Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
103
datasets available to search
ShareScore release 0.9.0
Dataset results
103 results for “Magnetospheres”
Trifurcate structure of oxygen band EMIC waves excited in a warm magnetospheric plasma: Linear theory
<p>Simulation data of "Trifurcate structure of oxygen band EMIC waves excited in a warm magnetospheric plasma: Linear theory"</p>
Dataset for "Energization of Cold Protons and Helium Ions by EMIC Waves in the Inner Magnetosphere: Hybrid Simulations"
<p>* Reduced datasets for figures in the manuscript.</p> <p>* Code for producing the simulation data.</p>
Data set of Precipitation rates of electrons interacting with lower-band chorus emissions in the inner magnetosphere
<p>Simulation data for paper entitled "Precipitation rates of electrons interacting with lower-band chorus emissions in the inner magnetosphere"</p>
Database for "A New Four-Component L*-dependent Model for Radial Diffusion based on Solar Wind and Magnetospheric Drivers of ULF Waves"
<p>Database for <strong>"A New Four-Component L*-dependent Model for Radial Diffusion based on Solar Wind and Magnetospheric Drivers of ULF Waves" </strong>submitted to Space Weather by Murphy et al. </p> <p>The repository contains 2 datasets:</p> <ul> <li>The power spectral density of the compressional magnetic field from THEMIS, Van Allen Probes, and GOES along with accompanying position (MLT, L, L* TS05), solar wind, and geomagnetic data</li> <li>The power spectral density of the azimuthal electric field from THEMIS and Van Allen Probes along with accompanying position (MLT, L, L* TS05), solar wind, and geomagnetic data</li> </ul> <p>Both datasets are provided as an IDL save file and as an HDF5 file.</p> <p>The IDL data can be loaded using: </p> <pre><code>filename='electric_field_psd.sav' filename='magnetic_field_psd.sav' restore, filename, /verbose</code></pre> <p>The HDF5 file can be opened and investigate using (small changes will be required to store each variable):</p> <pre><code class="language-python">import h5py filename = 'magnetic_field_psd.h5' # magnetic field data filename = 'magnetic_field_psd.h5' # electric field data with h5py.File(filename, "r") as f: # loop through all keys (data) #print key and key attribute and size for i in f.keys(): print(f"{i} - {f[i].attrs['attributes']}, shape - {f[i].shape}") ds_obj = f[i] # returns as a h5py dataset object ds_arr = f[i][()] # returns as a numpy array</code></pre> <p>Below is a description of unique and common variables in each file. The psd variables have a shape [f,t], indicating the first dimension is frequency and the second is time, the f_mhz variable has shape [f], and all time series have shape [t]; here [f] and [t] denotes the number of elements in frequency and time arrays. </p> <p>------------------------------------</p> <p><strong>Magnetic field data set:</strong></p> <p><strong><em>Files</em></strong></p> <ul> <li>magnetic_field_psd.h5</li> <li>magnetic_field_psd.sav</li> </ul> <p><strong><em>Unique Data (variable in file)</em></strong></p> <ul> <li>psd <ul> <li>Power spectral density of the compressional magnetic field from THEMIS, Van Allen Probes, and GOES</li> <li>Units - nT<sup>2</sup>/mHz</li> <li>Shape - [f, t]</li> </ul> </li> </ul> <p>------------------------------------</p> <p><strong>Electric field data set:</strong></p> <p><strong><em>Files</em></strong></p> <ul> <li>electric_field_psd.h5</li> <li>electric_field_psd.sav</li> </ul> <p><strong><em>Unique Data (variable in file)</em></strong></p> <ul> <li>psd <ul> <li>Power spectral density of the azimuthal electric field from THEMIS, Van Allen Probes, and GOES</li> <li>Units - (mV/m)<sup>2</sup>/mHz</li> <li>Shape - [f, t]</li> </ul> </li> </ul> <p>------------------------------------</p> <p><strong>Common Data in the Magnetic and Electric Field Datasets (variable in file):</strong></p> <ul> <li>probe <ul> <li>Corresponding satellite of each time stamp</li> <li>Shape [t]</li> </ul> </li> <li>t <ul> <li>Time stamp of each time series; number of seconds since 1970 (UNIX time), [t]</li> <li>Units - s</li> <li>Shape [t]</li> </ul> </li> <li>f_mhz <ul> <li>Frequency of psd data, [f]</li> <li>Units - mHz</li> <li>Shape [f] - (19)</li> </ul> </li> <li>ae <ul> <li>OMNI AE index of each time stamp</li> <li>Units - nT'</li> <li>Shape [t]</li> </ul> </li> <li>al <ul> <li>OMNI AL index of each time stamp, units - nT</li> <li>Shape [t]</li> </ul> </li> <li>au <ul> <li>OMNI AU index of each time stamp </li> <li>Units - nT</li> <li>Shape [t]</li> </ul> </li> <li>b_t <ul> <li>OMNI IMF B of each time stamp</li> <li>Units - nT</li> <li>Shape [t]</li> </ul> </li> <li>b_x <ul> <li>OMNI IMF Bx (GSM) of each time stamp</li> <li>Units - nT</li> <li>Shape [t]</li> </ul> </li> <li>b_y <ul> <li>OMNI IMF By (GSM) of each time stamp</li> <li>Units - nT</li> <li>Shape [t]</li> </ul> </li> <li>b_z <ul> <li>OMNI IMF Bz (GSM) of each time stamp</li> <li>Units - nT</li> <li>Shape [t]</li> </ul> </li> <li>dst <ul> <li>OMNI Dst of each time stamp</li> <li>Units - nT</li> <li>Shape [t]</li> </ul> </li> <li>kp - <ul> <li>OMNI Kp (Kp*10) of each time stamp</li> <li>units - NA</li> <li>Shape [t]</li> </ul> </li> <li>l_sh <ul> <li>L-shell of each time stamp</li> <li>Shape [t]</li> </ul> </li> <li>ls_t05 <ul> <li>L* from TS05 of each time stamp</li> <li>Shape [t]</li> </ul> </li> <li>mlt <ul> <li>Magnetic Local Time of each time stamp</li> <li>Unit - hour</li> <li>Shape [t]</li> </ul> </li> <li>n <ul> <li>OMNI Solar Wind Proton Density of each time stamp</li> <li>Units - n/cc</li> <li>Shape [t]</li> </ul> </li> <li>pdyn <ul> <li>OMNI Solar Wind Dynamic Pressure (flow pressure) of each time stamp</li> <li>Units - nPa</li> <li>Shape [t]</li> </ul> </li> <li>symh - b'OMNI Sym-H of each time stamp, units - nT', shape - (477205,)</li> <li>v_t <ul> <li>OMNI Solar wind V of each time stamp</li> <li>Units - km/s</li> <li>Shape [t]</li> </ul> </li> <li>v_x <ul> <li>OMNI Solar wind Vx (GSE) of each time stamp</li> <li>Units - km/s</li> <li>Shape [t]</li> </ul> </li> <li>v_y <ul> <li>OMNI Solar wind Vy (GSE) of each time stamp</li> <li>Units - km/s</li> <li>Shape [t]</li> </ul> </li> <li>v_z <ul> <li>OMNI Solar wind Vz (GSE) of each time stamp</li> <li>Units - km/s</li> <li>Shape [t]</li> </ul> </li> </ul> <p> </p> <p> </p> <p> </p>
Meridional wave power distribution data for article "Latitudinal Dependence of Ground VLF Transmitter Wave Power in the Inner Magnetosphere"
<p>The data are the meridional wave power distribution for the four VLF transmitters: NWC, NAA, NML, and NLK in the inner magnetosphere. Each transmitter has a .mat file, and in each data file, we provide the meridional wave power distribution for both ray tracing simulation (parameter "rt") and ERG observation (parameter "erg"). In each distribution data, the variables "x2d" and "z2d" are the cartesian coordinates in the meridional plane in the unit of Re (the Eearth's radius). x2d=r*cos(theta) and z2d=r*sin*(theta), where r is the radius from the Earth's center, and theta is the magnetic latitude. The variable "power" is the corresponding transmitter wave power in the unit of V^2/m^2.</p>
Thermal and energetic ion dynamics in Ganymede's magnetosphere
Open the record for dataset details and reuse information.
Whistler-mode waves excited by anisotropic hot electrons with a drift velocity in Earth's magnetosphere: Linear theory
<p>The data used to generate the figures in this paper.</p>
Simulation data for "Excitation of oxygen ion cyclotron harmonic waves in the inner magnetosphere: Hybrid simulations"
<p>Data output from hybrid simulations of the excitation of oxygen ion cyclotron harmonic waves in the inner magnetosphere.</p>
Reconstruction of magnetospheric storm-time dynamics using cylindrical basis functions and multi-mission data mining
<p>This zip file contains data used to create figures and tables, describing the results of the paper "Reconstruction of magnetospheric storm-time dynamics using cylindrical basis functions and multi-mission data mining", by N. A. Tsyganenko, V. A. Andreeva, and M. I. Sitnov.</p>
Data Mining Inspired Localized Resistivity in Global MHD Simulations of the Magnetosphere
<p>The upload contains data for the paper submitted to the Journal of Geophysical Research.</p>
Impact of solar wind density and velocity variation on Martian magnetosphere and ion escape process
Open the record for dataset details and reuse information.
