Acoustic waves in planetary atmospheres are attenuated by dissipative processes such as viscous stresses and heat conduction, particularly in the rarefied upper layers where multiple species exist in diffusive equilibrium. While the roles of viscosity and thermal conduction in wave attenuation are well understood, species diffusion-the relative motion of molecular species different from the bulk gas driven by gradients in concentration, pressure, and temperature-has received less attention. This study investigates species diffusion as an additional attenuation mechanism in dilute, multi-component gas mixtures, using generalized macroscopic transport equations derived from kinetic theory that reduce to the classical Navier-Stokes equations in the single-species limit. Using a multiple-scales approach, we derive a dispersion relation for linear acoustic and gravity waves, from which an expression for attenuation in multi-species atmospheres is obtained. We apply this framework to the upper atmospheres of Earth, Venus, Mars, Titan, Uranus, and Neptune. Results show that species diffusion-primarily via barodiffusion (diffusion driven by pressure gradients)-can significantly enhance acoustic attenuation on Earth, Venus, and Mars, reaching up to 16%, 45%, and 17%, respectively. On Earth, the effect is most pronounced above 150 km, where light and heavy species such as molecular nitrogen and atomic oxygen coexist in appreciable concentrations. In contrast, species diffusion plays a minor role-contributing less than ≤ 5%-on Titan, Uranus, and Neptune, with bulk and shear viscosity effects dominating wave attenuation in these atmospheres. These findings expand existing models of planetary wave propagation and have implications for planetary diagnostics, remote sensing, and space missions.

Equatorial Plasma Bubbles (EPBs) are a region of depleted ionospheric densities. EPBs are known to fluctuate both seasonally and day to day, and have been linked to changes in solar activity, geomagnetic activity, and seeding resulting from dynamics occurring at lower altitudes. Here, EPB activity is investigated over a 15-day period with overlapping coincident ground-based 630 nm oxygen airglow measurements, near-infrared hydroxyl mesospheric temperature mapper (MTM) measurements, and Rate Of change of Total Electron Content Index (ROTI) values. The data are compared with the Navy Global Environmental Model (NAVGEM) reanalysis over the same time period. It is found that several days with strong EPB activity coincided with the positive/northward meridional wind phase of the quasi-two-day wave (QTDW) in the mesosphere. These initial observations indicate correlations of the QTDW phase and the occurrence rates of EPBs, and suggest a need for further investigations to assess potential causal relationships that may affect the variability and prevalence of EPBs.

Earthquakes with moment magnitude (Mw) ranging from 6.5 to 7.0 have been observed to generate sufficiently strong acoustic waves (AWs) in the upper atmosphere. These AWs are detectable in Global Navigation Satellite System satellite signals-based total electron content (TEC) observations in the ionosphere at altitudes similar to 250-300 km. However, the specific earthquake source parameters that influence the detectability and characteristics of AWs are not comprehensively understood. Here, we extend our approach of coupled earthquake-atmosphere dynamics modelling by combing dynamic rupture and seismic wave propagation simulations with 2-D and 3-D atmospheric numerical models, to investigate how the characteristics of earthquakes impact the generation and propagation of AWs. We developed a set of idealized dynamic rupture models varying faulting types and fault sizes, hypocentral depths and stress drops. We focus on earthquakes of Mw 6.0-6.5, which are considered the smallest detectable with TEC, and find that the resulting AWs undergo non-linear evolution and form acoustic shock N waves reaching thermosphere at similar to 90-140 km. The results reveal that the magnitude of the earthquakes is not the sole or primary factor determining the amplitudes of AWs in the upper atmosphere. Instead, various earthquake source characteristics, including the direction of rupture propagation, the polarity of seismic wave imprints on the surface, earthquake mechanism, stress drop and radiated energy, significantly influence the amplitudes and periods of AWs. The simulation results are also compared with observed TEC fluctuations from AWs generated by the 2023 Mw 6.2 Suzu (Japan) earthquake, finding preliminary agreement in terms of model-predicted signal periods and amplitudes. Understanding these nuanced relationships between earthquake source parameters and AW characteristics is essential for refining our ability to detect and interpret AW signals in the ionosphere.

