2024 Space Weather Article

Report generated on 02/04/2025 13:54:02

cdaweb was referenced in 23 papers
spdf was referenced in 20 papers
space physics data facility was referenced in 36 papers
omni was referenced in 57 papers
omniweb was referenced in 63 papers
sscweb was referenced in 1 papers
iri was referenced in 30 papers
international reference ionosphere was referenced in 25 papers

113 of 188 possible papers ( 60% ) contained references to SPDF keywords

Papers:

Authors=Gao, Pengdong; Cai, Jinhui; Wang, Zheng; Qiu, Chu; Wang, Guojun; Qi, Quan; Wang, Bo; Shi, Jiankui; Wang, Xiao; Ding, Kai
Title=Prediction of Ionograms With/Without Spread-F at Hainan by a Combined Spatio-Temporal Neural Network, 2024, doi:10.1029/2023SW003727, ID=26807463
journal=Space Weather
Keywords found:iri
Sample usage ( BODY ) =They indicated that the proposed final/second NN (NN2) yielded better results than the IRI model on average by a margin of 15%-16%. Oyeyemi and McKinnell ( 2008) presented another foF2 prediction model of M(3000)F2. The designed network consisted of two hidden layers that contained 20 neurons and the response was improved compared with the IRI model. Athieno et al. ( 2017) also developed an NN model to predict foF2 values for a single station in the polar cap and compared their results with IRI2012. The Root Mean Square Error (RMSE) values between their predictions and observations demonstrated that the proposed NN model performed better than the IRI model during low solar activity and the equinoxes. As for the ionospheric event scintillation, Zhao et al. ( 2021) proposed a prediction model of day-to-day occurrence of low latitude ionospheric disturbances with scintillation S4 index from 8 GPS receivers in Brazil and the prediction accuracy was ~85%.

Authors=Jeong, Se-Heon; Lee, Woo Kyoung; Kil, Hyosub; Jang, Soojeong; Kim, Jeong-Heon; Kwak, Young-Sil
Title=Deep Learning-Based Regional Ionospheric Total Electron Content Prediction—Long Short-Term Memory (LSTM) and Convolutional LSTM Approach, 2024, doi:10.1029/2023SW003763, ID=26807474
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =For this study, the DCGAN model is trained using the International Reference Ionosphere (IRI)-2016 model (Bilitza et al., 2017) TEC data during the period of 2002-2019.

Authors=Lyu, D.; Qin, G.; Shen, Z. -N.
Title=Long-Term Variation of the Galactic Cosmic Ray Radiation Dose Rates, 2024, doi:10.1029/2023SW003804, ID=26807483
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =The solar wind speed V sw and magnetic field magnitude B are values monthly averaged near Earth using data from the OMNI website ( https://omniweb.gsfc.nasa.gov/ ). a is the computed tilt angle for the new model from the WSO. dB is the square root of the magnetic field variances (magnetic turbulence magnitude) calculated using the method described in Qin and Shen ( 2017), and due to the sharp magnitude of the calculated turbulent magnetic field variation, we smooth the calculated results for studying the long time varying GCR radiation dose.

Authors=Chen, Zhou; Wang, Kang; Li, Haimeng; Liao, Wenti; Tang, Rongxin; Wang, Jing-song; Deng, Xiaohua
Title=Storm-Time Characteristics of Ionospheric Model (MSAP) Based on Multi-Algorithm Fusion, 2024, doi:10.1029/2022SW003360, ID=26807833
journal=Space Weather
Keywords found:spdf, space physics data facility, omni, omniweb, iri, international reference ionosphere
Sample usage ( BODY ) =IGS-TEC hourly data is from the Goddard Space Flight Center ( https://spdf.gsfc.nasa.gov/pub/data/gps/tec1hr_igs ). The MSAP model is based on the data from 2011 to 2019, there are 78,888 TEC maps, and the test set is the TEC data of 2020.
Sample usage ( BODY ) =Data Availability Statement Both the IGS-TEC and the OMNI data were downloaded from the Space Physics Data Facility of Goddard Space Flight Center, their website are https://spdf.gsfc.nasa.gov/pub/data/gps/tec1hr_igs and https://omniweb.gsfc.nasa.gov/ow.html , respectively.
Sample usage ( BODY ) =The factors we take into account are storm intensity, solar activity, month, and Universal Time (UT). Based on the OMNI data from 2011 to 2019, we have selected 116 geomagnetic storm events with a length of 6 days.
Sample usage ( BODY ) =Other data are from the OMNI data set ( https://omniweb.gsfc.nasa.gov/ow.html ). IRI-2016 Model The IRI is an international project that is jointly established by the Committee on Space Research and the International Union of Radio Science (Bilitza et al., 2014).
Sample usage ( BODY ) =The IRI-2016 model is the latest version. In this paper, IRI TEC maps are calculated by the IRI-2016 model in the Python environment of Linux.
Sample usage ( ABSTRACT ) =Our validation shows the MSAP model outperforms the IRI-2016 model in predicting global TEC for the next 6 days in the test set.
Sample usage ( BODY ) =Considering that we need to use reference TEC data to reflect the stability and physical characteristics of the MSAP model, we used the International Reference Ionosphere (IRI)-2016 model, a climate model, as the reference model in this study.

