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.

Satellite estimation of chlorophyll-a (Chl-a) concentration in the Changjiang Estuary is challenging for ocean-colour retrieval algorithms. The Changjiang Estuary is characterized by suspended-sediment-dominated waters in the mouth and optically complex case 2 waters offshore of the mouth. Satellite ocean-colour products show that high-sediment loads of estuarine waters can cause overestimations or invalid flags of Chl-a concentration. A synthetic chlorophyll index (SCI) was designed for extracting chlorophyll information and for minimizing the influence of sediments on the remote-sensing reflectance spectrum. An SCI algorithm, a quadratic polynomial function of the SCI versus Chl-a concentration, was applied to the estimation of Chl-a concentration from Medium Resolution Imaging Spectrometer (MERIS) images. The overestimation of Chl-a concentration was corrected. The SCI algorithm has applications for MERIS estimation of Chl-a concentration in turbid waters with a moderate to high suspended-sediment concentration.

Measuring the transport of the Changjiang (also known as the Yangtze) River–derived buoyant coastal current, that is, the Min–Zhe Coastal Current, is of great importance for understanding the fate of terrestrial materials from this large river into the open ocean, but it is usually difficult to achieve because of the energetic tidal currents along the Chinese coast. In February 2012, a detiding cruise survey was carried out using the phase-averaging method. For the first time, this coastal current has been quantified with in situ data and has been shown to have a volume transport of 0.215 Sv (1 Sv ≡ 106 m3 s−1) and a maximum surface velocity of ~50 cm s−1. The ratio between the volume transport of the buoyant coastal current and that of the Changjiang is O(10). Freshwater transport by the buoyant coastal current accounts for over 90% of the Changjiang River's discharge. Buoyancy and winds are both important in driving this current.

An outdoor tank experiment is carried out to analyse the interrelationships between remote-sensing reflectance and sediment characteristics in the highly turbid waters of the Yangtze River and the Yellow River estuaries. The results show that the sensitivity of remote-sensing reflectance to water turbidity is inversely related to suspended sediment concentration (SSC). SSC estimation in the highly turbid waters (SSC > 0.15 g l⁻¹) is best achieved by using ocean colour ratios, especially the ratio at 810 nm: 700 nm. The effect of particle size of suspended sediment matter (SSM) on the observed remote-sensing reflectance is significant and depends on wavelengths and a SSC range. The mineral composition of SSM has a weak effect on observed reflectance in comparison to that of particle size.