Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4401-2021
https://doi.org/10.5194/gmd-14-4401-2021
Development and technical paper
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16 Jul 2021
Development and technical paper | Highlight paper |  | 16 Jul 2021

fv3gfs-wrapper: a Python wrapper of the FV3GFS atmospheric model

Jeremy McGibbon, Noah D. Brenowitz, Mark Cheeseman, Spencer K. Clark, Johann P. S. Dahm, Eddie C. Davis, Oliver D. Elbert, Rhea C. George, Lucas M. Harris, Brian Henn, Anna Kwa, W. Andre Perkins, Oliver Watt-Meyer, Tobias F. Wicky, Christopher S. Bretherton, and Oliver Fuhrer

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Pace v0.2: a Python-based performance-portable atmospheric model
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Cited articles

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Brenowitz, N. D. and Bretherton, C. S.: Spatially Extended Tests of a Neural Network Parametrization Trained by Coarse-Graining, J. Adv. Model. Earth Sy., 11, 2728–2744, https://doi.org/10.1029/2019MS001711, 2019. a
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Short summary
FV3GFS is a weather and climate model written in Fortran. It uses Fortran so that it can run fast, but this makes it hard to add features if you do not (or even if you do) know Fortran. We have written a Python interface to FV3GFS that lets you import the Fortran model as a Python package. We show examples of how this is used to write model scripts, which reproduce or build on what the Fortran model can do. You could do this same wrapping for any compiled model, not just FV3GFS.
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