Canopy escape correction dominates processing-induced differences in TROPOMI SIF-derived photosynthetic phenology

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Abstract
Satellite-observed solar-induced chlorophyll fluorescence (SIF) provides a novel observational constraint for monitoring photosynthetic phenology. However, phenological estimates derived from different SIF processing schemes remain difficult to compare directly, and the relative impacts of observation geometry, temporal aggregation, and canopy escape correction remain unclear. Using TROPOMI far-red SIF observations from 2019 to 2021, we constructed four 0.1° gridded products across vegetated regions of the Northern Hemisphere: daily canopy SIF, 8-day averaged canopy SIF, nadir-normalized daily canopy SIF, and escape-corrected 8-day SIF. Within a unified framework integrating Whittaker time-series reconstruction and double logistic phenology extraction, we quantified the impacts of angular effects, temporal aggregation, and canopy escape correction on the start of season (SOS), peak of season (POS), end of season (EOS), and length of season (LOS) through three paired comparisons. Results showed that angular effects and temporal aggregation caused relatively small phenological changes, with area-weighted mean changes generally within ±1.5 d and mean absolute differences generally ranging from 2 to 6 d. In contrast, canopy escape correction contributed the largest processing-induced differences: SOS and POS were delayed by 6.9 and 5.0 d, respectively, whereas EOS occurred 5.3 d earlier, and LOS was shortened by 12.2 d. The mean absolute difference in LOS reached 21.0 d and remained 20.6 d when comparisons were restricted to common valid pixels. This influence exhibited pronounced latitudinal and vegetation-type dependence, with the largest LOS shortening (39.2 d) occurring in low-latitude regions. Seasonal curve analysis further indicated that canopy escape correction primarily modified the curve structure near the peak; in some pixels, POS shifted by up to 18.0 d, whereas SOS and EOS changed by only 2.5 and 1.2 d, respectively. It should be noted that this study does not aim to validate the absolute accuracy of phenological estimates using ground observations; rather, it focuses on quantifying the relative impacts of different SIF processing schemes on photosynthetic phenology estimates. Our results demonstrate that canopy escape correction exerts the strongest influence on differences among TROPOMI SIF-derived phenological estimates, whereas angular effects and temporal aggregation play secondary roles. These findings provide a basis for comparing, interpreting, and assessing uncertainties in satellite SIF-based photosynthetic phenology products.

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