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Author: Baumgarten, G. × Author: Lübken, F.-J. × Has files: Yes × Subject: lidar × Subject: polar mesospheric cloud ×

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    Coincident measurements of PMSE and NLC above ALOMAR (69° N, 16° E) by radar and lidar from 1999-2008
    (Göttingen : Copernicus, 2011) Kaifler, N.; Baumgarten, G.; Fiedler, J.; Latteck, R.; Lübken, F.-J.; Rapp, M.
    Polar Mesosphere Summer Echoes (PMSE) and Noctilucent Clouds (NLC) have been routinely measured at the ALOMAR research facility in Northern Norway (69° N, 16° E) by lidar and radar, respectively. 2900 h of lidar measurements by the ALOMAR Rayleigh/Mie/Raman lidar were combined with almost 18 000 h of radar measurements by the ALWIN VHF radar, all taken during the years 1999 to 2008, to study simultaneous and common-volume observations of both phenomena. PMSE and NLC are known from both theory and observations to be positively linked. We quantify the occurrences of PMSE and/or NLC and relations in altitude, especially with respect to the lower layer boundaries. The PMSE occurrence rate is with 75.3% considerably higher than the NLC occurrence rate of 19.5%. For overlapping PMSE and NLC observations, we confirm the coincidence of the lower boundaries and find a standard deviation of 1.26 km, hinting at very fast sublimation rates. However, 10.1% of all NLC measurements occur without accompanying PMSE. Comparison of occurrence rates with solar zenith angle reveals that NLC without PMSE mostly occur around midnight indicating that the ice particles were not detected by the radar due to the reduced electron density.
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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.