Vicarious Calibration of GOCI for NASA's Ocean Color Algorithms

The Geostationary Ocean Color Imager (GOCI), launched by the Republic of Korea in 2010, is the first instrument in geostationary orbit capable of taking ocean color observations from space providing multiple daily observations within the field of view. The SeaDAS open-source software package has the capability of processing ocean color sensors supported by NASA, and now includes GOCI. The vicarious calibration of ocean color sensors supported by NASA relies on in situ data from the Marine Optical BuoY (MOBY). However, GOCI's footprint does not cover MOBY, and therefore, alternative sources of data need to be used. The vicarious calibration for GOCI specific for NASA's ocean color algorithms is presented here. This work updates the calibration gains in the NASA's standard atmospheric correction algorithm as implemented in the l2gen code and distributed through SeaDAS. In this case, we used data from a concurrent sensor (MODIS on Aqua) as a source for the calibration of the visible bands, which have the advantage of potentially having more calibration match-ups than in situ data from autonomous ocean-based observatories and sensors aboard ships. Additionally, we tested the approach of using climatological data from a well-calibrated sensor (SeaWiFS) as a source for the calibration of the visible bands, as suggested by Franz et al (2007). The results presented in this work optimize the performance of GOCI for studying oceans using NASA's ocean color algorithms by improving the accuracy of the detection of changes in the ocean properties. These results support the use of a concurrent sensor for the vicarious calibration when in situ data are not available, and demonstrate that using climatology from a well-calibrated sensor like SeaWiFS for the vicarious calibration is a valid alternative when it is not possible to use a concurrent sensor or in situ data.