with a larger-scale flow, wave-induced mean flow, wave-wave interactions in general, wave breaking and its implications for mixing, and the parameterization of these processes in models not explicitly resolving IGWs. The observational record, both on a global scale and with respect to local small-scale processes, is not yet sufficiently able to yield appropriate constraints. The session is intended to bring together experts from all fields of geophysical and astrophysical fluid dynamics working on related problems. Presentations on theoretical, modelling, experimental, and observational work with regard to all aspects of IGWs are most welcome, including those on major collaborative projects, which seek to accurately parameterize the role of IGWs in numerical models.
Among the different types of atmospheric waves, infrasound corresponds to low-frequency acoustic waves that can propagate over thousands of kilometers within atmospheric waveguides formed between the surface and the middle-atmosphere (MA, 15-90 km) or the lower thermosphere (90-120 km). Infrasound is a technology used to monitor the atmosphere for the Comprehensive Nuclear-test Ban Treaty (CTBT). Infrasound stations of the International Monitoring System put in place to monitor compliance with CTBT continuously record infrasound waves, which can be seen as a tracer of the MA and lower thermosphere dynamics. At these altitudes, Numerical Weather Prediction (NWP) models are biased, notably due to the lack of observations to assimilate, especially for winds, or for instance due to an approximate representation of the impact of atmospheric gravity waves on the dynamics. We propose a method based on the observation of infrasound of oceanic origin, known as microbaroms, to evaluate and compare the performances of atmospheric models in the middle atmosphere. We present a complete processing chain that simulates microbarom arrivals at an infrasound station and that compares them to observations. It explicitly accounts for both the oceanic source emission mechanism and the atmospheric propagation. Beyond the atmospheric diagnostics enabled by this method, we have implemented our modeling of microbarom arrivals within a variational data assimilation (DA) framework to constrain wind and temperature atmospheric fields in the MA. As proof-of-concept, first DA synthetic experiments were conducted in simplified atmospheric configurations to demonstrate the added value of infrasound observations in constraining the MA dynamics.
How to cite: Letournel, P., Listowski, C., Bocquet, M., Le Pichon, A., and Farchi, A.: Using an oceanic acoustic noise model to evaluate and constrain simulated atmospheric states, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7463, https://doi.org/10.5194/egusphere-egu26-7463, 2026.
Gravity waves (GWs) are ubiquitous in stably stratified background states of the atmosphere from the boundary layer to the thermosphere. As a mesoscale phenomenon with typical scales smaller than the model effective resolution, they need to be parameterized in climate models based on numerous underlying simplifications. However, our understanding of the GW climate impacts is based mainly on their parameterized effects and may be model dependent and with uncertain relation to the real atmosphere dynamics.
Based on the whole span of the ERA5 reanalysis, here I present a "quasi - observational" assessment of GW dynamical effects in the extratropical upper troposphere and stratosphere. Part of our results confirms the textbook knowledge and expectations regarding the gravity wave role in decelerating the jet streams. But, after a closer inspection of the data, we found also previously unreported interactions and dynamical effects connected with GWs in the vicinity of the subtropical jet that can change the way how we parameterize them.
How to cite: Šácha, P., Procházková, Z., and Zajíček, R.: Dynamical effects of atmospheric gravity waves in the upper troposphere and stratosphere as revealed by a high-resolution reanalysis., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17239, https://doi.org/10.5194/egusphere-egu26-17239, 2026.
Internal gravity waves (IGWs) play a key role in ocean dynamics by interacting with mesoscale eddies, topography, and other waves, leading to wave breaking and mixing that influence small and large-scale circulations. Despite local variability, the IGW energy distribution exhibits a remarkably universal spectral shape, the Garrett-Munk (GM) spectrum, within which we study the scattering of IGWs via wave-wave interactions under the weak-interaction assumption.
We use the kinetic equation derived from a non-hydrostatic Boussinesq system with constant rotation and stratification. By developing Julia-native numerical codes, we evaluate the energy transfers for resonant and non-resonant interactions. Our results confirm that resonant triads dominate energy transfers, while non-resonant interactions are negligible in isotropic spectra but can contribute under anisotropic conditions. We show that the Boltzmann rates are small such that the weak-interaction assumption is satisfied. We find non-local interactions to be essential to understand the energy transfers within the IGW field, while local interactions are of minor importance. Parametric subharmonic instability drives a forward energy cascade in vertical wavenumber and an inverse cascade in frequency. Induced diffusion emerges as a primary energy transfer to small scales, and elastic scattering plays a similar but weaker role. We also find a new interaction mechanism, the third parametric generation, which provides a forward energy cascade in frequency and vertical wavenumber. We assess the convergence of the kinetic equation by introducing a cutoff in the IGW energy spectrum, or with a change in slope mimicking the transition to turbulence. Our findings provide convergent results at reduced computational costs, improving the efficiency and reliability of energy transfer evaluations in oceanic IGW spectra.
