PICO
Numerical simulations of the baroclinic lifecycle of the jet stream show gravity wave-like structures in the upper troposphere. Here, we employ a novel method to decompose any flow into slow (geostrophically) balanced part and fast wave part to these structures. The method originates from the optimal potential vorticity balance method by Viudez and Dritschel (2004) but is modified to be applied to general flow. It was compared earlier to the asymptotic decomposition method by Warn et al (1995) and was shown to perform equally well. Here, we apply the novel method to an idealised numerical model of the baroclinic lifecycle of the jet stream and show how much of the gravity wave-like structures in the upper troposphere are part of the balanced part of the flow, and how much of it are really gravity waves.
How to cite: Eden, C., Chouksey, M., and Rosenau, S.: Does the jet stream generate gravity waves?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8424, https://doi.org/10.5194/egusphere-egu25-8424, 2025.
Starting with simulations of idealized linear gravity wave packets, we show how interference between multiple gravity wave packets can result in an underestimation of their combined vertical flux of horizontal momentum by up to 50%. The two key ingredients for this result are the packets must have similar enough frequencies that their projections onto the time-frequency domain overlap, and that they propagate in different horizontal directions. This combination results in errors in the estimated phase relationship between wave-induced horizontal and vertical wind anomalies and reduces the estimate of the magnitude of the packets’ combined momentum flux. Because this mechanism doesn’t affect estimates of the power of a single variable, we propose using a scaling relationship derived from the theory of linear gravity waves in a Boussinesq atmosphere to estimate the momentum flux from the wave energy. We then apply this relationship to data from three lower stratosphere super-pressure balloon campaigns: Loon, Concordiasi, and Strateole-2. We find that both ingredients for wave interference are typically present in the data, evidence that our scaling relationship is appropriate for these calculations, and that momentum fluxes may be underestimated by even more than our simulations of idealized waves suggest. Our results show that the upward flux of horizontal momentum from the troposphere into the stratosphere by gravity waves is likely higher than previously thought, and that care must be taken analyzing output from models that resolve part of the gravity wave spectrum.
How to cite: Green, B., Sheshadri, A., and Podglajen, A.: Reduction of the estimated gravity wave momentum flux by concurrent wave packets, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13965, https://doi.org/10.5194/egusphere-egu25-13965, 2025.
Atmospheric gravity waves (GWs) play a crucial role in vertically coupling the lower and upper atmosphere, significantly impacting middle atmosphere dynamics. Despite their importance, accurately representing GWs remains a persistent challenge for numerical weather prediction and global atmospheric models.
Atmospheric particulate matter or aerosols present in both the troposphere and the stratosphere are deeply involved in radiative processes and atmospheric chemistry. A strong interplay exists between GWs and aerosols, particularly in the formation and evolution of cirrus clouds. Furthermore, aerosol-induced warming processes can also generate GWs within the atmospheric boundary layer, especially over polluted tropical cities. The dynamics of the aerosol vertical distribution can, in certain cases, serve as tracers for GWs, particularly during intense aerosol mixing driven by strong meteorological events in the troposphere and stratosphere.
This study examines GW-induced perturbations in lidar backscatter profiles observed above the Maïdo Observatory at La Réunion (21°S, 55°E) on the night of November 21, 2023 near the southern subtropical barrier. Complementary data from lidar-based temperature and wind measurements, radiosondes, COSMIC-2 satellite observations, and ERA5 reanalysis confirm key GW characteristics in the mid-troposphere. These include a vertical wavelength of 5-6 km, an observed period of approximately 24 hours, an downward phase propagation, and an upward energy propagation into the stratosphere.
How to cite: Chane Ming, F., Tremoulu, S., Gantois, D., Payen, G., Sicard, M., Khaykin, S., Hauchecorne, A., Keckhut, P., and Duflot, V.: Gravity Wave-Induced Perturbations in Lidar Backscatter Profiles above La Réunion (21°S, 55°E), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5174, https://doi.org/10.5194/egusphere-egu25-5174, 2025.
