Uncertainty.
This section lists problem-factors and thinking-traps that this process can address. In general, addressing the issue requires the issue to be filtered through the processes of self-awareness qv and open-mindedness qv.
?? Avoid temptation to do nothing just because probability and underconfidence (uncert?) don't allow certainty that action would always work.
significant results
robustness of actions across range of RVs and models (iterate if not)
Relationship with Other Components.
Further reading.
Quote: A man with a watch knows what time it is. A man with two watches is never sure. Segal's Law.
Assess SD (systems-thinking qv) effects. Will bad things always happen, or only in limited circumstances? Can also test implications of assumptions being wrong (really??).
Link to complex-behaviour qv and probability qv (incl risk management?): sensitivity can be used to assess range of results possible given probabilistic inputs.
May require iteration of systems-thinking qv and optimisation qv to assess sensitivity.
If one set of actions gives widely differing results given different values of random variables in the model, confidence in those actions should be low; consider a different approach or diversify and/or adapt.
has been used for uncertainty (rather than just probability qv), but validity of this has been contested (PhD p. 32).
"ensembles" of forecasts based on differing initial conditions are used to give forecasters a feel for the how likely any particular prediction is. Instead of one forecast, there are many. [Spiegelhalter p.308]
scenario-based-planning qv is related but much broader (and often unquantifiable).
Do this after significance qv, because there's no point assessing sensitivity of a random occurrence.
"...instead of trying to make our responses just right for the climate of the future we should seek out resilient and flexible solutions, remedies that will be robust in a wide range of possible climate outcomes."