Can Model Structure Families Be Inferred from Model Output?

Abstract:

In model studies, a careful consideration of uncertainty is needed. Parameter and data uncertainty can be explored by sampling, but model structure uncertainty is more challenging to capture since the underlying hypotheses of many models are not directly clear. This study explores whether model structure can be inferred from model output. We created a dendrogram (family tree) based on model structure using a modular modelling framework. Subsequently, we created dendrograms based on model output. We determined the correlation between both dendrograms to analysed if model structure families could be inferred from model output. Results from this experiment over 671 climate instances showed that the performance of the inference depends on the type of output evaluated, and the climate. However, the performance of the inference is overall low, implying that model structure cannot be inferred from model output. These results demonstrates the need to further investigate opportunities to sample model space.