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OCIAM**

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Oxford Centre for Industrial and Applied Mathematics
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Dr Leonard A Smith's Publications**

What might we learn from Climate Forecasts?

L.A. Smith. Proc. National Academy of Science (2001) In Press

ABSTRACT
Climate models are, for the most part, large dynamical systems involving a
million (or more) variables on big computers. Given that they are
nonlinear and that they are not perfect, what can we expect to learn from
them about the Earth's climate? How can we determine which aspects of
their output might be useful and which are noise? and how should we
distribute resources between making them ``better'', estimating variables
of true social and economic interest, and quantifying how good they are at
the moment? Just as ``chaos'' prevents accurate weather forecasts, so
model error precludes accurate forecasts of the distributions
which define climate. This yields uncertainty of the second kind. Can we
estimate the uncertainty in our uncertainty estimates? These questions
are discussed. Ultimately, all uncertainty is quantified within a given
modelling paradigm; our forecasts need never reflect the uncertainty in a
physical system.

## Contact Information

Tel: 01865-2-70517

E-mail: lenny@maths.ox.ac.uk
Last updated: 14 Feb 2001

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