Temporal relationship of solar-Induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) measured at ground to satellite scale over different ecosystems
Authors: Quiros Juan , Herrera David , Siegmann Bastian , Calvet Jean Christophe , Krieger Vera , Van Hoolst Roel , El-Madany Tarek , Migliavacca Mirco , Rascher Uwe 
Published: July 2023

Plant physiological processes like photosynthesis play a key role in the global carbon cycle, thus, having a significant impact on energy exchanges between vegetation and atmosphere. Nevertheless, current approaches to introduce photosynthesis in Land Surface Models (LSMs) are generally based on the extrapolation of locally measured photosynthetic rates to entire biomes. Therefore, plant physiological information at higher spatiotemporal resolution covering large areas (regional to global) is necessary to improve estimates of the seasonal dynamics of photosynthesis in LSMs. &#160;Due to the accelerated development of sensors and methods for vegetation monitoring in the last decades the required spatiotemporal resolution can be provided by remote sensing satellite data and derived products. In this context, compared to reflectance based vegetation indices, information about solar-induced chlorophyll fluorescence (SIF) is particularly interesting because of its direct relationship with photosynthesis. In this study, our goal is to provide information on the temporal relation between remote sensing SIF and photosynthesis data, the latter represented by gross primary productivity (GPP) information. We analyzed the relation of satellite-SIF data (from the TROPOspheric Monitoring Instrument; TROPOMI) with ground- (from Eddy Covariance towers) and satellite-GPP products in two ecosystems: (i) an intensive temperate agricultural area (Germany) and (ii) a tree-grass Mediterranean ecosystem (so called &#8216;Dehesa&#8217;; Spain). High statistical correlations in form of R2 = 0.75 (p < 0.001) and R2 = 0.65-0.69 (p < 0.001) were found between the ground- and satellite-based GPP data in both the temperate intensive agricultural area and the tree-grass ecosystem, respectively. SIF was also highly correlated with both (ground- and satellite-) GPP products derived from the agricultural area and at a similar correlation with the satellite-GPP in the tree-grass ecosystem R2 ~ 0.72 (p < 0.001). In contrast, the tower-based GPP-SIF correlation was distinctly lower (R2 = 0.29, p < 0.01) for the tree-grass ecosystem. &#160;The high correlations of SIF with ground- and satellite-based GPP information demonstrate the potential of SIF to be used as a new additional input parameter for an improved representation of photosynthetic processes in LSMs. Further investigations are needed to determine the added value of including SIF as measure of &#160;photosynthesis on the performance of the Soil-Biosphere-Atmosphere Interaction (ISBA; METEO-France) LSM. Most of the data presented in this study was collected and analyzed within the frame of the Photoproxy project of the European Space Agency (ESA), as part of the preparatory studies for the forthcoming FLuorescence EXplorer (FLEX) satellite mission, which will deliver high resolution (300 m pixel-1) SIF data in the coming years.