This session provides an open venue for scientists to share the latest advances in Lagrangian techniques, explore diverse applications, and build new connections.
We invite presentations on topics including, but not limited to:
- Planetary circulations and variability (fundamental processes shaping jets, gyres, waveguides, overturning circulations, transport barriers across atmosphere and ocean)
- Mesoscale eddies and coherent structures (eddy transport, wave-mean flow interactions, blocking)
- Turbulence and mixing (turbulent and convective entrainment, breaking internal waves, boundary layers)
- Numerical and computational advances (incl. data-driven techniques, GPU acceleration, graph-theoretical formulations, adaptive methods, data assimilation)
- Inverse modeling techniques (long-range transport of volcanic plumes, wildfire smoke, hazardous material, aerosols, plastics, micro-organisms, and their impacts on global composition, health, and climate)
- Field campaigns (drifters, floats, superpressure balloons, etc)
Orals: Mon, 4 May, 08:30–10:15 | Room -2.15
Ocean currents transport material like nutrients, plankton and plastic over the globe. The most natural way to study these transport pathways and the connections between ocean basins is by using trajectories, computed by simulating virtual Lagrangian particles in fine-resolution ocean models.
In this presentation, I will show how my team uses our open source parcels-code.org framework to simulate the dispersion of virtual plastic particles by the three-dimensional ocean flow. I will discuss how we develop new parameterizations for subgrid-scale transport processes of buoyant plastics; and compare these parameterizations to field measurements.
I will particularly focus on how we combine the resulting dispersion maps with estimates of plastic pollution sources and then apply Bayesian inference techniques to find the most likely sources for heavily polluted locations.
While our application is plastic pollution in the ocean, the framework could be applied in other geophysical contexts where the sources of a signal in a complex Lagrangian transport process have to be determined, from air pollution tracking to glaciological proxy reconstruction.
How to cite: van Sebille, E.: Combining Lagrangian simulations and Bayesian inference for source attribution of ocean plastic pollution, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1946, https://doi.org/10.5194/egusphere-egu26-1946, 2026.
Microplastic pollution is one of the major threats to ocean health. However, the processes governing the transport and redistribution of microplastics remain poorly understood due to the interaction of multiple physical mechanisms at different scales We investigate the vertical transport and concentration of quasi-neutrally buoyant microplastics by direct numerical simulations of small inertial particles in an inhomogeneous turbulent flow. An idealized two-dimensional convective mixed-layer model reproduces some relevant features of the upper ocean: at the surface, a well-mixed region where temperature and density are nearly homogeneous, and a lower region of weak mixing and gravity waves with strong temperature and density gradients. The dynamics of these inertial particles in both regions are analyzed using a simplified model derived from the Maxey-Riley-Gatignol equation. The model assumes particle density equal to a reference fluid density at a given depth, with density variations only affecting buoyancy (i.e., the Boussinesq approximation). Our results show that temperature differences along Lagrangian paths determine whether particles settle at specific depths or remain near the surface. The observed vertical concentration profiles in the thermocline are explained using a discrete particle framework based on a stochastically forced wave–driven relaxation model. Particle accumulation occurs preferentially near specific depths where internal gravity wave signatures are detected through oscillations of the local isopycnal structure. In the proposed description, these wave-induced fluctuations imprint a structured modulation of the concentration profile, while turbulent fluctuations are represented as a white-noise forcing that accounts for particle spreading around the accumulation depths. The relative importance of wave-driven relaxation and turbulent diffusion varies with depth, reflecting the anisotropic and inhomogeneous nature of the stratified flow. This approach consistently reveals that, while gravity has a pivotal role on particle transport and accumulation, the fluid’s eddy diffusivity can also have non-negligible effects on the spreading of particles, depending on the physical properties of the latter.
How to cite: Silva Torres, L. A., Berti, S., and Calzavarini, E.: Vertical distribution of weakly inertial, quasi-neutrally buoyant particles in a convective ocean mixed layer, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4256, https://doi.org/10.5194/egusphere-egu26-4256, 2026.
The ocean biological carbon pump transfers particulate organic matter (POM) from surface waters to the deep ocean, playing a key role in long-term sequestration of organic matter. Small-scale turbulence and stratification strongly influence particle sinking, yet these processes are poorly represented in global models, which rely on simplified parameterizations.
