资源环境科技发展态势分析平台

Traditional methods of investment appraisal have been criticized in the context of climate change adaptation. Economic assessment of adaptation options needs to explicitly incorporate the uncertainty of future climate conditions and should recognise that uncertainties may diminish over time as a result of improved understanding and learning. Real options analysis (ROA) is an appraisal tool developed to incorporate concepts of flexibility and learning that relies on probabilistic data to characterise uncertainties. It is also a relatively resource-intensive decision support tool. We test whether, and to what extent, learning can result from the use of successive generations of real life climate scenarios, and how non-probabilistic uncertainties can be handled through adapting the principles of ROA in coastal economic adaptation decisions. Using a relatively simple form of ROA on a vulnerable piece of coastal rail infrastructure in the United Kingdom, and two successive UK climate assessments, we estimate the values associated with utilising up-dated information on sea-level rise. The value of learning can be compared to the capital cost of adaptation investment, and may be used to illustrate the potential scale of the value of learning in coastal protection, and other adaptation contexts.