We propose an approach to obtain weights for calculating averages of variables from Earth system models (ESM) based on concepts from information theory. It quantifies a relative distance between model output and reality, even though it is impossible to know the absolute distance from model predictions to reality. The relative ranking among models is based on concepts of model selection and multi-model averages previously developed for simple statistical models, but adapted here for ESMs.