Generalizing uncertainty decomposition theory in climate change impact assessments

Abstract

Most studies of the uncertainties in climate change impact assessments focus on each stage independently without considering correlations between stages. Therefore, it is difficult to quantify the relative contribution of each stage to the total uncertainty and to identify how uncertainties are propagated as the stages proceed. In this study, we propose a new method for decomposing total uncertainty to components from individual stages. The proposed method is more theoretically sound compared to existing methods because the sum of the uncertainties from individual stages is always equal to the total uncertainty. In addition, the results of real data analysis indicate that our proposed method provides reasonable uncertainty decomposition.