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The Epistemologies of Non-Forecasting Simulations, Part II: Climate, Chaos, Computing Style, and the Contextual Plasticity of Error

Published online by Cambridge University Press:  01 June 2009

Lambert Williams  and
William Thomas
Lambert Williams
Affiliation:
Harvard University and Max-Planck-Institut für Wissenschaftsgeschichte, Berlin
William Thomas
Affiliation:
Center for the History of Physics, American Institute of Physics, College Park, Maryland
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Argument

We continue our analysis of modeling practices that focus more on qualitative understanding of system behavior than the attempt to provide sharp forecasts. The argument here is built around three episodes: the ambitious work of the Princeton Meteorological Project; the seemingly simple models of convection in weather systems by Edward Lorenz at MIT; and then finally analysis of the dripping faucet by Robert Shaw and the Dynamical Systems Collective at UC Santa Cruz. Using the Princeton Meteorological Project as an argumentative foil for the later chaos work of Lorenz and Shaw, we first show how the epistemological interest of modeling came to shift from issuing predictions to probing the very meaning and limits of prediction. The second step of our argument shows that what may be seen in one context of use as a modeling technology that is error ridden, imprecise, or inadequate, may be parsed completely differently in another context. This argument about technology and practice, we argue, feeds through to epistemological conceptions of error. Far from being something that can be defined in the absolute, the notion of error is shown to be contextually plastic.

Type
Research Article
Information
Science in Context , Volume 22 , Issue 2 , June 2009 , pp. 271 - 310
Copyright
Copyright © Cambridge University Press 2009

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