Sea Ice

After building the consistency matrix the task is to find all possible projection
bundles and evaluate their overall consistency. The overall consistency value
it the sum of the paired consistency values of a projection bundle. The overall
consistency value of a projection bundle is the main feature used to interpret the
quality of such a bundle. A projection bundle with a high consistency value is a
good basis for a final scenario.
Other parameters to interpret the goodness of a projection bundle are:
The average consistency value, is the consistency value of a projection bundle
divided by the number of future projections contained in the bundle. If this
value close to the upper limit of the range of consistency values the bundle is very
consistent, and therefore a good candidate for a final scenario. The average consistency value is especially helpful to compare projects containing different numbers of key factors, because independently from the project it ranges between the lower and upper limit of paired consistency values.
The number of total inconsistencies. A projection bundle might carry a
very high overall consistency value, but at the same time contain one or more
total inconsistencies, i.e. the lowest possible paired consistency value for two future
projections. If any total inconsistency occurs the projection bundle must be
dropped, because a projection bundle containing a total inconsistency is inconsistent
itself. ScenLab drops projection bundles containing total inconsistencies
automatically.
The number of partial inconsistencies. These are very low paired consistency
values. A projection bundle with a high overall consistency but with too
many of partial inconsistencies might be doubtful. How many partial inconsistencies
per projection bundle are acceptable depends on the structure of set of
projection bundles. If there are many projection bundles without any partial
inconsistencies the projection bundles with partial consistencies should not be
considered at all. But is the number of projection bundles with no partial inconsistencies is low it might be useful to consider projection bundles with one or two
partial inconsistencies as well.
The overall plausibility of a projection bundle is derived by multiplying the
plausibility values of the future projections contained in a given projection bundle.
The value of the overall plausibility ranges from zero to (technically) one, but
usually the highest overall plausibility is significantly smaller than one. Hence,
down to what value a projection bundle is considered to be plausible depends on
the highest overall plausibility value found in a project.
Example 4 (Overall plausibility)
If the plausibility values of the three future projections contained in a bundle are
0.3, 0.45 and 0.1 respectively, then the overall plausibility of the bundle will be
0.3 · 0.45 · 0.1 = 0.0135.
One can already see that the overall plausibility values of a projection bundle
usually is a very small number.
The robustness. The robustness is an indicator of the quality of a projection
bundle unique to ScenLab. It is a combination of the plausibility value, consistency
value and the number of partial inconsistencies of a projection bundle. It will be
discussed further in Subsection 7.