Over the last two decades the complex network paradigm has proven to be a fruitful tool for the investigation of complex systems in many areas of science; for example, the Internet, neural networks and social networks. This book provides an overview of applications of network theory to climate variability, such as the El Niño/Southern Oscillation and the Indian Monsoon, presenting recent important results obtained with these techniques and showing their potential for further development and research. The book is aimed at researchers and graduate students in climate science. A basic background in physics and mathematics is required. Several of the methodologies presented here will also be valuable to a broader audience of those interested in network science, for example, from biomedicine, ecology and economics.

This book examines how interactions between organizations within the international climate change movement shape tactics and outcomes in climate change negotiations.

An overview of the forms of agency in urban climate politics, including their strengths, limitations and the power dynamics between them. Written by renowned scholars from around the globe, it is ideal for researchers and practitioners working in the area of urban climate politics and governance.

Published by the American Geophysical Union as part of the Geophysical Monograph Series, Volume 196. Extreme Events and Natural Hazards: The Complexity Perspective examines recent developments in complexity science that provide a new approach to understanding extreme events. This understanding is critical to the development of strategies for the prediction of natural hazards and mitigation of their adverse consequences. The volume is a comprehensive collection of current developments in the understanding of extreme events. The following critical areas are highlighted: understanding extreme events, natural hazard prediction and development of mitigation strategies, recent developments in complexity science, global change and how it relates to extreme events, and policy sciences and perspective. With its overarching theme, Extreme Events and Natural Hazards will be of interest and relevance to scientists interested in nonlinear geophysics, natural hazards, atmospheric science, hydrology, oceanography, tectonics, and space weather.

Climate change mechanisms, impacts, risks, mitigation, adaption, and governance are widely recognized as the biggest, most interconnected problem facing humanity. Big Data Mining for Climate Change addresses one of the fundamental issues facing scientists of climate or the environment: how to manage the vast amount of information available and analyse it. The resulting integrated and interdisciplinary big data mining approaches are emerging, partially with the help of the United Nation's big data climate challenge, some of which are recommended widely as new approaches for climate change research. Big Data Mining for Climate Change delivers a rich understanding of climate-related big data techniques and highlights how to navigate huge amount of climate data and resources available using big data applications. It guides future directions and will boom big-data-driven researches on modeling, diagnosing and predicting climate change and mitigating related impacts. This book mainly focuses on climate network models, deep learning techniques for climate dynamics, automated feature extraction of climate variability, and sparsification of big climate data. It also includes a revelatory exploration of big-data-driven low-carbon economy and management. Its content provides cutting-edge knowledge for scientists and advanced students studying climate change from various disciplines, including atmospheric, oceanic and environmental sciences; geography, ecology, energy, economics, management, engineering, and public policy.

Climate Change and Cities bridges science-to-action for climate change adaptation and mitigation efforts in cities around the world.

Detailed weather observations on local and regional levels are essential to a range of needs from forecasting tornadoes to making decisions that affect energy security, public health and safety, transportation, agriculture and all of our economic interests. As technological capabilities have become increasingly affordable, businesses, state and local governments, and individual weather enthusiasts have set up observing systems throughout the United States. However, because there is no national network tying many of these systems together, data collection methods are inconsistent and public accessibility is limited. This book identifies short-term and long-term goals for federal government sponsors and other public and private partners in establishing a coordinated nationwide "network of networks" of weather and climate observations.

This book presents innovative work in Climate Informatics, a new field that reflects the application of data mining methods to climate science, and shows where this new and fast growing field is headed. Given its interdisciplinary nature, Climate Informatics offers insights, tools and methods that are increasingly needed in order to understand the climate system, an aspect which in turn has become crucial because of the threat of climate change. There has been a veritable explosion in the amount of data produced by satellites, environmental sensors and climate models that monitor, measure and forecast the earth system. In order to meaningfully pursue knowledge discovery on the basis of such voluminous and diverse datasets, it is necessary to apply machine learning methods, and Climate Informatics lies at the intersection of machine learning and climate science. This book grew out of the fourth workshop on Climate Informatics held in Boulder, Colorado in Sep. 2014.

It is now widely recognized that the climate system is governed by nonlinear, multi-scale processes, whereby memory effects and stochastic forcing by fast processes, such as weather and convective systems, can induce regime behavior. Motivated by present difficulties in understanding the climate system and to aid the improvement of numerical weather and climate models, this book gathers contributions from mathematics, physics and climate science to highlight the latest developments and current research questions in nonlinear and stochastic climate dynamics. Leading researchers discuss some of the most challenging and exciting areas of research in the mathematical geosciences, such as the theory of tipping points and of extreme events including spatial extremes, climate networks, data assimilation and dynamical systems. This book provides graduate students and researchers with a broad overview of the physical climate system and introduces powerful data analysis and modeling methods for climate scientists and applied mathematicians.

The Urban Climate Change Research Network's Second Assessment Report on Climate Change in Cities (ARC3.2) is the second in a series of global, science-based reports to examine climate risk, adaptation, and mitigation efforts in cities. The book explicitly seeks to explore the implications of changing climatic conditions on critical urban physical and social infrastructure sectors and intersectoral concerns. The primary purpose of ARC3.2 is to inform the development and implementation of effective urban climate change policies, leveraging ongoing and planned investments for populations in cities of developing, emerging, and developed countries. This volume, like its predecessor, will be invaluable for a range of audiences involved with climate change and cities: mayors, city officials and policymakers; urban planners; policymakers charged with developing climate change mitigation and adaptation programs; and a broad spectrum of researchers and advanced students in the environmental sciences.