NP6.3
Orals: Wed, 26 Apr | Room 0.16
We investigate the importance of model resolution in identifying the nature of mixing and dispersion in the Gulf of Mexico, by comparing two data-assimilative, high-resolution simulations, one of which is submesoscale-resolving. By employing both Eulerian and Lagrangian metrics, upper-ocean differences between the mesoscale- and submesoscale-resolving simulations are examined. Focusing on regions characterized by high submesoscale activity, we approach the notion of mixing by tracking the generation of Lagrangian Coherent Structures (LCSs) and transport barriers. Finite-time Lyapunov exponents (FTLE) fields reveal higher separation rates of fluid particles in the submesoscale-resolving case which indicates more vigorous mixing. Using probability density functions (PDFs), the extent of mixing homogeneity is also explored, with preliminary results suggesting that mixing is more homogeneous in the submesosclae-resolving case. Finally, we aim to identify regions of convergence in the areas of interest by advecting passive tracers that tend to organize themselves along attracting LCSs. Applications of passive tracer advection are then translated to extreme event situations, such as the Deepwater Horizon.
How to cite: Ntaganou, N., Chassignet, E., and Bozec, A.: Impact of Model Resolution on Mixing and Dispersion in the Gulf of Mexico , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7220, https://doi.org/10.5194/egusphere-egu23-7220, 2023.
Lagrangian particle dispersal simulations are widely used for studying directed connectivity between different locations in the ocean. They are used, both, for the understanding of ocean physics and for interdisciplinary questions. One biological example is the dispersal of passively drifting marine organisms.
The typical modus operandi of such “bio-physical” studies is to design an underlying Lagrangian simulation in close synchronisation with a specific biological research question. This leads to a conflation of concerns between physical and biological aspects of the study. This conflation might result in repeated and slow development cycles of re-calculation for different scenarios and hence inhibit scientific progress.
We aim at improving the separation of concerns between biological and physical components for bio-physical Lagrangian studies, by aggregating physical Lagrangian data into directed multigraphs encoding locations as nodes and multiple parallel pathways as directed edges. Those graphs condense the physics-based information on directed oceanic relations and thus serve as a basis for simultaneously answering various biological questions on connectivity. As the proposed aggregation retains the distinction of different pathways between locations, it can, to some extent, also provide information of underway environmental conditions. This greatly enhances the range of applications of our approach over existing aggregations of Lagrangian data as connectivity probability graphs.
We present a specific set of biological case studies — the multi-year spreading of two oyster diseases in the North Sea — and develop a framework that facilitates efficiently and simultaneously testing multiple biological hypotheses for marine diseases of various species based on the same processed physical data set.
How to cite: Rath, W., Schmittmann, L., Trahms, C., Kirch, F., Mock, L., and Biastoch, A.: A versatile Lagrangian-data aggregation framework for marine biological dispersal studies, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6036, https://doi.org/10.5194/egusphere-egu23-6036, 2023.
Lagrangian eddies, generally referred to as elliptic Lagrangian coherent structures (LCS) in the dynamical systems literature, are material objects that trap and transport floating particles over large distances in the ocean in a coherent fashion. In order to expand our understanding of the transport of marine tracers, we need to accurately and reliably track the evolution of vortical flow structures. Drifter trajectories represent a valuable but sparse source of information for this purpose. We employ a recently developed single-trajectory Lagrangian diagnostic tool, the trajectory rotation average (TRA), to visualize oceanic vortices (or eddies) from sparse drifter data in a quasi-objective fashion. We apply the TRA to two drifter data sets that cover various oceanographic scales: the Grand Lagrangian Deployment (GLAD) and the Global Drifter Program (GDP). Based on the TRA, we develop a general algorithm that extracts approximate eddy boundaries. We find that the TRA outperforms other available single-trajectory-based eddy detection methodologies on sparse drifter data and identifies eddies on scales that are unresolved by satellite-altimetry.
How to cite: Encinas Bartos, A. P., O. Aksamit, N., and Haller, G.: Quasi-Objective Eddy Visualization from Sparse Drifter Data, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4003, https://doi.org/10.5194/egusphere-egu23-4003, 2023.
