The existential risk space of climate change.

Climate change is widely recognized as a major risk to societies and natural ecosystems but the high end of the risk, i.e., where risks become existential, is poorly framed, defined, and analyzed in the scientific literature. This gap is at odds with the fundamental relevance of existential risks for humanity, and it also limits the ability of scientific communities to engage with emerging debates and narratives about the existential dimension of climate change that have recently gained considerable traction. This paper intends to address this gap by scoping and defining existential risks related to climate change. We first review the context of existential risks and climate change, drawing on research in fields on global catastrophic risks, and on key risks and the so-called Reasons for Concern in the reports of the Intergovernmental Panel on Climate Change. We also consider how existential risks are framed in the civil society climate movement as well as what can be learned in this respect from the COVID-19 crisis. To better frame existential risks in the context of climate change, we propose to define them as those risks that threaten the existence of a subject, where this subject can be an individual person, a community, or nation state or humanity. The threat to their existence is defined by two levels of severity: conditions that threaten (1) survival and (2) basic human needs. A third level, well-being, is commonly not part of the space of existential risks. Our definition covers a range of different scales, which leads us into further defining six analytical dimensions: physical and social processes involved, systems affected, magnitude, spatial scale, timing, and probability of occurrence. In conclusion, we suggest that a clearer and more precise definition and framing of existential risks of climate change such as we offer here facilitates scientific analysis as well societal and political discourse and action.

Lessons from COVID-19 for managing transboundary climate risks and building resilience.

COVID-19 has revealed how challenging it is to manage global, systemic and compounding crises. Like COVID-19, climate change impacts, and maladaptive responses to them, have potential to disrupt societies at multiple scales via networks of trade, finance, mobility and communication, and to impact hardest on the most vulnerable. However, these complex systems can also facilitate resilience if managed effectively. This review aims to distil lessons related to the transboundary management of systemic risks from the COVID-19 experience, to inform climate change policy and resilience building. Evidence from diverse fields is synthesised to illustrate the nature of systemic risks and our evolving understanding of resilience. We describe research methods that aim to capture systemic complexity to inform better management practices and increase resilience to crises. Finally, we recommend specific, practical actions for improving transboundary climate risk management and resilience building. These include mapping the direct, cross-border and cross-sectoral impacts of potential climate extremes, adopting adaptive risk management strategies that embrace heterogenous decision-making and uncertainty, and taking a broader approach to resilience which elevates human wellbeing, including societal and ecological resilience.

Viewing the global health system as a complex adaptive system - implications for research and practice.

The global health system (GHS) is ill-equipped to deal with the increasing number of transnational challenges. The GHS needs reform to enhance global resilience to future risks to health. In this article we argue that the starting point for any reform must be conceptualizing and studying the GHS as a complex adaptive system (CAS) with a large and escalating number of interconnected global health actors that learn and adapt their behaviours in response to each other and changes in their environment. The GHS can be viewed as a multi-scalar, nested health system comprising all national health systems together with the global health architecture, in which behaviours are influenced by cross-scale interactions. However, current methods cannot adequately capture the dynamism or complexity of the GHS or quantify the effects of challenges or potential reform options. We provide an overview of a selection of systems thinking and complexity science methods available to researchers and highlight the numerous policy insights their application could yield.   We also discuss the challenges for researchers of applying these methods and for policy makers of digesting and acting upon them. We encourage application of a CAS approach to GHS research and policy making to help bolster resilience to future risks that transcend national boundaries and system scales.

Conceptualising and assessing health system resilience to shocks: a cross-disciplinary view.

