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http://dx.doi.org/10.7780/kjrs.2019.35.3.6

Development of a Retrieval Algorithm for Adjustment of Satellite-viewed Cloudiness  

Son, Jiyoung (Department of Climate and Energy Systems of Science and Engineering, Ewha Womans University)
Lee, Yoon-Kyoung (Center for Climate.Environment Change Prediction Research, Ewha Womans University)
Choi, Yong-Sang (Department of Environmental Science and Engineering, Ewha Womans University)
Ok, Jung (Center for Climate.Environment Change Prediction Research, Ewha Womans University)
Kim, Hye-Sil (Department of Climate and Energy Systems of Science and Engineering, Ewha Womans University)
Publication Information
Korean Journal of Remote Sensing / v.35, no.3, 2019 , pp. 415-431 More about this Journal
Abstract
The satellite-viewed cloudiness, a ratio of cloudy pixels to total pixels ($C_{sat,\;prev}$), inevitably differs from the "ground-viewed" cloudiness ($C_{grd}$) due to different viewpoints. Here we develop an algorithm to retrieve the satellite-viewed, but adjusted cloudiness to $C_{grd} (C_{sat,\;adj})$. The key process of the algorithm is to convert the cloudiness projected on the plane surface into the cloudiness on the celestial hemisphere from the observer. For this conversion, the supplementary satellite retrievals such as cloud detection and cloud top pressure are used as they provide locations of cloudy pixels and cloud base height information, respectively. The algorithm is tested for Himawari-8 level 1B data. The $C_{sat,\;adj}$ and $C_{sat,\;prev}$ are retrieved and validated with $C_{grd}$ of SYNOP station over Korea (22 stations) and China (724 stations) during only daytime for the first seven days of every month from July 2016 to June 2017. As results, the mean error of $C_{sat,\;adj}$ (0.61) is less that than that of $C_{sat,\;prev}$ (1.01). The percent of detection for 'Cloudy' scenario of $C_{sat,\;adj}$ (73%) is higher than that of $C_{sat,\;prev}$ (60%) The percent of correction, the accuracy, of $C_{sat,\;adj}$ is 61%, while that of $C_{sat,\;prev}$ is 55% for all seasons. For the December-January-February period when cloudy pixels are readily overestimated, the proportion of correction of $C_{sat,\;adj$ is 60%, while that of $C_{sat,\;prev}$ is 56%. Therefore, we conclude that the present algorithm can effectively get the satellite cloudiness near to the ground-viewed cloudiness.
Keywords
Satellite-viewed cloudiness; Ground-viewed cloudiness; Adjusted satellite-viewed cloudiness; Coordinate transformation;
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Times Cited By KSCI : 1  (Citation Analysis)
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