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73 results for “Vorticity”
ECMWF data for analysing smoked-charged vortices after the 2019-2020 Australian wildfires
<p>The dataset contains GRIB2 files produced from the operational IFS model and assimilation system of the European Centre for Medium Range Weather Forecast (ECMWF).</p> <p>OPZLWDA2020mmdd-SH.grd files contain log of surface pressure, zonal wind, meridional wind, temperature, relative vorticity and ozone mixing ratio for the 137 levels of the model on a 1°x1° grid in the southern hemisphere for the long window analysis at 6UTC and 18UTC every day from 1st January 2020 to 31 March 2020.</p> <p>OPZFCST2020mmdd-SH.grd files contain log of surface pressure, temperature, relative vorticity and ozone mixing ratio for the 137 levels of the model on a 1°x1° grid in the southern hemisphere every day for the 10-day forecast run starting at 00UTC every four days from 7 January 2020 to 31 March 2020.</p> <p>For basic access, these files are readable using python tools. The package pygrib available under conda-forge is recommended. The eccode library that allows read from C or Fortran is freely available from ECMWF and is installed along pygrib. Reading with eccode library is also possible in C and Fortran.</p> <p>A simple reader using pygrib is provided. </p> <p>Dedicated packages for the project are available on github/bernard-legras/STC/STC-Australia with dependencies in github/bernard-legras/STC/STC/pylib. The package that reads and process ECMWF data is github/bernard-legras/STC/STC/pylib/ECMWF_N.py. This package needs setup modification to discover the files where they have been copied.</p> <p>All requirements should be made to bernard.legras@lmd.ipsl.fr</p>
A temporally continuous divergence and vorticity dataset in Beijing derived from the radar wind profiler mesonet during 2023
<p>A temporally continuous horizontal divergence and vertical vorticity dataset is produced by horizontal winds derived from the radar wind profilers mesonet in Beijing by applying the triangle method. This dataset covers the period of 2023 with a temporal resolution of 6-minute and a vertical resolution of 120 m. The dataset is of significance for a multitude of scientific research and applications, including air quality, convection initiation and so on. The latest version includes rain flags of triangles.</p>
Data of the publication "An insight into the capability of the actuator line method to resolve tip vortices"
<p>This repository contains the data presented in "An insight into the capability of the actuator line method to resolve tip vortices", published by Melani et al. on the Wind Energy Science journal. More in detail, it contains all the data post-processed from BR-CFD, Frozen ALM, and Standard ALM simulations. </p>
Data for "Electric polarization near vortices in the extended Kitaev model"
<p>We formulate a Majorana mean-field theory for the extended <span><span><span><span>J</span><span>K</span><span>Γ</span></span></span></span> Kitaev model in a magnetic Zeeman field of arbitrary direction, and apply it for studying spatially inhomogeneous states harboring vortices. This mean-field theory is exact in the pure Kitaev limit and captures the essential physics throughout the Kitaev spin liquid phase. We determine the charge profile around vortices and the corresponding quadrupole tensor. The quadrupole-quadrupole interaction between distant vortices is shown to be either repulsive or attractive, depending on the parameters. We predict that electrically biased scanning probe tips enable the creation of vortices at preselected positions. Our results open new perspectives for the electric manipulation of Ising anyons in Kitaev spin liquids.</p> <p> </p>
Supplemental materials to "A quasi-2D model of convectively coupled vortices"
