정지기상위성 자료를 이용한 정량적 황사지수 개발 연구

The Study on the Quantitative Dust Index Using Geostationary Satellite

  • 김미자 (국립기상연구소 지구환경시스템연구팀) ;
  • 김윤재 (국립기상연구소 지구환경시스템연구팀) ;
  • 손은하 (국립기상연구소 지구환경시스템연구팀) ;
  • 김금란 (국립기상연구소 지구환경시스템연구팀) ;
  • 안명환 (조지워싱턴대학교 우주정책연구소)
  • Kim, Mee-Ja (Global Environment System Research Laboratory, National Institute of Meteorological Research) ;
  • Kim, Yoonjae (Global Environment System Research Laboratory, National Institute of Meteorological Research) ;
  • Sohn, Eun-Ha (Global Environment System Research Laboratory, National Institute of Meteorological Research) ;
  • Kim, Kum-Lan (Global Environment System Research Laboratory, National Institute of Meteorological Research) ;
  • Ahn, Myung-Hwan (Space Policy Institute, George Washington University)
  • 투고 : 2008.07.25
  • 심사 : 2008.10.26
  • 발행 : 2008.12.31

초록

The occurrence and strength of the Asian Dust over the Korea Peninsular have been increased by the expansion of the desert area. For the continuous monitoring of the Asian Dust event, the geostationary satellites provide useful information by detecting the outbreak of the event as well as the long-range transportation of dust. The Infrared Optical Depth Index (IODI) derived from the MTSAT-1R data, indicating a quantitative index of the dust intensity, has been produced in real-time at Korea Meteorological Administration (KMA) since spring of 2007 for the forecast of Asian dust. The data processing algorithm for IODI consists of mainly two steps. The first step is to detect dust area by using brightness temperature difference between two thermal window channels which are influenced with different extinction coefficients by dust. Here we use dynamic threshold values based on the change of surface temperature. In the second step, the IODI is calculated using the ratio between current IR1 brightness temperature and the maximum brightness temperature of the last 10 days which we assume the clear sky. Validation with AOD retrieved from MODIS shows a good agreement over the ocean. Comparison of IODI with the ground based PM10 observation network in Korea shows distinct characteristics depending on the altitude of dust layer estimated from the Lidar data. In the case that the altitude of dust layer is relatively high, the intensity of IODI is larger than that of PM10. On the other hand, when the altitude of dust layer is lower, IODI seems to be relatively small comparing with PM10 measurement.

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