Characterization of Climatic Variations in Spain at the Regional Scale: A Computational Intelligence Approach

Download
  1. (PDF, 535 KB)
AuthorSearch for: ; Search for: ; Search for:
TypeArticle
ConferenceProceedings of the IEEE World Congress on Computational Intelligence (WCCI-2008), June 1, 2008., Hong Kong, China
AbstractComputational intelligence and other data mining techniques are used for characterizing regional and time varying climatic variations in Spain in the period 1901?2005. Daily maximum temperature data from 10 climatic stations are analyzed (with and without missing values) using principal components (PC), similarity-preservation feature generation, clustering, Kolmogorov-Smirnov dissimilarity analysis and genetic programming (GP). The new features were computed using hybrid optimization (differential evolution and Fletcher-Reeves) and GP. From them, a scalar regional climatic index was obtained which identifies time landmarks and changes in the climate rhythm. The equations obtained with GP are simpler than those obtained with PC and they highlight the most important sites characterizing the regional climate. Whereas the general consensus is that there has been a clear and smooth trend towards warming during the last decades, the results suggest that the picture may probably be much more complicated than what is usually assumed.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number49905
NPARC number5764266
Export citationExport as RIS
Report a correctionReport a correction
Record identifieraea64c25-fd0f-4673-9dbd-7534d1db7a11
Record created2009-03-29
Record modified2016-05-09
Bookmark and share
  • Share this page with Facebook (Opens in a new window)
  • Share this page with Twitter (Opens in a new window)
  • Share this page with Google+ (Opens in a new window)
  • Share this page with Delicious (Opens in a new window)