scenarios and integrated these with co-created visions and systemic risk models to generate one hopeful (SSP1-RCP2.6) and one apprehensive (SSP5-RCP8.5) scenario narrative, informed by both local actor expertise and localized projections for the Erft Basin in Germany. We applied the two scenarios that illuminate divergent potential futures in a participatory workshop setting to review systemic future risk landscapes, prioritize future risks linked to floods and droughts, and define risk tolerance thresholds. Participating actors prioritized a combination of societal and biophysical risks, helping to develop a clearer understanding of risk landscapes from a systemic lens. The risk tolerance thresholds defined in this process are embedded in local realities and reflect the priorities and potential commitment of the actors. Our findings suggest that co-created scenario narratives prompt actors to recognize future systemic risks in a broader range of contexts, thereby enabling them to consider linked future risks in cross-sectoral risk landscapes, potentially enabling more robust and differentiated decision-making. By explicitly linking locally calibrated hybrid scenarios with actor participation, this approach promotes and facilitates forward-looking adaptation planning, such as adaptation pathways, and enhances actors' capacity to prioritize systemic future risk in the context of interconnected climate hazards.
How to cite: Dekker, G., Sparkes, E., Rackelmann, F., Werners, S. E., and Walz, Y.: Co-creating Scenario Narratives for Future Risk Landscapes in the Context of Interconnected Climate Hazards, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19774, https://doi.org/10.5194/egusphere-egu26-19774, 2026.
The Shared Socioeconomic Pathways (SSPs) have provided a widely adopted foundation for climate-centric research, yet their design increasingly limits applicability in the context of today’s interconnected “polycrisis.” Key challenges include artificial no-policy/no-impact baselines, insufficient and non-fundamental treatment of equity, and narratives that are difficult to translate to regional and local decision-making contexts. To address these limitations, the International Committee on New Climate Change Assessment Scenarios (ICONICS) has started the Scenario Evolution Process (SEP): a community-led initiative to critically reassess, adapt, and potentially transform the SSP framework to better support research on resilient, equitable, and sustainable development and develop socioeconomic scenarios that have a applicability beyond the climate change domain.
The Scenario Evolution Process critically reflects on all elements of the existing framework, but also emphasizes evolution, acknowledging that future adaptations may range from incremental refinements to more fundamental changes. Coordinated by ICONICS, the process is set up to be inclusive, transparent, and iterative, engaging a broad and diverse community of researchers, practitioners, and stakeholders across disciplines and regions.
The process starts with an information collection phase that consists of four main activities:
- A multi-stage survey to both scenario producers, as well as users of scenario-based information. Stakeholders will be drawn from established scenario and assessment communities (e.g., ICONICS, IPCC, IPBES, CMIP, GEO, IAMC), as well as from underrepresented disciplines such as political science, biodiversity research, and economics, with targeted efforts to include policymakers and civil society actors. This engagement aims to broaden perspectives and reduce Global North bias.
- An academic literature exchange, with a special issues soliciting proposals for an updated scenario framework, or for elements thereof.
- A series of workshops in the period 2026 to mid-2027 to engage with a diverse range of communities
- Collection of general audience inputs on their needs for climate scenario information.
The information collected will feed into an expert workshop in 2027 that will propose next steps in the evolution of the Scenarios Framework. This could include updated or expanded scenario narratives and key quantitative drivers.
This presentation aims to reach out to the EGU audience and point to the many ways that scenario users can engage with this process.
How to cite: van Ruijven, B., Ebi, K., Moyer, J., Schweizer, V., Menke, I., Green, C., and Andrijevic, M.: Community Scenarios beyond the Shared Socioeconomic Pathways: The Scenario Evolution Process , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13481, https://doi.org/10.5194/egusphere-egu26-13481, 2026.
Posters on site: Mon, 4 May, 16:15–18:00 | Hall X5
Yunlin County, as a major agricultural hub in Taiwan, faces critical challenges stemming from compound water stress under climate change. The interplay of rising demand, induced scarcity, and quality degradation exacerbates existing groundwater over-extraction and land subsidence problems. This research proposes an integrated framework to construct dynamic adaptation pathways that ensure physical and social robustness in water resource management.