Ocean submesoscales are characterized by horizontal scales smaller than approximately 10 km that evolve with timescales of O(1) day. Due to their small size and rapid temporal evolution, they are notoriously difficult to measure. In particular, the associated velocity field is not resolved in current satellite altimetry products. At these scales, surface ocean flows are populated by small eddies, and filaments linked with strong gradients of physical properties, such as temperature. Several recent studies indicate that submesoscale fronts are associated with important vertical velocities, thus playing a significant role in vertical transport. On that account, these fine-scale flows are key to the dynamical coupling between the interior and the surface of the ocean, as well as to plankton dynamics and marine ecology. In spite of their importance, the understanding of submesoscale ocean dynamics is still incomplete. In particular, a relevant open question concerns the role played by the ageostrophic components of the surface velocity field that manifest at these scales.
By means of numerical simulations, we investigate ocean submesoscale turbulence in the SQG+1 model, which accounts for ageostrophic motions generated at fronts, and which is obtained as a small-Rossby-number approximation of the primitive equations. In the limit of vanishing Rossby number, this system gives surface quasi-geostrophic (SQG) dynamics. In this study, we explore the effect of the ageostrophic flow components on the spreading process of Lagrangian tracer particles on the horizontal. We particularly focus on the characterization of pair-dispersion regimes and particle clustering, as a function of the Rossby number, using different indicators. The observed Lagrangian behaviours are further related to the structure of the underlying turbulent flow. We find that relative dispersion is essentially unaffected by the ageostrophic flow components. However, these components are found to be responsible for (temporary) particle aggregation in cyclonic frontal regions. These results appear interesting for the modelling of submesoscale dynamics and for comparison purposes with the new high-resolution surface current data that will be soon provided by the satellite SWOT.
How to cite: Maalouly, M., Mompean, G., and Berti, S.: Lagrangian tracer spreading in surface ocean turbulence with ageostrophic dynamics, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7212, https://doi.org/10.5194/egusphere-egu23-7212, 2023.
Vertical motions across the ocean are central to processes, like CO2 fixation, heat removal or pollutant transport, which are essential to the Earth’s climate. This presentation describes 3D conveyor routes across the Atlantic Meridional Overturning Circulation (AMOC), with the support of Lagrangian Coherent Structures. Our findings show the geometry of mixing structures in the upper and deep ocean layers. We identify among others, zones linked to vertical transport and characterize vertical transport time scales.
Acknowledgments: RB acknowledges support of a CSIC JAE intro fellowship. AMM and GGS acknowledge the support of a CSIC PIE project Ref. 202250E001 and MICINN grants PID2021-123348OB-I00 and EIN2020-112235. AMM is an active member of the CSIC Interdisciplinary Thematic Platforms POLARCSIC. JC acknowledges the support of the RyC project RYC2018-025169, the Spanish grant PID2020-114043GB-I00 and the Catalan Grant No. 2017SGR1049 and the ``Beca Leonardo a Investigadores y Creadores Culturales 2022 de la Fundación BBVA''.
How to cite: Mancho, A. M., Bruera, R., Curbelo, J., and Garcia-Sanchez, G.: Mixing and transport across the Atlantic Meridional Overturning Circulation: a 3D geometrical perspective, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-8646, https://doi.org/10.5194/egusphere-egu23-8646, 2023.
We study the transportation and rotational dynamics of a finite-sized spheroidal particle in a linear monochromatic surface gravity wave to better understand the transport dynamics of microplastics in oceanic flows. A spheroidal particle, modeled as an anisotropic tracer, attains preferential alignment in a linear wavy flow. We analyze the drift of a finite-size anisotropic particle and find that the horizontal drift of such particles can either increase or decrease depending on the initial orientation and the ratio of the size of the particle to the wavelength of the background wave field. Next, we derive the finite-size modification to the preferred alignment of the spheroidal particle with the flow propagation direction of the wave. In most scenarios, particles in the ocean can have a wide range of densities and are classified into positively and negatively buoyant particles. Negatively buoyant particles settle in a wavy flow with complex trajectories. We study the effect of the orientation and size of such particles on settling and show that the aspect ratio of the particle could alter the trajectory in the wave propagation direction. We also obtain a non-zero vertical Stokes drift. Finally, we consider the effects of fluid and particle inertia in our coupled evolution equations and study the drift and the orientation of an anisotropic particle in a wavy flow field. We demonstrate that considering such an effect could provide a complete picture of the transport and dynamics of microplastics in the upper part of the ocean that can be described more accurately.
