1. STARDEX STAtistical and Regional dynamical Downscaling of EXtremes for European regions
A project within the EC 5th Framework Programme
EVK2-CT
1 February 2002 to 31 July 2005
Co-ordinator: Dr Clare Goodess
Climatic Research Unit, UK

2. The STARDEX consortium

3. STARDEX general objectives
To rigorously & systematically inter-compare & evaluate statistical, dynamical & statistical-dynamical downscaling methods for the reconstruction of observed extremes & the construction of scenarios of extremes for selected European regions
To identify the more robust downscaling techniques & to apply them to provide reliable & plausible future scenarios of temperature & precipitation-based extremes for selected European regions

4. STARDEX regional case studies
The Mediterranean (Iberia & Greece)
Scandinavia
British Isles
Germany
The Alps
Europe ( stations)

5. STARDEX WP1: Data set development, co-ordination & dissemination

6. STARDEX WP1 deliverables
Public & members’ web sites
Standard data sets of:
station temperature/precipitation data
NCEP reanalysis data
Objective circulation patterns & indices
GCM & RCM data
damages arising from extreme events
Statistical diagnostic software tool
Final project report (July 2005)

7. STARDEX Diagnostic extremes indices software
Based on NCDC ClimateIndices/ECA code
Fortran subroutine:
19 temperature indices
e.g. 10/90th percentiles, growing degree days, frost days
35 precipitation indices
e.g. 20/40/50/60/80/90/95th percentiles, wet/dry spells
least squares linear regression to fit linear trends & Kendall-Tau significance test
Program that uses subroutine to process standard format station data
User information document

8. STARDEX core indices 90th percentile of rainday amounts (mm/day)
greatest 5-day total rainfall
simple daily intensity (rain per rainday)
max no. consecutive dry days
% of total rainfall from events > long-term P90
no. events > long-term 90th percentile of raindays
Tmax 90th percentile
Tmin 10th percentile
number of frost days Tmin < 0 degC
heat wave duration

9. STARDEX WP2: Observational analysis of changes in extremes, their causes & impacts
To analyse observed station/regional data series for the 2nd half of the 20th century from specific regions of Europe in order to identify trends in the magnitude/frequency of occurrence of extremes &, for specific events, their losses in life and financial costs
To investigate whether these changes are related to changes in potential predictor variables

10. trend in frost days
1.1 days/yr

11. 1958-2000 trend in heavy rain days
0.25 days/yr

12. Severe winter storms across Germany and Europe,
economic losses and causing circulation types
© Caspary

13. 11-year running average for the circulation type "West cyclonic"
11-year running average for the circulation type "West cyclonic" (Wz) for winter (Dec. - Feb.) for the period Black line: frequency (%), blue line: maximum persistence of Wz-periods (days).
© Caspary

14. STARDEX WP2 deliverables
Summary of the analysis of observed extremes, their causes & damages (February 2003)
Recommendations on the best predictor variables for extreme events (March 2003)

15. STARDEX WP3: Analysis of GCM/RCM output & their ability to simulate extremes and predictor variables
GCMs:
HadAM3H (1.25°x1.875°) 150 km
ECHAM4.5? (T106)
RCMs:
50 km RCMs
several models: HadRM, HIRHAM, CHRM, ...
for all study regions.
14 km RCM for some of the study regions

16. Heavy Alpine precipitation, 90% Quantile, Sept.-Nov.
Observations
CHRM (ERA-driven)
HadRM3 (GCM-driven 60-90)
HadRM3 (ERA-driven)
Figure provided by Christoph Frei

17. Daily rainfall SE England 1961-90
ewrain/badc: observed, HadRM3: simulated
ewrain: averages of 7 stations Regional: averages of 31 stations/12 grid points Multi: separate analysis of 31 stations/12 grid points, then averaged Scaled: upscaled to HadRM3 grid points (Osborn & Hulme)

18. STARDEX WP3 deliverables
Recommendations on variables & extremes for which downscaling is required (March 2003?)
Recommendations on the most reliable predictor variables & evaluation of inter-relationships (January 2004)

19. STARDEX WP4: Inter-comparison of improved downscaling methods with emphasis on extremes
To improve existing circulation-based statistical downscaling methods:
to reproduce observed extremes
to incorporate additional predictors (stationarity)
To calibrate/validate improved methods using predictor variables from (a) Reanalysis data, & (b) GCM output
To compare results with output from RCMs
To identify the more robust downscaling methods

20. Radial Basis Function daily precipitation downscaling - Rob Wilby, KCL
Maximum number of consecutive dry days
NW England regional precipitation
Calibration: / Validation:

21. WP5: Application of the more robust downscaling techniques to provide scenarios of extremes for European regions for the end of the 21st century
To use these scenarios to identify changes in extremes
To investigate whether these changes are in accordance with recent observed changes
To consider their potential impacts in terms of losses of life & financial costs
To assess the uncertainties associated with the scenarios

22. Co-ordinator: Dr Clare Goodess Climatic Research Unit, UK
STARDEX STAtistical and Regional dynamical Downscaling of EXtremes for European regions
Co-ordinator: Dr Clare Goodess
Climatic Research Unit, UK