The framework comprises three parts. First, we identify potential physical hazards associated with water resources in Yunlin County under climate change and analyze the causal interdependencies among different hazards. Simultaneously, we inventory all adaptation options and map these options to hazards, establishing a structure between risks and responses. Building upon this risk-response structure, the framework employs Dynamic Adaptation Policy Pathways (DAPP) to develop concrete adaptation pathways. The identified interdependencies are translated into tipping points and decision nodes within the DAPP framework, allowing for the construction of comprehensive storylines spanning from physical hazards to adaptive actions, and the strategy of policy making. Finally, to address social uncertainty inherent in policy implementation, the framework employs Agent-Based Modeling (ABM) for social stress-testing. By simulating stakeholder decision-making, ABM reveals how agent interactions influence the environment. We refine the pathways based on ABM outcomes, integrating social perspectives into the storylines. Furthermore, we incorporate water balance, agricultural income, and land subsidence into the evaluation, utilizing Multi-Criteria Decision Analysis (MCDA) to develop a dynamic adaptive plan.
By establishing this integrated system, this research aims to utilize DAPP and ABM to formulate robust adaptation strategies. It provides policymakers with a broader vision of the complex trade-offs between water scarcity, social feasibility, and agricultural systems.
How to cite: Lin, S.-E.: Socio-Hydrological Storylines under Deep Uncertainty: Applying DAPP and ABM to Compound Water Stress and Subsidence, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4009, https://doi.org/10.5194/egusphere-egu26-4009, 2026.
During the winter of 2023/24, northern France experienced two consecutive flood events that caused severe losses and damages in the region. Although the region is well-known for being exposed to flooding, the impact of these events was much greater than that of previous floods. Hundreds of municipalities were declared damaged while hundreds of houses were flooded. Some places and people were flooded twice during the winter.
This work aims to understand the physical and societal conditions that led to these impacts. We conduct an event-based storyline to investigate the flood hazard, the exposure of the inhabitants of the territory and their vulnerability (Sillmann et al 2020). The approach allows us to denaturalise disaster (Klinenberg, 1999) by studying the links between hazard and impacts, but also between exposure, vulnerability and impacts. This is done by combining various datasets.
The hazard analysis is based on long-term meteorological and hydrological observations. This enables us to identify the hydro-climatic drivers of the flood. We show it is the combination of the succession of eight storms and almost continuous rain during winter 2023/24 that led to extreme rainfall accumulation. The study of winter weather regimes based on ERA5 data explains the persistence of those drivers. Using Mann-Kendall statistics, we demonstrate that the hydro-climatic drivers observed during the flood events fall within a long-term trend towards higher average and extreme precipitation in Nord-Pas-de-Calais. We investigate the compound nature of the 2023/24 flood events (Zscheischler et al 2020). The succession of eight heavy precipitation events leading to two flood events emphasises the temporarily compound nature of the events. In addition, we explore the multi-variate compoundness of the event, through observations of the high tidal coefficients, the land use and land coverage during winter 2023/24, which can all be partly responsible for the flooding.
Finally, we use past flood events as milestones to compare to 2023/24 flood events, to better understand the drivers, both meteorological and non meteorological, which led to such extreme flooding.
Klinenberg, Eric. s. d. Denaturalizing Disaster: A Social Autopsy of the 1995 Chicago Heat Wave.
Sillmann, Jana, Theodore G. Shepherd, Bart van den Hurk, et al. 2021. « Event-Based Storylines to Address Climate Risk ». Earth’s Future 9 (2): e2020EF001783. https://doi.org/10.1029/2020EF001783.
Zscheischler, Jakob, Olivia Martius, Seth Westra, et al. 2020. « A Typology of Compound Weather and Climate Events ». Nature Reviews Earth & Environment 1 (7): 333‑47. https://doi.org/10.1038/s43017-020-0060-z.
How to cite: Doury, E., Jézéquel, A., Habets, F., and Fildier, B.: Storyline of the winter 2023/2024 flood events in Nord-Pas-de-Calais (France), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7517, https://doi.org/10.5194/egusphere-egu26-7517, 2026.
Small Island Developing States (SIDS) face complex and compounding climate risks, particularly tropical-cyclone winds and storm surges, which frequently disrupt tightly interconnected infrastructure systems, including electricity, transport, water, and telecommunications. Nevertheless, many current impact assessments are misaligned with practical adaptation requirements, relying predominantly on GDP-based exposure and loss metrics that fail to capture service disruptions, infrastructure interdependencies, or the dynamics of recovery. Moreover, the common assumption that infrastructure is fully restored within a single calendar year is often unrealistic in SIDS, where disruptions and recovery efforts may extend well beyond this timeframe. This underscores the need for more granular, service-oriented analyses.