How to cite: Sebastia Saez, P., Chouksey, M., Eden, C., and Olbers, D.: Evaluations of wave-wave interactions for the oceanic internal gravity wave field at very high grid resolution , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20157, https://doi.org/10.5194/egusphere-egu26-20157, 2026.
Internal gravity waves are scattered by inhomogeneities, such as background currents and bottom topography. Scattering modifies the wave's length and direction of propagation and in doing so, redistributes energy across wavenumbers and frequencies. When inhomogeneities are large relative to the waves, scattering reduces to a spectral diffusion process. Prior work on spectral diffusion considers only current-induced scattering via Doppler shift of the wave frequency. We generalise the diffusion framework to account for all large-scale inhomogeneities. This includes current-induced effects other than Doppler shift, and entirely different mechanisms such as scattering on bottom topography. We support our results with ray tracing simulations and analytical solutions.
How to cite: Cox, M., Kafiabad, H., and Vanneste, J.: Scattering of internal gravity waves by inhomogeneities, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19243, https://doi.org/10.5194/egusphere-egu26-19243, 2026.
Internal and inertial waves play a substantial role in ocean dynamics. They can transport a considerable amount of kinetic energy over long distances, and their amplitude in the abyssal ocean can reach gigantic vertical scales of several hundreds of meters. At the same time, packets of internal and inertial waves conserve a fixed angle with respect to gravity or the rotation axis upon reflection, which makes both their linear and nonlinear dynamics rather peculiar. Most hydrodynamical systems in closed domains can be described in terms of modes. In this framework, one usually assumes eigenfunctions satisfying the boundary conditions, for example Fourier standing modes in rectangular domains. These modes oscillate in time at every point in space but do not propagate in a specific spatial direction. Internal and inertial waves constitute a remarkable exception to this approach. It has been shown that, in a general geometry, wave beams of travelling waves converge toward a limiting path, known as a wave attractor, while global modes form a set of zero measure. Rectangular tanks aligned with gravity and/or rotation, actually represent an exceptional but very important case. Our work focuses on two aspects of internal waves in this context: first, the influence of the aspect ratio on the transition to turbulence and mixing for structurally stable wave attractors; second, the interplay between wave-attractor regimes and modal structures in the vicinity of rectangular geometries. Surprisingly, a conventional rectangular geometry may exhibit much more complex and strongly multistable regimes than those observed for simple wave attractors. We demonstrate competition between different triadic instability pairs, leading to multistability and a nearly uniform picket-fence spectrum, which is markedly different from the spectrum resulting from cascades of triadic instabilities driven by large-aspect-ratio wave attractors.
How to cite: Sibgatullin, I.: Aspect ratio effects, multistability and quantisation in wave attractors., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21268, https://doi.org/10.5194/egusphere-egu26-21268, 2026.
An offline methodology is applied to estimate parameters of a subgrid-scale non-orographic gravity-wave scheme using observations from constant-level balloons. The approach integrates the Ensemble Kalman Filter (EnKF) with an iterative parameter estimation method based on the expectationmaximization (EM) algorithm. The meteorological fields required for the parameterization offline are taken from the ERA5 reanalysis, corresponding to the instantaneous meteorological conditions found underneath the Strateole-2 balloon observations made in the lower tropical stratosphere from November 2019 to February 2021 and October 2021 to January 2022. Compared to a direct approach that minimizes a cost function and uses Bayesian inference of parameters, our analysis demonstrates that the EnKF/EM method effectively characterizes the launching amplitudes and altitudes of the parameterized gravity waves and while quantifying their associated uncertainties. Furthermore, we illustrate how the method can help improving a scheme, specifically the results indicate that introducing a background wave activity renders the convective wave parameterization more realistic.
How to cite: Lott, F., Tandeo, P., Pulido, M., and Bardet, D.: EnKF and EM based parameter estimation of a convective gravity wave parameterization using Strateole 2 constant level balloon data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13026, https://doi.org/10.5194/egusphere-egu26-13026, 2026.
