Introducing STARDEX: STAtistical and Regional dynamical Downscaling of EXtremes for European regions Clare Goodess* & the STARDEX team *Climatic Research Unit, UEA, Norwich, UK February 2002 to July 2005 http://www.cru.uea.ac.uk/projects/stardex COP10, 13 December 2004
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Introducing STARDEX: STAtistical and Regional dynamical Downscaling of EXtremes for European regions Clare Goodess* & the STARDEX team *Climatic Research.
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Introducing STARDEX:STAtistical and Regional dynamical
Downscaling of EXtremes for European regions
Clare Goodess* & the STARDEX team*Climatic Research Unit, UEA, Norwich, UK
The STARDEX team• University of East Anglia, UK • King's College London, UK• Fundación para la Investigación del Clima, Spain • University of Bern, Switzerland • Centre National de la Recherche Scientifique, France• Servizio Meteorologico Regional, ARPA-Emilia Romagna, Italy• Atmospheric dynamics group, University of Bologna, Italy• Danish Meteorological Institute, Denmark • Eidgenössische Technische Hochschule, Switzerland• Fachhochschule Stuttgart - Hochschule für Technik, Germany• Institut für Wasserbau, Germany• University of Thessaloniki, Greece
• PRUDENCE focuses on dynamical downscaling
• STARDEX is evaluating an alternative, complementary approach to providing high-resolution information: statistical downscaling (SDS)
• This approach has some advantages:– Provides station/point values– Less computer intensive than dynamical downscaling
• STARDEX is performing a rigorous and systematic inter-comparison and evaluation of SDS methods and comparison with dynamical downscaling
STARDEX is focusing on temperature & rainfall extremes:
• 10 core indices covering frequency, magnitude and persistence (the STARDEX software package calculates 57 indices in total)
• The more robust SDS methods will be used to construct scenarios of extremes for end of 21st century for 6 regions & Europe as a whole
The underlying principles of SDS:
• Observed relationships between the local surface climate and larger-scale climate (e.g., circulation patterns, atmospheric humidity) are established…
• And applied to GCM output for the future…
• On the assumption that these relationships will be unchanged in the future….
• And that the larger-scale climate is better simulated by GCMs than local climate
Greenland Anticyclone Sole Cyclone
1971-1983 (left) & 1983-1995 (right)
Examples of strong relationships between intense rainfall and
circulation established by STARDEX:
Guy Plaut, CNRS-INLN András Bárdossy, USTUTT-IWS
French Alpes Maritime German Rhine (winter)
Circulation pattern optimisation technique - CP02
So STARDEX has done a lot of work analysing observed data:
• Including a unique data set of daily station records for ~500 European stations - indices available from http://www.cru.uea.ac.uk/projects/stardex
• And denser station networks for 6 regions: Iberia, Greece, UK, German Rhine, Alps, northern Italy
1958-2000 trend in DJF frost days
Scale is days per year. Red is decreasing
AthensAthensFebruary 2004February 2004
Malcolm Haylock, UEA
1958-2000 trend in JJA heat wave duration
Scale is days per year. Red is increasing Malcolm Haylock, UEA
Property damage: US$ 13 bnProperty damage: US$ 13 bnFatalities: 27,000 (14,800 in France)Fatalities: 27,000 (14,800 in France)
Western EuropeWestern EuropeAugust 2003August 2003
1958-2000 trend in JJA heavy rain events
Scale is days per year. Blue is increasing
Central and Eastern EuropeCentral and Eastern EuropeAugust 2002August 2002