We introduce a storyline-based, transparent, and data-efficient workflow to evaluate cascading infrastructure impacts and recovery processes under physically consistent, multi-hazard tropical-cyclone scenarios. Storylines are based on historical or plausible events and are translated into gridded hazard fields representing wind and storm-surge inundation. Leveraging CLIMADA for hazard–exposure–impact analysis, we combine compound hazard intensities with sector-specific fragility and recovery functions to estimate direct damage, functional reliability, and time-dependent restoration trajectories for infrastructure assets. Utilizing open exposure datasets (e.g., OpenStreetMap-derived assets) and demand layers, we capture cross-sector dependencies, such as electricity enabling water supply and telecommunications, or transport influencing repair access, to quantify service disruption over time for affected populations.
We emphasize the heterogeneous fragility and recovery capacities across SIDS, incorporating composite proxy indicators (including infrastructure condition, accessibility, response capacity) to derive comparable metrics such as time-to-restoration thresholds and service loss duration. This framework enables the stress-testing of adaptation pathways and informs Loss and Damage strategies, and resilience planning by aiming to identify adaptation limits and avoiding maladaptation, while generating evidence relevant to international finance and support mechanisms.
How to cite: Gomez-Zapata, J. C., Siebert, A., Martyr, R., Guerra, M., and Schaeffer, M.: Storyline-Based Modelling of Cascading Critical Infrastructure Impacts and Recovery in Small Island Developing States, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15223, https://doi.org/10.5194/egusphere-egu26-15223, 2026.
Socioeconomic and demographic factors such as age structure, gender distribution, and education levels play a key role in shaping social vulnerability to climate-related risks. The Shared Socioeconomic Pathways (SSPs) provide national-level projections of these variables under different future scenarios, but these aggregated estimates neglect the spatial heterogeneity that drives local vulnerabilities. This study introduces a novel methodology for downscaling national SSP projections to subnational administrative units (NUTS2) in Europe. The methodology is illustrated for the SSP3.1 scenario and includes, first, the calculation of region-to-country ratios, analysis of historical trends, and validation of the model by quantifying its agreement with observed historical time series. National projections are then either downscaled to the administrative unit level and adjusted for temporal trends where they are statistically significant, or downscaled using 2020 reference proportions. The resulting dataset provides spatially explicit, SSP3.1-consistent projections that capture subnational variability while aligning with national trends. This dataset could support a wide range of applications, including climate impact assessments, socioeconomic modeling, and adaptation planning. By prioritizing transparency and replicability, this study offers a valuable resource for researchers and decision-makers seeking subnational socio-demographic projections for Europe.
How to cite: Sestito, B., Reimann, L., Bonatz, H., Botzen, W., Aerts, J., and Mazzoleni, M.: Downscaled Population Projections Under Shared Socioeconomic Pathways: A European Wide Application for Age, Gender and Education, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7535, https://doi.org/10.5194/egusphere-egu26-7535, 2026.
We introduce a novel approach to event attribution and developing storylines based on both recent and historical observed extreme events. Using the 20th Century Reanalysis system (20CRv3) we produce factual global reconstructions of observed events from different periods - the examples shown here are for a range of event types from 1910, 1976 and the last decade.
For modern events we produce a cooler counter-factual by reducing the SSTs used as boundary conditions and greenhouse gas levels in the reanalysis and assimilate the same surface pressure observations to produce the ‘same’ weather patterns in a cooler world. For the historical examples we produce a warmer counter-factual by increasing the SSTs and greenhouse gas levels to represent the same weather in a modern climate. The differences between factual and counter-factual provide estimates of the change in intensity of the observed event as represented by a modern numerical weather prediction model.
This approach allows a global perspective on extreme events and their impacts - the same experiments produce global factual and counter-factual reconstructions of every day in the chosen periods. The data will be made openly available to allow anyone to explore their own choice of extreme event anywhere in the globe. Counter-factuals will also be developed for future warmer climate conditions to understand how extreme events and their impacts will change, and help inform adaptation decisions.
How to cite: Hawkins, E., Thomas, R., Thompson, V., Schurer, A., Shepherd, T., Hegerl, G., Compo, G., Slivinski, L., and George, S.: Reanalysis-Based Attribution and Storylines of Extremes (ReBASE), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9957, https://doi.org/10.5194/egusphere-egu26-9957, 2026.
Climate change–driven extremes, including intensified rainfall and heatwaves, increasingly threaten urban systems not through isolated hazards but through cascading failures embedded in infrastructure interdependencies. In urban areas, outdated drainage systems may exacerbate flooding impacts by constraining electricity access and recovery during flooding, whereas concurrent power outages may further impair the pumping capacity, monitoring, and operational control of drainage systems. These coupled dynamics often result in nonlinear, system-wide functional collapse without identifying the respective system’s criticality in their operative conditions. Yet studies have been focused on evaluating water and energy system vulnerability independently and relying on analysis based averaged damage metrics, rendering them structurally incapable of capturing abrupt transitions and amplification processes arising from infrastructural interdependency.
