Content: In climatic time-series (atmospheric and sea surface temperature, sea level, atmospheric pressure, etc.), variability ranging from hours, days, months, seasons to several years can be detected. The present study discusses the application of symmetric digital filters, especially designed for daily time-series, such as the atmospheric temperature of the Observatory of Igueldo (1928-2012), to suppress variability with periods of less than a given period. The results of the spectral analysis show that the application of the filter, in time-series with a low proportion of gaps (less than 1%), permits to eliminate the variability below the cut-off period, with a low computational cost. However, the length of the window required for the digital filtering is relatively long (between 3 and 5 times the cut-off period). This leads to loss of information at the beginning and at the end of the time-series.