Climate change remains one of the greatest challenges of the 21^st century. Humans are not only the key driver of climate change, but are also affected by its consequences, with profound impacts on human life arising through changes in environmental and social circumstances. Climate change impacts on human behaviour are observed via two principle data types which both reflect daily human activity: social media and mobility data. Specifically, social media data are employed to analyse temperature impacts on hate speech online. Even though links between temperature and physical aggression are known, it remains unclear how these patterns extend to online environments, where hate speech can have detrimental consequences for the mental health of the affected persons. Using machine learning classifiers to identify hate speech in four billion geolocated tweets, we show that temperature has strong non-linear impacts on the occurrence of online hate speech across the USA with hate-tweet levels remaining low at moderate temperatures but sharply rising during both hot and cold extremes. This pattern persists across income groups, religious beliefs, and election outcomes and even various climate zones, including those where heat is common which suggests adaptation limits to hot temperatures. A complementary analysis for six European countries finds quasi-quadratic, nonlinear temperature impacts on digital racism and xenophobia across Europe. To assess not only the impacts of heat but also the ability to adapt we employ mobility data from New York City. An analysis of daily passenger data of more than 400 subway stations over six years shows that there is not only a strong, non-linear temperature impact on subway usage but also disparities between neighborhoods with respect to the capacity for heat mitigation. Correlations between neighbourhood-level mobility reductions and socioeconomic indicators suggest that the ability to reduce mobility on hot days is afforded by those that also hold other privileges, hence leading to unequal, compounding health impacts in disadvantaged neighbourhoods. Finally, we harness a combination of mobility data, Google search trends and Covid-19 data to explore how behavioural responses may develop under a prolonged or repeated risk exposure. The econometric approach explores changes in the response to Covid-19 risk through two channels: risk perception and the resulting behavioural response, i.e. mobility reduction. Across both channels, the risk response diminishes over time even before the availability of vaccines. This highlights the attenuation of behavioural responses to prolonged risks, with implications for managing long-term crises such as increasingly repeated exposure to weather extremes under ongoing climate change.

How to cite: Stechemesser, A.: Living in a warming world – climate impacts on society , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21492, https://doi.org/10.5194/egusphere-egu24-21492, 2024.

Extreme events (e.g., heatwaves, wildfires, droughts, floods, etc.) are anticipated to become more severe, persistent, and frequent throughout many parts of the world due to warming. Such extreme events occur across a diverse set of ecosystems and climatic regions and their multifaceted impacts cascade in space, time, and across sectors (e.g., water, energy, agriculture, economic, human health). To better understand the cascading impacts of extreme events and their feedbacks, we draw on recent examples such as the 2023 heatwaves and wildfires in Canada. In addition, we also examine other extreme events (e.g., droughts, floods) around the world and their feedbacks and interactions that pose challenges for modeling, monitoring, and managing associated risks. For example, we quantify how snowpack changes and drought across agricultural regions have wide-reaching impacts that affect remote areas. Our study highlights that the impacts of extreme events have important feedbacks that should be considered in resource and risk models and management as well as remote impacts that are not yet fully understood or well-tracked. Furthermore, we identify other challenges, existing knowledge gaps, and future directions to guide global monitoring and modeling of impact cascades for improved mitigation, adaptation, and climate change resilient policy advancements.

How to cite: Huning, L. and Brunner, M.: Cascading impacts of extreme events across an interconnected and warming world, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14111, https://doi.org/10.5194/egusphere-egu24-14111, 2024.

The complex interplay between environmental and anthropogenic factors across the globe results in differing impacts of climate and weather related disasters. Communities living in deprived socioeconomic conditions are usually subjected to severe impacts, as they are more vulnerable to disasters. However, in a world of rapid natural and anthropogenic change, this is not the only cause behind amplified risks and impacts. The aim of this study is to identify the pivotal global-scale factors that make a significant contribution to the impact severity of climate disasters.

Using an expansive dataset with disaster impact records, complemented with socioeconomic indicators and climate variables from >6000 events in >150 countries, our work is a global-scale investigation of the roles of hazard severity, exposure, and vulnerability influencing the impacts and risk of climate disasters. We use a spatio-temporal stratified approach to define hazard severity, exposure, and vulnerability with relevant variables at the local, regional and global levels. Then, we determine the main factors contributing to impact severity across regions and disaster types using a robust machine learning pipeline.

This study illustrates the importance of considering comprehensive aspects of risk in order to build resilient societies to climate extremes. Our research contributes to advancing scientific understanding of the drivers of climate disaster impacts, with the aim of developing more effective policies. It highlights the importance of integrating diverse data sources and advanced analytical methods to better anticipate, prepare for, and respond to the multifaceted challenges posed by climate disasters in a changing climate.

How to cite: Teber, K., Montero, D., and Mahecha, M. D.: An assessment of global-scale drivers of climate disaster impacts and risk, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10132, https://doi.org/10.5194/egusphere-egu24-10132, 2024.

The distribution of temperature and precipitation has been shown to impact economic productivity all around the world.
These heterogeneous patterns change under future warming and impact consumers not only locally but also remotely through supply chains. Due to the possibility of a non-linear economic response, these effects are difficult to quantify and have been subject to limited empirical assessment focusing on direct impacts of weather extremes.
Here we show in numerical simulations of weather-induced production disruptions (of more than 7000 profit-maximising producers and utility-optimising consumers with more than 1,8 million supply linkages) that, under present-day climatic conditions, consumption loss risks resulting from production disruptions propagating through the economic network are larger for lower than for higher income groups within countries. Comparison between countries shows that risks are larger for medium-income countries than for low and high-income countries, which emerges from differing trade dependencies as well as heterogeneous exposure and response.
Projecting observed econometric relations of weather variability and economic productivity until 2040, we find an amplification of loss risks due to near-term climate change in most regions. This amplification increases with income for middle and high-income countries, while it is homogeneous across income groups in low-income countries. 
Global warming thus poses an increasing challenge to consumers through supply chains around the globe which needs to be addressed by fostering resilience. To avoid further harm to productivity and consumer welfare the climate has to be stabilised. 