Despite routine detection of coseismic acoustic-gravity waves (AGWs) in Global Navigation Satellite System (GNSS) total electron content (TEC) observations, models of the earthquake-atmosphere-ionosphere dynamics, essential for validating data-driven studies, remain limited. We present the results of three-dimensional numerical simulations encompassing the entire coupling from Earth's interior to the ionosphere during the Mw ${M}_{w}$ 7.8 2016 Kaikoura earthquake. Incorporating the impact of data/model uncertainties in estimating the ionospheric state, the results show a good agreement between observed and simulated slant TEC (sTEC) signals, assessed through a set of metrics. The signals exhibit intricate waveforms, resulting from the integrated nature of TEC and phase cancellation effects, emphasizing the significance of direct signal comparisons along realistic line-of-sight paths. By comparing simulation results initialized with kinematic and dynamic source models, the study demonstrates the quantifiable sensitivity of sTEC to AGW source specifications, pointing to their utility in the analysis of coupled dynamics.

The Atmospheric Waves Experiment (AWE) is a new NASA mission aimed at investigating the effects of tropospheric weather on space weather. An Advanced Mesospheric Temperature Mapper (AMTM) airglow imager will be deployed on the International Space Station (ISS) in December 2023. This proven instrument will map the nighttime mesospheric temperature at the altitude of the hydroxyl (OH) layer (~87 km) during two years, providing 2D gravity wave (GW) fields over a 600 km field-of-view, every second.Four state-of-the-art models will also help achieving the three science objectives:Quantify the seasonal and regional variabilities and influences of GWs near the mesopause, Identify the dominant dynamical processes controlling GWs observed near the mesopause, Estimate the wider role of GWs in the Ionosphere-Thermosphere-Mesosphere (ITM). This presentation will give an overview of the AWE mission and describe the future data levels using synthetic images.

The Hunga-Tonga Hunga-Ha'apai volcano underwent a series of large-magnitude eruptions that generated broad spectra of mechanical waves in the atmosphere. We investigate the spatial and temporal evolutions of fluctuations driven by atmospheric acoustic-gravity waves (AGWs) and, in particular, the Lamb wave modes in high spatial resolution data sets measured over the Continental United States (CONUS), complemented with data over the Americas and the Pacific. Along with >800 barometer sites, tropospheric observations, and Total Electron Content data from >3,000 receivers, we report detections of volcano-induced AGWs in mesopause and ionosphere-thermosphere airglow imagery and Fabry-Perot interferometry. We also report unique AGW signatures in the ionospheric D-region, measured using Long-Range Navigation pulsed low-frequency transmitter signals. Although we observed fluctuations over a wide range of periods and speeds, we identify Lamb wave modes exhibiting 295-345 m s(-1) phase front velocities with correlated spatial variability of their amplitudes from the Earth's surface to the ionosphere. Results suggest that the Lamb wave modes, tracked by our ray-tracing modeling results, were accompanied by deep fluctuation fields coupled throughout the atmosphere, and were all largely consistent in arrival times with the sequence of eruptions over 8 hr. The ray results also highlight the importance of winds in reducing wave amplitudes at CONUS midlatitudes. The ability to identify and interpret Lamb wave modes and accompanying fluctuations on the basis of arrival times and speeds, despite complexity in their spectra and modulations by the inhomogeneous atmosphere, suggests opportunities for analysis and modeling to understand their signals to constrain features of hazardous events.

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.

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. GWs are well described by the Navier-Stokes equations, but solving these equations extending to very small scales remains daunting, and is limited by the computational costs of resolving the smallest important spatio-temporal features in a large-scale environment. This has led to developments of a wide variety of GW parameterization schemes for regional and global atmospheric models. Traditionally, GW parameterizations are based on linear theory, and no parameterization of secondary GWs (SGWs) has been developed to date. In addition, there remain many aspects of GW dynamics (e.g., GW self-acceleration, instability, GW breaking, SGW generation, and multi-scale interactions) that are important to describe, but cannot be addressed by linear theory or existing schemes. Here we describe an initial, two-dimensional (2-D), machine learning model – the Compressible Atmosphere Model Neural Network (CAMNet) - intended as a first step toward a more general, three-dimensional, highly-efficient, model for applications to nonlinear GW dynamics description. CAMNet employs a physics-informed neural operator and GPU hardware to dramatically accelerate GW and SGW simulations applied to two GW sources to date. CAMNet 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 SGW generation in two wind environments are described here. Results show that CAMNet can capture the key 2-D dynamics modeled by CGCAM with high precision. Spectral characteristics of primary and SGWs estimated by CAMNet agree well with those from CGCAM. Our results show that CAMNet 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.

