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57 results for “geomagnetic storm”

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zenodo32/100

Ionospheric data during the May 2024 super geomagnetic storm

<p>The Global Navigation Satellite System (GNSS) data, low latitude long range ionospheric radar (LARID) echo, and ionosonde data from the Ionospheric observational network for irregularity and scintillation in East/Southeast Asia (IONISE), the Chinese Meridian Project (http://data.meridianproject.ac.cn), and are archived at the Geophysics Center, National Earth System Science Data Center at BNOSE, IGGCAS (http://wdc.geophys.ac.cn/). The GNSS total electron content (TEC) with sampling rate of 30s are binned into 1&deg;&times;1&deg; grids every 5 minutes to investigate the ionospheric variation during the storm. The Rate of TEC index (ROTI) are binned into 1&deg;&times;1&deg; grids every 5 minutes to investigate the ionospheric irregularities during the storm. The LARID at Dongfang are used to investigate the ionospheric variation in a wide zonal span ~3800 km or more. The LARID worked at 20.4 MHz under a beam steering mode, stepped by 5&deg;. For each beam, the radar can receive signals from the slant ranges of 60 km to 9600 km. The ionosonde ionograms obtained at Meiji, Ledong, Wuhan and Beijing with temporal resolutions of 5, 7.5, 15 and 15 min, respectively were manually scaled to get the bottomside plasma frequency profiles.</p>

opencc-by-4.0Oct 2024View details →
zenodo32/100

Observations and Modeling Investigations of Ionospheric Response to April 23-24, 2023, G4-Class Geomagnetic Storm over Indian Sector

<p>This study explores the ionospheric response over the Indian sector to the G4-class geomagnetic storm of April 23-24, 2023. Utilizing multi-instrument observations and SAMI2 modeling, ionospheric behavior was examined during the storm's main phase (17:41 UT, April 23 - 04:03 UT, April 24) and the recovery phase (04:03 UT - 22:44 UT, April 24). During the main phase, ionosonde data from Tirunelveli showed rapid F-layer height (h&rsquo;F) variations driven by westward and eastward prompt penetration electric fields (PPEFs). The westward PPEF, induced by undershielding, led to an initial decrease in h&rsquo;F followed by an increase, suppressing pre-existing Equatorial Plasma Bubbles (EPBs) within two hours of the storm&rsquo;s onset. Despite a late-night rise in h&rsquo;F due to overshielding, no new EPB formed. The recovery phase exhibited a positive storm effect at low latitudes and a negative effect at higher latitudes, linked to disturbance dynamo electric fields (DDEFs) and thermospheric composition changes (O/N₂). Isofrequency analysis of CADI ionosonde and GNSS TEC data revealed large-scale traveling ionospheric disturbances (LSTIDs) with a ~2-hour period, ~2,450 km wavelengths, and ~340 m/s equatorward propagation speed. These LSTIDs were likely driven by atmospheric gravity waves or auroral heating. The westward DDEF suppressed the equatorial ionization anomaly (EIA) and inhibited post-sunset EPBs, while eastward DDEF increased h&rsquo;F post-midnight without EPB formation. We speculate this absence might be due to a lack of seeding mechanisms. SAMI2 simulations incorporating E&times;B drift data reproduced several storm-time features in the main and recovery phases.</p>

opencc-by-4.0Nov 2024View details →
zenodo32/100

RInex files from HK GNSS network in observing simultaneous and consecutive occurrence of thunderstorm and geomagnetic storm

<p>These are the RInex files from HK GNSS network in observing simultaneous and consecutive occurrence of thunderstorm and geomagnetic storm</p>

opencc-by-4.0Dec 2022View details →
zenodo32/100

Dataset of Geomagnetic Storm Forcasting with CEEMDAN-CWT

<p>Dataset of geomagnetic storm forcasting with CEEMDAN-CWT, associated with manuscript 《A new method for predicting non-recurrent geomagnetic storms》.</p> <p>&nbsp;</p> <p><strong>Previous Work</strong></p> <p><strong>Ye, Q., Wang, C., He, F., Xue, B., &amp; Zhang, X. (2022). The frequency-domain&nbsp;characterization of Cosmic Ray Intensity&nbsp;variations before Forbush decreases&nbsp;associated with geomagnetic storms.&nbsp;Space Weather, 20, e2021SW002863.&nbsp;https://doi.org/10.1029/2021SW002863</strong></p>

opencc-by-4.0Jun 2023View details →
zenodo32/100

The variable source of the plasma sheet during a geomagnetic storm: data

<p>This dataset contains the files supporting the paper &quot;The variable source of the plasma sheet during a geomagnetic storm&quot; published in Nature Communications.&nbsp; Included are the following:</p> <p>1) LEPI-HE2 contains cdf files&nbsp;of the He++ data of the LEPI instrument in the same format as the other species files available from the ERG science center (https://ergsc.isee.nagoya-u.ac.jp/)</p> <p>2)&nbsp; WIND_SWE contains idl save sets with the results of the fits to the WIND/SWE data using two proton peaks and an alpha peak.&nbsp; The data is in the structure ppa.fits, with variable descriptions in ppa.pnames and ppa.pdesc.</p> <p>3)&nbsp; The data that is plotted in Figures 3, 4, and 6.&nbsp; These are in tplot save formats that can be read with the spedas software (<a>http://themis.ssl.berkeley.edu/software.shtml</a>).&nbsp; IDL spedas programs (.pro) to read the data files and recreate the figures are also included.</p>

opencc-by-4.0Sep 2023View details →
zenodo28/100

Data for Reconstruction of extreme geomagnetic storms: Breaking the data paucity curse

