The global climate change debate is so far focused on collection of information on climate change indicators by being mainly forced by what is known as man-made global warming. This is a consequence of the increasing levels of green-house gases in the atmosphere in particular carbon dioxide. Enormous amount of research were put to get “validated” data on the average global surface temperature. However, existing knowledge on the associated indicators (http://www3.epa.gov/climatechange/science/indicators/) is mainly qualitative with major uncertainties what regards the spatio-temporal accuracies and uncertainties. Validated quantitative data and associated up and down scaling besides being very difficult to get using Environment and Climate Assessment Studies and Models are neither globally available not straightforward to get, e.g. for example using the spatio-temporal archives of lake-catchment systems to retrieve the complex data on indicators (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2854826/pdf/ukmss-29587.pdf). Also, another key issue in quantitative studies is the type of base-line indicators that exist as reference framework for predicting the changes from “normal values”, i.e. how abnormal is abnormal in our observations? We are still left with considerable unknowns of the known unknowns while many new unknowns ars still remain to be known.