This paper briefly reviews the current state of first-principles (i.e.physics-based) ionosphere-thermosphere-mesosphere (ITM) models that use numerical solutions to systems of underlying differential or algebraic equations.We identify compelling future directions and urgent needs, and make near-term recommendations for investments in several different aspects of physics-based modeling and simulation.These include multi-scale/multi-resolution capabilities, addition of unresolved physical processes, improvements in empirical specifications, and enhancements to modeling infrastructure. Summary of Recommendations:We advocate for investments in physics-based models to:-Improve resolution in general-purpose global ITM simulations to resolve the dominant range of mesoscale perturbations, using new techniques as they emerge.-Leverage adaptive mesh refinement (AMR) techniques in general-purpose models, to efficiently increase resolution in regions requiring refinement, e.g., those experiencing unstable cascade to small-scales or filamentary forcing, or formation of steep features.-Support custom model development for purposes of addressing specific problems not easily addressed by general purpose models, and for training opportunities for the next generation of ITM modeling researchers.-Include small-scale physical processes in high-resolution simulations to address current inadequacies.For ionospheric simulation this includes inertial and finite pressure effects, finite Larmor radius corrections, and 3D potential solutions, while neutral simulations at small scales must properly capture compressible dynamics and dissipation processes.-Continue to improve parameterizations and implementations for sub-grid physics of known importance, e.g., Farley-Buneman instability (in the ionosphere) and small-scale AGWs (in the neutral atmosphere).-Improve empirical and assimilative high-latitude energy inputs (particles and fields) for ITM models, including characterizations of mesoscale structures and interhemispheric asymmetries using data from upcoming missions.-Develop infrastructure via support for software engineering to improve efficiency and accessibility of codes for users (both scientific and operational), and resources for training developers of physics-based models.

We conducted an analysis of the process of GW breaking from an energy perspective using the output from a high-resolution compressible atmospheric model. The investigation focused on the energy conversion and transfer that occur during the GW breaking. The total change in kinetic energy and the amount of energy converted to internal energy and potential energy within a selected region were calculated.Prior to GW breaking, part of the potential energy is converted into kinetic energy, most of which is transported out of the chosen region. After the GW breaks and turbulence develops, part of the potential energy is converted into kinetic energy, most of which is converted into internal energy.The calculations for the transfer of kinetic energy among GWs, turbulence, and the BG in a selected region, as well as the contributions from various interactions (BG-GW, BG-turbulence, and GW-turbulence), are performed. At the point where the GW breaks, turbulence is generated. As the GW breaking process proceeds, the GWs lose energy to the background. At the start of the GW breaking, turbulence receives energy through interactions between GWs and turbulence, and between the BG and turbulence. Once the turbulence has accumulated enough energy, it begins to absorb energy from the background while losing energy to the GWs.The probabilities of instability are calculated during various stages of the GW-breaking process. The simulation suggests that the propagation of GWs results in instabilities, which are responsible for the GW breaking. As turbulence grows, it reduces convective instability.

Simulations of hypothesized but unobserved mesopause airglow (MA) disturbances generated by infrasonic acoustic waves (IAWs) during the 2016 M7.8 Kaikoura earthquake are performed. Realistic surface displacements are calculated in a forward seismic wave propagation model and incorporated into a 3‐D nonlinear compressible neutral atmosphere model as a source of IAWs at the surface‐air interface. Inchin et al. (2021), https://doi.org/10.1029/2020av000260 previously showed that Global Positioning System‐based total electron content (TEC) observations can be used to constrain the finite‐fault kinematics of the Kaikoura earthquake. However, due to limitations of Global Navigation Satellite System network coverage and coalescence of nonlinear IAW fronts, they pointed to the relative insensitivity of the observed near‐zenith TEC perturbations to the rupture evolution on the Papatea fault (PF). Here, we demonstrate that MA observations may have been able to supplement the investigation of the PF, providing information on both the timing of rupture initiation and its direction of propagation. The amplitudes of perturbations of vertically integrated volume emission rates for the simulated hydroxyl (OH)(3,1) and atomic oxygen O(1S) 557.7 nm reach ∼18% peak‐to‐peak, and ∼3.2% (5.8 K) peak‐to‐peak perturbations in OH(3,1) temperature. Our results suggest that observations of nighttime MA imprints of coseismic IAWs are feasible with ground‐based imagers, and may supplement the study of finite‐fault kinematics of large crustal earthquakes.