How to cite: Mishra, H. and Roy, A.: Inertial effects on the transport of an anisotropic particle in surface gravity waves, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13939, https://doi.org/10.5194/egusphere-egu23-13939, 2023.
The Salish Sea is a semi-enclosed coastal sea between Vancouver Island and the coast of British Columbia and Washington State, invaluable from both an economic and ecologic perspective. Pacific inflow to the Sea is the main contributor of many biologically important constituents. The contribution of Pacific water masses to the flow through Juan de Fuca Strait (JdF), the Salish Sea’s primary connection to the Pacific Ocean, is explored. Quantitative Lagrangian particle tracking using Ariane was applied to two numerical ocean models (CIOPS-W in the shelf region, and SalishSeaCast in the Salish Sea) matched together within JdF. Water parcels seeded near the entrance of JdF were integrated forwards and backwards in time to assess water mass path (and properties while on this path) from the shelf region and once within the Salish Sea in more detail than previously possible. During summer upwelling, intermediate flow from the north shelf and offshore dominate inflow, while during winter downwelling, intermediate flow from the south shelf and surface flow from the Columbia River plume are the dominant sources. A weaker and less consistent estuarine flow regime in the winter led to less Pacific inflow overall and a smaller percentage of said inflow reaching the Salish Sea's inner basins than in the summer. Nevertheless, it was found that winter dynamics are the main driver of interannual variability, in part due to the strongly anti-correlated behaviour and distinct properties of the two dominant winter sources. This analysis extends the knowledge on the dynamics of Pacific inflow to the Salish Sea and highlights the importance of winter inflow to the interannual variability in biogeochemical conditions in the region.
How to cite: Beutel, B. and Allen, S.: Interannual and seasonal water mass analysis in the Salish Sea using Lagrangian particle tracking, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-316, https://doi.org/10.5194/egusphere-egu23-316, 2023.
On 13 August 2021, the Fukutoku-Okanoba submarine volcano in the North Pacific Ocean was erupted. Satellites detected many pumice rafts that drifted westward to reach southern Japan in about two months. To cope with potential danger due to the pumice rafts, it is crucial to predict their trajectories. Using a Lagrangian particle tracking model, the trajectories of the rafts were investigated. The model results showed strong sensitivity to the windage coefficient of pumice rafts, which is uncertain and could cause large errors. By comparing the model results with satellite images using a skill score, the distance between a simulated particle and the nearest observed raft divided by the travel distance of the particle, an optimal windage coefficient was estimated. The optimal windage coefficients ranging between 2 to 3% produced pathways comparable to the obervation using satellites. The pumice rafts moved from Fukutoku-Okanoba, toward the Ryukyu Islands for approximately two months before being pushed toward Taiwan by the intensified wind. The techniques presented here may become helpful in managing coastal hazards due to diverse marine debris.
How to cite: Park, Y.-G., Iskandar, M. R., kim, K., and Jin, H.: Tracking the pumice rafts from the recent eruption of the submarine volcano Fukutoku-Okanoba, Japan using Satellites and Lagrangian Particles tracking, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10296, https://doi.org/10.5194/egusphere-egu23-10296, 2023.
