Measurements of the effects of gravity waves in the middle atmosphere using parametric models of density fluctuations. Part I: Vertical wavenumber and temporal spectra

Parametric models of spectral analysis offer several distinct advantages ov er statistical methods such as the correlogram analysis. These advantages i nclude higher spectral resolution and the ability, in principle, to separat e correlated (i.e., wave) behavior from noise-driven (i.e., turbulent) beha vior in the measurements. Here parametric models are used to highlight the spatial and temporal intermittency of the gravity wave spectrum. In Part II of this series the spatial and temporal spectrum are used to calculate ene rgy dissipation and the eddy diffusion coefficient. The spectra are compute d from measurements of density fluctuations obtained using a large power-ap erture product lidar during a 6-h period on 30 August 1994. It is shown tha t parametric models provide an excellent representation of the temporal and spatial data series. One difficulty of parametric models is selecting the model order, an analogous situation to determining the proper lag in the co rrelogram procedure or the window length in the periodogram method. Extensi ve experimentation has shown that the ratio of the data matrix eigenvalues to the photon noise eigenvalues is an excellent indicator for the selection of the model order. The underlying spectral form found using the parametri c models is similar to the standard correlogram method, that is, nominal un derlying spatial and temporal spectral slopes between -2 and -4 and -1.25 a nd -2, respectively, with variability outside this range. The spatial-tempo ral behavior of the spectra is highly variable with numerous intermittent a nd intense features rising well above the photon noise floor. The vertical wavenumber spectra on this night may show a variation of spectral slope wit h height; however, the slope is both extremely sensitive to the noise level of the data, steepening as the signal-to-noise level increases, and highly variable in time. The temporal spectra also show considerable variation wi th height, both in magnitude and slope.