Max-Planck-Institute for Meteorology: Predicting the global carbon cycle to support decision-making related to carbon management

In a recent study Dr. Tatiana Ilyina, Dr. Hongmei Li, Aaron Spring and Dr. Wolfgang Müller, scientists at the Max Planck Institute for Meteorology, and a team of international colleagues used a set of prediction systems based on Earth-system models to establish predictive skills of the ocean and land carbon sinks and to infer predictability of the atmospheric CO2 growth rate. They found an emerging capacity of the initialized Earth-system model simulations for predicting the global carbon cycle.

Still picture of a visualization showing the evolution of atmospheric CO2 concentration in a MPI-ESM simulation under historical emissions and climate change forcing scenario SSP5-85.

Knowing the pathways of anthropogenic CO₂ in the climate system is crucial to verify the eﬀectiveness of fossil fuel emissions reduction measures. Predictions of the near‐term evolution would assist policy‐relevant analysis and carbon management activities. Lead author Dr. Tatiana Ilyina: “The question was: Can we predict if atmospheric CO₂ changes slower or faster than expected from changes in emissions?”

The answer to this question is not straightforward because variations of the natural land and ocean carbon sinks in response to climate variability strongly regulate year‐to‐year variations in the growth rate of atmospheric CO₂.

To address the problem, the authors used diﬀerent prediction systems that are based on Earth-system models and initialized by the observed state of the physical climate to assess how well these capture variations of the global land and ocean carbon sinks and their predictability. For the ﬁrst time they examined the resulting predictability of variations in the growth rate of atmospheric CO₂ that is driven by the response of carbon sinks to climate variability.

For the globally integrated ocean carbon sink, they showed predictability horizons of up to six years for some models, with even higher regional predictive skill in the Southern Ocean, North Atlantic, and North Pacific. For the land carbon sink, the scientists found that variations are predictable up to two years and thus limit predictability of changes in atmospheric CO₂ growth rate to two years.

The improved predictive skills oﬀer a powerful tool in support of decisions related to carbon management. They will help to verify near-term carbon emission reduction pathways and assess their efficiency.

Original publication

Ilyina, T., Li, H., Spring, A., Müller, W. A., Bopp, L., Chikamoto, M. O., et al. (2020). Predictable variations in the carbon sinks and atmospheric CO₂ growth in a multi-model framework. Geophysical Research Letters, 47. doi: 10.1029/2020GL090695

Contact

Dr. Tatiana Ilyina
Max Planck Institute for Meteorology
Email: tatiana.ilyina@we dont want spammpimet.mpg.de

Dr. Hongmei Li
Max-Planck-Institut für Meteorologie
E-Mail: hongmei.li@we dont want spammpimet.mpg.de

Aaron Spring
Max-Planck-Institut für Meteorologie
E-Mail: aaron.spring@we dont want spammpimet.mpg.de

Dr. Wolfgang Müller
Max-Planck-Institut für Meteorologie
E-Mail: wolfgang.mueller@we dont want spammpimet.mpg.de

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