Statistical Downscaling and Bias Correction for Climate Research

Statistical downscaling and bias correction are becoming standard tools in climate impact studies. This book provides a comprehensive reference to widely-used approaches, and additionally covers the relevant user context and technical background, as well as a synthesis and guidelines for practitioners. It presents the main approaches including statistical downscaling, bias correction and weather generators, along with their underlying assumptions, skill and limitations. Relevant background information on user needs and observational and climate model uncertainties is complemented by concise introductions to the most important concepts in statistical and dynamical modelling. A substantial part is dedicated to the evaluation of regional climate projections and their value in different user contexts. Detailed guidelines for the application of downscaling and the use of downscaled information in practice complete the volume. Its modular approach makes the book accessible for developers and practitioners, graduate students and experienced researchers, as well as impact modellers and decision makers.

Table of Contents:
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.

About the Author :
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.

Review :
'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 'A large variety of statistical downscaling and bias correction methods are used for connecting climate change with impact assessments. The new book by D. Maraun and M. Widmann provides a very useful overview of the methods and topics involved and gives guidance for future users. The demand for downscaled information is rapidly growing and this book helps with understanding assets and drawbacks.' Daniela Jacob, Climate Service Center Germany (GERICS), Hamburg