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Effect of solar zenith angle on satellite cloud retrievals based on O-2-O-2 absorption band

  • 주제(기타) Remote Sensing
  • 주제(기타) Imaging Science & Photographic Technology
  • 설명문(일반) [Kim, Gyuyeon; Choi, Yong-Sang] Ewha Womans Univ, Dept Climate & Energy Syst Engn, EngineerB 353,52 Ewhayeodae Gil, Seoul 03760, South Korea; [Park, Sang Seo] Ulsan Natl Inst Sci & Technol, Dept Urban & Environm Engn, Ulsan, South Korea; [Kim, Jhoon] Yonsei Univ, Dept Atmospher Sci, Seoul, South Korea
  • 관리정보기술 faculty
  • 등재 SCIE, SCOPUS
  • 발행기관 TAYLOR & FRANCIS LTD
  • 발행년도 2021
  • URI http://www.dcollection.net/handler/ewha/000000181489
  • 본문언어 영어
  • Published As http://dx.doi.org/10.1080/01431161.2021.1890267

초록/요약

Recent studies have attempted to monitor global air quality with geostationary satellites. However, the monitoring accuracy is affected by a high solar zenith angle (SZA) during the day-to-night transition period, since the retrieval algorithms commonly use shortwave radiation. This study investigates the inaccuracy of background cloud retrievals for air quality at high SZAs that commonly use the O-2-O-2 absorption band at 477 nm. To this end, the differential optical absorption spectroscopy (DOAS) method with a radiative transfer model (RTM) simulations is used to quantify the amount of O-2-O-2 absorption by the cloud properties. The results show that the deviation of cloud retrievals from that retrieved at zero SZA increases exponentially with increasing SZA. The cloud deviation with increasing SZA can be larger for a smaller effective cloud fraction (ECF) and higher cloud centroid pressure (CCP). At an SZA of 80 degrees, the ECF is deviated up to 0.06 (28%) and the CCP up to - 90 hPa (-13%). This cloud deviation originates from the reduction in the 477 nm reflectance in the DOAS calculation, which is primarily owing to the in-cloud absorption effect in addition to the out-of-cloud O-2-O-2 absorption effect. Therefore, minimizing these absorption effects in the DOAS method during day-to-night transition is crucial for improving cloud retrievals and, eventually, the overall reliability of air quality monitoring.

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