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Cost733cat – A database of weather and circulation type classifications

Authors :
Philipp, Andreas
Bartholy, Judit
Beck, Christoph
Erpicum, Michel
Esteban, Pere
Fettweis, Xavier
Huth, Radan
James, Paul
Jourdain, Sylvie
Kreienkamp, Frank
Krennert, Thomas
Lykoudis, Spyros
Michalides, Silas C.
Pianko-Kluczynska, Krystyna
Post, Piia
Álvarez, Domingo Rasilla
Schiemann, Reinhard
Spekat, Arne
Tymvios, Filippos S.
Source :
Physics & Chemistry of the Earth - Parts A/B/C. Apr2010, Vol. 35 Issue 9-12, p360-373. 14p.
Publication Year :
2010

Abstract

Abstract: A new database of weather and circulation type catalogs is presented comprising 17 automated classification methods and five subjective classifications. It was compiled within COST Action 733 “Harmonisation and Applications of Weather Type Classifications for European regions” in order to evaluate different methods for weather and circulation type classification. This paper gives a technical description of the included methods using a new conceptual categorization for classification methods reflecting the strategy for the definition of types. Methods using predefined types include manual and threshold based classifications while methods producing types derived from the input data include those based on eigenvector techniques, leader algorithms and optimization algorithms. In order to allow direct comparisons between the methods, the circulation input data and the methods’ configuration were harmonized for producing a subset of standard catalogs of the automated methods. The harmonization includes the data source, the climatic parameters used, the classification period as well as the spatial domain and the number of types. Frequency based characteristics of the resulting catalogs are presented, including variation of class sizes, persistence, seasonal and inter-annual variability as well as trends of the annual frequency time series. The methodological concept of the classifications is partly reflected by these properties of the resulting catalogs. It is shown that the types of subjective classifications compared to automated methods show higher persistence, inter-annual variation and long-term trends. Among the automated classifications optimization methods show a tendency for longer persistence and higher seasonal variation. However, it is also concluded that the distance metric used and the data preprocessing play at least an equally important role for the properties of the resulting classification compared to the algorithm used for type definition and assignment. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
14747065
Volume :
35
Issue :
9-12
Database :
Academic Search Index
Journal :
Physics & Chemistry of the Earth - Parts A/B/C
Publication Type :
Academic Journal
Accession number :
52342268
Full Text :
https://doi.org/10.1016/j.pce.2009.12.010