Measuring gravity wave parameters from a nighttime satellite low-light image based on two-dimensional stockwell transform

Shensen Hu, Shuo Ma, Wei Yan, Neil P. Hindley, Kai Xu, Jun Jiang

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Atmospheric gravity waves are a kind of mesoscale disturbance, commonly found in the atmospheric system, that plays a key role in a series of mesospheric dynamic processes. When propagating to the upper atmosphere, the gravity waves will disturb the local temperature and density, and then modulate the intensity of the surrounding airglow radiation. As a result, the presence of gravity waves on a moonless night can usually cause the airglow to reveal ripple features in low-light images. In this paper we have applied a twodimensional Stockwell transform technique (2DST) to airglow measurements from nighttime low-light images of the day-night band on the Suomi National Polar-Orbiting Partnership. To our knowledge this study is the first to measure localized mesospheric gravity wave brightness amplitudes, horizontal wavelengths, and propagation directions using such a method and data. We find that the method can characterize the general shape and amplitude of concentric gravity wave patterns, capturing the dominant features and directions with a good degree of accuracy. The key strength of our 2DST application is that our approach could be tuned and then automated in the future to process tens of thousands of low-light images, globally characterizing gravity wave parameters in this historically poorly studied layer of the atmosphere.

Original languageEnglish
Pages (from-to)41-51
Number of pages11
JournalJournal of Atmospheric and Oceanic Technology
Volume36
Issue number1
Early online date7 Jan 2019
DOIs
Publication statusPublished - 31 Jan 2019

Keywords

  • Algorithms
  • Atmosphere
  • Gravity waves
  • Remote sensing
  • Satellite observations

ASJC Scopus subject areas

  • Ocean Engineering
  • Atmospheric Science

Cite this

Measuring gravity wave parameters from a nighttime satellite low-light image based on two-dimensional stockwell transform. / Hu, Shensen; Ma, Shuo; Yan, Wei; Hindley, Neil P.; Xu, Kai; Jiang, Jun.

In: Journal of Atmospheric and Oceanic Technology, Vol. 36, No. 1, 31.01.2019, p. 41-51.

Research output: Contribution to journalArticle

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