• 제목/요약/키워드: RRS cloud algorithm

검색결과 2건 처리시간 0.014초

OMI 구름 측정 자료들의 비교 분석과 그에 따른 오존 측정에 미치는 영향 평가 (Analyses of the OMI Cloud Retrieval Data and Evaluation of Its Impact on Ozone Retrieval)

  • 최수환;박주선;김재환;백강현
    • 대기
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    • 제25권1호
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    • pp.117-127
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    • 2015
  • The presences of clouds significantly influence the accuracy of ozone retrievals from satellite measurements. This study focuses on the influence of clouds on Ozone Monitoring instrument (OMI) ozone profile retrieval based on an optimal estimation. There are two operational OMI cloud products; OMCLDO2, based on absorption in $O_2-O_2$ at 477 nm, and OMCLDRR, based on filling in Fraunhofer lines by rotational Raman scattering (RRS) at 350 nm. Firstly, we characterize differences between $O_2-O_2$ and RRS effective cloud pressures using MODIS cloud optical thickness (COT), and then compare ozone profile retrievals with different cloud input data. $O_2-O_2$ cloud pressures are significantly smaller than RRS by ~200 hPa in thin clouds, which corresponds to either low COT or cloud fraction (CF). On the other hand, the effect of Optical centroid pressure (OCP) on ozone retrievals becomes significant at high CF. Tropospheric ozone retrievals could differ by up to ${\pm}10$ DU with the different cloud inputs. The layer column ozone below 300 hPa shows the cloud-induced ozone retrieval error of more than 20%. Finally, OMI total ozone is validated with respect to Brewer ground-based total ozone. A better agreement is observed when $O_2-O_2$ cloud data are used in OMI ozone profile retrieval algorithm. This is distinctly observed at low OCP and high CF.

Application Studies for Active Fire Monitoring over Korea Using MODIS Direct Broadcast Data

  • Song J.H.;Kim Y.S.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.410-414
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    • 2004
  • The MODIS Land Rapid Response System (RRS) has been developed to provide rapid access to MODIS data globally, with initial emphasis on 250 m color composite imagery and active fire data. Fire detection is based on a contextual algorithm that exploits the strong emission of mid-infrared radiation from fires. This algorithm examines each pixel of the MODIS swath, and ultimately assigns to each one of the following classes: missing data, cloud, water, non-fire, fire, or unknown. In this paper, we introduce the MODIS Rapid Response System established at the Korea Aerospace Research Institute (KARI) and present some application results for Korea using the direct broadcast data acquired at KARI ground station.

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