Understanding Mountain Waves Using Wavelet Analysis

During the Terrain-Induced Rotor Experiment (T-REX) field campaign of March and April 2006, the new NCAR High-performance Airborne Platform for Environment Resarch (HIAPER) Gulfstream V aircraft was used to observe mountain waves in the upper troposphere and lower stratosphere. The introduction of fast-response Differential GPS allowed for the measurement of key atmospheric properties such as energy and momentum fluxes. Such analysis has not previously been possible using aircraft data in gravity wave experiments. The computed gravity wave vertical energy fluxes revealed a surprising vertical energy flux reversal in the stratosphere during one of the flights. In previous work, the linear relationship between momentum and energy fluxes, analytically predicted for gravity waves by Eliassen and Palm, was confirmed. Wavelet techniques were employed to document spatial and spectral properties of mountain waves. Wavelet cross-spectrum techniques allowed for the isolation of packets of up-going and down-going energy. Wavelet cospectra were used to examine the energy transport of propagating waves while quadrature spectra were used to examine trapped waves.

In addition to previous work focusing exclusively on aircraft data, we examined both linear and non-linear numerical simulations. Wavelet analysis of model output provided theoretical expectations for wavelet signatures of mountain waves. T-REX numerical model intercomparison experiments were investigated to document mountain wave signatures in operational numerical models. The results from the wavelet analysis of the numerical experiments were used as the basis for our analysis of in-situ aircraft data.

Wave properties over the Sierra Nevada were analyzed for twelve cases with cross-barrier flow. Surprisingly down-going gravity waves were found to be nearly as common as up-going waves in the wavelet analysis. Additional investigation has revealed at least three more cases of down-going waves produced from secondary wave generation collocated with vertically propagating mountain waves. Large amplitude vertically propagating waves were found to commonly to be superposed with a down-going wave in the same location. Down-going waves were also sometimes stronger than up-going mountain waves in their wavelet power. Energy flux signatures of vertically propagating waves, trapped waves, and down-going waves were shown have unique signatures that allow for classification of wave packets on the basis of their associated vertical and horizontal energy fluxes.