Abstract. Solar-induced chlorophyll fluorescence (SIF) is a crucial proxy of photosynthetic processes in vegetation. In recent decades, advancements in remote sensing technology have facilitated long-term global SIF monitoring, significantly enhancing our understanding of vegetation dynamics on a global scale. Despite this progress, current SIF datasets face major challenges, including temporal inconsistencies among various satellite-derived products and a lack of long-term, high-resolution observations. In this study, we developed a “Long-term Harmonized SIF” (LHSIF) dataset spanning 1995 to 2024 with a fine spatial resolution of 0.05° by coordinating SIF satellite observations from GOME, SCIAMACHY, GOME-2, and OCO-2. Light use efficiency (LUE)-based spatial downscaling models were employed for each SIF product to generate fine-resolution global SIF maps. The long-term dataset was constructed using temporally corrected GOME-2A SIF (TCSIF) as a benchmark and was combined with a cumulative distribution function (CDF) normalization method for far-red SIF harmonization across satellite sensors from GOME, SCIAMACHY, and OCO-2. The resulting harmonized dataset shows a 49 % reduction in inter-sensor differences compared to the uncorrected data and exhibits a stable interannual increase of 0.31 ± 0.07 % yr−1. This result strongly aligns with the growth rate of gross primary production (GPP, 0.47 ± 0.03 % yr−1) and is consistent with ground-based SIF observations (R>0.60). Therefore, the long-term harmonized SIF dataset with a fine 0.05° resolution is valuable for estimating global photosynthesis over extended periods. The LHSIF dataset is available at https://doi.org/10.5281/zenodo.16394372 (Zou et al., 2025).
Zou et al. (2026) studied this question.