Articles | Volume 18, issue 15
https://doi.org/10.5194/gmd-18-4915-2025
https://doi.org/10.5194/gmd-18-4915-2025
Methods for assessment of models
 | 
11 Aug 2025
Methods for assessment of models |  | 11 Aug 2025

Spatially varying parameters improve carbon cycle modeling in the Amazon rainforest with ORCHIDEE r8849

Lei Zhu, Philippe Ciais, Yitong Yao, Daniel Goll, Sebastiaan Luyssaert, Isabel Martínez Cano, Arthur Fendrich, Laurent Li, Hui Yang, Sassan Saatchi, and Wei Li

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Short summary
This study enhances the accuracy of modeling the carbon dynamics of the Amazon rainforest by optimizing key model parameters based on satellite data. Using spatially varying parameters for tree mortality and photosynthesis, we improved predictions of biomass, productivity, and tree mortality. Our findings highlight the critical role of wood density and water availability in forest processes, offering insights to use in refining global carbon cycle models.
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