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

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The science behind global warming, and its history: how scientists learned to understand the atmosphere, to measure it, to trace its past, and to model its future. Global warming skeptics often fall back on the argument that the scientific case for global warming is all model predictions, nothing but simulation; they warn us that we need to wait for real data, “sound scienc The science behind global warming, and its history: how scientists learned to understand the atmosphere, to measure it, to trace its past, and to model its future. Global warming skeptics often fall back on the argument that the scientific case for global warming is all model predictions, nothing but simulation; they warn us that we need to wait for real data, “sound science.” In A Vast Machine Paul Edwards has news for these skeptics: without models, there are no data. Today, no collection of signals or observations—even from satellites, which can “see” the whole planet with a single instrument—becomes global in time and space without passing through a series of data models. Everything we know about the world's climate we know through models. Edwards offers an engaging and innovative history of how scientists learned to understand the atmosphere—to measure it, trace its past, and model its future.


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The science behind global warming, and its history: how scientists learned to understand the atmosphere, to measure it, to trace its past, and to model its future. Global warming skeptics often fall back on the argument that the scientific case for global warming is all model predictions, nothing but simulation; they warn us that we need to wait for real data, “sound scienc The science behind global warming, and its history: how scientists learned to understand the atmosphere, to measure it, to trace its past, and to model its future. Global warming skeptics often fall back on the argument that the scientific case for global warming is all model predictions, nothing but simulation; they warn us that we need to wait for real data, “sound science.” In A Vast Machine Paul Edwards has news for these skeptics: without models, there are no data. Today, no collection of signals or observations—even from satellites, which can “see” the whole planet with a single instrument—becomes global in time and space without passing through a series of data models. Everything we know about the world's climate we know through models. Edwards offers an engaging and innovative history of how scientists learned to understand the atmosphere—to measure it, trace its past, and model its future.

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

  1. 5 out of 5

    Manny

    A few weeks ago, I was on a train heading for Cornwall when a thirty-something guy sat down next to me. He was reading this book and making notes. We got talking, and he told me he was a meteorologist and that he'd agreed to review it for a meteorology journal. It was evident from the title that the book was about the climate change debate, though he said that was partly a marketing tactic: in fact, most of it was about the process of gathering and interpreting climate data, the treatment was hi A few weeks ago, I was on a train heading for Cornwall when a thirty-something guy sat down next to me. He was reading this book and making notes. We got talking, and he told me he was a meteorologist and that he'd agreed to review it for a meteorology journal. It was evident from the title that the book was about the climate change debate, though he said that was partly a marketing tactic: in fact, most of it was about the process of gathering and interpreting climate data, the treatment was historical in nature, and it was only in the last couple of chapters that the climate change debate per se became an important topic. He showed me the key sections. The presentation seemed very balanced and even-handed. The author said he was alarmed at the emotional tone the debate had assumed, particularly in the US, and appeared to be bending over backwards not to get emotional himself. One detail, however, I did find rather striking. Edwards explained that there was a spectrum of approaches in any science, that could be categorised by the level of certainty required before the researcher in question was willing to accept a result. You had cutting-edge people who went chasing the new stuff, but were forced by lack of data to publish things even when the evidence wasn't compelling, but only suggestive. And then you had more and more conservative types who required harder and harder evidence. The author said that, under normal circumstances, this was natural and healthy, and the different approaches complemented each other. Sometimes the speculative stuff panned out, sometimes it didn't, and it was very good that there were people who were willing to take the time to check it carefully. What he didn't like was the fact that large business interests now appeared to be systematically exploiting this pluralistic approach, and creating scientists who were in effect professional sceptics who offered themselves for hire. He said there were researchers who methodically followed the relevant controversies, fighting statistical rear-guard actions for as long as possible to delay general acceptance of results which were already established to high standards of certainty. A few of these people had migrated through as many as four quite separate areas, starting with links between smoking and lung cancer in the 60s and ending up in climate change today. Isn't scientific ethics complicated? I instinctively feel that a scientist who chooses that career path is doing something terribly wrong. But it's hard to find a clear argument to back up the feeling.

