Uncertainty Quantification Using Multiple Models—Prospects and Challenges

Abstract

Model evaluation for long-term climate predictions must be done on quantities other than the actual prediction, and a comprehensive uncertainty quantificationUncertainty quantificationis impossible. An ad hoc alternative is provided by coordinated model intercomparisonsModel intercomparisonswhich typically use a ``one model one vote'' approach. The problem with such an approach is that it treats all models as independent and equally plausible. Reweighting all models of the ensemble for performance and dependence seems like an obvious way to improve on model democracy, yet there are open questions on what constitutes a ``good'' model, how to define dependency, how to interpret robustnessRobustness, and how to incorporate background knowledgeBackground knowledge. UnderstandingUnderstandingthose issues have the potential to increase confidence in model predictions in modeling efforts outside of climate scienceClimate sciencewhere similar challenges exist.