Internal gravity waves with wavelengths of tens to hundreds of kilometers are frequently seen as ripples on high-resolution geostationary satellite animations of subtropical stratocumulus decks. To systematically detect and characterize these waves, several satellite data fields are employed. Daytime visible reflectance images have high contrast, with units of reflected insolation relevant to climate impacts. IR brightness temperature is available day and night, but requires high-pass filtering and contrast enhancements. The divergence of low cloud tracking winds, retrieved via Particle Image Velocimetry (PIVdiv), is a scalar field independent of those radiative quantities. Water vapor channel time differences show wave vertical displacements at midlevels.
In any given image array, Matlab’s Cauchy continuous wavelet transform detects packets of elongated phase crests and projects them into 10 logarithmic half-wavelength bins between 20-500 km, with angle discrimination of about 15 degrees, all on a 5 degree coarse geographical mesh. Cross-wavelet analysis probes for connections between pairs of images. Time pairs of the same field lead to estimates of wave propagation speed. Cross spectra of PIVdiv and radiative brightnesses help to quantitatively relate wave modulations of cloudiness to the vertical displacement of PBL top where the clouds reside. Connecting low level cloud signals to midlevel water vapor signals allows us to estimate vertical wavelength, allowing an independent check against propagation speed via the dispersion relation.
Preliminary wave rose maps, generated for the southeast Pacific during October–December 2023 reveal multiple source regions: synoptic jet-front disturbances in the South Pacific upper-level westerlies, intertropical convergence zone (ITCZ) convection, and orographic or thermal forcing from South America. We hypothesize that similar processes, plus tropical cyclones absent in this sample, drive similar wave activity in other basins and seasons.
The results may have several applications. Any novel observed signal stands as a challenge or target for high-resolution models. Wave sources inferred from these observations may usefully constrain estimates of physical and nonlinear processes in the atmosphere. Low cloud dependence on vertical velocity could have climate relevance, for instance case studies of strong waves have shown they can be rectified in closed to open cell transitions. If periodic waves are trackable for much longer than their inverse frequency, they could comprise a subtle source of surprisingly long predictability of convective initiation, coastal fog/clearing, or other local effects. Like all gravity waves, these redistribute zonal momentum via meridional and vertical fluxes, a process whose contribution to larger scale flows can now be estimated quantitatively.
By offering open-access wave data products, we hope to inspire collaborative efforts on all these application areas. By scaling up computations from 3 months in one region to many years around the globe, downgrading newer data to be comparable to older data as needed, we can build up a nearly global daily picture of tropospheric internal waves over the subtropical oceans through time. With so many degrees of freedom contributing to these high-resolution measurements, very subtle trends and differences should be detectable.
How to cite: Ratynski, M., Mapes, B., and Chaja, H.: Tropospheric gravity waves in the subtropics: Optical detection on low cloud decks , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6975, https://doi.org/10.5194/egusphere-egu25-6975, 2025.
Using the Doppler-Rayleigh lidars at Kühlungsborn (54°N, 12°E) and ALOMAR (69° N, 16° E), we have obtained simultaneous vertical profiles of horizontal wind and temperature on the poleward flank of the Polar Night Jet. This study presents a case where a modified hodograph technique was applied to identify quasi-monochromatic gravity waves within the high wind speed regime of the jet's flank. Our analysis reveals a reduction in gravity wave kinetic and potential energy within the core of the Polar Night Jet for both upward- and downward-propagating waves, attributed to a strong wind shear layer.
We will present a statistical overview of intrinsic gravity wave parameters for all resolved waves in the observation. We will demonstrate our ability to resolve low amplitude waves in the lidar observation down to amplitudes of ~0.5 K in the stratosphere.
As an extension, we will show preliminary attempts to estimate energy fluxes from the lidar data using structure-function and compared these results with hodograph-derived gravity wave energies to investigate turbulent energy transfer rates within the Polar Night Jet.
How to cite: Wing, R., Strelnikova, I., Poblet, F., Strelnikov, B., Gerding, M., Mossad, M., and Baumgarten, G.: Measurements of Quasi-monochromatic Gravity Waves and Estimates of Turbulence in the Polar Night Jet, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10840, https://doi.org/10.5194/egusphere-egu25-10840, 2025.
