Europe is increasingly threatened by climate-induced events happening remotely from the continent. To test the resilience of selected public and private finance risk instruments against external shocks we analyse multiple hypothetical scenarios based on historic events, focusing on cyclone risks, and various alternative realisations, so-called climate storylines. We present the storyline approach as a systems approach to examine whether events outside a system can affect elements within the system. Furthermore, we provide a framework to analyse possible transmission channels of such remote events jointly as well as separately. In doing so we combine a multi-model approach within single and multi-climate storylines to better address the various vulnerabilities of risk management and adaptation options for today and in the future. We specifically focus on humanitarian emergency assistance (via the Caribbean Catastrophe Risk Insurance Facility), public sector governance help (via the European Union Solidarity Fund), macro-economic financial effects (by assessing international financial flows and investment decisions) and consequences to insurance uptake due to remote climate events (via increases in risk aversion of reinsurers). The experiences made with this approach are compared with the advantages and disadvantages of both storylines and probabilistic assessments and we provide ways forward for a unified approach.

Systemic risks will be amplified due to global warming as climate-related shocks, like extreme weather events, cause cascading and compounding impacts across sectors and systems. To better understand and manage systemic risk, inter- and transdisciplinary collaborations between scientists and decision-makers are urgently needed. This backstory summarizes contributions to a focus collection showcasing scientific advances in modeling systemic risk and its drivers and provides examples of using local knowledge, sectoral data, and artificial intelligence for a better understanding of systemic risks.

Anthropogenic global warming affects all aspects of ecosystems and human life. Thus far, most climate impact studies have mainly focused on local impacts because climate-driven hazards – e.g., floods, storms, heat waves – occur locally. However, as the occurrence of past events has already shown, local climate impacts cascade across sectors, regions and scales, possibly leading to systemic risks. Here we highlight the main transmission channels of climate-driven systemic risks, and outline how they can challenge the achievement of the sustainable development goals. We argue for more research into integrated modeling frameworks, understanding and modeling of transmission pathways and systemic climate risk governance approaches.

In recent years, it has become more and more clear that climate change and its impacts do severely affect companies’ business. For example, acute climate risks driven by e.g. floods and tropical cyclones can impact physical assets and halt productions, whereas chronic climate risks such as droughts and temperature increases can have severe impacts on e.g. crop production, labour productivity and water availability. This increased understanding of climate risk on companies’ performances led to the establishment of the Task Force on Climate-related Financial Disclosure (TCFD) which provides a framework for disclosing and reporting climate-related risks and opportunities. As TCFD requires businesses to quantify, rate and manage climate risks across various perils and regions, there is the need to develop climate risk indicators which comply with its recommendations. In this talk, we will introduce the indicators developed by CLIMADA Technologies - an open-core ETH spin-off company - for multiple hazards, incl. tropical cyclones, floods, winter storms, wildfires, droughts, heat waves, and cold spells. The indicators allow assessing and coherently summarising climate risk information in line with TCFD recommendations and thus support companies in taking resilient actions.

Extreme weather events like tropical cyclones and floods severely impact economies, causing growth losses, tax revenue declines, and increased government debt due to short-term deficit financing. This challenge is particularly acute for countries with existing debt issues, which often rely on slow and uncertain foreign aid whose terms are typically agreed upon only ex-post. In contrast, ex-ante financial instruments, such as insurance and sovereign catastrophe risk pools, offer faster, more predictable funding while encouraging risk reduction and adaptation investments.Sovereign risk pools, such as the Caribbean Catastrophe Risk Insurance Facility (CCRIF), African Risk Capacity (ARC), and Pacific Catastrophe Risk Assessment and Financing Initiative (PCRAFI), have proven valuable. However, they may not fully realize their financial resilience potential, as pooling within the same region can limit risk diversification. This presentation will introduce a method to design risk pools by maximizing diversification across countries regardless of region. Results show this approach consistently enhances risk diversification, more evenly distributes risk shares within the pool, and increases the number of benefiting countries.Related publication:Ciullo, A., Strobl, E., Meiler, S. et al. Increasing countries’ financial resilience through global catastrophe risk pooling. Nat Commun 14, 922 (2023). https://doi.org/10.1038/s41467-023-36539-4

