Extension to GOCI-II of GOCI Yonsei Aerosol Retrieval algorithm

Abstract:

Since GOCI (Geostationary Ocean Color Imager) was successfully launched as the world's first geostationary ocean color sensor in 2010, the GOCI Yonsei aerosol retrieval (YAER) algorithm has been continuously updated to retrieve hourly aerosol optical properties. The GOCI YAER products show good agreement with other satellite aerosol products and AERONET. The GOCI YAER products have been widely used for the analysis of air quality over East Asia and data assimilation to improve air quality forecast.

GOCI-II was launched in February 2020 onboard the GEO-KOMPSAT-2B (GK-2B) satellite as the follow-up GOCI, and is going through in orbit tests. In terms of aerosol retrieval, GOCI-II has two major advantages compared to GOCI. First, the newly included UV band centered at 380 nm is advantageous to retrieve the radiative absorptivity of aerosols over the darker surface than a visible band. Second, the spatial resolution of GOCI-II is doubled to 250 m, compared to 500 m resolution of GOCI, which allows us to mask smaller-scale clouds and to retrieve the aerosol optical properties in better accuracy.

In this study, we evaluate the information content in the GOCI-II aerosol retrieval and compare it to that in GOCI. With the simulated GOCI-II observation system using a radiative transfer model, we calculate the degrees of freedom for signal (DFS) based on the optimal estimation approach. It is found that the utilization of UV band with the current GOCI spectral bands shows a much higher increase in the DFS than the inclusion of any other visible and NIR channels. Based on the findings mentioned earlier, we apply the YAER algorithm to GOCI-II measurement and retrieve aerosol optical properties. Furthermore, a feasibility study to retrieve aerosol layer height and imaginary part of refractive index is conducted.