Small-scale Dynamics Research Articles

High-resolution Observations of Clustered Dynamic Extreme-Ultraviolet Bright Tadpoles near the Footpoints of Corona Loops

Abstract An extreme ultraviolet (EUV) close-up view of the Sun offers unprecedented detail of heating events in the solar corona. Enhanced temporal and spatial images obtained by the Solar Orbiter during its first science perihelion enabled us to identify clustered EUV bright tadpoles (CEBTs) occurring near the footpoints of coronal loops. Combining SDO/AIA observations, we determine the altitudes of six distinct CEBTs by stereoscopy, ranging from ~1300 to 3300 km. We then notice a substantial presence of dark, cooler filamentary structures seemingly beneath the CEBTs, displaying periodic up-and-down motions lasting 3 to 5 minutes. This periodic behavior suggests an association of the majority of CEBTs with Type I spicules. Out of the ten selected CEBTs with fast downward velocity, six exhibit corrected velocities close to or exceeding 50 km s-1. These velocities notably surpass the typical speeds of Type I spicules. We explore the generation of such velocities. It indicates that due to the previous limited observations of spicules in the EUV wavelengths, they may reveal novel observational features beyond our current understanding. Gaining insights into these features contributes to a better comprehension of small-scale coronal heating dynamics.

Detection of the large-scale tidal field with galaxy multiplet alignment in the DESI Y1 spectroscopic survey

ABSTRACT We explore correlations between the orientations of small galaxy groups, or ‘multiplets’, and the large-scale gravitational tidal field. Using data from the Dark Energy Spectroscopic Instrument (DESI) Y1 survey, we detect the intrinsic alignment (IA) of multiplets to the galaxy-traced matter field out to separations of $100\,h^{-1}$ Mpc. Unlike traditional IA measurements of individual galaxies, this estimator is not limited by imaging of galaxy shapes and allows for direct IA detection beyond redshift $z=1$. Multiplet alignment is a form of higher order clustering, for which the scale-dependence traces the underlying tidal field and amplitude is a result of small-scale ($\lt 1h^{-1}$ Mpc) dynamics. Within samples of bright galaxies, luminous red galaxies (LRG) and emission-line galaxies, we find similar scale-dependence regardless of intrinsic luminosity or colour. This is promising for measuring tidal alignment in galaxy samples that typically display no IA. DESI’s LRG mock galaxy catalogues created from the A bacusS ummitN-body simulations produce a similar alignment signal, though with a 33 per cent lower amplitude at all scales. An analytic model using a non-linear power spectrum (NLA) only matches the signal down to 20 $h^{-1}$ Mpc. Our detection demonstrates that galaxy clustering in the non-linear regime of structure formation preserves an interpretable memory of the large-scale tidal field. Multiplet alignment complements traditional two-point measurements by retaining directional information imprinted by tidal forces, and contains additional line-of-sight information compared to weak lensing. This is a more effective estimator than the alignment of individual galaxies in dense, blue, or faint galaxy samples.

Primary colonization and small-scale dynamics of non-indigenous benthic species: a case study

Primary colonization and small-scale dynamics of non-indigenous benthic species: a case study

Neural downscaling for complex systems: from large-scale to small-scale by neural operator

Researchers have long been working on interpreting and predicting the dynamics of complex systems in various fields. Conventional methods including full-scale simulations and reduced-order models are used to solve related problems, but often yield unsatisfactory results in terms of precision and computational efficiency. This is primarily due to the challenges posed by simulating small-scale dynamics. An alternative consideration is to leverage well-represented and readily accessible large-scale dynamics to assist small-scale modelling. This paper proposes a novel methodology, named as Neural Downscaling (ND), that effectively captures small-scale dynamics within a complementary subspace from corresponding large-scale dynamics well-represented in a low-dimensional space. The framework of ND integrates neural operator techniques with the principles of inertial manifold and nonlinear Galerkin theory. The effectiveness and efficiency of ND are demonstrated in the complex systems governed by Kuramoto–Sivashinsky and Navier–Stokes equations. Being an unprecedentedly deterministic model targeted at general small-scale dynamics, ND sheds light on the intricate spatiotemporal nonlinear dynamics of complex systems and reveals how small-scale dynamics are interacting with large-scale dynamics.

