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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Cited articles

Ariza-Carricondo, C., Mauro, F., Op de Beeck, M., Roland, M., Gielen, B., Vitale, D., Ceulemans, R., and Papale, D.: A comparison of different methods for assessing leaf area index in four canopy types, Central European Forestry Journal, 65, 67–80, https://doi.org/10.2478/forj-2019-0011, 2019. a, b, c
Arora, V.: Modeling vegetation as dynamic component in soil-vegetation-atmosphere transfer schemes and hydrological models, Rev. Geophys., 40, 1–26, https://doi.org/10.1029/2001RG000103, 2002. a, b, c
Arsenault, K., Nearing, G., Wang, S., Yatheendradas, S., and Peters-Lidard, C.: Parameter Sensitivity of the Noah-MP Land Surface Model with Dynamic Vegetation, J. Hydrometeorol., 19, 815–830, https://doi.org/10.1175/JHM-D-17-0205.1, 2018. a, b
Asaadi, A., Arora, V. K., Melton, J. R., and Bartlett, P.: An improved parameterization of leaf area index (LAI) seasonality in the Canadian Land Surface Scheme (CLASS) and Canadian Terrestrial Ecosystem Model (CTEM) modelling framework, Biogeosciences, 15, 6885–6907, https://doi.org/10.5194/bg-15-6885-2018, 2018. a, b, c, d, e
Balzarolo, M., Valdameri, N., Fu, Y. H., Schepers, L., Janssens, I. A., and Campioli, M.: Different determinants of radiation use efficiency in cold and temperate forests, Global Ecol. Biogeogr., 28, 1649–1667, https://doi.org/10.1111/geb.12985, 2019. a
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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.