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

Cover Image Copyright Year: 2010
Author(s): Paul N. Edwards
Publisher: MIT Press
Content Type : Books & eBooks
Topics: Engineering Profession
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Abstract

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 doubters: 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. Edwards argues that all our knowledge about climate change comes from three kinds of computer models: simulation models of weather and climate; reanalysis models, which recreate climate history from historical weather data; and data models, used to combine and adjust measurements from many different sources. Meteorology creates knowledge through an infrastructure (weather stations and other data platforms) that covers the whole world, making global data. This infrastructure generates information so vast in quantity and so diverse in quality and form that it can be understood only by computer analysis--making data global. Edwards describes the science behind the scientific consensus on climate change, arguing that over the years data and models have converged to create a stable, reliable, and trustworthy basis for the reality of global warming.

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      Front Matter

      Paul N. Edwards Page(s): i - xviii
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Half Title, Title, Copyright, Dedication, Contents, Acknowledgments, Introduction View full abstract»

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      Thinking Globally

      Paul N. Edwards Page(s): 1 - 25
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Global Climate as an Object of Knowledge, Dynamics of Infrastructure Development, Weather and Climate Information Infrastructures, Knowledge Infrastructures, Meteorology as Infrastructural Globalism View full abstract»

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      Global Space, Universal Time : Seeing the Planetary Atmosphere

      Paul N. Edwards Page(s): 27 - 47
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Global Space, “Data Guys” : The Network Structure of Meteorology, Universal Time View full abstract»

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      Standards and Networks : International Meteorology and the Réseau Mondial

      Paul N. Edwards Page(s): 49 - 59
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: The International Meteorological Organization, The R éseau Mondial View full abstract»

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      Climatology and Climate Change before World War II

      Paul N. Edwards Page(s): 61 - 81
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Climatology as Geography and Statistical Law, Physical Theories of Global Climate Change, The “Callendar Effect”, View full abstract»

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      Friction

      Paul N. Edwards Page(s): 83 - 110
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Computing the Weather, World War I and Meteorology, The Forecast-Factory, “The Complete Statistical Machine”, From Analog to Digital . . . and Back Again, The Third Dimension, Managing Friction in Forecasting and Climatology View full abstract»

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      Numerical Weather Prediction

      Paul N. Edwards Page(s): 111 - 137
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Weather as a Weapon, Weather Forecasting as a Demonstration of Digital Computer Power, The IAS Meteorology Project, The ENIAC Experimental Forecasts, Computational Friction, Data Friction, and the ENIAC Forecasts, Climbing the Hierarchy of Models, Operational NWP, Predictive Skill in Early NWP, Organizational Effects of Computer Modeling in Meteorology View full abstract»

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      The Infinite Forecast

      Paul N. Edwards Page(s): 139 - 186
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: How Climate Models Work, The Prototype: Norman Phillips’s Model, The Geophysical Fluid Dynamics Laboratory, The UCLA Department of Meteorology, The Livermore Atmospheric Model (LAM), The National Center for Atmospheric Research, The General Circulation of Circulation Models, Climate Modeling and Computational Friction, 2×CO2 : A Paradigmatic Modeling Experiment, Data Friction, GCMs, and Climate Change View full abstract»

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      Making Global Data

      Paul N. Edwards Page(s): 187 - 227
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Meteorology and Cold War Geopolitics, The World Meteorological Organization: Infrastructural Globalism during the Cold War, IGY: Data Sharing and Technology on the Cusp of the Computer Age, Nuclear Weapons Tests and Global Circulation Tracers, The Technopolitics of Altitude, Global Data Infrastructures as Cold War Strategy View full abstract»

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      The First WWW

      Paul N. Edwards Page(s): 229 - 250
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: World Weather Watch Design as Technopolitics, Hierarchy: Planning for Information Overload, Growing an Infrastructure, An Analog-Digital Internetwork, The World According to GARP, The Weather Information Infrastructure Comes of Age View full abstract»

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      Making Data Global

      Paul N. Edwards Page(s): 251 - 285
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Automating Error Detection and Data Entry, Objective Analysis, “Models Almost All the Way Down”, Everything, All the Time: From Interpolation to 4-D Data Assimilation, The Global Instrument: Integrating Satellites, From Reductionism to Reproductionism: Data-Laden Models and Simulation Science, Model-Data Symbiosis, Versions of the Atmosphere: The Changing Meaning of “Data” View full abstract»

