Modeling for insights not numbers: The long-term low-carbon transformation

Limiting global warming to prevent dangerous climate change requires drastically reducing global greenhouse gases emissions and a transformation towards a low-carbon society. Existing energy- and climate-economic modeling approaches that are informing policy and decision makers in shaping the future net-zero emissions society are increasingly seen with skepticism regarding their ability to forecast the long-term evolution of highly complex, nonlinear social-ecological systems. We present a structured review of state-of-the-art modeling approaches, focusing on their ability and limitations to develop and assess pathways towards a low-carbon society. We find that existing methodological approaches have some fundamental deficiencies that limit their potential to understand the subtleties of long-term low-carbon transformation processes. We suggest that a useful methodological framework has to move beyond current state of the art techniques and has to simultaneously fulfill the following requirements: (1) representation of an inherent dynamic analysis, describing and investigating explicitly the path between different states of system variables, (2) specification of details in the energy cascade, in particular the central role of functionalities and services that are provided by the interaction of energy flows and corresponding stock variables, (3) reliance on a clear distinction between structures of the sociotechnical energy system and socioeconomic mechanisms to develop it and (4) ability to evaluate pathways along societal criteria. To that end we propose the development of a versatile multi-purpose integrated modeling framework, building on the specific strengths of the various modeling approaches available while at the same time omitting their weaknesses. This paper identifies respective strengths and weaknesses to guide such development

Statistical characteristics of surrogate data based on geophysical measurements

In this study, the statistical properties of a range of measurements are compared with those of their surrogate time series. Seven different records are studied, amongst others, historical time series of mean daily temperature, daily rain sums and runoff from two rivers, and cloud measurements. Seven different algorithms are used to generate the surrogate time series. The best-known method is the iterative amplitude adjusted Fourier transform (IAAFT) algorithm, which is able to reproduce the measured distribution as well as the power spectrum. Using this setup, the measurements and their surrogates are compared with respect to their power spectrum, increment distribution, structure functions, annual percentiles and return values. It is found that the surrogates that reproduce the power spectrum and the distribution of the measurements are able to closely match the increment distributions and the structure functions of the measurements, but this often does not hold for surrogates that only mimic the power spectrum of the measurement. However, even the best performing surrogates do not have asymmetric increment distributions, i.e., they cannot reproduce nonlinear dynamical processes that are asymmetric in time. Furthermore, we have found deviations of the structure functions on small scales

Barriers and Ways Forward to Climate Risk Management Against Indirect Effects of Natural Disasters: A Case Study on Flood Risk in Austria

Natural disasters, such as floods, can have severe consequences, especially as economies are becoming ever more interlinked and complex so that the cascading effects of disasters can amplify direct impacts. These trends are expected to continue in the future due to climate change and changing socio-economic structures. It is therefore important to promote climate risk management strategies that also deal with indirect effects due to natural disaster events in a proactive manner. However, there is a lack of studies which investigate the agents involved in climate risk management geared towards the indirect effects of disasters and how these indirect effects are or can be dealt with. We address this gap via a detailed case study of the Austrian flood risk management apparatus. Based on a detailed stakeholder analysis, we compile a stakeholder map of those potentially involved in indirect flood risk management as well as the relationships (or the lack thereof) among them. We further discuss current and future indirect risk management strategies and corresponding implementation barriers. Finally, based on the results obtained from the stakeholder process, we discuss and suggest possible ways forward to overcome these barriers to enable proactive management strategies for indirect climate risks. We find that although indirect risks are being considered in the Austrian flood risk management, they are managed to a marginal degree. To remedy this, we call for increased efforts in data collection, modelling and awareness raising and the revision of current financial as well as institutional structures. Greater focus should be put on interdependencies within systems as well as the adoption of long-term visions for establishing more integrated climate risk management against indirect effects

Indirect flood risk management in Austria: Challenges and ways forward

Natural disaster risks are among the greatest threats of the 21st century putting political, social and economic systems increasingly under pressure and at risk of instability (UNDRR/CRED 2020). Especially in recent years, the cascading effects and risks associated with such events have received great attention as economic losses and consequences have mounted (Handmer et al. 2020; Reichstein et al. 2021). Due to increasingly complex economic networks and interdependencies, natural disasters can result in large ripple effects including business or supply chain interruptions, changes in economic productivity or increased indebtedness. These so-called indirect losses can amount to or even exceed direct damages (Koks et al. 2015; Dottori et al. 2018). Climate change exacerbates the intensity and frequency of flood events. Accompanied by socioeconomic changes this leads to increasing flood damages. Therefore, more holistic and long-term disaster risk management (DRM) strategies that tackle indirect effects and which take into account climate change effects are called for. To implement these strategies, we require a deeper understanding of who could be involved in indirect flood risk management (FRM), which management strategies are already implemented and which should be implemented in the future, as well as what are the corresponding implementation barriers. These issues are addressed in this fact sheet in the context of Austrian climate risk management strategies discussing how indirect risks from floods are currently considered and how they could be proactively integrated on various scales (the discussion is based on Reiter et al. 2022)