A new airborne system for simultaneous high-resolution ocean vector current and wind mapping: first demonstration of the SeaSTAR mission concept in the macrotidal Iroise Sea

Abstract. Coastal seas, shelf seas and marginal ice zones are dominated by small-scale ocean surface dynamic processes that play a vital role in the transport and exchange of climate-relevant properties such as carbon, heat, water and nutrients between land, ocean, ice and atmosphere. Mounting evidence indicates that ocean scales below 10 km have far-ranging impacts on air–sea interactions, lateral ocean dispersion, vertical stratification, ocean carbon cycling and marine productivity – governing exchanges across key interfaces of the Earth system, the global ocean, and atmosphere circulation and climate. Yet, these processes remain poorly observed at the fine spatial and temporal scales necessary to resolve them. The Ocean Surface Current Airborne Radar (OSCAR) is a new airborne instrument with the capacity to inform these questions by mapping vectorial fields of total ocean surface currents and winds at high resolution over a wide swath. Developed for the European Space Agency (ESA), OSCAR is the airborne demonstrator of the satellite mission concept SeaSTAR, which aims to map total surface current and ocean wind vectors with unprecedented accuracy, spatial resolution and temporal revisit across all coastal seas, shelf seas and marginal ice zones. Like SeaSTAR, OSCAR is an active microwave synthetic aperture radar along-track interferometer (SAR-ATI) with optimal three-azimuth sensing enabled by unique highly squinted beams. In May 2022, OSCAR was flown over the Iroise Sea, France, in its first scientific campaign as part of the ESA-funded SEASTARex project. The campaign successfully demonstrated the capabilities of OSCAR to produce high-resolution 2D images of total surface current vectors and near-surface ocean vector winds, simultaneously, in a highly dynamic, macrotidal coastal environment. OSCAR current and wind vectors show excellent agreement with ground-based X-band-radar-derived surface currents, numerical model outputs and NovaSAR-1 satellite SAR imagery, with root mean square differences from the X-band radar better than 0.2 m s−1 for currents at 200 m resolution. These results are the first demonstration of simultaneous retrieval of total current and wind vectors from a high-squint three-look SAR-ATI instrument and the first geophysical validation of the OSCAR and SeaSTAR observing principle. OSCAR presents a remarkable new ocean observing capability to support the study of small-scale ocean dynamics and air–sea interactions across the Earth's coastal, shelf and polar seas.

The gendered dimensions of small-scale fishing activities: A case study from coastal Kenya

Although women contribute substantially to the small-scale fisheries sector globally, in many countries there is a severe lack of gender-disaggregated data on fishing activities. This gender data gap hampers a comprehensive understanding of small-scale fisheries dynamics with implications for fisheries management and food security. In this study, we investigate women's and men's engagement in small-scale fishing through a case study in coastal Kenya, a region characterized by a high dependence on fisheries for local livelihoods and nutritional needs. We applied a mixed method approach, combining participant observation, photography, semi-structured interviews on gender identities (n = 11) and gendered fishing practices (n = 28), an individual survey (n = 141), and pebble games (n = 35). Our results reveal a marked gendered division of labor across the seascape, with women mostly fishing in intertidal areas and men beyond the reef. Further, we find that women's fishing practices are characterized by less fishing gear, less catch, a lower functional diversity of catches, less fishing effort, and less income than those of men. However, women's catches contribute significantly to local diets, accounting for up to 50% of the fish and seafood consumed in fisherwomen-headed households. Despite women's fishing activities appearing less productive and profitable that those of men, they are important for achieving food security in Kenyan coastal communities. Results from this study contribute to broadening our understanding of the gendered dimensions of small-scale fishing and highlight relevant information for developing gender-inclusive management strategies. We conclude by providing key recommendations for fisheries research, management, and governance.

