Currently the United States is at risk of losing access to satellite ocean color data because the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) has ceased operation, the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Aqua satellite is aging, access to international satellite sensors is either limited or untested, and planned new operational satellite missions might not acquire data at the accuracy levels required for climate research. The absence of a community-consensus operational need for global ocean color data is largely responsible for this potential gap in data continuity, since the justification for launching operational satellite missions requires defined operational usages, while previous ocean color sensors were launched primarily to address research needs. A fundamental problem is that, what it means to make something “operational” varies widely depending on the application or the community in question. For environmental satellite applications, the primary operational use has traditionally been weather forecasting, an application that requires access to near-real-time (NRT) data streams, 24 hours a day, 7 days a week. Hence, there is often a misconception that all operational users of satellite data must always have NRT, 24/7 data. In contrast, operational uses of ocean color, which support NOAA's mission of mitigating coastal hazards, sustaining marine ecosystems, and monitoring climate change, require data less frequently (i.e., on a daily basis), but require careful calibration, validation, and re-processing in order to produce highly accurate, “climate-quality” datasets. This is an important distinction, as the generation of climate-quality datasets requires additional considerations throughout all aspects of the satellite mission, from on-board maneuvers to periodic reprocessing of datasets. The operational use of ocean color data will be presented in this context. A recent National Research Council report has summarized the minimum requirements to sustain global ocean color measurements for research and operational applications, and identified options to minimize the risk of a data gap. Highlights from this report will also be reviewed.