We investigate these effects using high-resolution direct numerical simulations (DNS) of stratified turbulence, designed to capture small-scale ocean dynamics, coupled with a Lagrangian inertial particle model. By resolving turbulent structures and particle–fluid interactions, we aim to quantify how turbulence intensity, stratification, and particle properties control sinking velocities and export efficiency. Multiple particle types are tracked under ocean-relevant conditions, constrained using oceanographic observations and reanalysis data to provide realistic ranges for turbulence, stratification, and vertical shear.
To bridge microscale processes to large-scale modeling, we incorporate DNS-derived insights into climate simulations using the Earth System Model EC-Earth, a fully coupled atmosphere–ocean configuration. The ocean and its biogeochemistry are simulated with NEMO-PISCES, and the atmosphere with OIFS. This approach allows us to assess how unresolved turbulence and particle dynamics affect particulate export at global scales. By combining turbulence-resolved Lagrangian simulations with global climate experiments, this work aims to reduce uncertainties in particle transport and improve understanding of biogeochemical microscale processes and their climate feedbacks. Simulation data and tools will be openly available to enable further research on microscale ocean transport processes and their representation in global climate and ocean models.
How to cite: Sozza, A. and Davini, P.: Towards a Lagrangian-informed representation of ocean particulate export: from small-scale turbulence to climate models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18046, https://doi.org/10.5194/egusphere-egu26-18046, 2026.
Mesoscale oceanic fronts and eddies form coherent structures that regulate transport, retention, and mixing in the upper ocean, yet how their internal physical and biogeochemical structure shapes the distribution of mobile predators remains poorly understood. Here we adopt an active Lagrangian perspective to investigate the distribution of neon flying squid (Ommastrephes bartramii) using a decade-long fisheries dataset from the Northwest Pacific, combined with mesoscale diagnostics and Biogeochemical Argo observations.
Across multiple frontal systems, squid catches exhibit a robust cross-frontal asymmetry: catches are on average 1.6-fold higher on the warm side, with an optimal fishing offset of ~10 km toward warmer waters. This pattern arises from behaviorally mediated effective transport across a sloping frontal interface. Squid undergo diel vertical migration, occupying colder subsurface layers during daytime and ascending toward frontal zones at night. Because frontal surfaces tilt downward toward the warm side, subsurface squid habitats are systematically displaced relative to surface frontal indicators and fishing locations, producing a persistent warm-side bias without invoking passive advection.
In mesoscale eddies, squid distributions display a contrasting but complementary structure. Squid preferentially aggregate near the cores of warm-core eddies, whereas in cold-core eddies they are predominantly distributed along the outer periphery. Biogeochemical Argo float observations reveal that these patterns are closely linked to differences in the vertical structure of temperature and dissolved oxygen, which modulate habitat depth and suitability. Warm-core eddies provide vertically expanded, oxygen-rich habitats conducive to retention near the eddy center, while cold-core eddies constrain suitable habitat to peripheral regions.
Together, these results demonstrate how mesoscale coherent structures—fronts acting as transport barriers and eddies acting as retentive or exclusionary features—interact with active predator behavior to shape asymmetric spatial distributions. This study highlights how effective transport and mixing of mobile marine organisms can be interpreted within a Lagrangian framework integrating physical structure, biogeochemical environment, and behavioral dynamics.
How to cite: Niu, Z., Chen, Z., Yu, W., and Wang, J.-Z.: Mesoscale fronts and eddies shape neon flying squid distribution through effective transport, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7025, https://doi.org/10.5194/egusphere-egu26-7025, 2026.
