The first part of the book (The Past) features the stories of computing pioneer John von Neumann at the Institute for Advanced Study in Princeton, 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 (and 2021 Nobel Laureate) Suki Manabe, who used computers to model the Greenhouse Effect, planetary scientist Jim Hansen, who raised public awareness of the problem of global warming, 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 the inexorable increase 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 assessing 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.