Articles | Volume 17, issue 8
https://doi.org/10.5194/gmd-17-3081-2024
https://doi.org/10.5194/gmd-17-3081-2024
Methods for assessment of models
 | 
19 Apr 2024
Methods for assessment of models |  | 19 Apr 2024

The computational and energy cost of simulation and storage for climate science: lessons from CMIP6

Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji

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Cited articles

Acosta, M. and Bretonnière, P.-A.: Towards Minimising Carbon Footprint of Climate Modelling: Modelling Centre Perspective, C report, 2018. a
Acosta, M. C., Palomas, S., and Tourigny, E.: Balancing EC-Earth3 Improving the Performance of EC-Earth CMIP6 Configurations by Minimizing the Coupling Cost, Earth Space Sci., 10, e2023EA002912, https://doi.org/10.1029/2023EA002912, 2023. a
Balaji, V.: Climate Computing: The State of Play, Comput. Sci. Eng., 17, 9–13, https://doi.org/10.1109/MCSE.2015.109, 2015. a
Balaji, V., Maisonnave, E., Zadeh, N., Lawrence, B. N., Biercamp, J., Fladrich, U., Aloisio, G., Benson, R., Caubel, A., Durachta, J., Foujols, M.-A., Lister, G., Mocavero, S., Underwood, S., and Wright, G.: CPMIP: measurements of real computational performance of Earth system models in CMIP6, Geosci. Model Dev., 10, 19–34, https://doi.org/10.5194/gmd-10-19-2017, 2017. a, b, c
Bauer, P., Dueben, P. D., Hoefler, T., Quintino, T., Schulthess, T. C., and Wedi, N. P.: The digital revolution of Earth-system science, Nat. Comput. Sci., 1, 104–113, https://doi.org/10.1038/s43588-021-00023-0, 2021. a
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Short summary
We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
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