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

Abstract We propose a globally applicable algorithm (GAASPM) to seamlessly retrieve the concentration of suspended particulate matter (SPM) (CSPM) from remote sensing reflectance (Rrs(λ)) across ocean to turbid river mouths without any hard-switching in its application. GAASPM is based on a calibrated relationship between CSPM and a generalized index for SPM (GISPM) from water color. The GISPM is mainly composed of three Rrs(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 Rrs(λ) in the longer wavelengths for increasing CSPM. Calibration of GAASPM employed data collected from multiple estuarine and coastal regions of Europe, China, Argentina, and the USA with the measured CSPM spanning from 0.2 to 2068.8 mg/L. Inter-comparison with several recalibrated well-known CSPM retrieval algorithms demonstrates that GAASPM has the best retrieval accuracy over the entire CSPM range with a relative mean absolute difference (rMAD) of 41.3% (N = 437). This averaged uncertainty in GAASPM-derived CSPM is mostly attributed to the retrievals from less turbid waters where CSPM