Atmospheric gravity waves (GWs) are a key driver of vertical energy and momentum transport in the atmosphere, with important implications for large-scale dynamics and chemistry. However, they remain difficult to predict in operational weather and climate models due to their small spatial scales relative to model resolution, and are typically not assimilated into numerical weather prediction (NWP) systems because of the large departures they introduce from model initial conditions.Here we use stratospheric temperature measurements from the Atmospheric Infrared Sounder (AIRS) and the Cross-track Infrared Sounder (CrIS) to evaluate how well archived operational analyses and forecasts from ECMWF’s Integrated Forecast System reproduce observed GW activity over Greenland, a major Northern Hemisphere source region for orographic GWs. The combined AIRS–CrIS sampling at high latitudes provides an unusually high measurement cadence, enabling assessment of forecast performance and time variability at relatively fine temporal resolution.Operational analyses and forecasts with lead times of up to 240 h are sampled at the AIRS and CrIS measurement footprints and regridded to a common resolution to allow consistent spectral analysis. A 2D+1 Stockwell Transform is applied to both synthetic and real observations to characterise GW amplitudes and spatial structure, producing directly comparable GW fields across forecast lead times.Using a Structure–Amplitude–Location (SAL) framework adapted from precipitation forecast verification, we quantify the evolution of GW forecast skill with lead time. We find that model performance exhibits only weak dependence on forecast range: across all lead times, the model systematically produces GWs with smaller horizontal scales and reduced amplitudes relative to observations, while errors in wave location increase only modestly with lead time. This behaviour is unexpected, as shorter lead times are associated with more accurate resolved winds, and would therefore be expected to yield more accurate GW generation. The results suggest that errors in simulated GW characteristics in operational forecasts are dominated by structural and representational limitations rather than by forecast wind errors alone.
How to cite: Wright, C. J., Berthelemy, P., Hindley, N. P., Polichtchouk, I., and Hoffmann, L.: Lead-time independence of gravity-wave forecast skill in operational analysis and forecasts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17588, https://doi.org/10.5194/egusphere-egu26-17588, 2026.
Gravity waves (GWs) are well known for their role in shaping large-scale dynamics of the atmosphere, but they also induce strong local variability in the vertical velocity, temperature, and other fields. Such variability is often omitted when it comes to global effects due to averaging and resolution limitations. However, small-scale dynamics, such as gravity waves, have a crucial role in cirrus microphysics and life cycle. Ice clouds, on the other hand, can have a pronounced effect on the Earth’s radiation budget and global moisture distribution, making their accurate representation in climate and numerical weather prediction (NWP) models particularly important.
This work investigates the effects of gravity waves on cirrus cloud microphysics using the global ICON (Icosahedral Nonhydrostatic) model. A novel, self-consistent parameterization of GW-induced homogeneous ice nucleation developed by Dolaptchiev et al. (2023) is employed, and additional GW effects on depositional ice growth are considered. The local GW field is represented using the Multi-Scale Gravity Wave Model (MS-GWaM), which supports multiple GW source types and three-dimensional wave propagation, thereby enhancing the physical realism of the parameterized GW dynamics. The full coupling of GW forcing, along with feedback from the supplemented ice scheme into the overall microphysics and radiation schemes, has been implemented and assessed within the ICON model.
The results of the global test runs reveal significant GW impacts on ice formation mechanisms, leading to enhanced homogeneous nucleation in the upper troposphere–lower stratosphere (UTLS) compared to the baseline ICON configuration. Furthermore, GW-induced temperature fluctuations obtained from MS-GWaM and coupled online to depositional growth substantially increase ice growth efficiency. It results in larger ice mixing ratios in the mid-latitudes and subtropical regions. Further analyses are planned to assess the sensitivity of the coupled version to different MS-GWaM configurations, the role of lateral GW propagation, and the relative contributions of different gravity wave sources.
How to cite: Kosareva, A., Dolaptchiev, S., Seifert, A., Spichtinger, P., and Achatz, U.: Impact of gravity waves on ice-cloud microphysics in a global NWP model using online coupling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10944, https://doi.org/10.5194/egusphere-egu26-10944, 2026.
