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American Geophysical Union, Journal of Geophysical Research: Atmospheres, 13(126), 2021

DOI: 10.1029/2021jd034643

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Modeling Responses of Polar Mesospheric Clouds to Gravity Wave and Instability Dynamics and Induced Large‐Scale Motions

Journal article published in 2021 by Wenjun Dong ORCID, David C. Fritts ORCID, Gary E. Thomas, Thomas S. Lund
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

AbstractA gravity wave (GW) model that includes influences of temperature variations and large‐scale advection on polar mesospheric cloud (PMC) brightness having variable dependence on particle radius is developed. This Complex Geometry Compressible Atmosphere Model for PMCs (CGCAM‐PMC) is described and applied here for three‐dimensional (3‐D) GW packets undergoing self‐acceleration (SA) dynamics, breaking, momentum deposition, and secondary GW (SGW) generation below and at PMC altitudes. Results reveal that GW packets exhibiting strong SA and instability dynamics can induce significant PMC advection and large‐scale transport, and cause partial or total PMC sublimation. Responses modeled include PMC signatures of GW propagation and SA dynamics, “voids” having diameters of ∼500–1,200 km, and “fronts” with horizontal extents of ∼400–800 km. A number of these features closely resemble PMC imaging by the Cloud Imaging and Particle Size (CIPS) instrument aboard the Aeronomy of Ice in the Mesosphere (AIM) satellite. Specifically, initial CGCAM‐PMC results closely approximate various CIPS images of large voids surrounded by smaller void(s) for which dynamical explanations have not been offered to date. In these cases, the GW and instabilities dynamics of the initial GW packet are responsible for formation of the large void. The smaller void(s) at the trailing edge of a large void is (are) linked to the lower‐ or higher‐altitude SGW generation and primary mean‐flow forcing. We expect an important benefit of such modeling to be the ability to infer local forcing of the mesosphere and lower thermosphere (MLT) over significant depths when CGCAM‐PMC modeling is able to reasonably replicate PMC responses.