Coping with climate change uncertainty for adaptation planning: An improved criterion for decision making under uncertainty using UKCP09

AbstractDespite information on the benefits of climate change adaptation planning being widely available and well documented, in the UK at least relatively few real-world cases of scenario led adaptation have been documented. This limited uptake has been attributed to a variety of factors including the vast uncertainties faced, a lack of resources and potentially the absence of probabilities assigned to current climate change projections, thereby hampering conventional approaches to decision making under risk. Decision criteria for problems of uncertainty have been criticised for being too restrictive, crude, overly pessimistic, and data intensive. Furthermore, many cannot be reproduced reliably from sub-samples of the UKCP09 probabilistic dataset.This study critically compares current decision criteria for problems of uncertainty and subsequently outlines an improved criterion which overcomes some of their limitations and criticisms. This criterion, termed the Green Z-score, is then applied to a simplified real-world problem of designing an irrigation reservoir in the UK under climate change. The criterion is designed to be simple to implement, support robust decision making and provide reproducible results from sub-samples of the UKCP09 probabilistic dataset. It is designed to accommodate a wide range of risk appetites and attitudes and thereby encourage its use by decision makers who are presently struggling to determine whether and how to adapt to future climate change and its potential impacts.Analyses using sub-samples of the complete probabilistic dataset showed that the Green Z-score had comparable reproducibility to Laplace and improved reproducibility compared to other current decision criteria, and unlike Laplace is able to accommodate different risk attitudes