Authors=Yordanova, E.; Temmer, M.; Dumbovic, M.; Scolini, C.; Paouris, E.; Werner, A. L. E.; Dimmock, A. P.; Sorriso-Valvo, L.
Title=Refined Modeling of Geoeffective Fast Halo CMEs During Solar Cycle 24, 2024, doi:10.1029/2023SW003497, ID=26807837
journal=Space Weather
Keywords found:cdaweb
Sample usage ( ACK ) =WIND data are available from Coordinated Data Analysis Web (CDAWeb). ENLIL simulation results have been provided by the Community Coordinated Modeling Center at Goddard Space Flight Center through their public Runs on Request system ( http://ccmc.gsfc.nasa.gov ).
Sample usage ( BODY ) =Data Availability Statement The WIND spacecraft data were downloaded from the Coordinated Data Analysis Web (CDAWeb) database (NASA, GSFC, 2021). The ENLIL model was run from the public Request system of the Community Coordinated Modeling Center at Goddard Space Flight Center (CCMC NASA GSFC, 2022).

Authors=Li, Xiaoyue; Valliappan, Senthamizh Pavai; Shukhobodskaia, Daria; Butala, Mark D.; Rodriguez, Luciano; Magdalenic, Jasmina; Delouille, Veronique
Title=A Transfer Learning Method to Generate Synthetic Synoptic Magnetograms, 2024, doi:10.1029/2023SW00349910.22541/essoar.168121495.53024244/v1, ID=26807839
journal=Space Weather
Keywords found:omni
Sample usage ( ACK ) =We thank all the team members of the SDO, OMNI, and PSP missions and acknowledge efforts supporting open-source solar data analysis Python packages we utilize in this work: NumPy, Matplotlib, PyTorch, sunpy, Astropy, and aiapy.
Sample usage ( BODY ) =The solid black line indicates the observations by OMNI/WIND data in plot (a) and (c) and PSP/SWEAP data in plot (b), the corresponding output of EUHFORIA are displayed in blue when using GONG magnetograms as input, and in red when using AI-synthetic magnetograms as input.

Authors=Elvidge, S.; Healy, S. B.; Culverwell, I. D.
Title=One-Dimensional Variational Ionospheric Retrieval Using Radio Occultation Bending Angles: 2. Validation, 2024, doi:10.1029/2023SW00357110.22541/essoar.168614389.93089525/v1, ID=26807849
journal=Space Weather
Keywords found:iri
Sample usage ( BODY ) =Finally, kh eff is the effective solar zenith angle given by 4 kh eff = kh + 90 - 0.24 exp 20 - 0.2 kh exp 12 kh - kh 0 1 + exp 12 kh - kh 0 , ${\chi }_{\mathit{eff}}=\frac{\chi +\left[90-0.24\,\mathrm{exp}\left(20-0.2\chi \right)\right]\cdot \mathrm{exp}\left(12\left(\chi -{\chi }_{0}\right)\right)}{1+\mathrm{exp}\left(12\left(\chi -{\chi }_{0}\right)\right)},$ where kh 0 is the zenith angle at night-day transition, 86.23 deg as given in ITU-R P.2297-1 ( 2019). hmE Across a range of models including NeQuick and the IRI hmE , the height of the E-region peak density, is usually set to a fixed height.

Authors=Enengl, F.; Spogli, L.; Kotova, D.; Jin, Y.; Oksavik, K.; Partamies, N.; Miloch, W. J.
Title=Investigation of Ionospheric Small-Scale Plasma Structures Associated With Particle Precipitation, 2024, doi:10.1029/2023SW003605, ID=26807855
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =The geomagnetic and solar wind parameters were downloaded from the NASA/GSFC’s OMNI data set through OMNIWeb (King Papitashvili, 2005). Further, all events show moderate local deflections in the horizontal magnetic field H component (over 100 nT).

Authors=Castillo, Angelica M.; Shprits, Yuri Y.; Aseev, Nikita A.; Smirnov, Artem; Drozdov, Alexander; Cervantes, Sebastian; Michaelis, Ingo; Penaranda, Marina Garcia.; Wang, Dedong
Title=Can We Intercalibrate Satellite Measurements by Means of Data Assimilation? An Attempt on LEO Satellites, 2024, doi:10.1029/2023SW003624, ID=26807857
journal=Space Weather
Keywords found:omni
Sample usage ( BODY ) =The SEM-2 MEPED instrument consists of eight particle detector systems: two proton solid-state detector telescopes (each +- 15deg wide), two electron solid-state detector telescopes (each +- 15deg wide) and four omni-directional (dome) proton detector systems. The electron/proton telescopes are mounted with different orientation in order to observe different particle populations: (a) the 0deg—telescope has the central axis of its field of view rotated 9deg in the XZ plane pointing away from the local zenith, (b) the 90deg—telescope is oriented almost perpendicular to the 0deg—telescope with the central axis of its field of view rotated 9deg in the YZ plane pointing away from the antiram direction.

Authors=Moraes, Alison; Sousasantos, Jonas; Costa, Emanoel; Pereira, Bruno Augusto; Rodrigues, Fabiano; Galera Monico, Joao. Francisco
Title=Characterization of Scintillation Events With Basis on L1 Transmissions From Geostationary SBAS Satellites, 2024, doi:10.1029/2023SW003656, ID=26807859
journal=Space Weather
Keywords found:spdf, space physics data facility, omni, omniweb
Sample usage ( BODY ) =The authors acknowledge the NASA Space Physics Data Facility staff.
Sample usage ( BODY ) =The OMNI data (F10.7) were obtained from the GSFC/SPDF OMNIWeb interface at https://omniweb.gsfc.nasa.gov .

