Invisible in the Storm
Language: English
Published by Princeton University Press, US, 2013
- Hardcover
- New

Seller: Rarewaves USA, HEBRON, KY, U.S.A.Rarewaves USA
AbeBooks seller since June 10, 2025
Condition: New
US$ 53.60
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Add to basketItem description from seller
Invisible in the Storm is the first book to recount the history, personalities, and ideas behind one of the greatest scientific successes of modern times--the use of mathematics in weather prediction. Although humans have tried to forecast weather for millennia, mathematical principles were used in meteorology only after the turn of the twentieth century. From the first proposal for using mathematics to predict weather, to the supercomputers that now process meteorological information gathered from satellites and weather stations, Ian Roulstone and John Norbury narrate the groundbreaking evolution of modern forecasting. The authors begin with Vilhelm Bjerknes, a Norwegian physicist and meteorologist who in 1904 came up with a method now known as numerical weather prediction. Although his proposed calculations could not be implemented without computers, his early attempts, along with those of Lewis Fry Richardson, marked a turning point in atmospheric science.Roulstone and Norbury describe the discovery of chaos theory's butterfly effect, in which tiny variations in initial conditions produce large variations in the long-term behavior of a system--dashing the hopes of perfect predictability for weather patterns. They explore how weather forecasters today formulate their ideas through state-of-the-art mathematics, taking into account limitations to predictability. Millions of variables--known, unknown, and approximate--as well as billions of calculations, are involved in every forecast, producing informative and fascinating modern computer simulations of the Earth system. Accessible and timely, Invisible in the Storm explains the crucial role of mathematics in understanding the ever-changing weather.…
Seller Inventory # LU-9780691152721
- Title
- Invisible in the Storm
- Author
- Ian Roulstone, John Norbury
- Publisher
- Princeton University Press, US
- Publication year
- 2013
- Condition
- New
- Binding
- Hardback
- Language
- English
- ISBN 10
- 0691152721
- ISBN 13
- 9780691152721
- Item weight
- 709 grams
An accessible book that examines the mathematics of weather prediction
Invisible in the Storm is the first book to recount the history, personalities, and ideas behind one of the greatest scientific successes of modern times―the use of mathematics in weather prediction. Although humans have tried to forecast weather for millennia, mathematical principles were used in meteorology only after the turn of the twentieth century. From the first proposal for using mathematics to predict weather, to the supercomputers that now process meteorological information gathered from satellites and weather stations, Ian Roulstone and John Norbury narrate the groundbreaking evolution of modern forecasting.
The authors begin with Vilhelm Bjerknes, a Norwegian physicist and meteorologist who in 1904 came up with a method now known as numerical weather prediction. Although his proposed calculations could not be implemented without computers, his early attempts, along with those of Lewis Fry Richardson, marked a turning point in atmospheric science. Roulstone and Norbury describe the discovery of chaos theory's butterfly effect, in which tiny variations in initial conditions produce large variations in the long-term behavior of a system―dashing the hopes of perfect predictability for weather patterns. They explore how weather forecasters today formulate their ideas through state-of-the-art mathematics, taking into account limitations to predictability. Millions of variables―known, unknown, and approximate―as well as billions of calculations, are involved in every forecast, producing informative and fascinating modern computer simulations of the Earth system.
Accessible and timely, Invisible in the Storm explains the crucial role of mathematics in understanding the ever-changing weather.
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