A21K-07
Analysis of aerosol optical properties over Korea during the 2015 MAPS-Seoul campaign using AERONET and GOCI
Tuesday, 15 December 2015: 09:30
3006 (Moscone West)
Myungje Choi1, Jhoon Kim1, Jaehwa Lee2, Seoyoung Lee1, Brent N Holben3 and Thomas F Eck4, (1)Yonsei University, Seoul, South Korea, (2)Earth System Science Interdisciplinary Center, University of Maryland, COLLEGE PARK, MD, United States, (3)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (4)Nasa Goddard SFC, Greenbelt, MD, United States
Abstract:
To investigate aerosol characteristics over East Asia, many campaigns using in-situ measurements, ground and satellite based remote sensing, and air quality modeling have been conducted as ACE-Asia in 2001, ABC-EAREX in 2005, and DRAGON-NE Asia in 2012, and planned KORUS-AQ in 2016. Planned KORUS-AQ 2016 campaigns provides excellent opportunity to monitor and analyze air quality including aerosol and trace gases from diverse platform including ground-based, airborne, shipborne and satellite platform. Prior to the upcoming KORUS-AQ campaign, the Megacity Air Pollution Studies (MAPS)-Seoul campaign was held from May 18 to June14, 2015. During the campaign, total 8 AERONET sunphotometers are deployed over Korea. GOCI Yonsei aerosol retrieval (YAER) algorithm was developed, improved and evaluated through the DRAGON-NE Asia campaign. GOCI YAER AOD at 550 nm with spatial resolution of 6 km showed good agreement with AERONET AOD (R > 0.88) during the DRAGON-NE Asia campaign. In this study, aerosol optical properties from AERONET and GOCI are analyzed together during the MAPS-Seoul campaign. Mean AERONET AOD at 550 nm over a megacity site, Seoul and a coastal site Gosan shows the lowest values in 2015 as 0.338 and 0.214, respectively, compared with values during the same period from 2011 to 2014 (0.557–0.645 at Seoul, and 0.447–0.618 at Gosan). GOCI YAER algorithm uses the minimum reflectivity technique from the composited Rayleigh-corrected reflectance during a month thus low AOD increase a possibility to find clear pixels to obtain accurate surface reflectance. To improve surface reflectance quality, multi-year GOCI data are also analyzed. Furthermore higher spatial resolution retrieval in 3 km is tested to detect small-scale aerosol features and point sources in megacities. DRAGON-NE Asia in 2012, MAPS-Seoul in 2015, and planned KORUS-AQ in 2016 field campaigns contribute to the continuous assessment of GOCI YAER algorithm performance for the improvements.