The implementation of continuous operational forecast systems using numerical models for coastal environments are scarce, computationally expensive, and difficult to maintain. As an alternative, computationally cheaper tools such as machine learning models can be employed. This is especially relevant when the time to produce a forecast is paramount like in oil spills, marine litter spread due to container-ship accidents, and search and rescue operations. Working in this direction, we tested the skill of an advanced deep learning model, namely a convolutional long short-term memory network (ConvLSTM), to predict the Lagrangian advection (the displacement vector of the center of mass) and the dispersion (the spread described by a covariance matrix) of patches of passive tracers. This model was trained with data from a realistic numerical simulation of the Dutch Wadden Sea: a multiple-inlet system of great ecological importance. Using the relevant drivers (wind, tidal amplitude, and atmospheric pressure), the model was set to learn the advection and dispersion after one tidal period of clouds of particles released on a 200 x 200 m grid, covering the entire DWS. Our results show that the model learned the system-wide temporal variability of both advection and dispersion, while the local spatial features were better reproduced for advection than for dispersion. We use the predicted advection and dispersion as inputs to a set of stochastic differential equations for the reconstruction of particle trajectories, as it is commonly done in particle tracking applications that employ diffusion instead of dispersion. We were able to predict the temporal evolution over several tidal periods of particle patches released from specific locations under contrasting cases like calm and stormy conditions. Our method was employed to predict only the horizontal spreading, but it can be extended to predict the 3D evolution of the particle clouds. Finally, our approach requires simulation data and relevant drivers (e.g. atmospheric forcing and tidal amplitudes) for training and the same drivers from any typical forecast systems for forecasting the evolution of particle patches, which makes it a promising operational tool.
How to cite: Fajardo-Urbina, J. M., Liu, Y., Gräwe, U., Georgievska, S., Grootes, M. W., Clercx, H. J. H., Gerkema, T., and Duran-Matute, M.: Forecast of Particle Spreading Using Machine Learning in a Complex Multiple-Inlet Coastal System, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6537, https://doi.org/10.5194/egusphere-egu23-6537, 2023.
Posters on site: Mon, 24 Apr, 16:15–18:00 | Hall X4
The increasing presence of plastics in the ocean is a harmful problem for marine ecosystems and the socio-economic sector. A recurrent type of debris gathered in waters of the Canary Islands are the identification tags employed at lobster traps deployed at the north-eastern coast of North America. Since 2016 to the present, these debris have been routinely collected and classified by the EOMAR group (MICROTROFIC Project) through coastal sampling focused on the eastern part of the Canary archipelago. In order to address this problem, a further understanding of the distribution and dynamics of these debris in the ocean is demanding. In this work, a pre-existing tool in Matlab has been upgraded to produce Lagrangian trajectories based on Marine Copernicus surface current velocity (GLORYS12V1). The main goal is to assess the trajectories that floating particles might follow in the North Atlantic subtropical gyre when released over a grid in the north-eastern coast of North America (Gulf of Maine). Our results provide a quantitative basis about the link between the North American north-eastern coast and the Canary Islands, where the presence of these and other debris is of increasing concern.
How to cite: Cividanes García, M., Aguiar González, B., Gómez Cabrera, M., Herrera Ulibarri, A., Martínez Sánchez, I., Rodríguez Santana, Á., and Machín Jiménez, F. J.: Lagrangian trajectories to assess marine plastic pollution distribution in the Canary Islands, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3970, https://doi.org/10.5194/egusphere-egu23-3970, 2023.
Mode waters are defined as thick, weakly stratified layers with homogeneous properties. They have the ability to store these properties, such as heat, carbon and nutrients, and exchange these with the surface or atmosphere during outcropping events or with other layers via mixing processes. Eighteen Degree Water (EDW) is the subtropical mode water of the western North Atlantic. Its yearly outcropping events in late winter makes it an important regulator of ocean heat, nutrients and carbon in the North Atlantic on annual timescales.
Previous studies have given insight into the formation and destruction of Eighteen Degree Water. These have largely focused on physical aspects such as EDW formation rates. Due to the importance of EDW formation in setting the biogeochemical environment in the North Atlantic, it is instructive to investigate how biogeochemical tracers are altered along EDW formation routes. This study investigates in particular how dissolved inorganic carbon (DIC) is altered along ocean water parcel trajectories as EDW is formed. To do so, we compute Lagrangian trajectories of subducted EDW backwards in time using a coupled hydrodynamic and biogeochemical model. By sampling biogeochemical tracer values along Lagrangian pathways, we construct timeseries which we use to map the dominant locations at which DIC concentrations are altered in space and time to identify the Lagrangian fingerprint of DIC in Eighteen Degree Water.
How to cite: Reijnders, D., Bakker, D., and van Sebille, E.: Lagrangian Spatiotemporal Fingerprints of Dissolved Inorganic Carbon in Eighteen Degree Water Formation, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-2725, https://doi.org/10.5194/egusphere-egu23-2725, 2023.