Prominence and coronal rain formation by steady versus stochastic heating and how we can relate it to observations

Prominences and coronal rain are two forms of coronal condensations for which we still lack satisfactory details on the formation pathways and conditions under which the two come to exist. Even more so, it is unclear why prominences and filaments appear in so many different shapes and sizes, with a vertical rather than a horizontal structure or vice-versa. It is also not clear why coronal rain is present in some cases and not in others. Our aim is to understand the formation process of prominences and coronal rain in more detail by exploring what influence two specific heating prescriptions can have on the resulting formation and evolution, using simulations. We try to determine why we see prominences with such a variety in their properties, particularly by looking at the large-scale topology and dynamics. We attempted to recreate some of these aspects by simulating different types of localised heating. Besides the differences we see on a large scale, we also attempted to determine what the smaller-scale phenomena are, such as reconnection, the influence of resistivity (or lack thereof), the influence of flows and oscillations. We compared prominences that formed via a steady versus stochastic type of heating. We performed 2.5D simulations using the open-source MPI-AMRVAC code. To further extend the work and allow for future direct comparison with observations, we used Lightweaver to form spectra of the filament view of our steady case prominence. With that, we analysed a reconnection event that shares certain characteristics with nanojets. We show how different forms of localised heating that induce thermal instability result in prominences with different properties. The steady form of heating results in prominence with a clear vertical structure stretching across the magnetic field lines. On the other hand, stochastic heating produces many threads that predominantly have a horizontal motion along the field lines. Furthermore, the specific type of heating also influences the small-scale dynamics. In the steady heating case, the prominence is relatively static; however, there is evidence of reconnection happening almost the entire time the prominence is present. In the case of stochastic heating, the threads are highly dynamic, with them also exhibiting a form of transverse oscillation (strongly resembling the decayless type) similar to the vertically polarised oscillations previously found in observations. The fact that the threads in the stochastic heating case are constantly moving along the field lines suppresses any conditions for reconnection. It, therefore, appears that, to first order, the choice of heating prescription defines whether the prominence-internal dynamics are oriented vertically or horizontally. We closely inspected a sample reconnection event and computed the synthetic optically thick radiation using the open-source Lightweaver radiative transfer framework. We find the associated dynamics to imprint clear signatures, both in Doppler and emission, on the resulting spectra that should be testable with state-of-the-art instrumentation such as DKIST.

Applicability Study of Euler–Lagrange Integration Scheme in Constructing Small-Scale Atmospheric Dynamics Models

The atmospheric flow field and weather processes exhibit complex and variable characteristics at small scales, involving interactions between terrain features and atmospheric physics. To investigate the mechanisms of these process further, this study employs a Lagrangian particle motion model combined with a Euler background field approach to construct a small-scale atmospheric flow field model. The model streamlines the modeling process by combining the benefits of the Lagrangian dynamics model and the Eulerian integration scheme. To verify the effectiveness of the Euler–Lagrange hybrid model, experiments using the Fluent wind field model were conducted for comparison. The results show that both models have their advantages in handling terrain-induced wind fields. The Fluent model excels in simulating the general characteristics of wind fields under specific terrain, while the Euler–Lagrange hybrid model is better at capturing the upstream and downstream disturbances of the terrain on the atmospheric flow field. These findings provide powerful tools for in-depth diagnostic analysis of atmospheric flow simulation and convective precipitation processes. Notably, the Euler–Lagrange hybrid model demonstrates excellent computational efficiency, with an average computation time of approximately 2 s per time step in a Python environment, enabling rapid simulation of 40 time steps within approximately 90 s.

