Abstract
Abstract. Sun-induced chlorophyll fluorescence (SIF) retrieved from satellite spectrometers can be a highly valuable proxy for photosynthesis. The SIF signal is very small and notoriously difficult to measure, requiring sub-nanometre spectral-resolution measurements, which to date are only available from atmospheric spectrometers sampling at low spatial resolution. For example, the widely used SIF dataset derived from the GOME-2 mission is typically provided in 0.5∘ composites. This paper presents a new SIF dataset based on GOME-2 satellite observations with an enhanced spatial resolution of 0.05∘ and an 8 d time step covering the period 2007–2018. It leverages on a proven methodology that relies on using a light-use efficiency (LUE) modelling approach to establish a semi-empirical relationship between SIF and various explanatory variables derived from remote sensing at higher spatial resolution. An optimal set of explanatory variables is selected based on an independent validation with OCO-2 SIF observations, which are only sparsely available but have a high accuracy and spatial resolution. After bias correction, the resulting downscaled SIF data show high spatio-temporal agreement with the first SIF retrievals from the new TROPOMI mission, opening the path towards establishing a surrogate archive for this promising new dataset. We foresee this new SIF dataset becoming a valuable asset for Earth system science in general and for monitoring vegetation productivity in particular. The dataset is available at https://doi.org/10.2905/21935FFC-B797-4BEE-94DA-8FEC85B3F9E1 (Duveiller et al., 2019).
Highlights
Mapping and monitoring the spatial and temporal patterns of terrestrial gross primary productivity (GPP) through the use of satellite remote sensing are of paramount interest for vegetation, ecosystem and climate science
This paper presents a new daily corrected sun-induced chlorophyll fluorescence (SIF) dataset with a spatial resolution of 0.05◦ at 8 d time steps for the period 2007–2018 based on two different retrievals of GOME-2 satellite observations
A comparison with SIF from the new TROPOMI mission indicates that this downscaled SIF could serve as an archive after a pixel-wise bias correction
Summary
Mapping and monitoring the spatial and temporal patterns of terrestrial gross primary productivity (GPP) through the use of satellite remote sensing are of paramount interest for vegetation, ecosystem and climate science. SIF is generally positively correlated with leaf photochemistry during specific light conditions that are common across the globe and should serve as valid proxy for GPP, even though the mechanistic link between the two is complex (Porcar-Castell et al, 2014). The origin of this signal is the fluorescence of chlorophyll a, consisting of a re-emission of absorbed photons at lower-energy wavelengths (from 650 to 850 nm, with peaks at approximately 690 and 740 nm). Duveiller et al.: A spatially downscaled SIF satellite product of non-photochemical quenching can be triggered (Maxwell and Johnson, 2000)
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