The direct measurement of subsurface ocean currents using neutrally buoyant free-floating instruments (or “floats”) has been used for decades by oceanographers. These observations are still useful to observe mean flows via repeated Lagrangian measurements, particularly in coastal regions where circulation schemes remain unresolved. To increase the statistical significance of these observations, it is desirable to maximize the number of measurements and therefore minimize the expense associated with collecting these measurements: with this in mind, many inexpensive observations of ocean flows can be preferable to fewer data-rich observations from more expensive platforms. In this talk, I will describe a simple neutrally buoyant GPS float that has been developed at a cost of €200 per unit to measure subsurface dispersion on timescales up to a month. The floats share some passing similarities with the original Swallow floats, thus they nicknamed “Swallow-ish”, or Swish floats. I will outline the float design; discuss the principles governing the neutrally buoyant nature of the floats; and present results from several deployments in the coastal seas of Canada, showing how these simple floats are being used track the dispersion of pollutants through coastal systems via measurements of advection, diffusion, and vertical motion.
How to cite: Stevens, S. and Pawlowicz, R.: Swish floats- an inexpensive neutrally buoyant float to monitor dispersion in coastal seas, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-520, https://doi.org/10.5194/egusphere-egu23-520, 2023.
Stirring of passive tracers on the surface of the Arabian Sea is studied from a long-term data set comprising AVISO surface geostrophic and Globcurrent on a sub-seasonal and interannual time scale. To begin with, we elucidate the spatiotemporal characterization of surface flow and sea-surface salinity. We then use lagrangian metrics such as Finite-Time Lyapunov exponents (Finite-Size Lyapunov exponents) to characterize the chaotic mixing and its probability density function on a sub-monthly timescale over the basin. Further, the M-function is used to identify and showcase the lagrangian barrier associated with mesoscale eddies and its role in transporting freshwater from the Bay of Bengal to the Arabian Sea during the northeast-monsoon period (November to February).
How to cite: Paul, N., Sukhatme, J., Mathur, M., and Sengupta, D.: Diagnosing stirring in the Arabian Sea from a long-term dataset, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4964, https://doi.org/10.5194/egusphere-egu23-4964, 2023.
Entrainment of particles by breaking waves are an important process for several applications. For example, entrainment of air bubbles is relevant for air-sea gas exchange, which in turn is relevant for climate modelling. Entrainment of oil droplets in a marine oil spill will have an effect on the fate of the oil, and help determine environmental effects. Hence, being able to measure and model these entrainment effects are important.
We are conducting experiments in a linear wave flume, with piston-type wave maker, looking at entrainment of air bubbles under breaking waves. Using a camera system with a uniform backlight and a telecentric lens, the SINTEF SilCam, we can image bubbles ranging in size from tens of micrometers, to cm scale. By accurately constraining the measurement volume, we can determine concentration of bubbles of different sizes. Taking images at high frequency, and repeating the same breaking wave many times, we are able to measure the time-development of the ensemble-average bubble size distribution.
In this poster, we describe the camera system and the image analysis pipeline, and we present some preliminary results and discuss some of the inherent challenges in measuring bubble size distributions close to the surface underneath breaking waves.
How to cite: Mostaani, A., Nordam, T., and Davies, E.: Measurements of bubble size distribution underneath breaking waves, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15441, https://doi.org/10.5194/egusphere-egu23-15441, 2023.
Lagrangian transport modelling is commonly applied for marine environmental transport problems. When applied to problems on a timescale of days to weeks, such as marine oil spills, Lagrangian models are often forced with environmental data from operational models for atmosphere, waves and ocean currents. These models typically have a temporal resolution of around 1 hour. Effects that take place on shorter timescale, such as entrainment of oil droplets and air bubbles due to breaking waves, must therefore be parametereised.
On short timescales, the random flight approach is clearly more realistic than a random walk, since the particles have a well-defined and realistic velocity, regardless of the length of the timestep, and since particles in real turbulence do not instantaneously change their direction by arbitrarily large amounts. A consequence of this is that in random flight, particles exhibit superdiffusion on short timescales, and normal diffusion on long timescales, compared to the de-correlation time of the turbulent motion. Random walk methods, on the other hand, always behave as diffusion. Hence, random flight methods are expected to be more relevant for small-scale modelling of transport on short timescale under breaking waves.