<p>This tar file contains data for 16 figures of the main paper &quot;Reconstruction of extreme geomagnetic storms: Breaking the data paucity curse&quot; and 5 figures from the Supporting Information file of this paper.&nbsp;</p>

opencc-by-4.0Jul 2020View details →
zenodo28/100

Latitude variation of the post-sunset plasma density enhancement during the minor geomagnetic storm on 27 May 2021

Open the record for dataset details and reuse information.

opencc-by-4.0Dec 2023View details →
zenodo28/100

Lidar, FPI and ionosonde data during the 05 November 2023 Geomagnetic storm

Open the record for dataset details and reuse information.

opencc-by-4.0Nov 2024View details →
zenodo28/100

TIEGCM simulations during Geomagnetic storm on December 01, 2023

<p>TIEGCM simulations</p>

opencc-by-4.0May 2024View details →
zenodo28/100

Extreme Responses of the ionospheric radial currents to the main phase of the super geomagnetic storm on 10 May 2024

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opencc-by-4.0Jul 2024View details →
zenodo28/100

East‐West Difference in the Ionospheric Response during the Recovery Phase of May 2024 Super Geomagnetic Storm over the East Asian

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opencc-by-4.0Aug 2024View details →
zenodo28/100

Diurnal UT Variation of low Latitude Geomagnetic Storms Using six Indices

<p>The&nbsp;derived parameters of the geomagnetic storms in Kyoto Dst and USGS Dst</p>

opencc-by-4.0Mar 2021View details →
zenodo28/100

Geomagnetic Induced Currents (GICs) estimations for Portugal mainland - Top 8 geomagnetic storms of solar cycle 24

<p>Geomagnetic Induced Currents, or GICs, are electric currents induced in conductive infrastructures (such as power lines and pipelines) due to changes in the Earth&#39;s magnetic field. GICs can cause power outages, damage transformers and other electrical equipment, and interfere with the operation of pipelines.</p> <p>We present here the GIC estimation for all the high voltage lines (150, 220 and 400 kV) over mainland Portugal for the eight most intense geomagnetic storms during solar cycle 24. The induced electric field is calculated from geomagnetic series obtained at Coimbra or San Fernando magnetic observatories, according to the Nearest Neighbour method and from 31 magnetotelluric soundings (https://doi.org/10.5281/zenodo.7147543).</p> <p>The GIC peak and standard deviation values for each substation are listed in the dataset. The criteria used for the definition of the geomagnetic storm duration in order to compute standard deviation values are based on the Ebre Observatory tables (https://www.obsebre.es/en/rapid) and the Hutchinson et al. (2011) criteria for the storm beginning and end, respectively.</p>

opencc-by-4.0Dec 2022View details →
zenodo24/100

Data for the paper "Impacts of soft electron precipitations on the neutral density and satellite drag during the 28-29 May 2010 geomagnetic storm"

<p>Data for the paper&nbsp;&quot;Impacts of soft electron precipitations on the neutral density and satellite drag during the 28-29 May 2010 geomagnetic storm&quot; by Qingyu Zhu, Yue Deng, Cheng Sheng, Phil Andersen and&nbsp;Aaron Bukowski</p> <p>GITM_3D.zip: GITM outputs at 12 UT, 05/29/2010 (Figure 3)</p> <p>HPs.zip: NOAA and Z2019 HP (Figure 1)</p> <p>rhos.zip: Neutral density along the GOCE orbit from observation, run1, run2, run3 and JB2008 model (Figures 2 and 4)</p>

opencc-by-4.0Jun 2020View details →
nasa24/100

Thermosphere-Ionosphere Modeling with Forecastable Inputs: Case Study of the June 2012 High Speed Stream Geomagnetic Storm

This is the companion dataset for the Journal paper ”Thermosphere-Ionosphere Modeling With Forecastable Inputs: Case Study of the June 2012 High Speed Stream Geomagnetic Storm” (under review). The dataset contains raw outputs from a global ionosphere-thermosphere model for a geomagnetic storm events. The outputs are in IDL binary format, containing the model solution of the total electron content, the magnetic field, density, velocity, and temperature for neutral and ion species. The outputs are analyzed in the paper to evaluate the forecast capability of the model.

restrictednotspecifiedMar 2025View details →
zenodo20/100

Investigation of the global Ionospheric response to 2015 geomagnetic storms using SAMI3 simulations and SWARM satellite data

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openDec 2024View details →
zenodo20/100

Dataset for 'Development of Super Plasma Bubbles during the September 7, 2017 Geomagnetic Storm Revealed by Coupled GITM-SAMI3 Simulations'

<p>This dataset includes the binary files of a simulation and the plotting programs.</p>

opencc-by-4.0Aug 2024View details →

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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.

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