<p>math_derivation_note: A hand-written note of key mathematical steps, mostly about section 4 and Appendix C. </p> <p>quasi-2D model.zip: The package of the quasi-2D model code.</p> <p>postprocess_code_quasi2D.zip: The package of the postprocessing codes and intermediate files (.mat) related to the quasi-2D simulations.</p> <p>postprocess_code_CM1.zip: The package of the postprocessing codes and intermediate files (.mat) related to the CM1 simulation.</p> <p>Group_dh.avi: The Group-dh experiments with varying convective intermittency (dh/H). The first, second, and third column shows Group-dh-1, Ref, and Group-dh-2. Only the first member of each experimental ensemble is shown. The first row shows the raw vorticity normalized by f. The second shows the Gaussian-filtered vorticity (with a length scale of <em>l</em>=30 km) normalized by f. The black contour is the zero-value contour of the Gaussian-filtered vorticity.</p> <p>Group_dL.avi: The Group-<em>l</em> experiments with varying convective filter length <em>l.</em> The first, second, and third column shows Ref (<em>l</em>=30 km), Group-<em>l</em>-1 (<em>l</em>=45 km), and Group-<em>l</em>-2 (<em>l</em>=60 km). Only the first member of each experimental ensemble is shown. The first row shows the raw vorticity normalized by f. The second shows the Gaussian-filtered vorticity (with a length scale of <em>l)</em> normalized by f. The black contour is the zero-value contour of the Gaussian-filtered vorticity.</p> <p>Group_fE.avi: The Group-fE experiments with varying Coriolis parameter f and Ekman number E<em>.</em> They differ in the strength of the rotational flow. The first, second, and third column shows Group-fE-1 (f=1e-5 1/s), Ref (f=1e-4 1/s), and Group-fE-2 (f=2e-4 1/s). Only the first member of each experimental ensemble is shown. The first row shows the raw vorticity normalized by f. The second shows the Gaussian-filtered vorticity (with a length scale of <em>l=</em>30 km<em>)</em> normalized by f. The black contour is the zero-value contour of the Gaussian-filtered vorticity.</p> <p>Group_eta.avi: The Group-eta experiments with varying mesoscale feedback parameter eta<em>.</em> They differ in the strength of the mesoscale feedback. The first, second, and third column shows Group-eta-1 (eta=0), Group-eta-2 (eta=1.2), and Group-eta-3 (eta=1.4). Only the first member of each experimental ensemble is shown. The first row shows the raw vorticity normalized by f. The second shows the Gaussian-filtered vorticity (with a length scale of <em>l=</em>30 km<em>)</em> normalized by f. The black contour is the zero-value contour of the Gaussian-filtered vorticity.</p> <p>Please contact Dr. Hao Fu (haofu@uchicago.edu) if you have any questions!</p>
Dataset of OAM spectra of vortices with different OAM
<p>Dataset of OAM spectra of electron beam vortices with different OAM obtained with an electrostatic OAM sorter. The data here reported was used to "benchmark" the sorting resolution of our second generation electrostatic OAM sorter. Here the second sorting element design changed, we were able to realize a phase correct or Sorter 2 with 11 alternativelly bias electrods.</p>
Wake vortices and dissipation in a tidally modulated flow past a three-dimensional topography
<p>LES simulation data of tidally modulated flow past an abyssal hill. Data used in the figures are available</p>
Data for "Spurious forces can dominate the vorticity budget of ocean gyres on the C-grid"
<p>This contains data for the submitted paper "Spurious forces can dominate the vorticity budget of ocean gyres on the C-grid" which has been submitted to JAMES.</p>
Ultrafast imaging of molecular chirality with photoelectron vortices
<p>This is the plotting data and plotting scripts for the publication: <strong>“Ultrafast imaging of molecular chirality with photoelectron vortices”. </strong>Preprint available at: https://arxiv.org/abs/2202.07289. A readme.txt file is included with the data.</p> <p><strong>Authors:</strong><br> Xavier Barcons Planas, Andrés Ordóñez, Maciej Lewenstein, Andrew Stephen Maxwell</p> <p><strong>Abstract:</strong></p> <p>Ultrafast imaging of molecular chirality is a key step towards the dream of imaging and interpreting electronic dynamics in complex and biologically relevant molecules. Here, we propose a new ultrafast chiral phenomenon exploiting recent advances in electron optics allowing access to the orbital angular momentum of free electrons. We show that strong-field ionization of a chiral target with a few-cycle linearly polarized 800 nm laser pulse yields photoelectron vortices, whose chirality reveals that <br> of the target, and we discuss the mechanism underlying this phenomenon. Our work opens new perspectives in recollision-based chiral imaging.</p>
Datasets containing velocity gradients and their residual vorticity magnitude.
