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237 results for “ionosphere”
Results of "Storm Time Data Assimilation in the Thermosphere Ionosphere with TIDA" CHAMP, GRACE-A, and GRACE-B neutral density data assimilation into CTIPe for 2003 Halloween Storms
<p># README</p> <p>Results for the article "Storm Time Neutral Density Assimilation in the Thermosphere Ionosphere with<br> TIDA".</p> <p>There are three storms presented here:</p> <p>1. 2003 storm: October 26-30, 2003<br> 2. 2004 storm: July 26-30, 2004<br> 3. 2002 storm: September 27 - October 2, 2002.</p> <p>For each of these three storms, there are four runs. For each storm, we've done a run<br> assimilating all satellites, and then three more assimilating each satellite individually and<br> comparing against the others.</p> <p>Each directory name before underscore identifies the date the run was<br> started. After the underscore identifies the date assimilated.</p> <p>This readme uses the notation that in curly brackets the satellites assimilated are given.</p> <p>- a stands for GRACE-A<br> - b stands for GRACE-B<br> - c stands for CHAMP</p> <p>The runs are summarized below:</p> <p>1. 2003 storm: {a, b, c}: 2021-12-29T1259_...<br> 3. 2003 storm: {a}: 2022-01-01T1654_...<br> 4. 2003 storm: {b}: 2022-01-02T1423_...<br> 2. 2003 storm: {c}: 2021-12-29T2342_...</p> <p>5. 2004 storm: {a, b, c}: 2022-01-03T1614_...<br> 6. 2004 storm: {a}: 2022-01-04T1027_...<br> 7. 2004 storm: {b}: 2022-01-04T2144_...<br> 8. 2004 storm: {c}: 2022-01-05T0502_...</p> <p>9. 2002 storm: {a, b, c}: 2022-01-02T2025_...<br> 10. 2002 storm: {a}: 2022-01-05T1056_...<br> 11. 2002 storm: {b}: 2022-01-05T1854_...<br> 12. 2002 storm: {c}: 2022-01-06T1017_...</p> <p>## Example result directory</p> <p>2021-12-29T1259_d2003-10-27<br> ├── density_champ_density.csv<br> ├── density_grace-a_density.csv<br> ├── density_grace-b_density.csv<br> └── inputs<br> ├── reference_2003-10-27_input.txt<br> └── special_2003-10-27_input.txt<br> <br> 1 directory, 5 files</p> <p>## Zenodo doesn't support directories</p> <p>So, the file structure has been flattened in the following way:</p> <p>Before: ./aaa/bbb/ccc.png</p> <p>After: ./aaa-bbb-ccc.png</p> <p>https://unix.stackexchange.com/~/45659</p> <p> </p>
Results of "Ensemble Kalman Filter for the Thermosphere Ionosphere", CHAMP neutral density assimilation into CTIPe for March 20, 2007
<p>These data are the result of assimilating neutral density measurements from the CHAMP satellite on March 20, 2007 into the CTIPe model and and comparison of results with observations made by the GRACE satellite. Data assimilation is performed in three configurations: Configuration (i) is ds, state correction. Configuration (ii) is dfds, both input estimatation and state correction. Configuration (iii) is df, estimation of model inputs only.</p> <p>This data is associated with the following publication:</p> <blockquote> <p>Codrescu S., M.V. Codrescu, and M. Fedrizzi (2018), An Ensemble Kalman Filter for the Thermosphere-Ionosphere, Space Weather, 16, doi:<a href="http://dx.doi.org/10.1002/2017SW001752" title="Link to external resource: 10.1002/2017SW001752">10.1002/2017SW001752</a>.</p> </blockquote> <p> </p>
Dataset for: Statistical properties of meso-scale plasma flows in the nightside high-latitude ionosphere
<p>This dataset is a compilation of statistical results from Gabrielse et al. [2018] (<a href="https://doi.org/10.1029/2018JA025440">https://doi.org/10.1029/2018JA025440</a>). If you would like to use the dataset, please contact Christine Gabrielse (cgabrielse@ucla.edu, cgabrielse@gmail.com). Depending on how the results are used, the main authors request co-authorship on publications. </p> <p>The following list describes the columns in each data file labeled, ***_FLOW-DATA-PCvsAO_YYYY.txt <br> Files named ***_FLOW-DATA-PCvsAO_YYYY_poleward.txt are for poleward-directed flows. <br> Each text file is for a different year (YYYY). <br> AO=auroral oval<br> PC=polar cap</p> <p> time [YYYYMMDDhhmmss]<br> flagAO [-1=flow could not be observed. 0=flow could be observed, but was not. 1=flow was observed]<br> flagPC [-1=flow could not be observed. 0=flow could be observed, but was not. 1=flow was observed]<br> FWHMavg_AO [degrees]<br> FWHMkmavg_AO=[km]<br> longtestranges=[ignore]<br> Velmaxavg_AO=[m/s, actual average of max V in each range gate used]<br> VelmaxFITavg_AO=[m/s, determined from the Gaussian fits]<br> FWHMavg_PC=[degrees]<br> FWHMkmavg_PC=[km]<br> Velmaxavg_PC=[m/s, actual average of max V in each range gate used]<br> VelmaxFITavg_PC=[m/s, determined from the Gaussian fits]<br> ;;For the bearings/orientation, see the orientation text files. The following four variables were calculated in a first step but are not<br> ;;those used in the paper. They were not found with the strict selection criteria. Please do not use.