Tropospheric internal gravity waves, often originating from jets, fronts, or deep convection, leave subtle but discernible imprints on the vast stratocumulus decks that cover subtropical oceans. These waves represent a non-negligible, yet poorly quantified, interaction between the free atmosphere and the marine boundary layer. This presentation introduces a robust, twopass methodology using 2D continuous wavelet transforms (CWT) on geostationary satellite imagery (GOES-16) to objectively detect, track, and characterize these wave packets. The core of our framework is its ability to precisely separate the intrinsic wave propagation signal from the dominant, large-scale advective flow of the cloud field.
Our method quantifies the primary physical signature of these waves: the modulation of cloudtop brightness caused by vertical displacements at the boundary layer inversion. By tracking these propagating brightness patterns, our algorithm identifies individual wave packets as dynamically evolving objects and measures their physical properties, including wavelength, propagation speed, and direction. To validate the method, we generate synthetic satellite imagery by superimposing the signatures of hypothetical wave fields (with known properties such as wavelength, speed, and direction) onto realistic, advected cloud scenes. This process allows us to confirm the method's ability to faithfully retrieve the initial parameters and to characterize its measurement uncertainties.
We then apply this validated methodology to a real-world case study from 12 October 2023 over the Southeast Pacific. The analysis successfully isolates a coherent wave packet with a ~150 km wavelength and tracks its dynamic evolution.
Potential applications are numerous, including the construction of wave climatologies, the study of wave-cloud interactions, the analysis of their role in organizing shallow convection, and the assessment of their long-range predictability. The tool, made available as open-source software, is intended to facilitate a systematic exploration of these key, yet often hidden, components of the climate system.
How to cite: Ratynski, M., Mapes, B., and Chaja, H.: Measuring tropospheric gravity waves over stratocumulus cloud decks , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4568, https://doi.org/10.5194/egusphere-egu26-4568, 2026.
The anthropogenic emission of carbon dioxide has been attributed as the main driver of global warming. However, its radiative properties also cause the middle atmosphere to cool and contract. This cooling, as well as associated changes in large-scale circulation patterns of the troposphere and stratosphere, result in trends in the mesosphere and lower thermosphere (MLT) region. We conducted a whole-atmosphere simulation employing the ICOsahedral Non-hydrostatic general circulation model with Upper Atmosphere extension (UA-ICON) in the configuration with the numerical weather prediction (NWP) physics package. As gravity waves are the main driver of the dynamics in the MLT and thus critically influence its thermal structure, we chose a horizontal resolution of 20 km to model a large portion of the gravity wave spectrum explicitly. A realistic large-scale circulation up to 50 km is ensured by constraining the dynamics of the troposphere and stratosphere to the ECMWF Reanalysis v5 (ERA5) dataset.
From the simulation, we derive trends of the atmospheric mean circulation and temperature. Additionally, the run is analyzed within the Transformed Eulerian Mean (TEM) framework to derive trends related to gravity waves and wave-mean flow interaction. For validation, the results are compared with the Atmospheric General circulation model for the Upper Atmosphere Research-Data Assimilation System (JAGUAR-DAS) whole neutral atmosphere reanalysis dataset (JAWARA).
How to cite: Pankrath, H., Kunze, M., Zülicke, C., Avalos, Y. M., Pedatella, N., and Stephan, C. C.: Modelling climate change in the MLT with a gravity-wave permitting setup of UA-ICON, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1670, https://doi.org/10.5194/egusphere-egu26-1670, 2026.
We present a new global, high-resolution (10 km) simulation of the atmosphere using the ICON modeling framework and extending the vertical domain from the surface to the mid-thermosphere up to 250 km. With this configuration, gravity waves (GWs) are explicitly resolved up to a horizontal wavelength of about 50 km, and we can study the generation and dissipation across atmospheric layers, providing an opportunity to investigate GW propagation into the mesosphere and lower thermosphere (MLT) and their interactions with large-scale tides. Particular emphasis is put on cascading gravity waves, whereby primary waves generate secondary and higher-order GWs, and on their role in coupling the lower and upper atmosphere.
The simulation captures the interaction of gravity waves and tides with dynamically active regions, including the polar vortex leading to a sudden stratospheric warming (SSW). Achieving global, whole-atmosphere simulations at this resolution poses significant numerical challenges, including maintaining a consistent energy budget and ensuring the stability of the forward-in-time integrator across a wide range of scales and densities. We discuss strategies employed to address these challenges and assess their implications for model fidelity.
This modeling capability represents a critical step toward realistic whole-atmosphere prediction and provides an essential tool for the design and interpretation of coordinated satellite observation campaigns targeting GW–tide interactions and vertical coupling processes.
