Support for addressing the on-going global changes needs solutions for
new scientific problems which in turn require new concepts and tools. A
key issue concerns a vast variety of irreducible uncertainties,
including extreme events of high multidimensional consequences, e.g.,
the climate change. The dilemma is concerned with enormous costs versus
massive uncertainties of extreme impacts. Traditional scientific
approaches rely on real observations and experiments. Yet no sufficient
observations exist for new problems, and "pure" experiments, and
learning by doing may be expensive, dangerous, or impossible. In
addition, the available historical observations are often contaminated
by past actions, and policies. Thus, tools are presented for the
explicit treatment of uncertainties using "synthetic" information
composed of available "hard" data from historical observations, the
results of possible experiments, and scientific facts, as well as "soft"
data from experts' opinions, and scenarios.