In the last decades, the World experienced an increasing frequency and severity of weather-related extremes. Such events can remarkably affect multiple sectors as food, energy, and biosphere. In the framework of the activities of the ERC project EUNICE, and in order to understand the possible future impacts caused by climate extremes on population and socio-economic indicators, we firstly constructed a global database of climate indicators including eleven hazards (e.g., heatwaves, droughts, rainfall extremes, and windstorms), ranging from 1881 to 2100. For each grid point (0.5°), we provided different metrics as frequency, intensity, and number of unprecedented events at annual scale, dividing the future into five SSPs (plus two including temperature overshoot), and using the bias-adjusted CMIP6-based ISIMIP3b dataset as input. We therefore aggregated the parameters at country-scale - for each hazard - and we focused on the exposure of population and GDP to unprecedented future climate extremes, i.e. events never recorded in the past. We performed the analyses for two 30-year periods (2041-2070 and 2071-2100) and four Global Warming Levels (GWLs from 1.5 °C to 4 °C). Depending on the selected SSP and period, we present a structured ranking of countries that show the highest socioeconomic exposure to single or combined climate impact drivers. In this presentation, we also discuss the cost, in terms of cumulated events, of temperature overshoot above the 1.5 °C level to comply with Paris Agreement's goals. At a later stage, this new set of climate indicators will be also used to quantify the added value of including climate extremes in dedicated damage functions.

How to cite: Spinoni, J., Chiani, L., Dosio, A., Emmerling, J., Ghirri, J., Mastropietro, M., and Tavoni, M.: Countries with future highest exposure to unprecedented climate extremes , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18055, https://doi.org/10.5194/egusphere-egu24-18055, 2024.

Overall uncertainty in climate model projections is composed of scenario, model, and internal variability components. While scenario uncertainty is expressed by considering different climate scenarios, model uncertainty and internal variability components are largely ignored by climate information service providers. Instead, model projections are often expressed through the ensemble mean, which may lead to both overly optimistic assessments of risk, or on the other hand misinformed maladaptation strategies.

Here, we propose a new uncertainty quantification approach that better informs end users of climate projections, showing that the multi-model internal variability, owing to its chaotic nature, is in fact virtually irreducible, and that model uncertainty grows moderately throughout the 21^st century. For three future scenarios, we quantified the global internal variability of two metrics: annual precipitation (PRCP) and boreal summer average maximum daily temperature (TXJJA), by employing a single realization of each CMIP6 climate model. Our results showed that observed internal variability of the 1981-2010 period for the TXJJA metric has a negligible variation throughout the 21^st century for all three scenarios. For the PRCP metric, small changes of internal variability were detected towards the end of the 21^st century in the most adverse scenario (SSP3-7.0). Importantly, we observed that characterizing uncertainty in such manner produced a nuanced, and non-misleading results compared to that of the ensemble mean approach. Furthermore, the proposed uncertainty quantification approach can be expanded to similarly evaluate the uncertainty in indices of extreme weather.

How to cite: Gomez-Garcia, M. and Pui, A.: Demystifying model uncertainty and internal variability in climate change projections over the 21st century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18103, https://doi.org/10.5194/egusphere-egu24-18103, 2024.

Future tropical cyclone risks will evolve depending on climate change and socio-economic development, entailing significant uncertainties. A comprehensive uncertainty and sensitivity analysis of future tropical cyclone risk changes is thus vital for robust decision-making not least in the context of physical climate risk disclosure. However, the outcomes of such uncertainty and sensitivity analyses are closely tied to the chosen model setup, warranting caution in interpretation and extrapolation. Our study investigates how four distinct tropical cyclone hazard models as well as alternate representations of socio-economic development influence future tropical cyclone risks. We find that average tropical cyclone risk increases 1-5% by 2050 across all models and global study region. But the estimated maximum risk increases by the end of the century range from 10-400% depending on the hazard model choice. Such diverging results are critically relevant for climate risk assessment in the financial and insurance sectors where usually model choices are made a priori and uncertainties are not quantified systematically. Additionally, socio-economic factors drive risk increase more strongly across all models, while the uncertainty in these risk drivers is hazard model-specific. For instance, the MIT model-based results are sensitive to the choice of global climate model, while estimates from CHAZ, STORM, and climate-conditioned IBTrACS are mainly influenced by exposure scaling based on Shared Socio-economic Pathways. Finally, we assert that quantitative estimates of uncertainty and sensitivity to model parameters greatly enhance the value and depth of climate risk assessments, which are essential for robust decision-making in the financial and insurance sector.