Mechanical disturbances associated with hazardous events—e.g., earthquakes, explosions (volcanic or man-made)—and severe weather – generate broad spectra of infrasound and acoustic-gravity waves (AGWs). These wave signals may provide diagnostic insight into the processes that generated them. They are routinely detected as fluctuations in atmospheric pressure, measured at ground or from balloon-borne platforms; at lower frequencies (<1 Hz), and where they may attain sufficient amplitudes at high altitudes, they may also be measured via the fluctuations that they impose in densities of layered species throughout the atmosphere and ionosphere. Thus, they provide complementary remote sensing opportunities, where waves and their effects, especially above and surrounding larger sources, may be diagnosed as they propagate. We review recent progress and techniques for high-fidelity modeling and simulation, to capture the propagation and evolution of low-frequency infrasound and AGWs throughout the atmosphere, from 0–500 km altitude (from surface to exobase). Strategies to (1) efficiently extend model simulation domains well into the diffusive thermosphere, to (2) connect models of atmospheric dynamics to those for other measurable processes (e.g., the ionosphere), and to (3) construct simulations that extend from source processes to specific remote sensing methodologies are discussed.

Seismically-induced infrasonic waves (IWs) are known sources of disturbances in the upper layers of the atmosphere. These waves experience growth and potential for nonlinear evolution with height and may ultimately exhibit amplitudes of ten(s) of % of local Mach number following events of sufficient strength and scale. Along with a routine detection of their impacts on the ionospheric plasma, e.g., in GPS signal-based measurements of integrated total electron content (TEC), studies demonstrate opportunities to exploit these observations for the investigation of earthquake sources.We present the results of specific case and parametric studies of the feasibility to infer earthquake source characteristics based on observations of IW impacts on mesospheric airglow emissions and ionospheric densities. Studies include numerical simulations performed with three-dimensional coupled seismic wave propagation, and neutral atmospheric and ionospheric models, covering the chain of processes from earthquake sources to observable signatures. The results suggest that upper-atmospheric/ionospheric measurements of IWs may supplement classical seismic and geodetic observations over complex ruptures or undersea earthquakes, by providing additional independent information. They also reveal key dependencies on model specifications – from physical processes to propagation environments in multiple media – and thus require comprehensive validation to establish their quantitative utility.

Explosive events, such as artificial or accidental explosions, and volcanic eruptions, among others, generate low-frequency acoustic waves that propagate through and perturb atmospheric and ionospheric layers (e.g., the hydroxyl and oxygen airglow layers, the sodium layer, and the ionospheric D-region). The subsequent disturbances (i.e., airglow emission intensity, sodium or other minor species density, or electron density fluctuations) are potentially detectable by optical or radio remote sensing methods. Understanding and quantifying the impact of acoustic waves on atmospheric layers are, therefore, crucial steps for establishing detectability thresholds (e.g., relative to source scales and effective yields). In this work, we investigate the propagation of upwardly-traveling acoustic perturbations induced by 1t to-1 kt of TNT-equivalent ground explosions and their signatures on different atmospheric layers. Specifically, we estimate the amplitudes and periods of the induced fluctuations of hydroxyl, sodium, and electron densities at mesospheric through lower-thermospheric altitudes. This work investigates the potential of such layers to serve as sensors for characterizing lower-atmospheric explosive events and the complementarity of such indirect measurements with direct sensing, e.g., of pressure fluctuations in situ.

Numerical simulations of mesopause airglow (MA) fluctuations induced by tsunami‐generated acoustic and gravity waves (TAGWs) are performed. Simulated tsunamis over realistic bathymetry are used to excite atmospheric waves at the surface level of a three‐dimensional nonlinear and compressible neutral atmospheric model. The model incorporates the dynamics and chemistry of hydroxyl OH(3,1) MA under nighttime assumptions. We report case study results of eight recent large tsunami events and demonstrate that TAGW‐induced MA fluctuations are readily detectable with modern ground‐ and space‐based imagers, and may provide quantitative insight. The amplitudes of MA fluctuations reflect the evolution of ocean surface displacements, enhancing or decreasing accordingly, and revealing the tsunami's lobes and local wave focusing. The results suggest that MA observations have potential to supplement early‐warning systems, providing information on spatial and temporal evolution of tsunami waves of ∼10 cm and higher for the cases shown. They may find applications in tsunami tracking over large open ocean areas, as well as in the investigation or reconstruction of tsunami source characteristics.

