Statistical Downscaling and Bias Correction for Climate Research

Nonfiction, Science & Nature, Science, Other Sciences, Meteorology, Mathematics
Cover of the book Statistical Downscaling and Bias Correction for Climate Research by Douglas Maraun, Martin Widmann, Cambridge University Press
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Author: Douglas Maraun, Martin Widmann ISBN: 9781108340304
Publisher: Cambridge University Press Publication: January 18, 2018
Imprint: Cambridge University Press Language: English
Author: Douglas Maraun, Martin Widmann
ISBN: 9781108340304
Publisher: Cambridge University Press
Publication: January 18, 2018
Imprint: Cambridge University Press
Language: English

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.

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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.

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