Authors=Ellis, J. A.; Emmons, D. J.; Cohen, M. B.
Title=Detection and Classification of Sporadic E Using Convolutional Neural Networks, 2024, doi:10.1029/2023SW003669, ID=26807861
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =.$ Next, the electron density of the background E region ( N E ) is calculated from the International Reference Ionosphere model (IRI-2016) (Bilitza et al., 2017) by inputting the height (hEs) and time information associated with the foEs measurement.

Authors=Kataoka, Ryuho; Nakamizo, Aoi; Nakano, Shinya; Fujita, Shigeru
Title=Machine Learning-Based Emulator for the Physics-Based Simulation of Auroral Current System, 2024, doi:10.1029/2023SW003720, ID=26807866
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( ACK ) =Acknowledgments We acknowledge the use of NASA’s high-resolution OMNI data and the Kyoto University’s AE index data. The REPPU simulation was performed with High-Performance Computing System at NICT, which is operated with the support of “Promotion of observation and analysis of radio wave propagation,” commissioned by the Ministry of Internal Affairs and Communications, Japan.
Sample usage ( BODY ) =The real-time solar wind data can differ from the finally calibrated solar wind data, such as OMNI data set. Nevertheless, it is essentially little problem for the machine-learning model to learn the REPPU simulation results for variable input patterns.
Sample usage ( BODY ) =Data Availability Statement The OMNI solar wind data with the AE/AU/AL indices are publicly available at https://omniweb.gsfc.nasa.gov/ow_min.html . The Python 3 scikit-learn/pca is open to public (Pedregosa et al., 2011).

Authors=Shih, Chung-Yu; Lin, Cissi Ying-tsen; Lin, Shu-Yu; Yeh, Cheng-Hung; Huang, Yu-Ming; Hwang, Feng-Nan; Chang, Chia-Hui
Title=Forecasting of Global Ionosphere Maps With Multi-Day Lead Time Using Transformer-Based Neural Networks, 2024, doi:10.1029/2023SW003579, ID=27140076
journal=Space Weather
Keywords found:omniweb, iri, international reference ionosphere
Sample usage ( BODY ) =We prepared SW features, such as ap index, Kp index, Dst index (disturbance storm-time index), F10.7, and sunspot number (R), obtained from the OMNIWeb Service. Because these features have different temporal resolutions, as shown in Table 2, we use the nearest neighbor interpolation to fill the gaps between different resolutions to 1 hr.
Sample usage ( BODY ) =However, owing to the nature of the IRI model, the TEC values from it are only a partial representation, leading to a less faithful depiction of the TEC when being compared against. However, the IRI results are still valuable as it serves as a climatological reference. Examining the hour-by-hour TEC variation, we observe that the variation of IRI TEC generally follows that of our predictions with less fluctuations but similar magnitudes of change.
Sample usage ( BODY ) =Figure 7 compares the predicted TEC with the TWRR data and IRI2020 (International Reference Ionosphere) model at (25degN, 120degE), a collocating grid of GIM and TWRR maps.

Authors=Laker, R.; Horbury, T. S.; O’Brien, H.; Fauchon-Jones, E. J.; Angelini, V.; Fargette, N.; Amerstorfer, T.; Bauer, M.; Mostl, C.; Davies, E. E.; Davies, J. A.; Harrison, R.; Barnes, D.; Dumbovic, M.
Title=Using Solar Orbiter as an Upstream Solar Wind Monitor for Real Time Space Weather Predictions, 2024, doi:10.1029/2023SW00362810.48550/arXiv.2307.01083, ID=27140154
journal=Space Weather
Keywords found:space physics data facility
Sample usage ( BODY ) =Data Availability Statement The data used in this paper are available at the following places: Solar Orbiter data can be found on the Solar Orbiter archive (ESA, 2023); Wind data can be found at the Space Physics Data Facility (NASA, 2023); quick look D ST data is available from (World Data Center for Geomagnetism et al., 2015); the SYM/H data is available from (World Data Center for Geomagnetism et al., 2022) and STEREO-A HI data are available from (UK Solar System Data Centre, 2023).

Authors=Acciarini, Giacomo; Brown, Edward; Berger, Tom; Guhathakurta, Madhulika; Parr, James; Bridges, Christopher; Baydin, Atilim. Gunes
Title=Improving Thermospheric Density Predictions in Low-Earth Orbit With Machine Learning, 2024, doi:10.1029/2023SW003652, ID=27140194
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =In a similar manner, the OMNI inputs are also processed through four layers with 500, 500, 500, and 175 nodes, generating 175 additional outputted features.
Sample usage ( BODY ) =Geomagnetic inputs both in the form of measurements (from NASA’s OmniWeb data service (King Papitashvili, 2005; NASA, 2023), and indices [from Celestrack (Kelso Sean, 2010)] and Space Environment Technologies, SET (Kent, 2023)).

Authors=Zhan, Weijia; Doostan, Alireza; Sutton, Eric; Fang, Tzu-Wei
Title=Quantifying Uncertainties in the Quiet-Time Ionosphere-Thermosphere Using WAM-IPE, 2024, doi:10.1029/2023SW003665, ID=27140480
journal=Space Weather
Keywords found:cdaweb, space physics data facility, omni, omniweb
Sample usage ( ACK ) =We acknowledge use of NASA/GSFC’s Space Physics Data Facility’s OMNIWeb (or CDAWeb or ftp) service, and OMNI data.
Sample usage ( BODY ) =Drivers and Their Data-Driven Uncertainty Representation To create the solar wind drivers using MCVAE, 5-min time resolution solar wind measurements during 1981-2021 were obtained from NASA OMNIWeb ( https://omniweb.gsfc.nasa.gov/ ). The parameters, including solar wind proton density, speed, and IMF Bz, that are used to drive WAM-IPE are selected.

