A wave‐number frequency wavelet analysis of convectively coupled equatorial waves and the MJO over the Indian Ocean

2021

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Stratospheric Kelvin waves are often understood as plane gravity waves, yet tropospheric Kelvin waves have been interpreted as a superposition between the baroclinic modes. Fourier filtering is used to decompose the ECMWF‐Interim reanalysis dynamical fields into upward and downward propagating components. Then wavelet regression is used to isolate the propagating Kelvin waves over the Indian Ocean across different speeds at zonal wavenumber 4. Results for fast waves show dry upward‐phase signal in the troposphere, while downward‐phase Kelvin waves occupy most of the stratosphere. The presence of upward‐phase tilted waves in the troposphere suggests that the tropospheric Kelvin wave is not a superposition of the upward and downward components, as one might expect in a normal mode. We found that propagating Kelvin waves in the troposphere obey gravity wave dynamics with geopotential height in phase with the zonal wind, the vertical velocity out of phase with the zonal wind, and the temperature in quadrature with the zonal wind. Both dry and moist tropospheric Kelvin waves show a westward vertical tilt, suggesting that tilt probably cannot be a superposition between baroclinic modes coupled to convective and stratiform heating. In the context of radiating gravity waves, results suggest that faster tropospheric Kelvin waves appear to be associated with higher Brunt–Väisälä frequencies, and waves maintain similar vertical tilt across a wide range of phase speeds.

Section: Methodsmentioning

confidence: 99%

Upward and downward atmospheric Kelvin waves over the Indian Ocean

Shaaban

2021

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“…To determine meridional movement, partial meridional–temporal Morlet wavelets, wavelet transforms, and power are calculated in a manner similar to Gahtan and Roundy (2020). As in Roundy (2018), we use the real portion of the Morlet wavelet. Partial meridional–temporal Morlet wavelets are given by:

ψ false(y, t false) = \frac{1}{γ} \cos false(2 π false(ly - F_{c} t false) false) \exp (\frac{- y^{2}}{G_{By}} + \frac{- t^{2}}{G_{Bt}}),

where y is the latitudinal grid point, t is the time step (which ranges from −96 to 96 days), l is the meridional wave number (with harmonics of 180° latitude), F c is the frequency (with harmonics of 96 days), and

γ = \sum_{y = 0}^{ny - 1} \sum_{t = - τ_{\max}}^{τ_{\max}} \exp (\frac{- y^{2}}{G_{By}} + \frac{- t^{2}}{G_{Bt}})

is the normalization factor.…”

Section: Methodsmentioning

confidence: 99%

“…To determine meridional movement, partial meridional-temporal Morlet wavelets, wavelet transforms, and power are calculated in a manner similar to Gahtan and Roundy (2020). As in Roundy (2018), we use the real portion of the Morlet wavelet. Partial meridional-temporal Morlet wavelets are given by:…”

Section: Waveletsmentioning

confidence: 99%

Meridional movement of geopotential height anomalies in the subtropics and the relationship to the base‐state flow

Gahtan

2020

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Qualities of the meridional movements of geopotential height anomalies in the upper troposphere of the subtropics are analysed via wavelet analysis using a meridional–temporal partial Morlet wavelet. Results show that power, which represents increased presence or amplitude of waves with direct meridional movement, is increased in regions where the corresponding equatorial winds in the upper troposphere are westerly or weakly easterly. Furthermore, equatorward power is enhanced near subtropical jet exit regions whereas poleward power is enhanced in jet entrance regions. Regressions of upper‐tropospheric winds, geopotential height, and outgoing long‐wave radiation (OLR) against the wavelet transforms demonstrate that the wavelets are identifying signals with tropical–extratropical interactions that are connected to organized convection in the tropics. The relationship of power with background‐state flow characteristics, including the horizontal winds and shear, are evaluated. Instead of the zonal wind and meridional shear of the zonal wind (du/dy), both the meridional wind and the zonal shear of the meridional wind (dv/dx) appear to have a clearer relationship with the power. Power is favoured for waves whose movement is aligned in the same direction as the meridional wind, and reduced in the opposite direction. Additionally, power increases with increasing zonal shear of the meridional wind in the Northern Hemisphere and with decreasing zonal shear of the meridional wind in the Southern Hemisphere. Power in the equatorward direction is stronger than in the poleward direction and more heavily influenced by background flow characteristics. Furthermore, power for wavelets with smaller meridional and temporal scales tends to have a higher sensitivity to the background horizontal flow as compared to larger meridional and temporal scales.

“…To isolate meridionally moving features, we calculate partial wavelet transforms in time and latitude, operating on the normalized geopotential height data. We chose to use the real portion of the Morlet wavelet, similar to Roundy (). While using only the real portion of the Morlet wavelet prevents us from determining power on individual days, we can determine average power for groups of similar days to produce a comparable result while reducing the amount of computation needed.…”

Section: Methodsmentioning

confidence: 99%

“…Here, we use wavelet analysis to identify meridionally propagating features and calculate wave‐number‐frequency power spectra, comparable to similar analysis in the zonal direction (e.g. Kikuchi and Wang, ; Roundy, ; ; Kikuchi, ). Benefits of wavelet analysis include the ability to localize transforms in both time and space, which is essential for the identification of regional signals.…”

Section: Introductionmentioning

confidence: 99%

Wavelet isolation of meridionally moving geopotential height perturbations near the subtropics of eastern Africa and their relationship with the Madden–Julian Oscillation

Gahtan

2019

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Prior to the onset of convection over the western Indian Ocean for many Madden–Julian Oscillation (MJO) events, equatorward‐propagating upper tropospheric negative geopotential height anomalies are observed along the east coast of Africa. To identify these signals independently from the MJO, we calculate partial meridional‐temporal wavelet transforms averaged between 35 and 45°E and centred in the subtropics. During times when the amplitudes of MJO indices are strong and leading up to convective onset over the western Indian Ocean, increased wavelet power relative to the mean state is observed in the equatorward direction at intraseasonal time‐scales from both hemispheres. Regressions against groups of equatorward intraseasonal wavelet transform time series centred on negative anomalies in the subtropics show extratropical Rossby wave trains extending to the west across the Atlantic similar to signals previously observed leading up to the onset of Indian basin convection in composite MJO events. Compared to globally averaged mean‐state power spectra in the subtropics, increased equatorward propagation of upper tropospheric geopotential height anomalies occurs regionally near eastern Africa on intraseasonal time‐scales, which suggests that local mean‐state conditions, in addition to the MJO, may influence meridional wave propagation. Since these anomalies may in turn influence the onset of MJO convection over the western Indian Ocean and have higher local power, mean‐state conditions near the subtropics of eastern Africa may change the timing of the MJO.