Preprints
https://doi.org/10.5194/essd-2025-94
https://doi.org/10.5194/essd-2025-94
28 Apr 2025
 | 28 Apr 2025
Status: this preprint is currently under review for the journal ESSD.

Development of the Long-term Harmonized multi-satellite SIF (LHSIF) dataset at 0.05° resolution (1995–2023)

Chu Zou, Shanshan Du, Xinjie Liu, and Liangyun Liu

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 2023 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 moment-matching normalization method for far-red SIF harmonization across satellite sensors from GOME, SCIAMACHY, and OCO-2. The resulting harmonization dataset exhibits a 45 % reduction in overall error and a stable interannual increase (0.42 ± 0.13 % yr⁻¹) compared with a fluctuating decline (−0.57 ± 0.27 % yr⁻¹) of the original observations. 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 a valuable tool for estimating global photosynthesis over extended periods. The LHSIF dataset is available at https://doi.org/10.5281/zenodo.14854185 (Zou et al., 2025).

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Share
Chu Zou, Shanshan Du, Xinjie Liu, and Liangyun Liu

Status: open (until 08 Jun 2025)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Chu Zou, Shanshan Du, Xinjie Liu, and Liangyun Liu

Data sets

LHSIF: the Long-Term Harmonized Multi-Satellite SIF dataset with a resolution of 0.05° spanning 1995 to 2023 Chu Zou et al. https://doi.org/10.5281/zenodo.14854184

Chu Zou, Shanshan Du, Xinjie Liu, and Liangyun Liu

Viewed

Total article views: 113 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
96 13 4 113 9 0 2
  • HTML: 96
  • PDF: 13
  • XML: 4
  • Total: 113
  • Supplement: 9
  • BibTeX: 0
  • EndNote: 2
Views and downloads (calculated since 28 Apr 2025)
Cumulative views and downloads (calculated since 28 Apr 2025)

Viewed (geographical distribution)

Total article views: 108 (including HTML, PDF, and XML) Thereof 108 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 02 May 2025
Download
Short summary
Understanding plant sunlight absorption is crucial for tracking global ecosystem health. We developed a 1995–2023 dataset that enhances satellite-based plant activity measurements by resolving data inconsistencies and improving resolution. Using advanced modeling, we harmonized signals from multiple satellites, cutting errors by 45 %. This offers clearer global photosynthesis trends, aiding climate research and vegetation monitoring.
Share
Altmetrics