How to cite: Quante, L., Willner, S., Otto, C., and Levermann, A.: Global economic impact of weather variability on the rich and the poor, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9524, https://doi.org/10.5194/egusphere-egu24-9524, 2024.

During Hurricane Katrine in New Orleans in 2005, the failure of telecommunication systems was a disaster by itself, creating chaos and seriously hampering mitigation measures during and directly after the event. Half of the telecom towers was destroyed by the heavy wind, the electrical grid was destroyed and an area as large as The Netherlands and Belgium combined was flooded. The rest of the telecom towers ceased operation 48 hours later, when their backup power was depleted. In some parts of New Orleans the water stood 4.5 meters high, and debris was making roads impassable, blocking emergency repairs. This created a disaster in a disaster, leaving local authorities and first responders without intercommunication and status updates, rendering well-informed and coordinated actions impossible.

Similarly, during Hurricane Irma in 2017, on the island of St. Maarten, 50% of the telecom towers were blown over, seriously hampering communications in large sections of the island. Fortunately, the sea cables connecting the island to the rest of the world remained unharmed, although even that was a close shave. Therefore, while the mobile phone network failed in large areas, the Emergency Support Functions of the government could still communicate with the outside world via the internet, to ask for support and specific equipment for emergency repairs (such as new telecom towers).

Similarly, after the Nepal earthquake in 2015, roads were rendered impassable by debris and all telecommunication networks were silenced, and the electrical grid destroyed. The first messages to the outside world were conveyed by radio amateurs, via ionospheric radio. Several inland villages remained isolated for several days, with no means to issue a call for assistance or medical help.

Despite these and other examples, most of the models and impact chains drawn by scientist to investigate disaster events ignore the role of telecommunication failure that aggravates the situation in the field. Also, scientific tools to predict risks and support decisions when the disaster unfolds and directly after it, are often provided via internet links, ignoring the likelihood of them being inaccessible when they are needed most, due to a telecom blackout.

It is therefore of the utmost importance to draw more attention of researcher to the role of telecommunications in impact chains, even when that is not their direct competence, and to interact with telecommunication experts and emergency organizations in the field to better prepare for telecommunication failure during and after disasters. A good example of such an initiative was shown in PARATUS, a scientific project on societal resilience, where information gathering on St. Maarten specifically included telecommunication during disasters. Crossing these boundaries between sectors will greatly amplify the practical impact of the scientific work.

How to cite: Witvliet, B.: Telecommunication – a blind spot in disaster resilience science, yet essential for disaster mitigation and recovery, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6634, https://doi.org/10.5194/egusphere-egu24-6634, 2024.

In the 21^st century, an increasing global population will be exposed to various risks caused by climate change. The impact depends not only on the geophysical climate change hazards, but also on the population’s vulnerability, its spatial distribution, and its capacity to adapt. Here we present a new database of climate impact indicators at various global warming levels (1.2 - 3.5°C) using global climate and hydrological model data from the latest Coupled Model Intercomparison Project (CMIP6) and Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b) simulation rounds.

Indicators include a variety of temperature and precipitation extremes, heatwaves, drought intensity, hydrological variability, and water stress. Building on previous work (Byers et al. 2018),  the first novel aspect of this work is the development of a bi-variate hazard index that includes statistics on the absolute hazard level (e.g. low or high precipitation) and the relative change under global warming compared to the historical baseline (e.g. a large change from low to high precipitation).

We combine this new index with gridded projections of population from the Shared Socioeconomic Pathways (SSPs) and land area to calculate temporal and spatial exposure.  Finally, to allow for risk assessment, we introduce the layer of vulnerability measured through various socio-economic indicators, such as income, inequality, or the Notre-Dame Global Adaptation Index (ND-GAIN).

In aggregate, we find that impacts manifest substantially even in the near-term at lower global warming levels. For example, even at 1.5°C 93% of the population of South Asia will face a medium exposure to heatwave events. Countries predominantly in the low latitudes and global south are comparatively more severely affected by multiple climate impacts. The window for reducing the risk burden is rapidly closing while there is substantial unavoidable risk even at 1.5C, thus adaptation actions will be key. By analysing impact and vulnerability hotspots, our work can help identify these adaptation needs, i.e. for financial assessments or loss and damage, down to high spatial resolution but also at the country level. With further categorisation, we can assess populations at the highest risk, such as those with high impacts, high vulnerability and lowest institutional governance capacities.

How to cite: Werning, M., Byers, E., Hooke, D., Andrijevic, M., Krey, V., and Riahi, K.: Comprehensive assessment of hazard, exposure, and vulnerability using a new database of climate impact indicators to identify hotspots for adaptation needs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17789, https://doi.org/10.5194/egusphere-egu24-17789, 2024.

More frequent, intense, and prolonged temperature extremes due to climate change increase the risk of human morbidity and mortality. However, public perception of these risks is often low, while people's awareness is crucial to reducing the health impact of temperature extremes. News media plays a key role in raising awareness by providing essential information on heat waves and cold spells such as releasing warnings, sharing weather forecasts, and discussing impacts. Any sentiment conveyed within newspaper articles about temperature extremes, either through positive, negative, or neutral phrasing, can influence the audience's perception of risk and, potentially, their actions. Newspaper coverage of temperature extremes and the related sentiment may be influenced by multiple factors other than the actual temperature anomalies, such as political alignment or editorial decisions, but also potentially the countries’ vulnerability to climate change. 