Despite significant progress in observational and theoretical studies on gravity wave (GW) dynamics, gaps remain in characterizing their variability and accurately representing their impact on the average state of the atmosphere in models. In particular, there is an altitudinal gap in estimating the kinetic and potential energy spectra of GWs between 30 and 70 km.
This study investigates the seasonal and altitudinal variations of GW energy spectra using high-resolution temperature and horizontal wind data recorded over seven years (2017-2023) by a Doppler Rayleigh lidar at the ALOMAR observatory (69°N, 16°E). We analyze spectral potential and kinetic energies across different frequencies and vertical wavenumbers to quantify the variability of dominant wave scales, amplitudes and spectral slopes. We also estimate the temporal and spatial variability of kinetic to potential energy ratio and its implication for the intrinsic values of observed GW frequencies. The findings aim to improve estimates of the atmospheric energy budget, compare theoretical predictions to observed data, and advance our understanding of the GW natural variability.
How to cite: Mossad, M., Strelnikova, I., Wing, R., Baumgarten, G., Gerding, M., Fiedler, J., and Morfa-Avalos, Y.: How variable are gravity wave spectral energies? Insights from a seven-year lidar climatology at 69°N, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12924, https://doi.org/10.5194/egusphere-egu25-12924, 2025.
CAIRT, the Middle-Atmosphere candidate and one of two finalists for ESA’s Earth Explorer
11 mission, offers unprecedented capabilities for observing and understanding atmospheric
dynamics. With an advanced infrared limb imager with high spectral resolution in the range of
720 cm-1 to 2200 cm-1, CAIRT is designed to measure a wide range of trace gas
concentrations and temperature from the upper troposphere and lower stratosphere (UTLS)
up to the lower thermosphere. The instrument enables 3D tomographic retrieval along the
satellite track with an along-track resolution of 50 km and an across-track resolution of 25 km
within a 400 km swath. In particular, temperature observations span altitudes of about 10 to
110 km with a 500 m vertical resolution, making CAIRT well-suited for observing Gravity Wave
(GW) activity throughout the middle atmosphere.
Here, we highlight CAIRT’s capabilities for GW observation and analysis based on model
simulations and synthetic retrieval runs. First, we present the methodology to isolate a
planetary wave (PW) background directly from the temperature observations, which is
essential for deriving the residual, GW-induced temperature perturbations.
Secondly, we demonstrate the analysis of the temperature residuals using the S3D
methodology (based on sinusoidal fits in limited volume data cubes). The analysis enables
robust estimation of individual GW parameters and allows the calculation of GW momentum
fluxes and the associated GW drag, thereby shedding light into the role of GWs in the middle
atmosphere dynamics. In particular, we investigate the GW contribution to the sudden
stratospheric warming (SSW) event during northern hemisphere winter 2018/2019.
Furthermore, the S3D methodology determines the 3D wave vector for individual GWs,
which we use for the initialization of GW ray-tracing to extend our analysis beyond the
observation window, offering insights into GW evolution and potential source regions.
If CAIRT is chosen as the Earth Explorer 11 following the User Consultation Meeting in July
2025, the mission would greatly increase our observational capabilities within the middle
atmosphere and advance our understanding of the middle atmosphere dynamics.
How to cite: Rhode, S., Ern, M., Preusse, P., Liu, H., Maniyattu, P., Mathew, A., Pedatella, N., Sinnhuber, B.-M., and Ungermann, J.: Gravity wave analyses with CAIRT – Temperature measurements, GWMF, and ray-tracing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11207, https://doi.org/10.5194/egusphere-egu25-11207, 2025.
Recently, there has been a significant interest in applying machine learning (ML) to improve the performance of general circulation models (GCMs). Subgrid processes not resolved directly in weather and climate models still require to be parameterized. ML constitutes a set of promising methods to address the problems such as computational cost and uncertainty introduced by parameterization in numerical simulations.
The current study examines the performance of deep learning in reconstructing nonorographic gravity waves (GWs) over midlatitude oceanic regions. A convolutional neural network (CNN) is employed to predict high-resolution variables—standard deviation of momentum flux, horizontal divergence, and vertical velocity—reflecting GW activity in the lowermost stratosphere. Both the targets and the coarse-resolution explanatory variables, spanning the troposphere, are obtained from the ERA5 dataset produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), as outlined by Amiramjadi et al. (2023).