Revealing indirect risks in complex socioeconomic systems: A highly detailed multi‐model analysis of flood events in Austria

Cascading risks that can spread through complex systems have recently gained attention. As it is crucial for decision-makers to put figures on such risks and their interactions, models that explicitly capture such interactions in a realistic manner are needed. Climate related hazards often cascade through different systems, from physical to economic and social systems, causing direct but also indirect risks and losses. Despite their growing importance in the light of ongoing climate change and increasing global connections, such indirect risks are not well understood. Applying two fundamentally different economic models—a computable general equilibrium model and an agent-based model—we reveal indirect risks of flood events. The models are fed with sector-specific capital stock damages, which constitutes a major methodological improvement. We apply these models for Austria, a highly flood exposed country with strong economic linkages. A key finding is that flood damages pose very different indirect risks to different sectors and household groups (distributional effects) in the short and long-term. Our results imply that risk management should focus on specific societal subgroups and sectors. We provide a simple metric for indirect risk, showing how direct and indirect losses are related. This can provide new ways forward in risk management, for example, focusing on interconnectedness of sectors and agents within different risk-layers of indirect risk. Although we offer highly relevant leverage points for indirect risk management in Austria, the methodology of analyzing indirect risks can be transferred to other regions

Revealing the indirect risks of flood events: A multi-model assessment for Austria

Flood events and the associated damages trigger direct as well as indirect effects due to economy-wide linkages. Hence, flood events pose indirect risks to complex socioeconomic systems and their individual agents. Despite their increasing importance in the light of ongoing climate change impacts, such indirect risks are not well understood. Using a set of three different economy-wide models – an input output model, a computable general equilibrium (CGE) model and an agent-based model – we reveal and study indirect risks of flood events for the case of Austria. The three models are fed with high resolution data on sector-specific capital stock damages, which is a major improvement with respect to existing approaches in disaster and climate change impact assessment. We find that indirect risks are very high for most economic sectors and that only the minority of sectors can gain from flood events. Furthermore, on the side of private households we find that floods pose a risk in terms of unequal distributional effects, since capital rents tend to increase while wages tend to decrease in the aftermath of a flood, leading to a re-distribution of income from highto low-income households. The study thus offers highly relevant leverage points for indirect risk management options in Austria. The used methodologies can be transferred to other regions

Revealing the indirect risks of flood events: A multi-model assessment for Austria

Flood events and the associated damages trigger direct as well as indirect effects due to economy-wide linkages. Hence, flood events pose indirect risks to complex socioeconomic systems and their individual agents. Despite their increasing importance in the light of ongoing climate change impacts, such indirect risks are not well understood. Using a set of three different economy-wide models – an input output model, a computable general equilibrium (CGE) model and an agent-based model – we reveal and study indirect risks of flood events for the case of Austria. The three models are fed with high resolution data on sector-specific capital stock damages, which is a major improvement with respect to existing approaches in disaster and climate change impact assessment. We find that indirect risks are very high for most economic sectors and that only the minority of sectors can gain from flood events. Furthermore, on the side of private households we find that floods pose a risk in terms of unequal distributional effects, since capital rents tend to increase while wages tend to decrease in the aftermath of a flood, leading to a re-distribution of income from highto low-income households. The study thus offers highly relevant leverage points for indirect risk management options in Austria. The used methodologies can be transferred to other regions

Living between languages: The politics of translation in Leila Aboulela’s Minaret and Xiaolu Guo’s A Concise Chinese-English Dictionary for Lovers

This is the author's final draft post-refereeing as published in The Journal of Commonwealth Literature 2012 47: 207 DOI:10.1177/0021989412440433. The online version of this article can be found at: http://jcl.sagepub.com/content/47/2/20

The Oxytocin Receptor (OXTR) Contributes to Prosocial Fund Allocations in the Dictator Game and the Social Value Orientations Task

Background: Economic games observe social decision making in the laboratory that involves real money payoffs. Previously we have shown that allocation of funds in the Dictator Game (DG), a paradigm that illustrates costly altruistic behavior, is partially determined by promoter-region repeat region variants in the arginine vasopressin 1a receptor gene (AVPR1a). In the current investigation, the gene encoding the related oxytocin receptor (OXTR) was tested for association with the DG and a related paradigm, the Social Values Orientation (SVO) task. Methodology/Principal Findings: Association (101 male and 102 female students) using a robust-family based test between 15 single tagging SNPs (htSNPs) across the OXTR was demonstrated with both the DG and SVO. Three htSNPs across the gene region showed significant association with both of the two games. The most significant association was observed with rs1042778 (p = 0.001). Haplotype analysis also showed significant associations for both DG and SVO. Following permutation test adjustment, significance was observed for 2–5 locus haplotypes (p,0.05). A second sample of 98 female subjects was subsequently and independently recruited to play the dictator game and was genotyped for the three significant SNPs found in the first sample. The rs1042778 SNP was shown to be significant for the second sample as well (p = 0.004, Fisher’s exact test). Conclusions: The demonstration that genetic polymorphisms for the OXTR are associated with human prosocial decisio