How to cite: Dörffel, T. and Stephan, C.: Using ICON to model from ground to thermosphere - a global perspective, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9936, https://doi.org/10.5194/egusphere-egu26-9936, 2026.
This talk will present our recent work of Weng et al. (2025, in manuscript). Intrinsic predictability of the weather defines the ultimate limit of our day-to-day weather forecasts. This study aims to investigate the variable- and scale-dependent intrinsic predictability of wave-convection coupled bands lasting nearly 10 hours near the south coast of China on 30 January 2018, by conducting perturbed and unperturbed convection-permitting simulations with 1-km horizontal grid spacing under varying initial moisture conditions. In particular, the predictability time scale of each selected forecast variable is quantified in the current study via the Loss Predictability Index (LPI), defined as the ratio of the forecast error (difference between perturbed and unperturbed) power spectrum to the reference (unperturbed) power spectrum at a given scale or within a range of scales. Spectral analysis reveals substantial differences in the reference power spectral slopes among variables, while their error growth behaviors consistently exhibit upscale features. The intrinsic predictability limit of the banded convection, measured by the difference total energy (DTE), is approximately 7 hours. Predictability varies with both scale and altitude: smaller scales (i.e., ~10 km) have shorter limits than larger scales (i.e., ~40 km), and the middle-level moist neutral stability layer is less predictable than the low-level ducting stable layer. In particular, for the moist neutral stability layer, different variables become more correlated under the coupling between gravity waves and moist convection, yielding more coherent predictability characteristics. In the dry experiment, predictability exceeds 12 hours with minimal error growth, regardless of the variable, scale, or altitude. Finally, the decomposition of the horizontal kinetic energy spectrum into divergent and rotational components (proxies for unbalanced and balanced components, respectively), demonstrates contrasting power spectra, intrinsic predictability limits, and their sensitivity to initial moist content, with the divergent component exhibiting longer predictability in the ducting stable layer at wavelengths <40 km. These findings highlight how vertical flow structure, moisture content, and distinct dynamical components jointly constrain the intrinsic predictability of mesoscale convective systems.
Reference:
Manshi Weng, J. Wei, Y. Du, Y. Q. Sun, and X. Zhang, 2025: Revisiting Intrinsic Predictability of Wave-Convection Coupled Bands Over Southern China: Variable and Scale-Dependent Error Growth, Journal of Geophysical Research: Atmospheres (Major Revision).
How to cite: Weng, M., Wei, J., Du, Y., Sun, Y. Q., and Zhang, X.: Revisiting Intrinsic Predictability of Wave-Convection Coupled Bands Over Southern China: Variable and Scale-Dependent Error Growth Characteristics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1843, https://doi.org/10.5194/egusphere-egu26-1843, 2026.
Tropical cyclones (TCs) are a source of atmospheric gravity waves, which contribute to mixing in the upper troposphere and lower stratosphere. Here, we conducted a large ensemble simulation run of the Weather and Forecasting Research (WRF, V4.4.1) model, assessing the impact of 15 combinations of microphysics (MP), planetary boundary layer physics (PBL), and a cumulus scheme (CU) on the model's ability to simulate the physics of Typhoon Soudelor (2015) and this typhoon's generation of gravity waves. The simulation is performed using a moving nested domain at 3 km horizontal resolution, with a 15 km exterior main domain. We use data from International Best Track Archive for Climate Stewardship to measure bias in track position and intensity of the typhoon, supported by the use of AIRS/Aqua satellite observations as a benchmark. Moving beyond traditional analyses, we also apply a kernel density estimator (KDE) approach to produce more comprehensive results.
Our results indicate that, while track errors remain below 100 km for the first 42 hours of the run, the simulated storm intensity and speed varied significantly from observations. Notably, simulations incorporating cumulus parameterization generally yield wider track spreads, whereas microphysics produced higher storm intensities and a more accurate representation of deep convective clouds compared to WSM6, despite an overall tendency to overestimate storm strength. We then examined coupling between tropical cyclone dynamics and stratospheric wave generation by comparing simulated Outgoing Longwave Radiation (OLR) and vertical wind speeds against satellite and reanalysis data. KDEs of OLR suggests, that while the Goddard MP effectively captures deep convection, the addition of a Grell-3 CU parameterization tends to produce more extensive mid-to-high-level cloud cover but underestimates the deepest convective cores. In the stratosphere, vertical wind speed profiles indicate that the MYJ and Goddard combinations produce the strongest wave activity, especially during the chosen peak events. Although the simulations slightly overestimate background wind speeds near the tropopause compared to ERA5 reanalysis output, the overall wave morphology remains consistent with observations. These findings reinforce the conclusion that no single physics combination optimally captures all TC attributes, though Goddard MP and specific PBL schemes offer superior performance in representing the convective forcing essential for stratospheric gravity wave excitation.