The results demonstrate that the model effectively reconstructs the GW signal and captures the seasonal cycle of GW activity with a reasonable computational cost. The mean coefficient of determination (R²) and Pearson’s correlation coefficient (R) across all grid points in the study area are approximately 0.42 and 0.67, respectively, using all predictors.
Reference:
Amiramjadi, M., Plougonven, R., Mohebalhojeh, A. R., & Mirzaei, M. (2023). Using machine learning to estimate nonorographic gravity wave characteristics at source levels. Journal of the Atmospheric Sciences, 80(2), 419–440.
How to cite: Khanlari, E., Amiramjadi, M., Mohebalhojeh, A. R., and Mirzaei, M.: Deep Learning-Based Reconstruction of Nonorographic Gravity Wave Patterns in the Lower Stratosphere, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7277, https://doi.org/10.5194/egusphere-egu25-7277, 2025.
Atmospheric gravity waves vary hugely in scale; with horizontal wavelengths ranging from a few to thousands of km. Typically, gravity waves are smaller than model grid-size and as a result, their effects are parametrised instead of being explicitly resolved. However, recent computational and scientific advancements have allowed for the development of higher resolution global-scale models. These models have horizontal resolutions of order a few km with around 1km vertical resolution in the stratosphere. At such scales, it should in principle be possible to accurately simulate the majority of GWs without relying on parametrisation.
In this work, we use data from three models from the DYAMOND Initiative (DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains). Specifically, IFS (Integrated Forecast System – produced by ECMWF) at 4km horizontal resolution, ICON (Icosahedral NonHydrostatic) at 5km horizontal resolution and GEOS (Goddard Earth Observing System model) at 3km horizontal resolution. All models are initialised with the same initial conditions and are free running for 40 days. We then compare the properties of resolved gravity waves with observations from the AIRS instrument (Atmospheric InfraRed Sounder) onboard NASA’s Aqua satellite. Importantly, we note that the AIRS observations are limited by the ‘observational filter’, wherein each observing system can only `see' a limited portion of the full GW spectrum. To account for this, an important step in this work is in resampling the model atmospheres as though viewed by the AIRS instrument.
We compare the representation of resolved waves in the three models and AIRS observations across 40-days in Austral winter. We use a recently developed machine learning wave identification method to separate gravity waves in the dataset and determine gravity wave occurrence frequencies. Next, we use spectral analysis to estimate gravity wave amplitudes, wavelengths and calculate momentum fluxes and the intermittency of gravity waves. This work provides an essential evaluation of the accuracy of current gravity wave modelling capabilities.
How to cite: Noble, P., Okui, H., Alexander, J., Ern, M., Hindley, N., Hoffmann, L., Holt, L., van Niekerk, A., Plougonven, R., Polichtchouk, I., Stephan, C., Bramberger, M., Corcos, M., and Wright, C.: Stratospheric Gravity waves in AIRS observations and high-resolution models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3820, https://doi.org/10.5194/egusphere-egu25-3820, 2025.
The atmosphere's flow becomes unpredictable beyond a certain time due to the inherent growth of small initial-state errors. While much research has focused on tropospheric predictability, predictability of the middle atmosphere remains less studied. This work contrasts the intrinsic predictability of different layers, with a focus on the mesosphere/lower thermosphere (MLT, ~50–120 km altitude). Ensemble simulations with the UA-ICON model for an austral winter/spring season are conducted with a gravity-wave permitting horizontal resolution of 20 km, and are contrasted to coarser resolution simulations. Initially small perturbations grow fastest in the MLT, reaching 10% of saturation after 5–6 days, compared to 10 days in the troposphere and two weeks in the stratosphere. However, perturbation energy in the MLT reaches 50% saturation only after about two weeks, similar to the troposphere. Those saturation times are overestimated by up to a factor of two when using a coarser resolution (grid size 160km), highlighting the need for gravity wave-resolving models. Predictability in the MLT depends on horizontal scales. Motions on scales of hundreds of kilometers are predictable for less than five days, while larger scales (thousands of kilometers) remain predictable for up to 20 days. This scale-dependent progression of predictability cannot be explained by simple scaling for upscale error growth. Vertical wave propagation plays a significant role, with gravity waves transmitting perturbations upward at early lead times and planetary waves enhancing long-term predictability. In summary, the study shows that MLT predictability is scale-dependent and highlights the necessity of high-resolution models to capture fast-growing perturbations and assess intrinsic predictability limits accurately.
