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Volume 15, issue 6 | Copyright

Special issue: BACCHUS – Impact of Biogenic versus Anthropogenic emissions...

Atmos. Chem. Phys., 15, 3463-3477, 2015
https://doi.org/10.5194/acp-15-3463-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 30 Mar 2015

Research article | 30 Mar 2015

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

R. E. Mamouri1 and A. Ansmann2 R. E. Mamouri and A. Ansmann
  • 1Cyprus University of Technology, Dept. of Civil Engineering and Geomatics, Limassol, Cyprus
  • 2Leibniz Institute for Tropospheric Research, Leipzig, Germany

Abstract. 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.

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