<br> mbearingAO=[degrees in magnetic coordinates, a negative value is South of East (clockwise from East), a positive value is North of East (CC)]<br> mbearingPC=[degrees in magnetic coordinates, a negative value is South of East (clockwise from East), a positive value is North of East (CC)] <br> gbearingAO=[degrees in geographic coordinates, a negative value is South of East (clockwise from East), a positive value is North of East (CC)]<br> gbearingPC=[degrees in geographic coordinates, a negative value is South of East (clockwise from East), a positive value is North of East (CC)]<br> ;;;;;;;;;;;;;;;<br> minlatAO=[degrees, min geographic latitude of the flow]<br> maxlatAO=[degrees, max geographic latitude of the flow]<br> minlatPC=[degrees, min geographic latitude of the flow]<br> maxlatPC=[degrees, max geographic latitude of the flow]<br> mltAO=[degrees (MLT)]<br> mltPC=[degrees (MLT)]<br> AE=[nT]<br> AL=[nT]<br> SYMH=[nT]<br> IMFBz=[nT]<br> IMFBy=[nT]<br> F107=[sfu]</p> <p>The following list describes the columns in each data file labeled, ***_orientation_YYYY.txt <br> Files named ***_orientation_YYYY_poleward.txt are for poleward-directed flows. <br> Each text file is for a different year (YYYY). <br> The orientation was determined when enough bearings between RGs were available. See Gabrielse et al. [2018] for description. <br> https://doi.org/10.1029/2018JA025440 <br> AO=auroral oval<br> PC=polar cap</p> <p> time [YYYYMMDDhhmmss]<br> mbearingAO [degrees clockwise from magnetic North]<br> gbearingAO [degrees clockwise from geographic North]<br> mbearingPC [degrees clockwise from magnetic North]<br> gbearingPC [degrees clockwise from geographic North]</p> <p>The following list describes the columns in each data file labeled, ***_SPEC_TEST_***_noRG1-2.txt</p> <p> time [YYYYMMDDhhmmss]<br> RG [the range gate number at which the polar cap boundary was determined at RNK, or the auroral oval's equatorial boundary at SAS]</p>
11 May 2024 Superstorm Ionospheric Observations in the Continental US
<p><strong>May11_150km.mat: </strong> MATLAB save file - Ionospheric total electron content data from worldwide GNSS receivers, processed by MIT Haystack Observatory through the Millstone Hill Geospace Facility. Data is line of sight and conversion assumes a non-standard 150 km ionospheric pierce point. </p> <p>Direct permanent link: Anthea Coster, MIT/Haystack Observatory. (2024) Data from the CEDAR Madrigal database. Available from https://w3id.org/cedar?experiment_list=experiments4/2024/gps/11may24&file_list=los_20240511.001.h5</p> <p>GPS TEC data products and access through the Madrigal distributed data system are provided to the community by the Massachusetts Institute of Technology under support from US National Science Foundation grant AGS-1952737. Data for the TEC processing is provided from the following organizations: UNAVCO, Scripps Orbit and Permanent Array Center, Institut Geographique National, France, International GNSS Service, The Crustal Dynamics Data Information System (CDDIS), National Geodetic Survey, Instituto Brasileiro de Geografia e Estatística, RAMSAC CORS of Instituto Geográfico Nacional de la República Argentina, Arecibo Observatory, Low-Latitude IonosphericSensor Network (LISN), Canadian High Arctic Ionospheric Network, Institute of Geology and Geophysics, Chinese Academy of Sciences, China Meteorology Administration, Centro di Ricerche Sismologiche, Système d'Observation du Niveau des Eaux Littorales (SONEL), RENAG: REseau NAtional GNSS permanent - https://doi.org/10.15778/resif.rg, GeoNet - the official source of geological hazard information for New Zealand, Finnish Meteorological Institute, SWEPOS - Sweden, Hartebeesthoek Radio Astronomy Observatory, TrigNet Web Application, South Africa, Australian Space Weather Services, RETE INTEGRATA NAZIONALE GPS, Estonian Land Board, TU Delft, Western Canada Deformation Array, EUREF Permanent GNSS Network, GeoDAF: Geodetic Data Archiving Facility, African Geodetic Reference Frame (AFREF), Kartverket - Norwegian Mapping Authority, Geoscience Australia, IGS Data Center of Wuhan University, Pacific Northwest Geodetic Array, Nevada Geodetic Laboratory, Earth Observatory of Singapore, National Time and Frequency Standard Laboratory - Taiwan, and Korea Astronomy and Space Science Institute.</p> <p><strong>teczero.mat:</strong> MATLAB save file - 5-minute averaged background median TEC map, derived from May11_150km.mat file.</p> <p><strong>TECmaps0.m:</strong> MATLAB script - plotting script, employing teczero.mat, and used for Figure 3 and Figure 4B of manuscript.</p> <p><strong>gps_map.mat:</strong> MATLAB save file - source data for Figure 4A of manuscript: median vertical TEC map over 2-minute interval 0207-0208 UTC on 2024-05-11. </p> <p><strong>Fig4a_map.m: </strong>MATLAB script - plotting script, employing gps_map.mat, and used for FIgure 4A of manuscript.</p> <p><strong>cntr.m</strong>: MATLAB script - coastline plotting function.</p> <p><strong>burst.m</strong>: MATLAB script - plots individual LOS TEC data showing TEC bursts. Saves to "bursts.mat". Inputs "May11_150km.mat".</p> <p><strong>bursts.mat</strong>: MATLAB save file - individual TEC burst results.</p> <p><strong>1 Missouri_Skies_-_All-Sky_Fisheye_Missouri_Skies_Fishey_2030UT_2127UT.mp4: </strong>MP4 image file. Fisheye lens image of aurora from Missouri during 2024-05-11 storm. Used in Figure 2 of manuscript.</p> <p><strong>{amt,att,bmt,bot,het,hmt,nmt,omt,pat,sum,vmt}240511.g.001.hdf5</strong> - MagStar magnetometer measurements in HDF5 self-documenting file format, used for magnetometer figures in manuscript. Downloaded from the Madrigal database system. Direct permanent link: Jenn Gannon, Paul E. Meade, Eframir Franco-Diaz, Computational Physics. (2024) Data from the CEDAR Madrigal database. Available from https://w3id.org/cedar?experiment_list=experiments/2024/het/11may24&file_list=het240511g.001.hdf5. (Replace "het" with appropriate 3-letter site name from above list).<br><br></p>
