Statistical Downscaling and Bias Correction for Climate Research

Author:   Douglas Maraun (Karl-Franzens-Universität Graz, Austria) ,  Martin Widmann (University of Birmingham)
Publisher:   Cambridge University Press
ISBN:  

9781107066052


Pages:   360
Publication Date:   18 January 2018
Format:   Hardback
Availability:   In stock   Availability explained
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Statistical Downscaling and Bias Correction for Climate Research


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Author:   Douglas Maraun (Karl-Franzens-Universität Graz, Austria) ,  Martin Widmann (University of Birmingham)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press
Dimensions:   Width: 17.80cm , Height: 2.10cm , Length: 25.30cm
Weight:   0.880kg
ISBN:  

9781107066052


ISBN 10:   1107066050
Pages:   360
Publication Date:   18 January 2018
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In stock   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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Reviews

'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 `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


'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


Author Information

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.

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