A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming Hardcover – Mar 12 2010
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"A Vast Machine is a beautifully written, analytically insightful, and hugely well-informed account of the development and influence of the models and data that are the foundation of our knowledge that the climate is changing and that human beings are making it change." -- Donald MacKenzie, Professor of Sociology, University of Edinburgh, author of An Engine, Not a Camera
"[A] stimulating, well-written analysis... a visual feast." -- Ronald E. Doel, American Historical Review
"This is an excellent book and a valuable resource for all sides in the debatesover global warming." -- Steven Goldman, Environmental History
"[A] a compelling account of how political and scientific institutions, observation networks, and scientific practice evolved together over several centuries to culminate in the global knowledge infrastructure we have today." -- Chad Monfreda, Review of Policy Research
" A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming by Paul Edwards is an outstanding example of the potential for historians to contribute to broader public debates and give non-specialists insight into the work done by scientists and the process by which computer simulation has transformed scientific practice." -- Thomas Haigh, Communications of the ACM
"A 2010 Book of the Year" -- The Economist
"A thorough and dispassionate analysis by a historian of science and technology, Paul Edwards' book is well timed. Although written before the University of East Anglia e-mail leak, it anticipates many of the issues raised by the 'climategate' affair. [...] A Vast Machine puts the whole affair into historical context and should be compulsory reading for anyone who now feels empowered to pontificate on how climate science should be done." -- Myles Allen, Nature
"A Vast Machine...will be readily accessible to that legendary target, the general reader... The author's impressive scholarship and command of his material have produced a truly magisterial account." -- Richard J. Somerville, Science Magazine
"I recommend this book with considerable enthusiasm. Although it's a term reviewers have made into a cliché, I think A Vast Machine is nothing less than a tour de force. It is the most complete and balanced description we have of two sciences whose results and recommendations will, in the years ahead, be ever more intertwined with the decisions of political leaders and the fate of the human species." -- Noel Castree, American Scientist
"On the whole, this is a very good and informative read on the problems in atmospheric modeling and the way computers are--and have been--used in the process." -- Jeffrey Putnam, Computing Reviews
"This important and articulate book explains how scientists learned to understand the atmosphere, measure it, trace its past, and model its future. Edwards counters skepticism and doom with compelling reasons for hope and a call to action." -- James Rodger Fleming, Professor of Science, Technology and Society, Colby College
"With this new book, Paul Edwards once again writes the history of technology on a grand scale. Through his investigation of computational science, international governance, and scientific knowledge production, he shows that the very ability to conceptualize a global climate as such is wrapped up in the history of these institutions and their technological infrastructure. In telling this story, Edwards again makes an original contribution to a crowded field." -- Greg Downey, University of Wisconsin-Madison
About the Author
Paul N. Edwards is Professor in the School of Information and the Department of History at the University of Michigan. He is the author of The Closed World: Computers and the Politics of Discourse in Cold War America (1996) and a coeditor (with Clark Miller) of Changing the Atmosphere: Expert Knowledge and Environmental Governance (2001), both published by the MIT Press.
Inside This Book(Learn More)
Top Customer Reviews
At the outset the point is made that we don't have another planet to do a paired plot analysis so the only way forward is to carry out experiments within a simulated environment. This has become an accepted way of doing business - mainly as a result of Climate Change, but also in as it becomes apparent much later in the book, due to the pioneering work to produce "Limits to Growth". The book is a good read about science and how it has proceeded in fits and starts (a machine maybe, but one that needs a lot of routine maintenance and frequent part replacements and upgrades) beginning with the identification of carbon dioxide as a factor influencing atmospheric temperatures in the mid 1800's.Read more ›
Additionally, data and models are inextricably linked. In meteorology, GCMs produce forecasts from observational data, but that same data from surface stations was fed through a series of algorithms ' a model for interpolation ' to make it cover an entire region. 'Without models, there are no data,' Edwards proclaims, and he makes a convincing case.
The majority of the book discussed the history of climate modelling, from the 1800s until today. There was Arrhenius, followed by Angstrom who seemed to discredit the entire greenhouse theory, which was not revived until Callendar came along in the 1930s with a better spectroscope. There was the question of the ice ages, and the mistaken perception that forcing from CO2 and forcing from orbital changes (the Milankovitch model) were mutually exclusive.
For decades, those who studied the atmosphere were split into three groups, with three different strategies. Forecasters needed speed in their predictions, so they used intuition and historical analogues rather than numerical methods. Theoretical meteorologists wanted to understand weather using physics, but numerical methods for solving differential equations didn''t exist yet, so nothing was actually calculated.Read more ›
Most Helpful Customer Reviews on Amazon.com (beta)
The story begins in the 1600s as systematic collection of weather data began (at least in the modern period, other cultures such as the Chinese have older records and it would be interesting to unearth these, although the data normalization issues would be extreme). It picks up speed in the 19th C with global trade and then the telegraph. The more data collected, and the more data is exchanged, the more important it becomes to normalize data for comparison. Normalization requires some form of data model, a theory that makes the data meaningful. Indeed, this is Edwards point, all data about weather and climate only becomes meaningful in the context of a model (this is of course generally true).
Work accelerated during WW2 and then exploded in the 50s and 60s as computers became more available. The role played by John Von Neumann in this is fascinating, as is the nugget that his second wife Klara Von Neumann taught early weather scientists how to program (there is a whole hidden history of the role of woman in developing computer programming that needs to be written - or if you know of one please add it to the comments of this review or tweet it to me @StevenForth).
Edwards also introduces some useful concepts such as Data Friction and Computational Friction. I think my company can apply these in its own work, so for me this has been a very practical text.
Modern models of climate are complex and are growing more so. They have to be to integrate data from multiple sources. One of the main lines of evidence for climate change is that data from many different sources are converging to suggest that climate change is a real and accelerating phenomena. One can meaningfully ask if this convergence is an artifact of the models, although this appears unlikely given the diversity of the data and models. But Edwards shows that it is idiotic to claim that the data and the models can be meaningfully separated. This is true in all science and not just climate science. A theory is a model to normalize and integrate data and to uncover and make meaningful relations between disparate data. That these models are now expressed numerically in computations, rather than as differential equations or sentences in a human language or drawings is one of the major shifts of the information age. It will be interesting to dig deeper into the formal relations between these diffferent modeling languages.
The authors portrayal of the meteorological weather forecasting networks enables the perception of their growing across the face of earth and linking up to form a global network that generated the World Meteorological Organization in 1950 and the Inter governmental Panel on Climate Change in 1988 gives a clear portrayal of the rising of a Global Network of scientists capable of perceiving planetary processes and providing the human species with strategic guidance.
These perceptions and their articulation are nested in a bed of very deep and detailed information regarding data, data generating methodologies and processes as well as significant events that every serious student of climate sciences will benefit from familiarizing themselves with.
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