Ecological modelling has enhanced our understanding of ecosystems and biodiversity, and it has been widely used in policy decision-making. Strengthening our ability to represent ecosystems and their interactions with human activities is a global priority for achieving conservation goals. However, most existing spatial conservation frameworks rely on staticMarine Protected Areas (MPAs), defined by fixed geographic boundaries and invariant management rules that do not account for the strong temporal variability, circulation-driven connectivity, and climate-induced shifts that characterize marine ecosystems. As a result, static MPAs may fail to consistently protect key ecological processes, particularly in pelagic systems where biological organization is shaped by moving water masses. One way to address this is through the design and implementation of “dynamic” Marine Protected Areas (dMPAs) - areas that shift in space and time based on plankton trajectories, given their ecological importance. The recognition of the importance of marine plankton for human well-being has sparked proposals to prioritize plankton in marine policymaking. Yet scientific investigation into defining species-based areas has not been undertaken, despite their fundamental role in sustaining the oceans and marine life. Our research demonstrates the value of adopting dynamic approaches for conserving marine ecosystems, which are highly variable and interconnected by ocean circulation. Using a Lagrangian particle-tracking framework implemented with OceanParcels, we simulate the transport, retention, and aggregation of planktonic communities by integrating hydrodynamic fields with plankton distribution models. From these simulations, we identify spatiotemporal hotspots of particle aggregation and retention, interpreted as regions of enhanced ecological significance, which we define as Plankton Priority Areas for Conservation (PPACs). By comparing aggregation patterns across winter, spring, summer, and autumn, we identify both seasonal hotspots and areas of persistent retention. To place PPACs in a broader conservation context, we assess their overlap with four complementary indicators - biodiversity distribution, climate resilience, carbon sequestration potential, and ecosystem vulnerability. Our results demonstrate that dynamic, circulation-informed conservation areas can reveal ecologically critical regions that are poorly represented by static MPAs and provide a flexible, scalable complement to existing conservation tools in a changing ocean.
How to cite: Esteban-Cantillo, O. J., Eveillard, D., Speich, S., and Casati, R.: Priority conservation areas based on plankton particle trajectories as an alternative to marine protected areas, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22376, https://doi.org/10.5194/egusphere-egu26-22376, 2026.
Harmful Algal Blooms (HABs) caused by the haptophyte Prymnesium parvum represent an ecological and socio-economic threat in brackish waters worldwide. In summer 2022, a catastrophic bloom in the Oder River (Germany–Poland) caused mass fish kills (~360 t). The Oder River discharges into the Oder (Szczecin) Lagoon, a region with fisheries tradition and growing importance for tourism and recreation. Understanding how the bloom affected the lagoon is important for future risk assessment.
We combined long-term (1972-2024) phytoplankton monitoring data from Polish and German environmental authorities, high-resolution (200m horizontal grid from MOM – Modular Ocean Model) hydrodynamic modeling, and Lagrangian particle tracking (Parcels framework) to (1) assess historical occurrence of Prymnesiophyceae in the lagoon, (2) simulate decay and transport of the 2022 bloom from the river into the lagoon, (3) evaluate connectivity between different regions in the lagoon and the Baltic Sea, and (4) generate ecological and socio-economic risk maps.
Phytoplankton time series show that Prymnesiophyceae have been present in the lagoon since 2007, with the higher abundance (~ 100 million cells L-1) recorded in July 2022, in the German side of the lagoon. Regarding the 2022 bloom, we released virtual water parcels with a P. parvum initial abundance of 150 million cells L-1 from the river mouth. We started the simulation on July 15 2022, applying different decay scenarios (no decay, 5-day and 10-day half-life). Particles were tracked for 30 days to identify hotspots and connectivity.
Even under slow decay, all water parcels remained in the Polish sector (Wielki Zalew), affecting beaches like Plaża w Czarnocinie about 6km from the river mounth. Connectivity matrix based on releasing water parcels from German and Polish sides supported the low connectivity between lagoon portions and the Baltic in a one-month time frame. This suggests that P. parvum observed on the German side in 2022 likely originated from local or previously established populations rather than direct influence by the bloom event.
We integrated modeled bloom dispersion with ecological subjects (key fish species and habitats) and socio-economic features (fisheries harbors, bathing beaches) to produce risk maps. Polish side areas were more affected from the bloom regardless the decay rate and presented higher risk.
However, in future scenarios, increasing drought frequency may support long-term risk of toxic algae blooms in the Oder River. Monitoring identifying Prymnesiophyceae and our risk maps could serve as important management information. Also, our particle tracking applied to different hydrodynamic conditions could help to improve the understanding of risk areas.
