Trends of Dust Transport Episodes in Cyprus Using a Classification of Synoptic Types Established with Artificial Neural Networks. (29th August 2013)

• Record Type: Journal Article
• Authors: Michaelides, S.; Tymvios, F.; Athanasatos, S.; Papadakis, M.
• Other Names: Paoletti Elena Academic Editor.; Rutgersson Anna Academic Editor.
• Is Part Of: Journal of climatology. Volume 2013(2013)
• Publication Date: 2013-08-29
• Subjects: Climatology -- Periodicals; Climatology; Meteorology; Periodicals; Electronic journals
• DOI: 10.1155/2013/280248
• Languages: English
• ISSNs: 2356-6361

Abstract

Abstract : 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/(m 3 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.