Browse
Submit Data
Databases
API
Help

Dataset Information

24 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Deep convection-driven vortex formation on Jupiter and Saturn.

ABSTRACT: The surfaces of Jupiter and Saturn have magnificent vortical storms that help shape the dynamic nature of their atmospheres. Land- and space-based observational campaigns have established several properties of these vortices, with some being similar between the two planets, while others are different. Shallow-water hydrodynamics, where the vortices are treated as shallow weather-layer phenomenon, is commonly evoked for explaining their formation and properties. Here, we report novel formation mechanisms for vortices where the primary driving mechanism is the deep planetary convection occurring in these planets. Using three-dimensional simulations of turbulent convection in rotating spherical shells, we propose two ideas: (i) Rotating turbulent convection generates deep axially aligned cyclones and anticyclones; (ii) a deep planetary dynamo acts to promote additional anticyclones, some as large as Jupiter's Great Red Spot, in an overlying atmospheric layer. We use these ideas to interpret several observational properties of vortices on Jupiter and Saturn.

SUBMITTER: Yadav RK

PROVIDER: S-EPMC7673750 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Deep rotating convection generates the polar hexagon on Saturn.

Project description:Numerous land- and space-based observations have established that Saturn has a persistent hexagonal flow pattern near its north pole. While observations abound, the physics behind its formation is still uncertain. Although several phenomenological models have been able to reproduce this feature, a self-consistent model for how such a large-scale polygonal jet forms in the highly turbulent atmosphere of Saturn is lacking. Here, we present a three-dimensional (3D) fully nonlinear anelastic simulation of deep thermal convection in the outer layers of gas giant planets that spontaneously generates giant polar cyclones, fierce alternating zonal flows, and a high-latitude eastward jet with a polygonal pattern. The analysis of the simulation suggests that self-organized turbulence in the form of giant vortices pinches the eastward jet, forming polygonal shapes. We argue that a similar mechanism is responsible for exciting Saturn's hexagonal flow pattern.

| S-EPMC7322008 | biostudies-literature

Jump rope vortex in liquid metal convection.

Project description:Understanding large-scale circulations (LSCs) in turbulent convective systems is important for the study of stars, planets, and in many industrial applications. The canonical model of the LSC is quasi-planar with additional horizontal sloshing and torsional modes [Brown E, Ahlers G (2009) J Fluid Mech 638:383-400; Funfschilling D, Ahlers G (2004) Phys Rev Lett 92:194502; Xi HD et al. (2009) Phys Rev Lett 102:044503; Zhou Q et al. (2009) J Fluid Mech 630:367-390]. Using liquid gallium as the working fluid, we show, via coupled laboratory-numerical experiments in tanks with aspect ratios greater than unity ([Formula: see text]), that the LSC takes instead the form of a "jump rope vortex," a strongly 3D mode that periodically orbits around the tank following a motion much like a jump rope on a playground. Further experiments show that this jump rope flow also exists in more viscous fluids such as water, albeit with a far smaller signal. Thus, this jump rope mode is an essential component of the turbulent convection that underlies our observations of natural systems.

| S-EPMC6294884 | biostudies-other

Deep learning in turbulent convection networks.

Project description:We explore heat transport properties of turbulent Rayleigh-Bénard convection in horizontally extended systems by using deep-learning algorithms that greatly reduce the number of degrees of freedom. Particular attention is paid to the slowly evolving turbulent superstructures-so called because they are larger in extent than the height of the convection layer-which appear as temporal patterns of ridges of hot upwelling and cold downwelling fluid, including defects where the ridges merge or end. The machine-learning algorithm trains a deep convolutional neural network (CNN) with U-shaped architecture, consisting of a contraction and a subsequent expansion branch, to reduce the complex 3D turbulent superstructure to a temporal planar network in the midplane of the layer. This results in a data compression by more than five orders of magnitude at the highest Rayleigh number, and its application yields a discrete transport network with dynamically varying defect points, including points of locally enhanced heat flux or "hot spots." One conclusion is that the fraction of heat transport by the superstructure decreases as the Rayleigh number increases (although they might remain individually strong), correspondingly implying the increased importance of small-scale background turbulence.

| S-EPMC6500159 | biostudies-literature

Convection-driven microfabricated hydrogels for rapid biosensing.

Project description:A microscale biosensing platform using rehydration-mediated swelling of bio-functionalized hydrogel structures and rapid target analyte capture is described. Induced convective flow mitigates diffusion limited incubation times, enabling model assays to be completed in under three minutes. Assay design parameters have been evaluated, revealing fabrication criteria required to tune detection sensitivity.

| S-EPMC7819640 | biostudies-literature

Convection-driven generation of long-range material gradients.