How to cite: Meiler, S., Kropf, C., Emanuel, K., and Bresch, D. N.: Choose Your Model Wisely: Navigating Uncertainties in Future Global Tropical Cyclone Risks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3055, https://doi.org/10.5194/egusphere-egu24-3055, 2024.

Climate physical risk assessment is crucial to inform adaptation policies and finance. However, science-based and transparent solutions to assess climate physical risks are still missing. This is a main limitation to fill the adaptation gap. We provide a methodology that quantifies physical risks on geolocalized productive assets, considering their exposure to both chronic and acute impacts (hurricanes) across the scenarios of the Intergovernmental Panel on Climate Change. Then, we translate asset-level shocks into economic and financial losses. We illustrate the methodology in an application to Mexico, a country that is highly exposed to physical risks, and attracts adaptation finance and foreign investments. We find that investor losses are underestimated up to 70% when neglecting asset-level information, and up to 82% when neglecting acute risks. Therefore, neglecting the asset-level and acute dimensions of physical risks can lead to large errors in the identification of the relevant adaptation policy response, investments and finance tools aimed to build resilience to climate change.

How to cite: Bressan, G., Duranovic, A., Monasterolo, I., and Battiston, S.: Asset-level assessment of climate physical risk matters for adaptation finance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2381, https://doi.org/10.5194/egusphere-egu24-2381, 2024.

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.

How to cite: Guillod, B., Ciullo, A., Bourgeois, Q., Bodenmann, L., Lehtomaa, J., and Glink, S.: Multi-hazards risk indicators for climate risk reporting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18364, https://doi.org/10.5194/egusphere-egu24-18364, 2024.

Climate change induced extreme precipitation poses a significant threat to agricultural production. Such impacts extend beyond local agricultural production regions, generating remote and cross-sector impacts that disrupt global supply chains (GSCs). While the direct impacts of extreme precipitation on agricultural production have been widely studied, how such local impacts cascade through supply chain networks to remote places remains elusive, partly because of the complex interdependencies within the global trade systems. To address this, we propose a Resilience Enhancement in Supply Chains Under Environmental Shocks (RESCUES) framework. RESCUES couples an agricultural production loss model with a dynamic recursive economic network model. It allows us to identify channels through which the impacts of climate change on agricultural production propagate along GSCs to interconnected sectors and regions. We design nine climate shock scenarios (i.e., dry, wet, and compound precipitation anomalies with extreme, severe, and moderate levels of severity) using the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) under two Shared Socioeconomic Pathways (SSPs) scenarios (SSP126 and SSP585). We then use RESCUES to simulate the GSCs dynamics over 2016-2050 under these nine scenarios. We find that direct agricultural losses driven by local precipitation anomalies can spread through GSCs to a wider range of countries and regions across the globe, creating large spatial spillover effects with direct and indirect economic losses. We estimate that the averaged per event total value-added (VA) losses caused by compound extremes is around $20.4/22.6 billion under SSP126/585, followed by dry extremes ($16.4/15.0 billion) and wet extremes ($8.7/11.6 billion). Moreover, the global distribution of direct and indirect losses exhibits high spatial heterogeneity. Countries with large agricultural outputs tend to have both high direct and indirect VA losses, especially in China, India, the United States, Russia, and Brazil. In contrast, poorer countries, such as Tanzania, Sudan, Myanmar, Yemen, Afghanistan, and Nepal, experience relatively larger direct losses, while rich regions heavily dependent on agricultural imports, including Hong Kong, Qatar, and Singapore, suffer relatively larger indirect losses. Considering that nations frequently implement export restrictions to ensure food self-sufficiency, we further design a hypothetical scenario to assess the global trade and economic impacts of near-term (2025-2030) agricultural export restrictions in four key food production regions (China, India, the United States, and Indonesia) under extreme precipitation anomalies. Our study highlights the importance of an integrated and comprehensive assessment of the risk footprint of climate change-related shocks, encompassing both direct and indirect impacts on GSCs. 

How to cite: Zhang, S. and He, X.: Vulnerabilities of Global Supply Chains to Agricultural Production Disruptions Caused by Individual and Compound Climate Shocks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6973, https://doi.org/10.5194/egusphere-egu24-6973, 2024.

