Uncertainty
Uncertainty is a lack of certainty, a state of having limited knowledge where it is impossible to exactly describe the existing state, a future outcome, or more than one possible outcome. In the case of climate change, uncertainty becomes important with regard to predictions of climate regimes in certain areas. It is not sure how temperature raises and precipitation develops in terms of droughts and floods occurring in different areas. On the other side, the further development of greenhouse gas emissions, technology and the human population is nearly unpredictable. Additionally, the reaction of natural systems on interferences is not clearly known jet. The high complexity of climate relations globally is further adding to the problem.
The handling of uncertainty in climate change is mostly done by scenarios. These are models of possible outcomes dependent on the progress of various factors. Moreover, a multidisciplinary approach within science with a connection to relevant political, private and civil institutions should be achieved. Broad-based and transparent communication of changes and threats is important to gain understanding and action by the people. Important capabilities herein are flexibility to react, visionary thinking for innovative ideas, directivity as well as thinking in a long-term perspective.
The risk of climate variability in water and agriculture addresses food security for the population and the livelihoods of rural communities. Hereafter we focus mainly on water-related impacts of climate change in the following.
Scenario Analysis
Scenario analysis is a common tool used to lower uncertainties. Herein some possible scenarios are analyzed in comparison.
Changes in complex systems and the important input factors are often only partly sizeable. Scenarios can assist in projecting possible outcomes by starting on the current base and giving various pathways on the base of most plausible estimations. The margin of discretion is displayed by the scope of several scenarios. Information for scenario development can be quantitative as well as qualitative data.
The selection of scenarios for an analysis should pay regard to the following principles:
- Limited number: the set of scenarios should be as small as possible
- Comprehensive: the framework needs to cover sufficiently different future development to represent a plausible range of assumptions and thus represent relevant uncertainties
- Comparability: the scenario set should make it possible for some research knowledge generated in one community to be compared with information generated in another
- Multi-scale: the storylines should provide enough explicit information on the aggregated scale to be clearly distinguishable also at finer scales. Similarly, storylines and scenarios should embrace near-term and long-term future conditions; the former providing linkages to ongoing trends and planning horizons, and the latter accommodating plausible large-scale divergences in key driving factors
- Structured but flexible: The scenario set should provide enough structure to facilitate consistency, but also offer flexibility for defining relevant details
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