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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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https://doi.org/10.5194/amt-2017-251
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
07 Aug 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).
GOCI Yonsei aerosol retrieval version 2 aerosol products: improved algorithm description and error analysis with uncertainty estimation from 5-year validation over East Asia
Myungje Choi1, Jhoon Kim1,2, Jaehwa Lee3,4, Mijin Kim1, Young-je Park5, Brent Holben4, Thomas F. Eck4,6, Zhengqiang Li7, and Chul H. Song8 1Department of Atmospheric Sciences, Yonsei University, Seoul, Republic of Korea
2Harvard - Smithsonian Center for Astrophysics, Cambridge, MA, USA
3Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
4NASA Goddard Space Flight Center, Greenbelt, MD, USA
5Korea Ocean Satellite Center, Korea Institute of Ocean Science and Technology, Ansan, Republic of Korea
6Universities Space Research Association, Columbia, MD, USA
7State Environmental Protection Key Laboratory of Satellite Remote Sensing, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China
8School of Environmental Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
Abstract. The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed for retrieving hourly aerosol optical depth at 550 nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD showed comparable accuracy compared to ground-based and other satellite-based observations, but still had errors due to uncertainties in surface reflectance and simple cloud masking. Also, it was not capable of near-real-time (NRT) processing because it required a monthly database of each year encompassing the day of retrieval for the determination of surface reflectance. This study describes the improvement of GOCI YAER algorithm to the version 2 (V2) for NRT processing with improved accuracy from the modification of cloud masking, surface reflectance determination using multi-year Rayleigh corrected reflectance and wind speed database, and inversion channels per surface conditions. Therefore, the improved GOCI AOD (τG) is similar with those of Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD compared to V1 of the YAER algorithm. The τG shows reduced median bias and increased ratio within 0.15τA+0.05 range (i.e. absolute expected error range of MODIS AOD) compared to V1 in the validation results using Aerosol Robotic Network (AERONET) AOD (τA) from 2011 to 2016. The validation using the Sun-Sky Radiometer Observation Network (SONET) over China also shows similar results. The bias of error (τGA) is within −0.1 and 0.1 range as a function of AERONET AOD and AE, scattering angle, NDVI, cloud fraction and homogeneity of retrieved AOD, observation time, month, and year. Also, the diagnostic and prognostic expected error (DEE and PEE, respectively) of τG are estimated. The estimated multiple PEE of GOCI V2 AOD is well matched with actual error over East Asia, and the GOCI V2 AOD over Korea shows higher ratio within PEE compared to over China and Japan.

Citation: Choi, M., Kim, J., Lee, J., Kim, M., Park, Y.-J., Holben, B., Eck, T. F., Li, Z., and Song, C. H.: GOCI Yonsei aerosol retrieval version 2 aerosol products: improved algorithm description and error analysis with uncertainty estimation from 5-year validation over East Asia, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-251, in review, 2017.
Myungje Choi et al.
Myungje Choi et al.
Myungje Choi et al.

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Short summary
This study is a major version upgrade of aerosol product from GOCI, the first and unique ocean color imager in geostationary earth orbit. It describes the improvement of GOCI Yonsei aerosol retrieval algorithm to the version 2 for near-real-time processing with improved accuracy from the modification of cloud masking, surface reflectance, and etc. The product is validated against AERONET/SONET over East Asia with analyses of various errors features, and a pixel-level uncertainty is calculated.
This study is a major version upgrade of aerosol product from GOCI, the first and unique ocean...
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