Global 8-Day Gross Primary Production (GPP) Product at 0.05° Resolution Derived from Sentinel-3 OLCI Canopy Chlorophyll Content Using CPM, 2016–2024
DOI: https://doi.org/10.5281/zenodo.21530751 This dataset provides a global Gross Primary Production (GPP) product at a spatial resolution of 0.05 degree and a temporal resolution of 8 days, covering the period from 2016 to 2024. The product was generated using the chlorophyll-based canopy photosynthesis model (CPM). The model estimates GPP using Sentinel-3 OLCI-derived canopy chlorophyll content (CCC) and topographically corrected potential photosynthetically active radiation (PARpot). The CCC input was derived from Sentinel-3 OLCI top-of-atmosphere observations using a two-step upscaling method integrating physical modeling and machine learning. Within the CPM framework, CCC represents canopy photosynthetic capacity, while PARpot represents the potential radiation available for photosynthesis. The dataset is organized into 9 annual NetCDF files. Each annual file contains 46 consecutive 8-day GPP layers. Data characteristics Variable: Gross Primary Production (GPP) Unit: gC/m²/day Data type: single (float32) Missing value: NaN Invalid values: All NaN values should be considered invalid. Missing values mainly result from unavailable or invalid Sentinel-3 CCC observations caused by cloud and snow contamination, insufficient valid observations, or retrieval failure. Spatial resolution: 0.05 degree Temporal resolution: 8-day composite, with 46 composites per year Temporal extent: 2016–2024 Number of annual files: 9 Spatial extent:Latitude: 90°N to 60°SLongitude: 180°W to 180°ERows: 3000; Columns: 7200 Projection: Regular geographic latitude–longitude grid File format: NetCDF GPP values are stored directly in gC/m²/day. No scale factor or offset conversion is required. File format and naming Each annual file is named using the format: YYYY.nc, where YYYY is the corresponding year. Examples: 2016.nc 2017.nc … 2024.nc Each file contains one GPP variable with dimensions of: 3000 × 7200 × 46 representing latitude, longitude, and 8-day composite periods, respectively. Application This dataset is suitable for regional- and global-scale studies of: terrestrial vegetation productivity; ecosystem carbon uptake; seasonal and interannual photosynthetic dynamics; crop, grassland, and forest productivity; terrestrial carbon-cycle assessment; ecosystem responses to climate variability and environmental stress; comparison and validation of satellite GPP products. Associated publication Please cite the following publication when using this dataset: Li, D., Gitelson, A. A., Schreiner-McGraw, A. P., Desai, A. R., Zhu, Y., Cao, W., & Yu, K. (2026).Chlorophyll-based canopy photosynthesis model: Development and global synergy analysis.Remote Sensing of Environment, 342, 115468.https://doi.org/10.1016/j.rse.2026.115468 The Sentinel-3 CCC input product is described in: Li, D., Croft, H., Duveiller, G., Schreiner-McGraw, A. P., Belwalkar, A., Cheng, T., et al. (2025).Global retrieval of canopy chlorophyll content from Sentinel-3 OLCI TOA data using a two-step upscaling method integrating physical and machine learning models.Remote Sensing of Environment, 328, 114845.https://doi.org/10.1016/j.rse.2025.114845 Contact For questions or feedback, please contact: Dong LiTechnical University of MunichEmail: dongmath.li@tum.deGitHub: https://github.com/lidongmath