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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| container_issue | 11 |
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| container_title | Atmospheric environment (1994) |
| container_volume | 42 |
| creator | Cazorla, A. Olmo, F.J. Alados-Arboledas, L. |
| description | 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. |
| doi_str_mv | 10.1016/j.atmosenv.2007.06.016 |
| format | Article |
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| fulltext | fulltext |
| identifier | ISSN: 1352-2310 |
| ispartof | Atmospheric environment (1994), 2008-04, Vol.42 (11), p.2739-2745 |
| issn | 1352-2310 1873-2844 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_20695934 |
| source | Elsevier ScienceDirect Journals |
| subjects | Aerosol optical depth Analysis methods Applied sciences Atmospheric pollution Earth, ocean, space Exact sciences and technology External geophysics Geophysics. Techniques, methods, instrumentation and models Meteorology Neural networks Particles and aerosols Pollution Radial basis networks Sky imagery Sky radiance |
| title | Using a Sky Imager for aerosol characterization |
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