Articles | Volume 15, issue 24
https://doi.org/10.5194/gmd-15-9111-2022
https://doi.org/10.5194/gmd-15-9111-2022
Model evaluation paper
 | 
20 Dec 2022
Model evaluation paper |  | 20 Dec 2022

Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)

Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan

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Cited articles

Alekseychik, P., Korrensalo, A., Mammarella, I., Vesala, T., and Tuittila, E. S.: Relationship between aerodynamic roughness length and bulk sedge leaf area index in a mixed-species boreal mire complex, Geophys. Res. Lett., 44, 5836–5843, https://doi.org/10.1002/2017GL073884, 2017. 
Bastrikov, V., MacBean, N., Bacour, C., Santaren, D., Kuppel, S., and Peylin, P.: Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2), Geosci. Model Dev., 11, 4739–4754, https://doi.org/10.5194/gmd-11-4739-2018, 2018. 
Bonan, G. B.: Climate Change and Terrestrial Ecosystem Modeling, Cambridge University Press, https://doi.org/10.1017/9781107339217, 2019. 
Botta, A., Viovy, N., Ciais, P., and Friedlingstein, P.: A global prognostic scheme of leaf onset using satellite data, Glob. Change Biol., 6, 709–726, 2000. 
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Short summary
There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
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