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30 results for “radiation belt”
datasets for "VLF Transmitters and Lightning Generated Whistlers 2: Diffusion of Radiation Belt Electrons"
<p>Supporting information for "VLF Transmitters and Lightning Generated Whistlers 2: Diffusion of Radiation Belt Electrons," submitted to Journal of Geophysical Research Space Physics. Diffusion coefficients for selected values of L and energy due to Very Low Frequency (VLF) transmitters and lightning generated whistlers (LGW), as well as Da0a0 and energy drag rates |dE/dt|/E from Coulomb collisions. Also provided are precipitation lifetimes, which include Da0a0 from plasmaspheric hiss but do not account for energy drag. Calculations are presented for high and low-density plasmasphere models, for all four combinations of ducted or nonducted VLF and LGW waves.</p>
Supporting Data for Drift Phase Structure Implications for Radiation Belt Transport by T.P. O'Brien et al. submitted to J. Geophysical Res.
<p>Datasets used in Drift Phase Structure Implications for Radiation Belt Transport by T.P. O'Brien et al. submitted to J. Geophysical Res.</p>
Supporting data for "Modeling the albedo neutron decay source of radiation belt electrons and protons"
<p>Data sets are provided in support of the publication to appear in JGR-Space Physics. They include tabulated values of computed albedo neutron flux above the atmosphere, and of resulting radiation belt electron and proton source functions. Data format is described in the README files.</p>
Radiation Belt Forecast Model and Framework (RBFMF) 10 Hour Hindcast Validation Data
<div><strong>Archived data for the manuscript “On the Performance of a Real-Time Electron Radiation Belt Specification Model” Staples et al., submitted to Space Weather, 2024.</strong></div> <div> </div> <div>Data in these files specify the radiation belt through phase space density (PSD) in adiabatic coordinate system. Simulated PSD is from the Radiation Belt Forecast Model and Framework (RBFMF) 10 hour hindcast, and measured PSD is from an intercalibrated multi-mission observatory (Van Allen Probes, GOES 13, 15, GPS, MMS, and THEMIS). For detailed description of the method used in the computation of this data, see sections 2 and 3 of the submitted manuscript.</div> <div> </div> <div>The THEMIS, Van Allen Probe, MMS, and GOES data used in computations is publicly available via http://cdaweb.gsfc.nasa.gov </div> <div>The GPS data is available via https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/</div> <div> </div> <div>Data Preperation: </div> <div>Adam Kellerman, akellerman@atmos.ucla.edu </div> <div>Frances Staples, frances.staples@atmos.ucla.edu</div> <div> </div> <div>Support for this work was provided by NASA grants 80NSSC20K1402 and 80NSSC23K0096, and NSF grant 2149782.</div> <div> </div> <div><strong>'PSD_10hrHC_Jan2016-Oct2018.mat'</strong></div> <div>Matlab data file format.</div> <div>Data time period: January 2016 - October 2018. </div> <div> Variable Descriptions:</div> <div>time - Serial date.</div> <div>InvMu - 1st adiabatic invariant coordinate, mu.</div> <div>InvK - 2nd adiabatic invariant coordinate, k.</div> <div>lstar - 3rd adiabatic invariant coordinate, l*.</div> <div>psd_sim - 10 hour radiaiton belt hindcast. Simulated PSD has dimensions corresponding to (time,lstar,mu,k). </div> <div>psd_obs - PSD observed by multi-mission dataset, with dimensions matching the simulated PSD (time, lstar, mu, k). </div> <div> </div> <div><strong>'PSD_10hrHC_Mar2019-Dec2020.mat'</strong></div> <div>Matlab data file format.</div> <div>Data time period March 2019 - December 2020. </div> <div> <div>Variable Descriptions:</div> </div> <div>time - Serial date.</div> <div>InvMu - 1st adiabatic invariant coordinate, mu.</div> <div>InvK - 2nd adiabatic invariant coordinate, k.</div> <div>lstar - 3rd adiabatic invariant coordinate, l*.</div> <div>psd_sim - 10 hour radiaiton belt hindcast. Simulated PSD has dimensions corresponding to (time,lstar,mu,k). </div> <div>psd_gps - PSD observed by the GPS constellation, with dimensions matching the simulated PSD (time, lstar, mu, k). </div> <div> </div> <div><strong>'RBSP_beacondata_Jan2016-Oct2018.mat'</strong></div> <div>Matlab data file format.</div> <div>Data time period January 2016 - October 2018. </div> <div>Variable Descriptions:</div> <div>time - Serial date.</div> <div>InvMu - 1st adiabatic invariant coordinate, mu.</div> <div>InvK - 2nd adiabatic invariant coordinate, k.</div> <div>lstar - 3rd adiabatic invariant coordinate, l*. l* dimensions correpond to the dimensions of the 2nd invariant, K (time, K)</div> <div>psd - real time PSD observed from Van Allen Probe b (beacon data), with dimensions corresponding to (time,mu,k). </div> <div>psd_err - observed error of beacon PSD data (i.e. Beacon_PSD - FinalRBSP_PSD).</div> <div>psd_q - observed quotient of beacon PSD data (i.e., Beacon_PSD/FinalRBSP_PSD).</div> <div> </div> <div><strong>'README.txt'</strong></div> <div>Downloadable file descriptions. </div>