Here, we consider small-scale modelling of oil droplet and air bubble entrainment, modelling the transport close to the surface, and at high temporal resolution. We use two different Lagrangian methods: random walk (AR0) and random flight (AR1), and compare the two modelling approaches to each other, as well as to pre-existing parameterisations of the average effects of entrainment. Input parameters to the Lagrangian models are informed by experimental turbulence measurements in a wave flume, and RANS-modelling of the breaking wave. Comparison of particle transport to observations in experimental flume work is ongoing.
How to cite: Nordam, T. and Mostaani, A.: Small-scale Lagrangian modelling of air bubbles and oil droplets under breaking waves, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14947, https://doi.org/10.5194/egusphere-egu23-14947, 2023.
We study the dynamics of dust particles in various vortical flows which is relevant to geophysical context. The inertial particles are advected by the background vortex flow. The dynamics is tracked using the Maxey-Riley equation. The finite inertia of the particles make their dynamics different from passive fluid parcels, which is interesting. The dust particles may show periodic dynamics or chaotic diffusion depending on parametric variations. The result contradicts the earlier predictions that only density matched inertial particles can have chaotic dynamics, which we justify through our explanation. In addition, the heavy inertial particles in a self rotating vortex patch is observed to be attracted near the vortical region, which is contrary to the physics where they should ideally centrifuged out. The reason behind this phenomena also we explore in detail here.
How to cite: Viswanathan Sreekumari Nath, A. and Roy, A.: Lagrangian dynamics of heavy inertial particles on vortical flows, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15421, https://doi.org/10.5194/egusphere-egu23-15421, 2023.
Posters virtual: Mon, 24 Apr, 16:15–18:00 | vHall ESSI/GI/NP
Eddies are prominent features in the ocean and these energetic circulatory motions influence lateral and vertical transport of heat, mass and momentum. Ability of these eddies to coherently transport various scalar species is an important consideration in understanding freshwater transport, locating regions of harmful algal blooms, oxygen deficient zones and potential fishing zones. In this study, we present an implementation of Lagrangian Averaged Vorticity Deviation (LAVD) technique to detect materially coherent eddies from satellite derived sea surface currents in the Bay of Bengal (BoB). We also evaluate the efficacy of a Eulerian method based on sea surface height (SSH) in capturing materially coherent eddies in the BoB. Parameter values for robust detection of eddies are determined by performing a systematic sensitivity analysis in both the methods. Finite time material behaviour of eddies detected using both the methods are evaluated by numerical particle advection experiments. We then focus on material coherence of Sri Lanka Dome (SLD), an annually occurring cyclonic eddy of dynamical relevance in the BoB. SLD characteristics including its spatio-temporal evolution is discussed by analysing ocean surface currents data spanning 27 years from 1993 to 2019.
How to cite: Jayan, L., Mandayi, J., Agarwal, N., Sharma, R., and Mathur, M.: Detection of materially coherent eddies in the Bay of Bengal, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11091, https://doi.org/10.5194/egusphere-egu23-11091, 2023.
In this presentation, we discuss the recent developments of Lagrangian detection of airflow hazards near Hong Kong International Airport. In particular, data assimiliation has been applied to three-dimensional velocity field to model the near-ground airflow in the near future (from the last observation) in high resolutions. Results show a more quantifiable correspondence of Lagrangian measures to the actual airflow disturbances recorded onboard aircrafts than previous approaches. In addition, dynamic mode decomposition techniques has also been used to quickly forecast airflow hazards from two-dimensional velocity data, as a complement to the more costly three-dimensional model runs. The results indicate some correspondence of coherent structures with "truth". Both developments show promise in better identification of the coherent patterns as depicted in Lagrangian coherent structures to identify airflow hazards near ground (airports).
How to cite: Tang, W. and Chan, P. W.: Recent advances in applying Lagrangian and dynamical tools to study airflow hazards at the Hong Kong International Airport, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10861, https://doi.org/10.5194/egusphere-egu23-10861, 2023.
