Presenting Climate Projection Ensembles as Mean and Reasonable Worst Case, with Application to EURO-CORDEX Precipitation

Abstract

Users of ensemble climate projections have choices with respect to how they interpret and apply the ensemble. A simplistic approach is to consider just the ensemble mean and ignore the individual ensemble members. A more thorough approach is to consider every ensemble member, although for complex impact models this may be unfeasible. Building on previous work in ensemble weather forecasting we explore an approach in-between these two extremes, in which the ensemble is represented by the mean and a reasonable worst case. The reasonable worst case is calculated using Directional Component Analysis (DCA), which is a simple statistical method that gives a robust estimate of worst-case for a given linear metric of impact, and which has various advantages relative to alternative definitions of worst-case. We present new mathematical results that clarify the interpretation of DCA and we illustrate DCA with an extensive set of synthetic examples. We then apply the mean and worst-case method based on DCA to EURO-CORDEX projections of future precipitation in Europe, with two different impact metrics. We conclude that the mean and worst-case method based on DCA is suitable for climate projection users who wish to explore the implications of the uncertainty around the ensemble mean without having to calculate the impacts of every ensemble member.