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Climate Change and Policy - The Calculability of Climate Change and the Challenge of Uncertainty (Paperback, 2011 ed.)
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Climate Change and Policy - The Calculability of Climate Change and the Challenge of Uncertainty (Paperback, 2011 ed.)
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The debate on how mankind should respond to climate change is
diverse, as the appropriate strategy depends on global as well as
local circumstances. As scientists are denied the possibility of
conducting experiments with the real climate, only climate models
can give insights into man-induced climate change, by experimenting
with digital climates under varying conditions and by extrapolating
past and future states into the future. But the 'nature' of models
is a purely representational one. A model is good if it is believed
to represent the relevant processes of a natural system well.
However, a model and its results, in particular in the case of
climate models which interconnect countless hypotheses, is only to
some extent testable, although an advanced infrastructure of
evaluation strategies has been developed involving strategies of
model intercomparison, ensemble prognoses, uncertainty metrics on
the system and component levels. The complexity of climate models
goes hand in hand with uncertainties, but uncertainty is in
conflict with socio-political expectations. However, certain
predictions belong to the realm of desires and ideals rather than
to applied science. Today's attempt to define and classify
uncertainty in terms of likelihood and confidence reflect this
awareness of uncertainty as an integral part of human knowledge, in
particular on knowledge about possible future developments. The
contributions in this book give a first hand insight into
scientific strategies in dealing with uncertainty by using
simulation models and into social, political and economical
requirements in future projections on climate change. Do these
strategies and requirements meet each other or fail? The debate on
how mankind should respond to climate change is diverse, as the
appropriate strategy depends on global as well as local
circumstances. As scientists are denied the possibility of
conducting experiments with the real climate, only climate models
can give insights into man-induced climate change, by experimenting
with digital climates under varying conditions and by extrapolating
past and future states into the future. But the 'nature' of models
is a purely representational one. A model is good if it is believed
to represent the relevant processes of a natural system well.
However, a model and its results, in particular in the case of
climate models which interconnect countless hypotheses, is only to
some extent testable, although an advanced infrastructure of
evaluation strategies has been developed involving strategies of
model intercomparison, ensemble prognoses, uncertainty metrics on
the system and component levels. The complexity of climate models
goes hand in hand with uncertainties, but uncertainty is in
conflict with socio-political expectations. However, certain
predictions belong to the realm of desires and ideals rather than
to applied science. Today's attempt to define and classify
uncertainty in terms of likelihood and confidence reflect this
awareness of uncertainty as an integral part of human knowledge, in
particular on knowledge about possible future developments. The
contributions in this book give a first hand insight into
scientific strategies in dealing with uncertainty by using
simulation models and into social, political and economical
requirements in future projections on climate change. Do these
strategies and requirements meet each other or fail? Gabriele
Gramelsberger is Principal Investigator of the Collaborative
Research Project is Principal Investigator of the Collaborative
Research Project
General
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