In this study, we analyze and compare the sentiment of temperature-related newspaper articles in eight countries (Israel, Malaysia, New Zealand, Philippines, Singapour, Pakistan, South Africa, and the United Kingdom) with different climates and societal vulnerabilities to climate change (food, water, health, ecosystem services, human habitat, and infrastructure). We consider leading English language, national newspapers and use daily maximum temperature data from the day of each article’s publication from the ERA5 reanalysis. The sentiment is determined in an automated way based on the fraction of positive and negative words in text. In addition to the sentiment, we determine whether or not each article mentions climate change. 

We find clear differences during times of extreme temperatures versus times with near-normal temperatures in all countries. During days with comparatively cold or warm temperatures (i) more temperature-related articles are published, (ii) their sentiments are more negative, and (iii) climate change is mentioned less frequently. While the latter finding is surprising, it suggests that there are unobserved confounding factors that require further research, which might relate to other events and anomalies occurring simultaneously. A comparison of the results across countries shows more negative sentiment and fewer mentions of climate change in countries with higher climate change vulnerability. Being aware of these media reporting patterns of extreme temperatures may help media outlets reassess their role in aiding public health responses.

How to cite: Bogdanovich, E., Schäfer, M. S., Brenning, A., Reichstein, M., De Polt, K., Guenther, L., Frank, D., and Orth, R.: Increased temperature-related newspaper coverage and more negative sentiment during hot and cold extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7883, https://doi.org/10.5194/egusphere-egu24-7883, 2024.

There are numerous efforts globally to enhance societies’ ability to prepare for and cope with disasters triggered by natural and human-made hazards such as heatwaves, flash floods, terrorist attacks, or earthquakes. Some of these efforts aim to enhance the effect of warnings by personalizing them. By addressing individual factors such as health issues and caregiving responsibilities and including tailored behavioral recommendations, they can become more inclusive. However, the compilation of these personalized warnings requires data, which can either be generated by a (one-time) query or extracted from individuals’ digital footprints. Thereby, the following key questions arise: Is there a desire for personalized warnings? Do these warnings improve safety culture, enhancing preparedness and responses in the face of disasters? Moreover, is the public aware of the type of data required to receive such warnings?

We will answer these questions by the means of a representative online survey in Switzerland with a between-subjects experiment by assigning participants to personalized heat warnings. It allows us to assess if people would like to receive personalized warnings and whether those warnings influence their intention to take protective measures and enhance inclusiveness. Further, we will analyze people’s data sharing preferences, their trust in warnings, and the influence of their online behavior (e.g., online-shopping, use of smart watches) on their preference for those warnings. Moreover, we will assess participants’ demographics to find patterns in what type of data different social groups are willing to share.

In our talk, we will present the first results of this survey and discuss implications for the further development of personalized warning messages.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101021746

How to cite: Kuratle, L. D., Dallo, I., and Marti, M.: Personalized warnings – Swiss public’s preferences and needs , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2158, https://doi.org/10.5194/egusphere-egu24-2158, 2024.

Extreme weather events lead to many adverse societal, economic, and environmental consequences. Anthropogenic climate change has been identified as a factor that, in many cases, increases the frequency and intensity of these weather extremes. In the last two decades, the methods of Extreme Event Attribution (EEA) have been used to quantify the extent to which climate change affected the nature of specific recent extreme weather events. More recently, these methods are being combined with socioeconomic impact data to quantify extreme weather’s impacts attributable to climate change in what we term Extreme Event Impacts Attribution (EEIA). EEIA is a quickly developing field that considers which kinds of questions about the impacts of climate change on extreme weather events we should ask, what methods are best suited to answer them, how to interpret the results these methods provide, and what purpose these results can serve. In this survey, we discuss the basic structure and methods of EEIA, review the results of the existing EEIA studies, and discuss the implications and outlook for this strand of research including its relevance for quantification of climate change costs, the Loss and Damage Fund, climate litigation, or adaptation planning.

How to cite: Noy, I., Stone, D., and Uher, T.: Extreme Event Impact Attribution: The state of the art, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1616, https://doi.org/10.5194/egusphere-egu24-1616, 2024.

Cities are facing increasing challenges of flood risk due to combined effects of climate change and socioeconomic development. At the same time understanding of the complexity of urban flood risk is still limited, hampering decision-making and effective urban adaptation planning. A socio-ecological system (SES) perspective offers a promising approach to analyze risk as a non-isolated entity by recognizing human and natural systems as complex and coupled structures and considering their interactive dynamics (e.g., delays, feedbacks, and non-linearity). Qualitative system dynamics modeling tools, such as causal loop diagrams, are particularly useful for this, as they allow the inclusion of different kinds of system variables.

This study applies a qualitative system dynamics modeling framework to holistically investigate urban flood risk under climate change and barriers to adaptation in a coupled SES using the city of Hamburg as a case study. The study deals with urban flood risk in the context of ‘water from 4 sides’ addressing questions in the growing research field of climate hazard interactions and compound risks. In a stepwise approach, a qualitative system dynamics model was developed based on an integrated interdisciplinary knowledge of researchers. Disciplinary mental maps were created by the researchers in various group interviews, followed by the development of an overall group causal loop diagram based on the disciplinary mental maps to form a holistic qualitative model. For the model analysis, causal chains of sub-processes and feedback loops were visually isolated and highlighted. Particular emphasis is placed on identifying and analyzing the reinforcing feedback loops underlying the complex urban system in order to understand the vicious circles of barriers that perpetuate and thus hinder the adaptation process. The findings on the system’s feedback loops help to understand why and how system behavior evolves in a specific direction. The integrated model shows that the main drivers of urban flood risk growth in the system are linked to socio-economic and institutional processes. Climate change mainly affects the city externally by increasing flood hazards, while the city itself contributes to flood risk through processes of exposure and social vulnerability. The results show that increasing flood risk and barriers to adaptation in the city are linked to the amplifying feedback loops of path dependency, river engineering measures, urban development, car dependency, the ‘levee effect’, poverty, urban health and silo-thinking.

