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73 results for “Vorticity”
Data for Seasonal Modulation of Dissolved Oxygen in the Equatorial Pacific by Tropical Instability Vortices
<p>This repository contains data used for the Analysis of "Seasonal Modulation of Dissolved Oxygen in the Equatorial Pacific by Tropical Instability Vortices" By Eddebbar et al. Submitted to JGR Oceans.</p> <p>Code used for the analysis of CESM-HR and CESM-LR model outputs and running and analyzing the particle tracking simulations are available at Zenodo on https://zenodo.org/record/5266337</p> <p>This repository contains the following items: </p> <ol> <li> Observational datasets used for model validation Figure 1 and 2 (obs.tar.gz) </li> <li>Low Resolution CESM outputs used for model resolution comparison Figure 1-3 (CESM_LR.tar.gz)</li> <li>High resolution CESM climatological output (CESM_HR_CLM.tar.gz and CESM_HR_CLM_all.tar.gz)</li> <li>Physical and BGC outputs from high resolution CESM from snapshot for Oct, 03, 0005 (CESM-HR_BGC.0005-10-03.tar.gz and CESM_HR_0005_10_03.tar.gz) used in Fig 3, 4, 5, 6, and 9 and Supp Fig 3.</li> <li>Outputs for year 5 of simulation for select variables from CESM-HR (CESM_HR_0005.tar.gz)</li> <li>Model Grid file: CESM_HR_grid.tar.gz</li> <li>Output for month 8, 9, 10, and 11 of year 5 of CESM-HR simulation used in figure 10, 11, and 12 for select variables including: CESM_HR_HMXL_08_09.tar.gz, CESM_HR_HMXL_10_11.tar.gz, CESM_HR_O2_08_09.tar.gz, CESM_HR_O2_10_11.tar.gz, CESM_HR_PD_08_09.tar.gz, CESM_HR_PD_10_11.tar.gz, CESM_HR_SSH_08_09.tar.gz, CESM_HR_SSH_10_11.tar.gz, CESM_HR_STF_O2_10_11.tar.gz, CESM_HR_TEMP_08_09.tar.gz, CESM_HR_TEMP_10_11.tar.gz, CESM_HR_UVEL_08_09.tar.gz)</li> <li>Near surface (15m) meridional and zonal velocity for the full CESM-HR simulation (CESM_HR_UV.tar.gz) for Fig 7</li> <li>Integrated O2 budget terms for CESM-HR (CESM_HR_O2_budget.tar.gz) used in figure 8</li> <li>Monthly mean O2 and PD (CESM_HR_O2_mon.tar.gz and CESM_HR_PD_mon.tar.gz) for Fig 7</li> <li>Particle trajectories for forward and backward parcels simulations used in fig 10-12 (particle_tracking_bwd_.tar.gz and particle_tracking_fwd_.tar.gz)</li> </ol>
Potential vorticity (850K)
<p>The archive contains an image of potential vorticity (PVU, m2 s-1K kg-1) on the level of 850K for each day of the winter periods (October-April) from 1979 to 2021.</p>
Computational results and python files for the work "Divergence-conforming velocity and vorticity approximations for incompressible fluids obtained with minimal facet coupling"
<p><br> This repository contains data accompanying the paper "Divergence-conforming velocity and vorticity approximations for incompressible fluids obtained with minimal facet coupling".</p> <p>The implementation is based on the python-interface of the NGSolve open source Finite Element library (ngsolve.org).</p> <p>The file solve_problem_allione.py represents a minimum working example where the proposed MCS/HDG (set the use_MCS flag) method is used to solve the problem from the numerics section of the paper.</p> <p>The files FlowTemplates.py and krylovspace_extension.py contain a somewhat larger and more modular implementation of the proposed method that also features preconditioned iterative solvers, including support for the NgsAMG NGSolve extension library as well as the NGSolve-PETSc interface.</p> <p>The files errors_hdg.pickle, errors_mcs.pickle and kappas.pickle contain the raw data the tables and pictures in the paper were generated from.</p> <p>This data was generated with the scripts conv3d_hdg.py, conv3d_mcs.py and calc_kappas.py which use the FlowTemplates.py infrastructure.</p>
