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Winsberg’s argument is closely linked to the concept of the Uncertainty Quantification that exists in the science of global climate models predict. According to him, Uncertainty Quantification is the most important method of knowledge communication among the policy-makers and specialists in a manner that was intended to be independent of the ethical and social influences within the community. Winsberg argues that in the area of climate modeling, the standard pattern of using probabilities for the separation of scientific practices from the ethical and social influences because of the significant complexity of these global climate models (111). To be more precise, the standard approach towards dealing with the science-related ethical or social values will not be appropriate in the framework of the Global climate models.
Uncertainty Quantification in Climate Science
The Uncertainty Quantification (UQ) problem in climate science means creating quantitative estimates about the various levels of uncertainty that surround the sphere of climate science. Since UQ is one of the most significant tools in communicating knowledge among policymakers and scientists, its role in climate science is indisputable. However, there is also an existing dichotomy between the view that since scientists possess knowledge about the climate, they should be the primary policymakers in climate issues and the view that they should only be responsible for the science behind the climate changes (Winsberg 112). Thus, while society wants the decisions made by the professionals, it also recognizes that the interests of the society should be accounted for.
Probabilities for Hypothesizing Potential Climate Change
Winsberg outlines the argument proposed by Richard Jeffrey that the main role of a scientist is to create the pattern of probabilities that will hypothesize the future events on the basis of the evidence that is already available. Then, policy-makers will be able to examine possible results and decide on further actions (Winsberg 115). To counter this argument, Winsberg claims that Jeffrey had come to such a conclusion with only one hypothesis for the scientists to make, while in reality, climate change predictions are linked to assigning the distributions of probability over an array of possible results.
The uselessness of probability in hypothesizing aspects of possible changes in climate also stems from the fact that the climate models usually have similarities in their history that are very complicated to distinguish. Because of this, and because of some models sharing the same code, there is doubt about the way already existing climate models are distributed at random.
BRDC and Climate Change Models
The modern models of global climate change are complicated and complex as they are the direct result of a significant amount of scientific work as well as they come from a long sequence of methodological choices, the effect of which cannot be disputed. Because of these factors, the use of the Bayesian response to the Douglas challenge (BRDC) is very hard to apply in the sphere of Global climate change prediction. BRDC implies that the influence of social and ethical values is possible to be separated with the help of the expert judgment, a factor that should be applied in the risk profiling method.
The features of the global climate models outlined above make the idea that every separate scientific agent will possess the quality of having a judgment for RRDC implementation implausible (Winsberg 129).