Tropical cyclone risks are expected to increase with climate change and socio-economic development and are subject to substantial uncertainties. We thus assess future global tropical cyclone risk drivers and perform a systematic uncertainty and sensitivity analysis. We combine synthetic tropical cyclones downscaled from CMIP6 global climate models for several emission scenarios with economic growth factors derived from the Shared Socioeconomic Pathways and a wide range of vulnerability functions. We highlight non-trivial effects between climate change and socio-economic development that drive future tropical cyclone risk. Furthermore, we show that the choice of climate model affects the output uncertainty most among all varied model input factors. Finally, we discover a positive correlation between climate sensitivity and tropical cyclone risk increase. We assert that quantitative estimates of uncertainty and sensitivity to model parameters greatly enhance the value of climate risk assessments, enabling more robust decision-making and offering a richer context for model improvement.

Abstract Tropical cyclone (TC) risks are expected to increase with climate change and socio-economic development and are subject to substantial uncertainties. We thus assess future global TC risk drivers and perform a systematic uncertainty and sensitivity analysis. We combine synthetic TCs downscaled from CMIP6 global climate models (GCMs) for several emission scenarios with economic growth factors derived from the Shared Socioeconomic Pathways (SSPs) and a wide range of vulnerability functions. We find a non-linear effect between climate change and socio-economic development that drives the future TC risk. Furthermore, we show that the choice of GCM affects the output uncertainty most among all varied model input factors. Finally, we discover a positive correlation between climate sensitivity and TC risk increase. We conclude that uncertainty and sensitivity analysis are powerful tools to improve the information value of climate-risk models, producing transparent output and providing a comprehensive context to quantitative results for robust decision-making.

Extreme weather events can severely impact national economies, leading the recovery of low- to middle-income countries to become reliant on foreign financial aid. Foreign aid is, however, slow and uncertain. Therefore, the Sendai Framework and the Paris Agreement advocate for more resilient financial instruments like sovereign catastrophe risk pools. Existing pools, however, might not fully exploit their financial resilience potential because they were not designed to maximize risk diversification and because they pool risk only regionally. Here we introduce a method that forms pools by maximizing risk diversification and apply it to assess the benefits of global pooling compared to regional pooling. We find that global pooling always provides a higher risk diversification, it better distributes countries’ risk shares in the pool’s risk and it increases the number of countries profiting from risk pooling. Optimal global pooling could provide a diversification increase to existing pools of up to 65 %.

Quote: “What I hear, I forget. What I see, I remember. What I do, I understand.” (Xunzi, ∼300 BCE).Modelling complex interactions involving climatic features, socio-economic vulnerability or responses, and long impact transmissions is associated with substantial uncertainty. Physical climate storylines are proposed as an approach to explore complex impact transmission pathways and possible alternative unfoldings of event cascades under future climate conditions. These storylines are particularly useful for climate risk assessment for complex domains, including event cascades crossing multiple disciplinary or geographical borders. For an effective role in climate risks assessments, development guidelines are needed to consistently develop and interpret the storyline event analyses.This paper elaborates on the suitability of physical climate storyline approaches involving climate event induced shocks propagating into societal impacts. It proposes a set of common elements to construct the event storylines. In addition, criteria for their application for climate risk assessment are given, referring to the need for storylines to be physically plausible, relevant for the specific context, and risk-informative.Apart from an illustrative gallery of storyline examples found in literature, three examples of varying scope and complexity are presented in detail, all involving the potential impact on European socio-economic sectors induced by remote climate change features occurring far outside the geographical domain of the European mainland. The storyline examples illustrate the application of the proposed storyline components and evaluate the suitability of the criteria defined in this paper. It thereby contributes to a rigorous design and application of event-based climate storyline approaches.