How to cite: de Ramos, B., Rühs, S., Engelke, C., Neumann, T., and Schernewski, G.: Tracing the toxic bloom: Dispersion, impacts, and perspectives of Prymnesium parvum in the Oder Lagoon, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19360, https://doi.org/10.5194/egusphere-egu26-19360, 2026.
Atmospheric turbulence above the planetary boundary layer (PBL) plays a critical role in the vertical and horizontal mixing of aerosols and trace gases. In the troposphere, such turbulence is highly intermittent and primarily associated with jet stream boundaries and planetary-scale waves, while in the stratosphere it is strongly modulated by the quasi-biennial oscillation. Owing to the long residence times of air masses in the stratosphere, vertical mixing across the tropopause and within the stratosphere is a key process controlling stratospheric composition. Accurate representation of stratospheric transport is also essential to understand the dispersion and lifetime of sulphur aerosols injected for potential solar radiation management applications.
Lagrangian atmospheric transport models commonly represent turbulent mixing using spatially and temporally constant diffusion coefficients, despite the inherently intermittent nature of turbulence in the free atmosphere. In this study, we implement a time- and space-dependent turbulent mixing scheme in the FLEXPART model, based on local diffusion coefficients derived from the Richardson number. This parameterization is consistent with the scheme used natively in the IFS model to represent turbulent exchange above the PBL.
Using a suite of sensitivity experiments, we investigate the impact of intermittent turbulent mixing on the distribution of trace gases in both the troposphere and stratosphere. Our approach provides a unified representation of turbulence from the boundary layer to the uppermost model levels, enabling a more physically consistent treatment of atmospheric mixing across dynamical regimes.
How to cite: Agasthya, L. N. and Stohl, A.: An Integrated clear air turbulence scheme for the FLEXPART model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21936, https://doi.org/10.5194/egusphere-egu26-21936, 2026.
In this project, we approach convective instabilities from the perspective of dynamical systems theory, as we seek to identify structures that organize the global and long-term behavior of a system. Lagrangian Coherent Structures (LCSs) are patterns in fluid flows delineating regions that share a certain notion of material coherence, shape global transport and act as mixing barriers [5]. Thus, characterizing these objectively defined structures allows us to gain new insight into how certain invariant manifolds have a fundamental impact on transport and mixing processes in complex natural environments.
On the other hand, thermal convection turns out to be a fundamental process in geophysical and astrophysical flows by driving large amounts of materials through plumes that allow physical processes to be in constant renewal. Examples are convective cores in massive stars and the interior of planets [1]. It also happens to be a crucial driver of turbulence in even more complicated systems, such as accretion disks [8].
To this end, we present an analysis of coherent structures in convective flows in a particularly unexplored geometry: a 2D annulus under the action of a radial inwardly increasing gravity contribution, g∝1/r (r denotes radius). As disks in astrophysical settings are often modeled as rotating concentric cylinders with small height-to-radius ratio, this simple 2D model allows us to make a fairly global picture of the 3D case with reduced computational cost. Thus, we perform hydrodynamic simulations using spectral tau methods via open-source software Dedalus3 [4]. Equipped with a set of tracer trajectories, we implement different (but complementary) coherent structures approaches, namely objective geometrical techniques such as Finite-Time Lyapunov Exponents (FTLE) and Lagrangian-Averaged Vorticity Deviation (LAVD) [6-7] as well as network-based methods [8].
In this presentation, we will discuss our latest results combining these approaches. We will also make some useful comparisons with [2-3] that complement their Eulerian study in the same geometry.
References
[1] E.H. Anders et al., The Astrophysical Journal, 926, 169 (2022).
[2] A. Bhadra, O. Shiskina, X. Zhu, Journal of Fluid Mechanics, 999, R1 (2024).
[3] A. Bhadra, O. Shiskina, X. Zhu, International Journal of Heat and Mass Transfer, 241, 126703 (2025).
[4] K.J. Burns, G.M. Vasil, J.S. Oishi, D. Lecoanet, B.P. Brown, Phys. Rev. Res., 2, 23–68 (2020).
[5] G. Haller and G. Yuan, Physica D: Nonlinear Phenomena, 147, 352-370 (2000)
[6] G. Haller, Journal of the Mechanics and Physics of Solids, 86, 70–93 (2015).
