Satellite measurements of ocean color provide a unique vantage point to measure global phytoplankton abundance and their contribution to the health of marine ecosystems, the global cycle of nutrients, oxygen, and carbon, and their response to long-term climate change. However, the United States is at risk of losing access to ocean color data because the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) has ceased operation, Moderate Resolution Imaging Spectroradiometer (MODIS) is aging and planned new satellite missions might not be able to acquire data at the accuracy levels required for climate research. Given the importance of maintaining the ocean color time-series, the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), the National Science Foundation (NSF), and the Office of Naval Research (ONR) requested the National Research Council (NRC) convene a committee of experts to review the minimum requirements to sustain global ocean color measurements for research and operational applications, and identify options to minimize the risk of a data gap. This paper summarizes the NRC report's findings. In particular, it reviews the minimum mission requirements to sustain at least the current capabilities for measuring ocean color at a global scale such as the need for post-launch vicarious calibration and monitoring of the sensor's stability. It also summarizes the report's recommendations regarding the options to improve the VIIRS/NPP mission. Moreover, it details how a data-centric planning effort could ensure that ocean color research can be advanced and maintained over the long term. It concludes that the ever broadening user community that depends on accurate and timely ocean color data highlights the urgency to improve VIIRS ocean color performance and develop the next generation capability. In particular, NASA's climate continuity and decadal survey missions PACE/ACE, GEOCAPE and HyspIRI are required to advance ocean color science and to extend and improve operational and research uses of the data.