Statistical Downscaling for Hydrological and Environmental Applications

Statistical Downscaling for Hydrological and Environmental Applications
Author :
Publisher : CRC Press
Total Pages : 165
Release :
ISBN-10 : 9780429861154
ISBN-13 : 042986115X
Rating : 4/5 (15X Downloads)

Book Synopsis Statistical Downscaling for Hydrological and Environmental Applications by : Taesam Lee

Download or read book Statistical Downscaling for Hydrological and Environmental Applications written by Taesam Lee and published by CRC Press. This book was released on 2018-09-03 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global climate change is typically understood and modeled using global climate models (GCMs), but the outputs of these models in terms of hydrological variables are only available on coarse or large spatial and time scales, while finer spatial and temporal resolutions are needed to reliably assess the hydro-environmental impacts of climate change. To reliably obtain the required resolutions of hydrological variables, statistical downscaling is typically employed. Statistical Downscaling for Hydrological and Environmental Applications presents statistical downscaling techniques in a practical manner so that both students and practitioners can readily utilize them. Numerous methods are presented, and all are illustrated with practical examples. The book is written so that no prior background in statistics is needed, and it will be useful to graduate students, college faculty, and researchers in hydrology, hydroclimatology, agricultural and environmental sciences, and watershed management. It will also be of interest to environmental policymakers at the local, state, and national levels, as well as readers interested in climate change and its related hydrologic impacts. Features: Examines how to model hydrological events such as extreme rainfall, floods, and droughts at the local, watershed level. Explains how to properly correct for significant biases with the observational data normally found in current Global Climate Models (GCMs). Presents temporal downscaling from daily to hourly with a nonparametric approach. Discusses the myriad effects of climate change on hydrological processes.


Statistical Downscaling for Hydrological and Environmental Applications Related Books

Statistical Downscaling for Hydrological and Environmental Applications
Language: en
Pages: 165
Authors: Taesam Lee
Categories: Science
Type: BOOK - Published: 2018-09-03 - Publisher: CRC Press

DOWNLOAD EBOOK

Global climate change is typically understood and modeled using global climate models (GCMs), but the outputs of these models in terms of hydrological variables
Statistical Downscaling for Hydrological and Environmental Applications
Language: en
Pages: 195
Authors: Taesam Lee
Categories: Science
Type: BOOK - Published: 2018-09-03 - Publisher: CRC Press

DOWNLOAD EBOOK

Global climate change is typically understood and modeled using global climate models (GCMs), but the outputs of these models in terms of hydrological variables
Statistical Downscaling and Bias Correction for Climate Research
Language: en
Pages: 365
Authors: Douglas Maraun
Categories: Mathematics
Type: BOOK - Published: 2018-01-18 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

A comprehensive and practical guide, providing technical background and user context for researchers, graduate students, practitioners and decision makers. This
Empirical-statistical Downscaling
Language: en
Pages: 228
Authors: Rasmus E. Benestad
Categories: Science
Type: BOOK - Published: 2008 - Publisher: World Scientific

DOWNLOAD EBOOK

Empirical-statistical downscaling (ESD) is a method for estimating how local climatic variables are affected by large-scale climatic conditions. ESD has been ap
Downscaling Techniques for High-Resolution Climate Projections
Language: en
Pages: 213
Authors: Rao Kotamarthi
Categories: Science
Type: BOOK - Published: 2021-02-11 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

Downscaling is a widely used technique for translating information from large-scale climate models to the spatial and temporal scales needed to assess local and