The Climate Demon: Past, Present, and Future of Climate Prediction

Cambridge University Press (to be published between Nov 2021 and Jan2022)

The Climate Demon (book cover with butterfly image)

Cover photo: The monarch butterfly, a metaphor for prediction uncertainty, faces an uncertain climate future

Humans do it.

Computers do it.

Even groundhogs do it.

We are talking about climate prediction, of course.

To deal with the climate crisis, we need to predict how much warmer it’s going to get over the next fifty years or longer! Computer models of climate are the tools we use to make such predictions.

Why should we trust these predictions? How certain, or uncertain, are they?

This book addresses the above questions by tracing the fascinating and intertwined history of digital computers and climate models from the mid 20th century to the present, and extrapolating it to the future – from the weather forecast made by ENIAC, the first digital computer, to climate projections that will soon run on massive Exascale supercomputers.

Written by an experienced climate scientist, but aimed at the general reader, the book provides a frank assessment of the strengths and limitations of climate models. It explains the scientific foundations and the philosophical considerations behind climate prediction, including the tension between simplicity and complexity of models and the interplay between data-driven and hypothesis-driven science.

The title refers to a recurring philosophical theme in the book, the notion of a Climate Demon. It is the climate analog of Laplace’s Demon, and serves as a metaphor for a model that accurately calculates the trajectory of future climate.

The first part of the book (The Past) features the stories of computing pioneer, John von Neumann, who helped make the first digital weather forecast, meteorologist Ed Lorenz, who discovered the Butterfly Effect, scientist and women’s rights pioneer Eunice Foote, who connected carbon dioxide with heating, climate scientist Suki Manabe, who used computers to model the Greenhouse Effect, and atmospheric chemist Susan Solomon, who deciphered the mysteries of the Ozone Hole. (Punxsutawney Phil, the prognosticating groundhog, makes a cameo appearance.)

The second part (The Present) discusses the current challenges faced by climate prediction, such as growth in model complexity, “tuning” of models to compensate for errors, and the need for model diversity. The distinction between well-known unknowns and poorly known unknowns, and the pitfalls of translating climate predictions for the general public, are also discussed.

The third part (The Future) describes trends in climate prediction driven by recent scientific developments such as geoengineering, the demise of Moore’s Law of ever faster chips, and the advent of machine learning. The book concludes with a discussion of philosophical and practical issues in dealing with the impacts and risks of climate change.

A central theme of the book is that climate models are metaphors of reality – their predictions should be taken seriously, but not literally. There is deep uncertainty regarding predictions of extreme climate change scenarios, but this uncertainty is by no means a reason for inaction. If anything, the uncertainty adds urgency to the need for strong action to mitigate global warming. The predictions we have now are confident enough for us to justify immediate action, but uncertain enough for us not to panic over doomsday scenarios.

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