This study develops a scenario-based analytical framework to examine how interdependent urban water–energy systems respond to climate extremes and under what conditions their dynamic behavior undergoes regime shifts. Water and energy infrastructures (i.e., drainage and sewer systems, and power grid systems) are conceptualized as integrated Social–Ecological–Technological Systems (SETs), allowing social capacity, ecological buffering, and technological performance to be analyzed within a unified system structure. Based on this theoretical framework, a Causal Loop Diagram (CLD) is constructed to explicitly represent feedback mechanisms and cascading failure pathways linking drainage capacity, power reliability, and damage recovery dynamics.
Building on the conceptual model, a System Dynamics (SD) approach is employed to explore coupled system behavior across scenarios that vary climate shock intensity, infrastructure functional degradation, interdependency-driven amplification, and the timing of policy intervention. Central to the analysis is the identification of critical transitions through a threshold-state variable that captures shifts from adaptive system functioning to persistent systemic stress. Rather than assuming proportional responses, the model identifies combinations of climatic and infrastructural conditions under which marginal perturbations produce self-reinforcing and potentially irreversible system responses. Results from the scenario analysis indicate that proactive interventions implemented prior to threshold crossings are substantially more effective in suppressing cascading dynamics than reactive measures introduced after system destabilization.
This study aims to advance urban climate adaptation research by reframing infrastructure resilience as a problem of system transition under interdependency, rather than isolated performance failure. By integrating threshold identification analysis, interdependent infrastructure dynamics, and scenario-driven simulation, the proposed framework offers a transferable foundation for designing anticipatory adaptation strategies capable of preventing regime shifts in urban systems under climate extremes.
How to cite: Gayoung, L. and Yeowon, K.: Scenario-Based Identification of Critical Thresholds in Interdependent Urban Water–Energy Systems under Climate Extremes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6337, https://doi.org/10.5194/egusphere-egu26-6337, 2026.
While in many regions worldwide climate change and socio-economic developments are increasing the likelihood of unprecedented extreme events, current risk management practices are often not prepared for such events, resulting in catastrophic impacts. This lack of preparedness is partly driven by the reluctance of both lay people and decision-makers to consider and plan for events that exceed those observed in the historical record. There is thus a need for approaches that generate plausible scenarios of unprecedented events that are both scientifically sound and intuitively understandable. Here we present several methods for constructing such scenarios for river flooding in Germany. These include spatial counterfactuals, in which the precipitation fields of historical floods are spatially shifted, and a perfect-storm approach, in which precipitation from historical events is combined with historical wet catchment conditions. In addition, we apply a stochastic simulation framework in which a large-scale weather generator drives a hydrological model. All three approaches produce events that are substantially more severe than those observed in Germany over the last 70 years (1951-2021). For example, even moderate deviations in the trajectory of the precipitation field of past floods, which were among the most expensive and catastrophic events in Germany, could have led to substantially higher severity across Germany. While all methods are able to provide unprecedented flood events, the choice of method depends on the intended application, such as stress-testing infrastructure or supporting risk communication.
How to cite: Merz, B., Nguyen, V. D., Han, L., and Vorogushyn, S.: Exploring Unprecedented Flood Events Using Counterfactual and Stochastic Approaches, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7336, https://doi.org/10.5194/egusphere-egu26-7336, 2026.
In this presentation, we introduce the project ATTENUATE (Creating the enabling conditions for UK climate adaptation investment), which aims to investigate how improvements in enabling conditions can mobilise additional public and private finance for climate change adaptation in the UK. The project focuses on the behavioural and institutional barriers embedded within the political economy of adaptation governance, including fragmented responsibilities across governance levels, persistent uncertainty over future climate risks, and limited incentives for private investment. Addressing these barriers is critical in light of the substantial adaptation finance gap identified in the UK, estimated to be at least £9 billion annually, with significant implications for infrastructure resilience, public services, and long-term economic stability.
A central and innovative component of ATTENUATE is the pioneering use of physical climate storylines in the context of adaptation finance. Climate storylines offer plausible, decision-relevant narratives of climate hazards and impacts that complement conventional risk assessments and probabilistic projections. By framing climate risks in ways that are tangible, locally relevant, and aligned with decision-making timescales, storylines have the potential to improve the communication, interpretation, and uptake of climate information within financial and policy processes.