The case study demonstrates the usefulness of the qualitative system dynamics modelling approach in developing a shared understanding of the complex social, economic, environmental and political and institutional interactions among multiple drivers of flood risk. Causal loop diagrams can be successfully used to articulate the viscous circles of barriers and lock-in effects of unsustainable development in urban adaptation. However, it should be noted that the model reflects the state of knowledge of the researchers involved in the model-building process and therefore only represents a ‘dynamic hypothesis’ of the structure and dynamics of the system under consideration. Further work is in progress to place this qualitative system dynamics model in the broader context of decisions support and policy through stakeholder involvement.

How to cite: Hanf, F. S. and the 'water from 4 sides' project team: A socio-ecological system perspective on urban flood risk and barriers to adaptation under climate change using causal loop diagrams – Case study of the city of Hamburg, Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2008, https://doi.org/10.5194/egusphere-egu24-2008, 2024.

Keywords: risk communication, protection-motivation, flood type, household, survey

Whether and how flood-affected people prepare for flooding is commonly assumed to depend on their perception of risk, options to cope and responsibilities. However, the influence of different flood types, i.e., fluvial, flash and urban pluvial floods, is unclear, but might be relevant for effective risk communications. We use survey data from more than 3000 households affected by different types of flooding in Germany to investigate their influence on adaptive behaviour and influencing factors. We use descriptive statistics, Kruskal-Wallis Tests and single factor ANOVA to identify differences and similarities between respondents. We use linear regressions to identify factors that influence adaptive behaviour of households in the context of fluvial, pluvial and flash flooding.

We found that most respondents were motivated to protect themselves, but that there were flood type specific differences in the factors influencing an adaptive response. For example, those affected by fluvial events have had implemented most often measures before the last flooding, showed signs of emotional coping frequently and were less likely to implement (more) measures, while those affected by flash flooding showed less confidence in the effectiveness of measures, but were less likely to rate their costs as too high and were most likely to implement measures after the event. We argue that inter alia the severity and experience of flooding, as well as the management of flooding, shapes adaptive behaviour. We further found that regardless of the type of flooding, the perception of the effectiveness of adaptive measures and a positive perception of personal responsibility are critical to promote the protection motivation of those affected. We found, that these two key elements can be strengthened by offering financial support for adaptive measures. We also found that communication on a municipality level enhances the sense of self-responsibility. We conclude that communication and management strategies need to involve municipalities and should be tailored to the type of flooding. Up to now, risk communication mainly addresses fluvial flooding situations.

How to cite: Dillenardt, L. and Thieken, A.: Individual Flood Risk Adaptation in Germany: Exploring the Role of Different Types of Flooding, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10652, https://doi.org/10.5194/egusphere-egu24-10652, 2024.

Increasingly frequent extreme hydro-meteorological events, attributable among others to non-stationary climate, can lead to devastating flooding and cause large costs to affected societies. A recent and prominently featured example includes the July 2021 flood in Germany with more than 140 casualties and billions of Euros in material damages. Such types of events could strike other parts of Europe at any time. Especially small-scale systems are likely to be affected more frequently by high intensity events. To ready society against such occurrences, preparedness needs to be increased form different viewpoints: 1) extreme value statistics and forecasting, 2) real-time data acquisition and high performance computing, 3) socio-technical translation into domains.

First, fast and accurate forecasting with reduced uncertainties requires integration of predictors at different spatial and temporal scales. Such predictors must be conditioned by local, real-time information retrieved from multi-sensor systems, whereby special attention is devoted to extreme event statistics. The uncertainty of prediction resulting from sources like forecast model deficiencies, measurement errors, or various critical system states, need to be adequately represented, as well as de-biased and sharpened in real-time through statistical approaches.

Second, real-time acquisition of local data plays an essential role in risk detection. To this end, novel sensor system integration must provide robust real-time information, either on the basis of flexibly positioned or body-mounted devices. The extended complexity of the methods involved make the efficiency of the computational methods and the integration of model-driven physical processes with data driven approaches and ubiquitous computing as key factor. This also concerns the reduction of computational complexity without compromising efficacy as well as the efficient interoperability between different system components or scales.

Third, such novel instruments need to be socio-technically translated for decision-makers as well as emergency services and citizens. User involvement needs to be bidirectional, that is, stakeholders and their concerns must be understood and taken seriously for them to gain confidence and adopt innovative, multi-sensor integrated forecasting technologies for risk mitigation. Moreover, proper visual mapping of hazardous situations including uncertainties and potential options for decision-support need to be provided.

How to cite: Reggiani, P., Fischer, S., Kolb, A., Van Laerhoven, K., and Schubert, C.: Novel instruments for flood risk mitigation in small, fast reacting watersheds by means of sensor integration, advanced computing and socio-technical translation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16716, https://doi.org/10.5194/egusphere-egu24-16716, 2024.

Floods impact a series of interconnected urban systems (referred to as the Urban Multiplex) that include the power grid and transportation networks, surface water and groundwater, sewerage and drinking water systems, inland navigation and dams – all intertwined with the natural environment and socioeconomic and public health sectors. While the Urban Multiplex is physically and functionally connected, the data produced within its individual sectors are not. This is the core reason why we still do not fully understand the total impact of floods on cities.

The Urban Flooding Open Knowledge Network (UFOKN) is an information infrastructure that (i) integrates Urban Multiplex data, (ii) produces real-time and long-term flood forecasts across the continental U.S., and (iii) serves as the foundation to evaluate the total impact of floods on cities. The latter includes assessment of cascading economic impacts of floods across multiple sectors, as well as cascading failures across infrastructure, ecosystems, and communities.