Untangling the drivers of the radiation belt environment
<p>2019_psd_ave_a.hdf5 - 30 min average of RBSP A radiation belt electron phase space density (PSD) 2013-2019</p> <p>2019_psd_ave_b.hdf5 - 30 min average of RBSP B radidation belt electron PSD 2013-2019</p> <p>2019_solwind_ave.hdf5 - 30 min average of solar wind parameters 2013-2019</p> <p>The files are in HDF5 formaten</p>
Calculation data for "Scattering of Radiation Belt Electrons by Fast Magnetosonic Waves: Considering the Kinetic Effects"
<p>Here are the calculation data for "Scattering of Radiation Belt Electrons by Fast Magnetosonic Waves: Considering the Kinetic Effects", using the format of ".mat". </p> <p>Term of "cold_plasma_dispersion_relation.mat" is the numerical results of cold plasma dispersion relation for MS waves;</p> <p>Term of "kinetic_dispersion_relation.mat" is the numerical results of kinetic dispersion relation for MS waves, using the WHAMP code by K. Rönnmark;</p> <p>Term of "Diffusion_coefficients_cold.mat" is the diffusion rates calculated based on the cold plasma dispersion relation;</p> <p>Term of "Diffusion_coefficients_kinetic.mat" is the diffusion rates calculated based on the kinetic dispersion relation;</p> <p>To be noted, the "D_{\alpha\alpha}_Bw2" in term "Diffusion_coefficients_kinetic.mat" is derived from the inferred wave magnetic field power spectral density.</p>
Pitch-angle resolved electron flux measurements in the Earth's radiation belt
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Nonlinear scattering of 90-degree pitch angle electrons in the outer radiation belt by large-amplitude EMIC waves
<p>This file is a collection of numeric data files which were used to create all figures in the paper (under review as of December 19, 2019). All the data were obtained from numerically solving the Lorentz equation of motion for 5 MeV electrons under EMIC waves superposed onto a dipolar background magnetic field. </p>
Rapid Outer Radiation Belt Flux Dropouts and Fast Acceleration during the March 2015 and 2013 Storms: The Role of ULF Wave Ttansport From a Dynamic Outer Boundary
<p>Duplicate copy of the electron phase space density provided for the Geospace Environment Modeling (GEM) challenge event in March 2013 selected by the <em>Quantitative Assessment of Radiation Belt Modeling</em> focus group. The original copy of the data is available from <a href="https://drive.google.com/drive/u/0/folders/0ByNhSbWkAgdfaGt6TnJMcElhUTg">https://drive.google.com/drive/u/0/folders/0ByNhSbWkAgdfaGt6TnJMcElhUTg</a></p> <p> </p> <p>Data Providers:<br> Michael G. Henderson (LANL; mghenderson@lanl.gov)<br> Steven K. Morley (LANL; smorley@lanl.gov)</p> <p>This data product provides electron phase space density from the Van Allen Probes<br> ECT suite of instruments. The data are calculated similarly to the method described<br> in Morley et al. (2013), with some differences that are noted below.</p> <p>The files are provided in HDF5 format, so the files are self-describing and contain<br> ISTP-style metadata. The files should be directly readable with:<br> - SpacePy (http://sourceforge.net/p/spacepy)<br> - import the spacepy.datamodel module, use the function fromHDF5 to read the data<br> - Autoplot (http://autoplot.org)<br> - MatLab and IDL provide convience routines for reading HDF5</p> <p>Method<br> ------<br> Starting with directional differential flux data from HOPE, MagEIS and REPT, we<br> calculate the PSD as a function of energy, pitch angle, position and time.<br> Following the same basic method given by Morley et al., we transform this to phase <br> space density as a function of the three adiabatic invariants (M, K, L*); note that<br> where Morley et al. used a relativistic Maxwellian fit to the flux spectrum, these<br> data use a smoothing spline fit so that more complex spectral shapes can be<br> represented. Note also that Morley et al. only used REPT, where these files represent<br> the energy ranges of MagEIS and REPT, but also use HOPE to constrain the fit at low<br> energies.</p> <p>While the pitch angles are determined using the EMFISIS data, all three adiabatic <br> invariants are derived from a magnetic field model. These PSD data files use the<br> Tsyganenko and Sitnov (2005) model (aka TS04, T05 or TS05). The models were run using<br> the "definitive" Qin-Denton data files provided by the RBSP ECT-SOC. These files<br> should be made available through the QARBM google drive. </p> <p><br> Caveats<br> -------<br> These data should be considered preliminary. They have undergone a limited amount of<br> verification and prior to publication the data providers should be contacted. New<br> versions of these data may be generated at some point - we do not expect noticeable <br> changes to the data present.