Health systems worldwide face major challenges in anticipating, planning for and responding to shocks from infectious disease epidemics, armed conflict, climatic and other crises. Although the literature on health system resilience has grown substantially in recent years, major uncertainties remain concerning approaches to resilience conceptualisation and measurement. This narrative review revisits literatures from a range of fields outside health to identify lessons relevant to health systems. Four key insights emerge. Firstly, shocks can only be understood by clarifying how, where and over what timescale they interact with a system of interest, and the dynamic effects they produce within it. Shock effects are contingent on historical path-dependencies, and on the presence of factors or system pathways (e.g. financing models, health workforce capabilities or supply chain designs) that may amplify or dampen impact in unexpected ways. Secondly, shocks often produce cascading effects across multiple scales, whereas the focus of much of the health resilience literature has been on macro-level, national systems. In reality, health systems bring together interconnected sub-systems across sectors and geographies, with different components, behaviours and sometimes even objectives - all influencing how a system responds to a shock. Thirdly, transformability is an integral feature of resilient social systems: cross-scale interactions help explain how systems can show both resilience and transformational capability at the same time. We illustrate these first three findings by extending the socioecological concept of adaptive cycles in social systems to health, using the example of maternal and child health service delivery. Finally, we argue that dynamic modelling approaches, under-utilised in research on health system resilience to date, have significant promise for identification of shock-moderating or shock-amplifying pathways, for understanding effects at multiple levels and ultimately for building resilience.

Differences in the dynamics of community disaster resilience across the globe.

The consideration of disaster resilience as a multidimensional concept provides a viable and promising way forward for reducing risk and minimizing impacts today and in the future. What is missing is the understanding of the actual dynamics of resilience over time based on empirical evidence. This empirical understanding requires a consistent measure of resilience. To that end, a Technical Resilience Grading Standard for community flood resilience, was applied in a longitudinal study from 2016 to 2018 in 68 communities across the globe. We analyse the dynamics of disaster resilience using an advanced boosted regression tree modelling framework. The main outcome of our analysis is twofold: first, we found empirical evidence that the dynamics of resilience build on a typology of communities and that different community clusters experience different dynamics; and second, the dynamics of resilience follows transitional behaviour rather than a linear or continuous process. These are empirical insights that can provide ways forward, theoretically as well as practically, in the understanding of resilience as well as in regard to effective policy guidance to enhance disaster resilience.

A co-designed heuristic guide for investigating the peace-sustainability nexus in the context of global change.

The interlinkages between peace and sustainability are embedded in several international agreements and declarations and recognized by various research studies. However, the characteristics of their bidirectional relationship remain underexamined. Here we scope the complex and multifaceted relationship between peace and sustainability based on an experts workshop held at Hiroshima University in August 2019. The workshop focused on how peace, as a process or a condition, can help or hinder sustainability and vice versa. Relevant environmental, socio-political, and economic and technological considerations highlighted at the workshop were integrated into a co-designed heuristic guide for investigating the peace-sustainability nexus in the context of global change. The proposed guide aims to assist academic and policy researchers in identifying the specific pathways through which peace and sustainability interact when addressing complex challenges. The reinforcing potential of the two will ultimately depend on the governance and management of global transformations.

Standardized disaster and climate resilience grading: A global scale empirical analysis of community flood resilience.

Suitable and standardized indicators to track progress in disaster and climate resilience are increasingly considered a key requirement for successfully informing efforts towards effective disaster risk reduction and climate adaptation. Standardized measures of resilience which can be used across different geographical and socioeconomic contexts are however sparse. We present and analyze a standardized community resilience measurement framework for flooding. The corresponding measurement tool is modelled based on and adapted from a so-called 'technical risk grading' approach as used in the insurance sector. The grading approach of indicators is based on a two-step process: (i) raw data is collected, and (ii) experts grade the indicators, called sources of resilience, based on this data. We test this approach using approximately 1.25 million datapoints collected across more than 118 communities in nine countries. The quantitative analysis is complemented by content analysis to validate the results from a qualitative perspective. We find that some indicators can more easily be graded by looking at raw data alone, while others require a stronger application of expert judgement. We summarize the reasons for this through six key messages. One major finding is that resilience grades related to subjective characteristics such as ability, feel, and trust are far more dependent on expert judgment than on the actual raw data collected. Additionally, the need for expert judgement further increases if graders must extrapolate the whole community picture from limited raw data. Our findings regarding the role of data and grade specifications can inform ways forward for better, more efficient and increasingly robust standardized assessment of resilience. This should help to build global standardized and comparable, yet locally contextualized, baseline estimates of the many facets of resilience in order to track progress over time on disaster and climate resilience and inform the implementation of the Paris Agreement, Sendai Framework, and the Sustainable Development Goals.

Integrated assessment of short-term direct and indirect economic flood impacts including uncertainty quantification.

