Recent Developments in Statistical Downscaling of Extremes
Abstract:Based on the output of general circulation models (GCMs) regionalization techniques are usually applied to obtain fine-scale climate change information. Different types of regionalization techniques have been developed which comprise regional climate models and statistical downscaling approaches such as conditional weather generators, artificial neural networks, synoptic studies, and transfer functions.
In the scope of climate variability and climate change the variations and changes of extremes are of special importance. Extreme events are not only of scientific interest but also have a profound impact on society. For the statistical downscaling of extremes, promising approaches have been introduced and/or developed further in the last few years.
Aspects of recent developments in the scope of statistical downscaling of extremes will be presented. In this context, various approaches to downscale extremes, particularly those associated with extreme precipitation events, will be discussed. Key problems related to statistical downscaling of extremes will be addressed. Furthermore, information on Working Group 4 "Extremes" of the EU COST action VALUE (www.value-cost.eu) will be provided. VALUE systematically validates and develops downscaling methods for climate change research in order to improve regional climate change scenarios for use in climate impact studies.