EGU21-15110
https://doi.org/10.5194/egusphere-egu21-15110
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Reconstructions and predictions of the global carbon cycle with an emission-driven Earth System Model

Hongmei Li1, Tatiana Ilyina1, Tammas Loughran2, and Julia Pongratz1,2
Hongmei Li et al.
  • 1Max Planck Institute for Meteorology, Hamburg, Germany (hongmei.li@mpimet.mpg.de)
  • 2Department of Geography, Ludwig Maximilian University, Munich, Germany

The global carbon budget including CO2 fluxes among different reservoirs and atmospheric carbon growth rate vary substantially in interannual to decadal time-scales. Reconstructing and predicting the variable global carbon cycle is of essential value of tracing the fate of carbon and the corresponding climate and ecosystem changes. For the first time, we extend our prediction system based on the Max Planck Institute Earth system model (MPI-ESM) from concentration-driven to emission-driven taking into account the interactive carbon cycle and hence enabling prognostic atmospheric carbon increment. 

By assimilating atmospheric and oceanic observational data products into MPI-ESM decadal prediction system, we can reproduce the observed variations of the historical global carbon cycle globally. The reconstruction from the fully coupled model enables quantification of global carbon budget within a close Earth system and therefore avoids the budget imbalance term of budgeting the carbon with standalone models. Our reconstructions of carbon budget provide a novel approach for supporting global carbon budget and understanding the dominating processes. Retrospective predictions based on the  emission-driven hindcasts, which are initiated from the reconstructions, show predictive skill in the atmospheric carbon growth rate, air-sea CO2 fluxes, and air-land CO2 fluxes. The air-sea CO2 fluxes have higher predictive skill up to 5 years, and the air-land CO2 fluxes and atmospheric carbon growth rate show predictive skill of 2 years. Our results also suggest predictions based on Earth system models enable reproducing and further predicting the evolution of atmospheric CO2 concentration changes. The earth system predictions will provide valuable inputs for understanding the global carbon cycle and supporting climate relevant policy development. 

How to cite: Li, H., Ilyina, T., Loughran, T., and Pongratz, J.: Reconstructions and predictions of the global carbon cycle with an emission-driven Earth System Model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15110, https://doi.org/10.5194/egusphere-egu21-15110, 2021.

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