The European Union has some dedicated tools and mechanisms available to respond to natural hazard events including the European Union Solidarity Fund (EUSF). It follows the objective of granting financial assistance to Member States in the event of a major disaster with serious consequences. In the latest EU long-term budget plan—the Multiannual Financial Framework 2021–2027—the EUSF was merged with the Emergency Aid Reserve (EAR) to form the new Solidarity and Emergency Aid Reserve (SEAR). One additional significant change was made in 2020 which saw an extension of the scope of the EUSF. This extension allowed the EUSF to cover losses incurred due to major public health emergencies such as the COVID-19 pandemic. It is therefore now a multi-hazard and multi-risk financing instrument designed to financially assist during the emergency phase in case of an emergency event. We assess the consequences of these changes in the light of potential advantages as well as disadvantages compared to the prior EUSF structure. The results will be used to provide some policy recommendations as to how to move forward with the identified challenges. We especially recommend separating the EUSF from the coverage of large-scale public health emergencies and the emergencies covered by the EAR. Instead, we suggest establishing a new flexibility instrument that covers emergencies such as public health related ones as well as the ones within the EAR. The analysis gives some important insights, scientific as well as policy wise, about advantages as well as limitations of financial instruments that simultaneously should tackle different types of hazards and risks.

Physical climate storylines, which are physically self-consistent unfoldings of events or pathways, have been powerful tools in understanding regional climate impacts. We show how embedding physical climate storylines into a causal network framework allows user value judgments to be incorporated into the storyline in the form of probabilistic Bayesian priors, and can support decision making through inspection of the causal network outputs.We exemplify this through a specific storyline, namely a storyline on the impacts of tropical cyclones on the European Union Solidarity Fund. We outline how the constructed causal network can incorporate value judgments, particularly the prospects on climate change and its impact on cyclone intensity increase, and on economic growth. We also explore how the causal network responds to policy options chosen by the user. The resulting output from the network leads to individualized policy recommendations, allowing the causal network to be used as a possible interface for policy exploration in stakeholder engagements.

Fiscal resilience against disasters is vital for the recovery in the aftermath of climate hazards. Without swift access to available funds for disaster relief, damages to human and the economy would be further exacerbated. How insurance may influence fiscal performance over time and can increase fiscal resilience for today and under a future climate has not been looked at yet in detail. Focusing on the Caribbean region and on the fiscal performance of governments after disaster events, we empirically analyze the effectiveness of the Caribbean Catastrophe Risk Insurance Facility (CCRIF) regarding the reduction of short-term fiscal effects. We embed this analysis within a novel climate impact storyline approach where we produce past plausible events and investigate the usefulness of insurance under such events. The storylines were modified according to global and climate change related boundary conditions to address the issue whether the CCRIF is fit for purpose or will need to be adapted in the future. We found that both hurricane strikes and the CCRIF affect fiscal outcomes of Caribbean countries. Furthermore, there are indications that CCRIF can counteract the negative fiscal consequences over the short term period induced by the disaster. Our analysis should shed some light on the current discussions on how development related assistance can be structured to enhance climate resilience in highly exposed countries for both direct and fiscal impacts of disasters.