Project description:Natural materials exhibit anisotropy with variations in soluble factors, cell distribution, and matrix properties. The ability to recreate the heterogeneity of the natural materials is a major challenge for investigating cell-material interactions and for developing biomimetic materials. Here we present a generic fluidic approach using convection and alternating flow to rapidly generate multi-centimeter gradients of biomolecules, polymers, beads and cells and cross-gradients of two species in a microchannel. Accompanying theoretical estimates and simulations of gradient growth provide design criteria over a range of material properties. A poly(ethylene-glycol) hydrogel gradient, a porous collagen gradient and a composite material with a hyaluronic acid/gelatin cross-gradient were generated with continuous variations in material properties and in their ability to regulate cellular response. This simple yet generic fluidic platform should prove useful for creating anisotropic biomimetic materials and high-throughput platforms for investigating cell-microenvironment interactions.

| S-EPMC2813888 | biostudies-literature

Laser speckle imaging based on photothermally driven convection.

Project description:Laser speckle imaging (LSI) is an interferometric technique that provides information about the relative speed of moving scatterers in a sample. Photothermal LSI overcomes limitations in depth resolution faced by conventional LSI by incorporating an excitation pulse to target absorption by hemoglobin within the vascular network. Here we present results from experiments designed to determine the mechanism by which photothermal LSI decreases speckle contrast. We measured the impact of mechanical properties on speckle contrast, as well as the spatiotemporal temperature dynamics and bulk convective motion occurring during photothermal LSI. Our collective data strongly support the hypothesis that photothermal LSI achieves a transient reduction in speckle contrast due to bulk motion associated with thermally driven convection. The ability of photothermal LSI to image structures below a scattering medium may have important preclinical and clinical applications.

| S-EPMC4962529 | biostudies-literature

Formation of electron radiation belts at Saturn by Z-mode wave acceleration.

Project description:At Saturn electrons are trapped in the planet's magnetic field and accelerated to relativistic energies to form the radiation belts, but how this dramatic increase in electron energy occurs is still unknown. Until now the mechanism of radial diffusion has been assumed but we show here that in-situ acceleration through wave particle interactions, which initial studies dismissed as ineffectual at Saturn, is in fact a vital part of the energetic particle dynamics there. We present evidence from numerical simulations based on Cassini spacecraft data that a particular plasma wave, known as Z-mode, accelerates electrons to MeV energies inside 4?RS (1?RS?=?60,330?km) through a Doppler shifted cyclotron resonant interaction. Our results show that the Z-mode waves observed are not oblique as previously assumed and are much better accelerators than O-mode waves, resulting in an electron energy spectrum that closely approaches observed values without any transport effects included.

| S-EPMC6265320 | biostudies-literature

The vortex-driven dynamics of droplets within droplets.

Project description:Understanding the fluid-structure interaction is crucial for an optimal design and manufacturing of soft mesoscale materials. Multi-core emulsions are a class of soft fluids assembled from cluster configurations of deformable oil-water double droplets (cores), often employed as building-blocks for the realisation of devices of interest in bio-technology, such as drug-delivery, tissue engineering and regenerative medicine. Here, we study the physics of multi-core emulsions flowing in microfluidic channels and report numerical evidence of a surprisingly rich variety of driven non-equilibrium states (NES), whose formation is caused by a dipolar fluid vortex triggered by the sheared structure of the flow carrier within the microchannel. The observed dynamic regimes range from long-lived NES at low core-area fraction, characterised by a planetary-like motion of the internal drops, to short-lived ones at high core-area fraction, in which a pre-chaotic motion results from multi-body collisions of inner drops, as combined with self-consistent hydrodynamic interactions. The onset of pre-chaotic behavior is marked by transitions of the cores from one vortex to another, a process that we interpret as manifestations of the system to maximize its entropy by filling voids, as they arise dynamically within the capsule.

| S-EPMC7782531 | biostudies-literature

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales.

Project description:A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014-2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation-buoyancy relation across the tropics. Deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.

| S-EPMC5939085 | biostudies-other

Project description:The effect of the Madden-Julian Oscillation (MJO) on the Northern Hemisphere wintertime stratospheric polar vortex in the period preceding stratospheric sudden warmings is evaluated in operational subseasonal forecasting models. Reforecasts which simulate stronger MJO-related convection in the Tropical West Pacific also simulate enhanced heat flux in the lowermost stratosphere and a more realistic vortex evolution. The time scale on which vortex predictability is enhanced lies between 2 and 4 weeks for nearly all cases. Those stratospheric sudden warmings that were preceded by a strong MJO event are more predictable at ?20 day leads than stratospheric sudden warmings not preceded by a MJO event. Hence, knowledge of the MJO can contribute to enhanced predictability, at least in a probabilistic sense, of the Northern Hemisphere polar stratosphere.

| S-EPMC5699436 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data