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      Data Wars

      Paul N. Edwards Page(s): 287 - 322
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Weather Data, Climate Data, Fighting for the Long Term: Building Stability into Change, Global Climate Data — Plural, Reconstructing the Climate Record, Metadata Friction, Proliferation within Convergence: Climate Data Today View full abstract»

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      Reanalysis: The Do-Over

      Paul N. Edwards Page(s): 323 - 336
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Gathering Resources and Assembling Data, Production: Data Friction, Again, Fingerprint: Reanalysis Data and Climate Change, The Future of the Past View full abstract»

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      Parametrics and the Limits of Knowledge

      Paul N. Edwards Page(s): 337 - 355
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Types of Parameterization, Living in the Semi-Empirical World, Models vs. Data: Validation, Verification, or Evaluation?, Model Intercomparisons as Standardized Gateways View full abstract»

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      Simulation Models and Atmospheric Politics, 1960–1992

      Paul N. Edwards Page(s): 357 - 396
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: Climate Change as Weather Modification: The 1960s, SCEP, SMIC, and the SST, Climate Politics in the 1970s, Sticky Numbers: Stabilizing Projections of Global Warming, Nuclear Winter and Ozone Depletion, Global Warming as Mass Politics, The Road to Rio: Climate Change as World Politics, Global Models as Policy Tools View full abstract»

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      Signal and Noise : Consensus, Controversy, and Climate Change

      Paul N. Edwards Page(s): 397 - 430
      Copyright Year: 2010

      MIT Press eBook Chapters

      This chapter contains sections titled: The Intergovernmental Panel on Climate Change, The Structure of Climate Controversies, The Scientific Integrity Hearings, Models as Gateways in the Climate Knowledge Infrastructure, Climate Science on the World Wide Web, Controversy within Consensus View full abstract»

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      Conclusion

      Paul N. Edwards Page(s): 431 - 439
      Copyright Year: 2010

      MIT Press eBook Chapters

      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 doubters: 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. Edwards argues that all our knowledge about climate change comes from three kinds of computer models: simulation models of weather and climate; reanalysis models, which recreate climate history from historical weather data; and data models, used to combine and adjust measurements from many different sources. Meteorology creates knowledge through an infrastructure (weather stations and other data platforms) that covers the whole world, making global data. This infrastructure generates information so vast in quantity and so diverse in quality and form that it can be understood only by computer analysis--making data global. Edwards describes the science behind the scientific consensus on climate change, arguing that over the years data and models have converged to create a stable, reliable, and trustworthy basis for the reality of global warming. View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Notes

      Paul N. Edwards Page(s): 441 - 507
      Copyright Year: 2010

      MIT Press eBook Chapters

      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 doubters: 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. Edwards argues that all our knowledge about climate change comes from three kinds of computer models: simulation models of weather and climate; reanalysis models, which recreate climate history from historical weather data; and data models, used to combine and adjust measurements from many different sources. Meteorology creates knowledge through an infrastructure (weather stations and other data platforms) that covers the whole world, making global data. This infrastructure generates information so vast in quantity and so diverse in quality and form that it can be understood only by computer analysis--making data global. Edwards describes the science behind the scientific consensus on climate change, arguing that over the years data and models have converged to create a stable, reliable, and trustworthy basis for the reality of global warming. View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Index

      Paul N. Edwards Page(s): 509 - 518
      Copyright Year: 2010

      MIT Press eBook Chapters

      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 doubters: 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. Edwards argues that all our knowledge about climate change comes from three kinds of computer models: simulation models of weather and climate; reanalysis models, which recreate climate history from historical weather data; and data models, used to combine and adjust measurements from many different sources. Meteorology creates knowledge through an infrastructure (weather stations and other data platforms) that covers the whole world, making global data. This infrastructure generates information so vast in quantity and so diverse in quality and form that it can be understood only by computer analysis--making data global. Edwards describes the science behind the scientific consensus on climate change, arguing that over the years data and models have converged to create a stable, reliable, and trustworthy basis for the reality of global warming. View full abstract»