Please use this identifier to cite or link to this item: https://oar.tib.eu/jspui/handle/123456789/5996
Files in This Item:
File SizeFormat 
Berger2019.pdf3.91 MBAdobe PDFView/Open
Title: A new description of probability density distributions of polar mesospheric clouds
Authors: Berger, U.Baumgarten, G.Fiedler, J.Lübken, F.-J.
Publishers Version: https://doi.org/10.5194/acp-19-4685-2019
Issue Date: 2019
Published in: Atmospheric Chemistry and Physics Vol. 19 (2019), No. 7
Publisher: Göttingen : Copernicus GmbH
Abstract: 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.
Keywords: backscatter; ice; lidar; polar mesospheric cloud; probability density function; statistical distribution; trend analysis
DDC: 550
License: CC BY 4.0 Unported
Link to License: https://creativecommons.org/licenses/by/4.0/
Appears in Collections:Geowissenschaften



This item is licensed under a Creative Commons License Creative Commons