The need for handling the deep uncertainty surrounding the future climate has led to various novel and robust approaches for decision-making under deep uncertainty (DMDU) when adapting to climate change. Here, an online and self-explanatory web-based tool was developed and tested with civil servants from five municipalities in Sweden challenged by rising sea levels. The municipalities used the tool by themselves and were then interviewed about the usability of the tool, the perceived urgency of climate change adaptation, and the possibilities for municipalities for handling the flexible solutions that are at the core of DMDU. Results were that the civil servants reported that the urgency of climate change adaptation has increased, that the tool changed their perspectives compared to traditional planning methods, and that changes in laws and regulations to accommodate decisions about flexible solutions were recommended.

Philosophers argue that many choices in science are influenced by values or have value-implications, ranging from the preference for some research method's qualities to ethical estimation of the consequences of error. Based on the argument that awareness of values in the scientific process is a necessary first step to both avoid bias and attune science best to the needs of society, an analysis of the role of values in the physical climate science production process is provided. Model-based assessment of climate sensitivity is taken as an illustrative example; climate sensitivity is useful here because of its key role in climate science and relevance for policy, by having been the subject of several assessments over the past decades including a recent shift in assessment method, and because it enables insights that apply to numerous other aspects of climate science. It is found that value-judgements are relevant at every step of the model-based assessment process, with a differentiated role of non-epistemic values across the steps, impacting the assessment in various ways. Scrutiny of current philosophical norms for value-management highlights the need for those norms to be re-worked for broader applicability to climate science. Recent development in climate science turning away from direct use of models for climate sensitivity assessment also gives the opportunity to start investigating the role of values in alternative assessment methods, highlighting similarities and differences in terms of the role of values that encourage further study.

Value sensitive design (VSD) aims at creating better technology based on social and ethical values. However, VSD has not been applied to long-term and uncertain future developments, such as societal planning for climate change. This paper describes a new method that combines elements from VSD with scenario planning. The method was developed for and applied to a case study of adaptation to sea level rise (SLR) in southern Sweden in a series of workshops. The participants of the workshops found that the method provided a framework for discussing long-term planning, enabled identification of essential values, challenged established planning practices, helped find creative solutions, and served as a reminder that we do not know what will happen in the future. Finally, we reflect on the limitations of the method and suggest further research on how it can be improved for value sensitive design of adaptation measures to manage uncertain future sea level rise.

Adaptive and flexible approaches based on implementing different measures as new information emerges have been proposed as a way of enabling robustness towards uncertain future climate change. However, the success of flexible approaches in practice depends on the stability of the relevant organizational landscapes. In this paper, we draw upon key insights from the institutional theories of organizations and research on public administration and climate adaptation in Sweden. We argue that potential organizational instabilities pose a substantial challenge for the mainstreaming of flexible approaches to climate adaptation. Given the unstable character of the relevant organizational landscape in a very stable country such as Sweden, it seems reasonable to also seriously doubt the capacity of the relevant authorities in less stable countries to carry out a great number of monitoring-intensive, and hence attention-demanding, adaptive governance processes over time. Based on our results we argue that it is perilous to simply assume that flexible approaches to climate adaptation will lead to greater robustness.

Value judgments in environmental risk assessments can sometimes have critical influences on policies. The phenomenon that values can have lasting effects is conceptualized as “value-inertia.” Value-inertia is exemplified and demonstrated through assessments of climate change risks. The problems of value-inertia are discussed, and suggestions to mitigate the problems are provided. Most importantly, decision-makers need to be aware that environmental risk assessments may be affected by value-inertia. However, because it is often difficult for decision-makers to both identify and compensate for previous value judgments, scientists and experts also have a moral responsibility to mitigate problems caused by value-inertia.

The Dynamic Adaptive Policy Pathways (DAPP) approach has successfully been used to manage uncertainties in large infrastructure projects. However, the viability of the DAPP approach for spatial planning in smaller municipal settings is not clear. This paper examines opportunities and constraints of using adaptive pathways approaches to help small municipalities plan for future sea-level rise. The methodology was based on developing a simplified DAPP-approach, which was tested in a multiple experimental case study of spatial planning projects in three municipalities in Sweden. The results show that the approach promoted vulnerability-based thinking among the end-users and generated new ideas on how to manage the uncertain long-term impacts of future sea-level rise. However, the increased understanding of uncertainties was used to justify static, rather than adaptive, solutions. This somewhat surprising outcome can be explained by perceived legal constraints, lack of experience of adaptive pathways, and unwillingness to prescribe actions that could prove difficult to enforce in the future. More research is needed to further understand at what planning phases dynamic policy pathway approaches work best and how current barriers in legislation, practices, mind-set, organization, and resources can be overcome.

Standard tools used in societal risk management such as probabilistic risk analysis or cost-benefit analysis typically define risks in terms of only probabilities and consequences and assume a utilitarian approach to ethics that aims to maximize expected utility. The philosopher Carl F. Cranor has argued against this view by devising a list of plausible aspects of the acceptability of risks that points towards a non-consequentialist ethical theory of societal risk management. This paper revisits Cranor's list to argue that the alternative ethical theory responsibility-catering prioritarianism can accommodate the aspects identified by Cranor and that the elements in the list can be used to inform the details of how to view risks within this theory. An approach towards operationalizing the theory is proposed based on a prioritarian social welfare function that operates on responsibility-adjusted utilities. A responsibility-catering prioritarian ethical approach towards managing risks is a promising alternative to standard tools such as cost-benefit analysis.

Handling uncertainties is a major challenge in climate change adaptation. A variety of robust decision support approaches that aim for better management of uncertainty have recently been emerging and are used in environmental planning. The present study examined to what extent existing processes of planning for future sea-level rise in Sweden utilised similar approaches. Three core principles of robust decision support approaches were identified and used as a tool for analyzing five cases of planning for future sea-level rise in companies and authorities at different levels in society. The results show that planning processes typically do not embrace uncertainties, do not use a bottom-up approach and do not specifically aim for robustness, which points to a discrepancy between current planning paradigms and the core principles of robust decision support approaches.

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions.