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Description and evaluation of the CNRM-Cerfacs Climate Prediction System (C3PS)
  • +8
  • Emilia Sanchez-Gomez,
  • Roland Séférian,
  • Lauriane Batté,
  • Christophe Cassou,
  • Boris Dewitte,
  • Marie-Pierre Moine,
  • Rym Msadek,
  • Chloe Prodhomme,
  • Yeray Santana-Falcón,
  • Laurent Terray,
  • Aurore Voldoire
Emilia Sanchez-Gomez
CERFACS

Corresponding Author:[email protected]

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Roland Séférian
CNRM (Météo-France/CNRS)
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Lauriane Batté
Météo-France
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Christophe Cassou
CNRS-Cerfacs
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Boris Dewitte
CEAZA
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Marie-Pierre Moine
CECI-CERFACS
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Rym Msadek
CNRS/CERFACS
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Chloe Prodhomme
No Institution
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Yeray Santana-Falcón
Centre National de Recherches Météorologiques
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Laurent Terray
CERFACS
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Aurore Voldoire
CNRM / Météo-France
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Abstract

The CNRM-Cerfacs Climate Prediction System (C3PS) is a new research modeling tool for performing climate reanalyses and seasonal-to-multiannual predictions for a wide array of earth system variables. C3PS is based on the CNRM-ESM2-1 model including interactive aerosols and stratospheric chemistry schemes as well as terrestrial and marine biogeochemistry enabling a comprehensive representation of the global carbon cycle. C3PS operates through a seamless coupled initialization for the atmosphere, land, ocean, sea ice and biogeochemistry components that allows a continuum of predictions across seasonal to interannual time-scales. C3PS has also contributed to the Decadal Climate Prediction Project (DCPP-A) as part of the sixth Coupled Model Intercomparison Project (CMIP6). Here we describe the main characteristics of this novel earth system-based prediction platform, including the methodological steps for obtaining initial states to produce forecasts. We evaluate the entire C3PS initialisation procedure with the most up-to-date observations and reanalysis over 1960-2021, and we discuss the overall performance of the system in the light of the lessons learnt from previous and actual prediction platforms. Regarding the forecast skill, C3PS exhibits comparable seasonal predictive skill to other systems. At the decadal scale, C3PS shows significant predictive skill in surface temperature during the first two years after initialisation in several regions of the world. C3PS also exhibits potential predictive skill in net primary production and carbon fluxes several years in advance. This expands the possibility of applications of forecasting systems, such as the possibility of performing multi-annual predictions of marine ecosystems and carbon cycle.
05 Mar 2024Submitted to ESS Open Archive
07 Mar 2024Published in ESS Open Archive