Global Ionosphere Maps of vertical electron content combined in real-time from the RT-GIMs of CAS, CNES, UPC-IonSAT, and WHU International GNSS Service (IGS) centers (from Dec 1, 2020, to March 1, 2021)
<p>The datasets consists on 91 daily files, in IONEX format (<a href="http://ftp.aiub.unibe.ch/ionex/draft/ionex11.pdf">http://ftp.aiub.unibe.ch/ionex/draft/ionex11.pdf</a>) , corresponding to three months of global ionospheric maps (GIM) of vertical total electron content (VTEC) computed in real-time from the assessed and combined real-time GIMs generated by four analysis centers. Indeed, the Real-Time Working Group (RTWG) of International GNSS Service (IGS) is dedicated to providing high-quality data, high-accuracy products for Global Navigation Satellite System (GNSS) navigation, positioning, timing, and Earth observations. As one of the important part of real-time products, the IGS combined Real-Time Global Ionosphere Map (RT-GIM) have been generated by real-time weighting technique with the help of RT-GIMs from IGS real-time ionosphere centers including the Chinese Academy of Sciences (CAS), Centre National d’Etudes Spatiales (CNES), Universitat Politècnica de Catalunya (UPC), and Wuhan University (WHU). Compared with IGS rapid Global Ionosphere Maps (GIMs) (corg, ehrg, emrg, esrg, igrg, jprg, uhrg, uprg, uqrg, whrg) and IGS final combined GIM (igsg), the IGS combined RT-GIM (irtg) is equivalent to the post-processed GIMs and even better than some rapid GIMs. The IGS RT-GIMs are reliable sources of real-time global VTEC information and has great potential for real-time applications including range error correction for transionospheric radio signals (such as GNSS positioning, search and rescue, air traffic, radar altimetry, and radioastronomy), the monitoring of space weather (such as geomagnetic and ionospheric storms, ionospheric disturbance) and detection of natural hazards on a global scale (such as hurricanes/typhoons, ionospheric anomalies associated with earthquakes)</p>
In situ observations of Ganymede's outflowing ionosphere
<p>The file contains values for ionospheric moments from the Juno flyby of Ganymede on 7 June 2021, during the period between 16:50 to 17:00, UTC. A description of the flyby and the data set is found in Valek et al. (2022), <em>In situ ion composition observations of the Ganynmede's outflowing ionosphere</em>, GRL DOI:10.1029/2022GL100281.</p>
Ionospheric Vertical Correlation Lengths Derived From IRI-2016 Model Errors
<p>Ionospheric vertical correlation lengths based on IRI-2016 model and Incoherent Scatter Radar (ISR) data.</p> <p><strong>Important! The analysis was performed in log space. </strong></p> <p>ISR used for this analysis:</p> <p>Jicamarca, Arecibo, Millstone Hill, Poker Flat ISR, and ResoluteBay North ISR.</p> <p>This metadata can be used for the construction of the covariance matrix for ionospheric data assimilation.</p> <p>Inside of the .nc file:</p> <p>lat=array of geomagnetic latitudes (degrees)<br> alt=arrays of altitudes (km)<br> vert_corr1=array of size (nalt, nlat), contains vertical correlation length above the reference point for different latitudes<br> vert_corr2=array of size (nalt, nlat), contains vertical correlation length below the reference point for different latitudes<br> </p>
WACCM-X simulation output in support of publication "Impact of upward propagating migrating diurnal and semidiurnal tides on the ionosphere-thermosphere seasonal variation"
<p>This dataset contains simulation output from the Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension (WACCM-X) in support of the publication "Impact of upward propagating migrating diurnal and semidiurnal tides on the ionosphere-thermosphere seasonal variation". Data files include the simulation results for a five-member ensemble of free-running simulations, simulations without the upward propagating diurnal migrating tide (DW1), and simulations without the upward propagating semidiurnal migrating tide (SW2). </p>
Corresponding Dataset for "Ganymede's Ionosphere observed by a Dual-Frequency Radio Occultation with Juno"