How to cite: Lu, Y.-S., Wright, C. J., Wu, X., and Hoffmann, L.: Sensitivity Analysis of Gravity Wave Characteristics to Physical Parameterization Options in WRF Simulations : A Case Study of Typhoon Soudelor (2015), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9749, https://doi.org/10.5194/egusphere-egu26-9749, 2026.
Most operational gravity-wave parameterizations use single-column and steady-state approximations, thus neglecting horizontal propagation and transience. Recent studies indicate that these simplifications can lead to inaccurate predictions. Orographic gravity waves, e.g., can propagate over substantial horizontal distances, leading to the deposition of momentum far from their sources. The neglect of this could be a cause of regional momentum-flux deficits in atmospheric models, e.g. downstream of the Andes. Moreover, the variability of low-level winds can make mountain-wave generation a highly transient process, challenging the legitimacy of the steady-state approximation. This motivates the development of more complex models.
MS-GWaM is a Lagrangian gravity-wave parameterization that is based on a multi-scale WKB theory allowing for both transience and horizontal propagation. In a previous study (Jochum et al., 2025), it was used in simulations within the idealized atmospheric flow solver PincFlow to investigate its ability to correctly describe the interaction between orographic gravity waves and a large-scale flow. 2D flows over periodic monochromatic orographies were considered, using MS-GWaM either in its fully transient implementation or in a steady-state implementation that represents classic mountain-wave parameterizations. Comparisons of wave-resolving simulations (not using MS-GWaM) and coarse-resolution simulations (using MS-GWaM) showed that allowing for transience leads to a significantly more accurate forcing of the resolved mean flow. The present study supplements MS-GWaM (within PincFlow's successor PinCFlow.jl) with a new blocked-layer scheme and continues the investigation with the more realistic case of an isolated 2D mountain range, where the impact of upstream blocking and horizontal propagation increases substantially, resulting in a more complex wave-mean-flow interaction. The blocked-layer scheme uses a relatively simple approach to blocking that is consistent with MS-GWaM's spectral representation of the unresolved orography. Its two parameters are calibrated via Ensemble Kalman Inversion, using a wave-resolving simulation as reference. The results show that the inclusion of this scheme yields a slightly improved forcing of the mean flow.
References
Jochum, F., Chew, R., Lott, F., Voelker, G. S., Weinkaemmerer, J., and Achatz, U. (2025). The impact of transience in the interaction between orographic gravity waves and mean flow. Journal of the Atmospheric Sciences.
How to cite: Jochum, F., Lott, F., and Achatz, U.: 2D transient parameterization of gravity waves generated above an isolated mountain range, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13124, https://doi.org/10.5194/egusphere-egu26-13124, 2026.
Representing gravity wave (GW) sources accurately remains a major challenge for climate models. While parameterizations for orographic and convective gravity waves are well established, studies have shown that additional sources, including fronts, jet streams, and jet exit regions, also generate gravity wave activity. These sources driven by dynamics are often not clearly defined in current parameterization methods, which leads to biases in momentum deposition and large-scale circulation.
In this study, we propose a machine learning-based framework to model gravity wave sources in a unified and data-driven way. We use high-resolution ICON simulations to resolve gravity wave generation from a wide range of atmospheric processes. A reduced-order representation of the gravity wave action density spectrum serves as the target function. This allows for a compact yet meaningful description of gravity wave emission. Input features include resolved large-scale flow characteristics, subgrid-scale orographic properties, and convective indicators taken from the model fields.
We train supervised machine learning models to learn the nonlinear relationship between the atmospheric state and the resulting gravity wave emission. The resulting parameterization accounts for gravity wave generation related not only to orography and convection but also to dynamically driven sources such as frontogenesis and jet-related processes.
How to cite: Mahmoudi, E., Prochazkova, Z., Dolaptchiev, S., Pohl, A., and Achatz, U.: Data-Driven Gravity Wave Source Parameterization Using Machine Learning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6563, https://doi.org/10.5194/egusphere-egu26-6563, 2026.
