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| Titel |
Investigation of trends in synoptic patterns over Europe with artificial neural networks |
| VerfasserIn |
S. Michaelides, F. Tymvios, D. Charalambous |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7340
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| Digitales Dokument |
URL |
| Erschienen |
In: 10th EGU Plinius Conference on Mediterranean Storms (2008) ; Nr. 23 (2010-11-15), S.107-112 |
| Datensatznummer |
250015114
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| Publikation (Nr.) |
 copernicus.org/adgeo-23-107-2010.pdf |
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| Zusammenfassung |
| The present study is a comprehensive application of a
methodology developed for the classification of synoptic situations using
artificial neural networks. In this respect, the 500 hPa geopotential height
patterns at 12:00 UTC (Universal Time Coordinated) determined from the
reanalysis data (ERA-40 dataset) of the European Centre for Medium range
Weather Forecasts (ECMWF) over Europe were used. The dataset covers a period
of 45 years (1957–2002) and the neural network methodology applied is the
SOM architecture (Self Organizing Maps). The classification of the synoptic
scale systems was conducted by considering 9, 18, 27 and 36 synoptic
patterns. The statistical analysis of the frequency distribution of the
classification results for the 36 clusters over the entire 44-year period
revealed significant tendencies in the frequency distribution of certain
clusters, thus substantiating a possible climatic change. In the following,
the database was split into two periods, the "reference" period that
includes the first 30 years and the "test" period comprising the remaining
14 years. |
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