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969 results for “velocity”
Laser Disdrometer Particle Size and Velocities Distributions Raw data (2014-2017) for Melbourne, Australia
<p>This dataset includes raw data obtained from Laser Disdrometers installed in the proximity of Melbourne, Australia. It includes data from 2 Thies LPM and 2 OTT Parsivel. The description of this dataset as well as a first step in the processing are described in Guyot et al. (under review) at Hydrology and Earth Sciences Systems (publisher EGU) under an open-source Discussion format. </p>
Current velocities measured by HF radars in Gulf of Trieste - April 2012
<p>CODAR SeaSonde HF-radar derived surface ocean velocity in the Gulf of Trieste during the TOSCA experiment - April 2012</p> <p>TOSCA - Tracking Oil Spill and Coastal Awareness, http://www.tosca-med.eu</p> <p>Sensors (CODAR SeaSonde HF Radars) property and data retrieval --> CNR-ISMAR, La Spezia;</p> <p>Sensors installation and operation --> OGS</p>
WASHTREET. Runoff velocity data using different Particle Image Velocimetry (PIV) techniques in a full scale urban drainage physical model
<p><strong>WASHTREET - Runoff velocity data using different Particle Image Velocimetry (PIV) techniques in a full scale urban drainage physical model.</strong></p> <p>This dataset contains raw data and runoff velocities results obtained using seeded and unseeded Particle Image Velocimetry (PIV) techniques in an urban drainage physical model, which is placed in the Hydraulic Laboratory of the Centre for Technological Innovation in Construction and Civil Engineering (CITEEC) at the University of A Coruña (Spain). The objective of this work is to obtain an accurate representation of the surface velocity distribution as part of the <a href="https://zenodo.org/communities/washtreet">WASHTREET project</a>, where a series of high-resolution experiments were performed measuring urban surface wash-off and sediment transport through gully pots and pipes under laboratory-controlled conditions. The experimental facility is a 36 m<sup>2</sup> full-scale street section and consists of a rainfall simulator placed over a concrete street surface with two gully pots that drain runoff into an underground pipe system. The dataset was used in the work developed in Naves et al. (2019) (DOI: <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">https://doi.org/10.1016/j.jhydrol.2019.05.003</a>).</p> <p>A detailed description of experimental setup, procedure, postprocessing and results can be consulted in ‘<em>1_TestsDescription.pdf’. </em>4K resolution and 25 fps raw videos from which frames are extracted for the PIV analysis are provided for each experiment performed in separated zip files (named as <em>‘2.</em>(test ID)<em>_RawVideos_</em>(configuration)<em>.zip’</em>). Experiments includes three different steady rainfalls of 30, 50 and 80 mm/h of rain intensity and were recorded with and without added fluorescent traces. Data to orthorectify frames from videos are provided in ‘<em>3_SpatialCalibration.zip</em>’. In addition, 60 seconds of steady conditions are extracted for each test and the frames are processed to obtain velocities from a PIV analysis. ‘<em>4_ProcessedFrames_SteadyFlow.zip’ </em>includes the 1500 rectified and processed frames for each experiment to perform the PIV analysis. Results of runoff velocity distributions are included in ‘<em>5_VelocityResults.zip’</em>.</p> <p>Further details of the rainfall simulator, physical model geometry and more hydraulic and sediment transport results can be consulted in <a href="http://doi.org/10.5281/zenodo.3233918"><em>WASHTREET hydraulic, wash-off and sediment transport experimental data</em></a>. In addition, data regarding the use of photogrammetry to obtain the elevation map of this physical model is included in <a href="http://www.doi.org/10.5281/zenodo.3241337">WASHTREET Structure from Motion data</a>.