scholarly journals Consequences of recent Southern Hemisphere winter variability on polar mesospheric clouds

2011 ◽  
Vol 73 (13) ◽  
pp. 2013-2021 ◽  
Author(s):  
David E. Siskind ◽  
Michael H. Stevens ◽  
Mark Hervig ◽  
Fabrizio Sassi ◽  
Karl Hoppel ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Polar Mesospheric Clouds ◽  
Mesospheric Clouds ◽  
Hemisphere Winter

scholarly journals An analysis of POAM II solar occultation observations of polar mesospheric clouds in the southern hemisphere

1997 ◽  
Vol 102 (D2) ◽  
pp. 1971-1981 ◽  
Author(s):  
D. J. Debrestian ◽  
J. D. Lumpe ◽  
E. P. Shettle ◽  
R. M. Bevilacqua ◽  
J. J. Olivero ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Polar Mesospheric Clouds ◽  
Solar Occultation ◽  
Mesospheric Clouds

POAM II observations of polar mesospheric clouds in the Southern Hemisphere

1997 ◽  
Vol 19 (4) ◽  
pp. 587-590 ◽  
Author(s):  
D.J Debrestian ◽  
J.D Lumpe ◽  
R.M Bevilacqua ◽  
E.P Shettle ◽  
J.S Hornstein ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Polar Mesospheric Clouds ◽  
Mesospheric Clouds

Middle ultraviolet imager observations of the distribution of polar mesospheric clouds

2001 ◽  
Vol 27 (10) ◽  
pp. 1703-1708 ◽  
Author(s):  
J.F. Carbary ◽  
D. Morrison ◽  
G.J. Romick ◽  
L.J. Paxton ◽  
C.-I. Meng
Keyword(s):  
Polar Mesospheric Clouds ◽  
Mesospheric Clouds

scholarly journals A new Description of Probability Density Distributions of Polar Mesospheric Clouds (PMC)

2018 ◽  
Author(s):  
Uwe Berger ◽  
Gerd Baumgarten ◽  
Jens Fiedler ◽  
Franz-Josef Lübken
Keyword(s):  
Probability Density ◽  
Mass Density ◽  
Particle Radius ◽  
Number Density ◽  
Data Set ◽  
Statistical Probability ◽  
Polar Mesospheric Clouds ◽  
Density Distributions ◽  
Mesospheric Clouds ◽  
Probability Density Distributions

Abstract. In this paper we present a new description about statistical probability density distributions (pdfs) of Polar Mesospheric Clouds (PMC) and noctilucent clouds (NLC). 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 RMR-lidar for all NLC seasons from 2002 to 2016. From this data set we derive a new class of pdfs that describe the statistics of PMC/NLC events which is different from previously statistical methods using the approach of an exponential distribution commonly named g-distribution. The new analysis describes successfully the probability statistic 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 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 facilitate, for example, trend analysis of PMC/NLC.

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