Articles | Volume 19, issue 1
https://doi.org/10.5194/gmd-19-1-2026
https://doi.org/10.5194/gmd-19-1-2026
Development and technical paper
 | 
05 Jan 2026
Development and technical paper |  | 05 Jan 2026

Representing dynamic grassland density in the land surface model ORCHIDEE r9010

Siqing Xu, Sebastiaan Luyssaert, Yves Balkanski, Philippe Ciais, Nicolas Viovy, Liang Wan, and Jean Sciare

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Cited articles

Allaby, M.: Grasslands, Biomes of the Earth, Chelsea House, New York, 192 pp., ISBN 978-0-8160-5323-0, 2006. 
Balkanski, Y., Bonnet, R., Boucher, O., Checa-Garcia, R., and Servonnat, J.: Better representation of dust can improve climate models with too weak an African monsoon, Atmos. Chem. Phys., 21, 11423–11435, https://doi.org/10.5194/acp-21-11423-2021, 2021. 
Bartlett, M. K., Scoffoni, C., and Sack, L.: The determinants of leaf turgor loss point and prediction of drought tolerance of species and biomes: a global meta-analysis, Ecol. Lett., 15, 393–405, https://doi.org/10.1111/j.1461-0248.2012.01751.x, 2012. 
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Prescribing a fixed grassland density in the ORCHIDEE model limits its ability to capture grassland dynamics, leading to unrealistic mortality, especially in semi-arid grasslands. We proposed a dynamic density approach where a positive density-precipitation relationship emerges. This method improves spatial pattern, significantly reduces mortality, sustains productivity, and raises the aridity threshold above which frequent mortality events occur in grasslands.
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