Estimated desert-dust ice nuclei profiles from polarization lidar: Methodology and case studies

A lidar method is presented that permits the estimation of height profiles of ice nuclei concentrations (INC) in desert dust layers. The polarization lidar technique is applied to separate dust and non-dust backscatter and extinction coefficients. The desert dust extinction coefficients σd are then...

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Main Authors: Mamouri, R.E., Ansmann, A.
Format: Article in Journal/Newspaper
Language:English
Published: München : European Geopyhsical Union 2015
Subjects:
ice
550
Online Access:https://doi.org/10.34657/5082
https://oa.tib.eu/renate/handle/123456789/290
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spelling ftleibnizopen:oai:oai.leibnizopen.de:UeQqsIYBdbrxVwz6b3Ee 2023-05-15T13:06:24+02:00 Estimated desert-dust ice nuclei profiles from polarization lidar: Methodology and case studies Mamouri, R.E. Ansmann, A. 2015 application/pdf https://doi.org/10.34657/5082 https://oa.tib.eu/renate/handle/123456789/290 eng eng München : European Geopyhsical Union CC BY 3.0 Unported https://creativecommons.org/licenses/by/3.0/ CC-BY Atmospheric Chemistry and Physics, Volume 15, Issue 6, Page 3463-3477 AERONET aerosol property dust estimation method ice lidar methodology particle size temperature profile 550 article Text 2015 ftleibnizopen https://doi.org/10.34657/5082 2023-03-06T00:14:52Z A lidar method is presented that permits the estimation of height profiles of ice nuclei concentrations (INC) in desert dust layers. The polarization lidar technique is applied to separate dust and non-dust backscatter and extinction coefficients. The desert dust extinction coefficients σd are then converted to aerosol particle number concentrations APC280 which consider particles with radius > 280 nm only. By using profiles of APC280 and ambient temperature T along the laser beam, the profile of INC can be estimated within a factor of 3 by means of APC-T-INC parameterizations from the literature. The observed close relationship between σd at 500 nm and APC280 is of key importance for a successful INC retrieval. We studied this link by means of AERONET (Aerosol Robotic Network) sun/sky photometer observations at Morocco, Cabo Verde, Barbados, and Cyprus during desert dust outbreaks. The new INC retrieval method is applied to lidar observations of dust layers with the spaceborne lidar CALIOP (Cloud Aerosol Lidar with Orthogonal Polarization) during two overpasses over the EARLINET (European Aerosol Research Lidar Network) lidar site of the Cyprus University of Technology (CUT), Limassol (34.7° N, 33° E), Cyprus. The good agreement between the CALIOP and CUT lidar retrievals of σd, APC280, and INC profiles corroborates the potential of CALIOP to provide 3-D global desert dust APC280 and INC data sets. publishedVersion Article in Journal/Newspaper Aerosol Robotic Network LeibnizOpen (The Leibniz Association)
institution Open Polar
collection LeibnizOpen (The Leibniz Association)
op_collection_id ftleibnizopen
language English
topic AERONET
aerosol property
dust
estimation method
ice
lidar
methodology
particle size
temperature profile
550
spellingShingle AERONET
aerosol property
dust
estimation method
ice
lidar
methodology
particle size
temperature profile
550
Mamouri, R.E.
Ansmann, A.
Estimated desert-dust ice nuclei profiles from polarization lidar: Methodology and case studies
topic_facet AERONET
aerosol property
dust
estimation method
ice
lidar
methodology
particle size
temperature profile
550
description A lidar method is presented that permits the estimation of height profiles of ice nuclei concentrations (INC) in desert dust layers. The polarization lidar technique is applied to separate dust and non-dust backscatter and extinction coefficients. The desert dust extinction coefficients σd are then converted to aerosol particle number concentrations APC280 which consider particles with radius > 280 nm only. By using profiles of APC280 and ambient temperature T along the laser beam, the profile of INC can be estimated within a factor of 3 by means of APC-T-INC parameterizations from the literature. The observed close relationship between σd at 500 nm and APC280 is of key importance for a successful INC retrieval. We studied this link by means of AERONET (Aerosol Robotic Network) sun/sky photometer observations at Morocco, Cabo Verde, Barbados, and Cyprus during desert dust outbreaks. The new INC retrieval method is applied to lidar observations of dust layers with the spaceborne lidar CALIOP (Cloud Aerosol Lidar with Orthogonal Polarization) during two overpasses over the EARLINET (European Aerosol Research Lidar Network) lidar site of the Cyprus University of Technology (CUT), Limassol (34.7° N, 33° E), Cyprus. The good agreement between the CALIOP and CUT lidar retrievals of σd, APC280, and INC profiles corroborates the potential of CALIOP to provide 3-D global desert dust APC280 and INC data sets. publishedVersion
format Article in Journal/Newspaper
author Mamouri, R.E.
Ansmann, A.
author_facet Mamouri, R.E.
Ansmann, A.
author_sort Mamouri, R.E.
title Estimated desert-dust ice nuclei profiles from polarization lidar: Methodology and case studies
title_short Estimated desert-dust ice nuclei profiles from polarization lidar: Methodology and case studies
title_full Estimated desert-dust ice nuclei profiles from polarization lidar: Methodology and case studies
title_fullStr Estimated desert-dust ice nuclei profiles from polarization lidar: Methodology and case studies
title_full_unstemmed Estimated desert-dust ice nuclei profiles from polarization lidar: Methodology and case studies
title_sort estimated desert-dust ice nuclei profiles from polarization lidar: methodology and case studies
publisher München : European Geopyhsical Union
publishDate 2015
url https://doi.org/10.34657/5082
https://oa.tib.eu/renate/handle/123456789/290
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source Atmospheric Chemistry and Physics, Volume 15, Issue 6, Page 3463-3477
op_rights CC BY 3.0 Unported
https://creativecommons.org/licenses/by/3.0/
op_rightsnorm CC-BY
op_doi https://doi.org/10.34657/5082
_version_ 1766004287267143680