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Abstract The Orbiting Carbon Observatory‐2 (OCO‐2) collects solar‐induced chlorophyll fluorescence (SIF) at high spatial resolution along orbits (oco2ₒrbit), but its discontinuous spatial coverage precludes its full potential for understanding the mechanistic SIF‐photosynthesis relationship. This study developed a spatially contiguous global OCO‐2 SIF product at 0. 05° and 16‐day resolutions (oco2₀05) using machine learning constrained by physiological understandings. This was achieved by stratifying biomes and times for training and predictions, which accounts for varying plant physiological properties in space and time. oco2₀05 accurately preserved the spatiotemporal variations of oco2ₒrbit across the globe. Validation of oco2₀05 with Chlorophyll Fluorescence Imaging Spectrometer airborne measurements revealed striking consistency (R 2 = 0. 72; regression slope = 0. 96). Further, without time and biome stratification, (1) oco2₀05 of croplands, deciduous temperate, and needleleaf forests would be underestimated during the peak season, (2) oco2₀05 of needleleaf forests would be overestimated during autumn, and (3) the capability of oco2₀05 to detect drought would be diminished.
Yu et al. (Tue,) studied this question.