<p> Corresponding Dataset for "Ganymede’s Ionosphere observed <br> by a Dual-Frequency Radio Occultation with Juno"<br> README FILE<br> VERSION 2<br> Dustin Buccino<br> April 22, 2024<br> Jet Propulsion Laboratory<br> California Institute of Technology</p> <p>=============================================================================<br>VERSION 2 INFORMATION<br>=============================================================================</p> <p> Version 2 of this dataset separates the Electron Density profile from the<br>main data files and makes a correction to the egress profile that was<br>discovered. Differences in egress profile are very small and within<br>the uncertainties. Furthermore egress is statistically a non-detection<br>(zero densities), but for sake of accuracy they are reposted to be<br>consistent with the publication.</p> <p>=============================================================================<br>INTRODUCTION<br>=============================================================================</p> <p> This dataset contains processed radio science data and results of the<br>Juno Ganymede radio occultation. This dataset is provided in order to <br>supplement the submitted article to the "Geophysical Research Letters"<br>journal:</p> <p> Buccino, D.R., et al (2022), Ganymede’s Ionosphere observed by a <br> Dual-Frequency Radio Occultation with Juno, Geophysical Research <br> Letters, submitted February 2022.</p> <p><br> Please note the raw data used in this analysis are not provided in this<br>supplementary dataset. The raw Juno Gravity Science Data may be found at <br>the Planetary Data System:</p> <p> Buccino, D. R. (2016). Juno jupiter gravity science raw data set <br> V1.0, JUNO-J-RSS-1 JUGR-V1.0, NASA planetary data system (PDS). <br> Retrieved from https://atmos.nmsu.edu/PDS/data/jnogrv_1001/<br> </p> <p>=============================================================================<br>ARCHIVE INFORMATION<br>=============================================================================</p> <p> This archive contains two files within the root directory.<br> <br> ROOT<br> `- JunoG34OccData_Egress_v2.csv</p> <p> This data file contains the EGRESS data relevant to the radio<br> occultation. The data is a timeseries of impact parameter, sky<br> sky frequency at X-band and Ka-band, the dual-frequency <br> combination, the calibrated dual-frequency, Total Electron <br> Content.</p> <p> `- JunoG34_GRL_Egress_Profile_v2.csv</p> <p> This data file contains the EGRESS Electron density, and <br> 1-sigma electron density uncertainty.</p> <p> `- JunoG34OccData_Ingress_v2.csv</p> <p> This data file contains the INGRESS data relevant to the radio<br> occultation. The data is a timeseries of impact parameter, sky<br> sky frequency at X-band and Ka-band, the dual-frequency <br> combination, the calibrated dual-frequency, Total Electron <br> Content.</p> <p> `- JunoG34_GRL_Ingress_Profile_v2.csv</p> <p> This data file contains the INGRESS Electron density, and <br> 1-sigma electron density uncertainty.</p> <p>=============================================================================<br>FILE FORMAT<br>=============================================================================</p> <p> This dataset contains only a comma-separated text files which are<br>given with the "*.csv" extension.</p> <p><br> CSV FILES<br> -------------------------------------------------------------------------</p> <p> The Comma-Separated Value (CSV) files are plain-text files. Values in<br> each data file are separated using a comma ",". Each column is defined <br> by a header row which provides a description of each column.<br> </p> <p>=============================================================================<br>ACKNOWLEDGMENTS<br>=============================================================================</p> <p>This work was carried out at the Jet Propulsion Laboratory, <br>California Institute of Technology, under contract with the National <br>Aeronautics and Space Administration. Government sponsorship acknowledged.</p> <p>EG, LGC, PT, MZ and AC are grateful to the Italian Space Agency (ASI) for <br>financial support through Agreement No. 2018-25-HH.0 in the context of ESA's <br>JUICE mission, and Agreement No. 2017-40-H.1-2020, and its extension <br>2017-40-H.02020-13-HH.0, for ESA’s BepiColombo and NASAs Juno radio science <br>experiments. EG is grateful to "Fondazione Cassa dei Risparmi di Forlì" for <br>financial support of his PhD fellowship.</p> <p>PS and AH were supported by NASA Contract NNM06AA75C from the Marshall <br>Space Flight Center under subcontract 699054X from Southwest Research <br>Institute.</p> <p><br>=============================================================================<br>PRIMARY POINT OF CONTACT<br>=============================================================================</p> <p>Dustin Buccino<br>Jet Propulsion Laboratory<br>Planetary Radar and Radio Sciences<br>(818) 393 - 1072<br>Dustin.R.Buccino@jpl.nasa.gov</p> <p>=============================================================================<br>ACRONYMS AND ABBREVIATIONS<br>=============================================================================</p> <p> ASCII American Standard Code for Information Interchange<br> DOY Day of year<br> DSN Deep Space Network<br> JPL Jet Propulsion Laboratory<br> NAIF Navigation Ancillary Information Facility<br> NASA National Aeronautics and Space Administration<br> PDS Planetary Data System<br> RS Radio Science<br> RSS Radio Science Subsystem<br> SIS Software Interface Specification<br> TXT Text file<br> UTC Universal Time, Coordinated</p>