While tipping points in the Earth system are recognized in the public and policy debate as one of the major risks of anthropogenic climate change, our current knowledge of their dynamics involves a broad range of uncertainties, and so far there is no systematic risk assessment quantifying the likelihood as well as the impacts of exceeding tipping points in the Earth system. 

Here we introduce the Tipping Point Modelling Intercomparison Project (TIPMIP, www.tipmip.org), a major international initiative setting out to fill this gap in a multi-model approach: Based on ensembles of simulations with Earth system models as well as offline models combined with current observations, the experiments will serve to assess (1) the risk of crossing critical thresholds in the Greenland and Antarctic ice sheets, the Atlantic Meridional Overturning Circulation, tropical and boreal forests as well as high-latitude permafrost; (2) the short- and long-term (committed) impacts of crossing individual tipping points; (3) the (ir)reversibility of impacts on different timescales; and (4) the role of the forcing rate. TIPMIP also sheds light on potential model shortcomings when it comes to such highly-nonlinear dynamics in the Earth system which may significantly change projections for the 21st century and beyond. 

The TIPMIP outcome will serve to generate a risk map, highlighting regions in the world which are most vulnerable to tipping transitions, which will be an important basis for forward-looking policy decisions. 

How to cite: Winkelmann, R., Dennis, D., Donges, J., Loriani, S., Sakschewski, B., and Rockström, J.: The Tipping Point Modelling Intercomparison Project (TIPMIP), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17399, https://doi.org/10.5194/egusphere-egu24-17399, 2024.

While financial investors are increasingly alert to the economic threats of climate change, most academic and regulatory assessments of financial risk have not accounted for climate tipping points. Here, we combine recent advances in the integrated assessment modeling of tipping points with return projections for major stock indices to assess index-specific risk exposures to climate change damages. We find that for the MSCI World, a globally diversified stock index, tipping points increase the expected loss due to climate change damages under SSP2-4.5 by 62% (USD 0.2 trillion)—a magnitude comparable to moving from meeting the Paris targets to the "hothouse world" scenario RCP8.5. The reason is that investment horizons are more affected by near-term risks of tipping points than by long-term differences in mitigation outcomes. Risk increases are driven by methane-related tipping points (permafrost thaw and ocean methane hydrates) and ice sheet disintegration, with the highest increases for investments in emerging markets with extensive coastal areas, such as India or Indonesia. The absolute magnitude of financial risks varies substantially across damage functions and assumptions regarding damage persistence. However, the relative importance of tipping points is robust across different damage specifications and investor discount rates. Therefore, our results call for integrating tipping points into climate scenario analyses in the financial sector and climate risk stress tests by regulators.

How to cite: Waidelich, P., Klaaßen, L., Battiston, S., and Steffen, B.: The risks of climate tipping points for financial investors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5217, https://doi.org/10.5194/egusphere-egu24-5217, 2024.

Biodiversity loss and ecosystem degradation could pose a substantial threat to financial stability and the wider economy. Despite scientific evidence of the ongoing ecosystem degradation, methodological and data challenges have so far prevented a detailed assessment of the economic and financial risks.  While progress has been made in assessing climate change related risks, our understanding of the linkages between the economy and ecosystem service degradation is still limited. Here we pioneer a nuanced approach to understanding the emerging financial risks of ecosystem change.  Using the LPLmL-MAgPIE-SEALS modeling framework, we assess physical, transition and financial risks considering feedbacks from climate change, land use, and degrading ecosystem services. Focusing mainly on the EU, we also assess interconnectedness with other global regions where loss of ecosystem services is more pervasive. Our framework includes climate-sensitive spatially explicitly biophysical data within a partial equilibrium land-system model. Modelled land-use patterns are downscaled to derive fine-scale changes in ecosystem service supply and associated economic feedbacks. We assess various scenarios that build on the existing NGFS (Network for Greening the Financial System) framework. These scenarios range from a degraded world without policy interventions, to an integrated climate-nature scenario, with ambitious policies to mitigate both climate and ecosystem service change. The results indicate diverging biodiversity response based on varying climate and nature policy ambition, emphasizing the need to extend biodiversity safeguarding beyond exclusive reliance on climate mitigation policies. Financial risks are assessed through an analysis of sectoral dependencies on various ecosystem services, laying out the basis for a comprehensive framework that supports informed decision-making facing emerging climate and nature-related risks.

