To cope with a large-scale introduction of renewables into power systems, it is important to understand the reduction of variability in the aggregated generation or the so-called smoothing effect. Knowledge of the degree of smoothing is used for assessing the potential impact of intermittent generation on the power system operation. Here, smoothing effects of aggregated wind power are assessed around Trondheim, Norway, by applying a recently proposed smoothing index based on the so-called Koopman Mode Decomposition (KMD). The method is shown to effectively decompose complex time-series of wind power outputs into a finite number of modes, each of which oscillates with a single frequency for all locations (or hypothetical wind farms). It is shown that the method is able to reconstruct the original power outputs well by only a small number of modes that retain the variability of the original time-series, and is able to provide a relevant quantification of the smoothing effects for each individual frequency (or mode).