RABBITS – II. The impact of AGN feedback on coalescing supermassive black holes in disc and elliptical galaxy mergers

ABSTRACT In this study of the ‘Resolving supermAssive Black hole Binaries In galacTic hydrodynamical Simulations’ (RABBITS) series, we investigate the orbital evolution of supermassive black holes (SMBHs) during galaxy mergers. We simulate both disc and elliptical galaxy mergers using the ketju code, which can simultaneously follow galaxy (hydro-)dynamics and small-scale SMBH dynamics with post-Newtonian corrections. With our SMBH binary subgrid model, we show how active galactic nuclei (AGNs) feedback affects galaxy properties and SMBH coalescence. We find that simulations without AGN feedback exhibit excessive star formation, resulting in merger remnants that deviate from observed properties. Kinetic AGN feedback proves more effective than thermal AGN feedback in expelling gas from the centre and quenching star formation. The different central galaxy properties, which are a result of distinct AGN feedback models, lead to varying rates of SMBH orbital decay. In the dynamical friction phase, galaxies with higher star formation and higher SMBH masses possess denser centres, become more resistant to tidal stripping, experience greater dynamical friction, and consequently form SMBH binaries earlier. As AGN feedback reduces gas densities in the centres, dynamical friction by stars dominates over gas. In the SMBH hardening phase, compared to elliptical mergers, disc mergers exhibit higher central densities of newly formed stars, resulting in accelerated SMBH hardening and shorter merger time-scales (i.e. $\lesssim 500$ Myr versus $\gtrsim 1$ Gyr). Our findings highlight the importance of AGN feedback and its numerical implementation in understanding the SMBH coalescing process, a key focus for low-frequency gravitational wave observatories.

Turbulent spot formation in three-dimensional yukawa liquids using large-scale molecular dynamics simulation—effect of system size

We have performed classical ‘first principles’ 3D Molecular Dynamics (MD) simulation of plane-Couette flow (PCF) in a 3D Yukawa liquid. The main aim of the present investigation is to study the effect of stream-wise (flow-direction) and span-wise (transverse direction to the flow) width on the subcritical transition to turbulence in plane Couette flow (PCF), separately. In the past, taking very large-aspect ratio systems, subcritical transition to turbulence in PCF has been studied in great detail. However, the effect of stream-wise and span-wise width on the turbulent dynamics separately, have not been studied in detail. In the present work, we have investigated the effect of stream-wise and span-wise width or length and found that the stream-wise length enhances the large-scale energy, which gives rise to strong large-scale flow, and span-wise width enhances the small-scale energy, which gives rise to strong small-scale structures. In other words, topology of the turbulent spot is observed to change with the change in system size. The spectral separation between the modes governing the large and small-scale dynamics improves with the increase in system sizes. The connection between the stream-wise vortices and the stream-wise velocity streaks is investigated in details. We have found that the number stream-wise velocity streaks is one unit larger than the number of stream-wise vortices. A qualitative comparison between the results obtained from the MD simulation and the hydrodynamics experiment is presented in this article. The behavior of the system was observed to vary with the range of interactions among the dust grains.

Departure from the statistical equilibrium of large scales in forced three-dimensional homogeneous isotropic turbulence

We study the statistically steady states of the forced dissipative three-dimensional homogeneous isotropic turbulence at scales larger than the forcing scale in real separation space. The probability density functions (p.d.f.s) of longitudinal velocity difference at large separations are close to, but deviate from, Gaussian, measured by their non-zero odd parts. The analytical expressions of the third-order longitudinal structure functions derived from the Kármán–Howarth–Monin equation prove that the odd-part p.d.f.s of velocity differences at large separations are small but non-zero. Specifically, when the forcing effect in the displacement space decays exponentially as the displacement tends to infinity, the odd-order longitudinal structure functions have a power-law decay with an exponent of $-$ 2, implying a significant coupling between large and small scales. Under the assumption that forcing controls the large-scale dynamics, we propose a conjugate regime to Kolmogorov's inertial range, independent of the forcing scale, to capture the odd parts of p.d.f.s. Thus, dynamics of large scales departs from the absolute equilibrium, and we can partially recover small-scale information without explicitly resolving small-scale dynamics. The departure from the statistical equilibrium is quantified and found to be viscosity-independent. Even though this departure is small, it is significant and should be considered when studying the large scales of the forced three-dimensional homogeneous isotropic turbulence.