<p>Disseminating the effects of climate change and its potential future impacts to a wider audience is a demanding task, yet of great importance to society. Moreover, quantifying causal chains emerging from global warming is often impeded by the growth of unknown parameters related to modeling socio-economic responses. One method to obtain insights into the complex consequences of climate change is the use of physical climate storylines. Conceptually, storylines correspond to reasonable choices for the unknowns within the modeled impact transmission chain. They allow us to understand and describe the unfolding of climate-induced extreme events, making the impacts of global warming tangible to a wide range of potential stakeholders.</p><p>The RECEIPT project develops and applies the concept of climate storylines to provide risk information on climate change effects with a remote origin and an impact on European socio-economic sectors. Sectors that are being addressed within RECEIPT are the European critical infrastructure, manufacturing chains, the food system, financial markets and European international cooperation with (developing) regions. Experts within the consortium construct credible storylines for these sectors, often starting from extreme, disrupting historical events and translating these to counterfactual climate and socio-economic futures. These analyses are being published in scientific journals, but the RECEIPT consortium envisions an alternative dissemination channel to target a larger community.</p><p>The storyline visualizer (https://www.climateimpactstories.eu) is an interactive, web-based user interface, aimed at communicating physical climate storylines to an audience of informed stakeholders. The visualizer enables storyline developers in RECEIPT to structure their message into a logical progression of sections, and support each page with text, pictures, geospatial data and interactive charts. The visualizer also allows the user to explore data used within the storyline and browse through counterfactual futures. Currently, five storylines have been visualized with this platform, describing:</p><ul><li> <p>the future impacts of sea level rise and storm surges upon critical infrastructure around the French Atlantic coast, based upon storm Xynthia;</p> </li> <li> <p>increased impacts of cyclones upon European overseas territories and the sustainability of the European Solidarity Fund within this context;</p> </li> <li> <p>soy production disruptions in a warming climate and their impact on the European food system;</p> </li> <li> <p>multi-breadbasket harvest failures, locust infestations and their impact upon food security in the Greater Horn of Africa;</p> </li> <li> <p>the impact of extreme hurricanes in the Houston metropolitan area for global manufacturing chains and European industry.</p> </li> </ul><p>Implementing these studies as captivating climate storylines in the visualizer has taught us valuable lessons; one particular challenge has been to handle the growing complexity of the analyses when multiple socio-economic aspects are taken into account. Using a minimalist approach, shifting the focus towards the modeled impacts rather than the full academic reasoning, have appeared to be a useful path forward, resulting in accessible yet credible storylines of climate impacts. In this session, we plan to showcase the capabilities of the storyline visualizer, review lessons learned during the implementation process and discuss possible applications beyond RECEIPT.</p>

Robust Decision Making (RDM) is an established framework for decision making under deep uncertainty. RDM relies on the idea of scenario neutrality, namely that decision robustness is not affected by how scenarios are generated if these are uniformly distributed and span a sufficiently large range of future states of the world. Several authors have shown that scenario neutrality may not hold, but they did so by adopting either new or computationally expensive modeling. We introduce the Belief-Informed Robust Decision Making (BIRDM) framework to assess how robustness might change under an arbitrary large number of non-uniform distributions at virtually no additional costs with respect to RDM. We apply BIRDM to a flood management problem and find that alternative distributions change the robustness and ranking of measures. BIRDM allows identifying what distributions lead to these changes and under what set of distributions a measure has a specific robustness and rank.

Modelling the risk of natural hazards for society, ecosystems, and the economy is subject to strong uncertainties, even more so in the context of a changing climate, evolving societies, growing economies, and declining ecosystems. Here, we present a new feature of the climate-risk modelling platform CLIMADA (CLIMate ADAptation), which allows us to carry out global uncertainty and sensitivity analysis. CLIMADA underpins the Economics of Climate Adaptation (ECA) methodology which provides decision-makers with a fact base to understand the impact of weather and climate on their economies, communities, and ecosystems, including the appraisal of bespoke adaptation options today and in future. We apply the new feature to an ECA analysis of risk from tropical cyclone storm surge to people in Vietnam to showcase the comprehensive treatment of uncertainty and sensitivity of the model outputs, such as the spatial distribution of risk exceedance probabilities or the benefits of different adaptation options. We argue that broader application of uncertainty and sensitivity analysis will enhance transparency and intercomparison of studies among climate-risk modellers and help focus future research. For decision-makers and other users of climate-risk modelling, uncertainty and sensitivity analysis has the potential to lead to better-informed decisions on climate adaptation. Beyond provision of uncertainty quantification, the presented approach does contextualize risk assessment and options appraisal, and might be used to inform the development of storylines and climate adaptation narratives.

Tropical cyclones (TCs) cause devastating damage to life and property. Historical TC data is scarce, complicating adequate TC risk assessments. Synthetic TC models are specifically designed to overcome this scarcity. While these models have been evaluated on their ability to simulate TC activity, no study to date has focused on model performance and applicability in TC risk assessments. This study performs the intercomparison of four different global-scale synthetic TC datasets in the impact space, comparing impact return period curves, probability of rare events, and hazard intensity distribution over land. We find that the model choice influences the costliest events, particularly in basins with limited TC activity. Modelled direct economic damages in the North Indian Ocean, for instance, range from 40 to 246 billion USD for the 100-yr event over the four hazard sets. We furthermore provide guidelines for the suitability of the different synthetic models for various research purposes.