<br> Some gaps may be present in the files that are due to calculation of the adiabatic <br> invariants failing. The issues causing these gaps have been resolved in the underlying <br> software, but the data have not yet been regenerated.</p> <p><br> References<br> ----------<br> Morley, S. K., M. G. Henderson, G. D. Reeves, R. H. W. Friedel, and D. N. Baker (2013), <br> Phase Space Density matching of relativistic electrons using the Van Allen Probes: REPT results,<br> Geophys. Res. Lett., 40, 4798-4802, doi:10.1002/grl.50909.</p> <p>Tsyganenko, N. A., and M. I. Sitnov (2005), <br> Modeling the dynamics of the inner magnetosphere during strong geomagnetic storms, <br> J. Geophys. Res., 110, A03208, doi:10.1029/2004JA010798.</p> <p> </p> <p>Also included is the copy of the LANLgeoMag software used in the paper provided on <a href="https://github.com/drsteve/LANLGeoMag">https://github.com/drsteve/LANLGeoMag</a> </p> <p>Copyright (c) 2014, Los Alamos National Security, LLC All rights reserved. Copyright 2014. Los Alamos National Security, LLC. This software was produced under U.S. Government contract DE-AC52-06NA25396 for Los Alamos National Laboratory (LANL), which is operated by Los Alamos National Security, LLC for the U.S. Department of Energy. The U.S. Government has rights to use, reproduce, and distribute this software. NEITHER THE GOVERNMENT NOR LOS ALAMOS NATIONAL SECURITY, LLC MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR ASSUMES ANY LIABILITY FOR THE USE OF THIS SOFTWARE. If software is modified to produce derivative works, such modified software should be clearly marked, so as not to confuse it with the version available from LANL.</p> <p>Additionally, redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. Neither the name of Los Alamos National Security, LLC, Los Alamos National Laboratory, LANL, the U.S. Government, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL LOS ALAMOS NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</p> <p><br> </p>
Modeling the Depletion and Recovery of the Outer Radiation Belt During a Geomagnetic Storm: Combined MHD and Test Particle Simulations
<p>Data associated with JGR: Space Physics paper, "Modeling the Depletion and Recovery of the Outer Radiation Belt During a Geomagnetic Storm: Combined MHD and Test Particle Simulations".</p>
The Mother's Day solar storm of 11 May 2024 and its effect on Earth's radiation belts.
<p>The dataset presneted here are used in "The Mother’s Day solar storm of 11 May 2024 and its effect on<br>Earth’s radiation belts." <br><br>EPT files (ept_protons_x and ept_electrons_x) contain the differential flux observed by the energetic particle telescope (EPT) averaged in L-time bins (0.25L - 6 hours) from May 1st 2024 to June 30th 2024, where L is the McIlwain parameter. This averages are performed for each energy chanel of the EPT (6 for electrons and 10 for protons). Differential fluxes are given in [(s cm² sr MeV)^-1].</p> <p>Similar to the EPT files, the POES files contain electrons and proton fluxes from the MEPED instrument on board MetOp3 averaged on the same grid as the EPT fluxes. In this case proton fluxes are differential fluxes in units of [(s cm² sr keV)^-1] whereas electron fluxes are integral fluxes in units of [(s cm² sr)^-1].</p> <p>GOES file contains the integral proton fluxes observed by GOES from May 1st to June 30th 2024. Proton fluxes are given in [(s cm²)^-1].</p> <p>The nmdb file contains the count rates from ground based neutron monitors retrieved from the neutron monitor database.</p> <p>Note that PROBA-V/EPT data are publicly available on the Space Situational Awareness website of ESA https://swe.ssa.esa.int/space-radiation. POES data are available on https://satdat.ngdc.noaa.gov/sem/poes/data. GOES on https://www.swpc.noaa.gov/products/goes-proton-flux and OMNI on https://omniweb.gsfc.nasa.gov/html/ow_data.html</p>
Relativistic electron model in the outer radiation belt using a neural network approach
<p>This dataset includes the models, dataset, and extra figures for the paper titled</p> <p>Relativistic electron model in the outer radiation belt using a neural network approach</p> <p> </p>
Remote Sensing of Radiation Belt Energetic Electrons Using Lightning Triggered Upper Band Chorus
<p>We report very low frequency (VLF) observation of interaction of waves from atmospheric lightning with radiation belt particles. The observation provides a unique opportunity to remotely sense the dynamics of the energetic particle population in the Earth’s radiation belts and how this population leads to amplification and generation of waves.</p>
Data and Images for the paper "Evidence for a radiation belt around a brown dwarf" by Climent et al.