Satellite observations of the atmosphere are often extremely noisy due to both hardware limitations and the inherent complexity of retrieving and making measurements of the atmosphere. Gravity waves, which are low amplitude signals present in the atmosphere, are hard to resolve in this data due to their relatively low amplitude and small spatial extent. As a result, noise becomes a limiting factor when trying to identify and characterise them in real observed data.
Current methods to address this problem often lean upon smoothing approaches; however, such approaches suppress small scale signals and reduce measured amplitude and momentum fluxes significantly. This impedes the process in developing the next generation of models where these waves must be resolved accurately.
A novel supervised machine learning approach is introduced which is able to accurately remove small scale noise features from nadir observations of gravity waves. This model was trained on synthetic observations derived from high resolution DYAMOND model runs. This is then applied to 22 years of NASA AIRS data and 12 years of MetOp IASI data and used to produce a new gravity wave climatology to better access small amplitude gravity waves.
How to cite: Hayes, A., Wright, C., Hindley, N., Hoffmann, L., and Noble, P.: Denoising Stratospheric Nadir Sounder Observations using a Machine Learning Technique for Gravity Wave Detection, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3063, https://doi.org/10.5194/egusphere-egu26-3063, 2026.
The MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) mission is a Swedish satellite mission designed to study atmospheric gravity waves the mesopause region. MATS was launched in November 2022 and carries a limb-imaging instrument that observes the Earth’s atmosphere in the altitude range from approximately 70 to 110 km and a nadir camera. The primary observables are airglow emissions in the O₂ A-band and ultraviolet light scattered by noctilucent clouds.
The limb instrument is a telescope that continuously images the atmospheric limb in six spectral channels: four channels in the near-infrared targeting the airglow, and two ultraviolet channels dedicated to noctilucent cloud observations. By exploiting limb geometry and multi-view sampling along the orbit, MATS enables tomographic reconstruction of three-dimensional atmospheric structures. The airglow measurements yield a high–vertical-resolution 3-D temperature product, allowing characterization of individual gravity waves, while the ultraviolet observations enable reconstruction of the spatial distribution and characteristics of noctilucent clouds.
This presentation will focus on the newly completed 3-D mesospheric temperature data set derived from the MATS airglow measurements. We will describe the tomographic retrieval, the characteristics and coverage of the temperature product. If available, early validation results will be presented.
The presentation will also provide an update on the current status of the MATS mission, which after severe technical and regulatory challenges since 2023, is expected to resume operations in February 2026.
How to cite: Megner, L., Krasauskas, L., Gumbel, J., Murtagh, D., Icvhenko, N., Linder, B., Stegman, J., Christensen, O. M., Hedin, J., and Hetmanek, J.: The MATS satellite: Mission update and 3-D mesospheric temperatures, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19909, https://doi.org/10.5194/egusphere-egu26-19909, 2026.
Internal tides are internal gravity waves with tidal frequencies, generated by the interaction of barotropic tides with rough seafloor topography. The breaking of internal tides constitutes one of the fundamental mechanisms for sustaining mixing within the deep ocean. However, past lack of large-scale deep-ocean observations caused uncertainties in characterizing their properties and spatial distribution patterns. The Southwestern Atlantic, with complex and diverse seafloor topography, provides an ideal site for studying deep-ocean internal tides while Deep Argo floats with full-water-depth observation capabilities enable this research. Based on data collected by Deep Argo floats during parking phase, the characteristics and spatial distribution of internal tides at 3000-4000 m in the deep Southwestern Atlantic Ocean are investigated. The analysis quantifies significant amplitudes of internal tides in the deep ocean, revealing spatial patterns distinct from the upper ocean. While upper-ocean internal tides are primarily modulated by large-scale topography, deep-ocean internal tides are subject to small-scale seafloor topography. Consequently, deep-ocean internal tides are spatially locked to local topography features rather than following far-field propagation paths, with semidiurnal internal tides exhibiting higher amplitudes in the Mid-Atlantic Ridge region, whereas diurnal internal tides are intensified near 28°S. These findings provide essential observational support for unraveling complex dynamics driven by small-scale seafloor topography.
How to cite: Zhou, X., Gao, Z., and Chen, Z.: Spatial Distribution of Internal Tides in the Deep Southwestern Atlantic Ocean, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7532, https://doi.org/10.5194/egusphere-egu26-7532, 2026.
