A web application to facilitate crop model comparison in ensemble studies

Crop models are reference tools that can be used to evaluate the performances of cropping systems under current and future agro-climatic scenarios. A recent trend is the adoption of multi-model ensembles, as crop model responses vary across pedoclimatic contexts. We present the web application MOBEDIS, aimed at investigating the causes of differences in crop models' behaviour. MOBEDIS combines non-parametric statistical methods (Spearman correlation, Random Forest, Hierarchical clustering, Mantel statistics) to analyze and cluster crop models according to the relationship between final outputs (e.g., yield) and a set of intermediate outputs related to plant processes. We applied MOBEDIS in three case studies to (1) discuss its capability to facilitate the understanding of the behaviour of two crop models in a simulation experiment, and (2) prove its applicability for model ensemble studies. MOBEDIS is freely available and ready-to-use for understanding single model responses and identifying groups of crop models sharing similar behaviour.