Authors=Li, Minjing; Deng, Yue; Harding, Brian J.; England, Scott
Title=Climatology of Dayside E-Region Zonal Neutral Wind Shears From ICON-MIGHTI Observations, 2024, doi:10.1029/2023SW003670, ID=27140492
journal=Space Weather
Sample usage ( BODY ) =All data are available on the ICON Data Products website ( ftp://icon-science.ssl.berkeley.edu/pub/LEVEL.2/ ) and NASA’s Space Physics Data Facility ( https://spdf.gsfc.nasa.gov/pub/data/icon/ ). Wind data within the altitude range of approximately 91-132 km, where large shears primarily occur, have been selected for this study.

Authors=Li, Shaoyang; Ren, Zhipeng; Yu, Tingting; Chen, Guangming; Li, Guozhu; Zhao, Biqiang; Yue, Xinan; Wei, Yong
Title=The Daytime Variations of Thermospheric Temperature and Neutral Density Over Beijing During Minor Geomagnetic Storm on 3-4 February 2022, 2024, doi:10.1029/2023SW003677, ID=27140511
journal=Space Weather
Keywords found:space physics data facility
Sample usage ( BODY ) =These indices are available at the Space Physics Data Facility website ( https://stereo-ssc.nascom.nasa.gov/ ). Methodology Neglecting transport of ionization, the lower daytime ionosphere below ~200 km (D, E, and F 1 layers) is in photochemical equilibrium and is thought to be in a quasi-stationary condition (Rishbeth Garriott, 1969).

Authors=Billett, D. D.; Sartipzadeh, K.; Ivarsen, M. F.; Iorfida, E.; Doornbos, E.; Kalafatoglu Eyiguler, E. C.; Pandey, K.; McWilliams, K. A.
Title=The 2022 Starlink Geomagnetic Storms: Global Thermospheric Response to a High-Latitude Ionospheric Driver, 2024, doi:10.1029/2023SW003748, ID=27140540
journal=Space Weather
Keywords found:omniweb
Sample usage ( BODY ) =The top panel shows the 1-min geomagnetic SYM-H index, obtained from NASAs OMNIWeb service, whilst panels (a) and (b) show the thermospheric neutral densities measured by GRACE-FO and Swarm C, respectively.

Authors=Fu, Zhiyi; Su, Zhenpeng; Miao, Bin; Wu, Zhiyong; Li, Yiren; Liu, Kai; Shan, Xu; Wang, Yuming
Title=A Substorm-Dependent Negative Limit of Non-Eclipse Surface Charging of a Chinese Geosynchronous Satellite, 2024, doi:10.1029/2023SW003780, ID=27140553
journal=Space Weather
Keywords found:spdf, space physics data facility
Sample usage ( BODY ) =Van Allen Probes data are available at NASA’s Space Physics Data Facility (SPDF) Website ( 2023). We have analyzed the following Van Allen Probes data: HOPE electron flux data (Funsten, 2022) and MagEIS electron flux data (Spence et al., 2022).

Authors=Aa, Ercha; Zhang, Shun-Rong; Erickson, Philip J.; Wang, Wenbin; Coster, Anthea J.; Rideout, William
Title=3-D Ionospheric Imaging Over the South American Region With a New TEC-Based Ionospheric Data Assimilation System (TIDAS-SA), 2024, doi:10.1029/2023SW003792, ID=27140561
journal=Space Weather
Keywords found:cdaweb, space physics data facility, iri, international reference ionosphere
Sample usage ( BODY ) =The solar and geophysical parameters data is acquired from NASA’s Space Physics Data Facility/Coordinated Data Analysis Web service ( https://cdaweb.gsfc.nasa.gov/ ) and Kyoto world data center for Geomagnetism ( http://wdc.kugi.kyoto-u.ac.jp/ ).
Sample usage ( BODY ) =Furthermore, empirical ionospheric models, such as the International Reference Ionosphere (IRI, Bilitza, 2001; Bilitza et al., 2017) and the NeQuick model (Nava et al., 2008; Radicella, 2009), have also been extensively employed in the development of ionospheric data assimilation systems.

Authors=Abduallah, Yasser; Alobaid, Khalid A.; Wang, Jason T. L.; Wang, Haimin; Jordanova, Vania K.; Yurchyshyn, Vasyl; Cavus, Huseyin; Jing, Ju
Title=Prediction of the SYM-H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification, 2024, doi:10.1029/2023SW00382410.48550/arXiv.2402.17196, ID=27140586
journal=Space Weather
Keywords found:cdaweb, space physics data facility, omni, omniweb
Sample usage ( ACK ) =We acknowledge the use of NASA/GSFC’s Space Physics Data Facility’s OMNIWeb and CDAWeb services, and OMNI data. This work was supported in part by U.S.
Sample usage ( BODY ) =Data Availability Statement The solar wind, IMF and derived parameters along with the SYM-H index data used in our study are publicly available from NASA’s Space Physics Data Facility at http://omniweb.gsfc.nasa.gov/ow.html . Details of SYMHnet can be found at https://doi.org/10.5281/zenodo.10602518 .