How to cite: Garny, H.: Role of resolving gravity waves for estimating the intrinsic predictability of the middle atmosphere, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6057, https://doi.org/10.5194/egusphere-egu25-6057, 2025.
Mountains affect the general circulation of the atmosphere on multiple spatial scales, some of which are too small to be explicitly resolved by weather and climate models. To represent the drag exerted by unresolved mountains and unresolved gravity waves, orographic drag parametrisations use statistics of unresolved orography to calculate the sub-grid-scale (SGS) drag. Processes such as large scale wave breaking and flow-blocking become resolved at today's model resolutions, but small-scale drag and turbulent orographic form drag remain in the SGS regime. This poses the open problem of a correct partitioning between resolved and unresolved orographic drag.
Recent studies have used ensemble data assimilation methods, in particular joint state and parameter estimation, to improve the representation of SGS boundary-layer turbulence in models. Inspired by those studies, we aim to to evaluate the sensitivity of an orographic drag scheme to its empirical parameters to identify candidates for effective parameter estimation experiments. Using the Weather Research and Forecasting (WRF) model, we conducted numerical experiments of mountain waves over complex terrain with a grid spacing of 10 km using the GSL drag scheme. This parametrisation represents large-scale gravity wave drag, flow blocking drag, turbulent orographic form drag, and small-scale gravity wave drag.
Using ensemble experiments with perturbed empirical parameters, we evaluate the correlation between individual parameters and the model state. The parameters that display the highest ensemble correlation with the model state have the greatest impact on the behaviour of the orographic drag parametrisation, making them candidates for parameter estimation. Our preliminary results refer to two parameters in the scheme that affect low-level wave breaking and the separation between blocking and non-blocking states, and illustrate their ensemble correlations with the model state.
How to cite: Thalassinos, G., Serafin, S., and Weissmann, M.: Sensitivity of an orographic drag parametrisation scheme to empirical parameters revealed by ensemble simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9483, https://doi.org/10.5194/egusphere-egu25-9483, 2025.
Expanding upon our previous work1, we extend the evaluation of gravity wave parameterization schemes in the Atmospheric Component of the IPSL Climate Model (LMDZ6A) by incorporating comparisons with high-resolution datasets from the ICOsahedral Nonhydrostatic Weather and Climate Model (ICON) and the Integrated Forecasting System (IFS). The ICON dataset corresponds to ~ 5 km horizontal resolution simulations for spring 2020, coarse-grained to a ~ 100 km grid (1°). The IFS dataset corresponds to 1 km horizontal resolution simulations for winter 2018, coarse-grained to a T42 grid (~2.8°). In both models, we assume that at each time and place in the stratosphere, the momentum fluxes due to the disturbances that are filtered out during coarse graining are due to subgrid-scale gravity waves. The parameterizations have been then run offline using ICON and IFS coarse-grained meteorological fields to predict these subgrid-scale gravity wave momentum fluxes.
The comparison shows that the parameterizations have some skills in predicting the geographical distribution of the simulated fluxes in different regions. More specifically, the gravity wave momentum fluxes due to the orographic and convective gravity waves are reasonably well predicted in the mountainous and tropical regions, respectively. The results are more contrasted concerning the gravity waves generated within fronts. Aloft the storm tracks the parameterized gravity wave momentum fluxes are larger than the ICON gravity wave fluxes and smaller than the IFS gravity wave fluxes. This challenges the dynamics at work in these models during geostrophic adjustment, suggesting that some high-resolution models potentially produce more gravity wave fluxes than are needed in GCMs to simulate the right climate. These results also highlight the importance of considering multiple high-resolution datasets to understand gravity wave characteristics better and tune their parameterizations more effectively.
