Drivers of intermodel uncertainty in land carbon sink projections

Padrón, Ryan S.; Gudmundsson, Lukas; Liu, Laibao; Humphrey, Vincent; Seneviratne, Sonia I.

doi:https://doi.org/10.5194/bg-19-5435-2022

Articles | Volume 19, issue 23

https://doi.org/10.5194/bg-19-5435-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-19-5435-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 23

Research article

|

05 Dec 2022

Research article |

| 05 Dec 2022

Drivers of intermodel uncertainty in land carbon sink projections

Ryan S. Padrón, Lukas Gudmundsson, Laibao Liu, Vincent Humphrey, and Sonia I. Seneviratne

Supplement

https://doi.org/10.5194/bg-19-5435-2022-supplement

Data sets

ESGF Node at LLNL ESGF https://esgf-node.llnl.gov/search/cmip6/

Model code and software

Scripts for the article "Drivers of intermodel uncertainty in land carbon sink projections" R. S. Padrón, L. Gudmundsson, L. Liu, V. Humphrey, and S. I. Seneviratne https://doi.org/10.3929/ethz-b-000579451

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Short summary

The answer to how much carbon land ecosystems are projected to remove from the atmosphere until 2100 is different for each Earth system model. We find that differences across models are primarily explained by the annual land carbon sink dependence on temperature and soil moisture, followed by the dependence on CO₂ air concentration, and by average climate conditions. Our insights on why each model projects a relatively high or low land carbon sink can help to reduce the underlying uncertainty.