Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model

Bacour, Cédric; MacBean, Natasha; Chevallier, Frédéric; Léonard, Sébastien; Koffi, Ernest N.; Peylin, Philippe

doi:https://doi.org/10.5194/bg-20-1089-2023

Articles | Volume 20, issue 6

https://doi.org/10.5194/bg-20-1089-2023

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

https://doi.org/10.5194/bg-20-1089-2023

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

Articles | Volume 20, issue 6

Research article

|

23 Mar 2023

Research article |

| 23 Mar 2023

Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model

Cédric Bacour, Natasha MacBean, Frédéric Chevallier, Sébastien Léonard, Ernest N. Koffi, and Philippe Peylin

Supplement

https://doi.org/10.5194/bg-20-1089-2023-supplement

Data sets

La Thuile Synthesis Dataset FLUXNET https://fluxnet.org/data/la-thuile-dataset/

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Short summary

The impact of assimilating different dataset combinations on regional to global-scale C budgets is explored with the ORCHIDEE model. Assimilating simultaneously multiple datasets is preferable to optimize the values of the model parameters and avoid model overfitting. The challenges in constraining soil C disequilibrium using atmospheric CO₂ data are highlighted for an accurate prediction of the land sink distribution.