</p> <p>The WASHTREET project is being developed in the scope of the PhD thesis of the first author, which is in receipt of a Spanish Ministry of Science, Innovation and Universities predoctoral grant [FPU14/01778]. The project also receive funding from the Spanish Ministry of Science, Innovation and Universities under POREDRAIN project RTI2018-094217-B-C33 (MINECO/FEDER-EU)</p> <p>Derived publications:</p> <ul> <li>Naves, J., Anta, J., Puertas, J., Regueiro-Picallo, M., & Suárez, J. (2019). Using a 2D shallow water model to assess Large-Scale Particle Image Velocimetry (LSPIV) and Structure from Motion (SfM) techniques in a street-scale urban drainage physical model. <em>Journal of Hydrology</em>, <em>575</em>, 54-65. <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">https://doi.org/10.1016/j.jhydrol.2019.05.003</a></li> <li>Naves, J., Anta, J., Suárez, J., & Puertas, J. (2020). Hydraulic, wash-off and sediment transport experiments in a full-scale urban drainage physical model. <em>Scientific Data</em>, <em>7</em>(1), 1-13. <a href="https://doi.org/10.1038/s41597-020-0384-z">https://doi.org/10.1038/s41597-020-0384-z</a></li> <li>Naves, J., García, J. T., Puertas, J., & Anta, J. (2021). Assessing different imaging velocimetry techniques to measure shallow runoff velocities during rain events using an urban drainage physical model. <em>Hydrology and Earth System Sciences</em>, <em>25</em>(2), 885-900. <a href="https://doi.org/10.5194/hess-25-885-2021">https://doi.org/10.5194/hess-25-885-2021</a> </li> </ul>
A Novel Hybrid Finite Element-Spectral Boundary Integral Scheme for Modeling Earthquake Cycles: Application to Rate and State Faults with Low-Velocity Zones
<p>We present a novel hybrid finite element (FE) - spectral boundary integral (SBI) scheme that enables efficient simulation of earthquake cycles. This combined FE-SBI approach captures the benefits of finite elements in modelling problems with nonlinearities, as well as the computational superiority of SBI. The domain truncation enabled by this scheme allows us to utilize high-resolution finite elements discretization to capture inhomogeneities or complexities that may exist in a narrow region surrounding the fault. Combined with an adaptive time stepping algorithm, this framework opens new opportunities for modeling earthquake cycles with high-resolution fault zone physics. In this initial study, we consider a two dimensional (2-D) anti-plane model with a vertical strike-slip fault governed by rate and state friction in the quasi-dynamic limit under the radiation damping approximation. The proposed approach is first verified using the benchmark problem BP-1 from the Southern California Earthquake Center (SCEC) sequence of earthquake and aseismic slip (SEAS) community verification effort. The computational framework is then utilized to model the earthquake sequence and aseismic slip of a fault embedded within a low-velocity fault zone (LVFZ) with different widths and compliance levels. Our results indicate that sufficiently compliant LVFZs contribute to the emergence of sub-surface events that fail to penetrate to the free surface and may experience earthquake clusters with nonuniform inter-seismic time. Furthermore, the LVFZ leads to slip rate amplification relative to the homogeneous elastic case. We discuss the implications of our results for understanding earthquake complexity as an interplay of fault friction and bulk heterogeneities. The complete work consists of all files listed below. </p>
Mid-crustal low-velocity zones beneath Southeastern Coastal China revealed by multimodal ambient noise tomography: insights into Mesozoic Magmatic Activities
<p><span>It contains Rayleigh dispersion data </span><span>and</span><span> a three</span><span>-</span><span>dimensional crustal shear</span><span>-</span><span>wave velocity model of the Southeastern Coastal China </span><span>(</span><span>SCC</span><span>)</span><span>.</span></p>
Velocity and strain rate fields of the Southern Tibetan Plateau
<p>This data set contains velocity and strain rate fields over the southern Tibetan Plateau, which are derived from Sentinel-1A and -1B synthetic aperture radar satellite data (SAR) and NETCDF (.grd) formats.</p> <p>This repository contains:</p> <p>(1) asc.grd : the InSAR LOS velocity field in the ascending tracks in a resolution of ~1000 m.</p> <p>(2) desc.grd : the InSAR LOS velocity field in the descending tracks in a resolution of ~1000 m.</p> <p>(3) dilatation_strain_rate.grd : the dilatational strain rate calculated from the interpolated GNSS Vn and InSAR-derived Ve.</p> <p>(4) second_invariant_horizontal_strain_rate.grd: the second invariant horizontal strain rate calculated from the interpolated GNSS Vn and InSAR-derived Ve.</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>
North-Southocean surface velocity component
Open the record for dataset details and reuse information.
