Paperback
Unlock the secrets of weather forecasting and understand tomorrow’s skies.

Weather Prediction: What Everyone Needs to Know®

$41.98

  • Paperback

    304 pages

  • Release Date

    26 February 2024

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Summary

Weather has always affected human life. Understanding how weather events form and predicting what kind of weather is coming can help enormously to manage weather-risk and will become even more important as we shift towards strongly weather-dependent energy sources.

Some big steps forward in numerical weather prediction have been made in the past 40 years, thanks to advances in four key areas: the way we observe the Earth, the scientific understanding of the phenomena, advances in high…

Book Details

ISBN-13:9780197652121
ISBN-10:0197652123
Author:Roberto Buizza
Publisher:Oxford University Press Inc
Imprint:Oxford University Press Inc
Format:Paperback
Number of Pages:304
Release Date:26 February 2024
Weight:358g
Dimensions:16mm x 139mm x 210mm
Series:WHAT EVERYONE NEEDS TO KNOW
A-Format
B-Format
Weather Prediction: What Everyone Needs to Know® by Roberto Buizza - ISBN: 9780197652121
139 × 210 mm
C-Format
A4
mm / in
What They're Saying

Critics Review

This book is a valuable resource for a solid introduction to weather forecasting and prediction for the lay person. Highly recommended. Undergraduates and general readers only. * Choice *
This book is heartily recommended, especially to those about to start a career in meteorology while having little knowledge of numerical weather prediction and to enthusiasts wanting an introduction to modern numerical weather prediction. * Dan Suri, Early View *

About The Author

Roberto Buizza

Roberto Buizza is Professor in Physics at Scuola Superiore Sant’Anna, and Honorary Research Fellow at Imperial College Grantham Institute for Climate Change. He has a degree in physics, a PhD in mathematics, and a master’s in business administration. From 1991 to 2018 he worked at the European Centre for Medium-Range Weather Forecasts, where he was a key developer of its prediction systems and served as Head of the Predictability Division and Lead Scientist.

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