STARDEX STAtistical and Regional dynamical Downscaling of EXtremes for European regions A project within the EC 5th Framework Programme EVK2-CT-2001-00115 1 February 2002 to 31 July 2005 Co-ordinator: Dr Clare Goodess Climatic Research Unit, UK c.goodess@uea.ac.uk http://www.cru.uea.ac.uk/projects/stardex/ http://www.cru.uea.ac.uk/projects/mps/

The STARDEX consortium

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

STARDEX regional case studies The Mediterranean (Iberia & Greece) Scandinavia British Isles Germany The Alps Europe (400-500 stations)

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

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)

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

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

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

1958-2000 trend in frost days 1.1 days/yr

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

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

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 1881- 2002. Black line: frequency (%), blue line: maximum persistence of Wz-periods (days). © Caspary

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)

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

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

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)

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)

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

Radial Basis Function daily precipitation downscaling - Rob Wilby, KCL Maximum number of consecutive dry days NW England regional precipitation Calibration: 1961-1980/ Validation: 1981-2000

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

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 c.goodess@uea.ac.uk http://www.cru.uea.ac.uk/projects/stardex/ http://www.cru.uea.ac.uk/projects/mps/