Weather Macroweather And Climate
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Weather, Macroweather, and the Climate
Author: Shaun Lovejoy
language: en
Publisher: Oxford University Press
Release Date: 2019-03-19
Weather, Macroweather, and the Climate is an insider's attempt to explain as simply as possible how to understand the atmospheric variability that occurs over an astonishing range of scales: from millimeters to the size of the planet, from milliseconds to billions of years. The variability is so large that standard ways of dealing with it are utterly inadequate: in 2015, it was found that classical approaches had underestimated the variability by the astronomical factor of a quadrillion (a million billion). Author Shaun Lovejoy asks - and answers - many fundamental questions such as: Is the atmosphere random or deterministic? What is turbulence? How big is a cloud (what is the appropriate notion of size itself)? What is its dimension? How can we conceptualize the structures within structures within structures spanning millimeters to thousands of kilometers and milliseconds to the age of the planet? What is weather? What is climate? Lovejoy shows in simple terms why the industrial epoch warming can't be natural - much simpler than trying to show that it's anthropogenic. We will discuss in simple terms how to make the best seasonal and annual forecasts - without giant numerical models. Above all, the book offers readers a new understanding of the atmosphere.
The Weather and Climate
Author: Shaun Lovejoy
language: en
Publisher: Cambridge University Press
Release Date: 2013-04-04
A new method of modeling the atmosphere, synthesizing data analysis techniques and multifractal statistics, for atmospheric researchers and graduate students.
Climate, Planetary and Evolutionary Sciences
This book presents the result of an innovative challenge, to create a systematic literature overview driven by machine-generated content. Questions and related keywords were prepared for the machine to query, discover, collate and structure by Artificial Intelligence (AI) clustering. The AI-based approach seemed especially suitable to provide an innovative perspective as the topics are indeed both complex, interdisciplinary and multidisciplinary, for example, climate, planetary and evolution sciences. Springer Nature has published much on these topics in its journals over the years, so the challenge was for the machine to identify the most relevant content and present it in a structured way that the reader would find useful. The automatically generated literature summaries in this book are intended as a springboard to further discoverability. They are particularly useful to readers with limited time, looking to learn more about the subject quickly and especially if they are new to the topics. Springer Nature seeks to support anyone who needs a fast and effective start in their content discovery journey, from the undergraduate student exploring interdisciplinary content, to Master- or PhD-thesis developing research questions, to the practitioner seeking support materials, this book can serve as an inspiration, to name a few examples. It is important to us as a publisher to make the advances in technology easily accessible to our authors and find new ways of AI-based author services that allow human-machine interaction to generate readable, usable, collated, research content.