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An advanced, updated, and self-contained treatment. Includes the fundamental system of equations governing large-scale atmospheric motions, coordinate systems, atmospheric wave motions, energetics, hyperbolic and elliptic equations, moisture modeling, solar and terrestrial radiation modeling, seasonal and climate prediction. Presupposes a knowledge of mathematics through calculus, some vector analysis, and introductory meteorology.
For advanced undergraduate and beginning graduate students in atmospheric, oceanic, and climate science, Atmosphere, Ocean and Climate Dynamics is an introductory textbook on the circulations of the atmosphere and ocean and their interaction, with an emphasis on global scales. It will give students a good grasp of what the atmosphere and oceans look like on the large-scale and why they look that way. The role of the oceans in climate and paleoclimate is also discussed. The combination of observations, theory and accompanying illustrative laboratory experiments sets this text apart by making it accessible to students with no prior training in meteorology or oceanography. * Written at a mathematical level that is appealing for undergraduates and beginning graduate students * Provides a useful educational tool through a combination of observations and laboratory demonstrations which can be viewed over the web * Contains instructions on how to reproduce the simple but informative laboratory experiments * Includes copious problems (with sample answers) to help students learn the material.
MATLAB scripts (M-files) are provided on the accompanying CD.
Numerical models have become essential tools in environmental science, particularly in weather forecasting and climate prediction. This book provides a comprehensive overview of the techniques used in these fields, with emphasis on the design of the most recent numerical models of the atmosphere. It presents a short history of numerical weather prediction and its evolution, before describing the various model equations and how to solve them numerically. It outlines the main elements of a meteorological forecast suite, and the theory is illustrated throughout with practical examples of operational models and parameterizations of physical processes. This book is founded on the author's many years of experience, as a scientist at Météo-France and teaching university-level courses. It is a practical and accessible textbook for graduate courses and a handy resource for researchers and professionals in atmospheric physics, meteorology and climatology, as well as the related disciplines of fluid dynamics, hydrology and oceanography.
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This book, first published in 2002, is a graduate-level text on numerical weather prediction, including atmospheric modeling, data assimilation and predictability.
This book, first published in 2006, is a history of weather forecasting for researchers, graduate students and professionals in numerical weather forecasting.
An Introduction to Numerical Weather Prediction Techniques is unique in the meteorological field as it presents for the first time theories and software of complex dynamical and physical processes required for numerical modeling. It was first prepared as a manual for the training of the World Meteorological Organization's programs at a similar level. This new book updates these exercises and also includes the latest data sets. This book covers important aspects of numerical weather prediction techniques required at an introductory level. These techniques, ranging from simple one-dimensional space derivative to complex numerical models, are first described in theory and for most cases supported by fully tested computational software. The text discusses the fundamental physical parameterizations needed in numerical weather models, such as cumulus convection, radiative transfers, and surface energy fluxes calculations. The book gives the user all the necessary elements to build a numerical model. An Introduction to Numerical Weather Prediction Techniques is rich in illustrations, especially tables showing outputs from each individual algorithm presented. Selected figures using actual meteorological data are also used. This book is primarily intended for senior-level undergraduates and first-year graduate students in meteorology. It is also excellent for individual scientists who wish to use the book for self-study. Scientists dealing with geophysical data analysis or predictive models will find this book filled with useful techniques and data-processing algorithms.