Authors=Tyska, J.; Deng, Y.; Zhang, S.; Lin, C. Y.
Title=Ionospheric Disturbances Generated by the 2015 Calbuco Eruption: Comparison of GITM-R Simulations and GNSS Observations, 2024, doi:10.1029/2023SW003502, ID=27140944
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =Although the domain of interest for this simulation is in the mid-latitudes, the relative magnitude of ionospheric perturbations is highly dependent on the background electron density distribution, therefore the IMF and solar wind conditions from OMNI-web are utilized to drive GITM-R run for ~8 hr prior to the addition of a volcanic perturbation, to better specify the background state.

Authors=Brandt, Daniel A.; Vega, Erick F.; Ridley, Aaron J.
Title=On Generalized Additive Models for Representation of Solar EUV Irradiance, 2024, doi:10.1029/2023SW003680, ID=27499796
journal=Space Weather
Keywords found:omniweb
Sample usage ( BODY ) =The selected indices were obtained from the NASA OMNIWeb Data Explorer (Papitashvili King, 2020). We used cubic smoothing splines to interpolate over gaps in the OMNIWeb solar index data, using the Python CSAPS package (De Boor De Boor, 1978). The FISM2, Level 3 TIMED/SEE, and Level 3 SDO/EVE irradiances were obtained from the LASP Interactive Solar Irradiance Datacenter (LASP, 2005) and we used nearest-neighbor interpolation to upsample them from their native daily resolution to the hourly resolution of the OMNIWeb solar indices. Additionally, the FISM2 and TIMED/SEE irradiances were arranged into 59 wavelength bins used by GITM for ease of comparison and for eventual ingestion into GITM (see Table 1 below).

Authors=Aa, Ercha; Zhang, Shun-Rong; Zou, Shasha; Wang, Wenbin; Wang, Zihan; Cai, Xuguang; Erickson, Philip J.; Coster, Anthea J.
Title=Significant Midlatitude Bubble-Like Ionospheric Super-Depletion Structure (BLISS) and Dynamic Variation of Storm-Enhanced Density Plume During the 23 April 2023 Geomagnetic Storm, 2024, doi:10.1029/2023SW003704, ID=27499798
journal=Space Weather
Keywords found:cdaweb, space physics data facility, omniweb
Sample usage ( BODY ) =The solar wind and geophysical parameters data are acquired from NASA/GSFC’s Space Physics Data Facility’s OMNIWeb service ( 2023) ( https://cdaweb.gsfc.nasa.gov/ ) and Kyoto world data center for Geomagnetism ( 2023) ( http://wdc.kugi.kyoto-u.ac.jp/ ).

Authors=Oyama, S.; Vanhamaki, H.; Cai, L.; Shinbori, A.; Hosokawa, K.; Sakanoi, T.; Shiokawa, K.; Aikio, A.; Virtanen, I. I.; Ogawa, Y.; Miyoshi, Y.; Kurita, S.; Nishitani, N.
Title=Thermospheric Wind Response to March 2023 Storm: Largest Wind Ever Observed With a Fabry-Perot Interferometer in Tromso, Norway Since 2009, 2024, doi:10.1029/2023SW003728, ID=27499799
journal=Space Weather
Keywords found:omni
Sample usage ( BODY ) =Solar Wind, Ionosphere, and Aurora Measurements Sym-H index and solar wind parameters such as the flow speed, density, and IMF Y-Z plane in the geocentric solar magnetospheric (GSM) coordinates were collected from the spacecraft-interspersed, 1-min averaged near-Earth solar wind (OMNI) magnetic field and plasma parameters (Papitashvili King, 2020).

Authors=Li, Liangchao; Liu, Haijun; Le, Huijun; Yuan, Jing; Wang, Haoran; Chen, Yi; Shan, Weifeng; Ma, Li; Cui, Chunjie
Title=ED-AttConvLSTM: An Ionospheric TEC Map Prediction Model Using Adaptive Weighted Spatiotemporal Features, 2024, doi:10.1029/2023SW003740, ID=27499800
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =Wen et al. ( 2021) LSTM The LSTM model outperformed BP and IRI-2016 in low solar activity years and magnetic storm at the BJFS station.
Sample usage ( ABSTRACT ) =We compared our ED-AttConvLSTM with IRI-2016, COPG, LSTM, GRU, ED-ConvLSTM and ED-ConvGRU. The results indicate that our model surpasses the comparison models in forecasting both high and low solar activity years, across most months and UT moments in a day.
Sample usage ( BODY ) =For example, ionospheric empirical models are widely used for TEC prediction, including the International Reference Ionosphere (Bilitza, 1986, 2001; Bilitza et al., 2017), NeQuick model (Hochegger et al., 2000; Nava et al., 2008), Bent model (Bent et al., 1975), etc.

Authors=Seba, Ephrem Beshir; Lapenta, Giovanni
Title=Modeling Equatorial to Mid-Latitudinal Global Night Time Ionospheric Plasma Irregularities Using Machine Learning, 2024, doi:10.1029/2023SW003754, ID=27499803
journal=Space Weather
Keywords found:omniweb
Sample usage ( ACK ) =We would also like to extend our gratitude to NASA OMNIWeb website for providing space weather data freely online. The first author also acknowledges the financial research support from SSGI.
Sample usage ( BODY ) =Space weather data including F10.7, sunspot number R, Dst, Kp, interplanetary electric field Ey, and Bz data are obtained from https://omniweb.gsfc.nasa.gov/form/dx1.html . Zonal and meridional wind data are obtained from the latest HWM14 from Matlab software.
Sample usage ( ABSTRACT ) =We utilize Random Forest (RF) and a one-dimensional Convolutional Neural Network (1D-CNN) model, incorporating data from the Swarm A, B, and C satellites, space weather data from the OMNIWeb data center, as well as zonal and meridional wind model data.

