Articles | Volume 3, issue 6
Atmos. Meas. Tech., 3, 1771–1784, 2010
https://doi.org/10.5194/amt-3-1771-2010

Special issue: The 2009 WE-Heraeus-Seminar on satellite remote sensing of...

Atmos. Meas. Tech., 3, 1771–1784, 2010
https://doi.org/10.5194/amt-3-1771-2010

  20 Dec 2010

20 Dec 2010

Satellite remote sensing of Asian aerosols: a case study of clean, polluted, and Asian dust storm days

K. H. Lee1 and Y. J. Kim2 K. H. Lee and Y. J. Kim
  • 1Department of Satellite Geoinformatics Engineering, Kyungil University, Geongsan, 712-701, Republic of Korea
  • 2Advanced Environmental Monitoring Research Center, Department of Environmental Science and Engineering, Gwangju Institute of Science and Technology, 1 Oryong dong, Buk-gu, Gwangju, 500-712, Republic of Korea

Abstract. In East Asia, satellite observation is important because aerosols from natural and anthropogenic sources have been recognized as a major source of regional and global air pollution. However, retrieving aerosols properties from satellite observations over land can be difficult because of the surface reflection, complex aerosol composition, and aerosol absorption. In this study, a new aerosol retrieval method called as the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite aerosol retrieval (MSTAR) was developed and applied to three different aerosol event cases over East Asia. MSTAR uses a separation technique that can distinguish aerosol reflectance from top-of-atmosphere (TOA) reflectance. The aerosol optical thickness (AOT) was determined by comparing this aerosol reflectance with pre-calculated values. Three case studies show how the methodology identifies discrepancies between measured and calculated values to retrieve more accurate AOT. The comparison between MODIS and the Aerosol Robotic Network (AERONET) showed improvement using the suggested methodology with the cluster-based look-up-tables (LUTs) (linear slope = 0.94, R = 0.92) than using operational MODIS collection 5 aerosol products (linear slope = 0.78, R = 0.87). In conclusion, the suggested methodology is shown to work well with aerosol models acquired by statistical clustering of the observation data in East Asia.