[7] G. Haller, A. Hadjighasem, M. Farazmand, F. Huhn, Journal of Fluid Mechanics, 795,
136–173 (2016).
[8] C. Schneide, P.P. Vieweg, J. Schumacher, K. Padberg-Gehle, Chaos, 32, 013123 (2022).
[9] R. Teed and H. Latter, MNRAS, 507, 5523-5541 (2021).
How to cite: Álamo, L., Curbelo, J., and Padberg-Gehle, K.: Lagrangian methods in 2D annular Rayleigh-Bénard convection, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-112, https://doi.org/10.5194/egusphere-egu26-112, 2026.
The management of air quality in residential areas adjacent to large industrial hubs requires addressing two distinct yet overlapping challenges: monitoring pollutants with health implications and mitigating odor nuisances that significantly degrade quality of life. This study presents a multidisciplinary, integrated system designed to track, quantify and attribute these atmospheric impacts in one of Europe’s largest coastal petrochemical complexes. In the industrial area of Syracuse Province (Sicily, Italy), the emissions from refineries and port activities are a persistent source of both health concerns and community complaints. The NOSE (Network for Odour SEnsitivity) system has been operational since 2019 across the municipalities of Melilli, Priolo, Augusta and Siracusa, enabling citizens to report, via a dedicated web-app, the intensity and specific characteristics of odor episodes. In this framework, we developed an experiment based on three integrated pillars: a network of air quality and meteorological monitoring stations, the GRAMM-GRAL Lagrangian dispersion model and the data collected by the NOSE system. To address the frequent underestimation of the emissions in standard inventories, a Bayesian inversion framework was implemented to optimize prior emission estimates of benzene (C6H6), toluene (C7H8) and hydrogen sulphide (H2S). Given the limitations of Lagrangian models in representing the photochemistry of complex volatile organic compounds, C6H6 and H2S were used as conservative tracers and proxies for highly odorant non-methane hydrocarbon mixtures typically emitted by refinery processes.
Our findings demonstrate that the inversion procedure substantially improved dispersion model performance. The use of posterior emissions reduced the average Root Mean Square Error across all stations from 1.69 to 0.78 µg m-3 for C6H6, from 2.46 to 0.76 µg m-3 for C7H8, and from 8.1 to 0.81 µg m-3 for H2S. Correspondingly, the average Pearson correlation coefficient increased from 0.25 to 0.67 for C6H6 and C7H8, and from near-zero values to 0.45 for H2S. Finally, we compared forward simulations using posterior emissions with spatio-temporal clusters of odor nuisance reports submitted by citizens. These results suggest that two major coastal refineries are the primary contributors to regulated pollutant concentrations and citizen-reported odor impacts. This integrated system, which combines citizen reporting, Lagrangian dispersion modeling and Bayesian inversion, provides local authorities with a powerful tool for identifying high-impact sources and developing targeted strategies for health protection and odor mitigation.
How to cite: Veratti, G., Abita, A., Tirone, N., Resci, G., Guidi, G., Bonasoni, P., and Landi, T. C.: Tracking Industrial Emissions and Odor Nuisance through Integrated Modeling and Citizen Reporting, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21101, https://doi.org/10.5194/egusphere-egu26-21101, 2026.
The descending flux of organic particles, formed in the euphotic layer of the ocean, is a key mechanism for delivering carbon and nutrients into the deep ocean layers. Our study aimed to enhance the model and numerical Eulerian-Lagrangian algorithm developed by Maderich et al. (2025) so that it can consider the time-dependent dynamics of aggregate flux and account for ballast minerals (silicate and calcium carbonate) in aggregate sinking. In the algorithm, the Euler equations were solved for spectral concentrations of aggregate components with different sizes, while the Lagrangian equations were solved for depth and sizes of individual aggregates. Novel analytical unsteady solutions of the system of one-dimensional equations in the Eulerian framework for the particulate organic matter (POM) concentration and the Lagrangian framework for the particle mass and depth for constant and age-dependent degradation were compared with numerical solutions. The impact of a bloom event on POM profile variability was simulated using the developed numerical algorithm.