Amplification and Dissipation of Magnetic Fields in Accreting Compact Objects

Magnetic fields play a crucial role in shaping the dynamics of accreting compact objects. Whether we consider the formation of a proto-neutron star during the gravitational collapse of a massive star or the accretion disk around a black hole after a compact binary merger, a key process that remains challenging to include in large-scale simulations is the amplification and dissipation of magnetic fields driven by turbulent fluid motions. Despite the enormous increase in computational power currently available, the large separation between all the relevant spatial and temporal scales still poses severe limits to what can be achieved with ideal fluid simulations. One way to tackle such issue is to rely on sub-grid models, which however need to be appropriately tuned in light of models probing the small-scale dynamics. In this work we present the current state-of-the-art of dynamo models in proto-neutron stars, which aim at describing the amplification of magnetar-like magnetic fields during the gravitational collapse of a massive star. We also review some of the works from the past few years that included turbulent dynamos in accretion disks around a black holes, relying on a mean-field formalism. Finally, we will present a recent study on polar jets with explicit turbulent resistivity which showcases the importance of employing highly accurate numerical schemes.

Risk-based hydrologic design under climate change using stochastic weather and watershed modeling

Water resources planning and management requires the estimation of extreme design events. Anticipated climate change is playing an increasingly prominent role in the planning and design of long-lived infrastructure, as changes to climate forcings are expected to alter the distribution of extremes in ways and to extents that are difficult to predict. One approach is to use climate projections to force hydrologic models, but this raises two challenges. First, global climate models generally focus on much larger scales than are relevant to hydrologic design, and regional climate models that better capture small scale dynamics are too computationally expensive for large ensemble analyses. Second, hydrologic models systematically misrepresent the variance and higher moments of streamflow response to climate, resulting in a mischaracterization of the extreme flows of most interest. To address both issues, we propose a new framework for non-stationary risk-based hydrologic design that combines a stochastic weather generator (SWG) that accurately replicates basin-scale weather and a stochastic watershed model (SWM) that accurately represents the distribution of extreme flows. The joint SWG-SWM framework can generate large ensembles of future hydrologic simulations under varying climate conditions, from which design statistics and their uncertainties can be estimated. The SWG-SWM framework is demonstrated for the Squannacook River in the Northeast United States. Standard approaches to design flows, like the T-year flood, are difficult to interpret under non-stationarity, but the SWG-SWM simulations can readily be adapted to risk and reliability metrics which bare the same interpretation under stationary and non-stationary conditions. As an example, we provide an analysis comparing the use of risk and more traditional T-year design events, and conclude that risk-based metrics have the potential to reduce regret of over- and under-design compared to traditional return-period based analyses.

A machine learning model for reconstructing skin-friction drag over ocean surface waves

In order to improve the predictive abilities of weather and climate models, it is essential to understand the behaviour of wind stress at the ocean surface. Wind stress is contingent on small-scale interfacial dynamics typically not directly resolved in numerical models. Although skin friction contributes considerably to the total stress up to moderate wind speeds, it is notoriously challenging to measure and predict using physics-based approaches. This work proposes a supervised machine learning (ML) model that estimates the spatial distribution of the skin-friction drag over wind waves using solely wave elevation and wave age, which are relatively easy to acquire. The input–output pairs are high-resolution wave profiles and their corresponding surface viscous stresses collected from laboratory experiments. The ML model is built upon a convolutional neural network architecture that incorporates the Mish nonlinearity as its activation function. Results show that the model can accurately predict the overall distribution of viscous stresses; it captures the peak of viscous stress at/near the crest and its dramatic drop to almost null just past the crest in cases of intermittent airflow separation. The predicted area-aggregate skin friction is also in excellent agreement with the corresponding measurements. The proposed method offers a practical pathway for estimating both local and area-aggregate skin friction and can be easily integrated into existing numerical models for the study of air–sea interactions.

