Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 8
Articles | Volume 16, issue 8
https://doi.org/10.5194/gmd-16-2235-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-2235-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 8
Development and technical paper
 | 
26 Apr 2023
Development and technical paper |  | 26 Apr 2023

The Common Community Physics Package (CCPP) Framework v6

Dominikus Heinzeller, Ligia Bernardet, Grant Firl, Man Zhang, Xia Sun, and Michael Ek

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Cited articles

Ahmadov, R., Grell, G., James, E., Csiszar, I., Tsidulko, M., Pierce, B., McKeen, S., Benjamin, S., Alexander, C., Pereira, G., Freitas, S., and Goldberg, M.: Using VIIRS fire radiative power data to simulate biomass burning emissions, plume rise and smoke transport in a real-time air quality modeling system, in: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2806–2808, IEEE, 23–28 July 2017, Fort Worth, TX, https://doi.org/10.1109/IGARSS.2017.8127581, 2017. a
American Meteorological Society: Parameterization, Glossary of Meteorology 2022, https://glossary.ametsoc.org/wiki/Parameterization (last access: 23 April 2023), 2022. a
Barnes, H. C., Grell, G., Freitas, S., Li, H., Henderson, J., and Sun, S.: Aerosol Impacts for Convective Parameterizations: Recent Changes to Grell-Freitas Convective Parameterization, AMS, https://ams.confex.com/ams/102ANNUAL/meetingapp.cgi/Paper/391989 (last access: 23 April 2023), 2022. a
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical weather prediction, Nature, 525, 47–55, https://doi.org/10.1038/nature14956, 2015. a
Bernardet, L. R., Kavulich, M., Firl, G., Heinzeller, D., Zhang, M., and Trahan, S.: CCPP v6.0.0 Technical Documentation, Zenodo [code], https://doi.org/10.5281/zenodo.6780447, 2022. a, b, c, d, e
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The Common Community Physics Package is a collection of physical atmospheric parameterizations for use in Earth system models and a framework that couples the physics to a host model’s dynamical core. A primary goal for this effort is to facilitate research and development of physical parameterizations and physics–dynamics coupling methods while offering capabilities for numerical weather prediction operations, for example in the upcoming implementation of the Global Forecast System (GFS) v17.
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