Authors=Zhou, Yang; Liu, Jing; Li, Shuhan; Li, Qiaoling
Title=Ionospheric TEC Prediction Based on Ensemble Learning Models, 2024, doi:10.1029/2023SW003790, ID=27499808
journal=Space Weather
Keywords found:cdaweb, space physics data facility, omni, iri, international reference ionosphere
Sample usage ( ACK ) =We acknowledge the use of NASA/GSFC’s Space Physics Data Facility’s OMNI Web (or CDAWeb or ftp) service and OMNI data, providers of OMNI data namely: Belgium SILSO Center, GFZ Potsdam, World Data Center for Geomagnetism Kyoto, as well as Center for Orbit Determination in Europe (CODE) of the University of Bern for the GIM data.
Sample usage ( BODY ) =As early as the last century and the beginning of this century, the Klobuchar model (Klobuchar, 1987), International Reference Ionosphere (IRI) and NeQuick models (Bilitza et al., 2011; Bilitza Reinisch, 2008; Rawer et al., 1978) were used in single-frequency high-precision positioning.

Authors=Hysell, D. L.; Kirchman, A.; Harding, B. J.; Heelis, R. A.; England, S. L.; Frey, H. U.; Mende, S. B.
Title=Using ICON Satellite Data to Forecast Equatorial Ionospheric Instability Throughout 2022, 2024, doi:10.1029/2023SW003817, ID=27499824
journal=Space Weather
Keywords found:iri
Sample usage ( BODY ) =Several empirical models are used to populate the related transport equations including NRLMSIS 2.0 for neutral atmospheric parameter specification, IRI-2016 for initial ion composition, and HWM14 for neutral winds (Bilitza et al., 2016; Drob et al., 2015; Emmert et al., 2021).

Authors=Nigusie, Ayanew; Tebabal, Ambelu; Galas, Roman
Title=Modeling Ionospheric TEC Using Gradient Boosting Based and Stacking Machine Learning Techniques, 2024, doi:10.1029/2023SW003821, ID=27499827
journal=Space Weather
Keywords found:space physics data facility, omniweb, iri, international reference ionosphere
Sample usage ( BODY ) =The data for the input variables sunspot number, F10.7, ap index, Dst index, SW speed, and IMF Bz were downloaded from https://omniweb.gsfc.nasa.gov . The IRI 2020 model TEC data is available at https://kauai.ccmc.gsfc.nasa.gov/instantrun/**iri**/ .
Sample usage ( BODY ) =Table 3 is a summary of the R, RMSE, MAE, and s values computed using GPS VTEC and modeled VTEC for both the ML models (from 4 algorithms) and the IRI 2020 model. The RMSE, MAE, and s values for ML models are considerably smaller than those obtained from the IRI 2020 global model, indicating superior performance.
Sample usage ( ABSTRACT ) =The predicted VTEC values of the four ML models were strongly correlated with the GPS VTEC, with a correlation coefficient of ~0.96, which is significantly higher than the corresponding value of the International Reference Ionosphere (IRI 2020) model, which is 0.87. Comparing the GPS VTEC values with the predicted VTEC values based on diurnal and seasonal characteristics showed that the predictions of the developed models were generally in good agreement and outperformed the IRI 2020 model.
Sample usage ( BODY ) =This led to the development of global ionospheric models like NeQuick (Hochegger et al., 2000; Nava et al., 2008) and International Reference Ionosphere (IRI) models (Bilitza, 2001; Bilitza et al., 2011, 2017).

Authors=Hu, Jingle; Xiang, Zheng; Ma, Xin; Liu, Yangxizi; Dong, Junhu; Guo, Deyu; Ni, Binbin
Title=Long-Term Variations of Energetic Electrons Scattered by Signals From the North West Cape Transmitter, 2024, doi:10.1029/2023SW003827, ID=27499832
journal=Space Weather
Keywords found:omniweb
Sample usage ( BODY ) =The geomagnetic indexes are obtained from https://omniweb.gsfc.nasa.gov .

Authors=Collado-Villaverde, Armando; Munoz, Pablo; Cid, Consuelo
Title=A Framework for Evaluating Geomagnetic Indices Forecasting Models, 2024, doi:10.1029/2024SW003868, ID=27499834
journal=Space Weather
Keywords found:cdaweb, space physics data facility, omni
Sample usage ( BODY ) =This means that studies in this field are typically constrained to the period after February 1998, marking the earliest science ready data from the ACE’s mission in NASA’s Coordinated Data Analysis Web (CDAWeb). Subsequent to Siciliano et al. ( 2020), there has been a consistent practice of using the same selection of geomagnetic storms for model training, validation and testing for the SYM-H index.
Sample usage ( BODY ) =Data Availability Statement The ACE level 2 data, preliminary parameters and the SYM-H index used for in this study is available through NASA’s Space Physics Data Facility Coordinated Data Analysis Web (CDAWeb) https://cdaweb.gsfc.nasa.gov/index.html .
Sample usage ( BODY ) =Both indices are retrieved form the OMNI_HRO_5 with a 5-min resolution. The input features are grouped into 5 min averages to match the indices resolution.

