High resolution, long and reliable rainfall time series are extremely important to assess reliable statistics, e.g. the Depth-Duration-Frequency curves that have been widely used to define design rainfalls and rain- fall drainage network dimensioning. The potential consequences of changes in measuring and recording techniques have been somewhat discussed in the literature with respect to a possible corresponding introduction of artificial inhomogeneities in time series. In this paper, we show how to detect another artificiality: most of the rainfall time series have a lower recording frequency than that is assumed, fur- thermore the effective high-frequency limit often depends on the recording year due to algorithm changes. This question is particularly important for operational hydrology, because we show that an error on the effective recording high frequency introduces biases in the corresponding statistics. We developed a simple automatic procedure to assess this frequency period by period and station by station on a large database. The scaling analysis of these time series also shows the influence of high frequency limitations on the scaling behaviour, leading to possible misinterpretation of the significance of characteristic scales and scale-dependent hydrological quantities.