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MODIS 적외채널 배경 밝기온도차를 이용한 동북아시아 황사 탐지

Detection of Yellow Sand Dust over Northeast Asia using Background Brightness Temperature Difference of Infrared Channels from MODIS

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참고문헌

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주제분류대기과학

초록

The technique of Brightness Temperature Difference (BTD) between 11 and 12 μm 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 μm 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.

Abstract

The technique of Brightness Temperature Difference (BTD) between 11 and 12 μm 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 μm 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.

참고문헌 (17)

  1. 김학성, "2005년 동아시아 지역에서 발생한 모래폭풍과 먼지침전(황사)의 관측", 한국지구과학회지, 30(2), pp.196~209 (2009), 한국지구과학회
  2. 신영철, "황사의 사회경제적 영향과 피해 비용", 설비저널, 35(4), pp.26~30 (2006)
  3. 이종재, "최근의 황사 발원지에서의 먼지 발생 특성-2002년 이후 먼지발생 경향 분석", 대기, 18(4), pp.493~506 (2008), 한국기상학회
  4. 조창범, "황사농도 단기예측모델의 PM10 농도와 실측 PM10 농도의 비교- 2006년 4월 7~9일 황사 현상에 대해 -", 대기, 17(1), pp.87~99 (2007), 한국기상학회
  5. 하종성, "적외선 채널을 이용한 에어로솔 탐지의 경계값 및 민감도 분석", 대한원격탐사학회지, 22(6), pp.507~518 (2006), 대한원격탐사학회
  6. 홍성재, "봄철 황사탐지를 위한 정지궤도위성 적외선 채널의 배경경계값 적용 가능성 연구", 대한원격탐사학회지, 26(4), pp.387~394 (2010), 대한원격탐사학회
  7. Ackerman, S. A., "Using the radiative temperature difference at 3.7 and 11 μm to tract dust outbreaks", Remote Sensing of Environment, 27(2), pp.129~133 (1989)
  8. Ackerman, S. A, "Remote sensing aerosols using satellite infrared observations", Journal of Geophysical Research, 102(D14), pp.17069~17079 (1997)
  9. Ackerman, S., "Discriminating clear-sky from cloud with MODIS algorithm theoretical basis document(MOD35)", MODIS Cloud Mask Team, 6(1), pp.117~ (2010)
  10. Ellrod, G. P, "Improved detection of airborne volcanic ash using multispectral infrared satellite data", Journal of Geophysical Research, 108(D12), pp.4356~ (2003)
  11. Legrand, M, "Satellite detection of dust using the IR imagery of Meteosat 1. Infrared difference dust index", Journal of Geophysical Research, 106(18), pp.18251~18274 (2001)
  12. Prata, A. J., "Observations of volcanic ash clouds in the10-12㎛ window using AVHRR", 2 data, 1989, pp.10(4-5), 751~761
  13. Stammes, P, "OMI Algorithm theoretical basis document: Clouds, aerosols, and surface UV irradiance", OMI Team, 3, pp.114~ (2002)
  14. Torres, O, "Derivation of aerosol properties from satellite measurements of backscatterd ultraviolet radiation: Theoretical basis", Journal of Geophysical Research, 103(D14), pp.17099~17110 (1998)
  15. J. Gleason, "Aerosols and surface UV products from Ozone Monitoring Instrument observations: An overview", Journal of Geophysical Research, 112(D24) (2007)[DOI]
  16. Wen, S., "Retrieval of sizes and total masses of particles in volcanic clouds using AVHRR bands 4 and 5", Journal of Geophysical Research, 99(D3), pp.5421~5431 (1994)
  17. Zhai, P, "Atmospheric Water Vapor over China", Journal of Climate, 10, pp.2643~2652 (1997)

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