Jupiter magnetosphere simulation data - average
<p>MHD simulation data of Jupiter's magnetosphere</p>
Data from Vlasov Plasma Waves solver Kinetic Alfven Waves Solutions in the inner magnetosphere
<p>Dispersion analysis output files for plasma waves propagating, at different L-shells and different propagation angles, in the inner magnetosphere considering multi-species and also electron-proton plasma. All data correspond to frequency and plasma wave diagnostic spectra as a function of wavenumber.</p> <p>Data includes:</p> <p>complex frequency</p> <p>polarization</p> <p>magnetic helicity</p> <p>magnetic compressibility </p> <p>electric field </p> <p>magnetic field</p>
Identifying the magnetospheric drivers of giant undulations: Global modeling of the evolving inner magnetosphere and its auroral manifestations
<p>We present the first global geospace simulation to reproduce auroral giant undulations (GUs). To identify their magnetospheric drivers, we employ the MAGE (Multiscale Atmosphere-Geospace Environment) model in a case study of a geomagnetic storm for which there were spacecraft- and ground-based observations of GUs. The model reproduces the spatial and temporal scales of the GUs as well as the presence of duskside subauroral polarization streams (SAPS) and plasmapause undulations. Based on our modeling, we are able to identify the magnetospheric drivers of GUs as mesoscale ring current injections which, after drifting westward, create inverted regions of flux-tube entropy (FTE) and subsequent interchange instability. Outward-protruding interchange fingers disrupt shielding of the inner magnetosphere, creating longitudinally-localized ripples in magnetospheric convection equatorward of the magnetospheric instability, which structure the plasmapause and duskside diffuse precipitation. While not causal, SAPS and plasmapause undulations are a consequence of the unstable magnetospheric configuration.</p>
Fitting parameters for "Concurrent Observation of High-frequency EMIC Waves and Low-harmonic Fast MS Waves within a Magnetic Dip in the Inner Magnetosphere"
<p>1. whamp_input_ionfit_*.mat</p> <p>The fitting parameters for the growth rate calculation of HFEMIC waves, which includes: </p> <div> <div>Bi-Maxwellian distribution parameters:</div> <div>PlasmaModel.B - magnetic field in nT</div> <div>PlasmaModel.Species.m - mass/mass_proton (0 means electron)</div> <div>PlasmaModel.Species.n - density in cm^-3</div> <div>PlasmaModel.Species.t - temperature in eV</div> <div>PlasmaModel.Species.a - anisotropy, Tperp/Tpara</div> <div> </div> </div> <p>2. shell_dist_*.mat</p> <p>The fitting parameters for the growth rate calculation of MS waves, which includes:</p> <div>Bi-Maxwellian distribution parameters:</div> <div>PlasmaModel.B - magnetic field in nT</div> <div>PlasmaModel.Species.m - mass/mass_proton (0 means electron)</div> <div>PlasmaModel.Species.n - density in cm^-3</div> <div>PlasmaModel.Species.t - temperature in eV</div> <div>PlasmaModel.Species.a - anisotropy, Tperp/Tpara</div> <div> </div> <div>Partial shell distribution parameters:</div> <div> <div>PlasmaModel.Shell.m - mass/mass_proton (0 means electron)</div> <div>PlasmaModel.Shell.ns - density in cm^-3</div> <div>PlasmaModel.Shell.sigma - the degree of pitch angle anisotropy</div> <div>PlasmaModel.Shell.Vs - the shell speed in m/s <div>PlasmaModel.Shell.theta_s - the thermal spread of the shell in m/s</div> </div> </div>
SCB model data for article 'The effects of localized thermal pressure on equilibrium magnetic fields and particle drifts in the inner magnetosphere'
<p>The SCB model simulation data for the article 'The effects of localized thermal pressure on equilibrium magnetic fields and particle drifts in the inner magnetosphere'.</p> <p>The 'Rxx_A xx_Sxx_Lxxparameters' files are the data files, where Rxx is the beta_0 value, Axx is the A_e value, Sxx is the sigma_0 value and Lxx is the L_0 value (see the article for the definition of the values)</p> <p>The 'SCB_variables.xlsx' is a table to describe the variables in the data file.</p> <p>The 'read_scb.pro' is an IDL program to read the data files.</p>
Interplay of Three-Dimensional Instabilities and Magnetic Reconnection in the Explosive Onset of Magnetospheric Substorms
<p>Datasets for "Interplay of Three-Dimensional Instabilities and Magnetic Reconnection in the Explosive Onset of Magnetospheric Substorms".</p>
Dataset of "Frequency Chirping of Electromagnetic Ion Cyclotron Waves in Earth's Magnetosphere"
<p>Dataset of "Frequency Chirping of Electromagnetic Ion Cyclotron Waves in Earth's Magnetosphere", including the electromagnetic fields observed by Cluster, THEMIS or Van Allen Probes satellites and their definitive positions used to calculate EMIC wave chirping rates in the paper. Each folder in the dataset contains the entire data of one in the 15 cases of EMIC wave frequency chirping.</p>
Variation of Electron Lifetime due to Scattering by Electrostatic Electron Cyclotron Harmonic Waves in the Inner Magnetosphere with Electron Distribution Parameters
<p>Dataset that supports the Results, Tables and Figures of "Variation of Electron Lifetime due to Scattering by Electrostatic Electron Cyclotron Harmonic Waves in the Inner Magnetosphere with Electron Distribution Parameters".</p>
The Study of the Quasi-periodicity Observed on Plasma Density and Magnetic Field on Saturn's Magnetosphere: An Information Theory Approach
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
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.