Use of AERONET-OC for validation of SGLI/GCOM-C products in Ariake Sea, Japan

A station of AErosol RObotic NETwork Ocean Color (AERONET-OC) has been set on the Ariake Observation Tower of Saga University on April, 2018, for verification of the Second generation Global Imager (SGLI)/Global Change Observation Mission-Climate (GCOM-C). Remote sensing reflectance (Rrs) observed by the AERONET-OC was used for verification of SGLI. SGLI Version 1 data underestimated the shortwave Rrs and Rrs (380) and Rrs(412) were mostly negative, while the estimation was improved by Version 2 with the correction of Rrs(412) to be positive. It was indicated that absorptive aerosol was influenced to SGLI atmospheric correction and caused the underestimation of Rrs. Simple linear correction method to improve shortwave Rrs also worked well for specifically Version 1 data. Water constituents, chlorophyll-a (Chl-a), total suspended matter (TSM) and colored dissolved organic matter (CDOM) of the SGLI were also verified by the ship observation data. All constituents were improved from Version 1 to 2 with the correction of Rrs, although Version 2 underestimated Chl-a and CDOM. Simple regression algorithms were also examined with in situ as well as SGLI Rrs data, and it indicated that more sophisticated algorithms may be required. Time series of water constituents derived from AERONET-OC and SGLI data were compared to river discharge and spring-neap tidal cycle. The results indicated that the behavior, such as the increase of Chl-a after river discharge and interaction of Chl-a and TSM with the spring-neap tidal cycles were observed, although estimations of water constituents were not completely separated by the algorithms.

Automated summary

A station of AERONET-OC has been set up for the verification of SGLI data. The study found that SGLI Version 1 data underestimated the shortwave reflectance, but Version 2 improved the estimation by correcting the reflectance values. The water constituents of SGLI were also examined and improved from Version 1 to Version 2. Regression algorithms were tested and more sophisticated algorithms may be needed. The study compared the time series of water constituents derived from AERONET-OC and SGLI data with river discharge and spring-neap tidal cycles.