Understanding and quantifying total economic impacts of flood events is essential for flood risk management and adaptation planning. Yet, detailed estimations of joint direct and indirect flood-induced economic impacts are rare. In this study an innovative modeling procedure for the joint assessment of short-term direct and indirect economic flood impacts is introduced. The procedure is applied to 19 economic sectors in eight federal states of Germany after the flood events in 2013. The assessment of the direct economic impacts is object-based and considers uncertainties associated with the hazard, the exposed objects and their vulnerability. The direct economic impacts are then coupled to a supply-side Input-Output-Model to estimate the indirect economic impacts. The procedure provides distributions of direct and indirect economic impacts which capture the associated uncertainties. The distributions of the direct economic impacts in the federal states are plausible when compared to reported values. The ratio between indirect and direct economic impacts shows that the sectors Manufacturing, Financial and Insurance activities suffered the most from indirect economic impacts. These ratios also indicate that indirect economic impacts can be almost as high as direct economic impacts. They differ strongly between the economic sectors indicating that the application of a single factor as a proxy for the indirect impacts of all economic sectors is not appropriate.

An overdue alignment of risk and resilience? A conceptual contribution to community resilience.

A systematic review of literature on community resilience measurement published between 2005 and 2014 revealed that the profound lack of clarity on risk and resilience is one of the main reasons why confusion about terms such as adaptive capacity, resilience, and vulnerability persists, despite the effort spared to operationalise these concepts. Resilience is measured in isolation in some cases, where a shock is perceived to arise external to the system of interest. Problematically, this contradicts the way in which the climate change and disaster communities perceive risk as manifesting itself endogenously as a function of exposure, hazard, and vulnerability. The common conceptualisation of resilience as predominantly positive is problematic as well when, in reality, many undesirable properties of a system are resilient. Consequently, this paper presents an integrative framework that highlights the interactions between risk drivers and coping, adaptive, and transformative capacities, providing an improved conceptual basis for resilience measurement.

A methodological framework to operationalize climate risk management: managing sovereign climate-related extreme event risk in Austria.

Despite considerable uncertainties regarding the exact contribution of anthropogenic climate change to disaster risk, rising losses from extreme events have highlighted the need to comprehensively address climate-related risk. This requires linking climate adaptation to disaster risk management (DRM), leading to what has been broadly referred to as climate risk management (CRM). While this concept has received attention in debate, important gaps remain in terms of operationalizing it with applicable methods and tools for specific risks and decision-contexts. By developing and applying a methodological approach to CRM in the decision context of sovereign risk (flooding) in Austria we test the usefulness of CRM, and based on these insights, inform applications in other decision contexts. Our methodological approach builds on multiple lines of evidence and methods. These comprise of a broad stakeholder engagement process, empirical analysis of public budgets, and risk-focused economic modelling. We find that a CRM framework is able to inform instrumental as well as reflexive and participatory debate in practice. Due to the complex interaction of social-ecological systems with climate risks, and taking into account the likelihood of future contingent climate-related fiscal liabilities increasing substantially as a result of socioeconomic developments and climate change, we identify the need for advanced learning processes and iterative updates of CRM management plans. We suggest that strategies comprising a portfolio of policy measures to reduce and manage climate-related risks are particularly effective if they tailor individual instruments to the specific requirements of different risk layers.

If Numbers Can Speak, Who Listens? Creating Engagement and Learning for Effective Uptake of DRR Investment in Developing Countries.

INTRODUCTION: With a renewed emphasis on evidence-based risk sensitive investment promoted under the Sendai Framework for Disaster Risk Reduction 2015-2030, technical demands for analytical tools such as probabilistic cost-benefit analysis (CBA) will likely increase in the foreseeable future. This begs a number of pragmatic questions such as whether or not sophisticated quantitative appraisal tools are effective in raising policy awareness and what alternatives are available. METHOD: This article briefly reviews current practices of analytical tools such as probabilistic cost-benefit analysis and identifies issues associated with its applications in small scale community based DRR interventions. RESULTS: The article illustrate that while best scientific knowledge should inform policy and practice in principle, it should not create an unrealistic expectation that the state-of-the art methods must be used in all cases, especially for small scale DRR interventions in developing countries, where data and resource limitations and uncertainty are high, and complex interaction and feedback may exist between DRR investment, community response and longer-term development outcome.  DISCUSSION: Alternative and more participatory approaches for DRR appraisals are suggested which includes participatory serious games that are increasingly being used to raise awareness and identify pragmatic strategies for change that are needed to bring about successful uptake of DRR investment and implementation of DRR mainstreaming.

