Lisø PhD Dissertation Manuscript - NTNU

LisÖ
In this context, a system can be the whole built environment,
clusters of buildings in a defined geographical
area or just a single building. Vulnerability and adaptation
are also discussed by Lisø et al. (2003). In
1999, the government appointed an official committee
to review Norway’s social vulnerability and disaster
preparedness (NOU, 2000, p. 21). Its report defines
vulnerability as follows:
‘Vulnerability’ expresses the problems a system
will have functioning when exposed to an undesirable
incident, and also the problems the system
experience when trying to resume its activities
after the occurrence of an undesirable event. Vulnerability
is identified with a possible loss of
value. The system can in this context be a state,
the national power supply, an industry or enterprise
or a single computer system. Vulnerability
is to a large degree self-inflicted. It is possible to
influence the degree of vulnerability, to limit
and reduce it.
(translated from Norwegian)
The latter definition is far more general than the IPCC
definition, which is limited to the threats of climate
change. The NOU definition of vulnerability embraces
all problems a system could encounter. However, they
are both appropriate starting points for discussions on
adaptive measures and strategies.
Bayesian approach
A classical approach to risk and risk analysis requires
well-defined data on the probability of occurrence
and the extent of impacts. Obviously, this is not the
case facing the unknown risks of future climate
change. A complementary approach to the riskbased,
precautionary and discursive strategies
described in this paper could be to employ Bayesian
methods. Bayesianism, named after the British mathematician
Thomas Bayes (1702–61), is the philosophical
principle that the mathematical theory of
probability applies to the degree of plausibility of statements,
or to the degree-of-belief of rational agents in
the truth of statements. The starting point of Bayesian
methods is the same as in all risk analysis, as it is
assumed that there exists an underlying true risk.
This risk is unknown, and subjective probability distributions
are used to express uncertainty about where
the true value lies (Aven, 2003). That is, a Bayesian
approach to risk allows for degree-of-belief interpretations
of mathematical probability. The Bayesian
approach is a systematic way of combining prior information
or belief in a statement and empirical observations.
Hence, a Bayesian analysis is a way to use
information to update prior beliefs. However, one
could assert that all probabilistic arguments in fact
are Bayesian, except, of course, in trivial instances
such as throwing dice. Projections of future climate
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risks that were made before global warming was recognized
were based on the belief that future climatic
impacts would be approximately the same as the past
(e.g. as when using historical climate data in the
design of buildings).
Aven (2003) provides a thorough description of a predictive
approach to Bayesian analysis.
Introducing risk-based management
strategies
Institutional capacity
To cope with actual and potential changes in climate
and climate variability, it is necessary that affected
institutions have the organizational and technological
capacity and human resources needed to combat
these challenges. The full range of impacts resulting
from climate change is still uncertain, but it is becoming
increasingly clear that adaptation to climate
change is necessary within several sectors (Lisø et al.,
2003). Adaptation to severe climate conditions has
always been crucial for the viability of Norwegian
society. However, both the functionality of the existing
built environment and the design of future buildings
are likely to be altered, and areas of vulnerability in
the construction industry must be identified (e.g.
changes in the decay rate of materials and structures
due to changes in temperatures and precipitation patterns).
These issues need to be considered by all
actors (on all levels) involved in the design, construction
and geographical localization of buildings, challenging
the capacity and cooperative abilities of
institutions to effect the necessary adaptation
measures.
Government regulatory measures
Ways to strengthen institutional capacity to implement
appropriate building performance requirements and
standards, and thus reducing the sensitivity of the
built environment, is an important element in adaptation
to climate change (Lisø et al., 2003). Spence
(2004) examines national policies of risk mitigation
and states that improved government action and regulation
can contribute to the reduction of impacts from
natural disasters. The most important government
regulatory measure to ensure adherence to building
codes and standards is the Technical Regulations
under the Norwegian Planning and Building Act,
which since 1997 have been performance-based. The
principal motive for a transition from a prescriptive
code to a performance-based code in Norway was to
contribute to an increase in the quality of buildings
and a reduction of the amount of building defects. Preliminary
findings from a case study of process-induced
building defects suggest that the adoption of a performance-based
building code has indeed led to a positive