Modelling the risk of natural hazards for society, ecosystems, and the economy is subject to strong uncertainties, even more so in the context of a changing climate, evolving societies, growing economies, and declining ecosystems. Here we present a new feature of the climate risk modelling platform CLIMADA which allows to carry out global uncertainty and sensitivity analysis. CLIMADA underpins the Economics of Climate Adaptation (ECA) methodology which provides decision makers with a fact-base to understand the impact of weather and climate on their economies, communities, and ecosystems, including appraisal of bespoke adaptation options today and in future. We apply the new feature to an ECA analysis of risk from tropical cyclone storm surge to people in Vietnam to showcase the comprehensive treatment of uncertainty and sensitivity of the model outputs, such as the spatial distribution of risk exceedance probabilities or the benefits of different adaptation options. We argue that broader application of uncertainty and sensitivity analyses will enhance transparency and inter-comparison of studies among climate risk modellers and help focus future research. For decision-makers and other users of climate risk modelling, uncertainty and sensitivity analysis has the potential to lead to better-informed decisions on climate adaptation. Beyond provision of uncertainty quantification, the presented approach does contextualise risk assessment and options appraisal, and might be used to inform the development of story-lines and climate adaptation narratives.

The Earth system and the human system are intrinsically linked. Anthropogenic greenhouse gas emissions have led to the climate crisis, which is causing unprecedented extreme events and could trigger Earth system tipping elements. Physical and social forces can lead to tipping points and cascading effects via feedbacks and telecoupling, but the current generation of climate-economy models do not generally take account of these interactions and feedbacks. Here, we show the importance of the interplay between human societies and Earth systems in creating tipping points and cascading effects and the way they in turn affect sustainability and security. The lack of modeling of these links can lead to an underestimation of climate and societal risks as well as how societal tipping points can be harnessed to moderate physical impacts. This calls for the systematic development of models for a better integration and understanding of Earth and human systems at different spatial and temporal scales, specifically those that enable decision-making to reduce the likelihood of crossing local or global tipping points.

Recent research introduced the concept of climate storylines as an alternative approach to estimate climate impact and better deal with uncertainties. A climate storyline is an event-based approach which aims at building "physically self-consistent unfolding of past events, or of plausible future events or pathways". As such, climate storylines may profit from downward counterfactual thinking, which aims at analyzing how past events could have been worse. Notwithstanding the various applications of downward counterfactual thinking in the natural risk management literature, no study relates this with the climate storyline approach. The main goal of this paper is thus to introduce a framework that supports the development of climate storylines from downward counterfactuals. The framework is event-oriented, it focuses on impact, and it is designed to be applied in a participatory fashion. As a proof-of-concept application, we study the impact of tropical cyclone events on the European Union Solidarity Fund (EUSF) and do not conduct a participatory analysis. These events represent a serious threat to the European outermost regions, and their impact to the EUSF capital availability has never been studied. We find that payouts due to tropical cyclones can hamper a recovery of the fund if large payouts concurrently occur in mainland Europe. To avoid this also considering future changes, an increase in capitalization up to 90 % percent may be required.

With increasing global economic damages due to weather-related events, insurance has even more become a valuable measure to share risks and increase resilience. Insurance solutions can be designed and implemented in various forms. Among these, cross-country insurance schemes emerged in the last years. Natural catastrophe risk pools have the potential benefit of diversifying losses (thus lowering premiums) and of reducing administrative costs (as they are shared among countries). Currently, there are three catastrophe risk pools globally in place: the Caribbean Catastrophe Risk Insurance Facility (CCRIF), the African Risk Capacity (ARC), and the Pacific Catastrophe Risk Assessment and Financing Initiative (PCRAFI). In the present work we aim to study the feasibility of establishing a global risk pool and, in particular, how countries might best be grouped together to achieve the greatest diversification. As a first step, this requires an assessment of global damages. We do this using the CLIMADA impact modeling platform and estimate worldwide damages from tropical cyclones. Then, we apply extreme value analysis and assess the diversification potential of various hypothetical pools based on measures from the systemic risk literature.