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Korean Meteorological Society (한국기상학회)
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Detection of Yellow Sand Dust over Northeast Asia using Background Brightness Temperature Difference of Infrared Channels from MODIS

MODIS 적외채널 배경 밝기온도차를 이용한 동북아시아 황사 탐지

  • Park, Jusun (Department of Atmospheric Sciences, Division of Earth Environmental System, Pusan National University) ;
  • Kim, Jae Hwan (Department of Atmospheric Sciences, Division of Earth Environmental System, Pusan National University) ;
  • Hong, Sung Jae (Department of Atmospheric Sciences, Division of Earth Environmental System, Pusan National University)
  • 박주선 (부산대학교 지구환경시스템학부 대기과학전공) ;
  • 김재환 (부산대학교 지구환경시스템학부 대기과학전공) ;
  • 홍성재 (부산대학교 지구환경시스템학부 대기과학전공)
  • Received : 2011.11.02
  • Accepted : 2012.01.20
  • Published : 2012.06.30
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Abstract

The technique of Brightness Temperature Difference (BTD) between 11 and $12{\mu}m$ separates yellow sand dust from clouds according to the difference in absorptive characteristics between the channels. However, this method causes consistent false alarms in many cases, especially over the desert. In order to reduce these false alarms, we should eliminate the background noise originated from surface. We adopted the Background BTD (BBTD), which stands for surface characteristics on clear sky condition without any dust or cloud. We took an average of brightness temperatures of 11 and $12{\mu}m$ channels during the previous 15 days from a target date and then calculated BTD of averaged ones to obtain decontaminated pixels from dust. After defining the BBTD, we subtracted this index from BTD for the Yellow Sand Index (YSI). In the previous study, this method was already verified using the geostationary satellite, MTSAT. In this study, we applied this to the polar orbiting satellite, MODIS, to detect yellow sand dust over Northeast Asia. Products of yellow sand dust from OMI and MTSAT were used to verify MODIS YSI. The coefficient of determination between MODIS YSI and MTSAT YSI was 0.61, and MODIS YSI and OMI AI was also 0.61. As a result of comparing two products, significantly enhanced signals of dust aerosols were detected by removing the false alarms over the desert. Furthermore, the discontinuity between land and ocean on BTD was removed. This was even effective on the case of fall. This study illustrates that the proposed algorithm can provide the reliable distribution of dust aerosols over the desert even at night.

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References

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