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CLUSTER ANALYSIS OF EUROPEAN DAILY TEMPERATURE SERIES: AN EXTREME VALUE APPROACH

This study explores the application of cluster analysis on European daily temperature series using extreme value methodology. The computation of Probability Density Functions (PDFs) and the estimation of return levels are discussed, along with the exploration of the European Climate Assessment dataset. Results are presented, including a dendrogram for 25-year return values using the average linkage method. The study concludes with key findings and references.

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CLUSTER ANALYSIS OF EUROPEAN DAILY TEMPERATURE SERIES: AN EXTREME VALUE APPROACH

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  1. CLUSTER ANALYSIS OF EUROPEAN DAILY TEMPERATURE SERIES: AN EXTREME VALUE APPROACH Andrés M. Alonso Departamento de Estadística Universidad Carlos II de Madrid Spain

  2. JOINT WORK WITH

  3. OUTLINE OF THE TALK

  4. INTRODUCTORY REMARKS

  5. INTRODUCTORY REMARKS

  6. MAIN PURPOSE

  7. TIME SERIES CLUSTER METHODOLOGY

  8. TIME SERIES CLUSTER METHODOLOGY

  9. COMPUTATION OF THE PDF’s

  10. COMPUTATION OF THE PDF’s

  11. COMPUTATION OF THE PDF’s

  12. COMPUTATION OF THE PDF’s

  13. COMPUTATION OF THE PDF’s Ourparameter of interestwillbethequantilexpfor a specifiedexceedanceprobabilityp AssumingthattheGeneralized Extreme Valuecorrespondstotheannualmaximum. Then, roughlyspeaking, xpisthereturnlevelthatisassociatedwiththereturnperiod 1/pforsmallp, in unit of years.

  14. COMPUTATION OF THE PDF’s

  15. COMPUTATION OF THE PDF’s

  16. COMPUTATION OF THE PDF’s

  17. COMPUTATION OF THE PDF’s

  18. DISSIMILARITY MATRIX

  19. Exploring the European Climate Assessment dataset

  20. Exploring the European Climate Assessment dataset

  21. TEMPERATURES

  22. RESULTS

  23. RESULTS

  24. DENDROGRAM FOR 25-YEARS RETURN VALUES (AVERAGE LINKAGE METHODS)

  25. CONCLUSIONS

  26. REFERENCES

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