Articles | Volume 14, issue 6
https://doi.org/10.5194/amt-14-4575-2021
https://doi.org/10.5194/amt-14-4575-2021
Research article
 | 
21 Jun 2021
Research article |  | 21 Jun 2021

Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns

Hyunkwang Lim, Sujung Go, Jhoon Kim, Myungje Choi, Seoyoung Lee, Chang-Keun Song, and Yasuko Kasai

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Cited articles

Bernard, E., Moulin, C., Ramon, D., Jolivet, D., Riedi, J., and Nicolas, J.-M.: Description and validation of an AOT product over land at the 0.6 µm channel of the SEVIRI sensor onboard MSG, Atmos. Meas. Tech., 4, 2543–2565, https://doi.org/10.5194/amt-4-2543-2011, 2011. 
Bilal, M., Nichol, J. E., and Wang, L.: New customized methods for improvement of the MODIS C6 Dark Target and Deep Blue merged aerosol product, Remote Sens. Environ., 197, 115–124, 2017. 
Chatterjee, A., Michalak, A. M., Kahn, R. A., Paradise, S. R., Braverman, A. J., and Miller, C. E.: A geostatistical data fusion technique for merging remote sensing and ground-based observations of aerosol optical thickness, J. Geophys. Res., 115, D20, https://doi.org/10.1029/2009JD013765, 2010. 
Cho, H. K., Jeong, M. J., Kim, J., and Kim, Y. J.: Dependence of diffuse photosynthetically active solar irradiance on total optical depth, J. Geophys. Res., 108, 4267, https://doi.org/10.1029/2002JD002175, 2003. 
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Short summary
Aerosol property observations by satellites from geostationary Earth orbit (GEO) in particular have advantages of frequent sampling better than 1 h in addition to broader spatial coverage. This study provides data fusion products of aerosol optical properties from four different algorithms for two different GEO satellites: GOCI and AHI. The fused aerosol products adopted ensemble-mean and maximum-likelihood estimation methods. The data fusion provides improved results with better accuracy.