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Temporal Signatures of Observations and Model Outputs: Do Time Series Decomposition Methods Capture Relevant Time Scales?

  • P. S. Porter
  • J. Swall
  • R. Gillian
  • E. L. Gego
  • Christian Hogrefe
  • A. Gilliland
  • J. S. Irwin
  • T. Rao
Conference paper

Time series decomposition methods were applied to meteorological and air quality data and their numerical model estimates. Decomposition techniques express a time series as the sum of a small number of independent modes which hypothetically represent identifiable forcings, thereby helping to untangle complex processes. Mode-to-mode comparison of observed and modeled data provides a mechanism for model evaluation.

Keywords

Empirical Orthogonal Function Empirical Mode Decomposition Noise Floor Wavelet Filter Temperature Time Series 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • P. S. Porter
    • 1
  • J. Swall
    • 2
  • R. Gillian
    • 2
  • E. L. Gego
    • 3
  • Christian Hogrefe
    • 4
  • A. Gilliland
    • 5
  • J. S. Irwin
    • 5
  • T. Rao
    • 2
  1. 1.University of Idaho308 Evergreen DriveIdaho FallsUSA
  2. 2.NERLU.S. Environmental Protection AgencyRTPUSA
  3. 3.University Corporation for Atmospheric ResearchIdaho FallsUSA
  4. 4.Atmospheric Science Research CenterNYSCDEC CentreAlbanyUSA
  5. 5.NOAA Atmospheric Sciences Modeling DivisionU.S. Environmental Protection AgencyResearch Triangle ParkUSA

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