Characterizing Uncertain Sea Level Rise Projections to Support Investment Decisions

Published in: Public Interest Energy Research Program White Paper, no. CEC-500-2012-056, July 2012

Posted on RAND.org on June 01, 2012

by Robert J. Lempert, Ryan L. Sriver, Klaus Keller

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Many institutions worldwide are considering how to include expectations about future sea level rise into their investment decisions regarding large capital infrastructures. This paper examines how to characterize deeply uncertain climate change projections to support such decision by examining a question facing the Port of Los Angeles: how to address the potential for presumably low probability but large impact levels of extreme sea level rise in its investment plans? Such extreme events—for instance, increased storm frequency and/or a rapid increase in the rate of sea level rise—can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study uses a robust decision making (RDM) analysis to address two questions: (1) under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme sea level rise at the next upgrade pass a cost-benefit test, and (2) does current science and other available information suggest such conditions are sufficiently likely to justify such an investment? A decision to harden at the next upgrade would merit serious consideration for only one of the four Port facilities considered and hardening costs would have to be 5 to 250 times smaller than current estimates to warrant consideration for the other three facilities. This study also compares and contrasts a robust decision making analysis with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations 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.

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