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

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

doi:https://doi.org/10.5194/gmd-18-4915-2025

Articles | Volume 18, issue 15

https://doi.org/10.5194/gmd-18-4915-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-18-4915-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 15

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

Supplement

https://doi.org/10.5194/gmd-18-4915-2025-supplement

Data sets

Source code and data for "Spatially varying parameters improve carbon cycle modeling in the Amazon rainforest with ORCHIDEE r8849" L. Zhu https://doi.org/10.5281/zenodo.15023110

Mapping Global Live Woody Vegetation Biomass at Optimum Spatial Resolutions Y. Yu et al. https://doi.org/10.5281/zenodo.7583611

CRU JRA v2.4: A forcings dataset of gridded land surface blend of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data; Jan.1901–Dec.2022 University of East Anglia Climatic Research Unit and I. C. Harris https://catalogue.ceda.ac.uk/uuid/aed8e269513f446fb1b5d2512bb387ad

Harmonized World Soil Database version 2.0 (https://data.isric.org/geonetwork/srv/api/records/54aebf11-ec73-4ff8-bf6c-ecff4b0725ea) FAO and IIASA https://doi.org/10.4060/cc3823en

Reference maps of soil phosphorus for the pan-Amazon region: code and data J. P. Darela-Filho and D. M. Lapola https://doi.org/10.25824/redu/FROESE

Global Patterns of Groundwater Table Depth (http://thredds-gfnl.usc.es/thredds/catalog/GLOBALWTDFTP/catalog.html) Y. Fan et al. https://doi.org/10.1126/science.1229881

Global patterns of tree wood density (1.0) H. Yang et al. https://doi.org/10.5281/zenodo.10804643

A Global, 0.05-Degree Product of Solar-Induced Chlorophyll Fluorescence Derived from OCO-2, MODIS, and Reanalysis Data (http://data.globalecology.unh.edu/data/GOSIF_v2/) X. Li and J. Xiao https://doi.org/10.3390/rs11050517

Model code and software

ORCHIDEE r8849 (Version r8849) L. Zhu https://doi.org/10.5281/zenodo.15080562

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.