EGU22-10228
https://doi.org/10.5194/egusphere-egu22-10228
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Near-term prediction of the global carbon cycle using EC-Earth3-CC, the Carbon Cycle version of the EC-Earth3 Earth System Model

Etienne Tourigny1, Raffaele Bernardello1, Valentina Sicardi1, Pablo Ortega1, Yohan Ruprich Robert1, Vladimir Lapin1, Juan C. Acosta Navarro1, Roberto Bilbao1, Arndt Meier1, Hongmei Li2, and Tatiana Ilyina2
Etienne Tourigny et al.
  • 1Barcelona Supercomputing Center, Earth Sciences Department, Barcelona, Spain
  • 2Max Planck Institute for Meteorology , Hamburg, Germany

Anthropogenic CO2 emissions are associated with global warming in the late 20th century and beyond. Climate-carbon feedbacks will likely result in a higher airborne fraction of emitted CO2 in the future. However, the variability in atmospheric CO2 growth rate is largely controlled by natural variability and is poorly understood. This can interfere with the attribution  of slowing CO2 growth rates  to reducing emissions during the implementation of the Paris Agreement. There is thus a need to both improve our understanding of the processes controlling the global carbon cycle and establish a near-term prediction system of the climate and carbon cycle.

As part of the 4C (Carbon Cycle Interactions in the Current Century) project, the Barcelona Supercomputing Center is implementing a new system for near-term prediction of the climate and carbon cycle interactions using EC-Earth3-CC, the Carbon Cycle version of the EC-Earth3 Earth System Model. This new system is based on the existing operational climate prediction system developed by the BSC, contributing to the WMO Global Annual to Decadal Climate Update. EC-Earth3-CC comprises the IFS atmospheric model, the NEMO ocean model, the PISCES ocean biogeochemistry model, the LPJ-GUESS dynamic vegetation model, the TM5 global atmospheric transport model and the OASIS3 coupler. The system uses initial conditions from in-house ocean biogeochemical and land/vegetation reconstructions based on global atmospheric/ocean reanalyses. By performing retrospective decadal predictions of ocean and land carbon uptake we are able to evaluate the performance of the system in predicting CO2 fluxes and atmospheric CO2 concentrations.

We will present results from the latest concentration- and emission-driven retrospective predictions (or hindcasts) using our system, highlighting the skill and biases of the carbon fluxes and atmospheric CO2. We will also present future predictions for 2022 and beyond, a prototype for the operational system for prediction of future atmospheric CO2.

How to cite: Tourigny, E., Bernardello, R., Sicardi, V., Ortega, P., Ruprich Robert, Y., Lapin, V., Acosta Navarro, J. C., Bilbao, R., Meier, A., Li, H., and Ilyina, T.: Near-term prediction of the global carbon cycle using EC-Earth3-CC, the Carbon Cycle version of the EC-Earth3 Earth System Model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10228, https://doi.org/10.5194/egusphere-egu22-10228, 2022.