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Titel |
Technical Note: Determination of aerosol optical properties by a calibrated sky imager |
VerfasserIn |
A. Cazorla, J. E. Shields, M. E. Karr, F. J. Olmo, A. Burden, L. Alados-Arboledas |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1680-7316
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Digitales Dokument |
URL |
Erschienen |
In: Atmospheric Chemistry and Physics ; 9, no. 17 ; Nr. 9, no. 17 (2009-09-08), S.6417-6427 |
Datensatznummer |
250007609
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Publikation (Nr.) |
copernicus.org/acp-9-6417-2009.pdf |
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Zusammenfassung |
The calibrated ground-based sky imager developed in the Marine Physical
Laboratory, the Whole Sky Imager (WSI), has been tested with data from the
Atmospheric Radiation Measurement Program (ARM) at the Southern Great Plain
site (SGP) to determine optical properties of the atmospheric aerosol.
Different neural network-based models calculate the aerosol optical depth
(AOD) for three wavelengths using the radiance extracted from the principal
plane of sky images from the WSI as input parameters. The models use data
from a CIMEL CE318 photometer for training and validation and the
wavelengths used correspond to the closest wavelengths in both instruments.
The spectral dependency of the AOD, characterized by the Ångström
exponent α in the interval 440–870 nm, is also derived using the
standard AERONET procedure and also with a neural network-based model using
the values obtained with a CIMEL CE318. The deviations between the WSI
derived AOD and the AOD retrieved by AERONET are within the nominal
uncertainty assigned to the AERONET AOD calculation (±0.01), in 80%
of the cases. The explanation of data variance by the model is over 92%
in all cases. In the case of α, the deviation is within the
uncertainty assigned to the AERONET α (±0.1) in 50% of the
cases for the standard method and 84% for the neural network-based model.
The explanation of data variance by the model is 63% for the standard
method and 77% for the neural network-based model. |
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