Tidal influence on midlatitude airglow: Comparison of satellite and ground-based observations with TIME-GCM predictions

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Meteorology And Atmospheric Dynamics: Mesospheric Dynamics

Scientific paper

WINDII, the Wind imaging interferometer on the Upper Atmosphere Research Satellite measures winds and emission rates from selected excited metastable species. Measurements of the 558-nm emission from atomic oxygen provide both the wind from the Doppler shift, and the atomic oxygen concentration from the emission rate. Thus the tides and their influence on atomic oxygen are measured with the same instrument. Ground-based airglow measurements provide vertical integrals of the same quantities and coordinated observations were obtained between WINDII and ground-based instruments at Bear Lake (42.5°N, 212°E) for O(1S)558nm winds and O2(b1Σ) (0,1) band emission rate and temperature. The TIME-GCM model has recently incorporated airglow photochemistry, so that direct comparisons may be made with airglow observations, without inverting those observations to atomic oxygen distributions. In this study, the influence of tides on air-glow emission at midlatitude is studied through the comparison of the above data sets with the TIME-GCM model, extending earlier studies conducted for the equatorial region. At the vernal equinox the upward propagating diurnal tide is found to be the dominant influence on airglow diurnal variation. At solstice the diurnal tide does not penetrate to as high an altitude, so that the dominant influence is then the in situ semidiurnal tide. This conclusion is consistent with both WINDII observations and TIME-GCM predictions, whose data sets agree extremely well with one another. The ground-based results agree well in the local time variation pattern, but the amplitudes observed are larger than for WINDII or the TIME-GCM by roughly a factor of 2. This difference illustrates very clearly the differences between a tidal pattern observed at a single site for a few nights, and a global pattern that is first zonally averaged, and then combined in local time over about 1 month, as is done with the WINDII data. The agreement of these averaged data with the TIME-GCM model strongly suggests that they accurately represent the behavior of the zonally averaged atmosphere.

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