Year-end Sale % OFF 
Abstract
Remote sensing of solar-induced chlorophyll fluorescence (SIF) provides new possibilities to estimate terrestrial gross primary production (GPP). To mitigate the angular and canopy structural effects on original SIF observed by sensors (SIF obs ), it is recommended to derive total canopy SIF emission (SIF total ) of leaves within a canopy using canopy interception ( i 0 ) and reflectance of vegetation ( R V ). However, the effects of the uncertainties in i 0 and R V on the estimation of SIF total have not been well understood. Here, we evaluated such effects on the estimation of GPP using the Soil-Canopy-Observation of Photosynthesis and the Energy balance (SCOPE) model. The SCOPE simulations showed that the R 2 between GPP and SIF total was clearly higher than that between GPP and SIF obs and the differences in R 2 ( Δ R 2 ) tend to decrease with the increasing levels of uncertainties in i 0 and R V . The resultant Δ R 2 decreased to zero when the uncertainty level in i 0 and R V was ~30% for red band SIF (RSIF, 683 nm) and ~20% for far-red band SIF (FRSIF, 740 nm). In addition, as compared to the TROPOspheric Monitoring Instrument (TROPOMI) SIF obs at both red and far-red bands, SIF total derived using any combination of i 0 (from MCD15, VNP15, and CGLS LAI products) and R V (from MCD34, MCD19, and VNP43 BRDF products) showed comparable improvements in estimating GPP. With this study, we suggest a way to advance our understanding in the estimation of a more physiological relevant SIF datasets (SIF total ) using current satellite products.
Highlights
Solar-induced chlorophyll fluorescence (SIF) has been shown to be a good indicator of terrestrial gross primary production (GPP) [1,2,3]
The relationships of instantaneous GPP with RSIFobs and FRSIFobs based on the Soil-Canopy-Observation of Photosynthesis and the Energy balance (SCOPE) simulations are shown in Figure 4(a) and 4(b), in which hyperbolic models were suitable for capturing the nonlinearity
Without considering the variation in the escape probability, RSIFobs was weakly and nonlinearly related to GPP (R2 = 0:38, Figure 4(a)), and FRSIFobs was moderately and nonlinearly related to GPP (R2 = 0:65, Figure 4(b)). These R2 for RSIFobs vs. GPP and FRSIFobs vs. GPP were set as the benchmark to evaluate the usefulness of SIFtotal after considering the escape probability effect
Summary
Solar-induced chlorophyll fluorescence (SIF) has been shown to be a good indicator of terrestrial gross primary production (GPP) [1,2,3]. Many efforts have been devoted into the satellite SIF retrievals using existing instruments such as the Japanese Greenhouse Gases Observing Satellite (GOSAT), the Global Ozone Monitoring Experiment-2 (GOME-2), the Orbiting Carbon Observatory-2/3 (OCO-2/3), the TROPOspheric Monitoring Instrument (TROPOMI), and the Chinese Carbon Dioxide Observation Satellite Mission (TanSat) [4,5,6,7,8,9,10] These satellite SIF data have been increasingly used to estimate global terrestrial GPP in two different approaches: constraining process-based biosphere models [11,12,13,14] and establishing the empirical relationship between GPP and SIF [2, 3, 15, 16].
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
