Climate change. Is weather event attribution necessary for adaptation funding?

Human Exceptionalist Thinking about Climate Change

Although global climate change poses a real and looming threat to both human societies and the natural world, large gaps in understanding exist between the general public and the scientific community. One factor contributing to such gaps could be the use of intuitive thinking to understand complex phenomena. In two studies, we explore climate change understanding and engagement through the lens of an intuitive pattern of thinking, human exceptionalism, which refers to the tendency to infer that humans are exceptional to, and separable from, the rest of the natural world. In both studies, undergraduates thought about global climate change in human exceptionalist ways that were orthogonal to accuracy—for example, they correctly think that humans uniquely contribute to climate change compared to other organisms, but incorrectly think that humans will be uniquely immune to the effects of global climate change. Moreover, human exceptionalist thinking has real-world consequences; it was negatively associated with eco-friendly attitudes and behaviors, and negatively predicted individuals’ attribution of damage from recent hurricanes (i.e., hurricanes Michael and Florence) to global climate change. Finally, we demonstrated that increasing the salience of connections between humans and global climate change reduced human exceptionalism. Findings suggest that intuitive thinking in general, and human exceptionalism in particular, make important contributions to how we understand and reason about global climate change, and may be promising targets for interventions aimed at increasing pro-environmental attitudes and behaviors.

Small is beautiful: climate-change science as if people mattered

There is a widely accepted gap between the production and use of climate information. It is also widely accepted that at least part of the reason for this situation lies in the challenge of bridging between what may be characterized as ''top-down'' approaches to climate information on the global scale, and local decision contexts, which necessarily take a ''bottom-up'' perspective, in which climate change is just one factor among many to consider. We here reflect on the insights provided in a different context-that of economics-by E.F. Schumacher in his celebrated book Small is Beautiful (1973), to see what light they might shed on this challenge, with a focus on climate-change science for adaptation. Schumacher asked how economics might look if it was structured "as if people mattered". We ask the same question of climate-change science, and find many parallels. One is the need to grapple with the complexity of local situations, which can be addressed by expressing climate knowledge in a conditional form. A second is the importance of simplicity when dealing with deep uncertainty, which can be addressed through the use of physical climate storylines. A third is the need to empower local communities to make sense of their own situation, which can be addressed by developing ''intermediate technologies'' that build trust and transparency. Much of climate-change science is necessarily big science. We argue that in order to make climate information useable for adaptation, it is also necessary to discover the beauty of smallness.

Revisiting the Basic/Applied Science Distinction: The Significance of Urgent Science for Science Funding Policy

There has been a resurgence between two closely related discussions concerning modern science funding policy. The first revolves around the coherence and usefulness of the distinction between basic and applied science and the second concerns whether science should be free to pursue research according to its own internal standards or pursue socially responsible research agendas that are held accountable to moral or political standards. In this paper, I argue that the distinction between basic and applied science, and the concomitant debate about freedom and social responsibility, require revision. I contend that the distinction can only be maintained in cases of urgent science. I go on to elucidate the notion of urgent science using a case study from research of the climate refugee crisis.

How to make value-driven climate science for policy more ethical

In previous works, I examine inferential methods employed in Probabilistic Weather Event Attribution studies (PEAs), and explored various ways they can be used to aid in climate policy decisions and decision-making about climate justice issues. This paper evaluates limitations of PEAs and considers how PEA researchers' attributions of "liability" to specific countries for specific extreme weather events could be made more ethical. In sum, I show that it is routinely presupposed that PEA methods are not prone to inductive risks and presuppose that PEA researchers thus have no epistemic consequences or responsibilities for their attributions of liability. I argue that although PEAs are nevertheless crucially useful for practical decision-making, the attributions of liability made by PEA researchers are in fact prone to indicative risks and are influenced by non-epistemic values that PEA researchers should make transparent to make such studies more ethical. Finally, I outline possible normative approaches for making sciences, including PEAs, more ethical; and discuss implications of my arguments for the ongoing debate about how PEAs should guide climate policy and relevant legal decisions.

Climate change attribution and legal contexts: evidence and the role of storylines

In a recent very influential court case, Juliana v. United States, climate scientist Kevin Trenberth used the "storyline" approach to extreme event attribution to argue that greenhouse warming had affected and will affect extreme events in their regions to such an extent that the plaintiffs already had been or will be harmed. The storyline approach to attribution is deterministic rather than probabilistic, taking certain factors as contingent and assessing the role of climate change conditional on those factors. The US Government's opposing expert witness argued that Trenberth had failed to make his case because "all his conclusions of the injuries to Plaintiffs suffer from the same failure to connect his conditional approach to Plaintiffs' local circumstances." The issue is whether it is possible to make statements about individual events based on general knowledge. A similar question is sometimes debated within the climate science community. We argue here that proceeding from the general to the specific is a process of deduction and is an entirely legitimate form of scientific reasoning. We further argue that it is well aligned with the concept of legal evidence, much more so than the more usual inductive form of scientific reasoning, which proceeds from the specific to the general. This has implications for how attribution science can be used to support climate change litigation. "The question is", said Alice, "whether you can make words mean different things." "The question is", said Humpty Dumpty, "which is to be master - that's all." (Lewis Carroll, Alice's Adventures in Wonderland).

