An Introduction to Numerical Weather Prediction Techniques (Hardcover)

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.

General

Imprint:	Crc Press
Country of origin:	United States
Release date:	December 1995
First published:	1996
Authors:	T.N. Krishnamurti • Lahouari Bounoua
Dimensions:	234 x 156 x 17mm (L x W x T)
Format:	Hardcover
Pages:	304
ISBN-13:	978-0-8493-8910-8
Categories:	Books > Earth & environment > Earth sciences > Meteorology > General Promotions
LSN:	0-8493-8910-0
Barcode:	9780849389108

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