  2. 4 out of 5

    Blair

    Fortunately this book is not as political as one might expect from the title. It is a detailed history of the development of weather and climate forecasting. Very detailed – some readers might not be interested in every meeting of the World Meteorological Organization, or every version of the General Circulation Models produced by the National Center for Atmospheric Research. To be fair he warns the reader about this in the introduction, and suggests strategies about what parts of the book to re Fortunately this book is not as political as one might expect from the title. It is a detailed history of the development of weather and climate forecasting. Very detailed – some readers might not be interested in every meeting of the World Meteorological Organization, or every version of the General Circulation Models produced by the National Center for Atmospheric Research. To be fair he warns the reader about this in the introduction, and suggests strategies about what parts of the book to read depending on your interest. There are many worthwhile ideas to be learned here. He introduces the concepts of data and computational "friction". These refer to all the delays in gathering the data for a weather forecast, and the problems with trying to compute it. Reducing this friction is accomplished by new technology, and just as important, new international institutions for sharing data. In peacetime these institutions could be developed, and in wartime weather research was accelerated to support the war effort. Later, he observes that the development of the World Weather Watch in the 1960’s dealt with all the same networking issues the World Wide Web encountered later. Weather forecasting and climate modeling have been part of the same process from the beginning. General Circulation Models were originally developed as part of the weather forecasting effort in the 1970's as the computer power to do this became available, long before there was any political concern about global warming. The way climate models work is finally explained in chapter 13, “Parametrics and the Limits of Knowledge.” Ideally these models should be based only on physics of the air, oceans and surface of the Earth. In the real world it is impossible to calculate the physics for every molecule when the models can have a grid size of hundreds of kilometers. “Parameterization” is the process of trying to simplify the real world into something that can be modeled. For example, you cannot model every raindrop, but you can model rainfall over a certain region. The models are improved by to making these parameterizations more complex and realistic. The next step is called “Tuning”, which is adjusting the parameterization to get better results. He says, “Better may mean that the result agrees more closely with observations, or that it corresponds more closely to the modeler’s expert judgment about what one modeler I interviewed called the ‘physical plausibility’ of the change.” He tells us that parameterization and tuning are scientific art forms whose connection to physical theory and observational data varies widely from case to case. Modelers can become so deeply involved in adding parameters and tweaking them to adjust model output that they lose track of the physical justification for these practices. He devotes several pages quoting modelers describing the problems with this process. It is clear that these models have a long way to go before they are completely reliable. This book is worthwhile for anyone interested in gaining a better perspective about weather and climate modeling. But it is long and not always an easy read.

  3. 4 out of 5

    Jack

    This is a remarkable book. It is not only a history of climate change (although it is that), and a history of computing. It is also a remarkably real portrait of how science actually gets done, and how science is contested. The climate stuff was very interesting (I almost said "cool", but realized how unacceptable that would be), but I found Edwards careful way of thinking about how large systems work very generative for thinking about systems very different from his own. Well worth the investme This is a remarkable book. It is not only a history of climate change (although it is that), and a history of computing. It is also a remarkably real portrait of how science actually gets done, and how science is contested. The climate stuff was very interesting (I almost said "cool", but realized how unacceptable that would be), but I found Edwards careful way of thinking about how large systems work very generative for thinking about systems very different from his own. Well worth the investment -- not always a page-turner, although Edwards is a very good craftsman for his subject -- and quite rewarding.

  4. 4 out of 5

    Ross

    I found this book so interesting that I give it 4 stars, which is a very high rating for me. The book covers the history of the science of meteorology and climatology starting in the 19th century down to recent days. I am extremely interested in the climate change that is taking place today, generally referred to as global warming, which is caused by the burning of fossil fuels beginning with the industrial revolution. The material in the book is very technical and is really only recommended for I found this book so interesting that I give it 4 stars, which is a very high rating for me. The book covers the history of the science of meteorology and climatology starting in the 19th century down to recent days. I am extremely interested in the climate change that is taking place today, generally referred to as global warming, which is caused by the burning of fossil fuels beginning with the industrial revolution. The material in the book is very technical and is really only recommended for individuals with significant training in the physical sciences and computer modeling.

  5. 5 out of 5

    Ben

    This book is awesome. If you are interested in learning about the history of meteorology (it's an epic history) and want to get an understanding of how meteorology and climatology functions, I cannot recommend this book enough. It's a big one (and sometimes technical), but it's well worth it. This book is awesome. If you are interested in learning about the history of meteorology (it's an epic history) and want to get an understanding of how meteorology and climatology functions, I cannot recommend this book enough. It's a big one (and sometimes technical), but it's well worth it.