Climate change as a driver of food insecurity in the 2007 Lesotho-South Africa drought

Climate-induced food production shocks, like droughts, can cause food shortages and price spikes, leading to food insecurity. In 2007, a synchronous crop failure in Lesotho and South Africa-Lesotho's sole trading partner-led to a period of severe food insecurity in Lesotho. Here, we use extreme event attribution to assess the role of climate change in exacerbating this drought, going on to evaluate sensitivity of synchronous crop failures to climate change and its implications for food security in Lesotho. Climate change was found to be a critical driver that led to the 2007 crisis in Lesotho, aggravating an ongoing decline in food production in the country. We show how a fragile agricultural system in combination with a large trade-dependency on a climatically connected trading partner can lead to a nonlinear response to climate change, which is essential information for building a climate-resilient food-supply system now and in the future.

Attribution of extreme weather and climate-related events

Extreme weather and climate-related events occur in a particular place, by definition, infrequently. It is therefore challenging to detect systematic changes in their occurrence given the relative shortness of observational records. However, there is a clear interest from outside the climate science community in the extent to which recent damaging extreme events can be linked to human-induced climate change or natural climate variability. Event attribution studies seek to determine to what extent anthropogenic climate change has altered the probability or magnitude of particular events. They have shown clear evidence for human influence having increased the probability of many extremely warm seasonal temperatures and reduced the probability of extremely cold seasonal temperatures in many parts of the world. The evidence for human influence on the probability of extreme precipitation events, droughts, and storms is more mixed. Although the science of event attribution has developed rapidly in recent years, geographical coverage of events remains patchy and based on the interests and capabilities of individual research groups. The development of operational event attribution would allow a more timely and methodical production of attribution assessments than currently obtained on an ad hoc basis. For event attribution assessments to be most useful, remaining scientific uncertainties need to be robustly assessed and the results clearly communicated. This requires the continuing development of methodologies to assess the reliability of event attribution results and further work to understand the potential utility of event attribution for stakeholder groups and decision makers. WIREs Clim Change 2016, 7:23-41. doi: 10.1002/wcc.380 For further resources related to this article, please visit the WIREs website.

Adapting to extreme events related to natural variability and climate change: the imperative of coupling technology with strong regulation and governance

In recent years there has been an increase in extreme events related to natural variability (such as earthquakes, tsunamis and hurricanes) and climate change (such as flooding and more extreme weather). Developing innovative technologies is crucial in making society more resilient to such events. However, little emphasis has been placed on the role of human decision-making in maximizing the positive impacts of technological developments. This is exacerbated by the lack of appropriate adaptation options and the privatization of existing infrastructure, which can leave people exposed to increasing risk. This work examines the need for more robust government regulation and legislation to complement developments and innovations in technology in order to protect communities against such extreme events.

Attribution of changes in precipitation patterns in African rainforests

Tropical rainforests in Africa are one of the most under-researched regions in the world, but research in the Amazonian rainforest suggests potential vulnerability to climate change. Using the large ensemble of Atmosphere-only general circulation model (AGCM) simulations within the weather@home project, statistics of precipitation in the dry season of the Congo Basin rainforest are analysed. By validating the model simulation against observations, we could identify a good model performance for the June, July, August (JJA) dry season, but this result does need to be taken with caution as observed data are of poor quality. Additional validation methods have been used to investigate the applicability of probabilistic event attribution analysis from large model ensembles to a tropical region, in this case the Congo Basin. These methods corroborate the confidence in the model, leading us to believe the attribution result to be robust. That is, that there are no significant changes in the risk of low precipitation extremes during this dry season (JJA) precipitation in the Congo Basin. Results for the December, January, February dry season are less clear. The study highlights that attribution analysis has the potential to provide valuable scientific evidence of recent or anticipated climatological changes, especially in regions with sparse observational data and unclear projections of future changes. However, the strong influence of sea surface temperature teleconnection patterns on tropical precipitation provides more challenges in the set up of attribution studies than midlatitude rainfall.

Projections of future extreme weather losses under changes in climate and exposure

Many attempts are made to assess future changes in extreme weather events due to anthropogenic climate change, but few studies have estimated the potential change in economic losses from such events. Projecting losses is more complex as it requires insight into the change in the weather hazard but also into exposure and vulnerability of assets. This article discusses the issues involved as well as a framework for projecting future losses, and provides an overview of some state-of-the-art projections. Estimates of changes in losses from cyclones and floods are given, and particular attention is paid to the different approaches and assumptions. All projections show increases in extreme weather losses due to climate change. Flood losses are generally projected to increase more rapidly than losses from tropical and extra-tropical cyclones. However, for the period until the year 2040, the contribution from increasing exposure and value of capital at risk to future losses is likely to be equal or larger than the contribution from anthropogenic climate change. Given the fact that the occurrence of loss events also varies over time due to natural climate variability, the signal from anthropogenic climate change is likely to be lost among the other causes for changes in risk, at least during the period until 2040. More efforts are needed to arrive at a comprehensive approach that includes quantification of changes in hazard, exposure, and vulnerability, as well as adaptation effects.