Single-electron-charge transfer into putative Majorana and trivial modes in individual vortices
<p>Supporting data for Jian-Feng Ge, et al. “Single-electron-charge transfer into putative Majorana and trivial modes in individual vortices”.</p> <p>The following data files are used for the following figures.</p> <p> Fig. 1 a Illustration figure, no data used<br> b NbSe2_04_220202_0184.txt<br> c FeTeSe_08_210604_0614.txt</p> <p> Fig. 2 a NbSe2_04_220202_0133_raw.txt<br> b NbSe2_04_220202_dIdV_0033_0037_raw.txt<br> c NbSe2_04_220202_0133_raw.txt<br> d NbSe2_04_220202_0133_deconv.txt<br> e NbSe2_04_220202_dIdV_0033_0037_deconv.txt<br> f NbSe2_04_220202_0133_deconv.txt</p> <p> Fig. 3 a FeTeSe_08_210604_0188_raw.txt<br> b FeTeSe_08_210604_dIdV_0121_0122_raw.txt<br> c FeTeSe_08_210604_0188_raw.txt<br> d FeTeSe_08_210604_0188_deconv.txt<br> e FeTeSe_08_210604_dIdV_0121_0122_deconv.txt<br> f FeTeSe_08_210604_0188_deconv.txt</p> <p> Fig. 4 a 220210_NbSe2_04_2.3K_spectrum_06_08.txt<br> b qeff_NbSe2.txt<br> c 210622_FeTeSe08_2.3K_spectrum_06_04.txt<br> d qeff_FeTeSe.txt</p> <p>Supplementary Fig. 1 a PbtipPb111.txt<br> b PbtipAu111.txt<br> c Pbtipfits.txt</p> <p>Supplementary Fig. 2 a Illustration figure, no data used<br> b linecut_raw.txt<br> c linecut_deconv.txt<br> d peak_pos.txt<br> e peak_amp.txt</p> <p>Supplementary Fig. 3 a NbSe2_04_220202_0098_raw.txt<br> b NbSe2_04_220202_0098_c_33_31_a_63_0_raw.txt<br> c NbSe2_04_220202_0098_raw.txt<br> d 220210_NbSe2_04_2.3K_spectrum_04_03.txt<br> e NbSe2_04_220202_0098_deconv.txt<br> f NbSe2_04_220202_0098_c_33_31_a_63_0_deconv.txt<br> g NbSe2_04_220202_0098_deconv.txt<br> h 220210_NbSe2_04_2.3K_spectrum_04_03_qeff.txt<br> i NbSe2_04_220202_0172_raw.txt<br> j NbSe2_04_220202_0098_c_33_35_a_0_63_raw.txt<br> k NbSe2_04_220202_0172_raw.txt <br> l 220210_NbSe2_04_2.3K_spectrum_10_11.txt<br> m NbSe2_04_220202_0172_deconv.txt<br> n NbSe2_04_220202_0098_c_33_35_a_0_63_deconv.txt<br> o NbSe2_04_220202_0172_deconv.txt<br> p 220210_NbSe2_04_2.3K_spectrum_10_11_qeff.txt</p> <p>Supplementary Fig. 4 a FeTeSe_08_210604_0355_raw.txt<br> b FeTeSe_08_210604_0355_c_26_30_a_63_0_raw.txt<br> c FeTeSe_08_210604_0355_raw.txt<br> d 210622_FeTeSe08_2.3K_spectrum_15_14.txt<br> e FeTeSe_08_210604_0355_deconv.txt<br> f FeTeSe_08_210604_0355_c_26_30_a_63_0_deconv.txt<br> g FeTeSe_08_210604_0355_deconv.txt<br> h 210622_FeTeSe08_2.3K_spectrum_15_14_qeff.txt<br> i FeTeSe_08_210604_0463_raw.txt<br> j FeTeSe_08_210604_0463_c_26_27_a_0_0_raw.txt<br> k FeTeSe_08_210604_0463_raw.txt <br> l 210622_FeTeSe08_2.3K_spectrum_27_24.txt<br> m FeTeSe_08_210604_0463_deconv.txt<br> n FeTeSe_08_210604_0463_c_26_27_a_0_0_deconv.txt<br> o FeTeSe_08_210604_0463_deconv.txt<br> p 210622_FeTeSe08_2.3K_spectrum_27_24_qeff.txt</p> <p>Supplementary Fig. 5 a 220210_NbSe2_04_2.3K_spectrum_06_08_qeff.txt<br> b 210622_FeTeSe08_2.3K_spectrum_06_04_qeff.txt</p> <p>Supplementary Fig. 6 a FeSeTe_07_180716_0309_topo.txt<br> b FeSeTe_07_180716_0309_ring.txt<br> c FeTeSe_08_210604_0355_raw.txt<br> d 180809_FeSeTe7_ring_2.5MOhm_3K_map_04.txt<br> e 180907_FeSeTe7_Pbtip_10MOhm_3K_spectra_24.txt<br> f 180907_FeSeTe7_Pbtip_10MOhm_3K_spectra_24_qeff.txt<br> <br> Supplementary Fig. 7 qeff_vs_qpcontrib.py</p> <p>Supplementary Fig. 8 a FeTeSe_10_211111_didv_FB.txt<br> b FeTeSe_10_211111_didv_FB_ratio_sim.txt</p> <p>Supplementary Fig. 9 220810_NbSe2_06_2.3K_spectrum_01_19.txt</p> <p>Supplementary Fig. 10 a NbSe2_05_220503_dIdV_0017.txt<br> b 220510_NbSe2_05_2.3K_spectrum_01.txt</p>
Animation of surface relative vorticity around Green Island, Taiwan.