UFOKN aims to provide actionable answers to questions such as:

• Real-time flood mitigation and response: Will my house or place of business flood? Will I have access to water and power? Which district to evacuate first? When? Which traffic routes are safe? Will this storm disrupt the power grid, drinking water treatment plant, or a bridge?

• Long-term design, planning and research: Which critical urban infrastructure will likely fail in a future flood? Which failures will affect the most people or the most vulnerable people? Which areas will experience repeated flooding? Which houses should the city buy out? Should a hospital be built at location X? What are the common triggers of Urban Multiplex failures?

The interdisciplinary team behind this project has brought together academic researchers, industry, federal government, U.S. National labs and local stakeholders. UFOKN is funded by the U.S. National Science Foundation’s Convergence Accelerator Program that is structured to enable rapid advancement in highly complex problems of critical societal importance.

How to cite: Yeghiazarian, L. and the Lilit Yeghiazarian: The Urban Flooding Open Knowledge Network: From Real-Time Flood Forecasts to Cascading Failures Through Infrastructure, Ecosystems, Communities and Economy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13258, https://doi.org/10.5194/egusphere-egu24-13258, 2024.

Catastrophe models are complex numerical models that simulate extreme events to estimate the economic cost of natural disasters, usually developed by model providers and adopted by clients in the (re)insurance, finance, and other sectors. Before adopting a model, the model user typically engages in an evaluation process that can be a challenging and resource-intensive task, and challenging for non-experts. This process is not standardised across the industry, so model users need to establish their approach from scratch. Yet effective evaluation is repetitive and takes time and resources – an effort that is being duplicated across organisations and teams, which would be better placed on an exploratory side of testing that progresses knowledge and understanding of models. By automating the repetitive part of model evaluation, data visualisations and results can be reproduced quickly. This would allow for more frequent assessment, leading to an improved understanding of the limitations of catastrophe models and increased confidence in the insights gained from using a catastrophe model.

We present AutoVal, a catastrophe model evaluation tool that automates standard loss validation tests. The premise of AutoVal is very simple: third party data is transformed at the point of use into benchmark expectations, for assessment against catastrophe model outputs. In our work to date, third party insurance claims data or published estimates of event losses are used to calculate average annual losses, loss exceedance curves, and map spatial and temporal distributions of loss for comparison with modelled estimates. Further work is ongoing to expand the capability of AutoVal to evaluate components within the natural catastrophe model, including vulnerability functions and hazard maps.

AutoVal can aid model users from both industry and academic backgrounds through the application of standard, repeatable tests. It assists with the effective review of model configurations across a range of perils or scenarios, allowing decision makers to better understand model sensitivity and behaviour. AutoVal also has the potential to remove the repetition in model evaluation, allowing for more frequent model evaluation and faster feedback loops between developers and users. In this presentation, we will share our progress so far with designing and automating the evaluation of our catastrophe models, including – but not limited to – standardised schemas for benchmark data, validation exercises to assess modelled estimates of loss, and new approaches to interpreting model sensitivity.

To realise the potential of AutoVal, we invite colleagues from the risk management sector to discuss our ongoing work towards establishing a set of benchmark tests that can complement industry-wide progress towards consistent and common standards.

How to cite: Massam, A., Burns, D., Jordan, O., Nix, B., O'Malley, N., Oldham, P., Sahu, B., and Vasiljeva, K.: AutoVal: A framework for scientific validation of flood catastrophe models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15783, https://doi.org/10.5194/egusphere-egu24-15783, 2024.

Climate change is a critical context for the development of human civilization. Case studies on the societal impacts of climate change contribute to the understanding of the mechanisms of interactions between natural forces, ecosystems, and human societies. This study investigates the Chongzhen Drought occurring in 1627-1644 in China, which was very likely the worst drought in eastern China in the past 1500 years. Its duration, scope, and number of people affected are rare in history. At the same time, a large-scale famine broke out, which is argued as a main trigger of the peasant uprisings that led to the fall of the Ming Dynasty. This paper extracted 1,802 drought records and 1,977 famine records from Chinese historical documents (mainly local chronicles and history books) and reconstructed the spatio-temporal evolution of drought from 1627 to 1644 in eastern China as well as its impact on famine. First, we classified the drought events into four levels according to the duration and severity, based on the semantic differences. Then the kernel density estimation was used to reconstruct the spatial pattern of drought at annual resolution, as well as a series of Drought Kernel Density Index (DKDI) in different regions. The main drought area in 1627-1644 was located north of 29°N and shifted from Northwest China to North China and then expanded to the south. The development of drought in different regions was not synchronized. The DKDI series of North China approximated a single-peaked curve, with the drought gradually worsening from 1633-1640; the peak of DKDI in Northwest China also appeared in 1640. However, the DKDI series of the Yangtze-Huai Region showed a multi-peaked curve, constantly experiencing a cycle of drought aggravation-reduction in the early period and reaching its peak in 1641. Second, the spatio-temporal evolution of famine was also reconstructed and compared with drought. It showed that the range of drought and famine largely overlapped and their developing trends were generally similar.  However, the movement of the Famine Kernel Density Index (FKDI) series tended to be 1-2 years later than that of DKDI, suggesting a lag and continuation of transmission of drought impacts to the human system. Finally, the regression analysis showed that drought was the most critical factor triggering famine in this case with a contribution weight of 67.3%. The weight is higher at 73.4% in North China in comparison with other subnational regions. The study identified the transmission pathway from climate change to social consequences through “persistent drought → declining agricultural harvests → food shortage → famine”. While socioeconomic factors and human behaviours also played various roles in regulating the transmission process.

