The idea this lesson is working on — Students take agreement with past data as proof that a model is right, and so cannot tell a tuned fit from a test. The book sets the Pinatubo forecast, made before the data existed, against two models that fit the same past and diverge. Ask: what data was this model fitted to, and what has it predicted that it was not shown? The idea to reach is that fitting is a minimum and out-of-sample prediction is the test.
Matching the past is not yet a prediction — Hansen, Lacis, Ruedy and Sato published the Pinatubo forecast in Geophysical Research Letters in 1992; the observed cooling matched it closely, which is why it is the standard example of an out-of-sample test. Water-cycle numbers are rounded from Trenberth et al. (2007). The two diverging model curves on the last page are illustrative, not real model output.
Uncertainty is quantified, not hidden — Good models report a range and say where it comes from — measurement error, unknown parameters, or scenario choices. IPCC AR6 (2021) gives equilibrium climate sensitivity as likely 2.5–4 °C, best estimate 3 °C. A single number with no range is the less trustworthy output.