How to cite: Stevanovic, M., von Jeetze, P. J., Johnson, J. A., Ceglar, A., and Popp, A.: Navigating Nature and Climate Risks: An Integrated Framework for Economic Assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10342, https://doi.org/10.5194/egusphere-egu24-10342, 2024.

There has been increasing focus on climate risk disclosure within the industry, evidenced by a shift from guidance (TCFD) to standards (ISSB) based approach.  However, surveys show that climate scenario modelling remains challenging, with high complexity and lack of expertise cited as key reasons.

While there are global scenarios such as NGFS to support practitioners by providing key analytical foundations and parameters, concerns have been raised regarding the robustness of physical and transition risk assessment methodologies, and hence the fitness for such scenarios.  Given that the primary aim of climate scenario analysis at an entity level is to inform prudent risk management and business strategy, it is instructive to explore fundamental questions and context around the design of these scenarios, leading to an improved interpretation of end results.

To this end, we aim to critically review the fourth iteration of NGFS scenarios that have recently been released, with a particular focus on 3 areas: First, the evolution of scenarios since the first vintage in 2020. Secondly, the design limitations of IAMs which do not feature frictions that could allow for misprinting and price bubbles. Thirdly, we discuss how the scenario design could benefit from incorporating uncertainty into its variable projections.

How to cite: Werner, S., Pui, A., and Tomita, M.: NGFS scenarios: Scope, design limitations and gaps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13865, https://doi.org/10.5194/egusphere-egu24-13865, 2024.

Climate change and biodiversity loss are not happening in isolation. The erosion of natural capital by human activities will compound and amplify physical climate risks, and vice versa. We present new analyses that demonstrates that ignoring nature in physical climate financial risk assessment will lead to significant underestimates of the scale of the risks. This has implications for financial institutions and for the prudential policies of Central Banks and supervisors. We develop the first set of integrated climate-nature scenarios to explore the potential scale of physical risks, building upon the NGFS conceptual framework, alongside a global risk assessment approach that combines the ENCORE tool with global natural capital datasets and a multi-regional input-output modelling approach. We produce estimates of risks for five ecosystem services - surface water, ground water, pollination, air quality and water quality - across 7 sectors and 44 countries and 5 rest of world regions. Our analysis suggests that nature-related risks are material in scale, exceeding $7 trillion value at risk. Based on analyses of historical analogues and risk transmission channels we show that nature and climate risks are strongly interconnected and share characteristics in their potential for non-linear, cascading impacts. We propose a set of principles for scenario analysis and a framework for developing decision-relevant scenarios, including an inventory of almost eighty potential nature-related physical risk shocks (hazard-primary economic receptor pairs) that can form the basis to scenario development.

How to cite: Alvarez, J., Ranger, N., Freeman, A., Harwood, T., Obersteiner, M., Paulus, E., and Sabuco, J.: The Green-Scorpion: a preliminary study on the potential amplification of physical climate financial risks by nature-related risks and feedbacks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12089, https://doi.org/10.5194/egusphere-egu24-12089, 2024.

The realisation that climate change threatens economic systems has led investors, standard-setters and regulators to call on businesses to assess their exposure to climate-related risks, and to disclose the financial impact of these in their annual reports and financial statements where material. Indeed, mandatory disclosure requirements have already been implemented in some jurisdictions and are being proposed elsewhere. Mandatory disclosure of physical climate risk by a single business predisposes that the business can reasonably assess this risk. Here, we use the analogy of a spider’s web to examine how changes in the frequency and magnitude of extremes, that break parts of the web, combine to affect the efficiency of a hypothetical business. We demonstrate that the precise location of an extreme event, the precise characteristics of the event, and whether a subsequent event occurs close to or distant from an earlier event strongly influences vulnerability. In short, to estimate the impact of climate change induced extremes on a business requires not merely the general frequency of events, but the precise geolocation of the event mapped on the vulnerabilities of the business. We conclude that mandatory disclosure of future climate risk by a business cannot be other than deeply uncertain and this is not resolvable via foreseeable advances in global or regional climate modelling.

How to cite: Pitman, A., Saribatir, E., Greenhill, C., Green, S., and Pitman, S.: Assessing the risk of climate change to a business, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2056, https://doi.org/10.5194/egusphere-egu24-2056, 2024.