<p>This repository contains 4 datasets:</p> <p> </p> <ol> <li>validation dataset</li> <li>100k entry testing dataset</li> <li>non-sampled training dataset</li> <li>training dataset consisting of 2 part which will be used for training over sampled data </li> </ol>
Data and Source Codes used in "Development of a Global Quasi-3-D Multiscale Modeling Framework: I. Vector Vorticity Model on Cubed Sphere as Cloud-Resolving Component"
<p>Data and Source Codes used in the paper "Development of a Global Quasi-3-D Multiscale Modeling Framework: I. Vector Vorticity Model on Cubed Sphere as Cloud-Resolving Component"</p> <p>Advection Test (ADV): East-West A_TST (100km, Cube), C_TST (25km, Cube), E_TST (5km, Cube),</p> <p> North-South K_TST (100km, Cube), M_TST (25km, Cube), O_TST (5km, Cube) </p> <p>Barotropic Test (BAR): A_TST5 (100km, Cube), Y_TST4 (100km, RLL), C_TST3 (5km, Cube), C_TST1 (5km, RLL)</p> <p>Baroclinic Test (BCL): J_TST30 (100km, Cube), J_TST20 (100km, RLL)</p>
Data set associated with the paper "Implementation of the Vector Vorticity Dynamical Core on Cubed Sphere for Use in the Quasi-3-D Multiscale Modeling Framework"
<p>New data set associated with the revision of the paper "Development of a Global Quasi-3-D Multiscale Modeling Framework: <br> I. Vector Vorticity Model on Cubed Sphere as Cloud-Resolving Component"</p> <p>The title of the paper has been changed to "Implementation of the Vector Vorticity Dynamical Core on Cubed Sphere for Use in the Quasi-3-D Multiscale Modeling Framework"</p> <p>New simulated data set of the advection test is in the folder ADVEC_NEW; New simulated data set of the barotropic instability test is in the folder BARO_NEW; New simulated data set of the baroclinic instability test is in the folder BCL_NEW</p>
Effects of surface fluxes on the moist potential vorticity distribution in the tropical cyclone boundary layer
<p>Hourly model outputs (t=150-240 hrs) from five axisymmetric simulations of tropical cyclones are provided as follows :</p> <ol> <li>cm1_test40_ver2 (referred to as CONTROL in the manuscript)</li> <li>cm1_test41_ver2 (referred to as H2.0 in the manuscript)</li> <li>cm1_test42_ver2 (referred to as H0.5 in the manuscript)</li> <li>cm1_test43_ver2 (referred to as M2.0 in the manuscript)</li> <li>cm1_test44_ver2 (referred to as M0.5 in the manuscript)</li> </ol> <p>Model outputs from the 3D simulation are interpolated to cylindrical coordinates and saved individually for each variable in binary format, and these are provided for t=150-240 hrs as follows:</p> <ol> <li>cm1_test13_ver2 (referred to as 3D-TC in the manuscript)</li> </ol> <p>Jupyter notebooks are also provided to read and analyze processed outputs from the datasets described above and plot the figures included in the manuscript. The datasets used in "<em>figure_05.ipynb</em>", "<em>figure_06.ipynb</em>", and "<em>figure_07.ipynb</em>" are large and can be made available by the authors upon request.</p>
ESA 4DMED-Sea - Finite-Time Lagrangian Vorticity in the Mediterranean Sea derived from 4DVARNET8 geostrophic velocities (1/24°)
<p>This product provides the Finite-Time Lagrangian Vorticity derived from surface geostrophic velocities result from the application of the 4DVARNET algorithm (<a href="https://isprs-annals.copernicus.org/articles/V-3-2021/295/2021/isprs-annals-V-3-2021-295-2021.html" target="_blank" rel="noopener">Fablet et al., 2021</a>; resolution of the dynamical model used for the learning/training (<a href="https://github.com/ocean-next/eNATL60">eNATL60-BLB02</a>) downgraded to 1/8°) to altimetry L3-data (https://doi.org/10.5281/zenodo.10908416) at a resolution of 1/24° over the Mediterranean Sea and for the period from April 2016 to July 2022. </p> <p>Algorithm used to compute Finite-Time Lagrangian Vorticity was developed by I. Hernandez-Carrasco (Hernandez-Carrasco et al, 2011, Ocean modelling. https://doi.org/10.1016/j.ocemod.2010.12.006).</p> <p>----------------------------------------------------------------------------------------</p> <p>Geographical coverage: Mediterranean Sea</p> <p>Grid and horizontal spatial resolution: Evenly spaced 1/24º grid</p> <p>Vertical levels: Only surface level</p> <p>Temporal resolution: Daily (April 2016 - July 2022)</p> <p>-----------------------------------------------------------------------------------------</p> <p>Variables:</p> <p>lon (1D)</p> <p>lat (1D)</p> <p>time (1D)</p> <p>ftlv (2D)</p>
