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Climate effect studies are currently of high interest to predict the impact of a changing climate. The results of such studies are used by decision makers as a basis for planning how to mitigate and adapt to the effects of expected climate changes. However, these studies require heavy computations on large sets of data in several steps. This combination of heavy computation and results being basis for important decisions makes it extremely important to have an efficient and well documented process for computations, to provide accurate results in an efficient way. In this paper, the authors describe the problem and present their DBS (Distribution Based Scaling) tailoring tool that has been implemented to support the process.
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