Twenty-eighth Report Adapting Institutions to Climate Change Cm ...

Chapter 4
UNCERTAINTY
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ii Four causes of uncertainty need to be considered in the context of climate change adaptation:
uncertainty of input data in climate models;
uncertainty inherent in the methodologies used to produce climate models;
uncertainty as to the impacts of climate change and the responses of natural systems; and
uncertainty in social and technological systems (for example, the rate and direction of technological
change).
The first three types of uncertainty were addressed in Chapter 2. Uncertainty in the Global
Circulation Models (GCMs), uncertainties about the impacts of climate change and uncertainties
about the responses of natural systems mean that while we understand the direction of future
change, it will often not be possible to predict accurately the magnitude and rate of the change, nor
its precise expression. Institutions must therefore be able to understand and work with uncertainty
and risk.
Whilst some institutions are very capable of managing uncertainty and risk, others fall back on a
‘predict and provide’ approach, which can offer an attractive appearance of certainty and which
readily translates into organisational goals and objectives (which are frequently short term). Whilst
prediction and provision are important tasks for any organisation, in that all must make plans for
the future, the term ‘predict and provide’ can denote a narrow approach that assumes a high
level of confidence in future predictions, and an assumption that the policy is simply to meet the
predicted circumstances irrespective of wider considerations.
The nature of the challenge is illustrated in Figure 4-I, which provides a schematic representation
of the different levels of understanding about any risk issue, based on knowledge about
the likelihood of occurrence and the probable outcomes. Those who make policy or investment
decisions often presume that a given problem falls into the top-left quadrant, where outcomes
or impacts are well defined and there is a reasonable basis for estimating probabilities using
traditional risk assessment, decision analysis and/or cost–benefit approaches. The issue is simply
one of managing risks.
Climate change does not, however, fall into this category. It may fall into the ‘uncertainty’,
‘ambiguity’ or even ‘ignorance’ quadrants in Figure 4-I according to understanding of likelihoods
and outcomes. With increasing uncertainty and lack of knowledge, different decision approaches
become important – from probabilistic risk modelling and sensitivity testing under conditions
of data and information uncertainty, through to scenario analysis under conditions of ambiguity
and more general horizon scanning and enhanced research under conditions of ignorance. High
levels of uncertainty are the main reason why a crude ‘predict and provide’ model of adaptation
response, where predictions are in the form of precise forecasts of, say, future rainfall patterns,
may not be helpful for policy making.
ii We use the term ‘uncertainty’ in the broad sense as defined by the Oxford English Dictionary: The quality of
being uncertain in respect of duration, continuance, occurrence, etc.; the quality of being indeterminate as to the
magnitude or value.
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