problem of climate science. Chapters Two and Three review some contemporary work being done in complexity theory, with a particular focus on attempts to define and quantify the notion of “complexity” itself, then sketch an account of complexity that builds on the work done in Chapter One.
Second, there are methodological questions. These questions are more specifically concerned
with the structure and operation of a particular branch of science; the methodological questions
that will concern (say) a fundamental physicist will be different from the methodological
questions that will concern a climate scientist. Questions about how climate science makes its
predictions, on what basis we ought to trust those predictions, how we might use the tools of
climate science to make better predictions, how to interpret the climate data on record, and how
to best make use of our limited computing resources are all methodological questions. "How
should we decide which factors to include in our climate model?" is a paradigmatic
methodological question. Chapters Four, Five, and Six will focus on methodological
questions. Chapter Four consists in a general introduction to the project of climate modeling,
with a focus on the limitations of simple climate models that are solvable in the absence of pure
computer simulations. In Chapter Five, I examine the challenges of building more complex
climate models, with special attention to the problems posed by non-linearity and chaos in the
climate system. In Chapter Six, I examine the role that computational simulation plays in
working with climate models, and attempt to reconcile the novel problems posed by “science by
simulation” with the results of climate science.
The answers to questions in each of the categories will (of course) be informed by answers to
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