Climate predictions - and the computer models behind them - play a key role in shaping public opinion and our response to the climate crisis. Some people interpret these predictions as 'prophecies of doom' and some others dismiss them as mere speculation, but the vast majority are only vaguely aware of the science behind them. This book gives a balanced view of the strengths and limitations of climate modeling. It covers historical developments, current challenges, and future trends in the field. The accessible discussion of climate modeling only requires a basic knowledge of science. Uncertainties in climate predictions and their implications for assessing climate risk are analyzed, as are the computational challenges faced by future models. The book concludes by highlighting the dangers of climate 'doomism', while also making clear the value of predictive models, and the severe and very real risks posed by anthropogenic climate change.
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R. Saravanan is Head of the Department of Atmospheric Sciences at Texas A&M University. He is a climate scientist with a background in physics and fluid dynamics and has been a lead researcher using computer models of the climate for over thirty years. He built an open-source simplified climate model from scratch, and has worked on complex models run on the world's most powerful supercomputers. He has worked with scientists at multiple climate modeling centers: the Geophysical Fluid Dynamics Laboratory (GFDL) in Princeton; the UK Universities Global Atmospheric Modelling Programme (UGAMP) in Cambridge; and the National Center for Atmospheric Research (NCAR) in Boulder, Colorado. Saravanan has served on national and international committees on climate science, including the National Research Council (NRC) Committee on the Assessment of Intraseasonal to Interannual Climate Prediction and Predictability, and the Science Steering Committee of the Prediction and Research Moored Array in the Atlantic (PIRATA). He recently helped create the TED-Ed animated short, 'Is the weather actually becoming more extreme?'.
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