High resolution data is overwhelming and this paper , co-authored by Pierre Gentine and Tom Beucler, tries to define an unsupervised machine learning technique to better compare Storm Resolving Climate Models (SRMs). Their analysis found that only six out of nine considered SRMs are dynamically consistent. This split among SRMs highlights the need to further investigate sub-grid parameterization choices.