Sea Level and Socioeconomic Uncertainty Drives High-End Coastal Adaptation Costs
Tony E. Wong, Catherine Ledna, Lisa Rennels, Hannah Sheets, Frank C., Errickson, Delavane Diaz, David Anthoff

TL;DR
This study demonstrates that using only a few benchmark percentiles to represent sea-level rise uncertainty can significantly underestimate high-end risks and the full range of adaptation costs, leading to potentially biased decision-making.
Contribution
It shows that simplified uncertainty characterizations in coastal impact models underestimate risks and costs compared to full ensemble approaches.
Findings
Underestimation of high-end damages by 18-46% using benchmark percentiles.
Underestimation of adaptation cost uncertainty range by a factor of 2-4.
Simplified models can bias coastal adaptation and mitigation decisions.
Abstract
Sea-level rise and associated flood hazards pose severe risks to the millions of people globally living in coastal zones. Models representing coastal adaptation and impacts are important tools to inform the design of strategies to manage these risks. Representing the often deep uncertainties influencing these risks poses nontrivial challenges. A common uncertainty characterization approach is to use a few benchmark cases to represent the range and relative probabilities of the set of possible outcomes. This has been done in coastal adaptation studies, for example, by using low, moderate, and high percentiles of an input of interest, like sea-level changes. A key consideration is how this simplified characterization of uncertainty influences the distributions of estimated coastal impacts. Here, we show that using only a few benchmark percentiles to represent uncertainty in future…
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Taxonomy
TopicsTropical and Extratropical Cyclones Research · Climate variability and models · Oceanographic and Atmospheric Processes