Vladimir Maderich, Igor Brovchenko, Kateryna Kovalets, Seongbong Seo, and Kyeong Ok Kim (2025). Simple Eulerian–Lagrangian approach to solving equations for sinking particulate organic matter in the ocean. Geosci. Model Dev., 18, 7373–7387
How to cite: Seo, S., Maderich, V., Kovalets, K., Brovchenko, I., and Kim, K. O.: Time-variable flux of sinking aggregates to the deep ocean: Hybrid Eulerian-Lagrangian model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9297, https://doi.org/10.5194/egusphere-egu26-9297, 2026.
The prediction of ocean surface trajectories remains a key challenge in coastal and island-influenced regions, were strong spatial variability limits model skill. Previous Lagrangian studies have shown the usefulness of drifter observations to assess trajectory predictability and to compare different sources of surface currents (e.g. Dagestad and Röhrs, 2019). In this context, Lagrangian approaches provide a direct and observation-based framework to evaluate surface transport.
This study assesses surface transport predictability around the Canary Islands using trajectories from two surface drifters (CODE/Davis type, drogued at 1 m depth) and numerical simulations performed with the OpenDrift framework (Dagestad et al., 2018). Simulations are forced with surface currents from the Iberia–Biscay–Ireland (IBI) regional ocean model distributed by the Copernicus Marine Environment Monitoring Service (CMEMS), and, where available, from the high-resolution coastal forecasting system SAMOA (Sotillo et al., 2019), operationally implemented for Spanish ports. Wind forcing is provided by ERA5 atmospheric fields, and wave-induced Stokes drift is included using IBI wave products from CMEMS.
From each observed drifter position, short-term forward simulations are performed to predict the subsequent drifter location. Model performance is quantified through the separation distance between simulated and observed positions, allowing a direct comparison of transport skill between different current products and forcing configurations.
The oceanic and atmospheric datasets used in this study correspond to operational or near-real-time products rather than fully consolidated reanalysis, reflecting realistic conditions for trajectory forecasting applications. The results reveal pronounced spatial and temporal variability in the separation between modeled and observed positions, with the relative performance of SAMOA and IBI depending on location and conditions, and neither consistently outperforming the other. While further improvements in transport predictability are expected once consolidated reanalysis products become available, the present results already provide a robust assessment of Lagrangian model skill under operational conditions.
Acknowledgments:
This work was supported by the projects SIRENA and SIRENA 2, funded by the collaboration of the Biodiversity Foundation of the Ministry for the Ecological Transition and the Demographic Challenge, through the Pleamar Program, and are co-financed by the European Union through the EMFAF (European Maritime, Fisheries and Aquaculture Fund).
References:
Dagestad, K.-F., Röhrs, J., Breivik, Ø., & Ådlandsvik, B. (2018): OpenDrift v1.0: a generic framework for trajectory modelling, Geoscientific Model Development, 11, 1405–1420, https://doi.org/10.5194/gmd-11-1405-2018
Dagestad, K.-F., & Röhrs, J. (2011): Prediction of ocean surface trajectories using satellite derived vs. modeled ocean currents, Ocean Modelling. https://doi.org/10.1016/j.rse.2019.01.001
Sotillo, M. G., Cerralbo, P., Lorente, P., Grifoll, M., Espino, M., Sanchez-Arcilla, A., & Álvarez-Fanjul, E. (2019): Coastal ocean forecasting in Spanish ports: the SAMOA operational service, Journal of Operational Oceanography, 13, 37–54, https://doi.org/10.1080/1755876X.2019.1606765
Copernicus Marine Environment Monitoring Service (CMEMS): IBI Ocean Currents Product, https://doi.org/10.48670/moi-00027
Copernicus Marine Environment Monitoring Service (CMEMS): IBI Stokes Drift Product, https://doi.org/10.48670/moi-00025
Hersbach, H. et al. (2020): ERA5 global reanalysis, Copernicus Climate Change Service (C3S), https://doi.org/10.24381/cds.adbb2d47
How to cite: Torres-Ojeda, J. S., Rodríguez-Santana, Á., Gonzáles-Ramos, A. J., Mancho, A. M., Garcia-Mendoza, A., Cuervo-Londoño, G. A., Yubero, L., and Marrero-Díaz, Á.: Lagrangian evaluation of surface transport around the Canary Islands using drifter observations and OpenDrift simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10343, https://doi.org/10.5194/egusphere-egu26-10343, 2026.