ESA 4DMED-Sea - Finite-Time Lagrangian Vorticity in the Mediterranean Sea derived from 4DVARNET8 geostrophic velocities (1/72°)
<p>This product provides the Finite-Time Lagrangian Vorticity derived from surface geostrophic velocities result from the application of the 4DVARNET algorithm (<a href="https://isprs-annals.copernicus.org/articles/V-3-2021/295/2021/isprs-annals-V-3-2021-295-2021.html" target="_blank" rel="noopener">Fablet et al., 2021</a>; resolution of the dynamical model used for the learning/training (<a href="https://github.com/ocean-next/eNATL60">eNATL60-BLB02</a>) downgraded to 1/8°) to altimetry L3-data (https://doi.org/10.5281/zenodo.10908416) at a resolution of 1/72° over the Mediterranean Sea and for the period from April 2016 to July 2022. </p> <p>Algorithm used to compute Finite-Time Lagrangian Vorticity was developed by I. Hernandez-Carrasco (Hernandez-Carrasco et al, 2011, Ocean modelling. https://doi.org/10.1016/j.ocemod.2010.12.006).</p> <p>----------------------------------------------------------------------------------------</p> <p>Geographical coverage: Mediterranean Sea</p> <p>Grid and horizontal spatial resolution: Evenly spaced 1/72º grid</p> <p>Vertical levels: Only surface level</p> <p>Temporal resolution: Daily (April 2016 - July 2022)</p> <p>-----------------------------------------------------------------------------------------</p> <p>Variables:</p> <p>lon (1D)</p> <p>lat (1D)</p> <p>time (1D)</p> <p>ftlv (2D)</p>
ESA 4DMED-Sea - Finite-Time Lagrangian Vorticity in the Mediterranean Sea derived from MIOST geostrophic velocities (1/24°)
<p>This product provides the Finite-Time Lagrangian Vorticity derived from surface geostrophic velocities result from the application of the MIOST algorithm (Ubelmann et al., 2019; https://doi.org/10.1029/2020JC016560) to altimetry L3-data (https://doi.org/10.5281/zenodo.10648981) at a resolution of 1/24° over the Mediterranean Sea and for the period from April 2016 to July 2022. </p> <p>Algorithm used to compute Finite-Time Lagrangian Vorticity was developed by I. Hernandez-Carrasco (Hernandez-Carrasco et al, 2011, Ocean modelling. https://doi.org/10.1016/j.ocemod.2010.12.006).</p> <p>----------------------------------------------------------------------------------------</p> <p>Geographical coverage: Mediterranean Sea</p> <p>Grid and horizontal spatial resolution: Evenly spaced 1/24º grid</p> <p>Vertical levels: Only surface level</p> <p>Temporal resolution: Daily (April 2016 - July 2022)</p> <p>-----------------------------------------------------------------------------------------</p> <p>Variables:</p> <p>lon (1D)</p> <p>lat (1D)</p> <p>time (1D)</p> <p>ftlv (2D)</p>
ESA 4DMED-Sea - Finite-Time Lagrangian Vorticity in the Mediterranean Sea derived from MIOST geostrophic velocities (1/72°)
<p>This product provides the Finite-Time Lagrangian Vorticity derived from surface geostrophic velocities result from the application of the MIOST algorithm (Ubelmann et al., 2019; https://doi.org/10.1029/2020JC016560) to altimetry L3-data (https://doi.org/10.5281/zenodo.10648981) at a resolution of 1/72° over the Mediterranean Sea and for the period from April 2016 to July 2022. </p> <p>Algorithm used to compute Finite-Time Lagrangian Vorticity was developed by I. Hernandez-Carrasco (Hernandez-Carrasco et al, 2011, Ocean modelling. https://doi.org/10.1016/j.ocemod.2010.12.006).</p> <p>----------------------------------------------------------------------------------------</p> <p>Geographical coverage: Mediterranean Sea</p> <p>Grid and horizontal spatial resolution: Evenly spaced 1/72º grid</p> <p>Vertical levels: Only surface level</p> <p>Temporal resolution: Daily (April 2016 - July 2022)</p> <p>-----------------------------------------------------------------------------------------</p> <p>Variables:</p> <p>lon (1D)</p> <p>lat (1D)</p> <p>time (1D)</p> <p>ftlv (2D)</p>
ESA 4DMED-Sea - Finite-Time Lagrangian Vorticity in the Mediterranean Sea derived from 4DVARNET20 geostrophic velocities (1/24°)
