The cloud amount, one of the basic parameter in atmospheric observation, have been observed by naked eyes of observers, which is affected by the subjective view. In order to ensure reliable and objective observation, a new algorithm to retrieve cloud amount was constructed using true color images co...
The cloud amount, one of the basic parameter in atmospheric observation, have been observed by naked eyes of observers, which is affected by the subjective view. In order to ensure reliable and objective observation, a new algorithm to retrieve cloud amount was constructed using true color images composed of red, green and blue (RGB). The true color image is obtained by the Skyview, an all-sky imager taking pictures of sky, at the Science Building of Yonsei University, Seoul for a year in 2006. The principle of distinguishing clear sky from cloudy sky lies in the fact that the spectral characteristics of light scattering is different for air molecules and cloud. The result of Skyview's algorithm showed about 77% agreement between the observed cloud amount and the calculated, for the error range, the difference between calculated and observed cloudiness, within ${\pm}2$. Seasonally, the best accuracy of about 83% was obtained within ${\pm}2$ range in summer when the cloud amounts are higher, thus better signal-to-noise ratio. Furthermore, as the sky turbidity increased, the error also increased because of increased scattering which can explain the large error in spring. The algorithm still need to be improved in classifying sky condition more systematically with other complimentary instruments to discriminate thin cloud from haze to reduce errors in detecting clouds.
The cloud amount, one of the basic parameter in atmospheric observation, have been observed by naked eyes of observers, which is affected by the subjective view. In order to ensure reliable and objective observation, a new algorithm to retrieve cloud amount was constructed using true color images composed of red, green and blue (RGB). The true color image is obtained by the Skyview, an all-sky imager taking pictures of sky, at the Science Building of Yonsei University, Seoul for a year in 2006. The principle of distinguishing clear sky from cloudy sky lies in the fact that the spectral characteristics of light scattering is different for air molecules and cloud. The result of Skyview's algorithm showed about 77% agreement between the observed cloud amount and the calculated, for the error range, the difference between calculated and observed cloudiness, within ${\pm}2$. Seasonally, the best accuracy of about 83% was obtained within ${\pm}2$ range in summer when the cloud amounts are higher, thus better signal-to-noise ratio. Furthermore, as the sky turbidity increased, the error also increased because of increased scattering which can explain the large error in spring. The algorithm still need to be improved in classifying sky condition more systematically with other complimentary instruments to discriminate thin cloud from haze to reduce errors in detecting clouds.
Skyview PSC-100은 일정시간마다 하늘을 촬영하고, 그 영상을 JPEG 압축파일형식으로 PC에 자동적으로 저장하는 장치이다. 2005년 11월에 연세대학교 대기복사연구실에서 구입하여 이과대학 옥상에 설치된 이후 계속 작동하고 있다.
태양의 직달광이 사진에 찍히는 것은 무엇 때문인가?
이는 태양의 직달광이 사진에 직접 찍히거나 돔에 반사될 때, 또는 구름의 가장자리나 연무가 있을 때 빛이 반사되는 경우로 나타났다. 태양의 직달광이 사진에 찍히는 것은 차폐판이 태양과 태양 주위의 강한 직달광을 가릴 만큼 충분한 면적을 가지지 못하기 때문이다. 이러한 태양 직달광은 전천 사진에서 흰색으로 나타고 R/B 값도 높게 나타난다.
전천사진을 통한 자동 운량 분석 방법은 어떤 장점들이 있는가?
이 연구에서는 현재 가장 활발히 연구되고 있고 일부 현업에서 기상정보로 제공되는 방법 중 하나인 전천사진을 통한 자동 운량 분석 방법을 시도하였다. 전천카메라가 고정된 장소에서 계획된 시간 마다 일정 범위의 전천사진을 찍으므로 이를 통해 얻은 자료는 균일하고 안정성을 갖는 장점이 있다. 또 카메라에서 측정된 에너지의 절대값에 의존하지 않고 파장별 비율을 사용하기 때문에 절대보정 (absolute calibration)이 필요 없어, 어떤 컬러카메라에도 적용가능하다.
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