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5 results for “ULF waves”
ULF Wave Radial Diffusion Coefficients
<p>Hourly radial diffusion coefficients, DLL, derived from ground-based magnetometer measurements from March 16 to March 20, 2015 in units of days<sup>-1</sup>. The DLL values are plotted out at 100 equally spaced L* values from L*=1 to L*=5 derived from the TS05 magnetic field model at K=0 G<sup>1/2</sup>Re. These DLL values are used to reproduce the the evolution of the electron phase space density profiles in the Earth's outer radiation belt during the March 2015 geomagnetic storm presented in:</p> <p>Ozeke et al., The March 2015 Superstorm Revisited: Phase Space Density Profiles and Fast ULF Wave Diffusive Transport, Journal of Geophysical Research, 2019, submitted.</p> <p>The attached plot shows a comparison of these event specific diffusion coefficient with those obtained from the empirical models of:</p> <p>Brautigam, D. H., and J. M. Albert (2000), Radial diffusion analysis of outer radiation belt electrons during the October 9, 1990, magnetic storm, <em>J. Geophys. Res.</em>, 105(A1), 291–309, doi:10.1029/1999JA900344.</p> <p>and</p> <p>Ozeke, L. G., I. R. Mann, K. R. Murphy, I. Jonathan Rae, and D. K. Milling (2014), Analytic expressions for ULF wave radiation belt radial diffusion coefficients, <em>J. Geophys. Res. Space Physics</em>, 119, 1587–1605, doi:10.1002/2013JA019204.</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </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>
ULF wave events during THEMIS-CMO-FAIR magnetic conjunctions
<p>This dataset corresponds to an hdf5 file with stored information on Ultra Low Frequency (ULF) wave events during magnetic conjunctions between (1) NASA's Time History of Events and Macroscale Interactions during Substorms (THEMIS) satellites, (2) USGS College Alaska (CMO) magnetic observatory, and (3) the FAIR GNSS receiver near Fairbanks, Alaska. Magnetic field measurements are used for THEMIS (~3s sampling interval) and CMO (1s sampling interval), while 1s Total Electron Content (TEC) measurements are used from high-rate RINEX data for FAIR obtained from the NASA Crustal Dynamics Data Information System (CDDIS) archive of space geodesy data. The file also contains solar wind measurements and geomagnetic activity indices from NASA's OMNIWeb (https://omniweb.gsfc.nasa.gov/) database for the same magnetic conjunction intervals. </p> <p>ULF wave events are identified in different components of the magnetic field measured at THEMIS and/or CMO. They are also identified Total Electron Content (TEC) measured between FAIR and various GNSS satellites. Several properties of the waves are recorded, including wave power (nT^2 or TECU^2, see below for conversion factor to TECU^2/Hz or nT^2/Hz) and frequency, as well as supporting information. </p> <p> </p> <p><strong>The HDF5 file contains the following components:</strong></p> <p>- Groups: Logical containers that hold datasets and other groups.</p> <p>- Datasets: Multi-dimensional arrays holding the actual data.</p> <p>- Attributes: Metadata attached to datasets or groups providing additional information. </p> <p> </p> <p><strong>The top-level groups</strong> contain the names of each conjunction event including the conjunction date (YYYY-MM-DD) and middle time (HHMM), THEMIS satellite probe name (tha, thd, or the), ground magnetometer name (cmo), and GPS receiver name (fair).</p> <p> </p> <p><strong>The second-level groups</strong><strong> </strong>contain group names of individual GPS satellite (GPS**_psd_peak_info), three components of ground magnetic field perturbations (dgB*_psd_peak_info), three components of satellite magnetic field perturbations (dsB*_psd_peak_info), solar wind and geomagnetic indices (omni_data), and THEMIS electron flux (thm_eflux_data).</p> <p> </p> <p><strong>Under each GPS satellite group (GPS**_psd_peak_info), relevant datasets are: </strong></p> <p>common_peak_arr: this is a 1 by 6 array contains information on if a common peak to the TEC PSD is identified in any magnetic field perturbations from the THEMIS satellite or ground magnetometer. It is organized by [dgBx, dgBy, dgBz, dsBx, dsBy, dsBz]. [0,0,1,0,0,0] means a common peak with TEC PSD is identified in the ground magnetometer perturbation in the Bz component. Note that TEC data from a GPS satellite may not have any common peaks with magnetic field perturbations from the THEMIS satellite or ground magnetometer, in this case, this dataset (common_peak_arr) will be missing in this GPS satellite group.</p> <p>common_peak_freq [HZ]: the frequencies of all the common peaks identified.</p> <p>end_lat [degree]: latitude of IPP at 450 km at the end of the conjunction time.</p> <p>end_lon [degree]: longitude of IPP at 450 km at the end of the conjunction time.