Weather Machine : Political Machine :: forge : weave. Hey, first time I've ever used an analogy in that particular format in the title of a review. The answer, of course, is that all four are ways of making different things. Forging is the process of creating metal objects, weaving is the process of creating cloth objects. Similarly, a "political machine" is the process of creating some political outcome, and according to Blum in this text, a "Weather Machine" is the process of creating a... weather forecast.
Blum begins with a history of some of the earliest attempts at forecasting the weather for a given location, moving from the realm of religion and superstition to the realm of science - religion and superstition by another name, but sounding better to the "modern" ear. The history largely culminates with a discussion of the early 20th century concept of the "Weather Machine", a giant warehouse full of human computers using slide rules to run calculations based on observations placed into a mathematical model in order to predict the weather.
An admiral goal well ahead of its time... but once computers (and particularly supercomputers) became a thing... perhaps an ideal no longer ahead of ours. It is here, in the era of computing, that Blum spends the rest of the text, showing how the first and earliest computer models found success all the way up to showing how certain modern models and teams work to forecast ever further out ever more rapidly... and how all of this now largely happens inside the computer itself, rather than in the suppositions of "trained meteorologists".
In other words, this is a book not about weather itself, but about the process and, yes, *business*, of creating a weather *forecast* and the various issues and histories tha come to bear in this process.
Ultimately a very illuminating work about the business side of forecasting, Blum could have perhaps spent more time showing how say hurricane and tornado forecasts are formed and how much they have progressed in the last few decades, rather than forecasting more generally - but he also ultimately stayed more true to his general premise in staying more general, showing how forecasting *as a whole* has gotten so much more detailed without diving too deep into any particular area of forecasting itself.
Ultimately a rather fascinating look at a topic few people truly understand.
Very much recommended.