How to cite: Chen, S., Su, Y., Chen, X., and Yang, L. E.: Examining the Spatial-Temporal Evolution of the Chongzhen Drought (1627-1644) in China and Its Impact on Famine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5548, https://doi.org/10.5194/egusphere-egu24-5548, 2024.

Floodplains have been crucial agricultural and populated areas throughout history and in present. Rivers typically shape the human activities within floodplains through water supply and flood risk, forming unique human-water interaction patterns. Here, we focus on the Lower Yellow River Floodplain, where continuous levees divide homogenous cultivated plain with different flood risk, creating a quasi-natural experiment, while the river's hydrology has undergone dramatic transformation since the 1990s. We utilize Landsat-based data including open-surface water bodies, cropland and NDVI to analyze the mechanism of river-agriculture interaction and whether this mechanism has changed. The results reveal that agriculture activities were less developed inside the floodplain than outside, and were even worse in regions closest to the river. This was attributed to frequent channel diversions, heightened flood threat, and actual inundation within the floodplain. However, the Lower Yellow River experienced a silt-load reduction, trenching, and channel stabilization after the late 1990s, while submerged cropland area in the floodplain also decreased. The declining flood threat has encouraged cultivation and agriculture investment in the floodplain, consequently reducing the productivity difference across the levees. This study illustrates a prototypical human-water interaction pattern in floodplains, underscoring the significance of effective river management for sustainable development in these regions, and provides a reference on understanding regional human-environment relationship in other floodplain areas.

How to cite: Jiao, C., Wu, X., Song, S., Wang, S., Xiang, B., and Fu, B.: River Regulation Reshaped Human-water Interaction in the Lower Yellow River Floodplain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7487, https://doi.org/10.5194/egusphere-egu24-7487, 2024.

River basins couple the natural ecosystem with the socio-economic system. Regime shifts due to climate change and social-economic factors highlight the importance of quantifying and strengthening the water resilience in the river basin. Water resilience in river basin systems requires more specific quantification. The Yellow River Basin (YRB) was well-known for its historically severe water supply pressure in recent decades, profoundly adjusted by the social-economic system. A system dynamic model named the Water-Sediment-Social Economic-Ecological Model (WSSEEM) was proposed around the interactions and feedback among water supply, sediment discharge, vegetation changes, food production and social-economic development in the YRB. Using WSSEEM, we simulate water supply and demand resilience to changes and distributions, including policy implementation and engineered measures during the historical time (1981-2020) and future scenarios. Our result indicates that technology enhancement and engineered measures are instructive in water management and sediment discharge. The WSSEEM offers a comprehensive approach to representing the river basin system, providing valuable insights into using model simulation to achieve sustainable goals and resilient water management.

How to cite: Yu, L., Song, S., Wu, X., Wang, S., and Fu, B.: Water resilience to policy implementation and engineered measures in the Yellow River Basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11668, https://doi.org/10.5194/egusphere-egu24-11668, 2024.

South Asia is one of the hotspot regions for extreme weather and climate events such as heatwaves, droughts, and extreme precipitation. This work aims to present a comprehensive analysis of the future changes (2071-2100) in the frequency and duration of compound dry-hot extremes in South Asia. Given the current gap in specific data for such compound events in this region, our approach involves utilizing state-of-the-art regional climate models from the Coordinated Output for Regional Evaluations (CORE) project embedded in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework. The focus will be on understanding the interplay between dry and hot days conditions, and how their concurrent occurrence may exacerbate environmental and socio-economic challenges. We will analyze an ensemble of regional climate projections to identify potential trends in these compound events by the end of the 21^st century. The outcomes of this study are expected to provide valuable insights into the evolving nature of compound climate extremes in South Asia, thereby informing policy and adaptation strategies for enhanced regional resilience.

How to cite: Saleem, F., Weber, T., and Remedio, A.: Projected changes in compound dry-hot events in South Asia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10949, https://doi.org/10.5194/egusphere-egu24-10949, 2024.

Drought affects people, agriculture, and businesses across all sectors in every populated continent on Earth, and with climate change, both drought frequency and duration are increasing globally. Losses of $124 Billion to the global economy over the last two decades (1998 - 2017) have been directly attributed to drought. Hence, it is vital to gain an accurate understanding of drought risk in the present and how it may change in the future. 

Here, we describe the development of a climate-driven drought model which provides a global view of drought risk for (re)insurers. 

First, a historical catalogue (1950-present) consisting of yearly aggregated drought severity and duration footprints is derived by combining a selection of state-of-the-art drought indexes over varied time scales. Second, leveraging this historical catalogue, a large stochastic set of drought footprints is generated via the use of Principle Component Analysis, in which the drought risk is conditioned to the climate state. The model is then deployed on historical climate conditions (ERA5) or alternative and future climate conditions (indicated by the CEMS-LENS multi-member reanalysis model (present-2100)). 

These products are critical to inform damage models in the (re)insurance sector, with the model thus far proving useful in predicting subsidence risk in a France-based use case. Showcased results will provide an evaluation of drought risk both in the historical and changing future climate, as well as a newly developed risk score metric based on merged severity and duration information.

How to cite: Shaylor, M., Bruneau, N., Joffrain, M., Azemar, F., and Loridan, T.: A Global Climate-Driven Stochastic Drought Model for Risk Assessment , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8646, https://doi.org/10.5194/egusphere-egu24-8646, 2024.