<p>Data used for the figures that appear in the main text and also in the supplementary materials in the paper titled "Evidence for a radiation belt around a brown dwarf" by Climent et al. published in Science.</p>
Data from: Quantifying radiation belt electron loss processes at L < 4
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Supporting data for "POES/MEPED angular response functions and the precipitating radiation belt electron flux"
<p>Data sets included as supporting information with the publication to appear in JGR - Space Physics. Numerical values are provided for the POES/MEPED energy and angular response functions, derived by Geant4 simulation, for application to electron and proton radiation belt data interpretation.</p>
Dataset of "Quantifying the Effects of Magnetic Field Line Curvature Scattering on Radiation Belt and Ring Current Particles"
<p>Dataset of "Quantifying the Effects of Magnetic Field Line Curvature Scattering on Radiation Belt and Ring Current Particles".</p><p>The following contains the simulation data used for drawing.</p>
Asymmetry in Uranus' high energy proton radiation belts
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Simulation data output used in test-particle simulations of linear and nonlinear interactions between a 2D whistler-mode wave packet and radiation belt electrons
<p><strong>Dataset</strong></p> <p>The zip file contains the data used in the paper "Test-particle simulations of linear and nonlinear interactions between a 2D whistler-mode wave packet and radiation belt electrons" submitted for publication in Geophysical Research Letters (GRL) by da Silva et al. See the GRL paper and Supporting Information for details about the simulations. This data has been uploaded to Zenodo to comply with AGU's data policy.</p> <p>To load the data please run the self-explanatory script load_hyb_test_part.m in Matlab. See README.txt for further instructions.</p> <p>C. L. da Silva, Mar/21/2018</p> <p> </p> <p><strong>Corresponding Article</strong></p> <p>C. L. da Silva, R. E. Denton, M. K. Hudson, R. M. Millan, K. Liu, J. Bortnik (2018) Test-particle simulations of linear and nonlinear interactions between a 2D whistler-mode wave packet and radiation belt electrons, Submitted for publication, <em>Geophys. Res. Lett.</em>, doi:10.1002/2018GL077877.</p> <p> </p> <p><strong>Article Abstract</strong></p> <p>Using test-particle simulations, we describe (in 2D) the interaction of an ensemble of electrons with a discrete whistler-mode wave packet, which propagates with a moderate wave-normal angle with respect to the background magnetic field. We evaluate both the average transport coefficients used in quasi-linear diffusion transport, and also the full nonlinear wave-particle interactions. The magnitude of the calculated diffusion coefficients is found to increase proportionally to the wave amplitude squared, in agreement with quasi-linear diffusion theory. Cyclotron resonance of counterstreaming electrons (n=1 harmonic number) is more important for pitch-angle scattering than Landau resonance. Landau resonance of costreaming electrons (n=0) is comparable to cyclotron resonance for energy diffusion and advection. Strong acceleration of high-pitch-angle, costreaming electrons arises in nonlinear wave-particle interactions with high amplitude waves. In our simulations with zero parallel electric field, the energy source for electron acceleration is the wave's perpendicular electric field, in both the cyclotron and Landau resonances. The Landau resonance can happen even with zero parallel electric field, if the wave packet propagates with a finite wave-normal angle. This resonance between the particle's azimuthal velocity and the wave fields leads to trapping and substantial parallel acceleration.</p> <p> </p> <p><strong>Article key points</strong></p> <p>Cyclotron resonance of counterstreaming electrons is dominant for pitch-angle scattering, consistent with quasi-linear theory</p> <p>Landau and cyclotron resonances are comparable for acceleration; here the energy source is the wave perpendicular electric field in both</p> <p>Substantial Landau parallel acceleration occurs with a finite wave-normal angle, even with zero parallel electric field</p> <p> </p> <p><strong>Acknowledgments</strong></p> <p>These simulations were performed at Dartmouth's Discovery computer cluster. We would like to thank all the supporting staff for their assistance and for their splendid maintenance of Discovery.</p> <p> </p> <p> </p> <p> </p>
UBER v1.0: A universal kinetic equation solver for radiation belts
<p>The zip file contains all scripts and simulation data used for producing Figure 2, Figure 3, Figure 4, Figure 5, Figure 6 and Table 2 of the manuscript "UBER v1.0: A universal kinetic equation solver for radiation belts".</p>
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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.
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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.