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DOI10.5194/acp-17-11861-2017
Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula
Cazorla, Alberto1,2; Andres Casquero-Vera, Juan1,2; Roman, Roberto1,2; Luis Guerrero-Rascado, Juan1,2; Toledano, Carlos3; Cachorro, Victoria E.3; Orza, Jose Antonio G.4; Luisa Cancillo, Maria5,6; Serrano, Antonio5,6; Titos, Gloria7; Pandolfi, Marco7; Alastuey, Andres7; Hanrieder, Natalie8; Alados-Arboledas, Lucas1,2
2017-10-09
发表期刊ATMOSPHERIC CHEMISTRY AND PHYSICS
ISSN1680-7316
EISSN1680-7324
出版年2017
卷号17期号:19
文章类型Article
语种英语
国家Spain
英文摘要

The interest in the use of ceilometers for optical aerosol characterization has increased in the last few years. They operate continuously almost unattended and are also much less expensive than lidars; hence, they can be distributed in dense networks over large areas. However, due to the low signal-to-noise ratio it is not always possible to obtain particle backscatter coefficient profiles, and the vast number of data generated require an automated and unsupervised method that ensures the quality of the profiles inversions. In this work we describe a method that uses aerosol optical depth (AOD) measurements from the AERONET network that it is applied for the calibration and automated quality assurance of inversion of ceilometer profiles. The method is compared with independent inversions obtained by colocated multiwavelength lidar measurements. A difference smaller than 15% in backscatter is found between both instruments. This method is continuously and automatically applied to the Iberian Ceilometer Network (ICENET) and a case example during an unusually intense dust outbreak affecting the Iberian Peninsula between 20 and 24 February 2016 is shown. Results reveal that it is possible to obtain quantitative optical aerosol properties (particle backscatter coefficient) and discriminate the quality of these retrievals with ceilometers over large areas. This information has a great potential for alert systems and model assimilation and evaluation.


领域地球科学
收录类别SCI-E
WOS记录号WOS:000412581800001
WOS关键词LIDAR ; AEROSOL ; EARLINET ; BACKSCATTER ; RETRIEVAL ; EVENT ; PRECIPITATION ; EXTINCTION ; PARTICLES ; EVOLUTION
WOS类目Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/24982
专题地球科学
作者单位1.Univ Granada, IISTA CEAMA, Andalusian Inst Earth Syst Res, Junta Andalucia, Granada, Spain;
2.Univ Granada, Dept Appl Phys, Granada, Spain;
3.Univ Valladolid, GOA, Valladolid, Spain;
4.Univ Miguel Hernandez, Fis Aplicada, SCOLAb, Elche, Spain;
5.Univ Extremadura, Dept Phys, Badajoz, Spain;
6.Univ Extremadura, IACYS, Inst Water Res Climate Change & Sustainabil, Badajoz, Spain;
7.CSIC, Inst Environm Assessment & Water Res IDAEA, Barcelona, Spain;
8.Inst Solar Res, German Aerosp Ctr DLR, Plataforma Solar Almeria, Almeria, Spain
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GB/T 7714
Cazorla, Alberto,Andres Casquero-Vera, Juan,Roman, Roberto,et al. Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2017,17(19).
APA Cazorla, Alberto.,Andres Casquero-Vera, Juan.,Roman, Roberto.,Luis Guerrero-Rascado, Juan.,Toledano, Carlos.,...&Alados-Arboledas, Lucas.(2017).Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula.ATMOSPHERIC CHEMISTRY AND PHYSICS,17(19).
MLA Cazorla, Alberto,et al."Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula".ATMOSPHERIC CHEMISTRY AND PHYSICS 17.19(2017).
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