Using insights from these comparisons, we vary the parameters in the schemes to improve the fit with the high-resolution simulations and test impacts in online runs done with the LMDZ6A climate model. Our results illustrate how high-resolution model datasets can improve gravity wave parameterizations in climate models.
1Toghraei, I., Lott, F., Köhler, L., Stephan, C., and Alexander, J.: Comparison between the gravity wave stress parameterized in a climate model and simulated by the high-resolution non-hydrostatic global model ICON, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5181, https://doi.org/10.5194/egusphere-egu24-5181, 2024.
How to cite: Toghraei, I., Lott, F., Köhler, L., Stephan, C., and Alexander, J.: Evaluation of gravity wave parameterization schemes in a climate model using high-resolution ICON and IFS simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5853, https://doi.org/10.5194/egusphere-egu25-5853, 2025.
Gravity waves (GWs) have a significant influence on the formation,
microphysical properties, and life cycle of ice clouds. However,
understanding how to accurately account for the complex interactions
between GWs and ice physics in atmospheric models remains a
challenge. For instance, some ice nucleation parameterizations
consider only the strong vertical updraft velocities generated by GWs,
which lead to high ice crystal number concentrations. However,
temperature and pressure fluctuations associated with GWs can locally
produce high supersaturation levels, triggering ice crystal nucleation
even when the large-scale saturation ratio is below the critical
threshold or in region where GW vertical velocity is zero.
In this study, we present a testbed for coupling transient GW dynamics
with ice physics used for the development of corresponding
parameterizations. We utilize a model capable of operating in two
modes: one that resolves both wave dynamics and nucleation explicitly,
and another that parameterizes those processes. To test our coupling
strategy, we perform idealized experiments involving the superposition
of wave packets passing through an ice-supersaturated region. We
evaluate the resulting microphysical properties of ice clouds and
cloud cover fraction in different simulations. Our findings suggest
that this approach can be successfully implemented in climate models
equipped with transient GW parameterization.
How to cite: Dolaptchiev, S. and Achatz, U.: Gravity wave dynamics influencing ice clouds, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8712, https://doi.org/10.5194/egusphere-egu25-8712, 2025.
An idealized reentrant channel model is utilized to investigate whether wind forcing alone can generate a Garrett-Munk (GM) internal wave (IW) spectrum and where the bulk of the IW energy comes from. It is shown that high-frequency winds can easily generate a GM-like IW spectrum in an eddying ocean without sophisticated model settings. During the formation of a GM-like spectrum, energy transferred from mesoscale eddies to IWs is comparable to that from submesoscale motions. In the pycnocline, IW energy is partially absorbed into mesoscale eddies, which may partly explain why only a small portion of wind-induced IWs penetrates into the deep ocean. This study complements previous study that tidal forcing alone can generate a GM-like IW spectrum. These two studies together imply that a GM-like spectrum can be easily generated through a forcing agent alone, suggestive of a reason why it is ubiquitously observed in the ocean.
How to cite: Chen, Z. and Zhang, Q.: Formation of a Garrett-Munk-like internal wave spectrum in an eddying ocean by wind forcing alone, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4985, https://doi.org/10.5194/egusphere-egu25-4985, 2025.
Internal tides (ITs) are internal waves characterized by tidal or quasi-tidal period, resulting from the interplay between barotropic tidal flow and submarine topography features in a stratified ocean. The dominant tidal constituents in this region are identified as M2 and K1 through in-situ observations from the moored buoys at AD08, AD09, AD10, and RAMA, with S2 and O1 following, respectively. A 3D Massachusetts Institute of Technology General Circulation model simulation is used to identify the key generation sites in the eastern Arabian Sea. The analysis revealed three primary locations: (1) the continental shelf-slope break off Mumbai (SD1), (2) the Lakshadweep region (SD2), and (3) the vicinity of the Maldives Islands (SD3). Among these, the SD1 and SD3 are identified as the major generation sites, collectively contributing approximately 70% of the total baroclinic energy within the study area. The energy budget analysis reveals that the semidiurnal energy conversion reaches its maximum in April at SD1 and in July at SD3, whereas the diurnal energy conversion exhibits peak values in October at SD1 and in July at SD3. SD2 demonstrated minimal seasonal variation in both semidiurnal and diurnal energy conversions. The energy flux patterns reveal south-westward propagation originating from the Mumbai region and westward propagation emanating from the Maldives. The findings highlight that the seasonal variability of ITs in the eastern Arabian Sea is predominantly governed by variations in stratification, offering valuable insights into the region's IT dynamics.