In today’s interconnected world, assessing the risks of extreme events has become increasingly complex. These events often trigger far-reaching consequences that spread throughout various sectors and systems due to complex interactions, resulting in compound and cascading impacts. While qualitative and quantitative approaches are commonly used separately in systemic impact research, we argue that methodological pluralism is necessary to address the complexity of these social-ecological systems. In this talk, we propose an integrative methodological approach for studying impact cascades and exemplify it via two case-study applications. The first focuses on using dimensionality reduction and pattern-mining techniques to assess spatiotemporal patterns in the occurrence of drought impacts in Germany. We explore how these patterns differ during multi-year drought events in contrast to short-lived droughts. Second, we leverage qualitative cognitive maps derived from 25 stakeholder interviews to investigate how drought impacts propagate in a case study in Thuringia, Germany. By using graph theory, we identify influential variables and show how pooling the knowledge of diverse stakeholder crowds can create new, emergent knowledge. We find that combining different methods helps revealing various facets of impact cascades and helps compensating for the limitations of individual methods. This can strengthen the research confidence as results that agree across different methods are less likely to be artefacts.

How to cite: Madruga de Brito, M., Sodoge, J., Reckhaus, Z., Mahecha, M., and Kuhlicke, C.: Analyzing impact cascades: an integrative approach for assessing the interconnected effects of extreme events across sectors and systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1496, https://doi.org/10.5194/egusphere-egu24-1496, 2024.

To comprehensively manage the impacts from hazards and disasters, a nuanced understanding of the systemic nature of risks is needed. The effects of natural hazards, climate change and other human-generated shocks transcend borders, sectors and systems, highlighting the interconnected nature of risks. The lack of resilience in one sector can propagate risks across multiple other sectors, and interventions in response can generate trade-offs and unintended negative consequences leading to maladaptation. This emphasises that not only do we need to analyse risk from a systemic perspective, we must also approach risk management and adaptation to consider interconnected positive and negative cascading effects. 

Despite recent progress in complex risk assessment, translating information into actionable inputs for risk management remains a challenge. These challenges are especially pressing in countries burdened by increasing exposure to natural hazards and extreme climate effects. To support addressing this challenge, we integrated a novel  systemic risk analysis method named Impact Webs (Sparkes et al., 2023) with a pathways approach, to co-create disaster and climate risk management pathways with stakeholders, using the Republics of Malawi and South Africa as case studies. 

Impact Webs are system-oriented conceptual risk models that identify interconnections between hazards, risks, impacts, interventions, drivers of risks and root causes, mapping their interaction  across different sectors and at various scales. We co-developed Impact Webs with stakeholders, building on them to identify lessons for risk management adopting a pathways approach. Pathways are a flexible planning approach that incorporates stakeholders’ perspectives into decision making, reducing path dependencies and managing trade-offs. Decisions are taken based on how future conditions unfold. Our pathways development was also driven by stakeholders’ inputs, first using Impact Webs to identify entry points for risk management options. Barriers to implementing options were then identified, as well as enabling conditions to overcome them. We then engaged with potential trade-offs and positive cascading effects, identifying pathways for Malawi and South Africa that could strengthen resilience across multiple sectors. We took a transformational pathways approach, developing pathways for wide-ranging system changes needed to reach high resilience futures. The work was done over four workshops with a range of expert stakeholders, and was complemented by desk study and interviews.

Reflecting on the approach, a challenge arose in sequence actions, i.e., justifying the selection of one risk management option before another. This was due to developing pathways at the national scale across many sectors, therefore they were not targeted towards a specific decision or group of decision-makers. Despite this, the integration of the Impact Webs and pathways provides a useful methodology to move from systemic risk analysis to systemic risk management. Collecting feedback from stakeholders during the workshops, the co-creation process, and engaging with the visual output of an Impact Web, helped them think about risks and risk management in an interconnected manner, by considering cascading effects and response risks of interventions. This can foster understanding among decision makers about the interdependencies between sectors, thus supporting disaster and climate risk management that strengthens system-wide resilience across multiple sectors.

How to cite: Sparkes, E., Cotti, D., Manyuchi, A., Kita, S., Naomi Ukatu, N., Pfeiffer, S., Werners, S. E., and Hagenlocher, M.: From systemic risks to systemic resilience: A pathways approach for disaster and climate risk management in Malawi and South Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20037, https://doi.org/10.5194/egusphere-egu24-20037, 2024.

The humanitarian community has a long history of attempting to reduce the human impact of extreme weather and climate events. Over the past decade there has been an increasing shift in the humanitarian community towards using climate science to better anticipate climate impacts on vulnerable communities and hence guide humanitarian planning and responses. However, large uncertainties, climate and non-climate, and complex compounding risks pose significant challenges to integrating climate information into humanitarian planning.

In the glossary of the IPCC Working Group I contribution to the Sixth Assessment Report storylines are defined as “A way of making sense of a situation or a series of events through the construction of a set of explanatory elements” and “can be used to describe plural, conditional possible futures or explanations of a current situation, in contrast to single, definitive futures or explanations”.

With this they are valuable for the humanitarian sector as storylines related approaches including impact pathways and complex risk frameworks offer the potential to provide robust and valuable understanding of risk, as well as supporting the development of effective interventions. They do not remove the underlying uncertainty, however, they do help to shift the questions asked from “What is going to happen”, to “What would unfold if this storyline occurred".  This shift has the potential to connect with decision making options and processes far more effectively than presentations of aggregate uncertainty ranges.

We explore the potential value  of storylines for climate risk management within the humanitarian sector, we present practical examples of effectively applying them to estimate and describe  systemic climate-related risks, especially in vulnerable regions.

How to cite: Vogel, M. M. and Jack, C. D.: Navigating climate risk in humanitarian action: The potential of storyline approaches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-905, https://doi.org/10.5194/egusphere-egu24-905, 2024.

Anthropogenic climate change, driven by elevated levels of greenhouse gases, is accelerating at an unprecedented rate, causing significant changes in climatic and biogeochemical conditions. The adverse effects of climate change include detrimental impacts on natural and managed ecosystems, as well as on socio-economic systems, human health, and welfare. Recognising the urgent need to address these challenges, the IRISCC (Integrated Research Infrastructure Services for Climate Change Risks) project aims to provide scientific and knowledge-based services to support societal adaptation to climate change. The project is funded by the European Union under grant agreement No 101131261 (HORIZON Research and Innovation Actions in Research Infrastructure Programme topic HORIZON- INFRA-2023-SERV-01-01) and has over 70 partners providing research services.