The application of climate storylines to adaptation finance requires engagement across multiple governance levels and sectors, including policymakers, public authorities, investors, and practitioners. Through a participatory co-creation approach [1], ATTENUATE works with these actors to co-develop bespoke storylines that explicitly link climate impacts to financial outcomes, policy choices, and investment risks. Through this process, the project seeks to identify and address behavioural barriers that constrain more ambitious and transformative adaptation responses, particularly those affecting perceptions of risk, responsibility, and bankability. We co-develop storylines in two contrasting local climate risk contexts in the UK - flood risks to infrastructure and property in the West Midlands, and heat-related risks in Hackney, London – and in a national-level case study with the UK Government’s Environment Ministry. Financial metrics adopted are differentiated according to whether the adaptation response will be funded from public or private sources.
The presentation will outline the conceptual foundations, development process, and piloting of climate storylines within ATTENUATE, and reflect on their potential to shift decision-making practices and support more financeable adaptation pathways. In particular, we will present partial results from a collaborative workshop with stakeholders held in January 2026. Finally, we will discuss how our approach introduces a model for the use of storylines in planning and decision-making in this multistakeholder finance context.
Acknowledgement: This work was supported by the UK Research & Innovation (grant number UKRI282).
Reference:
[1] Beswick, A., Watkiss, P., England K., Gannon, K., de Melo Virissimo, F., Mehryar, S., Dookie, D., Rhodes V. 2025. Co-creation protocol for the ATTENUATE project. https://eprints.lse.ac.uk/130961
How to cite: de Melo Viríssimo, F., Dookie, D. S., Hunt, A., Athanassiadou, M., Dawson, M., Beswick, A., Gannon, K., Ellis, M., Harrington-Abrams, R., Love, A., Mehryar, S., Piccaro, E., Rusby, C., and Thornton, A.: Piloting climate storylines in adaptation finance as a tool to shift the political economy of adaptation policy and bankability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7451, https://doi.org/10.5194/egusphere-egu26-7451, 2026.
The Danube River Basin is a vital artery for European energy production, food security, and inland transport, yet it is increasingly emerging as a hotspot for hydroclimatic extremes, particularly droughts. Although global thermodynamic warming signals are robust, regional climate change projections remain uncertain due to the large impact of atmospheric circulation at these scales. In particular, the seasonal response of the North Atlantic jet stream to forcing is not robust across models. Here, we define physical climate storylines based on CMIP6 data to partition the uncertainty associated with diverging jet stream responses in speed and latitude. Subsequently, we use bias-adjusted CMIP6 projections to generate hydrological simulations for the Upper Danube Basin, focusing on the high-emission scenario SSP5-8.5 but finding similar results for SSP2-4.5. We identify an intensification of historically rare low-flow events in several storylines at a +2°C and +3°C global warming level. Notably, return periods in winter are modulated depending on the jet stream response. Consequently, adaptation planning must move beyond historical benchmarks to prepare for a reality of more frequent water scarcity in the future.
How to cite: Weis, V. L., Stanzel, P., Kling, H., and Ossó, A.: Change of return periods for low-flow extremes across storylines in a warming Danube River Basin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10258, https://doi.org/10.5194/egusphere-egu26-10258, 2026.
Understanding historical and future patterns of urbanization is essential for anticipating demographic change, guiding sustainable development, and managing climate and hazard risks. Although Shared Socioeconomic Pathways (SSPs) incorporate urbanization conceptually, few settlement projections have been adapted to fine spatial scales that capture intra-urban heterogeneity. Because most growth in developing-country cities occurs via horizontal expansion at the peri-urban fringe, improving spatially explicit models of land conversion and build-up dynamics remains a key methodological need.
We evaluate alternative open and reproducible modeling approaches for the Accra metropolitan area (Ghana), a rapidly growing and spatially uneven urban region. Using satellite-derived land use/land cover and built-up layers (2001, 2005, 2009), we compare (i) established urban growth modeling (UGM) toolchains focused on binary expansion (MOLUSCE, FUTURES, SLEUTH) against a flexible statistical learning baseline (LEARN), and (ii) newer approaches that model the continuous built-up surface directly. For the expansion-focused setup, models are trained on 2001–2005 and evaluated by predicting 2009 transitions using a shared covariate set (e.g., prior urban extent/LULC, distance to roads and waterways, protected areas, elevation, and distance to existing development).