Climate change is a risk to the financial stability of countries. The economic impacts of rising temperatures, increasingly frequent and intense extreme events, as well as the costs of adapting to these risks have the potential to significantly strain government (sovereign) finances. Perceived national climate risk hotspots may also discourage investment, reduce economic growth, and increase global inequality. To gauge sovereign financial risk, investors rely on sovereign credit ratings that assess a nation’s ability to repay its debt. A country’s credit rating determines its borrowing costs, influences investor confidence, and has impacts on economic stability and growth.

Recent estimates show that climate-induced sovereign credit downgrades could materialize for nearly 60 countries by 2030 (Klusak et al, 2023) because of the labour productivity impacts of increasing temperatures (Kahn et al, 2021). These sovereign climate risk estimates are severe, yet likely still an underestimate, as they do not consider the materialization of extreme events (acute climate risk) (Stern, 2016).

In this study, we provide new estimates of climate-induced sovereign credit downgrades by combining the sovereign climate risk model developed by Klusak et al. (2023) with models of acute climate risk. We focus on countries in south-east Asia and calculate the extreme losses from river floods and tropical cyclones under different future warming scenarios and the implications for sovereign credit risk. We also explore different options to adapt to these risks nationally, their associated costs, and model the risk reduction benefits of their implementation.

There is a failure to integrate extreme climate risk into economic and financial assessments (Stern et al, 2022). Many of these risks are underestimated in the current financial assessment of climate change (Trust et al, 2023) and may support more credible assessments of short-term risk. Our findings add to the growing body of work highlighting the importance of considering acute climate risk in estimates of climate financial risk (Pittman et al, 2022). We also show that adaptation can significantly reduce future losses and resultant sovereign credit risk, which serves as evidence against divestment from risk-prone countries and for investment in adaptation. We conclude by exploring the fiscal policy implications of our analysis for Thailand.

How to cite: Bernhofen, M., Burke, M., Ranger, N., and Shrimali, G.: Physical climate risk, sovereign credit ratings, and the benefits of adaptation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12339, https://doi.org/10.5194/egusphere-egu24-12339, 2024.

The last decade has witnessed a surging occurrence of extreme heat worldwide. This can directly dampen local production capacity and also induce indirect repercussions through the global supply network. Yet, the cascading effect of region-specific extreme heat may differ greatly, which is by far poorly understood. By combining temperature observations with Acclimate—a dynamic agent-based model, we identify the region-specific temperature threshold for dampening local production and investigate the response of the global supply network to extreme heat in a region-by-region manner. Economic agents with significant repercussions on the globe are identified and indirect benefits along the global supply network from local heat adaptation are revealed. The outcome of this study supports common but differentiated adaptation strategies towards extreme heat.

How to cite: Wu, X., Quante, L., and Levermann, A.: Indirect impacts of region-specific heat extremes along the global supply network , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11412, https://doi.org/10.5194/egusphere-egu24-11412, 2024.

The socioeconomic impacts of compound extremes are sudden, severe, and multidimensional. Without precautionary measures, social and economic safety nets including community support and insurance, the negative effects of a single, short-run shock on households can extend to the long-run and persist over many years. Studies on the impacts of compound extremes have focused on objective measurements of well-being, including income, health, education; with much fewer studies on subjective well-being. Looking into subjective well-being takes an evaluative perspective on the quality of life, wherein the recovery from a disaster takes more than just the return to employment, for instance. Previous studies have shown that subjective well-being is also a good predictor of life expectancy, productivity, educational performance, and voting behaviour. Using econometric methods on sub-national, household panel data from the EU Survey of Income and Living Conditions (EU-SILC) and a composite index for the simultaneous occurrence of droughts and heatwaves, I quantify and compare the impacts of compound dry-and-hot events (CDHE) in Europe on objective and subjective measurements of well-being. The results of this study provide new information on the magnitude, as well as, the persistence of effects from CDHE, based on both the traditional income-based measurements versus the self-reported measurements of well-being.

How to cite: Schleypen, J. R.: The Impact of Compound Hot-and-Dry Events on Household Well-being, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7412, https://doi.org/10.5194/egusphere-egu24-7412, 2024.

