Characterization of the organic vs. inorganic fraction of suspended particulate matter in coastal waters based on ocean color radiometry remote sensing

Abstract

Abstract. Knowledge of the organic and inorganic particulate fraction of suspended material in coastal waters is essential for the study of particle dynamics and biogeochemical cycles in these complex and highly variable environments. Thanks to the availability of appropriate spatial sensors and to the considerable improvements in algorithms dedicated to the satellite observation of coastal waters from ocean color radiometry (OCR) achieved in the last 2 decades, various optical and biogeochemical parameters can now be routinely monitored over coastal waters. Here we show that a proxy for particulate composition (PPC) can be estimated from OCR observations. The present algorithm, based on a neural network approach, has been validated using a broad range of biogeochemical data collected in various contrasted coastal waters and has been applied to MERIS observations over the global coastal ocean at a 1 km × 1 km spatial resolution from 2002 to 2012. The relevance of the temporal occurrence of PPC in a given water pixel has been illustrated over the global coastal ocean, and its pertinence has been discussed in depth for the English Channel and the southern North Sea, which are characterized by a well-documented variability in suspended particulate matter composition. The present algorithm can directly be applied to all OCR sensors.