<p>This animation is based on a 60m resolution simulation using UCLA-ROMS. The simulation is forced at it's boundaries by high frequency internal tides and waves as well as sub-tidal eddies and fronts. The surface forcing is derived from the ERA5 reanalysis dataset.</p>
Data from: A method of separating linear internal wave and vortical mode energies using shipboard ADCP velocity measurements
Open the record for dataset details and reuse information.
Data from: Flamingos use their L-shaped beak and morphing feet to induce vortical traps for prey capture
Open the record for dataset details and reuse information.
Flow through a submerged canopy partially covering the bed: spatial flow pattern, multi-dimensional vortices and junction momentum exchange
<p>The dataset (including videos) are uploaded to support the research study <strong>Flow through a submerged canopy partially covering the bed: spatial flow pattern, multi-dimensional vortices and junction momentum exchange (submitted to Water Resources Research) </strong></p>
Global Observation-based LInear Vorticity Vertical Velocities (OLIV3) over isopycnal levels
<p>Observation-based Linear Vorticity Vertical Velocities (OLIV3) estimates from observation-based geostrophic velocities within the global themocline during the 1993-2019 period at annual frequency.</p> <p>The beta-plane geostrophic OLIV3 fields are computed following the Indefinite depth-integrated geostrophic linear vorticity balance methodology described in <em>Cortés-Morales and Lazar, 2024, </em><em>Diego Cortés Morales, 2023 [thesis] and Cortés-Morales et al., (submitted) </em>applied to the ARMOR3D [<em>Mulet et al., 2013; https://data.marine.copernicus.eu/product/MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012</em>] geostrophic meridional velocities. The boundary condition used is the Ekman pumping vertical velocities computed from ERA5 wind stress [DOI: 10.24381/cds.f17050d7]. The velocity field is quality-flagged based on the relative error and interannual correlation coefficient between w_g and w_tot in an OGCM perfect model test (<em>Cortés-Morales et al., (submitted)</em>).</p> <p>----------------------------------------------------------------------------------------</p> <p>Geographical coverage: Global Ocean</p> <p>Grid and horizontal spatial resolution: Evenly spaced 0.25º grid</p> <p>Vertical levels: 71 levels from sigma level 21 to 28.17 kg/m^3.</p> <p>Temporal resolution: Annual (1993-2019)</p> <p>-----------------------------------------------------------------------------------------</p> <p>Variables:</p> <p>lon (2D): Longitude</p> <p>lat (2D): Latitude</p> <p>isolev (1D): Isopycnal level</p> <p>time (1D): Year</p> <p>w_oliv3(4D): Beta-plane geostrophic vertical velocities</p> <p>h_depth (4D): Depth isopycnal surfaces</p> <p>flag_time_var (3D): Flag based on correlation coeffcient between geostrophic and total vertical velocties from OGCM</p> <p>flag_time_mean (3D): flag based on relative error between geostrophic and total vertical velocties from OGCM</p>
Identified Potential Vorticity Structures associated with African Easterly Waves
<p>This data set contains identified and tracked 3-D Potential Vorticity (PV) structures associated with African Easterly Waves (AEWs), based on the ERA-5 reanalysis of the years 2002-2022 from June to October.</p><p>First the AEW troughs are identified as outlined and separately submitted in <a href="https://zenodo.org/records/8403744">this dataset.</a> To extract the 3-D PV structures in these waves, a Hilbert transform is employed to compute the wave phase at every point in the domain. This yields the trough area of the waves. Within these areas, PV is collected and processed, and assigned a low-dimensional description, including a best-fit ellipsoid for statistical analyses. More details on the methodology can be found in a soon to be submitted publication.</p><p>The JSON files within this dataset provide a description of the PV features, structured as follows:</p><ol><li>Each file contains one year of data, with one set each.</li><li>Each set includes:<ul><li>A list of timestamps, where each timestamp contains the identified troughs at a specific time. Each time entry contains a list of objects (PV features), with each containing a set-unique identifier and properties describing the feature, such as the ellipsoid and a bounding box.</li><li>The data graph, consisting of a list of edges, wherein each edge connects one parent object to multiple child objects, forming the tracking graph. A connection between a parent and child indicates that they represent the same feature entity, with the child being the next manifestation of the parent entity along the time line.</li><li>A list of tracks, with each track represented as a data graph as well.</li></ul></li></ol><p> </p>
Data for Numerical Simulation of Tornado-like Vortices Induced by Small-Scale Cyclostrophic Wind Perturbations
Open the record for dataset details and reuse information.
