Journal of the Korean earth science society (한국지구과학회지)

The Korean Earth Science Society (한국지구과학회)
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Estimation of Total Cloud Amount from Skyviewer Image Data

Skyviewer 영상 자료를 이용한 전운량 산출

  • Kim, Bu-Yo (Department of Atmospheric & Environmental Sciences, Gangneung-Wonju National University) ;
  • Jee, Joon-Bum (Weather Information Service Engine, Hankuk University of Foreign Studies) ;
  • Jeong, Myeong-Jae (Department of Atmospheric & Environmental Sciences, Gangneung-Wonju National University) ;
  • Zo, Il-Sung (Research Institute for Radiation-Satellite, Gangneung-Wonju National University) ;
  • Lee, Kyu-Tae (Department of Atmospheric & Environmental Sciences, Gangneung-Wonju National University)
  • 김부요 (강릉원주대학교 대기환경과학과) ;
  • 지준범 (한국외국어대학교 차세대도시농림융합기상사업단) ;
  • 정명재 (강릉원주대학교 대기환경과학과) ;
  • 조일성 (강릉원주대학교 복사-위성연구소) ;
  • 이규태 (강릉원주대학교 대기환경과학과)
  • Received : 2015.05.26
  • Accepted : 2015.07.28
  • Published : 2015.08.30
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Abstract

For this study, we developed an algorithm to estimate the total amount of clouds using sky image data from the Skyviewer equipped with CCD camera. Total cloud amount is estimated by removing mask areas of RGB (Red Green Blue) images, classifying images according to frequency distribution of GBR (Green Blue Ratio), and extracting cloud pixels from them by deciding RBR (Red Blue Ratio) threshold. Total cloud amount is also estimated by validity checks after removing sunlight area from those classified cloud pixels. In order to verify the accuracy of the algorithm that estimates total cloud amount, the research analyzed Bias, RMSE, and correlation coefficient compared to records of total cloud amount earned by human observation from the Gangwon Regional Meteorological Administration, which is in the closest vicinity of the observation site. The cases are selected four daily data from 0800 LST to 1700 LST for each season. The results of analysis showed that the Bias in total cloud amount estimated by the Skyviewer was an average of -0.8 tenth, and the RMSE was 1.6 tenths, indicating the difference in total cloud amount within 2 tenths. Also, correlation coefficient was very high, marking an average of over 0.91 in all cases, despite the distance between the two observation sites (about 4 km).

본 연구에서는 CCD 카메라가 장착된 Skyviewer로부터 촬영된 하늘 영상 자료를 이용하여 전운량을 산출하는 알고리즘을 개발하였다. 전운량 산출은 RGB 영상 내의 차폐 영역을 제거하고 GBR 빈도분포에 따른 영상을 분류하며, RBR 경계값을 결정하여 구름 화소를 분류한다. 분류된 구름 화소에서 태양광 영역을 제거한 후 유효성 검사를 통해 전운량을 산출하게 된다. 전운량 산출 알고리즘의 정확성을 검증하기 위하여 관측소와 가장 가까운 강원지방기상청의 목측 전운량 자료와 편이(Bias), 평균제곱근오차(RMSE), 상관계수를 분석하였다. 선정된 사례는 계절별 일 사례로 8시부터 17시까지의 정시 자료를 사용하였다. 분석 결과 Skyviewer로부터 산출된 전운량의 편이는 평균적으로 -0.8할의 차이를 보였으며, 평균제곱근오차는 1.6할로 전운량의 차이가 2할 내에서 나타나고 있었다. 또한, 두 관측소는 떨어진 거리의 차이가 있음(약 4 km)에도 불구하고 상관계수가 모든 사례에서 평균 0.91 이상으로 매우 높았다.

Keywords

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