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Keywords = Cloudnet target classification algorithm

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15 pages, 34761 KB  
Article
Ground-Based Measurements of Cloud Properties at the Bucharest–Măgurele Cloudnet Station: First Results
by Răzvan Pîrloagă, Dragoş Ene, Mihai Boldeanu, Bogdan Antonescu, Ewan J. O’Connor and Sabina Ştefan
Atmosphere 2022, 13(9), 1445; https://doi.org/10.3390/atmos13091445 - 6 Sep 2022
Cited by 14 | Viewed by 3621
Abstract
Data collected over a period of 18 months (December 2019–May 2021) at the Bucharest–Măgurele Cloudnet station were analysed for the first time to determine the macrophysical and microphysical cloud properties over this site. A total number of 1,327,680 vertical profiles containing the target [...] Read more.
Data collected over a period of 18 months (December 2019–May 2021) at the Bucharest–Măgurele Cloudnet station were analysed for the first time to determine the macrophysical and microphysical cloud properties over this site. A total number of 1,327,680 vertical profiles containing the target classification based on the Cloudnet algorithm were analysed, of which 1,077,858 profiles contained hydrometeors. The highest number of profiles with hydrometeors (>60%) was recorded in December 2020, with hydrometeors being observed mainly below 5 km. Above 5 km, the frequency of occurrence of hydrometeors was less than <20%. Based on the initial Cloudnet target classification, a cloud classification scheme was implemented. Clouds were more frequently observed during winter compared with other seasons (45% of all profiles). Ice clouds were the most frequent type of cloud (468,463 profiles) during the study period, followed by mixed phases (220,280 profiles) and mixed phased precipitable clouds (164,868 profiles). The geometrical thickness varied from a median value of 244 m for liquid clouds during summer to 3362 m for mix phased precipitable clouds during spring. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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21 pages, 60499 KB  
Article
Geometrical and Microphysical Properties of Clouds Formed in the Presence of Dust above the Eastern Mediterranean
by Eleni Marinou, Kalliopi Artemis Voudouri, Ioanna Tsikoudi, Eleni Drakaki, Alexandra Tsekeri, Marco Rosoldi, Dragos Ene, Holger Baars, Ewan O’Connor, Vassilis Amiridis and Charikleia Meleti
Remote Sens. 2021, 13(24), 5001; https://doi.org/10.3390/rs13245001 - 9 Dec 2021
Cited by 16 | Viewed by 5435
Abstract
In this work, collocated lidar–radar observations are used to retrieve the vertical profiles of cloud properties above the Eastern Mediterranean. Measurements were performed in the framework of the PRE-TECT experiment during April 2017 at the Greek atmospheric observatory of Finokalia, Crete. Cloud geometrical [...] Read more.
In this work, collocated lidar–radar observations are used to retrieve the vertical profiles of cloud properties above the Eastern Mediterranean. Measurements were performed in the framework of the PRE-TECT experiment during April 2017 at the Greek atmospheric observatory of Finokalia, Crete. Cloud geometrical and microphysical properties at different altitudes were derived using the Cloudnet target classification algorithm. We found that the variable atmospheric conditions that prevailed above the region during April 2017 resulted in complex cloud structures. Mid-level clouds were observed in 38% of the cases, high or convective clouds in 58% of the cases, and low-level clouds in 2% of the cases. From the observations of cloudy profiles, pure ice phase occurred in 94% of the cases, mixed-phase clouds were observed in 27% of the cases, and liquid clouds were observed in 8.7% of the cases, while Drizzle or rain occurred in 12% of the cases. The significant presence of Mixed-Phase Clouds was observed in all the clouds formed at the top of a dust layer, with three times higher abundance than the mean conditions (26% abundance at −15 °C). The low-level clouds were formed in the presence of sea salt and continental particles with ice abundance below 30%. The derived statistics on clouds’ high-resolution vertical distributions and thermodynamic phase can be combined with Cloudnet cloud products and lidar-retrieved aerosol properties to study aerosol-cloud interactions in this understudied region and evaluate microphysics parameterizations in numerical weather prediction and global climate models. Full article
(This article belongs to the Special Issue Radar Remote Sensing of Cloud and Precipitation)
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