Integration of GOCI and AHI Yonsei Aerosol Optical Depth Products During the 2016 KORUS-AQ and 2018 EMeRGe Campaigns

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dc.contributor.authorLim, Hyunkwang
dc.contributor.authorGo, Sujung
dc.contributor.authorKim, Jhoon
dc.contributor.authorChoi, Myungje
dc.contributor.authorLee, Seoyoung
dc.contributor.authorSong, Chang-Keun
dc.contributor.authorKasai, Yasuko
dc.date.accessioned2020-11-03T19:16:54Z
dc.date.available2020-11-03T19:16:54Z
dc.date.issued2020-09-17
dc.description.abstractThe Yonsei AErosol Retrieval (YAER) algorithm for the Geostationary Ocean Color Imager (GOCI) retrieves aerosol optical properties only over dark surfaces, so it is important to mask pixels with bright surfaces. The Advanced Himawari Imager (AHI) is equipped with three shortwave-infrared and nine infrared channels, which is advantageous for bright-pixel masking. In addition, multiple visible and near-infrared channels provide a great advantage in aerosol property retrieval from the AHI and GOCI. By applying the YAER algorithm to 10 minutes AHI or 1 hour GOCI data at 6 km × 6 km resolution, diurnal variations and aerosol transport can be observed, which has not previously been possible from low-earth-orbit satellites. This study attempted to estimate the optimal aerosol optical depth (AOD) for East Asia by data fusion, taking into account satellite retrieval uncertainty. The data fusion involved two steps: (1) analysis of error characteristics of each retrieved result with respect to the ground-based Aerosol Robotic Network (AERONET), and bias correction based on normalized difference vegetation indexes; and (2) estimation of the fused product using ensemble-mean and maximum-likelihood estimation methods. Fused results show a better statistics in terms of fraction within the expected error, correlation coefficient, root-mean-square error, median bias error than the retrieved result for each product.en_US
dc.description.sponsorshipThis subject is supported by Korea Ministry of Environment (MOE) as "Public Technology Program based on Environmental Policy (2017000160001)". This work was also supported by a grant from the National Institute of Environment Research (NIER), funded by the Ministry of Environment (MOE) of the Republic of Korea (NIER-2020-01-02-007). This research was also supported by the National Strategic Project-Fine particle of the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT(MSIT), the Ministry of Environment(ME), and the Ministry of Health and Welfare(MOHW) (NRF-2017M3D8A1092022). We thank all members of the KORUS-AQ science team for their contributions to the field study and the data processing (doi:10.5067/Suborbital/KORUSAQ/DATA01).en_US
dc.description.urihttps://amt.copernicus.org/preprints/amt-2020-336/en_US
dc.format.extent32 pagesen_US
dc.genrejournal article preprintsen_US
dc.identifierdoi:10.13016/m2mqch-xvn2
dc.identifier.citationLim, H., Go, S., Kim, J., Choi, M., Lee, S., Song, C.-K., and Kasai, Y.: Integration of GOCI and AHI Yonsei Aerosol Optical Depth Products During the 2016 KORUS-AQ and 2018 EMeRGe Campaigns, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-336, in review, 2020.en_US
dc.identifier.urihttps://doi.org/10.5194/amt-2020-336
dc.identifier.urihttp://hdl.handle.net/11603/20005
dc.language.isoen_USen_US
dc.publisherCopernicus Publicationsen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Joint Center for Earth Systems Technology
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rightsAttribution 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.titleIntegration of GOCI and AHI Yonsei Aerosol Optical Depth Products During the 2016 KORUS-AQ and 2018 EMeRGe Campaignsen_US
dc.typeTexten_US

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