1. Global/European Analysis of Extremes - recent trends - Albert Klein Tank KNMI, the Netherlands 11 June 2002 acknowledgements: Lisa Alexander (Met Office, UK) Janet Wijngaard, Aryan van Engelen & Günther Können (KNMI) 36 ECA-participants (Europe & Middle East)

2. European Study: http://www.knmi.nl /samenw/eca

4. What types of extremes? Trends in extreme events characterised by the size of their societal or economic impacts Trends in “very rare” extreme events analysed by the parameters of extreme value distributions Trends in observational series of phenomena with a daily time scale and typical return period < 1 year (as indicators of extremes) NO YES

6. Approach Focus on counts of days crossing a threshold; either absolute/fixed thresholds or percentile/variable thresholds relative to local climate Using derived climate indices as proposed by the joint CCL/CLIVAR Working Group on Climate Change Detection (Peterson et al., WMO-TD No. 1071, 2001) Standardisation enables comparisons between results obtained in different parts of the world (e.g. Frich et al., Clim. Res. 2002; also in IPCC-TAR)

7. Motivation for choice of “extremes” The detection probability of trends depends on the return period of the extreme event and the length of the observational series For extremes in daily series with typical length ~50 yrs, the optimal return period is 10-30 days rather than 10-30 years

8. example: 80% detection prob. (5%-level) (see also: Frei & Schär, J.Climate, 2001) N T

9. Temperature indices I Example of “frost days” as an extreme index based on an absolute temperature threshold

10. Frich et al. (Clim.Res., 2002) in IPCC-TAR

11. Temperature indices II Example of “warm nights” as an extreme index based on counts of events over a (seasonally varying) percentile threshold

12. After: Jones et al. (Climatic Change, 1999) Yan et al. (…, 2002, IMPROVE- issue) “warm nights” upper 10-ptile 1961-1990 the year 1996 lower 10-ptile 1961-1990

13. Frich et al. (Clim.Res., 2002)

14. Kiktev et al. (J. Climate, submitted) HadAM3 atmosphere only GCM- simulation “warm nights”

15. IPCC-TAR (Ch.2, Folland and Karl)

16. Europe-average trends (86 ECA-stations)

19. Precipitation indices I

20. Easterling et al. (BAMS, 2000) in IPCC-TAR see also Groisman et al. (Clim.Change, 1999) Linear trends in rainy season over ~50 years

21. Precipitation indices II Example of “R95%tot” extreme index for the precipitation fraction due to very wet days

22. Precipitation fraction due to very wet days “R95%tot” 1) Identify very wet days using a site specific threshold = 95th percentile at wet days in the 1961-90 period 2) Determine fraction of total precipitation in each year that is due to these days 3) Trend analysis in series of fractions

23. Annual amount “R95%tot”

25. Frich et al. (Clim.Res., 2002) in IPCC-TAR

26. IPCC-TAR conclusions Temperature extremes “lengthening of the freeze-free season in most mid- and high latitude regions” “reduction in frequency of extreme low monthly and seasonal average temperatures and smaller increase in frequency of extreme high average temperatures” Precipitation extremes “in regions where total precipitation has increased... even more pronounced increases in heavy precipitation events” “2 to 4% increase in frequency of heavy events in mid- and high latitudes of the NH”

27. Key-issues to be discussed I Are good quality observational series available with daily resolution and adequate data coverage? Is there a need for improved methods of homogeneity testing and gridding the daily series? Can trend analysis of extremes in daily series go beyond phenomena that occur on average ~10 times per year? Can trend analysis of extremes do without standardised indices if we want a global picture of changes? YES, but possibly NO

28. Key-issues to be discussed II Are the standardised simple indices adequate for: - improving our understanding of the physical mechanisms behind changes in extremes? - evaluating the capacity of climate models to reproduce occurrences of extremes? - constructing scenarios of future occurrences of extremes for impact assessment? Do we communicate the results of extremes analysis in such a way that they can be used for climate change detection/attribution and impact analysis? ???

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