Small-scale computational fluid dynamics modelling of the wave induced ice floe-grease ice interaction in the Antarctic marginal ice zone

Computational sea ice models have been developed to simulate sea ice formation, melt and motion characteristics on a regional scale. However, the highly dynamic sea ice behaviour in the Antarctic marginal ice zone (MIZ), the area where sea ice and ocean waves interact, still eludes reliable prediction. This is due to the complex sea ice composition consisting of relatively small and mobile ice floes governed by collision and fracture mechanisms. To improve the accuracy of sea ice models, the realistic sea ice distribution needs to be accounted for at a high resolution so that key aspects defining the interplay of ice motion and wave propagation can be suitably distinguished. In this work a computational fluid dynamics model based on the small-scale continuum approach has been developed to simulate the dynamics of a heterogeneous sea ice cover. The model makes use of a realistic sea ice layout and studies the mechanical behaviour of sea ice as affected by wave forcing and the specific material properties of ice floes and grease ice. Taking advantage of the continuum approach paired with a heterogeneous sea ice cover, the floe-grease ice interaction is elucidated by discussing detailed temporal and spatial distributions of the mechanical response of sea ice. Results show that the interplay between waves and the ice floe collision behaviour is directly controlled by sea ice inertia, where the frequency and severity of ice floe collisions increase with the wave period. Furthermore, the interaction of grease ice with ice floes through form drag at the interface leads to high localised grease ice strain rate gradients and low viscosity values due its shear thinning characteristics.

Unveiling fracture mechanics of a curved coating/substrate system by combined digital image correlation and numerical finite element analyses

A mechanism of coated, curved substrate failure is characterized via a C-ring compression test and multiscale modeling analysis. Coating crack formation is driven by sudden through-thickness cleavage in accordance with Mode I fracture type. The fracture is arrested at the coating/substrate interface. The cracks continue to widen as the underlying substrate experiences periodic regions of high stress under the crack and regions of relaxed stresses under the remaining intact coating. An analytical, closed form solution model developed via curved beam theory captures the hoop stress in the axis transverse to external loading and predicts the external load at crack initiation. After the onset of cracking, the system transitions to cleavage driven failure, which is simulated via element deletion failure in a small-scale explicit dynamics finite element model. The macroscale explicit dynamics finite element model, analytical solution, and bulk experimental results agree. The correlation between coating microstructure and deposition method is also investigated and reveals that high interfacial roughness and equiaxed grain morphology correspond to higher loader carrying capability and lower crack density while low interfacial roughness and smooth columnar grains correspond to higher strain to coating failure.

Characterizing Small-Scale Dynamics of Navier-Stokes Turbulence with Transverse Lyapunov Exponents: A Data Assimilation Approach.

Data assimilation (DA) of turbulence, which involves reconstructing small-scale turbulent structures based on observational data from large-scale ones, is crucial not only for practical forecasting but also for gaining a deeper understanding of turbulent dynamics. We propose a theoretical framework for DA of turbulence based on the transverse Lyapunov exponents (TLEs) in synchronization theory. Through stability analysis using TLEs, we identify a critical length scale as a key condition for DA; turbulent dynamics smaller than this scale are synchronized with larger-scale turbulent dynamics. Furthermore, considering recent findings for the maximal Lyapunov exponent and its relation with the TLEs, we clarify the Reynolds number dependence of the critical length scale.

