Hyperspectral (every 5 nm) absorption coefficients of “pure” seawater in the range of 350–550 nm are derived from remote sensing reflectance measured in oligotrophic oceans. The absorption spectrum is reduced by $\sim 50–70\%$ for the 350–400-nm range and $\sim 5–10\%$ for the 510–530-nm range compared with the commonly adopted standard for ocean color processing and shows different spectral curvatures. The application of this new spectrum resulted in better retrievals of the phytoplankton absorption coefficient in oligotrophic oceans and will provide better closure of remote sensing reflectance for the UV–visible domain.

The suspended particulate matter (SPM) concentration (unit: mg l⁻¹) in surface waters is an essential measure of water quality and clarity. Satellite remote sensing provides a powerful tool to derive the SPM with synoptic and repeat coverage. In this study, we developed a new global SPM algorithm utilizing the remote sensing reflectance (R_rs(λ)) at near‐infrared (NIR), red, green, and blue bands (NIR‐RGB) as input. The evaluations showed that the NIR‐RGB algorithm could predict SPM with the median absolute percentage difference of ∼35%–39% over a wide range from ∼0.01 to >2,000 mg l⁻¹. The uncertainty is smaller (29%–37%) for turbid waters where R_rs(671) ≥ 0.0012 sr⁻¹ and slightly higher (41%–44%) for clear waters where R_rs(671) < 0.0012 mg l⁻¹. The algorithm was implemented with the global R_rs(λ) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar‐orbiting Partnership (SNPP) satellite. We provided a brief characterization of the spatial distribution and temporal trends of the SPM products in global waters based on the monthly SPM composites. Case studies of the SPM time series in coastal and inland waters suggest that the satellite SPM estimations registered spatial and seasonal variation and episodic events in regional scales as well. The VIIRS‐generated global SPM maps provide a valuable addition to the existing ocean color products for environmental and climate applications.