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Abstract An exceptionally strong westward propagating quasi‐6‐day wave (Q6DW) with zonal wavenumber 1 in connection with the rare 2019 Southern Hemispheric Sudden Stratospheric Warming (SSW) is observed by two meteor radars at 30°S and is found to modulate and interact with the diurnal tide and gravity waves (GWs). The diurnal tide is amplified every 6 days and a prominent 21 hr child wave attributed to Q6DW‐diurnal tide nonlinear interaction occurs. Q6DW modulation on GWs is confirmed as the 4–5 day periodicity in GW variances. Simultaneously, the Q6DW appears to shift its period toward the periodicity of the modulated GW variances. Enhancement is also observed in the first results of meteor radar observed Q6DW Eliassen‐Palm flux, which may facilitate the global perturbation and persistence of this Q6DW. We conclude that the observed SSW triggered Q6DW‐tide and Q6DW‐GW interactions play an important role in coupling the lower atmospheric forcings to ionospheric variabilities. 

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–August), the observed wave occurrence frequency is higher, and preferential wave propagation is equator‐ward. In austral summer (November–February), 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. 

Abstract Fritts, Wang, Lund, and Thorpe (2022,https://doi.org/10.1017/jfm.2021.1085) and Fritts, Wang, Thorpe, and Lund (2022,https://doi.org/10.1017/jfm.2021.1086) described a 3‐dimensional direct numerical simulation of interacting Kelvin‐Helmholtz instability (KHI) billows and resulting tube and knot (T&K) dynamics that arise at a stratified shear layer defined by an idealized, large‐amplitude inertia‐gravity wave. Using similar initial conditions, we performed a high‐resolution compressible simulation to explore the emission of GWs by these dynamics. The simulation confirms that such shear can induce strong KHI with large horizontal scales and billow depths that readily emit GWs having high frequencies, small horizontal wavelengths, and large vertical group velocities. The density‐weighted amplitudes of GWs reveal “fishbone” structures in vertical cross sections above and below the KHI source. Our results reveal that KHI, and their associated T&K dynamics, may be an important additional source of high‐frequency, small‐scale GWs at higher altitudes. 

Abstract 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.