The dynamics of anisotropic crystals in cellular convective flows are critical for understanding the development of seismic anisotropy and chemical mixing in the Earth's mantle. In this study, we investigate the transport and orientation of slender rigid inclusions, proxies for anisotropic minerals such as olivine, using a Lagrangian framework. The crystals are modelled as inertialess rod-like tracers, with translational motion derived by averaging the background flow velocity along the crystal's major axis, and rotational dynamics determined by the moment of the background velocity field evaluated along the length. Unlike passive point tracers, these extended objects exhibit intrinsically coupled translation and rotation, resulting in preferred orientations (LPO) that depend sensitively on both the convective flow structure and crystal aspect ratio.
To benchmark the model, crystal dynamics are first examined in idealised laminar flows relevant to mantle kinematics, including two-dimensional Taylor–Green cellular flow and eigenmodes of Rayleigh–Bénard convection. These configurations allow for the analysis of crystal trajectories, stability near stagnation points, and the influence of density contrasts (settling) on crystal residence times. The study is then extended to vigorous, chaotic thermal convection by generating high-Rayleigh-number flows using direct numerical simulations of the Boussinesq-approximated Navier–Stokes equations. Crystals are introduced into the statistically steady flow field to simulate entrainment and mixing processes.
Confinement effects, representing lithospheric boundaries or phase transitions, are modelled using a soft-wall collision scheme, while periodic boundary conditions mimic the lateral extent of the mantle. We quantify crystal dispersion and alignment over a range of geophysical parameters, exploring variations in the Rayleigh number and crystal geometry. Statistical analyses focus on long-time orientation distribution functions (ODFs) and dispersion rates. Our results reveal how convective vigour and coherent structures (e.g., plumes and downwellings) jointly govern the evolution of fabric in the mantle, offering a controlled framework for interpreting seismic anisotropy in thermally driven flows.
How to cite: Murthi, R., V S Nath, A., and Roy, A.: Lagrangian Dynamics of Anisotropic Crystals in Vigorous Mantle Convection, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17328, https://doi.org/10.5194/egusphere-egu26-17328, 2026.
Atmospheric Lagrangian particle dispersion models (LPDMs) are commonly combined with Bayesian inversion/optimization methods to infer emission fluxes across spatial scales from local to global. These tools are central to monitoring greenhouse gases, especially CO₂, CH₄, and N₂O. However, uncertainties in flux estimates arise from multiple sources: prior flux information, representation of the background atmospheric composition, statistical model choices (including hyperparameters and error covariance assumptions), and errors in atmospheric transport. In this presentation, we describe current uncertainty quantification activities linked to ongoing projects (e.g. EYE-CLIMA). We will discuss the use of meteorological ensemble simulations to assess transport related uncertainty and explore connections with dynamical systems tools and common assumptions such as Gaussian errors. Emphasis will be placed on high-resolution transport modelling applications.
How to cite: Pisso, I.: Uncertainties associated with Lagrangian transport in greenhouse gas flux estimates, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22836, https://doi.org/10.5194/egusphere-egu26-22836, 2026.
We apply generalized spectral clustering methods to the global Argo dataset and compare the identified clusters with those obtained from established dynamical systems approaches, including finite-time Lyapunov exponents (FTLEs), Lagrangian-averaged vorticity deviation (LAVD), encounter volume, and a newly introduced tool— retention volume.
Spectral clustering provides a powerful framework for identifying Lagrangian coherent clusters from particle trajectories, grouping together trajectories that evolve similarly while remaining distinct from others. Traditionally, spectral clustering relies on physical proximity to define similarity between particles. Here, we extend this approach by incorporating additional oceanographic properties—such as temperature, salinity, density, and spiciness—into the similarity measure. This generalization allows us to detect coherent water masses that are not only spatially coherent but also share key physical characteristics.
Our results highlight the potential of the generalized spectral clustering method, combined with Argo measurements, to provide new insights into ocean transport and water mass transformations.
How to cite: Curbelo, J. and Rypina, I. I.: Application of a generalized spectral clustering method for characterizing water masses using Argo floats, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14129, https://doi.org/10.5194/egusphere-egu26-14129, 2026.
