Using a Sky Imager for aerosol characterization
The All-Sky Imager developed by the Atmospheric Physics Group has been tested for aerosol characterization. Different neural network-based models calculate the aerosol optical depth (AOD) for two wavelengths and the Ångström turbidity parameter α using as input parameters data extracted from the pri...
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Veröffentlicht in: | Atmospheric environment (1994) 2008-04, Vol.42 (11), p.2739-2745 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | The All-Sky Imager developed by the Atmospheric Physics Group has been tested for aerosol characterization. Different neural network-based models calculate the aerosol optical depth (AOD) for two wavelengths and the Ångström turbidity parameter
α using as input parameters data extracted from the principal plane of sky images from the All-Sky Imager. The models use data from a CIMEL CE318 radiometer for training and validation. The deviations between model and reference values are in the range of uncertainties assigned to Aerosol Robotic Network (AERONET) network. |
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ISSN: | 1352-2310 1873-2844 |
DOI: | 10.1016/j.atmosenv.2007.06.016 |