Supp1-3136243.pdf

Abstract

The Ocean and Land Colour Instrument (OLCI) on Sentinel-3 is one of the most advanced ocean colour satellite sensors for aquatic environment monitoring. However, limited studies have been focused on a comprehensive assessment of atmospheric correction (AC) methods for OLCI. With an attempt to fill the gap, this study evaluated seven different AC methods for OLCI using global automatic in-situ observations from Aerosol Robotic Network-Ocean Colour (AERONET-OC). Results showed that: POLYnomial-based algorithm applied to MERIS (POLYMER) had the best performance for bands with wavelength⩽443 nm, and SeaDAS method based on 779 and 865 nm was the best for longer spectral bands; however, SeaDAS (SeaWiFS Data Analysis System) processing algorithm based on 779 and 1020 nm as well as 865 and 1020 nm obtained degraded AC performance; Case 2 Regional CoastColour (C2RCC) also produced large uncertainties; Baseline Atmospheric Correction (BAC) method might be better than SeaDAS method; and simple subtraction method was the worst except for turbid waters. POLYMER and C2RCC underestimated high remote sensing reflectance (Rrs) at red and green bands; SeaDAS method based on 779 and 865 nm held advantage for clear waters over the other two band combinations, while their difference turned small for turbid waters. AC uncertainties generally impacted the performance of Chlorophyll retrievals. POLYMER outperformed other methods for Chlorophyll retrieval. This study provides a good reference for selecting suitable AC method for aquatic environment monitoring with Sentinel-3 OLCI.