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34 results for “Periodic wave”
Data and figures of JGR planet paper entitled "Pressure effects on the SEIS-InSight instrument, improvement of seismic records and characterization of long period atmospheric waves from ground displacements" by Raphael F. Garcia and co-authors
<p>Data and figures of the JGR Planet paper entitled "Pressure effects on the SEIS-<br> InSight instrument, improvement of seismic records and characterization of long<br> period atmospheric waves from ground displacements"<br> by<br> Raphael F. Garcia1, Balthasar Kenda2 , Taichi Kawamura2 , A. Spiga3,4, N.<br> Murdoch1 , P. Lognonné2, R. Widmer-Schnidrig5, N. Compaire1 , G.<br> Orhand-Mainsant1 , D. Banfield6, W. B. Banerdt7</p> <p>List of files and directories</p> <p>*extractAllDataFromFig.m : matlab code to extract the data in txt file from the<br> matlab figures listed in the following directories<br> Figure1<br> Figure10<br> Figure11<br> Figure2<br> Figure3<br> Figure4<br> Figure5<br> Figure6<br> Figure7<br> Figure8<br> Figure9</p> <p>*figures_combined : combined figures for JGR paper</p> <p>*INSIGHT_Data : data in miniseed format used in the paper<br> -- Deglitch_data : data after removing glitchs used in the paper<br> -- Data_figure11 : data used for the plots in figure 11 (plots done easily with<br> SeisGram software)</p> <p>*PREPRINT : preprint of the paper</p> <p> </p>
Shoreline position, wave height and wave period datasets at Grand Popo (Benin) and Nha Trang (Vietnam)
<p>Shoreline position, wave height and wave period datasets at Narrabeen (Australia), Grand Popo (Benin) and Nha Trang (Vietnam)</p> <p>(.mat files)</p>
Dataset for "Contributions of Parameterized Gravity Waves and Resolved Equatorial Waves to the QBO Period in a Future Climate of CESM2" by Lee et al. (2024)
Open the record for dataset details and reuse information.
Scaling theory of wave confinement in classical and quantum periodic systems
<p>Data repository to manuscript 'Scaling theory of wave confinement in classical and quantum periodic systems'. The upload contains the file "README.txt" explaining the content of the upload.</p>
Influence of thermospheric impacts of solar activity on the general circulation and long-period planetary waves in the middle atmosphere
<p>This dataset contains model output files and examples of scripts for depicting figures related to the article "Influence of thermospheric impacts of solar activity on the general circulation and long-period planetary waves in the middle atmosphere " by A.V. Koval, N. M. Gavrilov, A. I. Pogoreltsev, N. O. Shevchuk.</p> <p><br> Contents:<br> Output data from model simulations averaged over 16 pairs of model runs with high and low solar activity:</p> <p><br> gh_m1_hsa5.dx, gh_m1_lsa5.dx – amplitudes of the geopotential height variations in g.p.m. at high and low solar activity caused by long-period PW modes with zonal wavenumber 1 averaged over 80 time subintervals selected from pairs of the MUAM runs (structure described in w1_tp1_hsa.ctl, w1_tp1_lsa.ctl).<br> gh_m2_hsa5.dx, gh_m2_lsa5.dx, gh_m3_hsa5.dx, gh_m3_lsa5.dx, gh_m4_hsa5.dx, gh_m4_lsa5.dx – the same but for zonal wavenumbers 2,3,4.<br> gh_m1_disp_dif5.dx – dispersion of differences in corresponding wave amplitudes between high and low solar activitiy (w1_tp1_disp.ctl).<br> gh_m2_disp_dif5.dx, gh_m3_disp_dif5.dx, gh_m4_disp_dif5.dx – the same but for zonal wavenumbers 2,3,4.<br> index_refr1_1_5.dx, index_refr1_2_5.dx, index_refr1_3_5.dx, index_refr1_4_5.dx – the zonal-mean quasi-geostrophic complex refractivity index squared (RI2) for PW modes with zonal wavenumbers 1-4 (ind_refr1_1.ctl).<br> uq_vwres1_pv_Jan_1_5.dx, uq_vwres1_pv_Jan_2_5.dx, uq_vwres1_pv_Jan_3_5.dx, uq_vwres1_pv_Jan_4_5.dx – the Eliassen-Palm flux for PW modes with zonal wavenumbers 1-4 (uqep1_vwres_1.ctl).<br> zw_a0_grads5_hsa.dx, tp_a0_grads5_hsa.dx – zonal-mean zonal wind in m/s and temperature in K for December – February averaged over 16-member ensemble of model runs for high solar activity (m0_zw5_hsa.ctl, m0_tp5_hsa.ctl).<br> zw_a0_grads5_lsa.dx, tp_a0_grads5_lsa.dx – the same but for the low solar activity<br> disp_U_dif5_.dx, disp_T_dif5_.dx – dispersion of differences in zonal wind and temperature between high and low solar activitiy for December – February averaged over 16-member ensemble of model runs (tp1_disp.ctl).<br> Additional data including outputs from separate model runs are available from the authors upon request.</p>
Can quasi-periodic gravity waves influence the shape of ice crystals in cirrus clouds?
