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.
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.
Using R for Data Analysis in Social Sciences
Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage, visualize, and analyze data. The focus is on how to address substantive questions with data analysis and replicate...
GARCH Models: Structure, Statistical Inference and Financial Applications
Provides a comprehensive and updated study of GARCH models and their applications in finance, covering new developments in the discipline
This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results...
Computer Graphics Through OpenGL®: From Theory to Experiments
COMPREHENSIVE COVERAGE OF SHADERS AND THE PROGRAMMABLE PIPELINE
From geometric primitives to animation to 3D modeling to lighting, shading and texturing, Computer Graphics Through OpenGL®: From Theory to Experiments is a comprehensive introduction to computer graphics which uses an active...
Artificial Intelligence in Health: First International Workshop, AIH 2018, Stockholm, Sweden, July 13-14, 2018, Revised Selected Papers (Lecture Notes in Computer Science (11326))
This book constitutes the refereed post-conference proceedings of the First International Workshop on Artificial Intelligence in Health, AIH 2018, in Stockholm, Sweden, in July 2018. This workshop consolidated the workshops CARE, KRH4C and AI4HC into a single event.
The 18 revised full papers included in this...
Maoism: A Global History
*** WINNER OF THE 2019 CUNDILL HISTORY PRIZE
SHORTLISTED FOR THE BAILLIE GIFFORD PRIZE FOR NON-FICTION 2019
SHORTLISTED FOR THE NAYEF AL-RODHAN PRIZE FOR GLOBAL UNDERSTANDING
SHORTLISTED FOR DEUTSCHER PRIZE
LONGLISTED FOR THE 2020 ORWELL PRIZE FOR POLITICAL WRITING***... Air Pollution: Sources, Impacts and Controls
The problem of air pollution has become a global issue, driven by rapid economic growth, industrialization, and urbanization. Pollutants directly emitted into the atmosphere include nitrogen oxides, carbon monoxide, sulphur oxides, particulate matter (PM), volatile organic compounds, carbonaceous particles, dust, and sea-salt. Secondary...