Abstract

Attribution studies investigate the causes of recent global warming. For a few decades the scientific community generally adopted dynamical models – the so-called Global Climate Models (GCMs) – for such an investigation. These models show the essential role of anthropogenic forcings in driving the temperature behaviour of the last half century. In the last period even other (data-driven) methodological approaches were adopted for attribution studies. This allows the scientific community to compare the results coming from these different approaches and to possibly increase their robustness. For such a purpose, the paper explores the possibility of applying a robustness framework, so far used only in the case of multi-model GCM ensembles, to a strategy including models from different methodological orientations, assessing such an application especially in the light of the independence issue.

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