Satellite ocean color remote sensing is presently the only feasible means for obtaining global, repetitive, and high-spatial-resolution measurements of bio-optical properties in the surface ocean. However, each satellite is limited in spatial coverage due to cloud and sun-glint contamination, as well as orbital constraints. In addition, individual satellite sensors have finite operational lifespans. As a result, merging observations from multiple satellites is essential to achieve continuous, long-term, and global coverage. A key requirement for such data fusion is ensuring consistency in bio-optical properties across different satellite missions. Without this consistency, systematic biases can be introduced into the merged dataset. This presentation introduces the Cross-Satellite Atmospheric Correction (CSAC) system. CSAC uses the highest quality remote sensing reflectance (Rrs) from MODIS-Aqua as a reference baseline and converts top-of-atmosphere reflectance from other sensors into MODIS-Aqua–equivalent Rrs. When applied to SeaWiFS, MERIS, and VIIRS, the approach significantly improves consistency in Rrs across these satellite missions, particularly in high-latitude regions and areas affected by sun glint. Subsequently, a Global, Long-term Ocean-color Synthesis Series (GLOSS) is produced by merging observations from SeaWiFS, MODIS-Aqua, and SNPP-VIIRS. GLOSS provides a nearly 30-year record of consistent global ocean bio-optical properties, greatly enhancing the study of ocean processes under a changing climate.

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