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Trends of Dust Transport Episodes in Cyprus Using a Classification of Synoptic Types Established with Artificial Neural Networks
Joint Authors
Michaelides, S.
Papadakis, M.
Athanasatos, S.
Tymvios, F.
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-08-29
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
The relationship between dust episodes over Cyprus and specific synoptic patterns has long been considered but also further supported in recent studies by the authors.
Having defined a dust episode as a day when the average PM10 measurement exceeds the threshold of 50 mg/(m3 day), the authors have utilized Artificial Neural Networks and synoptic charts, together with satellite and ground measurements, in order to establish a scheme which links specific synoptic patterns with the appearance of dust transport over Cyprus.
In an effort to understand better these complicated synoptic-scale phenomena and their associations with dust transport episodes, the authors attempt in the present paper a followup of the previous tasks with the objective to further investigate dust episodes from the point of view of their time trends.
The results have shown a tendency for the synoptic situations favoring dust events to increase in the last decades, whereas, the synoptic situations not favoring such events tend to decrease with time.
American Psychological Association (APA)
Michaelides, S.& Tymvios, F.& Athanasatos, S.& Papadakis, M.. 2013. Trends of Dust Transport Episodes in Cyprus Using a Classification of Synoptic Types Established with Artificial Neural Networks. Journal of Climatology،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-459881
Modern Language Association (MLA)
Michaelides, S.…[et al.]. Trends of Dust Transport Episodes in Cyprus Using a Classification of Synoptic Types Established with Artificial Neural Networks. Journal of Climatology No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-459881
American Medical Association (AMA)
Michaelides, S.& Tymvios, F.& Athanasatos, S.& Papadakis, M.. Trends of Dust Transport Episodes in Cyprus Using a Classification of Synoptic Types Established with Artificial Neural Networks. Journal of Climatology. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-459881
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-459881