For the researchers focusing on climate change risks, IRISCC will offer services, such as open data and access to research platforms via transnational access and virtual access programs. Here IRISCC employs an integrated approach to understanding climate change risks, encompassing hazards, exposure, and vulnerability. By fostering interdisciplinary collaboration, the project strives to support science enabling all users of IRISCC services to better predict, mitigate, and adapt to climate-related risks affecting human and natural systems. The project's overarching mission is to facilitate in-depth knowledge production on climate change risks and accelerate the translation of scientific knowledge into innovative solutions.

The IRISCC consortium comprises expertise from several research infrastructures, covering domains such as Earth systems, health and environment, and social sciences, each bringing in their research service portfolios. Through inter- and transdisciplinary approaches, the project aims to provide transnational and virtual access to cutting-edge research, innovation, training, and digital services. 

In summary, the IRISCC project aligns with the session's focus on systems thinking approaches, presenting a comprehensive strategy supporting users to tackle the interconnected issues of climate-related hazards, risks, and impacts. The commitment of the project to provide integrated research infrastructure services positions it as a key player in advancing our ability to predict, mitigate, and adapt to the multifaceted challenges posed by climate change in European regions and cities.

How to cite: Rinne, J., Brus, M., Nikolaidis, N., Bäck, J., Laj, P., Kutsch, W., Schaap, D., Steenberg Larsen, K., Phillippin, S., Petracca Altieri, R., Lund, C., Vendelboe, K., Haapanala, P., Virkki, S., Kivekäs, N., and Sorvari Sundet, S.: IRISCC: supporting society’s capacity to address and strengthen resilience to climate change risks , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5855, https://doi.org/10.5194/egusphere-egu24-5855, 2024.

How to cite: Bloemendaal, N., Sluijter, R., Diepeveen, J., and Koks, E.: Towards hurricane impact forecasting for the Dutch Caribbean  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18130, https://doi.org/10.5194/egusphere-egu24-18130, 2024.

Loss exceedance curves have fat tails arising from cascading losses.  Even though such losses are rare, insight can be gained by considering alternative downward counterfactual realizations of historical events.  The use of downward counterfactuals provides a methodology for constructing climate change storylines (e.g. Climate Risk Management, 2021).

The downward counterfactual search for cascading losses can identify potential tipping points for disasters.  Such tipping points can arise from the perturbation of a historical system state through additional climate forcing, combined with human factors, such as human error, negligence or malicious action.   

Examples are given of how lessons learned from historical compound events, e.g. wind and heatwave, might have averted disaster.  The Californian utility, Pacific Gas & Electric (PG&E), narrowly missed liability for the 2017 Tubbs Fire in Northern California.  Increased inspection of their electricity power lines would have mitigated the risk of liability from future wildfires.  The following year, the Camp fire occurred, the deadliest and most destructive in Californian history.  PG&E were indicted for repeatedly ignoring warnings about its aging power lines and faulty maintenance, and in early 2019, PG&E were forced to file for Chapter 11 bankruptcy.

On 9 September 2023, Storm Daniel transitioned into a Mediterranean tropical cyclone, and made landfall near Benghazi in Libya, the following day.  The intense rainfall caused the collapse of the two Wadi Derna dams on 11 September, and the devastation of Derna.  Counterfactual analysis would have given prior warning. A Libyan hydrologist had pointed out in 2022 that the 1959 storm would have caused the failure of the dams, had they existed then.

Exploration of downward counterfactuals would augment societal resilience against climate extremes and compound events.

How to cite: Woo, G.: Downward counterfactual search for cascading losses, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7449, https://doi.org/10.5194/egusphere-egu24-7449, 2024.

How to cite: Migliavacca, M., Bras, T., Rougieux, P., Patani, S., Bausano, G., Achard, F., Avitabile, V., Beuchle, R., Bourgoin, C., Cescatti, A., Ceccherini, G., Colditz, R., De Laurentiis, V., Orza, V., Vancutsem, C., and Mubareka, S.: Assessing the deforestation embodied in the European Union consumption and trade of forest risk commodities. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7721, https://doi.org/10.5194/egusphere-egu24-7721, 2024.

Ecosystems around the world are showing symptoms of resilience loss. With them there is an increasing risk of critical transitions or regime shifts: large, abrupt and difficult to reverse changes in the function and structure of ecosystems. When regime shifts occur they often impact the flow of benefits that people get from nature, and with them the ability of companies, cities or nations to satisfy human needs. Here we ask who is exposed to ecological regime shift risks, and by being exposed, who has the agency or power to intervene and perhaps avoid tipping points?

To answer this question we match companies whose activities imply the use or extraction of natural resources in places vulnerable to regime shifts. First, we use Earth observations to quantify resilience loss in marine systems. We also used temeprature records to quantify the probability of extreme and severe heat wave events in the oceans. Both are conditions that can reduce primary productivity and impact fisheries. Then, we identify vessels that fish in these areas of the world and match their owners and shareholders when available in public databases.

For publicly listed companies we reconstruct social networks of companies ownership and investments. The networks serve to identify financial actors exposed to ecological tipping points through several investments or regions of the world. The multilayer network can be centred around companies, shareholders, investors, or countries. Clustering at different levels of aggregation allow us to identify actors with disproportional risk exposure, but also companies, investors or countries who could make a difference in mitigating risk.

How to cite: Rocha, J. and Galaz, V.: Identifying financial actors exposed to tipping point risks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7653, https://doi.org/10.5194/egusphere-egu24-7653, 2024.