CATASTROPHE, UNCERTAINTY, AND THE COSTS OF CLIMATE CHANGE DAMAGES
by
Evelyn
L. Wright
A Thesis Submitted to the Graduate
Faculty of Rensselaer Polytechnic Institute
in Partial
Fulfillment of the
Requirements for the Degree of
DOCTOR OF PHILOSOPHY
ABSTRACT
This dissertation presents a science-based approach to the economics of climate catastrophe. Despite the significant consideration of climate-related catastrophe in international greenhouse gas negotiations, little progress has been made in incorporating high-damage events into cost-benefit assessments. Climate economists appear to be waiting for climate scientists to provide them with a well-founded list of potential events and their probabilities. Meanwhile, the consensus emerging from the optimal control problem emphasizes low investment in greenhouse gas reductions and a strong role for economic adaptation.
An investigation of the sources of uncertainty about climate catastrophe reveals that, regardless of progress in scientific understanding, the probabilities of catastrophic events, their outcomes, and any greenhouse gas thresholds for their occurrence are likely to remain uncertain. A detailed review of paleoclimatic and modeling research concludes that the complex nature of the climate system makes transitions between alternative quasistable states inherently unpredictable. It is found that two widely discussed catastrophic scenarios fit the low-probability, high-damage profile universally assumed by economists. However, the possibility of major changes in ocean circulation patterns and accompanying regional climate disruptions does not. Rapid, globally synchronous changes in regional climates are found to be a common feature of the paleoclimate record, particularly at times when radiative forcing is undergoing change. It has been widely hypothesized that these changes are caused by changes in global patterns of ocean circulation. Several climate models have indicated that such changes are a likely consequence of increasing greenhouse gas concentrations.
This evidence suggests that a shift in current understanding of the source of climate change damages is required. Decreases in climate predictability, rather than the direct effects of a changed climate, are found to be the most significant source of damages. An option value investment model and a Bayesian learning model are then used to explore the impact of climate predictability on the timing of adaptation. These models find that decreased predictability leads to postponed adaptation and increased pre-adaptation damage costs, indicating that previous estimates of the damage reductions to be gained through adaptation have been excessively optimistic. The implications for climate economics and climate policy are then discussed.