Long-Term Passive Acoustic Monitoring to Support Adaptive Management in a Sciaenid Fishery (Tagus Estuary, Portugal)

AbstractPassive acoustic monitoring (PAM) is useful for monitoring vocal fish but has had so far limited application in fisheries management. Here, four years (2016–2019) of concurrent daily catch and effort fishery data in Portugal and species-specific vocal activity in the Tagus estuary are compared to describe biological and small-scale fishery dynamics for a large sciaenid fish, the meagre (Argyrosomus regius), that aggregates to spawn. Consistent patterns in seasonality of acoustic and fisheries variables indicate that most fishing takes place within the Tagus estuary in spring and summer months, when higher vocal activity related to spawning aggregations is detected in the PAM station. Good fit of statistical models shows that PAM (sound pressure level in the third-octave band with centre frequency at 500 kHz during dusk) and PAM-supported variables (mean weekly catch per first sale transaction) can provide useful surveillance indicators to improve local management. Signs of overexploitation and hyperstability are detected and communicated to the estuarine fishing communities with the aim to initiate an adaptive local management cycle. The approach can be relevant for fisheries targeting other vocal fish that seasonally aggregate and face similar threats of overexploitation. Graphical Abstract

Passive scalar small-scale anisotropy and mixing characteristics in magnetohydrodynamic turbulent channel flow

In wall-bounded turbulent flows, both velocity and scalar fluctuations exhibit inhomogeneity and anisotropy. This study investigates the statistical properties of the small-scale scalar fluctuations in a turbulent channel flow at Reτ≈585 using direct numerical simulations with and without a magnetic field. The influence of the Hartmann, Ha, and Prandtl, Pr, numbers on turbulent velocity and passive scalar fields is examined at Ha=0, 20, and 40 and Pr=0.7 and 1.4. Small-scale dynamics of the passive scalar and velocity fields are studied, analyzing their probability density functions and higher-order moments, as well as their gradients. We observed that the magnetic field substantially changes flow dynamics such as the typical cliff-and-ramp type structures. The presence of the magnetic field led to statistical anisotropy, even at small-scale gradient fields. The findings reveal that the skewness of the normal derivative of scalar fluctuations remains at the order of 2. We investigated mixing characteristics by analyzing scalar dissipation rates. Scalar dissipation rates near the wall remain close to unity and decrease sharply toward the channel center, reaching a minimum value. Moreover, an increase in scalar dissipation rates leads to a decrease in the corresponding mixing timescale of the flow. This could suggest a connection between an increase in the Lorentz force and potential adjustments in the mixing timescale, potentially contributing to enhance overall mixing. Additionally, we argue that combined effects of strong intermittency and persistency of anisotropy at small scales can influence the mixing characteristics of magnetohydrodynamic turbulent flow.

A remote sensing approach for exploring the dynamics of jellyfish, relative to the water current

Drifting in large numbers, jellyfish often interfere in the operation of nearshore electrical plants, cause disturbances to marine recreational activity, encroach upon local fish populations, and impact food webs. Understanding the dynamic mechanisms behind jellyfish behavior is of importance in order to create migration models. In this work, we focus on the small-scale dynamics of jellyfish and offer a novel method to accurately track the trajectory of individual jellyfish with respect to the water current. The existing approaches for similar tasks usually involve a surface float tied to the jellyfish for location reference. This operation may induce drag on the jellyfish, thereby affecting its motion. Instead, we propose to attach an acoustic tag to the jellyfish’s bell and then track its geographical location using acoustic beacons, which detect the tag’s emissions, decode its ID and depth, and calculate the tag’s position via time-difference-of-arrival acoustic localization. To observe the jellyfish’s motion relative to the water current, we use a submerged floater that is deployed together with the released tagged jellyfish. Being Lagrangian on the horizontal plane while maintaining an on-demand depth, the floater drifts with the water current; thus, its trajectory serves as a reference for the current’s velocity field. Using an acoustic modem and a hydrophone mounted to the floater, the operator from the deploying boat remotely changes the depth of the floater on-the-fly, to align it with that of the tagged jellyfish (as reported by the jellyfish’s acoustic tag), thereby serving as a reference for the jellyfish’s 3D motion with respect to the water current. We performed a proof-of-concept to demonstrate our approach over three jellyfish caught and tagged in Haifa Bay, and three corresponding floaters. The results present different dynamics for the three jellyfish, and show how they can move with, and even against, the water current.