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Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods
Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods
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Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods
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Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods
Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods

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Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods
Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods
Journal Article

Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods

2020
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Overview
Gravity waves are important drivers of dynamic processes in particular in the middle atmosphere. To analyse atmospheric data for gravity wave signals, it is essential to separate gravity wave perturbations from atmospheric variability due to other dynamic processes. Common methods to separate small-scale gravity wave signals from a large-scale background are separation methods depending on filters in either the horizontal or vertical wavelength domain. However, gravity waves are not the only process that could lead to small-scale perturbations in the atmosphere. Recently, concerns have been raised that vertical wavelength filtering can lead to misinterpretation of other wave-like perturbations, such as inertial instability effects, as gravity wave perturbations. In this paper we assess the ability of different spectral background removal approaches to separate gravity waves and inertial instabilities using artificial inertial instability perturbations, global model data and satellite observations. We investigate a horizontal background removal (which applies a zonal wavenumber filter with additional smoothing of the spectral components in meridional and vertical direction), a sophisticated filter based on 2D time–longitude spectral analysis (see Ern et al., 2011) and a vertical wavelength Butterworth filter. Critical thresholds for the vertical wavelength and zonal wavenumber are analysed. Vertical filtering has to cut deep into the gravity wave spectrum in order to remove inertial instability remnants from the perturbations (down to 6 km cutoff wavelength). Horizontal filtering, however, removes inertial instability remnants in global model data at wavenumbers far lower than the typical gravity wave scales for the case we investigated. Specifically, a cutoff zonal wavenumber of 6 in the stratosphere is sufficient to eliminate inertial instability structures. Furthermore, we show that for infrared limb-sounding satellite profiles it is possible as well to effectively separate perturbations of inertial instabilities from those of gravity waves using a cutoff zonal wavenumber of 6. We generalize the findings of our case study by examining a 1-year time series of SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) data.