Abstract
AbstractSatellites provide a global view of the structure in the fields that they measure. In the mesosphere and lower thermosphere, the dominant features in these fields at low zonal wave number are contained in the zonal mean, quasi‐stationary planetary waves, and tide components. Due to the nature of the satellite sampling pattern, stationary, diurnal, and semidiurnal components are aliased and spectral methods are typically unable to separate the aliased waves over short time periods. This paper presents a data processing scheme that is able to recover the daily structure of these waves and the zonal mean state. The method is validated by using simulated data constructed from a mechanistic model, and then applied to Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature measurements. The migrating diurnal tide extracted from SABER temperatures for 2009 has a seasonal variability with peak amplitude (20 K at 95 km) in February and March and minimum amplitude (less than 5 K at 95 km) in early June and early December. Higher frequency variability includes a change in vertical structure and amplitude during the major stratospheric warming in January. The migrating semidiurnal tide extracted from SABER has variability on a monthly time scale during January through March, minimum amplitude in April, and largest steady amplitudes from May through September. Modeling experiments were performed that show that much of the variability on seasonal time scales in the migrating tides is due to changes in the mean flow structure and the superposition of the tidal responses to water vapor heating in the troposphere and ozone heating in the stratosphere and lower mesosphere.
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