VALUE: A framework to validate downscaling approaches for climate change studies. Issue 1 (7th January 2015)

• Record Type: Journal Article
• Authors: Maraun, Douglas; Widmann, Martin; Gutiérrez, José M.; Kotlarski, Sven; Chandler, Richard E.; Hertig, Elke; Wibig, Joanna; Huth, Radan; Wilcke, Renate A.I.
• Is Part Of: Earth's future. Volume 3:Issue 1(2015)
• Page Start: 1
• Page End: 14
• Publication Date: 2015-01-07
• Subjects: Downscaling -- Validation -- Regional Climate Modelling -- Statistical Downscaling -- Dynamical Downscaling -- Bias Correction; Environmental sciences -- Periodicals; Environmental sciences; Periodicals; 550
• DOI: 10.1002/2014EF000259
• Languages: English
• ISSNs: 2328-4277

Abstract

Abstract: VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. In this paper, we present the key ingredients of this framework. VALUE's main approach to validation is user‐ focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community‐open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies. Key Points: VALUE has developed a framework to validate and compare downscaling methods The experiments comprise different observed and pseudo‐reality reference data The framework is the basis for a comprehensive downscaling comparison study