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Scientific data sets generated by numerical simulations or experimental measurements often contain a substantial amount of noise. Smoothing the data removes noise but can have potentially drastic effects on the qualitative nature of the data, thereby influencing its characterization and visualization via topological analysis, for example. We propose a method to track topological changes throughout the smoothing process. As a preprocessing step, we oversmooth the data and collect a list of topological events, specifically the creation and destruction of extremal points. During rendering, it is possible to select the number of topological events by interactively manipulating a merging parameter. The result that a specific amount of smoothing has on the topology of the data is illustrated using a topology-derived transfer function that relates region connectivity of the smoothed data to the original regions of the unsmoothed data. This approach enables visual as well as quantitative analysis of the topological effects of smoothing.