Revisiting the 'disaster and development' debate - Toward a broader understanding of macroeconomic risk and resilience.

Debate regarding the relationship between socioeconomic development and natural disasters remains at the fore of global discussions, as the potential risk from climate extremes and uncertainty pose an increasing threat to developmental prospects. This study reviews statistical investigations of disaster and development linkages, across topics of macroeconomic growth, public governance and others to identify key challenges to the current approach to macro-level statistical investigation. Both theoretically and qualitatively, disaster is known to affect development through a number of channels: haphazard development, weak institutions, lack of social safety nets and short-termism of our decision-making practices are some of the factors that drive natural disaster risk. Developmental potentials, including the prospects for sustainable and equitable growth, are in turn threatened by such accumulation of disaster risks. However, quantitative evidence regarding these complex causality chains remains contested due to several reasons. A number of theoretical and methodological limitations have been identified, including the use of GDP as a proxy measurement of welfare, issues with natural disaster damage reporting and the adoption of ad hoc model specifications and variables, which render interpretation and cross-comparison of statistical analysis difficult. Additionally, while greater attention is paid to economic and institutional parameters such as GDP, remittance, corruption and public expenditure as opposed to hard-to-quantify yet critical factors such as environmental conditions and social vulnerabilities. These are gaps in our approach that hamper our comprehensive understanding of the disaster-development nexus. Important areas for further research are identified, including recognizing and addressing the data constraints, incorporating sustainability and equity concerns through alternatives to GDP, and finding novel approaches to examining the complex and dynamic relationships between risk, vulnerability, resilience, adaptive capacity and development.

Probabilistic cost-benefit analysis of disaster risk management in a development context.

Limited studies have shown that disaster risk management (DRM) can be cost-efficient in a development context. Cost-benefit analysis (CBA) is an evaluation tool to analyse economic efficiency. This research introduces quantitative, stochastic CBA frameworks and applies them in case studies of flood and drought risk reduction in India and Pakistan, while also incorporating projected climate change impacts. DRM interventions are shown to be economically efficient, with integrated approaches more cost-effective and robust than singular interventions. The paper highlights that CBA can be a useful tool if certain issues are considered properly, including: complexities in estimating risk; data dependency of results; negative effects of interventions; and distributional aspects. The design and process of CBA must take into account specific objectives, available information, resources, and the perceptions and needs of stakeholders as transparently as possible. Intervention design and uncertainties should be qualified through dialogue, indicating that process is as important as numerical results.

Refocusing disaster aid.

With new modeling techniques for estimating and pricing the risks of natural disasters, the donor community is now in a position to help the poor cope with the economic repercussions of disasters by assisting before they happen. Such assistance is possible with the advent of novel insurance instruments for transferring catastrophe risks to the global financial markets. Donor-supported risk-transfer programs not only would leverage limited disaster-aid budgets but also would free recipient countries from depending on the vagaries of postdisaster assistance. Both donors and recipients stand to gain, especially because the instruments can be closely coupled with preventive measures.

The contribution from shipping emissions to air quality and acid deposition in Europe.

A global three-dimensional Lagrangian chemistry-transport model STOCHEM is used to describe the European regional acid deposition and ozone air quality impacts along the Atlantic Ocean seaboard of Europe, from the SO2, NOx, VOCs and CO emissions from international shipping under conditions appropriate to the year 2000. Model-derived total sulfur deposition from international shipping reaches over 200 mg S m(-2) yr(-1) over the southwestern approaches to the British Isles and Brittany. The contribution from international shipping to surface ozone concentrations during the summertime, peaks at about 6 ppb over Ireland, Brittany and Portugal. Shipping emissions act as an external influence on acid deposition and ozone air quality within Europe and may require control actions in the future if strict deposition and air quality targets are to be met.