Cost733cat - A database of weather and circulation type classifications

Andreas Philipp, Judit Bartholy, Christoph Beck, Michel Erpicum, Pere Esteban, Xavier Fettweis, Radan Huth, Paul James, Sylvie Jourdain, Frank Kreienkamp, Thomas Krennert, Spyros Lykoudis, Silas C. Michalides, Krystyna Pianko-Kluczynska, Piia Post, Domingo Rasilla Álvarez, Reinhard Schiemann, Arne Spekat, Filippos S. Tymvios

Research output: Contribution to journalArticle

207 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)360-373
Number of pages14
JournalPhysics and Chemistry of the Earth
Volume35
Issue number9-12
DOIs
Publication statusPublished - Apr 9 2010

Keywords

  • COST 733
  • Circulation type classification
  • Dataset
  • Europe
  • Weather type classification

ASJC Scopus subject areas

  • Geophysics
  • Geochemistry and Petrology

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    Philipp, A., Bartholy, J., Beck, C., Erpicum, M., Esteban, P., Fettweis, X., Huth, R., James, P., Jourdain, S., Kreienkamp, F., Krennert, T., Lykoudis, S., Michalides, S. C., Pianko-Kluczynska, K., Post, P., Álvarez, D. R., Schiemann, R., Spekat, A., & Tymvios, F. S. (2010). Cost733cat - A database of weather and circulation type classifications. Physics and Chemistry of the Earth, 35(9-12), 360-373. https://doi.org/10.1016/j.pce.2009.12.010