Annual Cycle of Gravity Wave Activity Derived From a High-Resolution Martian General Circulation Model

Takeshi Kuroda, Erdal Yiğit, Alexander S. Medvedev

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

The paper presents results of simulations with a high-resolution (equivalent to ∼67-km grid size) Martian general circulation model (MGCM) from the surface up to the mesosphere for a full Martian year. The obtained climatology of the small-scale disturbances can serve as a proxy for gravity waves (GWs) that are largely not resolved by MGCMs with conventional grid resolution and thus have to be parameterized. GW activity varies greatly with season and geographical location, which contradicts with the constant in space and time sources in the lower atmosphere adopted by GW parameterizations employed by coarse-grid MGCMs. In particular, lower-atmospheric GW activity is smaller in polar regions of the troposphere throughout all seasons, and the intensity is larger in southern spring and summer and in winter hemisphere at both solstices. In the mesosphere, the peak of GW activity shifts toward middle and high latitudes, and the interhemispheric symmetry is much larger compared to the lower atmosphere. The detailed climatology created in this study can be used for prescribing sources of GWs in parameterizations utilized by MGCMs as well as for validating the parameterizations in the middle and upper atmosphere.

Original languageEnglish
Pages (from-to)1618-1632
Number of pages15
JournalJournal of Geophysical Research: Planets
Volume124
Issue number6
DOIs
Publication statusPublished - 2019 Jun

Keywords

  • Mars
  • general circulation model
  • gravity waves
  • planetary meteorology

ASJC Scopus subject areas

  • Earth and Planetary Sciences (miscellaneous)
  • Geochemistry and Petrology
  • Geophysics
  • Space and Planetary Science

Fingerprint

Dive into the research topics of 'Annual Cycle of Gravity Wave Activity Derived From a High-Resolution Martian General Circulation Model'. Together they form a unique fingerprint.

Cite this