Improved process representation of leaf phenology significantly shifts climate sensitivity of ecosystem carbon balance

Norton, Alexander J.; Bloom, A. Anthony; Parazoo, Nicholas C.; Levine, Paul A.; Ma, Shuang; Braghiere, Renato K.; Smallman, T. Luke

doi:https://doi.org/10.5194/bg-20-2455-2023

Articles | Volume 20, issue 12

https://doi.org/10.5194/bg-20-2455-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-20-2455-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 12

Research article

|

28 Jun 2023

Research article |

| 28 Jun 2023

Improved process representation of leaf phenology significantly shifts climate sensitivity of ecosystem carbon balance

Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman

Data sets

CARDAMOM Phenology Study: Dataset and Analysis Code Alexander Norton, Anthony A. Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and Luke T. Smallman https://doi.org/10.5281/zenodo.7793974

Model code and software

CARDAMOM-framework/CARDAMOM_v2.3: Publication: Norton et al. 2023 Alexander Norton https://doi.org/10.5281/zenodo.8063861

Short summary

This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.