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A Fast Cloud Detection Algorithm Applicable to Monitoring and Nowcasting of Daytime Cloud Systems
The Advanced Himawari Imager (AHI) onboard Japanese geostationary satellite Himawari-8 provides two more visible, three more near-infrared, and six more infrared channels than the only one visible and four infrared channels available from the previous geostationary imager instruments. By taking advantage of AHI's newly added channels 1, 3, and 4 with wavelengths centered at 0.46, 0.64, and 0.86~\mu \text{m} , respectively, a fast cloud detection algorithm is developed. Since the spectral differences of the reflectance between any two of AHI's channels 1, 3, and 4 over clouds are smaller than those over land and ocean, a visible-based cloud index (VCI) for daytime cloud detection can thus be defined by the root mean square of the three differences between any two of these three channels. An AHI pixel is identified as cloudy if the VCI is smaller than a threshold, which has different values over ocean and land. Cloud detection is further adjusted by a bias correction using AHI channels 7 and 13. The average accuracy of the proposed simple cloud detection is comparable with those obtained from a more complicated cloud mask algorithm involving not only more channels but also model simulations. It is also found that the bias correction is needed mostly over cirrus clouds and Gobi.
A Fast Cloud Detection Algorithm Applicable to Monitoring and Nowcasting of Daytime Cloud Systems
The Advanced Himawari Imager (AHI) onboard Japanese geostationary satellite Himawari-8 provides two more visible, three more near-infrared, and six more infrared channels than the only one visible and four infrared channels available from the previous geostationary imager instruments. By taking advantage of AHI's newly added channels 1, 3, and 4 with wavelengths centered at 0.46, 0.64, and 0.86~\mu \text{m} , respectively, a fast cloud detection algorithm is developed. Since the spectral differences of the reflectance between any two of AHI's channels 1, 3, and 4 over clouds are smaller than those over land and ocean, a visible-based cloud index (VCI) for daytime cloud detection can thus be defined by the root mean square of the three differences between any two of these three channels. An AHI pixel is identified as cloudy if the VCI is smaller than a threshold, which has different values over ocean and land. Cloud detection is further adjusted by a bias correction using AHI channels 7 and 13. The average accuracy of the proposed simple cloud detection is comparable with those obtained from a more complicated cloud mask algorithm involving not only more channels but also model simulations. It is also found that the bias correction is needed mostly over cirrus clouds and Gobi.
A Fast Cloud Detection Algorithm Applicable to Monitoring and Nowcasting of Daytime Cloud Systems
Zhuge, Xiao-Yong (author) / Zou, Xiaolei / Wang, Yuan
2017
Article (Journal)
English
Local classification TIB:
770/3710/5670
BKL:
38.03
Methoden und Techniken der Geowissenschaften
/
74.41
Luftaufnahmen, Photogrammetrie
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