Articles | Volume 15, issue 18
Geosci. Model Dev., 15, 6957–6984, 2022
https://doi.org/10.5194/gmd-15-6957-2022
Geosci. Model Dev., 15, 6957–6984, 2022
https://doi.org/10.5194/gmd-15-6957-2022
Model description paper
16 Sep 2022
Model description paper | 16 Sep 2022

Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest

Bahar Bahrami et al.

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Short summary
Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.