Predicting Our Climate Future: What We Know, What We Don't Know, And What We Can't Know

Author:   David Stainforth (Professorial Research Fellow, Principal Research Fellow, London School of Economics and Political Science)
Publisher:   Oxford University Press
Edition:   1
ISBN:  

9780198812937


Pages:   368
Publication Date:   12 October 2023
Format:   Hardback
Availability:   To order   Availability explained
Stock availability from the supplier is unknown. We will order it for you and ship this item to you once it is received by us.

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Predicting Our Climate Future: What We Know, What We Don't Know, And What We Can't Know


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Author:   David Stainforth (Professorial Research Fellow, Principal Research Fellow, London School of Economics and Political Science)
Publisher:   Oxford University Press
Imprint:   Oxford University Press
Edition:   1
Dimensions:   Width: 16.40cm , Height: 2.10cm , Length: 24.00cm
Weight:   0.001kg
ISBN:  

9780198812937


ISBN 10:   0198812930
Pages:   368
Publication Date:   12 October 2023
Audience:   General/trade ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   To order   Availability explained
Stock availability from the supplier is unknown. We will order it for you and ship this item to you once it is received by us.

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Reviews

Climate is, in some respects, highly predictable; yet, in other respects, highly unpredictable. But there is no contradiction. The resolution of this seeming paradox in Predicting Our Climate Future leads in turn to a vision for how humankind must respond to this most important problem of all time. * George Akerlof, Nobel Laureate in Economics, 2001 * A profound yet very accessible guide to climate science, highlighting the significant uncertainties without apology. This book explains clearly why doubt creates a greater and more urgent need to act now to build a better future. * Trevor Maynard, Executive Director of Systemic Risks, Cambridge Centre for Risk Studies * The immense complexity of the climate system raises deep questions about what science can usefully say about the future. David Stainforth navigates philosophical and mathematical questions that could hardly be of greater practical importance. He questions what it is reasonable to ask of climate scientists and his conclusions challenge the way in which science should be conducted in the future. * Jim Hall, Professor of Climate and Environmental Risk, University of Oxford * Is the science settled? Are climate models rubbish? Stainforth's book serves up nuanced answers to big questions in climate science, in an easy conversational style. * Cameron Hepburn, Professor of Environmental Economics, University of Oxford * A thoughtful exploration of the foundations and limitations of climate prediction that explains how its chaotic and probabilistic nature lead to deep uncertainty when assessing climate risk. * Ramalingam Saravanan, Professor of Atmospheric Sciences, Texas A&M University * Predicting Our Climate Future is an erudite and very personal reflection on climate change, the state of climate science, and their implications for the decisions society needs to take. It should be top of the reading list for scientists, practitioners and anyone who wants to truly comprehend the challenge of climate prediction. * Simon Dietz, Professor of Environmental Policy, London School of Economics and Political Science *


Author Information

After studying Physics at Oxford, David Stainforth worked on ocean modelling and then studied for a Masters on Environmental Management before working as a renewable energy consultant. He returned to academia to pursue research on computer models of the atmosphere before joining Professor Myles Allen to develop the climateprediction.net project, a public-resource, distributed-computing project which engaged hundreds of thousands of people worldwide with climate modelling. He went on to an Associate Professor position at Exeter University and then to LSE, pursuing research on the philosophy of climate science, climate economics, climate modelling and climate decision making under deep uncertainty.

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