<p>This is the Raman Lidar data recorded at Physical Research Laboratory (PRL), Ahmedabad, India owned by PRL and maintained by Dr. Som Kumar Sharma. Associate Professor and Mrs. Sourita Saha, Sci./Engg.-SC</p> <p>Data (RCS_20Feb2016.mat) is Range Corrected Signal on 20th Feb 2016 and the corresponding time (time_20Feb2016.mat) in UTC and height(height.mat) in km are provided.</p>
CongDong2023_Macroscale regionalized ensemble estimation and analyses of wave periods across Canada
<p>Data for temporal variabilities and trends of Canadian wave periods.</p>
Dataset and Software for An anisotropic shear velocity model of the Earth's mantle using normal modes, body waves, surface waves and long-period waveforms
<p><strong>What is the nature of flow in the mantle?</strong><br> <strong>How fast do waves travel anywhere on Earth?</strong><br> <strong>Where can radial anisotropy be robustly detected?</strong><br> <strong>Can we reconcile a broad spectrum of seismic data? What are the benefits?</strong></p> <p>We use normal-mode splitting functions in addition to surface-wave phase anomalies, body-wave travel times and long-period waveforms to construct a three-dimensional model of anisotropic shear-wave velocity in the Earth's mantle. This is the <strong>first tomographic study</strong> to exploit the sensitivity of mode-splitting data to constrain radial anisotropy in the Earth's mantle jointly with several other types of data. Our modeling approach inverts for mantle velocity and anisotropy as well as transition-zone discontinuity topographies, and incorporates new crustal corrections for the splitting functions that are consistent with the nonlinear corrections we employ for the waveforms. Our preferred anisotropic model, S362ANI+M, is an update to the earlier model S362ANI, which did not include normal-mode splitting functions in its derivation.</p> <p><strong>Feedback/Questions?</strong> Please contact Raj Moulik (<a href="https://rajmoulik.com">rajmoulik.com</a>) at <a href="mailto:moulik@caa.columbia.edu?subject=Query%20from%20Zenodo">moulik@caa.columbia.edu</a> </p> <p><strong>Reference:</strong></p> <p><em>Please cite the following work if you use this data or software.</em></p> <ul> <li>Moulik, P. & Ekström, G., 2014. An anisotropic shear velocity model of the Earth's mantle using normal modes, body waves, surface waves and long-period waveforms, <em>Geophys. J. Int.</em>, <strong>199</strong>(3), 1713-1738, doi: <a href="http://dx.doi.org/10.1093/gji/ggu356">10.1093/gji/ggu356</a>. <em><a href="https://rajmoulik.com/Publications/MoulikEkstrom_GJI2014.pdf">pdf</a></em></li> </ul> <p><em>You can also cite the dataset and software from this Zenodo page (Optional).</em></p> <ul> <li> <p>Moulik, P. & Ekström, G., 2014. Dataset and Software for An anisotropic shear velocity model of the Earth's mantle using normal modes, body waves, surface waves and long-period waveforms. In Geophys. J. Int. (v1.0, Vol. 199, pp. 1713–1738). Zenodo. doi: <a href="https://doi.org/10.5281/zenodo.8357379">10.5281/zenodo.8357379</a></p> </li> </ul> <p><strong>Data Products:</strong></p> <ul> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANIplusM_Figures.tar.gz"><strong>S362ANIplusM_Figures.tar.gz</strong></a> - contains all figures from the paper in .png format</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANI%2BM_MapViewsCrossSections.pdf"><strong>S362ANI+M_MapViewsCrossSections.pdf</strong></a> - Some cross sections and map views at various depths in the mantle</li> <li><strong><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANI%2BM">S362ANI+M</a> - </strong>Coefficients of the spline basis functions for each parameter. Refer c<sub>ij</sub> in equation 11. This is our preferred global model of shear-wave velocity. In this model, radial anisotropy is confined to the uppermost mantle (that is, since the anisotropy is parameterized with only the four uppermost splines, it becomes very small below a depth of 250 km, and vanishes at 410 km). This is an updated version of S362ANI (Kustowski et al., 2008) which did not include normal modes in its derivation. Please note the stronger isotropic shear velocity anomalies in the transition zone.</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/STW105"><strong>STW105</strong></a> - reference model used in S362ANI+M. Described in Kustowski et al. (2008)</li> <li><strong><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/setup.cfg">setup.cfg</a> - </strong>Some configuration metadata relevant to this model for reproducibility.