  6. 5 out of 5

    Madison

    Interesting and important but also way too dense and reads like a textbook. I could get the same information with bullet points.

  7. 4 out of 5

    Daniel R.

    A detailed and engaging history of climatology. A central theme of the book is the importance of data and how data collection, transmission, storage, and analysis over the decades is much more complicated than just jotting down the reading on a thermometer every day. Even with good data when trying to construct models and simulations that span the entire world the issue of not having enough data or enough computing power requires understanding additional tradeoffs. Independent of the scientific A detailed and engaging history of climatology. A central theme of the book is the importance of data and how data collection, transmission, storage, and analysis over the decades is much more complicated than just jotting down the reading on a thermometer every day. Even with good data when trying to construct models and simulations that span the entire world the issue of not having enough data or enough computing power requires understanding additional tradeoffs. Independent of the scientific challenges there are political implications about how research is funded, data is shared between governments, and how scientists themselves organize and reach consensus. In the long run openness and rigor has brought us the Intergovernmental Panel on Climate Change (IPCC) and a belief that we will probably never get a more exact estimate of future climate change than we already have. A very sobering conclusion given the troubling predictions reached by the various models and summarized in the IPCC report.

  8. 5 out of 5

    Devereaux Library SDSM&T

    Quotes from Editorial Reviews "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 "A thorough and dispassionate anal Quotes from Editorial Reviews "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 "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

  9. 4 out of 5

    Richard Knepper

    Was hoping to see a little more discussion about computational infrastructure, but it certainly felt like I had a good overview of the history of climatology, the gist is sort of two things: data friction (collecting from many instruments, different instruments, historical changes) and computational friction (complex multidimensional analysis) make it hard to analyze and model large & complex systems like global weather or climate; and models and data are infinitely tangled -- the radiosonde tha Was hoping to see a little more discussion about computational infrastructure, but it certainly felt like I had a good overview of the history of climatology, the gist is sort of two things: data friction (collecting from many instruments, different instruments, historical changes) and computational friction (complex multidimensional analysis) make it hard to analyze and model large & complex systems like global weather or climate; and models and data are infinitely tangled -- the radiosonde that is sending atmospheric information is based on models (which themselves made use of earlier data) that drive the instrument, which in turn affect the data collected.

  10. 5 out of 5

    Matthew

    The book can be quite technical at time. But it comprehensively explains the global climate data collection infrastructure and governance. For anyone interested on the intricacies of data creation this a book for you. I would highly recommend that this book be read in conjunction with The Information: A history, A Theory, A Flood. Climate data was advanced along with the power of humans to create and store information.

  11. 4 out of 5

    Peter

    An outstanding and insightful book. Although specifically about global climate science, it's more broadly applicable to other endeavors that transform vast quantities of raw data into scientific understanding. One of the central points is that there is no data without models. Those who say that they only trust climate data, but that they don't trust models, don't understand the pervasiveness and necessity of modeling. An outstanding and insightful book. Although specifically about global climate science, it's more broadly applicable to other endeavors that transform vast quantities of raw data into scientific understanding. One of the central points is that there is no data without models. Those who say that they only trust climate data, but that they don't trust models, don't understand the pervasiveness and necessity of modeling.

  12. 4 out of 5

    Alix J

  13. 4 out of 5

    Bas

  14. 5 out of 5

    shankar lord

  15. 4 out of 5

    George M.

  16. 4 out of 5

    Thomas Østerlie

  17. 5 out of 5

    Robin

  18. 5 out of 5

    Oliver

  19. 4 out of 5

    Daniel Rothenberg

  20. 5 out of 5

    John Coombs

  21. 4 out of 5

    Will

  22. 4 out of 5

    Mauricio Santoro

  23. 4 out of 5

    Tawfiqam

  24. 5 out of 5

    Mike Thicke

  25. 5 out of 5

    Ezra

  26. 4 out of 5

    Joseph Petrzelka

  27. 5 out of 5

    Nicole Zampieri

  28. 5 out of 5

    Erich Theiss

  29. 5 out of 5

    Ben Toth

  30. 5 out of 5

    Stefan Krieger

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