Performance is assessed using the Figure of Merit (FoM), a change-focused accuracy measure that avoids inflated scores under rare-change conditions typical of urban expansion. In the expansion-only comparison, the statistical learning framework LEARN provides the strongest baseline performance (FoM ≈ 0.20), exceeding MOLUSCE (0.07), FUTURES (0.01), and SLEUTH (0.10).
We then extend the task from binary land conversion to predicting the continuous build-up surface. A random forest baseline that models built-up change directly achieves FoM ≈ 0.50 in Accra. Building on this, we implement a two-head U-Net that jointly estimates (i) the likelihood of expansion and (ii) the magnitude of build-up increase, with constraints to keep predicted change non-negative and spatially plausible. This neural approach performs best overall (FoM ≈ 0.65), improving substantially on both classical UGM baselines and the random-forest model.
Overall, results indicate that modeling build-up as a continuous surface—and explicitly coupling expansion with magnitude via neural networks—can markedly improve change-prediction skill in fast-growing cities, while remaining compatible with scenario-consistent urban forecasting frameworks.
How to cite: Noi, E., Hawker, L., Carioli, A., Espey, J., Hilton, J., and Tatem, A.: From Classical Urban Growth Models to Data-Driven Methods: Predicting Urban Expansion and Built-Up Intensity in Accra, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11681, https://doi.org/10.5194/egusphere-egu26-11681, 2026.
With the rising level of the Seine River during hurricane Kirk, the city of Alfortville (Paris area, France) was facing a major concern. If the water level goes over 6,5m high, 97% of the city will be flooded in 2 days and the decision makers will have to manage the evacuation of 45.000 inhabitants. The massive evacuation of the population in case of a major flood in the Paris area remains a major challenge for emergency managers.
This presentation introduces the results of an agent-based model designed to simulate evacuation behaviors in response to different types of flooding across three territories in the Paris metropolitan area. The model, built using the NetLogo environment, is part of the Paris-Area Flood Evacuation (PAFE) project. We constructed a synthetic population using seven socio-demographic variables, calibrated to match census data and spatially distributed in a realistic way across households in each territory. Individual evacuation decisions were informed by a large-scale empirical survey (n = 5,000), with agents’ responses linked to their socio-economic profiles. Finally, the model was refined in collaboration with local experts and decision-makers who have direct experience with past flood events in the region.
How to cite: Santoni, V., Rufat, S., Enderlin, E., and Lhomme, S.: Refining Flood Evacuation ABM with local stakeholders in the Paris Area, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12217, https://doi.org/10.5194/egusphere-egu26-12217, 2026.
Extreme heat exacerbated by climate change is one of the greatest threats to the global sports industry. There are two contrasting seasonal challenges facing the sports industry. In the case of winter sports, increasing temperatures due to climate change lead to reduced natural snow cover and ice formation, as well as causing artificial snow and ice to melt. Meanwhile, the effect of extreme heat on athletes impacts summer sports, with high temperatures causing exertional heat illnesses (EHI).
The impact extreme warming is having on winter sports in particular, is already prevalent. Recent Winter Olympic Games have been severely impacted by extreme warming events, such as heat waves in the case of Sochi 2018, and as host locations are selected up to a decade before hosting, significant changes can occur within that timeframe.
This research examines the last 30 years of temperature and snow depth in order to evaluate the feasibility of minimum snow depth requirements occurring naturally in the location of Cortina d'Ampezzo for the upcoming Winter Olympic and Paralympic Games in 2026. Subsequently, a selection of individual CMIP6 models for the next 50 years are analysed to evaluate the feasibility of this location continuing to host major sporting events that require snow depths for athlete safety, and whether this can be facilitated by natural snow alone or if artificial snow will be required. This analysis involved the creation of a snow model in R to estimate future snow accumulation and melt in the region.
Additionally, due to the Olympics and Paralympics occurring in this venue in February and March 2026 this study is in a unique position to report from the event itself and evaluate how the previous 30 years of observations link with the reality on the ground. There has also been an opportunity to complete a mixed-methods study adding a layer of human experience by completing surveys and interviews of athletes and coaches competing in these games. As well as this the quantitative and qualitative data can be brought together in an ArcGIS StoryMap in order to illustrate whether Cortina d’Ampezzo can still host the Winter Olympic Games in the future.
This research has the potential to expose the need for adaptation of sports infrastructure and sporting regulations to deal with the threat of extreme heat as a result of climate change.
How to cite: Kielt, A.: Sport adaptation to extreme heat in a warming world: Can Cortina d’Ampezzo continue to host the Winter Olympic Games?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19318, https://doi.org/10.5194/egusphere-egu26-19318, 2026.
