An empirical algorithm to seamlessly retrieve the concentration of suspended particulate matter from water color across ocean to turbid river mouths

We propose a globally applicable algorithm (GAA_SPM) to seamlessly retrieve the concentration of suspended particulate matter (SPM) (C_SPM) from remote sensing reflectance (R_rs(λ)) across ocean to turbid river mouths without any hard-switching in its application. GAA_SPM is based on a calibrated relationship between C_SPM and a generalized index for SPM (GI_SPM) from water color. The GI_SPM is mainly composed of three R_rs(λ) ratios (671, 745, and 862 nm over 551 nm, respectively), along with weighting factors assigned to each ratio. The weighting factors are introduced to ensure the progressive application of R_rs(λ) in the longer wavelengths for increasing C_SPM. Calibration of GAA_SPM employed data collected from multiple estuarine and coastal regions of Europe, China, Argentina, and the USA with the measured C_SPM spanning from 0.2 to 2068.8 mg/L. Inter-comparison with several recalibrated well-known C_SPM retrieval algorithms demonstrates that GAA_SPM has the best retrieval accuracy over the entire C_SPM range with a relative mean absolute difference (rMAD) of 41.3% (N = 437). This averaged uncertainty in GAA_SPM-derived C_SPM is mostly attributed to the retrievals from less turbid waters where C_SPM < 50 mg/L (rMAD = 50%, N = 214). GAA_SPM was further applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) measurements over prominent coastal areas and produced reliable C_SPM maps along with realistic spatial patterns. In contrast, applications of other C_SPM algorithms resulted in less reliable C_SPM maps with either unjustified numerical discontinuities in the C_SPM spatial distribution or unsatisfactory retrieval accuracy. Therefore, we propose GAA_SPM as a preferred algorithm to retrieve C_SPM over regions with a wide range of C_SPM, such as river plume areas.