Simulation code for fluids in two dimensions - vorticity movie
<p>A movie of the vorticity in a transverse only run. The data for the movie has been obtained using the simulation code found <a href="https://zenodo.org/record/5786090#.YbtUr71BwuU">here</a>.</p>
Repository for the paper "Stability of the Jupiter southern polar vortices inspected through vorticity using Juno/JIRAM data"
<p>This repository contains all the *img and *lbl files that have been used in the analysis reported in "Stability of the Jupiter southern polar vortices inspected through vorticity using Juno/JIRAM data". Please see the text for details. </p>
The oscillatory motion of Jupiter's polar cyclones results from vorticity dynamics - Movies S1, S2
<p>Movie S1: An animation of the observed trajectories of the south polar cyclones, as illustrated in Fig. 2a, along the 45-months of observations. The blue arrows represent the estimated net forces on the cyclones, as presented in Fig. 4.</p> <p>Movie S2: An animation of the simulated trajectories of the south polar cyclones, as illustrated in Fig. 5a, along 45-months.<br> The blue arrows represent the net forces on the cyclones.</p>
Deterministic creation and braiding of chiral edge vortices
<p>These codes are used to calculate the numerical results including the band dispersion, current density and also scattering phase.</p>
Observations of island wakes at high Rossby numbers: Evolutions of submesoscale vortices and free shear layer
<p>The dataset contains shipboard and moored current and temperature measurements used to produce the figures in a manuscript entitled as "Observations of island wakes at high Rossby numbers: Evolutions of submesoscale vortices and free shear layer". All the data are in MATLAB file format.</p> <p>Fig3_Experiment2.mat: current velocity and temperature data shown in Figure 3 in ten surveys.</p> <p>Fig4_MOORING.mat: Moored zonal velocity data at W1 and W2 shown in Figure 4.</p> <p>Fig6_L6.mat: meridional current data, Ro and shear-squared shown in Figure 6.</p> <p>Fig7_Experiment1_T1.mat: temperature and current data in Figures 7a-c.</p> <p>Fig7_case05.mat: temperature and current data in Figures 7d and 7g.</p> <p>Fig7_case08.mat: temperature and current data in Figures 7e and 7h.</p> <p>Fig7_case11.mat: temperature and current data in Figure 7f and 7i.</p> <p>Fig8_(a)-(e): temperature and current data in Figure 8.</p> <p> </p> <p> </p>
APS DPP 2024 - The impact of stable modes on the merging dynamics of Kelvin- Helmholtz vortices
<p>Supplementary figures for the poster presentation</p>
Data for "Evaluating vertical velocity retrievals from vertical vorticity equation constrained dual-Doppler analysis of real, rapid-scan radar data"
<p>This archive contains data from the Rapid Scanning X-Band Polarimetric (RaXPol) radar, Atmospheric Imaging Radar (AIR), and Shared Mobile Atmospheric Research and Teaching radar (SMART-R) for 4 September 2018 in central Oklahoma. This is a rapid-scan dual-Doppler dataset of a convective storm. RaXPol and AIR were the two radars that can be used for dual-Doppler retrievals and the SMART-R data can be used for verification of vertical velocity.</p> <p>The AIR and RaXPol data have been quality controlled and are provided in cfRadial format. The SMART-R data has not been quality controlled and are available in its raw data format. All data can be read using the Python ARM Radar Toolkit.</p> <p>This dataset was used for the manuscript:</p> <p>Gebauer, J. G., A. Shapiro, C. K. Potvin, N. A. Dahl, M. I. Biggerstaff, and A. A. Alford, 2021: Evaluating vertical velocity retrievals from vertical vorticity equation constrained dual-Doppler analysis of rapid-scan radar data. <em>J. Atmos. Meas. Tech., </em>in review.</p>
Data and movies for Finley et al. "Impact of the Streamwise Vorticity Current on Low-level Mesocyclone Development in a Simulated Supercell"
<p>The netcdf data files and python files used to make the figures, and the movies provided in the supplemental material in Finley et al. Netcdf software is available from https://www.unidata.ucar.edu/software/netcdf/. Figures 1-4 and movies were made with VisIt, which is available from https://visit-dav.github.io/visit-website/. </p>
The potential vorticity contours
<p>Anomalies and contours of potential vorticity (PV) at 330 and 350 K for extreme precipiation events in Siberia and Mongolia</p> <p>The anomalies of PV are shown by filling, at 330 K (upper figure) and 350 K (lower figure). The black dots correspond to the precipitation areas.</p>
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