Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4442842 | Atmospheric Environment | 2008 | 7 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Atmospheric Science
Authors
A. Cazorla, F.J. Olmo, L. Alados-Arboledas,