Modeling Dynamic Climate Systems

In the process of building and using models to comprehend the dynamics of the atmosphere, ocean and climate, the reader will learn how the different components of climate systems function, interact with each other, and vary over time. Topics include the stability of climate, Earths energy balance, parcel dynamics in the atmosphere, the mechanisms of heat transport in the climate system, and mechanisms of climate variability. Special attention is given to the effects of climate change.

This textbook presents all aspects of climate system dynamics, on all timescales from the Earth's formation to modern human-induced climate change. It discusses the dominant feedbacks and interactions between all the components of the climate system: atmosphere, ocean, land surface and ice sheets. It addresses one of the key challenges for a course on the climate system: students can come from a range of backgrounds. A glossary of key terms is provided for students with little background in the climate sciences, whilst instructors and students with more expertise will appreciate the book's modular nature. Exercises are provided at the end of each chapter for readers to test their understanding. This textbook will be invaluable for any course on climate system dynamics and modeling, and will also be useful for scientists and professionals from other disciplines who want a clear introduction to the topic.

Climate Systems Modeling presents an interdisciplinary and comprehensive study of the dynamics of the whole global system. As a comprehensive text it will appeal to students and researchers concerned with any aspect of climatology and the study of related topics in the broad earth and environmental sciences.

A three-tier approach is presented: (i) fundamental dynamical concepts of climate processes, (ii) their mathematical formulation based on balance equations, and (iii) the necessary numerical techniques to solve these equations. This book showcases the global energy balance of the climate system and feedback processes that determine the climate sensitivity, initial-boundary value problems, energy transport in the climate system, large-scale ocean circulation and abrupt climate change.

This book is a survey of the research work done by the author over the last 15 years, in collaboration with various eminent mathematicians and climate scientists on the subject of tropical convection and convectively coupled waves. In the areas of climate modelling and climate change science, tropical dynamics and tropical rainfall are among the biggest uncertainties of future projections. This not only puts at risk billions of human beings who populate the tropical continents but it is also of central importance for climate predictions on the global scale. This book aims to introduce the non-expert readers in mathematics and theoretical physics to this fascinating topic in order to attract interest into this difficult and exciting research area. The general thyme revolves around the use of new deterministic and stochastic multi-cloud models for tropical convection and convectively coupled waves. It draws modelling ideas from various areas of mathematics and physics and used in conjunction with state-of-the-art satellite and in-situ observations and detailed numerical simulations. After a review of preliminary material on tropical dynamics and moist thermodynamics, including recent discoveries based on satellite observations as well as Markov chains, the book immerses the reader into the area of models for convection and tropical waves. It begins with basic concepts of linear stability analysis and ends with the use of these models to improve the state-of-the-art global climate models. The book also contains a fair amount of exercises that makes it suitable as a textbook complement on the subject.

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 present monograph is dedicated to a new branch of the theory of climate, which is titled by the authors, "Mathematical Theory of Climate. " The foundation of this branch is the investigation of climate models by the methods of the qUalitative theory of differential equa tions. In the Russian edition the book was named "Fundamentals of the Mathematical Theory of Climate. " Respecting the recommenda tions of Wayne Yuhasz (we are truly grateful to him for this advice), we named the English edition of the book "Mathematics of Climate Modelling. " This title appears to be more appropriate, since the con structive results of the theory are at present preliminary and have not been fully tested with experiments in climate modelling. This branch of science is yet developing and its practical results will be obtained only in the near future. Nevertheless, we want to keep the terminology which we have used in the introduction to the Russian edition of the book, since the authors hope that this term will be accepted by the scientific community for identification of a given branch of climate theory. On preparing the English edition, new ideas were established con necting some significant new research results obtained by the author. We are deeply grateful to G. Marchuk for continual encourage ment of this scientific enterprise and fruitful discussions, to our young colleagues A. Gorelov, E. Kazantsev, A. Gritsun, and A.

The social cost of carbon (SCC) for a given year is an estimate, in dollars, of the present discounted value of the damage caused by a 1-metric ton increase in CO2 emissions into the atmosphere in that year; or equivalently, the benefits of reducing CO2 emissions by the same amount in that given year. The SCC is intended to provide a comprehensive measure of the monetized value of the net damages from global climate change from an additional unit of CO2, including, but not limited to, changes in net agricultural productivity, energy use, human health effects, and property damages from increased flood risk. Federal agencies use the SCC to value the CO2 emissions impacts of various policies including emission and fuel economy standards for vehicles, regulations of industrial air pollutants from industrial manufacturing, emission standards for power plants and solid waste incineration, and appliance energy efficiency standards. There are significant challenges to estimating a dollar value that reflects all the physical, human, ecological, and economic impacts of climate change. Recognizing that the models and scientific data underlying the SCC estimates evolve and improve over time, the federal government made a commitment to provide regular updates to the estimates. To assist with future revisions of the SCC, the Interagency Working Group on the Social Cost of Carbon (IWG) requested the National Academies of Sciences, Engineering, and Medicine complete a study that assessed the merits and challenges of a limited near-term update to the SCC and of a comprehensive update of the SCC to ensure that the estimates reflect the best available science. This interim report focuses on near-term updates to the SCC estimates.

This book presents stochastic dynamical systems theory in order to synthesize our current knowledge of climate variability, for graduate students and researchers.

Atmosphere is a chaotic system. As such it is inherently unpredictable. The book applies chaos theory to understand and predict climate systems. Author presents a cell dynamical system model for turbulent fluid flows. The model envisages the irregular space-time fluctuations of the atmospheric flow pattern generated as a consequence of the superimposition of a continuum of eddies. The natural space-time variability is quantified in terms of the universal inverse power-law form of the statistical normal distribution. A range of possible applications of the cell dynamical system model for weather and climate system is discussed. The book provides a comprehensive reference material for scientists and academicians working in the field of atmospheric sciences and related topics.