Internal Solitary Waves (ISWs) are among the most important physical processes in oceanic systems. Specifically, they play a significant role in vertical mixing, energy transfer across the continental shelf, sediment resuspension, nutrient redistribution, and the regulation of thermocline structure. Their breaking and subsequent turbulent dissipation contribute significantly to the global energy cascade. Additionally, ISWs remain challenging to study: they are strongly nonlinear, inherently nonhydrostatic, and often require three-dimensional, high-resolution modelling to capture steep fronts, overturning, and mixing. Consequently, accurate numerical simulation of ISWs is vital for improving our understanding of their mechanisms and impact on ocean circulation and climate-relevant processes.
Since the mid-20th century, numerical models have become indispensable tools for analyzing and predicting oceanic systems and processes. As such, considerable research has focused on developing discretization methods that faithfully simulate physical phenomena while minimizing numerical artifacts. Such frequent artifact is the Spurious Diapycnal Mixing (SDM), in which, due to numerical diffusion, the vertical advection scheme introduces mixing across the density layers, thus severely altering the stratification. Due to this, various methods to track and remedy SDM have been proposed [1].
SLS is a numerical ocean model introduced by A. Alexandris and co-authors in [2]. It uses a hybrid Finite Volume / Finite Element spatial discretization and treats the full pressure field through a Pressure Poisson equation. Thus, SLS is inherently a nonhydrostatic ocean model and can faithfully simulate dispersive phenomena, such as solitons. The main novelty of SLS is its Arbitrary Lagrangian Eulerian (ALE) scheme that suitably defines the vertical grid motion.
Since the seminal paper, the ALE scheme of SLS was further improved through extensive numerical modelling and simulation of ISWs. To facilitate this, an optimization process was designed with the goal of reducing SDM. The optimality is expressed through a variational principle that defines the ALE grid motion through an elliptic equation. The mathematical derivation/ analysis of the scheme and its impact on SDM is organized in the preprint [3], which is submitted to Ocean Modelling and is under review. This also includes extensive simulations of ISWs including breaking and overturning on a sloping beach.
In the present work, further experiences of simulating ISWs with SLS are presented. This includes the application of the ALE method to more challenging 3D turbulent simulations, where the ability of SLS to control SDM is further tested. Additionally, the stability of the ALE scheme is investigated, alongside analysis of some spurious behaviors that are caused by the interplay of the Lagrangian and Eulerian mesh dynamics.
References:
[1] Fox-Kemper, Baylor, et al. "Challenges and prospects in ocean circulation models." Frontiers in Marine Science 6 (2019): 65.
[2] Alexandris-Galanopoulos, Andreas, George Papadakis, and Kostas Belibassakis. "A semi-Lagrangian Splitting framework for the simulation of non-hydrostatic free-surface flows." Ocean Modelling 187 (2024): 102290.
[3] Alexandris-Galanopoulos, Andreas, and George Papadakis. "An ALE approach to reduce spurious numerical mixing through variational minimizers: application to internal waves." arXiv preprint arXiv:2511.20092 (2025)
How to cite: Alexandris-Galanopoulos, A. and Papadakis, G.: Simulation of Internal Waves within an ALE ocean model: numerical challenges and modelling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10233, https://doi.org/10.5194/egusphere-egu26-10233, 2026.
Turbulence in the ocean mixed layer is a major source of internal gravity waves, yet the efficiency and pathways of this energy transfer remain less understood. We investigate how mixed-layer turbulence excites internal waves and drives the rapid decay of mixed-layer kinetic energy following strong forcing events. Using numerical simulations of a turbulent mixed layer overlying a stratified interior, we explicitly resolve the generation and propagation of internal waves. The non-hydrostatic model shows that surface wave-generated turbulence in the mixed layer radiates high-frequency internal waves near the buoyancy frequency, exporting ~13% of the mixed-layer energy in 20 hours. A hydrostatic model shows that near-inertial baroclinic modes, especially mode 2, redistribute this energy vertically over 2–10 days. These mechanisms provide a fast, localized pathway for upper‑ocean mixing. Normal-mode and spectral analyses link this turbulent radiation to low-baroclinic modes, near-inertial adjustment, and anisotropic wave emission in the presence of a background flow. Together, these results provide compact scaling relations that connect observable mixed-layer properties and turbulence intensity to internal-wave energy fluxes, enabling realistic parameterizations of mixed–layer–to–interior energy transfer in ocean and climate models.
How to cite: Dhar, S., Seshasayanan, K., and D'Asaro, E.: Role of mixed layer turbulence on the generation of internal waves , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20398, https://doi.org/10.5194/egusphere-egu26-20398, 2026.
