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.

Model code and software

Parsimonious Canopy Model (PCM) v1.0 Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar https://doi.org/10.5281/zenodo.6373776

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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.