A cloud-computing framework for downscaled global 300 m SIF retrieval from Sentinel-3 and TROPOSIF

Sun-induced chlorophyll fluorescence (SIF) is a critical indicator of photosynthetic activity. Yet, existing satellite SIF products typically suffer from coarse spatial resolutions, generally coarser than 500 m, which limits their utility for fine-scale ecosystem studies. Here, we present a cloud-computing framework designed for the generation of a downscaled SIF product (S3-SIF₇₄₃) derived from Sentinel-3 (S3) Ocean and Land Colour Instrument (OLCI), with a spatiotemporal resolution of 300 m and 4 days. Our approach uses the Google Earth Engine (GEE) cloud-computing platform to integrate SIF produced from TROPOspheric Monitoring Instrument measurements within the 743-758 nm retrieval ( ${\text{TROPOSIF}}_{743}$ ), S3 radiances, S3-based vegetation traits, latitude and longitude within a Random Forest (RF) regression framework. Model training over Europe achieved robust performance against ${\text{TROPOSIF}}_{743}$ reference data ( $R^2$ = 0.767, RMSE = 0.137 mW m^-2 sr ${}^{-1}{\mathrm{nm}}^{-1}$ ), and the approach was subsequently extended globally. Validation against ground-based tower observations confirmed that S3-SIF₇₄₃ effectively reproduces seasonal dynamics across diverse ecosystems. Comparisons against ${\text{TROPOSIF}}_{743}$ demonstrated strong spatial consistency in temperate agricultural regions, with the highest $R^2$ values in croplands and lower agreement in sparsely vegetated or persistently cloudy regions. Global mapping revealed coherent patterns of photosynthetic activity, with peak values in tropical rainforests and major agricultural zones. Importantly, S3-SIF₇₄₃ reduces retrieval noise relative to ${\text{TROPOSIF}}_{743}$ and provides unprecedented insights into sub-kilometer spatial heterogeneity. By combining S3's rich spectral capabilities with GEE's scalable computing environment, our approach bridges the gap between current coarse-resolution SIF products and ESA's upcoming FLEX mission, offering a flexible and operational pathway for high-resolution monitoring of terrestrial photosynthesis.