Signal filtering of daily cloud types' trends as derived from satellite images

Jules R. Dim; Hiroshi Murakami

doi:10.1117/12.872443

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3 February 2011 Signal filtering of daily cloud types' trends as derived from satellite images

Jules R. Dim, Hiroshi Murakami

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Proceedings Volume 7870, Image Processing: Algorithms and Systems IX; 787006 (2011) https://doi.org/10.1117/12.872443
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

The relationship between the intensity functions of contiguous pixels of an image is used on daily global clouds satellite data to extract local edge gradients for cloud types' classification. The images are cloud top temperatures (CTT) derived from the National Oceanic and Atmospheric Administration/Advanced Very-High-Resolution Radiometer (NOAA-AVHRR) satellite observations. The cloud type classification method used is a histogram-based gradient scheme described as the occurrence of low, mid or high edge gradients in a block of pixels. The distribution of these cloud types is analyzed, then, the consistency of the monthly variations of the cloud type amount estimation is evaluated. A clear dependence of the cloud type amount signal on the solar zenith angle is noticeable. This dependence, due to the gradual satellite drift, is removed through a filtering process using the empirical mode decomposition (EMD) method. The EMD component, associated with the drift or the solar zenith angle change, is filtered out. The cloud types' amount series corrected show a substantial improvement in their trends.

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Jules R. Dim and Hiroshi Murakami "Signal filtering of daily cloud types' trends as derived from satellite images", Proc. SPIE 7870, Image Processing: Algorithms and Systems IX, 787006 (3 February 2011); https://doi.org/10.1117/12.872443

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