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dc.contributor.authorCazorla Cabrera, Alberto 
dc.contributor.authorShields, J. E.
dc.contributor.authorKarr, M. E.
dc.contributor.authorOlmo Reyes, Francisco José 
dc.contributor.authorBurden, A.
dc.contributor.authorAlados Arboledas, Lucas 
dc.date.accessioned2014-05-20T10:37:22Z
dc.date.available2014-05-20T10:37:22Z
dc.date.issued2009
dc.identifier.citationCazorla, A.; et al. Technical Note: Determination of aerosol optical properties by a calibrated sky imager. Atmospheric Chemistry and Physics, 9: 6417-6427 (2009). [http://hdl.handle.net/10481/31808]es_ES
dc.identifier.issn1680-7316
dc.identifier.issn1680-7324
dc.identifier.urihttp://hdl.handle.net/10481/31808
dc.description.abstractThe 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 A° ngstro¨m exponent 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 , the deviation is within the uncertainty assigned to the AERONET (±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.es_ES
dc.description.sponsorshipThis work was supported by the Centro de Investigación Científica y Tecnológica (CICYT) of the Spanish Ministry of Science and Technology through projects CGL2007- 66477-C02-01 and CSD2007-00067 and the Andalusian Regional Government through project P06-RNM-01503 and P08-RNM-3568). First author has been funded by the Andalusian Regional Government and his research stay at University of California at San Diego has been also funded by the Andalusian Regional Government.es_ES
dc.language.isoenges_ES
dc.publisherCopernicus Publicationses_ES
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Licensees_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es_ES
dc.subjectUV erythema irradiancees_ES
dc.subjectHeat-wavees_ES
dc.subjectSoutheaster Spaines_ES
dc.subjectAtmospheric aerosolses_ES
dc.subjectPrincipal-planees_ES
dc.subjectNetworkses_ES
dc.titleTechnical Note: Determination of aerosol optical properties by a calibrated sky imageres_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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