Database of Nightside, High-latitude Ionosphere Meso-scale Flow Characteristics
<p>This database is a compilation of nightside, high-latitude ionosphere meso-scale flow characteristics built on those used in Gabrielse et al. [2018] (<a href="https://doi.org/10.1029/2018JA025440">https://doi.org/10.1029/2018JA025440</a>). It is the most complete version. If you would like to use the database, please contact Christine Gabrielse (cgabrielse@ucla.edu, cgabrielse@gmail.com, and/or christine.gabrielse@aero.org). Depending on how the results are used, the main authors request co-authorship on publications that utilize this database. </p> <p>The methodology and selection criteria can be found in Gabrielse et al. [2018] (<a href="https://doi.org/10.1029/2018JA025440">https://doi.org/10.1029/2018JA025440</a>). </p> <p>The following list describes the columns in each data file labeled, ***_FLOW-DATA-PCvsAO_YYYY.txt <br> The first three letters (RNK or SAS) designate the station used (Rankin Inlet or Saskatoon).<br> Files named ***_FLOW-DATA-PCvsAO_poleward_YYYY.txt are for poleward-directed flows. <br> Each text file is for a different year (YYYY). <br> <br> AO=Auroral Oval for Rankin Inlet; equatorward of the auroral oval for Saskatoon (not used)<br> PC=Polar Cap for Rankin Inlet; Auroral Oval for Saskatoon</p> <p>(Note: the data files for RNK and SAS have the same format, so the PC designator means flows above the pertinent boundary (polar cap boundary for RNK, auroral oval equatorward boundary at SAS) and the AO designator means flows below the pertinent boundary.)</p> <p> time [YYYYMMDDhhmmss]<br> flagAO [-1=flow could not be observed. 0=flow could be observed, but was not. 1=flow was observed]<br> flagPC [-1=flow could not be observed. 0=flow could be observed, but was not. 1=flow was observed]<br> FWHMavg_AO [degrees]<br> FWHMkmavg_AO=[km]<br> longtestranges=[ignore]<br> Velmaxavg_AO=[m/s, actual average of max V in each range gate used]<br> VelmaxFITavg_AO=[m/s, determined from the Gaussian fits]<br> FWHMavg_PC=[degrees]<br> FWHMkmavg_PC=[km]<br> Velmaxavg_PC=[m/s, actual average of max V in each range gate used]<br> VelmaxFITavg_PC=[m/s, determined from the Gaussian fits]</p> <p>;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;<br> For the bearings/orientation, see the orientation text files. The following four variables were calculated in a first step but are not<br> those used in the paper. They were not found with the strict selection criteria. **Please do not use.**<br> mbearingAO=[degrees in magnetic coordinates, a negative value is South of East (clockwise from East), a positive value is North of East (CC)]<br> mbearingPC=[degrees in magnetic coordinates, a negative value is South of East (clockwise from East), a positive value is North of East (CC)] <br> gbearingAO=[degrees in geographic coordinates, a negative value is South of East (clockwise from East), a positive value is North of East (CC)]<br> gbearingPC=[degrees in geographic coordinates, a negative value is South of East (clockwise from East), a positive value is North of East (CC)]<br> ;;;;;;;;;;;;;;;<br> minlatAO=[degrees, min geographic latitude of the flow]<br> maxlatAO=[degrees, max geographic latitude of the flow]<br> minlatPC=[degrees, min geographic latitude of the flow]<br> maxlatPC=[degrees, max geographic latitude of the flow]<br> mltAO=[degrees (MLT)]<br> mltPC=[degrees (MLT)]<br> AE=[nT]<br> AL=[nT]<br> SYMH=[nT]<br> IMFBy=[nT]<br> IMFBz=[nT] <br> F107=[sfu]</p> <p>The following list describes the columns in each data file labeled, ***_orientation_YYYY.txt <br> Files named ***_orientation_poleward_YYYY.txt are for poleward-directed flows. <br> Each text file is for a different year (YYYY). <br> The orientation was determined when enough bearings between RGs were available. See Gabrielse et al. [2018] for description. <br> https://doi.org/10.1029/2018JA025440 <br> AO=auroral oval<br> PC=polar cap</p> <p> time [YYYYMMDDhhmmss]<br> mbearingAO [degrees clockwise from magnetic North]<br> gbearingAO [degrees clockwise from geographic North]<br> mbearingPC [degrees clockwise from magnetic North]<br> gbearingPC [degrees clockwise from geographic North]</p> <p>The following list describes the columns in each data file labeled, ***_SPEC_TEST_***_noRG1-2.txt</p> <p> time [YYYYMMDDhhmmss]<br> RG [the range gate number at which the polar cap boundary was determined at RNK, or the auroral oval's equatorial boundary at SAS]</p>
Derivation of Hemispheric Ionospheric Current Functions From Ground-Level Magnetic Fields
