Using a Sky Imager for aerosol characterization

被引：44

作者：

Cazorla, A. ^{[1
,2
]}

Olmo, F. J. ^{[1
,2
]}

Alados-Arboledas, L. ^{[1
,2
]}

机构：

[1] Univ Granada, Fac Ciencias, Dept Fis Aplicada, E-18071 Granada, Spain

[2] Junta Andalucia Univ Granada, CEAMA, Granada 18071, Spain

来源：

ATMOSPHERIC ENVIRONMENT | 2008年 / 42卷 / 11期

关键词：

sky imagery; sky radiance; aerosol optical depth; neural networks; radial basis networks;

D O I：

10.1016/j.atmosenv.2007.06.016

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

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 Angstrom, turbidity parameter a 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. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：2739 / 2745

页数：7

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