Climate modeling and simulation teach us about past, present, and future conditions of life on earth and help us understand observations about the changing atmosphere and ocean and terrestrial ecology. Focusing on high-end modeling and simulation of earth's climate, Climate Modeling for Scientists and Engineers presents observations about the general circulations of the earth and the partial differential equations used to model the dynamics of weather and climate, covers numerical methods for geophysical flows in more detail than many other texts, discusses parallel algorithms and the role of high-performance computing used in the simulation of weather and climate, and provides supplemental lectures and MATLAB® exercises on an associated Web page.

Climate modeling and simulation teach us about past, present, and future conditions of life on earth and help us understand observations about the changing atmosphere and ocean and terrestrial ecology. Focusing on high-end modeling and simulation of earth's climate, Climate Modeling for Scientists and Engineers presents observations about the general circulations of the earth and the partial differential equations used to model the dynamics of weather and climate, covers numerical methods for geophysical flows in more detail than many other texts, discusses parallel algorithms and the role of high-performance computing used in the simulation of weather and climate, and provides over 100 pages of supplemental lectures and MATLAB? exercises on an associated web page. This book is intended for graduate students in science and engineering. It is also useful for a broad spectrum of computational science and engineering researchers, especially those who want a brief introduction to the methods and capabilities of climate models and those who use climate model results in their investigations. Information on numerical methods used to solve the equations of motion and climate simulations using parallel algorithms on high-performance computers challenges researchers who aim to improve the prediction of climate on decadal to century time scales.

This book demystifies the models we use to simulate present and future climates, allowing readers to better understand how to use climate model results. In order to predict the future trajectory of the Earth’s climate, climate-system simulation models are necessary. When and how do we trust climate model predictions? The book offers a framework for answering this question. It provides readers with a basic primer on climate and climate change, and offers non-technical explanations for how climate models are constructed, why they are uncertain, and what level of confidence we should place in them. It presents current results and the key uncertainties concerning them. Uncertainty is not a weakness but understanding uncertainty is a strength and a key part of using any model, including climate models. Case studies of how climate model output has been used and how it might be used in the future are provided. The ultimate goal of this book is to promote a better understanding of the structure and uncertainties of climate models among users, including scientists, engineers and policymakers.

Provides students with a solid foundation in climate science, with which to understand global warming, natural climate variations, and climate models. As climate models are one of our primary tools for predicting and adapting to climate change, it is vital we appreciate their strengths and limitations. Also key is understanding what aspects of climate science are well understood and where quantitative uncertainties arise. This textbook will inform the future users of climate models and the decision-makers of tomorrow by providing the depth they need, while requiring no background in atmospheric science and only basic calculus and physics. Developed from a course that the author teaches at UCLA, material has been extensively class-tested and with online resources of colour figures, Powerpoint slides, and problem sets, this is a complete package for students across all sciences wishing to gain a solid grounding in climate science.

Mathematics and Climate is a timely textbook aimed at students and researchers in mathematics and statistics who are interested in current issues of climate science, as well as at climate scientists who wish to become familiar with qualitative and quantitative methods of mathematics and statistics. The authors emphasize conceptual models that capture important aspects of Earth's climate system and present the mathematical and statistical techniques that can be applied to their analysis. Topics from climate science include the Earth?s energy balance, temperature distribution, ocean circulation patterns such as El Ni?o?Southern Oscillation, ice caps and glaciation periods, the carbon cycle, and the biological pump. Among the mathematical and statistical techniques presented in the text are dynamical systems and bifurcation theory, Fourier analysis, conservation laws, regression analysis, and extreme value theory. The following features make Mathematics and Climate a valuable teaching resource: issues of current interest in climate science and sustainability are used to introduce the student to the methods of mathematics and statistics; the mathematical sophistication increases as the book progresses and topics can thus be selected according to interest and level of knowledge; each chapter ends with a set of exercises that reinforce or enhance the material presented in the chapter and stimulate critical thinking and communication skills; and the book contains an extensive list of references to the literature, a glossary of terms for the nontechnical reader, and a detailed index.

Warren M. Washington is consultant and advisor to a number of government officials and committees on climate-system modelling. Now along with Claire Parkinson (NASA) he gives the reader insight into the complex field of climate modelling. Updated and revised from the first edition, this book is a welcome reference on climate modeling; an area that is becoming more and more sought after in light of environmental changes. Suitable for those wanting an in-road into understanding climate modeling but also an excellent companion for those with some prior knowledge of modeling meteorological systems.

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 regional climate impacts, vulnerability, risk and resilience. This book is a comprehensive guide to the downscaling techniques used for climate data. A general introduction of the science of climate modeling is followed by a discussion of techniques, models and methodologies used for producing downscaled projections, and the advantages, disadvantages and uncertainties of each. The book provides detailed information on dynamic and statistical downscaling techniques in non-technical language, as well as recommendations for selecting suitable downscaled datasets for different applications. The use of downscaled climate data in national and international assessments is also discussed using global examples. This is a practical guide for graduate students and researchers working on climate impacts and adaptation, as well as for policy makers and practitioners interested in climate risk and resilience.