<p>These files provide the input and output data for the Figures shown in the paper "Derivation of<br> Hemispheric Ionospheric Current Functions From Ground-Level Magnetic Fields" by Daniel Weimer, published in the Journal of Geophysical Research, Space Physics, paper number 2018JA026191, doi:10.1029/2018JA026191</p> <p>Two IDL program files and the original, PDF versions of the figures are included.</p> <p>The data are provided as IDL "SAVE" files, readable in IDL with the "RESTORE" command. NetCDF<br> versions are included, readable with any NetCDF software library. These NetCDF files have the same<br> names as the ".xdr" files, except they have the extension ".nc". Scalar variables (length 1) are put<br> into the Global Attributes in these files.</p> <p>The files in this archive are:</p> <p>Figures:<br> Figure_1.PDF<br> Figure_2.PDF<br> Figure_3.PDF<br> Figure_4.PDF<br> Figure_5.PDF<br> Figure_6.PDF</p> <p>IDL Programs:<br> spherical_cap_90_fits.pro : Routines for fitting magnetic field data on a hemispheric cap (90<br> degrees), using spherical harmonics having both internal and external sources (or external alone),<br> and functions for evaluating the results as equivalent currents, or the magnetic field components.</p> <p> AllLegendre.pro : Required by spherical_cap_90_fits.pro, provides computations of Associated<br> Legendre Polynominals as arrays, for all combinations of l and m, up to Lmax and Mmax, as well as first derivatives.</p> <p>Data Files:</p> <p> Figures_1_2_3_4_dB_ModelData.xdr : Magnetic field values (output from the 2013 empirical model),<br> shown in Figure 1, and used to calculate the coefficients used to make Figures 2, 3, and 4.<br> Contents:<br> ALLLATS FLOAT = Array[8640] , array of latitude values, degrees<br> ALLMLTS FLOAT = Array[8640] , array of Magnetic Local Time (MLT) values, hours<br> DBNS FLOAT = Array[8640] , array of northward magnetic field values<br> DBES FLOAT = Array[8640] , array of eastward magnetic field values<br> DBVS FLOAT = Array[8640] , array of vertical (downward) magnetic field values<br> NLATS FLOAT = 180.000<br> NMLTS INT = 48<br> empirical model inputs:<br> BT FLOAT = 10.0000 , magnitude of the IMF<br> ANGLE FLOAT = 180.000 , IMF clock angle<br> F107 FLOAT = 120.000 , F10.7 solar index<br> SWVEL FLOAT = 400.000 , solar wind velocity<br> TILTA FLOAT = 0.00000 , dipole tilt angle</p> <p> Figures_2_3_4_SCHA90FitResults.xdr : The coefficients obtained from the fits, used to generate<br> Figures 2, 3, and 4.<br> Contents:<br> SPHCE DOUBLE = Array[115] , external spherical harmonic coefficients<br> SPHCI DOUBLE = Array[115] , interal spherical harmonic coefficients<br> NOINT_SPHCE DOUBLE = Array[115] , external spherical harmonic coefficients,<br> derived without using the internal terms in the fitting of the magnetic potential<br> The following variables are documented in the IDL program spherical_cap_90_fits.pro:<br> MAXL INT = 34<br> MAXM INT = 3<br> ODD INT = 1<br> EVEN INT = 0<br> CSIZE INT = 115<br> LS INT = Array[115]<br> MS INT = Array[115]<br> AB BYTE = Array[115]</p> <p> Figures_3_4_dB_ModelData-Dst.xdr : Magnetic field values, after subtraction of the ring current<br> magnetic field, used to calculate the coefficients to make Figures 3 and 4.<br> Contents: Same variables as in file Figures_1_2_3_4_dB_ModelData.xdr</p> <p> Figures_3_4_SCHA90FitResults-Dst.xdr : The coefficients obtained from fitting the magnetic field<br> that had the ring current subtracted, used to make Figures 3, and 4.<br> Contents: Same variables as in file Figures_2_3_4_SCHA90FitResults.xdr</p> <p> Figure_5_dB_ModelDataTilt3x-Dst.xdr : eight sets of magnetic field values, after subtraction of the<br> ring current magnetic field, used to calculate the coefficients to generate Figure 5.<br> Contents: Similar variables as in file Figures_1_2_3_4_dB_ModelData.xdr, except that TILTA is<br> replaced by TILTS, an array with the eight dipole tilt angles. The magnetic field values are<br> replaced by these arrays:<br> DBN3X FLOAT = Array[180, 48, 3] , northward magnetic field, eight sets<br> DBE3X FLOAT = Array[180, 48, 3] , eastward magnetic field, eight sets<br> DBV3X FLOAT = Array[180, 48, 3] , vertical magnetic field, eight sets</p> <p> Figure_5_SCHA90FitResultsTilt3x-Dst.xdr : eight sets of coefficients obtained from fitting the<br> magnetic field, used to make Figure 5.<br> Contents: Same variables as in file Figures_2_3_4_SCHA90FitResults.xdr, except for these arrays:<br> SPHCE3X DOUBLE = Array[115, 3] , external spherical harmonic coefficients, eight sets<br> SPHCI3X DOUBLE = Array[115, 3] , internal spherical harmonic coefficients, eight sets</p> <p> Figure_6_dB_ModelDataClock8x-Dst.xdr : Eight sets of magnetic field values, after subtraction of<br> the ring current magnetic field, used to calculate the coefficients to generate Figure 6.<br> Contents: Similar variables as in file Figures_1_2_3_4_dB_ModelData.xdr, except that ANGLE is<br> replaced by ANGLES, an array with the eight IMF clock angles. The magnetic field values are<br> replaced by these arrays:<br> DBN8X FLOAT = Array[180, 48, 8] , northward magnetic field, eight sets<br> DBE8X FLOAT = Array[180, 48, 8] , eastward magnetic field, eight sets<br> DBV8X FLOAT = Array[180, 48, 8] , vertical magnetic field, eight sets</p> <p> Figure_6_SCHAFitResultsClock8x-Dst.xdr : Eight sets of coefficients obtained from fitting the<br> magnetic field, used to make Figure 6.<br> Contents: Same variables as in file Figures_2_3_4_SCHA90FitResults.xdr, except for these arrays:<br> SPHCE8X DOUBLE = Array[115, 8] , external spherical harmonic coefficients, eight sets<br> SPHCI8X DOUBLE = Array[115, 8] , internal spherical harmonic coefficients, eight sets<br> </p>