The Royal Netherlands Meteorological Institute (KNMI) recently published nine different climate risk storylines to prepare for climate hazards in the current and near future climate. This study specifically zooms in on the climate risk storyline for a heatwave in Amsterdam. The summer of 2018 was exceptional, leading to the first code Orange for extreme heat. In this study we investigate whether, and how, the heatwave of 2018 could plausibly have evolved into a more extreme event. Using ensemble forecasts from ECMWF, we identify an alternative but physically consistent meteorological evolution in which the cooling front of late July 2018 did not reach the Netherlands. This alternative scenario, termed ‘Heatwave XL’, is dynamically downscaled using the regional climate model RACMO, with corrections for model bias. Urban heat island diagnostics are applied to derive spatially explicit heat exposure across Amsterdam. Sectoral impact knowledge from impact partners is then integrated to assess potential societal impacts and cascading effects. The Heatwave XL storyline results in several additional days of extreme daytime temperatures exceeding 35 °C, combined with persistently hot nights, likely exacerbating societal impacts already seen in 2018. This case demonstrates the value of storyline approaches for stress-testing preparedness and supporting anticipatory decision-making under uncertainty in a warming climate.
How to cite: van Voorst, L. and Pereira Marghidan, C.: Could the 2018 Amsterdam heatwave have been more extreme? A climate risk storyline of plausible extreme heat, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8221, https://doi.org/10.5194/egusphere-egu26-8221, 2026.
Event storylines are a variant of storylines and can be used to explore the consequences of low-likelihood high impact events. In particular, they provide the basis for a realistic emergency operations center exercise: stakeholders and scientists can run through different - also management - scenarios and asseess their complex and cascading risks and costs.
Different approaches to implementing event storylines exist; most are based on some variant of the pseudo global warming approach: an observed event is simulated under the actual (boundary) conditions and under modified boundary conditions representing selected scenarios. The simulations can then be fed into quantiative impact models and further be used for qualitative assessments. But this (in theory) very elegant approach comes along with several challenges in its practical implementation.
Here we use the example of a severe landslide event in Southern Austria to illustrate these challenges and present solutions. Heavy rainfall, caused by a slowly moving cut-off low and falling on saturated soils, triggered at least 952 landslides and resulted in substantial damage of infrastructure and buildings. To model the event, we combine kilometer-scale regional climate model simulations with a statistical landslide model, trained on a comprehensive dataset of observed landslide, meteorological, geological, topographical and vegetation data. We simulate the event under present, observed boundary conditions, as well as under modified conditions representing different global warming levels as simulated by global climate models. The actual implementation of changes in boundary conditions, however, is not a priori clear. Also, even though the event is well simulated, it is dislocated compared to observations by a few tens of kilometers. This dislocation is of the same order of magnitude as the area affected by landslides and thus makes a direct use of the simulations for driving the landslide model unfeasible for representing a specific event.
In a set of sensitivity studies, we first explore the influence of (1) simulating the event with climatological boundary conditions over a large domain with spectral nudging vs. event-type specific boundary conditions over a small domain without spectral nudging; and (2) imprinting altitude dependent or constant changes in different atmospheric variables, from temperature only to temperature, humidty and sea level pressure. The results depend strongly on the implementation. However, a process-based analysis reveals that only the small-domain variant with sea level pressure and consistent altitude-dependent changes in temperature and relative humidity simulates physically plausible changes. Second, we develop a delta change approach, which (1) replaces temporal by spatial averaging to calculate change factors, and (2) applies changes separately to precipitation at different time-scales. Finally, we discuss the relevance of carefully defining the event in time, including preconditioning by antecedent precipitation which may change in a warming climate, and how changes in these preconditions can be simulated.
Our study demonstrates the great potential of event storylines for risk assessments, but also highlights the need for a range of critical choices and post-processing steps that need to be carefully considered to arrive at plausible results.
How to cite: Maraun, D., Lezameta, L., and Truhetz, H.: Challenges in using event storylines for climate risk assessments. The example of a severe landslide event in Austria., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17887, https://doi.org/10.5194/egusphere-egu26-17887, 2026.
We present a harmonized dataset of globally comprehensive up-to-date emissions trajectories and their emulated climate outcomes, developed to support the ScenarioMIP experiment within CMIP7. Drawing from a set of around 90 candidate scenarios, a small subset of 7 marker scenarios is selected to span a wide range of emissions and climate outcomes to be simulated by earth system models (ESMs) in the AR7 Fast-Track.
