The manuscript "TorchClim v1.0: A deep-learning framework for climate model physics" by David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett describes an application of a machine learning (ML) approach within the CAM AGCM. The aim of this study is to introduce an effective framework that can be adapted to implement ML approaches in climate models development. The sudy has a technical aspect and a climate model related aspect. My background is in climate dynamics and modelling. I cannot really comment on the computer technology aspects. The study addresses an important aspect in climate model development: how to include powerful ML approaches into model development. The manuscript should be considered for publication, but there are a number of aspects the authors should consider before publication.
Baker, Allison, Dorit Hammerling, Michael Levy, Haiying Xu, John Dennis, Brian Eaton, James Edwards, Cecile Hannay, Sheri Mickelson, Richard Neale, Doug Nychka, Jay Shollenberger, Joseph Tribbia, Mariana Vertenstein, David Williamson, 2015:A new ensemble-based consistency test for the Community Earth System Model (pyCECT v1.0).Geoscientific Model Development,OpenSky.
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