The Time Variable Ionospheric Electric Field (TiVIE) Model Outputs v 1.0
<p>These are the outputs for the TiVIE model v 1.0 produced by Maria-Theresia Walach, Lancaster University for the publication Walach, M.-T., and Grocott, A. (submitted 2024). </p>
The impact of 11 May 2024 super geomagnetic storm on the plasma distribution over the Indian equatorial/low latitude ionospheric region
<p>The file contains the data set and the software for the generation the plots used in the manuscript " The impact of 11 May 2024 super geomagnetic storm on the plasma distribution over the Indian equatorial/low latitude ionospheric region".</p>
First In-Situ Measurements of Travelling Ionospheric Disturbances at 420 km Altitude by the Scintillation Observations and Response of The Ionosphere to Electrodynamics (SORTIE) CubeSat
<p>Companion dataset to the paper entitled "First In-Situ Measurements of Travelling Ionospheric Disturbances at 420 km Altitude by the Scintillation Observations and Response of The Ionosphere to Electrodynamics (SORTIE) CubeSat". The dataset includes the SORTIE CubeSat IVM Level 2 ion density and GPS TEC data used in the study along with the WRF simulation results.</p>
Additional results for article "A new approach for the generation of real-time GNSS low-latitude ionospheric scintillation maps"
<p>Complete set of interpolation error and correlation metrics for the approaches GDA, IDW, RBF and GPR for all the 12 pre-processing options using the SSS cross-validation scheme for the 10-hour dataset (40 maps with 16-minute interval for each approach and each pre-processing options) - file “Complete table of interpolation errors and correlation.csv”.</p> <p>Complete set of scintillation maps for the approaches GDA, IDW, RBF and GPR for all the 12 pre-processing options covering the 10-hour dataset (40 maps with 16-minute interval for each approach and each pre-processing options) - file “Scintillation maps for the 10-hour dataset.zip”.</p> <p>Comparison plots of the scintillation maps generated by the approaches GDA, IDW, RBF and GPR with the pre-processing options SAR, SMR and VQI for each of the 40 intervals of time of 16 minutes covering the 10-hour dataset - file “Set of maps for all 4 approaches with the SAR, SMR and VQI sets of options.zip”.</p> <p>Sequence of scintillation maps for the 8-hour dataset generated by the GPR(VQI) approach for the three time resolutions (1, 2, and 16-minute) - file “Scintillation maps for the 8-hour comparison dataset.zip”.</p> <p>Animations corresponding to the sequence of maps generated by the GPR(VQI) approach for the 8-hour dataset, and for the three time resolutions (1, 2, and 16-minute) - file “Animations of GPR(VQI) maps for the 8-hour comparison dataset.zip”.</p>
Electronic Supplement / Data Archive for "Global Variations in the Time Delays Between Polar Ionospheric Heating and the Neutral Density Response"
<p>These files provide supplemental data to accompany the paper "Global Variations in the Time Delays Between Polar Ionospheric Heating and the Neutral Density Response" submitted to AGU journal <em>Space Weather</em>, with manuscript number 2022SW003410. Details are provided in the file <strong>ReadMe_DataArchive.pdf</strong>.<br> </p>
Dataset of Machine Learning forecasted VTEC from paper: Uncertainty Quantification for Machine Learning-based Ionosphere and Space Weather Forecasting
<p>The *csv files contain forecasted one-day-ahead Vertical Total Electron Content (VTEC), consisting of the mean/median VTEC values and the upper and lower VTEC bounds of the 95% confidence intervals of 4 models based on machine learning for test data.</p> <p>The first part of the *csv file name corresponds to the type of model: SE stands for the super-ensemble VTEC model, QGB stands for the quantile gradient boosting VTEC model, BNN1 stands for the Bayesian neural network VTEC model, and BNN2 stands for the Bayesian neural network with negative log-likelihood (NLL) loss VTEC model. The second part of the file name refers to the geographic location of the VTEC points for which the forecast is performed, i.e., 10E70N for 10 degree of longitude and 70 degree of latitude, 10E40N for 10 degree of longitude and 40 degree of latitude, and 10E10N for 10 degree of longitude and 10 degree of latitude. The last part of the file name corresponds to the test year, i.e., year 2017.</p> <p>The SE_*_2017.csv file consists of 14 columns. The index column ("Date-time") is expressed in Coordinated Universal Time (UTC) as YYYY-MM-DD. Columns 1-3 contain the VTEC forecast results of Random Forest (RF) trained on three data subsets; columns 4-6 contain the VTEC forecast results of Adaptive Boosting (AB) trained on three data subsets; columns 7-9 contain the VTEC forecast results of Gradient Boosting (XGBoost) trained on three data subsets. Column 10 ("Mean") represents the mean of columns 1-9, i.e., the ensemble mean; column 11 ("Std") represents the standard deviation of columns 1-9, i.e., the ensemble spread; columns 12 ("UB") and 13 ("LB") contain the upper and lower bounds of the 95% confidence interval of VTEC, respectively; and column 14 contains the Global Ionosphere Maps (GIM) values of CODE, i.e., the ground-truth in this study.