GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia
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Published:2018-01-17
Issue:1
Volume:11
Page:385-408
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ISSN:1867-8548
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Container-title:Atmospheric Measurement Techniques
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language:en
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Short-container-title:Atmos. Meas. Tech.
Author:
Choi MyungjeORCID, Kim JhoonORCID, Lee Jaehwa, Kim Mijin, Park Young-Je, Holben BrentORCID, Eck Thomas F., Li Zhengqiang, Song Chul H.
Abstract
Abstract. The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER)
version 1 algorithm was developed to retrieve hourly aerosol optical depth at
550 nm (AOD) and other subsidiary aerosol optical properties over East Asia.
The GOCI YAER AOD had accuracy comparable to ground-based and other
satellite-based observations but still had errors because of uncertainties
in surface reflectance and simple cloud masking. In addition, near-real-time
(NRT) processing was not possible because a monthly database for each year
encompassing the day of retrieval was required for the determination of
surface reflectance. This study describes the improved GOCI YAER algorithm
version 2 (V2) for NRT processing with improved accuracy based on updates to
the cloud-masking and surface-reflectance calculations using a multi-year
Rayleigh-corrected reflectance and wind speed database, and inversion channels for surface conditions. The improved GOCI AOD τG is closer to that of the Moderate Resolution Imaging
Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD than was the case for AOD from the YAER V1 algorithm. The V2
τG has a lower median bias and higher ratio within
the MODIS expected error range (0.60 for land and 0.71 for ocean) compared with
V1 (0.49 for land and 0.62 for ocean) in a validation test against Aerosol
Robotic Network (AERONET) AOD τA from 2011 to
2016. A validation using the Sun-Sky Radiometer Observation Network (SONET)
over China shows similar results. The bias of error (τG−τA) is within −0.1 and 0.1, and it is
a function of AERONET AOD and Ångström exponent (AE), scattering angle, normalized difference vegetation index (NDVI), cloud fraction and
homogeneity of retrieved AOD, and observation time, month, and year. In
addition, the diagnostic and prognostic expected error (PEE) of τG are estimated. The estimated PEE of GOCI V2 AOD is well
correlated with the actual error over East Asia, and the GOCI V2 AOD over
South Korea has a higher ratio within PEE than that over China and Japan.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
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