Gaussianity of the Current and Temperature Data from the Trimoored Internal Wave Experiment (IWEX).

Abstract

This report describes the time variability of the Gaussianity of the East and North velocity components, and the Up (vertical displacement) variable of the Internal Wave Experiment (IWEX). In order to use the classical Chi-square and Two-Tailed Kolmogorov-Smirnov goodness-of-fit tests on a Gaussian distribution, one must consider the correlation structure of the data, i.e., the non-white spectral characteristics of the three variables. Starting with artificially generated random time series that are white in frequency space, the Gentleman and Sande (1966) method is used to incorporate desired spectral shapes into the series. Three frequency filters modeling the internal wave power spectrum very roughly and to different degrees of accuracy are used in the simulations. These in turn are used to find for the two goodness-of-fit tests new confidence levels that recognize the presence of an internal wave-like correlation structure in the data series. The evolution of the Gaussianity of East, North, and Up throughout IWEX is briefly discussed. Since no considerations were given to the frequency-domain behavior of the data, other than the overall spectral shape for use in generating the artificial data, this report is a preliminary study only, because the temporal evolution of the Gaussianity of the various frequency bands in the internal wave field is the underlying question of importance to study of internal wave self and external interactions.

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1975
Accession Number
ADA020760

Entities

People

  • Lucio Iida
  • Melbourne G. Briscoe

Organizations

  • Woods Hole Oceanographic Institution

Tags

DTIC Thesaurus Topics

  • Frequency
  • Frequency Bands
  • Frequency Domain
  • Gaussian Distributions
  • Goodness Of Fit Tests
  • Internal Waves
  • Personal Information Managers
  • Power Spectra
  • Spectra
  • Wave Power
  • Waves

Readers

  • Approximation Theory.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Regression Analysis.

Technology Areas

  • Space