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Atmospheric waves are a key driving mechanism for the circulation in the Earth's atmosphere. Such waves covervarious spatial and temporal scales, e.g., planetary waves with periods of several days, atmospheric tides with periods of aninteger fraction of a day and gravity waves with periods ranging from minutes to several hours. In particular, atmospheric tidesgain large amplitudes at the Mesosphere/lower Thermosphere (MLT) region. Recently the day-to-day tidal variability as driverof the thermosphere-ionosphere system become an emerging topic. Here we study the intermittent behavior of atmospheric tides by using meteor radars at altitudes of 75-110 km accompanied with lidar measurements. The observations are comparedto meteorological analyses from NAVGEM-HA to infer how well the tidal variability on a daily to a seasonal basis is capturedin the model. Therefore, a new diagnostic approach, a so-called adaptive spectral filter, is used to decompose the time seriesinto a mean wind (zonal and meridional component) and temperature containing the planetary wave activity, atmospheric tides(diurnal, semi-diurnal and terdiurnal) as well as the gravity wave activity. By combining the local data with global reanalysis fields, we extract the relative contribution of the migrating and non-migrating tides for the available data using a global versionof the adaptive spectral filter. Our results indicate that the SW2 tide, which is the dominant mode at mid- and high latitudes at theMLT, shows a large seasonal variability in amplitude and phase. The comparison of NAVGEM-HA results and the meteor radarobservations demonstrate that the reanalysis data reproduce rather consistent the mean seasonal behavior as well as the day-to-day variability. This is especially obvious during sudden stratospheric warmings, where the SW2 tide shows a significant phase shift and amplitude modulation. These findings show the benefit of combining global high altitude data assimilation productswith ground-based observations of the MLT region to better understand the tidal variability in the atmosphere. [ABSTRACT FROM AUTHOR]