Statistical Downscaling and Bias Correction for Climate Research

Douglas Maraun is an associate professor and Head of the Regional Climate Modelling Group at the Wegener Center for Climate and Global Change at the Karl-Franzens-Universität Graz, Austria. His research interests include the processes governing local extreme events, assessing uncertainties of regional climate projections, and statistical post-processing of climate simulations for adaptation planning. He chaired the VALUE network which carried out the most comprehensive inter-comparison and evaluation of different downscaling approaches, and is involved in steering activities of the international downscaling initiative CORDEX. Martin Widmann is a senior lecturer and climate scientist in the School of Geography, Earth and Environmental Sciences at the University of Birmingham. His current main research area is regional climate change, in particular the development and validation of statistical downscaling methods. He was one of the first to apply bias correction in a climate change context, and recently co-chaired the VALUE network. His other field of research is past climates, in particular the development of data assimilation methods to combine climate simulations with empirical knowledge from proxy data.

• Preface; Acknowledgements; 1. Introduction; Part I. Background and Fundamentals: 2. Regional climate; 3. History of downscaling; 4. Rationale of downscaling; 5. User needs; 6. Mathematical and statistical methods; 7. Reference observations; 8. Climate modelling; 9. Uncertainties; Part II. Statistical Downscaling Concepts and Methods: 10. Structure of statistical downscaling methods; 11. Perfect prognosis; 12. Model output statistics; 13. Weather generators; 14. Other approaches; Part III. Downscaling in Practice and Outlook: 15. Evaluation; 16. Performance of statistical downscaling; 17. A regional modelling debate; 18. Use of downscaling in practice; 19. Outlook; Appendix A. Methods used in this book; Appendix B. Useful resources; References; Index.

'This book provides an invaluable reference for anyone involved in developing or using local and regional projections to quantify climate change impacts. As climate model output becomes increasingly accessible and open source code for downscaling is shared by the research community, the selection of methods and data to use for a local climate impacts analysis becomes more complex. This reference provides comprehensive guidance for those developing improved downscaling approaches, applying existing methods, or using data generated by others. The authors keep a clear focus on quantifying the uncertainties involved in each step of a downscaling process, and highlighting opportunities to ultimately produce more skilful information for decision-makers challenged with responding to climate change impacts.' Ed Maurer, Santa Clara University, California