<p>This product provides the Finite-Time Lagrangian Vorticity derived from surface geostrophic velocities result from the application of the 4DVARNET algorithm (<a href="https://isprs-annals.copernicus.org/articles/V-3-2021/295/2021/isprs-annals-V-3-2021-295-2021.html" target="_blank" rel="noopener">Fablet et al., 2021</a>; resolution of the dynamical model used for the learning/training (<a href="https://github.com/ocean-next/eNATL60">eNATL60-BLB02</a>) downgraded to 1/20°) to altimetry L3-data (https://doi.org/10.5281/zenodo.10912777) at a resolution of 1/24° over the Mediterranean Sea and for the period from April 2016 to July 2022. </p> <p>Algorithm used to compute Finite-Time Lagrangian Vorticity was developed by I. Hernandez-Carrasco (Hernandez-Carrasco et al, 2011, Ocean modelling. https://doi.org/10.1016/j.ocemod.2010.12.006).</p> <p>----------------------------------------------------------------------------------------</p> <p>Geographical coverage: Mediterranean Sea</p> <p>Grid and horizontal spatial resolution: Evenly spaced 1/24º grid</p> <p>Vertical levels: Only surface level</p> <p>Temporal resolution: Daily (April 2016 - July 2022)</p> <p>-----------------------------------------------------------------------------------------</p> <p>Variables:</p> <p>lon (1D)</p> <p>lat (1D)</p> <p>time (1D)</p> <p>ftlv (2D)</p>
ESA 4DMED-Sea - Finite-Time Lagrangian Vorticity in the Mediterranean Sea derived from 4DVARNET20 geostrophic velocities (1/72°)
<p>This product provides the Finite-Time Lagrangian Vorticity derived from surface geostrophic velocities result from the application of the 4DVARNET algorithm (<a href="https://isprs-annals.copernicus.org/articles/V-3-2021/295/2021/isprs-annals-V-3-2021-295-2021.html" target="_blank" rel="noopener">Fablet et al., 2021</a>; resolution of the dynamical model used for the learning/training (<a href="https://github.com/ocean-next/eNATL60">eNATL60-BLB02</a>) downgraded to 1/20°) to altimetry L3-data (https://doi.org/10.5281/zenodo.10912777) at a resolution of 1/72° over the Mediterranean Sea and for the period from April 2016 to July 2022. </p> <p>Algorithm used to compute Finite-Time Lagrangian Vorticity was developed by I. Hernandez-Carrasco (Hernandez-Carrasco et al, 2011, Ocean modelling. https://doi.org/10.1016/j.ocemod.2010.12.006).</p> <p>----------------------------------------------------------------------------------------</p> <p>Geographical coverage: Mediterranean Sea</p> <p>Grid and horizontal spatial resolution: Evenly spaced 1/72º grid</p> <p>Vertical levels: Only surface level</p> <p>Temporal resolution: Daily (April 2016 - July 2022)</p> <p>-----------------------------------------------------------------------------------------</p> <p>Variables:</p> <p>lon (1D)</p> <p>lat (1D)</p> <p>time (1D)</p> <p>ftlv (2D)</p>
Observation of vortices in a dipolar supersolid
<p>Supersolids are states of matter that spontaneously break two continuous symmetries: translational invariance<br>due to the appearance of a crystal structure and phase invariance due to phase locking of single-particle wave<br>functions, responsible for superfluid phenomena. While originally predicted to be present in solid helium,<br>ultracold quantum gases provided a first platform to observe supersolids, with particular success coming<br>from dipolar atoms. Phase locking in dipolar supersolids has been probed through e.g. measurements of<br>the phase coherence and gapless Goldstone modes, but quantized vortices, a hydrodynamic fingerprint of<br>superfluidity, have not yet been observed. Here, with the prerequisite pieces at our disposal, namely a method to<br>generate vortices in dipolar gases and supersolids with two-dimensional crystalline order, we report on<br>the theoretical investigation and experimental observation of vortices in the supersolid phase. Our work reveals<br>a fundamental difference in vortex seeding dynamics between unmodulated and modulated quantum fluids. This<br>opens the door to study the hydrodynamic properties of exotic quantum systems with multiple spontaneously<br>broken symmetries, in disparate domains such as quantum crystals and neutron stars.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.