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||Hardware errors in model outcomes arise from bugs in hardware. An obvious example is the bug in
the early version of the Pentium processor for personal computers, which gave rise to numerical
error in a broad range of floating-point calculations performed on that processor.
The processor had already been widely used worldwide for quite some time, when the bug was
discovered. It cannot be ruled out that hardware used for environmental models contains undiscovered
bugs that might affect the outcomes, although it is unlikely that they will have a significant influence
on the models' performance.
To secure against hardware error, one can test critical model output for reproducibility on a
computer with a different processor before the critical output enters the policy debate.|
||Hedging is a quantitative technique for the iterative handling of uncertainties in decision making.
It is used, for instance, to deal with risks in finance and in corporate R&D decisions.
For example, a given future scenario may be considered so probable that all decisions which are made
assume that the forecast is correct. However, if these assumptions
are wrong, there may be no flexibility to meet other outcomes. Thus, rather than solely developing a course of
action for one particular future scenario, business strategic planners prefer to tailor a hedging strategy that will
allow adaptation to a number of possible outcomes. Applied to climate change, it could for example be used by
stakeholders from industry to reduce the risks of investing in energy technology, pending governmental measures
on ecotax. Anticipating a range of measures from government to reduce greenhouse gases emissions, a branch
of industry or a company could estimate the cost-effectiveness of investing or delaying investments in more
advanced energy technology.|
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