Authors=Gowtam, V. Sai; Connor, Hyunju; Kunduri, Bharat S. R.; Raeder, Joachim; Laundal, Karl M.; Tulasi Ram, S.; Ozturk, Dogacan S.; Hampton, Donald; Chakraborty, Shibaji; Owolabi, Charles; Keesee, Amy
Title=Calculating the High-Latitude Ionospheric Electrodynamics Using a Machine Learning-Based Field-Aligned Current Model, 2024, doi:10.1029/2023SW003683, ID=27837867
journal=Space Weather
Keywords found:space physics data facility, omni, omniweb
Sample usage ( ACK ) =The authors acknowledge use of NASA/GSFC’s Space Physics Data Facility’s OMNIWeb service, and OMNI data ( https://omniweb.gsfc.nasa.gov/form/omni_min.html ).
Sample usage ( BODY ) =The IMF, solar wind, and geomagnetic indices data are available from the NASA Space Physics Data Facility OMNIWeb data server (OMNIWeb, 2024). The CNN-FAC model is available in Kunduri ( 2020).
Sample usage ( BODY ) =Solar wind/Interplanetary Magnetic Field conditions are shown with dashed vertical line in Figure 3. 3 Figure (a) IMF B y and B z , (b) solar wind velocity Vx in the Geocentric Solar Magnetospheric coordinates, and (c) number density obtained from the NASA OMNI data during 14 May 2013. The bottom panel shows the cross polar cap potential drop (Ph PC ) of the northern hemisphere predicted by the ML-AIM (blue), Weimer ( 2005) (green), and SuperDARN potential models (orange).

Authors=Walker, Simon James; Laundal, Karl Magnus; Reistad, Jone Peter; Ohma, Anders; Hatch, Spencer Mark; Chisham, Gareth; Decotte, Margot
Title=A Comparison of Auroral Oval Proxies With the Boundaries of the Auroral Electrojets, 2024, doi:10.1029/2023SW003689, ID=27837868
journal=Space Weather
Keywords found:omni
Sample usage ( BODY ) =This quantity is calculated using solar wind and IMF measurements from the NASA OMNI database at one-minute resolution (King Papitashvili, 2005). e N can range from 0 to over 160 and is highly correlated with the auroral electrojet geomagnetic index.

Authors=Baruah, Yoshita; Roy, Souvik; Sinha, Suvadip; Palmerio, Erika; Pal, Sanchita; Oliveira, Denny M.; Nandy, Dibyendu
Title=The Loss of Starlink Satellites in February 2022: How Moderate Geomagnetic Storms Can Adversely Affect Assets in Low-Earth Orbit, 2024, doi:10.1029/2023SW003716, ID=27837869
journal=Space Weather
Keywords found:cdaweb, omni
Sample usage ( BODY ) =The solar wind in-situ data from 1 February to 6 February 2022 are provided by the Wind (Koval Szabo, 2021) and ACE spacecraft (Smith Ness, 2022), and geomagnetic indices are provided by the WDC Kyoto (Nose et al., 2015) and NOAA’s NCEI via OMNI (King Papitashvili, 2005), all accessible at NASA’s CDAWeb. We have used the SunPy (SunPy Community et al., 2020) package for analysis of data and the JHelioviewer (Muller et al., 2017) software for visualization of solar data.

Authors=Forsythe, Victoriya V.; Bilitza, Dieter; Burrell, Angeline G.; Dymond, Kenneth F.; Fritz, Bruce A.; McDonald, Sarah E.
Title=PyIRI: Whole-Globe Approach to the International Reference Ionosphere Modeling Implemented in Python, 2024, doi:10.1029/2023SW003739, ID=27837870
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( ACK ) =This work is sponsored by the Office of Naval Research. The IRI homepage at http://irimodel.org provides open access to the FORTRAN model code of all major version of the model, to online computations of IRI parameters, and to information about IRI members, workshops, and publications. The online IRI run was completed using CCMC Instant Run System at https://kauai.ccmc.gsfc.nasa.gov/instantrun/**iri**/ .
Sample usage ( BODY ) =A recent review paper by Bilitza et al. ( 2022) describes the current state of the IRI model, its history, and recent developments. It is important to mention that there are several Python IRI wrappers and interfaces, for example, iri2016 (Ilma, 2017). However, they merely wrap the original FORTRAN IRI code to make its execution more convenient for Python users. This work, for the first time, introduces a novel software package that redefines the core of the IRI fully in the Python language.
Sample usage ( ABSTRACT ) =The International Reference Ionosphere (IRI) model is widely used in the ionospheric community and considered the gold standard for empirical ionospheric models.
Sample usage ( BODY ) =Therefore, in order to establish the high frequency (HF) communication link between any two positions it is crucial to know the amount of the electrons along the signal path. The International Reference Ionosphere (IRI) empirical model estimates the electron density in the ionosphere based on a statistical analysis of ionospheric climatology over 4 years.
Sample usage ( TITLE ) =PyIRI: Whole-Globe Approach to the International Reference Ionosphere Modeling Implemented in Python

Authors=Al Shidi, Q.; Pulkkinen, T. I.; Welling, D.; Toth, G.
Title=Accuracy of Global Geospace Simulations: Influence of Solar Wind Monitor Location and Solar Wind Driving, 2024, doi:10.1029/2023SW003747, ID=27837871
journal=Space Weather
Keywords found:cdaweb, spdf, space physics data facility, omni, omniweb
Sample usage ( BODY ) =We acknowledge use of NASA/GSFC’s Space Physics Data Facility’s OMNIWeb (or CDAWeb or ftp) service, and OMNI data (N. E. Papitashvili King, 2020).
Sample usage ( BODY ) =Therefore, we use the separate propagated WIND measurements provided by NASA Space Physics Data Facility (SPDF) to collate missing parameters such as the phase front normal with the outputs.
Sample usage ( BODY ) =Simulation Inputs The storms were simulated with the SWMF Geospace model using the OMNI solar wind and interplanetary magnetic field (IMF) observations.

