A new description of probability density distributions of polar mesospheric clouds
<p>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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2019-04-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/19/4685/2019/acp-19-4685-2019.pdf |
| _version_ | 1819050506827333632 |
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| author | U. Berger G. Baumgarten J. Fiedler F.-J. Lübken |
| author_facet | U. Berger G. Baumgarten J. Fiedler F.-J. Lübken |
| author_sort | U. Berger |
| collection | DOAJ |
| description | <p>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 <span class="inline-formula"><i>g</i></span> distribution. The new analysis describes
successfully the probability distributions of ALOMAR lidar data. It turns out that the
former <span class="inline-formula"><i>g</i></span>-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.</p> |
| first_indexed | 2024-12-21T11:49:08Z |
| format | Article |
| id | doaj.art-b20e5869c9e6472b89e7ae1b864c238b |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-12-21T11:49:08Z |
| publishDate | 2019-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-b20e5869c9e6472b89e7ae1b864c238b2022-12-21T19:05:06ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242019-04-01194685470210.5194/acp-19-4685-2019A new description of probability density distributions of polar mesospheric cloudsU. BergerG. BaumgartenJ. FiedlerF.-J. Lübken<p>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 <span class="inline-formula"><i>g</i></span> distribution. The new analysis describes successfully the probability distributions of ALOMAR lidar data. It turns out that the former <span class="inline-formula"><i>g</i></span>-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.</p>https://www.atmos-chem-phys.net/19/4685/2019/acp-19-4685-2019.pdf |
| spellingShingle | U. Berger G. Baumgarten J. Fiedler F.-J. Lübken A new description of probability density distributions of polar mesospheric clouds Atmospheric Chemistry and Physics |
| title | A new description of probability density distributions of polar mesospheric clouds |
| title_full | A new description of probability density distributions of polar mesospheric clouds |
| title_fullStr | A new description of probability density distributions of polar mesospheric clouds |
| title_full_unstemmed | A new description of probability density distributions of polar mesospheric clouds |
| title_short | A new description of probability density distributions of polar mesospheric clouds |
| title_sort | new description of probability density distributions of polar mesospheric clouds |
| url | https://www.atmos-chem-phys.net/19/4685/2019/acp-19-4685-2019.pdf |
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