A 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.
Results of two‐dimensional and narrow three‐dimensional (2‐D and 2.5‐D) simulations of a gravity wave (GW) packet localized in altitude and along its propagation direction employing a new, versatile compressible model are described. The simulations explore self‐acceleration and instability dynamics in an idealized atmosphere at rest under mean solar conditions in a domain extending to an altitude of 260 km and 1,800 km horizontally without artificial dissipation. High resolution in the central 2.5‐D domain enables the description of 3‐D instability dynamics accounting for breaking, dissipation, and momentum deposition within the GW packet. 2‐D results describe responses to localized self‐acceleration effects, including generation of secondary GWs (SGWs) at larger scales able to propagate to much higher altitudes. 2.5‐D results exhibit instability forms consistent with previous 3‐D simulations of instability dynamics and cause SGW generation and propagation at smaller spatial scales to weaken significantly compared to the 2‐D results. SGW responses at larger scales are driven primarily by GW/mean flow interactions arising at early stages of the self‐acceleration dynamics prior to strong GW instabilities and dissipation. As a result, they exhibit similar responses in both the 2‐D and 2.5‐D simulations and readily propagate to high altitudes at large distances from the initial GW packet. A companion paper examines these dynamics for an initial GW packet localized in three dimensions and evolving in a representative 3‐D tidal wind field.more » « less
- NSF-PAR ID:
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
A compressible numerical model is applied for three‐dimensional (3‐D) gravity wave (GW) packets undergoing momentum deposition, self‐acceleration (SA), breaking, and secondary GW (SGW) generation in the presence of highly‐structured environments enabling thermal and/or Doppler ducts, such as a mesospheric inversion layer (MIL), tidal wind (TW), or combination of MIL and TW. Simulations reveal that ducts can strongly modulate GW dynamics. Responses modeled here include reflection, trapping, suppressed transmission, strong local instabilities, reduced SGW generations, higher altitude SGW responses, and induced large‐scale flows. Instabilities that arise in ducts experience strong dissipation after they emerge, while trapped smaller‐amplitude and smaller‐scale GWs can survive in ducts to much later times. Additionally, GW breaking and its associated dynamics enhance the local wind along the GW propagation direction in the ducts, and yield layering in the wind field. However, these dynamics do not yield significant heat transport in the ducts. The failure of GW breaking to induce stratified layers in the temperature field suggests that such heat transport might not be as strong as previously assumed or inferred from observations and theoretical assessments. The present numerical simulations confirm previous finding that MIL generation may not be caused by the breaking of a transient high‐frequency GW packet alone.
Dong et al. (2020,
https://doi.org/10.1029/2019JD030691) employed a new compressible model to examine gravity wave (GW) self‐acceleration dynamics, instabilities, secondary gravity wave (SGW) generation, and mean forcing for GW packets localized in two dimensions (2D). This paper extends the exploration of self‐acceleration dynamics to a GW packet localized in three dimensions (3D) propagating into tidal winds in the mesosphere and thermosphere. As in the 2D packet responses, 3D GW self‐acceleration dynamics are found to be significant and include 3D GW phase distortions, stalled GW vertical propagation, local instabilities, and SGW and acoustic wave generation. Additional 3D responses described here include refraction by tidal winds, localized 3D instabilities, asymmetric SGW propagation, reduced SGW and acoustic wave responses at higher altitudes relative to 2D responses, and forcing of transient, large‐scale, 3D mean responses that may have implications for chemical and microphysical processes operating on longer time scales.
Gravity waves (GWs) and their associated multi‐scale dynamics are known to play fundamental roles in energy and momentum transport and deposition processes throughout the atmosphere. We describe an initial machine learning model—the Compressible Atmosphere Model Network (CAM‐Net). CAM‐Net is trained on high‐resolution simulations by the state‐of‐the‐art model Complex Geometry Compressible Atmosphere Model (CGCAM). Two initial applications to a Kelvin‐Helmholtz instability source and mountain wave generation, propagation, breaking, and Secondary GW (SGW) generation in two wind environments are described here. Results show that CAM‐Net can capture the key 2‐D dynamics modeled by CGCAM with high precision. Spectral characteristics of primary and SGWs estimated by CAM‐Net agree well with those from CGCAM. Our results show that CAM‐Net can achieve a several order‐of‐magnitude acceleration relative to CGCAM without sacrificing accuracy and suggests a potential for machine learning to enable efficient and accurate descriptions of primary and secondary GWs in global atmospheric models.
The Polar Mesospheric Cloud Turbulence (PMC Turbo) experiment was designed to observe and quantify the dynamics of small‐scale gravity waves (GWs) and instabilities leading to turbulence in the upper mesosphere during polar summer using instruments aboard a stratospheric balloon. The PMC Turbo scientific payload comprised seven high‐resolution cameras and a Rayleigh lidar. Overlapping wide and narrow camera field of views from the balloon altitude of ~38 km enabled resolution of features extending from ~20 m to ~100 km at the PMC layer altitude of ~82 km. The Rayleigh lidar provided profiles of temperature below the PMC altitudes and of the PMCs throughout the flight. PMCs were imaged during an ~5.9‐day flight from Esrange, Sweden, to Northern Canada in July 2018. These data reveal sensitivity of the PMCs and the dynamics driving their structure and variability to tropospheric weather and larger‐scale GWs and tides at the PMC altitudes. Initial results reveal strong modulation of PMC presence and brightness by larger‐scale waves, significant variability in the occurrence of GWs and instability dynamics on time scales of hours, and a diversity of small‐scale dynamics leading to instabilities and turbulence at smaller scales. At multiple times, the overall field of view was dominated by extensive and nearly continuous GWs and instabilities at horizontal scales from ~2 to 100 km, suggesting sustained turbulence generation and persistence. At other times, GWs were less pronounced and instabilities were localized and/or weaker, but not absent. An overview of the PMC Turbo experiment motivations, scientific goals, and initial results is presented here.