A centennial-scale data of suspended particulate matter over the global ocean

Suspended Particulate Matter (SPM) is a crucial indicator of marine nutrient transport, the carbon cycle, and land-sourced pollution. However, SPM research has been constrained by limited data. While marine remote sensing has helped fill this gap since late 20th century, pre-2000 data remains scarce, particularly for global datasets with high spatiotemporal resolution. To address the shortage of in-situ SPM observations, we developed two empirical models for estimating SPM concentrations: one based on remote sensing reflectance (Rrs) and the other on Secchi depth (Zsd). Model evaluation shows that retrieval uncertainties do not exceed 35 %. To mitigate errors in highly turbid waters (>100 mg l-1), we applied data quality constraints by excluding samples above this threshold. The resulting dataset merges in-situ SPM observations, providing global coverage of SPM concentrations from 1890 to 2020. Temporal and spatial analysis reveals an overall increase in global SPM concentrations, with a sharp rise between 1920 and 1942, followed by a rapid return to pre-1920 levels. The underlying causes of this fluctuation warrant further investigation. This unique dataset holds considerable potential for marine resource management, climate modeling, human activity assessment, and environmental protection.