How to cite: Makar, P., Rao, A. D., Yadidya, B., and Pant, V.: The Internal Tides of the Eastern Arabian Sea: A Seasonal Perspective, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-773, https://doi.org/10.5194/egusphere-egu25-773, 2025.
Under investigation in this article is the propagation of internal solitary waves in the deep ocean. Based on the principles of nonlinear theory, perturbation expansion and multi-scale analysis, a time-dependent modified cubic Benjamin-Ono (mCBO) equation is derived to describe internal solitary waves in the deep ocean with stronger nonlinearity. When the dispersive term vanishes, the mCBO equation transforms into the cubic BO equation. Under certain conditions, the mCBO equation can be converted to BO or modified Korteweg-de Vries (mKdV) equation. Compared with the traditional BO model, the mCBO model takes into account stronger nonlinearity. To gain deeper insights into solitary waves' characteristics, conservation of mass and momentum associated with them are discussed. By employing Hirota's bilinear method, we obtain the bilinear form and soliton solutions for mCBO equation, and subsequently investigate interactions between two solitary waves with different directions leading to the occurrence of important events such as rogue waves and Mach reflections. Additionally, we explore how certain parameters influence Mach stem while drawing meaningful conclusions. Our discoveries reveal the complex dynamics of internal solitary waves within the deep ocean and contribute to a broader understanding of nonlinear wave phenomena.
How to cite: Yu, D. and Song, J.: Modeling and propagation evolution of ocean internal solitary waves, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8479, https://doi.org/10.5194/egusphere-egu25-8479, 2025.
Internal solitary waves (ISWs) affect oceanic human activities and play an essential role in ocean mixing. Satellite observations provide a wide-ranging perspective for understanding ISWs. The surface current induced by ISWs can create rough and smooth regions on the sea surface due to the modulated roughness, presenting alternating bright and dark stripes in radar images. Moreover, the pressure distribution characteristic of ISWs creates surface solitons, leading to significant sea surface height anomalies in satellite altimetry. These signatures can be observed synchronously in a swath mode and high spatial resolution by surface water and ocean topography (SWOT) satellite, providing a unique new opportunity to understand both the surface and subsurface characteristics of ISWs. Numerous studies have established the correlation between the surface features and the ISWs parameters in the ocean interior, enabling the inversion of ISWs using remote sensing datasets. However, existing methods still require further improvement, as they are generated from specific assumptions and are highly dependent on the selection of ocean stratifications. By measuring surface divergence and surface height anomalies in laboratory experiments, this study establishes the relationship between surface features and internal characteristics of ISWs. The results reveal that both the strong nonlinearity and the effects of non-hydrostatic contribute significantly to the interpretation of ISWs' surface features, which pose challenges to the accurate retrieval of ISWs parameters. To address these problems, a fully nonlinear, non-hydrostatic method is developed and tested under different laboratory and oceanic conditions, demonstrating a precise connection between surface divergence, surface height anomaly and ISWs parameters. Based on this method, we use sea surface height anomalies and radar backscatter intensities provided by SWOT to perform the inversion. The results indicate that the combination of these two signatures enables accurate retrieval of ISWs parameters and the corresponding pycnocline depth, even if the real-time measurement of stratifications is not available. This study establishes a reliable method to understand ISWs in the global oceans and also provides insights into the challenge of separating ISWs signatures from other oceanic phenomena in SWOT observations.
How to cite: Xu, T., Chen, X., Li, Q., He, X., and Meng, J.: Determining Oceanic Internal Solitary Waves Properties from Surface Signatures captured by SWOT Observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12691, https://doi.org/10.5194/egusphere-egu25-12691, 2025.
