Impact of meteorological ancillary data on GOCI products

Abstract

We investigate improvements to the quality of Geostationary Ocean Color Imager (GOCI) operational ocean color data processing, which requires routine ocean color product production in near real-time (NRT) and scientific reprocessing. The product can be made with the appropriate choice of the meteorological ancillary data sources which are used in the processing of Level-2 (L2) ocean color products for deriving ocean color products, e.g., the normalized water-leaving radiances as well as the bio-optical products further derived from these radiances using empirical algorithms. The ancillary dataset includes meteorological data (e.g., wind speed, atmospheric pressure, relative humidity) and concentrations of atmospheric gases (e.g., water vapor, ozone, nitrogen dioxide). Recently, new reanalysis dataset, ERA5, is released from the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA5 has the high-resolution compared to the previous version of the ERA-Interim. Also, the candidates of ancillary dataset include the National Centers for Environmental Prediction (NCEP) reanalysis-II and its climatology. Therefore, we quantify the uncertainty of each ancillary data sources compared to the observation of the weather buoy, which is collected from the Korean Meteorological Agency (KMA). Then we have re-processed the products of the ocean color images for the period of the in-situ observation (i.e., about three yea