Abstract
Simulation-based weather and climate prediction now involves the use of methods that reflect a deep
concern with uncertainty. These methods, known as ensemble prediction methods, produce multiple
simulations for predictive periods of interest, using different initial conditions, parameter values and/or
model structures. This paper provides a non-technical overview of current ensemble methods and
considers how the results of studies employing these methods should be interpreted, paying special
attention to probabilistic interpretations. A key conclusion is that, while complicated inductive
arguments might be given for the trustworthiness of probabilistic weather forecasts obtained from
ensemble studies, analogous arguments are out of reach in the case of long-term climate prediction. In
light of this, the paper considers how predictive uncertainty should be conveyed to decision makers.