East-West ocean surface velocity component
Open the record for dataset details and reuse information.
Waveform Data for paper "Eikonal surface-wave phase-velocity tomography of continental China"
<p>The files uploaded here contain the vertical component records of earthquakes used to measure Rayleigh wave phase velocities in continental China.</p>
Fast measurement of angular velocity in air-driven flat rotors with periodical features - Supplementary Data
<p>Supplementary Movie and data files used for generating Figure 4 in the main text. The files are compressed pickled pandas Dataframes and can be read with:</p> <pre><code class="language-python">import pandas as pd df = pd.read_pickle('/folder/file.xz', compression='xz')</code></pre> <p>Along with those files there are .txt files containing the physical information of each experiment.</p>
Data used in: Low Velocity Zones in the Martian Upper Mantle Highlighted by Sound Velocity Measurements
<p>Data used in</p> <p> </p> <p><strong>Low Velocity Zones in the Martian Upper Mantle Highlighted by Sound Velocity Measurements</strong></p> <p>F. Xu<strong><sup>1,</sup></strong><sup>†<strong>,</strong>‡</sup><strong>,</strong>, N. C. Siersch<sup>1<strong>,</strong>‡</sup>, S. Gréaux<sup>2</sup>, A. Rivoldini<sup>3</sup>, H. Kuwahara<sup>2,4</sup>, N. Kondo<sup>2</sup>, N. Wehr<sup>5</sup>, N. Menguy<sup>1</sup>, Y. Kono<sup>2</sup>, Y. Higo<sup>6</sup>, A.-C. Plesa<sup>7</sup>, J. Badro<sup>5</sup>, D. Antonangeli<sup>1</sup></p> <p><sup>1</sup> Sorbonne Université, Muséum National d‘Histoire Naturelle, UMR CNRS 7590, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, IMPMC, Paris, France</p> <p><sup>2</sup> Geodynamics Research Center, Ehime University, Matsuyama, Japan</p> <p><sup>3</sup> Royal Observatory of Belgium, Brussels, Belgium</p> <p><sup>4</sup> Institute for Planetary Materials, Okayama University, Misasa, Tottori, Japan</p> <p><sup>5</sup> Université de Paris, Institut de physique du globe de Paris, CNRS, Paris, France</p> <p><sup>6</sup> Japan Synchrotron Radiation Research Institute, SPring-8, Hyogo, Japan</p> <p><sup>7</sup> DLR Institute of Planetary Research, Berlin, Germany</p> <p> </p> <p>Corresponding author: Daniele Antonangeli (<a href="mailto:email@address.edu)">daniele.antonangeli@upmc.fr)</a></p> <p><sup>†</sup> Current address: Department of Earth Sciences, University College London, London, United Kingdom</p> <p><sup>‡</sup> Equal contributing authors</p> <p> </p> <p> </p>
Ice Velocity of Icelandic Glaciers
<p>Ice velocity map of Icelandic glaciers derived from Sentinel-1 SAR data acquired from 2014-10-01 to 2020-12-31. The surface velocity is derived applying feature tracking techniques. The ice velocity map is provided at 100m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity is provided in true meters per day, towards EASTING(vx) and NORTHING(vy) direction of the grid, and the vertical displacement (vz), is derived from a digital elevation model. Provided is a NetCDF file with the velocity components: vx, vy, vz and vv (magnitude of the horizontal components), along with maps of valid pixel count and uncertainty (stdx, stdy). The product was generated by ENVEO.<br> </p>
Sichuan Basin dipsersion data & velocity model
<p>We obtained a 3-D isotropic and azimuthal anisotropic model in the Sichuan Basin and adjacent areas. These datasets contain the dispersion data we picked, and the models we obtained.</p>
Changes in the velocity of money circulation
<p>Summary of data from empirical research.</p>
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