Modelling solar-induced chlorophyll fluorescence using the P-model, an optimality-based model for vegetation productivity.

Photosynthesis is the core engine of vegetation productivity, usually estimated by Gross Primary Production (GPP), the rate of carbon fixed by photosynthesis per unit of ground area. A better understanding of ecosystem productivity relies on two main streams of information: observations and modelling. However, both streams have severe limitations with respect to GPP: 1- no large-scale measurements exist for GPP, 2- while satellites typically measure light reflectance by foliage, the light reactions (i.e., light absorption by photosystems generating reduction power and energy for carbon-fixation) are still described empirically in vegetation models.

Part of the energy absorbed by the Chlorophyll pigments is radiatively dissipated through fluorescence. In the recent years, using narrow band observations in the oxygen A-band, first global Solar Induced Chlorophyll Fluorescence (SIF) measurements were obtained opening a new insight for estimates of vegetation photosynthesis. Yet, fluorescence quenching is a passive energy quenching and fluorescence yields are dependant of the faction of energy used for photochemistry and dissipated through non-photochemical quenching (NPQ). Thus direct comparison between GPP and SIF can lead to misinterpretation.

In this study, we append the P-model to include SIF simulations. The P-model is a new-generation vegetation model based on optimality principles and require minimal parametrisation. Two approaches to simulate fluorescence yield are tested. The first one is based on the van der Tol et al. (2014) fluorescence model and simulate fluorescence using an empirical method. The second is based on recent development from Johnson and Berry (Johnson and Berry, 2021), who proposed a process-based model for partitioning absorbed light between photochemistry, NPQ and fluorescence. The two approaches are evaluated and assessed against SIF satellite products.