Consistent bio-optical properties across multiple ocean-color satellites are the key prerequisite to merging products from these satellites, thereby enhancing spatial coverage and extending temporal spans. Currently, due to factors such as sensor specifics and separate data processing algorithms, bio-optical properties (e.g., remote sensing reflectance, Rrs) from different ocean-color missions exhibit varying discrepancies in oceanic, coastal, and inland waters. Here, we show that through a scheme termed cross-satellite atmospheric correction (CSAC), the consistency of Rrs products between satellite ocean color missions can be significantly improved. Specifically, using data from SeaWiFS, MODIS-Aqua, and MERIS, the difference of Rrs between satellite ocean color missions is found reduced by a factor upto 2.5 for wavelengths of 412 – 667 nm. These results suggest that CSAC is a promising scheme to obtain consistent Rrs products, and subsequently Rrs-derived bio-optical properties, from various ocean color satellites, facilitating extensive and long-term ocean color observations of the global ocean.

Ocean color,Neural Networks,SeaWiFS,MODIS-Aqua,Atmospheric correction