</p> <p>The QGB_*_2017.csv file consists of 4 columns. The index column ("Date-time") is expressed in UTC as YYYY-MM-DD. Column 1 ("Median") contains the median VTEC forecast, column 2 ("LB") contains the lower VTEC bound of the 95% confidence interval, column 3 ("UB") contains the upper VTEC bound of the 95% confidence interval, and column 4 contains the GIM values of CODE, i.e., the ground-truth in this study.</p> <p>The BNN*_2017.csv file consists of 5 columns. The index column ("Date-time") is expressed in UTC as YYYY-MM-DD. Column 1 ("Mean") contains the mean VTEC forecast, column 2 ("Std") contains the standard deviation, column 3 contains GIM values of CODE, i.e., ground-truth in this study; column 4 ("UB") contains the upper VTEC bound of the 95% confidence interval, and column 5 ("LB") contains the lower VTEC bound of the 95% confidence interval.</p> <p>----------------------------------------------------------------------------------------------------------------------------------------</p> <p>Contact</p> <p>----------------------------------------------------------------------------------------------------------------------------------------</p> <p>If you have any questions regarding these data, please contact:</p> <p>Randa Natras</p> <p>Deutsches Geodätisches Forschungsinstitut (DGFI-TUM)</p> <p>Technical University of Munich</p> <p>Arcisstraße 21</p> <p>80333 München</p> <p>randa.natras@tum.de</p>
Hubei STEC Data through CORS stations for DOY 059 and 061 of the year 2018 which used in (Using Real GNSS Data for Ionospheric Disturbance Remote Sensing Associated with Strong Thunderstorm over Wuhan City, manuscript submitted to Earth and Space Science Journal AGU)
<p>Manuscript submitted to Earth and Space Science AGU entitled with <br> (Using Real GNSS Data for Ionospheric Disturbance Remote Sensing Associated with Strong Thunderstorm over Wuhan City)<br> by: Mohamed Freeshah, Xiaohong Zhang, Xiaodong Ren, Jun Chen, and Zhibo Zhao</p> <p>The STEC data inside two compressed folders named as stec059 and stec061, respectively.<br> The STEC file name has the CORS station name for the first forth letters and next three numbers epresent the Day of the year.<br> For example:<br> ES010590.18STEC<br> ES01 is the station name<br> 059 is the day of year (DOY), 2018</p>
Data used in "Quiet night Arctic ionospheric D region characteristics"
<p>Data used in 'Quiet night Arctic ionospheric D region characteristics', as zipped text files</p>
Electron density and altitude of the main ionospheric peak of Mars as observed by Mars Express instruments. Archived data for the paper "Seasonal and geographical variability of the Martian ionosphere from Mars Express observations", submitted to JGR-Planets
<p>This repository contains archived data for the manuscript "Seasonal and geographical variability of the Martian ionosphere from Mars Express observations", published in Journal of Geophysical Research-Planets. Details about the methods to generate the data can be found in the paper.</p> <p>5 data files plus 2 readme text files are included.</p> <p>The file MEx_ionpeak.dat (described in the readme file README_ionpeak.txt) contains the peak electron densities and peak altitudes resulting from 34539 observations. Each record includes 14 columns. The content of each column is:</p> <p>Column 1: Instrument providing the observation (MARSIS or MaRS)<br> Column 2: Mars Year at which the observation was obtained (from MY27 to MY33)<br> Column 3: Solar Longitude (Ls) of the observation (unit: degrees)<br> Column 4: Latitude of the observation (unit: degrees)<br> Column 5: Longitude of the observation (unit: degrees)<br> Column 6: Solar Zenith Angle (SZA) of the observation (unit: degrees)<br> Column 7: F10.7 solar proxy index at 1 Astronomic Unit (unit: solar flux units)<br> Column 8: Peak electron density measured by the instrument (unit: cm-3)<br> Column 9: Peak electron density at the subsolar point, i.e., corrected for the SZA variation (unit: cm-3)<br> Column 10: Peak electron density at the subsolar point and at F10.7 (1AU)=100, i.e., corrected for the SZA and the solar radiation output variations (unit: cm-3)<br> Column 11: Peak electron density at the subsolar point, at F10.7 (1AU)=100 and corrected for the seasonal variation (unit: cm-3)<br> Column 12: Peak altitude measured by the instrument (unit: km)<br> Column 13: Peak altitude at the subsolar point, i.e. corrected for the SZA variation (unit: km)<br> Column 14: Peak altitude at the subsolar point and corrected for the seasonal variation (unit: km)</p> <p> </p> <p>The files eprofiles_MaRS.dat, eprofiles_MARSIS_prof1.dat, eprofiles_MARSIS_prof2.dat and eprofiles_MARSIS_prof3.dat contain 4 electron density profiles. They are described in the file README_eprofiles.txt. Each file includes 2 columns, the first one being the altitude (unit: km) and the second one the electron density (unit: cm-3).</p> <p> </p> <p>Contact: Francisco Gonzalez-Galindo, ggalindo@iaa.es<br> </p>
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