</p> <p>mad_dVTEC [TECU]: the median absolute deviation of the detrended VTEC time series during the conjunction interval.</p> <p>max_Elev [degree]: maximum elevation angle of the GPS satellite during the conjunction interval.</p> <p>max_VTEC [TECU]: maximum value of the VTEC time series during the conjunction interval.</p> <p>max_dVTEC [TECU]: maximum value of the detrended VTEC time series during the conjunction interval.</p> <p>mean_Elev [degree]: mean elevation angle of the GPS satellite during the conjunction interval.</p> <p>mean_lat [degree]: mean latitude of IPP at 450 km during the conjunction interval.</p> <p>mean_lon [degree]: mean longitude of IPP at 450 km during the conjunction interval.</p> <p>mean_VTEC [TECU]: mean value of VTEC time series during the conjunction interval.</p> <p>mid_lat [degree]: latitude of IPP at 450 km at the middle of the conjunction time.</p> <p>mid_lon [degree]: longitude of IPP at 450 km at the middle of the conjunction time.</p> <p>min_Elev [degree]: minimum elevation angle of the GPS satellite during the conjunction interval.</p> <p>min_VTEC [TECU]: minimum value of the VTEC time series during the conjunction interval.</p> <p>min_dVTEC [TECU]: minimum value of the detrended VTEC time series during the conjunction interval.</p> <p>peak_freq [HZ]: the frequencies of all peaks identified in the dVTEC PSD.</p> <p>peak_power [TECU^2]: the power of all peaks identified in the dVTEC PSD. To convert to TECU^2/Hz, multiply by 0.000868 .</p> <p>peak_prominence: the prominences of all peaks identified in the dVTEC PSD</p> <p>peak_width: FWHM of all peaks identified in the dVTEC PSD</p> <p>start_lat [degree]: latitude of IPP at 450 km at the beginning of the conjunction time.</p> <p>start_lon [degree]: longitude of IPP at 450 km at the beginning of the conjunction time.</p> <p> </p> <p><strong>Under each magnetic field perturbation group (d*B*_psd_peak_info), relevant datasets are: </strong></p> <p>common_peak_freq [HZ]: the frequencies of all the common peaks identified. This will be missing if no common peak is identified.</p> <p>peak_freq [HZ]: the frequencies of all peaks identified in the PSD of specific magnetic field component perturbation.</p> <p>peak_power [nT^2]: the power of all peaks identified in the PSD of specific magnetic field component perturbation. To convert to nT^2/Hz, multiply by 0.000868 .</p> <p>peak_prominence: the prominences of all identified in the PSD of specific magnetic field component perturbation.</p> <p>peak_width: FWHM of all peaks identified in the PSD of specific magnetic field component perturbation.</p> <p> </p> <p><strong>Under the omni_data group, relevant datasets are: </strong></p> <p>AE_INDEX [nT]: mean AE index during the conjunction interval.</p> <p>AL_ INDEX [nT]: mean AL index during the conjunction interval.</p> <p>ASY_D [nT]: mean ASY_D index during the conjunction interval.</p> <p>ASY_H [nT]: mean ASY_H index during the conjunction interval.</p> <p>AU_INDEX [nT]: mean AU index during the conjunction interval.</p> <p>BX_GSE [nT]: mean IMF Bx in the GSE coordinates during the conjunction interval.</p> <p>BY_GSE [nT]: mean IMF By in the GSE coordinates during the conjunction interval.</p> <p>BZ_GSE [nT]: mean IMF Bz in the GSE coordinates during the conjunction interval.</p> <p>DST [nT]: mean Dst index during the conjunction interval.</p> <p>F10_INDEX: mean F10 index during the conjunction interval.</p> <p>KP: mean Kp index during the conjunction interval.</p> <p>Pressure [nPa]: mean solar wind dynamic pressure during the conjunction interval.</p> <p>SYM_D [nT]: mean SYM_D index during the conjunction interval.</p> <p>SYM_H [nT]: mean SYM_H index during the conjunction interval.</p> <p>Vx [km/s]: mean solar wind speed in the X direction during the conjunction interval.</p> <p>Vy [km/s]: mean solar wind speed in the Y direction during the conjunction interval.</p> <p>Vz [km/s]: mean solar wind speed in the Z direction during the conjunction interval.</p> <p>proton_density [cc]: mean solar wind proton density during the conjunction interval.</p> <p> </p> <p><strong>Under the thm_eflux_data group, the relevant dataset is:</strong></p> <p>thm_eflux [ergs/cm^2/s]: mean THEMIS electron flux during the conjunction interval.</p> <p> </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>
Simulation Results for "Characteristics of Electron Precipitation Directly Driven by Poloidal ULF waves"
<p>This dataset contains the simulation results and the corresponding code to produce the figures in the manuscript "Characteristics of Electron Precipitation Directly Driven by Poloidal ULF waves". The name of each data file indicates its corresponding figure, and the Matlab code could be used to produce the figures in the manuscript.</p>
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