Sean McCarthy

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About

Sean McCarthy is a leading figure in ocean color remote sensing, specializing in atmospheric correction and the calibration of emerging satellite technologies. His research focuses on improving the accuracy of water-leaving radiance retrievals—critical for estimating chlorophyll, absorption, and backscattering coefficients from space. In his highly cited 2012 paper (15 citations), McCarthy demonstrated how aerosol model selection introduces significant uncertainty into satellite-derived bio-optical properties, a foundational insight for the ocean color community. More recently, he has pioneered the use of machine learning to automate atmospheric correction for nanosatellites, as shown in his 2023 work (5 citations) that leverages coincident data from traditional ocean-viewing sensors. His complementary 2023 study (5 citations) assesses the viability of commercial Planet nanosatellites for ocean color applications, addressing the critical need for vicarious calibration to compute accurate normalized water-leaving radiance. By bridging the gap between heritage satellite missions and the burgeoning nanosatellite fleet, McCarthy is enabling high-resolution, frequent coastal monitoring that was previously impossible. His work is essential for researchers seeking to harness next-generation sensors for marine ecosystem studies.