Articles | Volume 9, issue 3
Atmos. Meas. Tech., 9, 1377–1398, 2016

Special issue: Meso-scale aerosol processes, comparison and validation studies...

Atmos. Meas. Tech., 9, 1377–1398, 2016

Research article 01 Apr 2016

Research article | 01 Apr 2016

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign

Myungje Choi et al.

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Cited articles

Ahn, J. H., Park, Y. J., Ryu, J. H., Lee, B., and Oh, I. S.: Development of Atmospheric Correction Algorithm for Geostationary Ocean Color Imager (GOCI), Ocean Sci. J., 47, 247–259, 2012.
Choi, J. K., Park, Y. J., Ahn, J. H., Lim, H. S., Eom, J., and Ryu, J. H.: GOCI, the world's first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity, J. Geophys. Res.-Oceans, 117, C09004,, 2012.
Ciren, P. and Kondragunta, S.: Dust aerosol index (DAI) algorithm for MODIS, J. Geophys. Res.-Atmos., 119, 4770-4792, 2014.
Cox, C. and Munk, W.: Statistics of the sea surface derived from sun glitter, J. Marine Res., 13, 198–227, 1954.
Dubovik, O. and King, M. D.: A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements, J. Geophys. Res.-Atmos., 105, 20673–20696, 2000.
Short summary
The Geostationary Ocean Color Imager (GOCI) is the first ocean color sensor in geostationary orbit. It enables hourly aerosol optical properties to be observed in high spatial resolution. This study presents improvements of the GOCI Yonsei Aerosol Retrieval (YAER) algorithm and its validation results using ground-based and other satellite-based observation products during DRAGON-NE Asia 2012 Campaign. Retrieval errors are also analyzed according to various factors through the validation studies.