Denoising ozone concentration measurements with BAMS filtering


Journal Article

We propose a method for filtering self-similar geophysical signals infected by an autoregressive noise using a combination of non-decimated wavelet transform and a Bayesian model. In the application part, we consider separating the instrumentation noise from high frequency ozone concentration measurements sampled in the atmospheric boundary layer. The elicitation of priors needed to specify the statistical model in this application is guided by the well-known Kolmogorov K41-theory, which describes the statistical structure of turbulent high frequency scalar concentration fluctuations. © 2005 Elsevier B.V. All rights reserved.

Full Text

Duke Authors

Cited Authors

  • Katul, G; Ruggeri, F; Vidakovic, B

Published Date

  • July 1, 2006

Published In

Volume / Issue

  • 136 / 7 SPEC. ISS.

Start / End Page

  • 2395 - 2405

International Standard Serial Number (ISSN)

  • 0378-3758

Digital Object Identifier (DOI)

  • 10.1016/j.jspi.2005.08.016

Citation Source

  • Scopus