</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/epix.tar.gz"><strong>epix.tar.gz</strong></a> - Perturbations in horizontally (vsh) and vertically polarized shear velocity (vsv), Voigt-average isotropic velocity (vs), ansotropy (as) and topography of the internal boundaries. This is calculated from the spline coefficients at every 1 by 1 degree cell-centered pixel and at every ~25 km depth region from Moho to the core-mantle boundary and stored in extended pixel format (.epix) ASCII files. </li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANI%2BM.BOX25km_PIX1X1.avni.nc4"><strong>S362ANI+M.BOX25km_PIX1X1.avni.nc4</strong></a> - The perturbations in a standard AVNI format that utilizes the NETCDF4 container format. This file can be read in Python using either xarray or AVNI libraries. For example, to plot vs perturbations at 24.4-50 km depth range <ul> <li><em>import xarray as xr</em></li> <li><em>ds = xr.open_dataset('S362ANI+M.BOX25km_PIX1X1.avni.nc4')</em></li> <li><em>ds.vs[0].plot()</em></li> </ul> </li> <li><strong>Fortran Code</strong> <ul> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/readme"><strong>readme</strong></a> - contains a description of all files in the folder below</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/PROGRAMS.tar.gz"><strong>PROGRAMS.tar.gz</strong></a> - tools for obtaining model values at specific locations and some GMT plotting tools</li> </ul> </li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/GRD.tar.gz"><strong>GRD.tar.gz</strong></a> - longitude-latitide-velocity files with vsh, vsv, and Voigt average in km/s evaluated on a grid of points at many depths in the mantle</li> </ul>
Trapped Solitary Waves in a Periodic External Force: A Numerical Investigation using the Whitham Equation and the Sponge Layer Method
<p>Supplementary Videos.</p>
Periodic Heat Waves-induced neuronal etiology in the elderly is mediated by Gut-Liver-Brain axis: A Transcriptome Profiling Approach
GEO Series GSE252887. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Effect of Remimazolam Use During Perioperative Period on Brain Waves and Postoperative Cognitive Function
ClinicalTrials.gov study NCT04601350. IPD Sharing: Not stated. Countries: 1. Publications: 0.
CSRM Level 2 dataset: long-period Rayleigh wave ellipticity in continental China from earthquake data
<p>This dataset contains the long-period Rayleigh wave ellipticity (20 - 80 s in period) measured from three-component Rayleigh wave waveforms of <strong>9361</strong> tele-seismic events recorded by <strong>4193</strong> seismic stations deployed in continental China during 1990 and 2020. This dataset results from a project of constructing the high-resolution China Seismological Reference Model (<strong>CSRM-1.0</strong>) in the top 100 km of the crust and uppermost mantle in continental China (<a href="https://doi.org/10.1029/2024JB029520">Xiao et al, JGR, 2024</a>) (<a href="https://doi.org/10.5281/zenodo.11098135">model link</a>). </p> <p>本数据库包含了利用 1990 至 2020 年间中国大陆区域 <strong>4193</strong> 个地震台站记录的 <strong>9361</strong> 个远震瑞利波波形测量得到的长周期瑞利波偏振( 周期 20 - 80 s )。该数据库源于构建中国大陆区域高精度地壳和上地幔顶部100 公里三维地震学模型(CSRM-1.0)的工作 (<a href="https://doi.org/10.1029/2024JB029520">Xiao et al, JGR, 2024</a>) (<a href="https://doi.org/10.5281/zenodo.11098135">模型链接</a>) 。</p> <p>If you face any problem or issue in the usage of this dataset, please feel free to communicate with the corresponding author Xiao Xiao (<strong>xiaox.seis@gmail.com</strong>). </p>
Supplementary dataset for "Ultra-broadband seismic and tsunami wave observation of high-sampling ocean-bottom pressure gauge covering periods from seconds to hours"
<p>Supplementary dataset for "Ultra-broadband seismic and tsunami wave observation of high-sampling ocean-bottom pressure gauge covering periods from seconds to hours". This file includes the tilt record at the coastal tiltmeter SAMH during the 2010 Chile earthquake. The dataset was uploaded to Zenodo during the review process, but now can be available at the institutional repository of the National Research Institute for Earth Science and Disaster Resilience (NIED-IR, https://nied-ir.bosai.go.jp). To access the dataset, please visit http://doi.org/10.17598/NIED.0018.</p> <div> </div>
CSRM Level 2 dataset: short-period Rayleigh wave ellipticity in continental China
<p>This dataset contains the short-period Rayleigh wave ellipticity (4 - 8 s in period) measured from continuous waveforms of seismic ambient noise recorded by 3848 seismic stations deployed in continental China during 1990 and 2017. This dataset results from a project of constructing a 3-D seismic model of the shallow crust in continental China (<a href="https://doi.org/10.1093/gji/ggab022">Xiao et al, 2021, GJI</a>) (<a href="https://doi.org/10.5281/zenodo.8099245">model link</a>). </p> <p>本数据库包含了利用1990 至 2017 年间中国大陆区域地震台站记录的连续背景噪声波形测量得到的短周期瑞利波偏振( 周期 4 - 8 s )。该数据库源于构建中国大陆区域高精度浅层地壳三维地震学模型的工作 (<a href="https://doi.org/10.1093/gji/ggab022">Xiao et al, 2021, GJI</a>) (<a href="https://doi.org/10.5281/zenodo.8099245">模型链接</a>) 。</p> <p>If you face any problem or issue in the usage of this dataset, please feel free to communicate with the corresponding author Xiao Xiao (<strong>xiaox.seis@gmail.com</strong>). </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
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.