10.1.4.4 Computational, Multiscenario Simulation Approaches
Computational, multiscenario simulation is a new analytic approach to the assessment
of climate change policy. Bankes (1993), Lempert et al. (1996), and Laitner
and Hogan (2000) have employed this approach, as have Morgan and Dowlatabadi
(1996), van Asselt and Rotmans (1997), and, to some extent, Yohe (1996). Also,
the IPCC Special Report on Emissions Scenarios (IPCC, 2000b) presented a large
set of very different baseline scenarios. The basic idea is to use computer
simulation models to construct a range of a large number of fundamentally different
scenarios of the future and, instead of aggregating the results using a probabilistic
weighting, make policy arguments from comparisons of fundamentally different,
alternative cases. These methods are most useful under conditions of deep uncertainty.
For example, when we do not have reliable information or widespread agreement
among the stakeholders about the system model, the prior probability distributions
on the parameters of the system model, and/or the loss function to use in evaluating
alternative outcomes (Lempert and Schlesinger, 2000).
These multiscenario simulation approaches offer the promise of a powerful synthesis
between the narrative, process-oriented methods of scenario-based planning (Schwartz,
1996; van der Heijden, 1996) and quantitative tools such as decision analysis,
game theory, and portfolio analysis. From the quantitative methods, multiscenario
simulation draws systematic methods of handling large quantities of data and
normative descriptions of good decisions. From scenario-planning, multiscenario
simulation draws the insight that multiple views of the future are crucial to
allow groups to transmit and receive information about highly uncertain futures.
Also scenario planning shows that groups can often agree on actions to take
in the face of deep uncertainty without agreeing on the reasons for these actions
(Lempert and Schlesinger, 2000). For instance, multiscenario simulation can
adopt a meaningful cost–benefit framework for climate change, but at the
same time acknowledge the deep uncertainty and differing values among stakeholders.
These make it impossible to fully quantify the costs and benefits or to assign
widely accepted probabilities to many of the key outcomes of interest. Such
computational, multiscenario simulations are enabled by new computer technology–primarily
large quantities of inexpensive memory; fast, networked processors; and powerful
visualization tools–and are only just becoming available.
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