Statistical Characteristics of High-frequency Gravity Waves Observed by an Airglow Imager at Andes Lidar Observatory

Alan Z Liu, Bing Cao

Research output: Contribution to journalArticlepeer-review

Abstract

The long-term statistical characteristics of high-frequency quasi-monochromatic gravity waves are presented using multi-year airglow images observed at Andes Lidar Observatory (ALO, 30.3° S, 70.7° W) in northern Chile. The distribution of primary gravity wave parameters including horizontal wavelength, vertical wavelength, intrinsic wave speed, and intrinsic wave period are obtained and are in the ranges of 20–30 km, 15–25 km, 50–100 m s−1, and 5–10 min, respectively. The duration of persistent gravity wave events captured by the imager approximately follows an exponential distribution with an average duration of 7–9 min. The waves tend to propagate against the local background winds and show evidence of seasonal variations. In austral winter (May–Aug), the observed wave occurrence frequency is higher, and preferential wave propagation is equator-ward. In austral summer (Nov–Feb), the wave occurrence frequency is lower, and the waves mostly propagate pole-ward. Critical-layer filtering plays a moderate role in determining the preferential propagation direction in certain months, especially for waves with a smaller observed phase speed (less than typical background winds). The observed wave occurrence and preferential propagation direction are related to the locations of convection activities nearby and their relative distance to ALO. However, direct wave generations are less likely due to the large distance between the ALO and convective sources. Other mechanisms such as secondary wave generation and possible ducted propagation should be considered. The estimated mean momentum fluxes have typical values of a few m2 s−2.

Original languageAmerican English
JournalEarth and Space Science
DOIs
StatePublished - May 23 2022
Externally publishedYes

Keywords

  • gravity waves
  • the Andes
  • airglow
  • mesopause

Disciplines

  • Earth Sciences
  • Engineering Physics
  • Numerical Analysis and Computation
  • Statistical Models

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