[Talk + Poster] From risk to action: Climate decision-making under deep uncertainty

Climate change adaptation decision-making is difficult due to the deep uncertainty in climate risk. Additionally, characteristics of the adaptation decisions such as cost, priorities of the decision-maker, etc. are often uncertain as well. We apply Bayesian Decision Analysis, a decision-making method designed to account for uncertainty, to an idealised example of heat stress in the United Kingdom. We perform uncertainty and sensitivity analysis (U&SA) to investigate how the optimal decision responds to variation in both risk and decision-related factors. By carrying out U&SA on the decision itself, rather than on the climate risk alone, we show that high uncertainty in risk does not necessarily lead to high uncertainty in decision. Additionally, the decision can often be more sensitive to decision-related characteristics rather than to components of risk, with great spatial variation. Performing U&SA through to the output decision is crucial to inform robust climate adaptation decision-making.