Boundary-Layer Meteorology

, Volume 119, Issue 2, pp 339–374 | Cite as

Maximal Overlap Wavelet Statistical Analysis With Application to Atmospheric Turbulence

  • Charles R. Cornish
  • Christopher S. Bretherton
  • Donald B. Percival


Statistical tools based on the maximal overlap discrete wavelet transform (MODWT) are reviewed, and then applied to a dataset of aircraft observations of the atmospheric boundary layer from the tropical eastern Pacific, which includes quasi-stationary and non-stationary segments. The wavelet methods provide decompositions of variances and covariances, e.g. fluxes, between time scales that effectively describe a broadband process like atmospheric turbulence. Easily understood statistical confidence bounds are discussed and applied to these scale decompositions, and results are compared to Fourier methods for quasi-stationary turbulence. The least asymmetric LA(8) wavelet filter yields coefficients that exhibit better uncorrelatedness across scales than the Haar filter and is better suited for decomposition of broadband turbulent signals. An application to a non-stationary segment of our dataset, namely vertical profiles of the turbulent dissipation rate, highlights the flexibility of wavelet methods.


Analysis of variance Marine boundary layer Turbulence Wavelet 



Analysis of Variance


Discrete Wavelet Transform


Equivalent Degrees Of Freedom


Least Asymmetric


Maximal Overlap Discrete Wavelet Transform


Power Spectral Density


Sea Surface Temperature


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Copyright information

© Springer 2006

Authors and Affiliations

  • Charles R. Cornish
    • 1
  • Christopher S. Bretherton
    • 1
  • Donald B. Percival
    • 2
  1. 1.Department of Atmospheric ScienceUniversity of WashingtonSeattleU.S.A
  2. 2.Applied Physics LaboratoryUniversity of WashingtonSeattleU.S.A

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