These scenarios are calculated using seven Integrated Assessment Models (AIM, COFFEE, GCAM, IMAGE, MESSAGE-GLOBIOM-GAINS, REMIND-MAgPIE, and WITCH) and are based on newly updated socioeconomic pathways (SSPs).
In CMIP6, ESM projections have mainly been driven by changes in atmospheric concentrations. CMIP7 prioritises emissions-driven climate projections, meaning the harmonization and spatial distribution of emissions are of increased importance.
For CMIP7, we combine multiple strands of previous work into one workflow that includes: (1) compiling a common historical emissions dataset, for each IAM region, and all climatically relevant emissions species, (2) harmonizing sectoral emissions pathways to 2023 emissions, (3) generating harmonized gridded emissions data, (4) running updated simple climate models to emulate the range of possible climate outcomes of the emissions pathways.
In this presentation, we present: the workflow, the new CMIP7 scenario set, and how it compares to the CMIP6 scenarios.
The data presented are meant support earth system modelling and impact assessment across the CMIP7 Assessment Fast-Track and beyond, including model intercomparison projects such as ISIMIP, AerChemMIP, and CDRMIP, and in doing so, support upcoming IPCC assessments.
References
- Van Vuuren, D., O’Neill, B., Tebaldi, C., Chini, L., Friedlingstein, P., Hasegawa, T., Riahi, K., Sanderson, B., Govindasamy, B., Bauer, N., Eyring, V., Fall, C., Frieler, K., Gidden, M., Gohar, L., Jones, A., King, A., Knutti, R., Kriegler, E., Lawrence, P., Lennard, C., Lowe, J., Mathison, C., Mehmood, S., Prado, L., Zhang, Q., Rose, S., Ruane, A., Schleussner, C.-F., Seferian, R., Sillmann, J., Smith, C., Sörensson, A., Panickal, S., Tachiiri, K., Vaughan, N., Vishwanathan, S., Yokohata, T., Ziehn, T., 2025. The Scenario Model Intercomparison Project for CMIP7 (ScenarioMIP-CMIP7). EGUsphere 1–38. https://doi.org/10.5194/egusphere-2024-3765
How to cite: Kikstra, J., Högner, A., Zecchetto, M., Ahsan, H., Gidden, M., Riahi, K., Smith, C., Smith, S., and Nicholls, Z.: CMIP7-ScenarioMIP emissions set and probabilistic climate outcomes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14856, https://doi.org/10.5194/egusphere-egu26-14856, 2026.
Stress-testing has long been a fundamental practice in fields like finance to evaluate systemic resilience under extreme conditions. Climate scenarios however typically feature average projections and expected impacts, often neglecting critical questions such as “What if we face extremes at the upper ends of climate uncertainty, or at what levels are critical thresholds breached?”. The SPARCCLE project seeks to fill this gap by integrating stress-testing approaches into climate scenario analysis, thereby exploring the implications of extreme, but plausible climate futures under a 1.5° and a current policy scenario.
For this purpose, the SPARCCLE project has actively engaged a diverse set of stakeholders from the energy, health, and finance sectors to co-develop three stress-testing storyline-and-simulation approaches. These were translated into narrative aspects of interest on various climate and socioeconomic European challenges into quantified scenarios. These scenarios illustrate conditions that stretch the limits of existing adaptation and risk management frameworks.
Through structured webinars, a 2-day workshop with 30 participants including stakeholders and climate modellers, and ongoing iterative discussions to prompt aspects of interest then validate quantifications, we identified key vulnerabilities and cascading impacts of extreme climate events on critical sectors. The result are three storylines focusing on (i) Europe under heat stress, (ii) Water – too little and too much and (iii) Europe in a fragmented world. Our interdisciplinary collaboration with modelling experts encompasses methodologies ranging from simple climate models to impact models to integrated assessment models (IAMs), ensuring alignment between stakeholder-driven storylines and cutting-edge scientific insights.
In this presentation, we will provide a comprehensive overview of our co-development process, detailing our methodological framework, present the three storylines and the transition of qualitative narratives into quantitative multi-model experiments. We will highlight challenges encountered and solutions devised throughout this journey. Furthermore, we will discuss how the stress-test scenario exercise can contribute to improved decision-making both for adaptation and mitigation.
How to cite: Menke, I., Schmidt, S., Byers, E., and Zhu, Q.: From Narratives to Quantification: Co-Developing Stress-Test Scenarios for Climate Adaptation and Mitigation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13846, https://doi.org/10.5194/egusphere-egu26-13846, 2026.
