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DDC: 550 × Type: Text × Subject: ice × Subject: lidar ×

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    A new description of probability density distributions of polar mesospheric clouds
    (Göttingen : Copernicus GmbH, 2019) Berger, U.; Baumgarten, G.; Fiedler, J.; Lübken, F.-J.
    In this paper we present a new description of statistical probability density functions (pdfs) of polar mesospheric clouds (PMCs). The analysis is based on observations of maximum backscatter, ice mass density, ice particle radius, and number density of ice particles measured by the ALOMAR Rayleigh-Mie-Raman lidar for all PMC seasons from 2002 to 2016. From this data set we derive a new class of pdfs that describe the statistics of PMC events that is different from previous statistical methods using the approach of an exponential distribution commonly named the g distribution. The new analysis describes successfully the probability distributions of ALOMAR lidar data. It turns out that the former g-function description is a special case of our new approach. In general the new statistical function can be applied to many kinds of different PMC parameters, e.g., maximum backscatter, integrated backscatter, ice mass density, ice water content, ice particle radius, ice particle number density, or albedo measured by satellites. As a main advantage the new method allows us to connect different observational PMC distributions of lidar and satellite data, and also to compare with distributions from ice model studies. In particular, the statistical distributions of different ice parameters can be compared with each other on the basis of a common assessment that facilitates, for example, trend analysis of PMC. © Author(s) 2019.
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    Estimated desert-dust ice nuclei profiles from polarization lidar: Methodology and case studies
    (München : European Geopyhsical Union, 2015) Mamouri, R.E.; Ansmann, A.
    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.