The 15 January 2022 climactic eruption of Hunga volcano, Tonga, produced an explosion in the atmosphere of a size that has not been documented in the modern geophysical record. The event generated a broad range of atmospheric waves observed globally by various ground-based and spaceborne instrumentation networks. Most prominent was the surface-guided Lamb wave (≲0.01 hertz), which we observed propagating for four (plus three antipodal) passages around Earth over 6 days. As measured by the Lamb wave amplitudes, the climactic Hunga explosion was comparable in size to that of the 1883 Krakatau eruption. The Hunga eruption produced remarkable globally detected infrasound (0.01 to 20 hertz), long-range (~10,000 kilometers) audible sound, and ionospheric perturbations. Seismometers worldwide recorded pure seismic and air-to-ground coupled waves. Air-to-sea coupling likely contributed to fast-arriving tsunamis. Here, we highlight exceptional observations of the atmospheric waves.

A 2D nonlinear, compressible model is used to simulate the acoustic‐gravity wave (AGW, i.e., encompassing the spectrum of acoustic and gravity waves) response to a thunderstorm squall‐line type source. We investigate the primary and secondary neutral AGW response in the thermosphere, consistent with waves that can couple to the F‐region ionospheric plasma, and manifest as Traveling Ionospheric Disturbances (TIDs). We find that primary waves at z = 240 km altitude have wavelengths and phase speeds in the range 170–270 km, and 180–320 m/s, respectively. The secondary waves generated have wavelengths ranging from ∼100 to 600 km, and phase speeds from 300 to 630 m/s. While there is overlap in the wave spectra, we find that the secondary waves (i.e., those that have been nonlinearly transformed or generated secondarily/subsequently from the primary wave) generally have faster phases than the primary waves. We also assess the notion that waves with fast phase speeds (that exceed proposed theoretical upper limits on passing from the mesosphere to thermosphere) observed at F‐region heights must be secondary waves, for example, those generated in situ by wave breaking in the lower thermosphere, rather than directly propagating primary waves from their sources. We find that primary waves with phase speeds greater than this proposed upper limit can tunnel through a deep portion of the lower/middle atmosphere and emerge as propagating waves in the thermosphere. Therefore, comparing a TID's/GWs phase speed with this upper limit is not a robust method of identifying whether an observed TID originates from a primary versus secondary AGW.

Acoustic emissions from lightning discharges are usually attributed to two mechanisms. The audible part of their spectrum mainly results from the shock wave generated by the heating of the lightning channel. On the other hand, the infrasonic component is associated with the conversion to sound of the electrostatic energy stored in the thundercloud. While there is a broad scientific consensus on the former mechanism, the latter process is still controversial. The electrostatic mechanism was proposed by C. T. R. Wilson in 1921 and can be summarized as follows. Due to the electrostatic repulsion of the charged particles, the pressure within a thundercloud is lower than outside. At discharge, the electrostatic field collapses, and the sudden air volume contraction produces an acoustic pulse. This work examines the existing theoretical models of the electrostatic mechanism with the data observed for thundercloud dimensions, charge densities, and total charges. Our results show that, although possible, this mechanism, as currently described, cannot explain observations. Our findings might support the hypothesis that the heating of the lightning channel is responsible for the generation of both infrasound and audible sound. However, a definitive answer remains precluded and requires a better understanding of cloud formation and electrification processes.

Meteorology, especially strong tropospheric convection, is widely appreciated to generate broad spectra of acoustic and gravity waves (AWs and GWs or, together, AGWs). These include GWs with scales of tens to hundreds of kilometers and periods of ∼5 min to hours, that readily propagate upward, reach high altitudes (often to the lower-thermosphere), and grow to large amplitudes so that they may evolve nonlinearly prior to being overcome by dissipation. Strong convective dynamics, e.g., thunderstorms and tornadoes, are also known to radiate AWs at very low infrasonic frequencies (e.g., 0.1 Hz down to ∼4 mHz) that reach high altitudes and may be detectable in fluctuations of the atmosphere and ionosphere [e.g., Nishioka et al. (2013); Heale et al. (2019)]. The breaking of strong GW fields may also generate secondary AWs and, more generally, AGWs [Snively (2017); Heale et al. (2021)]. Together, convection and secondary AGW processes contribute to a broad spectrum of AWs with ∼mHz periods that are readily detectable at high altitudes and in pressure signals also measured at ground. Although AWs are excluded from traditional numerical weather prediction models, we report on models and simulation experiments designed to capture AW/AGW evolutions and their resulting observable signatures. In particular, we review and highlight scenarios by which ∼mHz AWs may reveal source processes of interest, as well as the opportunities to use atmospheric and ionospheric signals of AWs/AGWs as complement to ground-based infrasound recordings.