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Understanding radioxenon time series and being able to distinguish anthropogenic from nuclear explosion signals are fundamental issues for the technical verification of the Comprehensive Nuclear-Test-Ban Treaty. Every radioxenon event categorisation methodology must take into account the background at each monitoring site to uncover anomalies that may be related to nuclear explosions. Feedback induced by local meteorological patterns on the equipment and on the sampling procedures has been included in the analysis to improve a possible event categorisation scheme. The occurrence probability of radioxenon outliers has been estimated with a time series approach characterising and avoiding the influence of local meteorological patterns. A power spectrum estimator for radioxenon and meteorological time series was selected; the randomness of the radioxenon residual time series has been tested for white noise by Kolmogorov–Smirnov and Ljung–Box tests. This methodological approach was applied to radioxenon data collected at two monitoring sites located at St. John’s, Canada and Charlottesville, USA, equipped with two different noble gas systems. It shows different feedback with local meteorological patterns and randomness for the radioxenon data recorded at the selected sites of St. John’s and Charlottesville as well as a different occurrence probability of the outliers in the normalized radioxenon original and residual time series.