Articles | Volume 26, issue 4
https://doi.org/10.5194/acp-26-2561-2026
https://doi.org/10.5194/acp-26-2561-2026
Research article
 | 
18 Feb 2026
Research article |  | 18 Feb 2026

Constraining a data-driven CO2 flux model by ecosystem and atmospheric observations using atmospheric transport

Samuel Upton, Markus Reichstein, Wouter Peters, Santiago Botía, Jacob A. Nelson, Sophia Walther, Martin Jung, Fabian Gans, László Haszpra, and Ana Bastos

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Latest update: 01 Aug 2026
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Short summary
We create a hybrid ecosystem-level carbon flux model using both eddy-covariance observations and observations of the atmospheric mole fraction of CO2 at three tall-tower observatories. Our study uses an atmospheric transport model (STILT) to connect the atmospheric signal to the ecosystem-level model. We show that this inclusion of atmospheric information meaningfully improves the model's representation of the interannual variability of the global net flux of CO2.
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