|Statistical and Regional dynamical Downscaling of Extremes for European regions (STARDEX)|
|Projektleiter:||Prof. Dr. rer.nat. Dr.-Ing. András Bárdossy|
|Wissenschaftliche Mitarbeiter:||Dr.-Ing. Yeshewatesfa Hundecha, M.Sc.|
|Projektdauer:||1.2.2002 - 31.7.2005|
The European Commission, Programme "Energy, Environment and Sustainable Development"|
|Projektpartner:||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), University of Bologna (Italy), Danish Meteorological Institute (Denmark), Eidgenössische Technische Hochschule (Switzerland), Fachhochschule Stuttgart - Hochschule für Technik (Germany), University of Stuttgart (Germany), University of Thessaloniki (Greece)|
Zusammenfassung:Changes in the frequency and intensity of extreme events are likely to have more of an impact on the environment and human activities than changes in mean climate. Losses of life and very high economic damages have, for example, been experienced during recent flooding events in Italy, Switzerland, France, the UK and across central Europe. The severe heatwaves which have occurred in the eastern Mediterranean in recent summers illustrate the risks to human health from short-duration temperature extremes. A vital question for Europe is, therefore, whether such events will occur more frequently in the future. For many socio-economic and environmental sectors in Europe there is a clear need for more reliable, high-resolution scenarios of extremes.
In order to address the above problem, the project aims at rigorously and systematically inter-comparing and evaluating statistical, dynamical and statistical-dynamical downscaling methods for the reconstruction of observed extremes and the construction of scenarios of extremes for selected European regions. Based on this evaluation, the more robust downscaling techniques will be identified and be applied to provide reliable and plausible future scenarios of temperature and precipitation-based extremes for selected European regions.