Driven by regulations to understand and attempt to mitigate risk from climate change there is an increase in demand for climate risk data from the financial sector. This has led to the generation of 3rd party data providers, such as Climate X, who aim to bridge the gap between academic research and the requirements of the financial sector. This requires a multi-disciplinary team bringing together hazard, remote sensing, and climate scientists which allows us to combine open-source earth observations and climate model data with in-house hazard modelling to generate metrics and losses that are useful and useable for our clients.

In this talk we will cover the key requirements of our clients: asset-level and global intelligence, multi-hazard and loss information and multiple scenarios. We will outline how we address these, and how academic researchers can engage with the private sector to make their work as relevant as possible.

How to cite: Reveley, G., Brennan, J., Woodhouse, S., Ramsamy, L., Leach, N., Sullivan, P., Davies, J., and Stables, J.: Climate services for finance, lessons learned and feedback for the public sector, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15905, https://doi.org/10.5194/egusphere-egu24-15905, 2024.

In the ECB top-down, economy-wide climate stress test, we developed novel damage functions to measure damages to physical capital from different natural hazards at granular firm-level. Combining address-level, forward-looking physical risk scores from Moody’ Four Twenty Seven with projected damages from acute and chronic physical risk from NGFS, we translated firms’ exposure towards floods, wildfire and sea level rise risk to future losses on their physical capital. Using loan-level information from the euro area credit registry, we assessed the deterioration in firms' profitability and indebtness due to physical damages and subsequently the change in default probabilities and expected losses on banks' corporate loan portfolios.  The dataset is unprecedented in terms of coverage, integrating both regulatory and private data sources and comprising financial and climate risk data for a total of 2.6 million European firms and 1,600 euro area banks, covering around 80% of total loan exposures of the euro area regulatory credit registry.  

Losses from physical risk were calculated as the product of firms’ future exposure towards the frequency and intensity of wildfire risk, flood risk and sea level rise and combining this with the expected physical damages as a share of GDP from the NGFS scenarios. Annual firm-level losses from physical risk were calculated between 2020 and 2050 and for three different scenarios, i.e. the NGFS Net Zero 2050, Delayed Transition and Current Policies scenarios. The results show that acute physical risk will lead to moderate to high damages on firms’ physical capital in the long term, depending on the expected temperature increase of the scenario in question. By 2050, damages will be disproportionately higher in a Current Policy scenario relative to the other scenarios, leading to a maximum deterioration of 3% of firms’ assets compared to a maximum deterioration of 1% in a Net Zero 2050 scenario. The results show that until 2050, the credit risk of borrowers most vulnerable to physical risk is around 25% higher in a Current Policy scenario relative to a Net Zero 2050 scenario.

How to cite: Emambakhsh, T.: Measuring physical damages from natural hazards in the ECB top-down, economy-wide climate stress test , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4075, https://doi.org/10.5194/egusphere-egu24-4075, 2024.

Projections of economic damages from climate change are key for evaluating the benefits of climate mitigation and informing discussions around adaptation needs. So far, global and country-level top-down assessments of GDP damages have focused on annual mean temperature changes and annual precipitation. Recent backward-looking studies have identified further impacts of variability and extremes in precipitation and temperatures on income growth.

Here, we examine GDP impacts and uncertainties under different global warming levels by combining empirical dose-response functions for temperature variability, rainfall deviations, and extreme precipitation with climate projections of 33 CMIP6 models. The main contribution of this work is to understand the projected relative contributions of multiple climate variables under many possible future climates.

We find that at a +3°C global warming level, global average losses reach 10% of GDP, with worst effects (up to 17%) in poorer, low-latitude countries. Relative to annual temperature damages, which find to seemingly capture heat wave impacts, the additional GDP impacts of projecting variability and extremes are relatively small and dominated by inter-annual variability, especially in lower latitudes. However, accounting for variability and extremes when estimating the temperature dose-response function still raises global GDP losses by nearly 2%-pts and exacerbates tail risks for economic growth.

Our results call for region-specific risk assessments and complementary research into climatic extremes not considered here, including their indirect effects on temperature dose-response functions. Additionally, it will be very important to further the work on understanding historical and future persistence and adaptive capacities for these different impact channels.

How to cite: Kikstra, J., Waidelich, P., Batibeniz, F., Rising, J., and Seneviratne, S.: Climate damage projections beyond annual temperature, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18139, https://doi.org/10.5194/egusphere-egu24-18139, 2024.