Nonlinear and Stochastic Climate Dynamics

Nonlinear and Stochastic Climate Dynamics

Author: Christian L. E. Franzke

Publisher: Cambridge University Press

Published: 2017-01-19

Total Pages: 612

ISBN-13: 1316883213

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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.


Stochastic Climate Theory

Stochastic Climate Theory

Author: Serguei G. Dobrovolski

Publisher: Springer Science & Business Media

Published: 2013-11-11

Total Pages: 290

ISBN-13: 3662041197

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The author describes the stochastic (probabilistic) approach to the study of changes in the climate system. Climatic data and theoretical considerations suggest that a large part of climatic variation/variability has a random nature and can be analyzed using the theory of stochastic processes. This work summarizes the results of processing existing records of climatic parameters as well as appropriate theories: from the theory of random processes (based on the results of Kolmogorov and Yaglom) and Hasselmann's "stochastic climate model theory" to recently obtained results.


Stochastic Climate Models

Stochastic Climate Models

Author: Peter Imkeller

Publisher: Birkhäuser

Published: 2012-12-06

Total Pages: 413

ISBN-13: 3034882874

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A collection of articles written by mathematicians and physicists, designed to describe the state of the art in climate models with stochastic input. Mathematicians will benefit from a survey of simple models, while physicists will encounter mathematically relevant techniques at work.


Nonlinear Climate Dynamics

Nonlinear Climate Dynamics

Author: Henk A. Dijkstra

Publisher: Cambridge University Press

Published: 2013-06-17

Total Pages: 371

ISBN-13: 1107244374

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This book introduces stochastic dynamical systems theory in order to synthesize our current knowledge of climate variability. Nonlinear processes, such as advection, radiation and turbulent mixing, play a central role in climate variability. These processes can give rise to transition phenomena, associated with tipping or bifurcation points, once external conditions are changed. The theory of dynamical systems provides a systematic way to study these transition phenomena. Its stochastic extension also forms the basis of modern (nonlinear) data analysis techniques, predictability studies and data assimilation methods. Early chapters apply the stochastic dynamical systems framework to a hierarchy of climate models to synthesize current knowledge of climate variability. Later chapters analyse phenomena such as the North Atlantic Oscillation, El Niño/Southern Oscillation, Atlantic Multidecadal Variability, Dansgaard–Oeschger events, Pleistocene ice ages and climate predictability. This book will prove invaluable for graduate students and researchers in climate dynamics, physical oceanography, meteorology and paleoclimatology.


Stochastic Modeling and the Theory of Queues

Stochastic Modeling and the Theory of Queues

Author: Ronald W. Wolff

Publisher: Pearson

Published: 1989

Total Pages: 580

ISBN-13:

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An integrated and up-to-date treatment of applied stochastic processes and queueing theory, with an emphasis on time-averages and long-run behavior. Theory demonstrates practical effects, such as priorities, pooling of queues, and bottlenecks. Appropriate for senior/graduate courses in queueing theory in Operations Research, Computer Science, Statistics, or Industrial Engineering departments. (vs. Ross, Karlin, Kleinrock, Heyman)


Foundations of Stochastic Inventory Theory

Foundations of Stochastic Inventory Theory

Author: Evan L. Porteus

Publisher: Stanford University Press

Published: 2002

Total Pages: 330

ISBN-13: 9780804743990

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This book has a dual purpose?serving as an advanced textbook designed to prepare doctoral students to do research on the mathematical foundations of inventory theory, and as a reference work for those already engaged in such research. All chapters conclude with exercises that either solidify or extend the concepts introduced.


Theory and Applications of Stochastic Processes

Theory and Applications of Stochastic Processes

Author: Zeev Schuss

Publisher: Springer Science & Business Media

Published: 2009-12-09

Total Pages: 486

ISBN-13: 1441916059

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Stochastic processes and diffusion theory are the mathematical underpinnings of many scientific disciplines, including statistical physics, physical chemistry, molecular biophysics, communications theory and many more. Many books, reviews and research articles have been published on this topic, from the purely mathematical to the most practical. This book offers an analytical approach to stochastic processes that are most common in the physical and life sciences, as well as in optimal control and in the theory of filltering of signals from noisy measurements. Its aim is to make probability theory in function space readily accessible to scientists trained in the traditional methods of applied mathematics, such as integral, ordinary, and partial differential equations and asymptotic methods, rather than in probability and measure theory.


Energy Balance Climate Models

Energy Balance Climate Models

Author: Gerald R. North

Publisher: John Wiley & Sons

Published: 2017-12-04

Total Pages: 389

ISBN-13: 3527411321

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Energy Balance Climate Models Written by renowned experts in the field, this first book to focus exclusively on energy balance climate models provides a concise overview of the topic. It covers all major aspects, from the simplest zero-dimensional models, proceeding to horizontally and vertically resolved models. The text begins with global average models, which are explored in terms of their elementary forms yielding the global average temperature, right up to the incorporation of feedback mechanisms and some analytical properties of interest. The eff ect of stochastic forcing is then used to introduce natural variability in the models before turning to the concept of stability theory. Other one dimensional or zonally averaged models are subsequently presented, along with various applications, including chapters on paleoclimatology, the inception of continental glaciations, detection of signals in the climate system, and optimal estimation of large scale quantities from point scale data. Throughout the book, the authors work on two mathematical levels: qualitative physical expositions of the subject material plus optional mathematical sections that include derivations and treatments of the equations along with some proofs of stability theorems. A must-have introduction for policy makers, environmental agencies, and NGOs, as well as climatologists, molecular physicists, and meteorologists.


Climate Econometrics

Climate Econometrics

Author: Jennifer L. Castle

Publisher: Now Publishers

Published: 2020-08-18

Total Pages: 190

ISBN-13: 9781680837087

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Climate Econometrics: An Overview provides a review of the research in this new and growing field. The structure of the monograph is as follows: First, section 2 describes econometric methods for empirical climate modeling that can account for wide-sense non-stationarity, namely both stochastic trends and location shifts, with possibly large outliers, as well as dynamics and non-linearities. Section 3 considers hazards confronting empirical modeling of nonstationary time-series data using an example where a counter-intuitive finding is hard to resolve. The framework has a clear subject-matter theory, so is not mere 'data mining', yet the empirical result flatly contradicts the well-based theory. Section 4 provides a brief excursion into climate science, mainly concerned with the composition of the Earth's atmosphere and the role of CO2 as a greenhouse gas. Section 5 considers the consequences, both good and bad, of the Industrial Revolution raising living standards beyond the wildest dreams of those living in the 17th century, but leading to dangerous levels of CO2 emissions from using fossil fuels and consider applications of climate econometrics against that background. Section 6 illustrates the approach by modeling past climate variability over the Ice Ages. Section 7 models UK annual CO2 emissions over 1860-2017 to walk through the stages of modeling empirical time series that manifest all the problems of wide-sense non-stationarity. Section 8 concludes and summarizes a number of other empirical applications.