Energy Flux and Wavelet Diagnostics of Secondary Mountain Waves

Bryan K. Woods Yale University, New Haven, Connecticut

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Ronald B. Smith Yale University, New Haven, Connecticut

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Abstract

In recent years, aircraft data from mountain waves have been primarily analyzed using velocity and temperature power spectrum and momentum flux estimation. Herein it is argued that energy flux wavelets (i.e., pressure–velocity wavelet cross-spectra) provide a more powerful tool for locating and classifying different types of mountain waves. In the first part of the paper, pressure–velocity cross-spectra using various linear mountain-wave solutions are shown to be capable of disentangling collocated waves with different propagation directions and wavelength. A field of group velocity vectors can also be determined.

In the second part, the energy flux wavelet technique is applied to five cases of mountain waves entering the stratosphere from the Terrain-Induced Rotor Experiment (T-REX) in 2006. Perturbation pressure along the flight track is determined using aircraft static pressure corrected hydrostatically with GPS altitude. In four of the cases, collocated long up-propagating and short down-propagating waves are seen in the stratosphere. These waves have strong, but opposite, pw′ cospectra. In one of these cases, a patch of turbulence is collocated with the up and down waves. In two other cases, trapped waves riding on the tropopause inversion layer (TIL) are seen. These trapped waves have pw′ quadrature spectra that reverse sign across the tropopause. These newly discovered wave types may arise from secondary wave generation (i.e., a nonlinear transfer of energy from the long vertically propagating waves to shorter modes).

Corresponding author address: Bryan K. Woods, Yale University, KGL 106D, P.O. 208109, New Haven, CT 06520–8109. Email: bryan.woods@yale.edu

This article included in the Terrain-Induced Rotor Experiment (T-Rex) special collection.

Abstract

In recent years, aircraft data from mountain waves have been primarily analyzed using velocity and temperature power spectrum and momentum flux estimation. Herein it is argued that energy flux wavelets (i.e., pressure–velocity wavelet cross-spectra) provide a more powerful tool for locating and classifying different types of mountain waves. In the first part of the paper, pressure–velocity cross-spectra using various linear mountain-wave solutions are shown to be capable of disentangling collocated waves with different propagation directions and wavelength. A field of group velocity vectors can also be determined.

In the second part, the energy flux wavelet technique is applied to five cases of mountain waves entering the stratosphere from the Terrain-Induced Rotor Experiment (T-REX) in 2006. Perturbation pressure along the flight track is determined using aircraft static pressure corrected hydrostatically with GPS altitude. In four of the cases, collocated long up-propagating and short down-propagating waves are seen in the stratosphere. These waves have strong, but opposite, pw′ cospectra. In one of these cases, a patch of turbulence is collocated with the up and down waves. In two other cases, trapped waves riding on the tropopause inversion layer (TIL) are seen. These trapped waves have pw′ quadrature spectra that reverse sign across the tropopause. These newly discovered wave types may arise from secondary wave generation (i.e., a nonlinear transfer of energy from the long vertically propagating waves to shorter modes).

Corresponding author address: Bryan K. Woods, Yale University, KGL 106D, P.O. 208109, New Haven, CT 06520–8109. Email: bryan.woods@yale.edu

This article included in the Terrain-Induced Rotor Experiment (T-Rex) special collection.

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