Model independence in multi-model ensemble prediction

Abstract

This paper outlines the emerging research area of model independence in multimodel ensemble prediction, explains why it is important, and contextualises several published attempts to characterise it. In particular, we highlight model independence and model performance as two unrelated properties of model prediction, and by doing so address the common misconception that striving for independent model ensemble members promotes divergence from observed behaviour.