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Spatial attribution of temporal variability in global land-atmosphere CO2 exchange using a model-data integration framework
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  • Hoontaek Lee,
  • Martin Jung,
  • Nuno Carvalhais,
  • Markus Reichstein,
  • Matthias Forkel,
  • A. Anthony Bloom,
  • Javier Pacheco-Labrador,
  • Sujan Koirala
Hoontaek Lee
Max Planck Institute for Biogeochemistry

Corresponding Author:[email protected]

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Martin Jung
Max-Planck-Institute for Biogeochemistry
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Nuno Carvalhais
Max Planck Institute for Biogeochemistry
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Markus Reichstein
Max Planck Institute fur Biogeochemistry
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Matthias Forkel
Technische Universität Dresden
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A. Anthony Bloom
Jet Propulsion Laboratory, California Institute of Technology
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Javier Pacheco-Labrador
Environmental Remote Sensing and Spectroscopy Laboratory (SpecLab), Spanish National Research Council (CSIC)
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Sujan Koirala
Max Planck Institute for Biogeochemistry
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Abstract

The spatial contribution to the global land-atmosphere carbon dioxide (CO\textsubscript{2}) exchange is crucial in understanding and projecting the global carbon cycle, yet different studies diverge on the dominant regions. Informing land models with observational data is a promising way to reduce the parameter and structural uncertainties and advance our understanding. Here, we develop a parsimonious diagnostic process-based model of land carbon cycles, constraining parameters with observation-based products. We compare CO\textsubscript{2} flux estimates from our model with observational constraints and Trends in Net Land-Atmosphere Carbon Exchange (TRENDY) model ensemble to show that our model reasonably reproduces the seasonality of net ecosystem exchange (NEE) and GPP and interannual variability (IAV) of NEE. Finally, we use the developed model, TRENDY models, and observational constraints to attribute variability in global NEE and gross primary productivity (GPP) to regional variability. The attribution analysis confirms the dominance of Northern temperate and boreal regions in the seasonality of CO\textsubscript{2} fluxes. Regarding NEE IAV, we identify a significant contribution from tropical savanna regions as previously perceived. Furthermore, we highlight that tropical humid regions are also identified as at least equally relevant contributors as semi-arid regions. At the same time, the largest uncertainty among ensemble members of NEE constraint and TRENDY models in the tropical humid regions underscore the necessity of better process understanding and more observations in these regions. Overall, our study identifies tropical humid regions as key regions for global land-atmosphere CO\textsubscript{2} exchanges and the inter-model spread of its modeling.
05 Jun 2024Submitted to ESS Open Archive
10 Jun 2024Published in ESS Open Archive