Abstract
Climate change policy—including matters involving both mitigation and adaptation—is informed by assessments of the risks and damages caused by climate change. Such assessments, in turn, depend on our ability to attribute specific impacts to climate change. Of particular interest is the exacerbating effect climate change is having on damaging, costly and potentially deadly extreme weather events, including heat waves, droughts, floods, storms and tornado outbreaks. A vigorous debate has arisen among researchers regarding best practices for attributing such events to climate change. This debate hinges on issues that are both scientific and philosophical in nature. Among the complicating considerations are (a) the differing levels of confidence in “thermodynamic” (direct effects of warming) and “dynamical” (indirect effects related to changes in atmospheric circulation and stability) influences, (b) the relative merit of “storyline” vs probability-based approaches, and in the latter case (c) alternative preferences for frequentist vs. Bayesian approaches to statistical inference. Last, but not least, is (d) the limitations of climate model-based attribution approaches in capturing subtle, real-world linkages between climate change and extreme weather events that are not well resolved in current generation climate models. I will review the current state of play in this debate, discussing some of my own research contributions in these areas.
