Modeling climate change impacts at the science-policy boundary
Climate change is a daunting policy challenge, where decision-makers must respond to a highuncertainty and high-risk problem in an environment with a diverse multitude of stakeholders and unresolved ethical questions. For the past 25 years, integrated assessment models (IAMs) of global climate change have become standard tools for informing climate policy. IAMs are computer models that combine representations of biophysical systems and socioeconomic systems; they are used to simulate the causes, dynamics, and impacts of climate change. While IAMs are typically developed by scientists, their explicit purpose is to generate policy-relevant information. In this paper-based dissertation, I use a pragmatic model of science-policy relations as a theoretical and normative framework to examine the production and application of IAMs. My research contributes conceptually and empirically to the existing scholarship on the role of scientific models in policymaking. Together, the three articles included in this dissertation advance our understanding of the various inputs and outputs of policy-relevant scientific models, using climate change IAMs as a case study. In Article #1, my co-author and I investigate the sources and consequences of the numerous difficult modeling choices that IAM developers are required to make as a result of the pervasive uncertainty—both scientific and ethical—surrounding this topic. We argue that these choices are made in particular epistemic, ethical, and social contexts. Correspondingly, we illuminate the epistemic, ethical, and political consequences of these choices. Finally, adopting a co-productionist approach, we suggest that past modeling choices may constrain future model development by setting epistemic benchmarks, establishing ethical norms, and creating biases in academic publishing and policy application. We review and build on findings from various literatures to unpack the complex intersection of science, ethics, and politics that IAMs occupy. This leads us to suggest avenues for future empirical and theoretical research that may enable an integrated epistemicethical-political understanding of IAMs. Such transparency is necessary to judge the usefulness of IAMs in supporting climate change policymaking that is scientifically sound, ethically fair, and politically acceptable. Articles #2 and #3 extrapolate practical consequences from the conceptual groundwork established in Article #1. In Article #2, I apply a narrative research approach to examine how values and beliefs embedded in modeling choices may influence policy. I draw on research on the role of storytelling in scientific modeling, as well as a growing literature in policy studies investigating the