A Vast Machine: Computer Models, Climate Data, and the by Paul N. Edwards

By Paul N. Edwards

The technological know-how in the back of worldwide warming, and its heritage: how scientists realized to appreciate the ambience, to degree it, to track its earlier, and to version its destiny.

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Extra resources for A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming

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Thus it locates the meaning of individual action in its relationship to the gigantic whole. Finally, it affirms that global change matters so deeply that it should occupy the intimate corners of everyday awareness and guide each person’s every choice. 1 Photograph of Earth taken from Apollo 8, December 1968. Image courtesy NASA. of maps, parlor globes, or pre-Darwinian cosmologies. Instead, it meant grasping the planet as a dynamic system: intricately interconnected, articulated, evolving, but ultimately fragile and vulnerable.

For example, far more important than hardware in linking global financial markets into a single infrastructure were institutional, legal, and political gateways that permitted trans-border stock trading, currency exchange, and so on. No system or network can ever fulfill all the requirements users may have. Systems work well because of their limited scope, their relative coherence, and their centralized control. System builders try to expand by simply increasing their systems’ scale to reach more potential users, thereby excluding competitors.

27 This book is going to invert the climate knowledge infrastructure for you, but scientists themselves do it often. Infrastructural inversion is, in fact, fundamental to how scientists handle data. Climate scientists put it this way: For long-term climate analyses—particularly climate change analyses—to be accurate, the climate data used must be homogeneous. A homogeneous climate time series is defined as one where variations are caused only by variations in weather and climate. Unfortunately, most long-term climatological time series have been affected by a number of non-climatic factors that make these data unrepresentative of the actual climate variation occurring over time.

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