1. European Climate Assessment & Dataset
Judging homogeneity of daily series
Fourth seminar for homogenization
Budapest, 6-10 October 2003
Janet Wijngaard, KNMI, the Netherlands

2. Topics
ECA&D project
Approach to homogeneity
Results, Conclusions

3. ECA&D project data analysis focusing on observed changes in extremes
gather daily series of observations at meteorological stations in
Europe and the Middle East
quality control and homogeneity analysis of the series
dissemination of data and analyses results

4. Current participation
Most data from 1900 up to 2001
More than 200 stations
Tmin, Tmax, Tmean,
precipitation amount, pressure
Success is afhankelijk van deelname van de participanten!

5. Trend analysis of extremes requires:
A dense, high-resolution, accurate and consistent dataset

6. Method Homogenization of daily series Instead: labelling of series
-> confidence for trend and variability analysis

7. Two-step approach
Four homogeneity tests applied to ECA dataset to identify potential inhomogeneities in annual resolution testing variables representative for the daily resolution
Grouping of results -> overall classification

8. Homogeneity tests and variables
Tests (absolute):
SNHT
Buishand Range
Pettitt
Von Neumann Ratio
 Variables:
precipitation: number of wet days
temperature: mDTR and vDTR (annual mean of absolute day-to-day
differences of DTR)

9. vDTR DTRi: Diurnal temperature Range for day i in a specific year
M: number of days in the year

10. Classification Labels: Useful (0/1 tests significant)
Doubtful (2 tests significant)
Suspect (3/4 tests significant)

11. Station Groningen (NL)
1948: change of observation hut
1951: relocation
1959: change in sensor height

12. Station Groningen (NL)
Buishand Range, Pettitt and Von Neumann significant -> ‘suspect’

13. Temperature
mDTR
vDTR
->54% ‘suspect’, breaks (partly) supported by metadata

14. Precipitation 1946-1999 Paper: International Journal of Climatology,
Number of wet days
Paper: International Journal of Climatology,
May, 2003
-> 10% ‘suspect’

15. Conclusions most severe step-wise breaks are detected
most severe step-wise breaks are detected
metadata support for detected breaks essential
no homogenizing of daily series
labelling system good basis for series selection in trend analysis

16. And… further investigations to test homogeneity on daily basis
further investigations to test homogeneity on daily basis
MASH method used for homogenization on monthly ECA&D series

17. More info at: http://www.knmi.nl/samenw/eca