Presenter: Jianwei Wei (NOAA/STAR; Global Science & Technology Inc.)

Description:
The natural (inland, coastal, and oceanic) waters contain various suspended particles originating locally and from allogenic processes. Measuring the suspended particulate matter (SPM) concentration can help monitor the water quality, including water turbidity and color, and the transport of particles, including pollutants. Ocean color satellite sensors are a powerful tool that can be used to map the SPM concentration. However, estimating SPM from satellite data has been hampered by the complexity of the particle optics. As a result, global satellite derived SPM products have generally been unavailable. This work first reports the recent development of the SPM algorithm designed for global application. The new algorithm explicitly uses the input of the remote sensing reflectance at near-infrared, red, green, and blue bands. So it is applicable to almost all existing ocean color satellite sensors, including VIIRS, MODIS, OLCI, SGLI, and GOCI. Evaluations were carried out with both field measurements and field-satellite matchups. It is shown that such estimated SPM concentrations have a high accuracy (<~40%, median absolute percentage difference) over global waters (from ~0.01 mg l⁻¹ to > 2000 mg l⁻¹). We then report the experimental mission-long SPM products derived from VIIRS, made available in the public domain as global daily, 8-day, and monthly composites. In addition, global gap-free SPM data and merged SPM products from multiple missions are also generated. Lastly, we demonstrate the spatial pattern and temporal variation of the SPM products as derived from satellites. In particular, we showcase the SPM time-series observations (2012–2021) in inland and coastal environments as part of a case study. We emphasize that the satellite SPM products have registered spatial and seasonal signals and episodic events at various scales, representing a valuable data resource for the environment- and climate-related applications.