Paper
27 October 2010 Estimating scaled cloud optical thickness from SEVIRI by implementing a semi-analytical cloud retrieval algorithm
Praveen Pandey, Koen De Ridder, Nicole Van Lipzig
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Abstract
We present a satellite remote sensing technique to retrieve the cloud optical thickness (COT) which is based on visible and shortwave infrared imagery from MSG-SEVIRI. The semi-analytical cloud retrieval algorithm (SACURA) is implemented on a monthly dataset of SEVIRI level 1.5 images. The background surface albedo (A) plays an important role for thin clouds. Thus, A is calculated by the minimum composite approach of reflectance in the visible channel, at pixel level, during the month. Cloud ice and cloud water discrimination scheme is made on the basis of ratio of reflectance in channel 1.6 μm to 0.6 μ. Reflectance of semi-infinite (R 0 ∞) cloud is a function of cosines of solar azimuth angle (vo), satellite azimuth angle (v) and relative azimuth angle (Ψ). Thus, reflectance values, R 0 ∞, R 0 ∞, are interpolated from a look up table of reflectance, calculated from radiative transfer model, to corresponding sun-satellite angular values. Hence, total scaled cloud optical thickness is calculated as summation of scaled cloud optical thickness of water and scaled cloud optical thickness of ice. The result is compared with that of Cloudsat and it shows good agreement.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Praveen Pandey, Koen De Ridder, and Nicole Van Lipzig "Estimating scaled cloud optical thickness from SEVIRI by implementing a semi-analytical cloud retrieval algorithm", Proc. SPIE 7827, Remote Sensing of Clouds and the Atmosphere XV, 782702 (27 October 2010); https://doi.org/10.1117/12.864559
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Clouds

Satellites

Reflectivity

Remote sensing

Satellite imaging

Commercial off the shelf technology

Image processing

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