Authors=Vandegriff, Erik M.; Welling, Daniel T.; Mukhopadhyay, Agnit; Dimmock, Andrew P.; Morley, Steven K.; Lopez, Ramon E.
Title=Exploring Localized Geomagnetic Disturbances in Global MHD: Physics and Numerics, 2024, doi:10.1029/2023SW003799, ID=27837874
journal=Space Weather
Keywords found:space physics data facility, omni, omniweb
Sample usage ( BODY ) =We acknowledge use of NASA/GSFC’s Space Physics Data Facility’s OMNIWeb service, and OMNI data (King Papitashvili, 2020).
Sample usage ( BODY ) =Figure 1 shows the upstream solar wind conditions taken from OMNI that we use as the inputs to the SWMF for the 6-8 September 2017 event, which is a relevant storm that has been examined by previous studies for its significance to GICs (Dimmock et al., 2019, 2021; Piersanti et al., 2019).

Authors=Ma, Jiayu; Fu, Haiyang; Huba, J. D.; Jin, Yaqiu
Title=A Novel Ionospheric Inversion Model: PINN-SAMI3 (Physics Informed Neural Network Based on SAMI3), 2024, doi:10.1029/2023SW003823, ID=27837878
journal=Space Weather
Keywords found:spdf, space physics data facility, omni
Sample usage ( BODY ) =The solar activity data (OMNI) are obtained from Goddard Space Flight Center (GSFC)/Space Physics Data Facility (SPDF) ( https://spdf.gsfc.nasa.gov/pub/data/omni/ ).
Sample usage ( BODY ) =The F10.7, Ap and Kp data are obtained from Helmholtz Centre Potsdam ( https://kp.gfz-potsdam.de/en/data ). The solar activity data (OMNI) are obtained from Goddard Space Flight Center (GSFC)/Space Physics Data Facility (SPDF) ( https://spdf.gsfc.nasa.gov/pub/data/omni/ ).

Authors=Huang, Fuqing; Ruan, Haibing; Lei, Jiuhou; Zhong, Jiahao; Yue, Xinan; Li, Guozhu; Chen, Yiding; He, Jianhui; Li, Na; Luan, Xiaoli; Xiong, Chao; Dou, Xiankang
Title=Empirical Models of foF2 and hmF2 Reconstituted by Global Ionosonde and Reanalysis Data and COSMIC Observations, 2024, doi:10.1029/2023SW003848, ID=27837879
journal=Space Weather
Keywords found:omniweb, iri, international reference ionosphere
Sample usage ( BODY ) =Data Availability Statement We acknowledge OMNIWeb ( https://omniweb.gsfc.nasa.gov/ ) for Ap and F107 data; and the ASWFC ( https://www.sws.bom.gov.au/World\_Data\_Centre ) ( https://wdc.nict.go.jp/IONO/wdc/index.html ), and IONISE network from the Beijing National Observatory of the Space Environment, Institute of Geology and Geophysics, and CAS through the Geophysics Center, National Earth System Science Data Center ( http://wdc.geophys.ac.cn ) for ionosonde data.
Sample usage ( BODY ) =It should be noted that the CCIR predictions from IRI-2016 used in this study are the latest because the next version (IRI-2020) does not update the CCIR models of foF2 and hmF2.
Sample usage ( ABSTRACT ) =The derived empirical models (referred to as the USTC models within this study) are specified through global ionosonde and reanalysis data based on the International Reference Ionosphere (IRI) Consultative Committee on International Radio (CCIR) method and Constellation Observindg System for Meteorology, Ionosphere, and Climate (COSMIC) observations based on the empirical orthogonal function analysis, respectively. The USTC models are validated against the IRI CCIR model prediction. The comparison results revealed that the empirical foF2 model performs better in capturing the foF2 variations than the IRI CCIR model, which can overcome the underestimation of the IRI CCIR model at low latitudes. Although the IRI CCIR model overestimation at middle latitudes is addressed by the empirical hmF2 model, the visible differences between the model predictions and ionosonde observations still exist at low latitudes, which could be attributed to the significant difference between COSMIC and ionosonde hmF2 measures.
Sample usage ( BODY ) =Here only a few relevant empirical models are listed, and no attempt is made to provide a complete compilation of references. The International Reference Ionosphere (IRI) model is the most widely used ionospheric model, which provides several options for the foF2 and hmF2 parameters (Bilitza et al., 2022).

Authors=Tacza, J.; Li, G.; Raulin, J. -P.
Title=Effects of Forbush Decreases on the Global Electric Circuit, 2024, doi:10.1029/2023SW003852, ID=27837880
journal=Space Weather
Keywords found:omniweb
Sample usage ( BODY ) =Data Availability Statement Solar and geomagnetic indexes (IMF, Bz, solar wind speed, Dst, and Kp indexes) are publicly available from https://omniweb.gsfc.nasa.gov/form/dx1.html . Neutron monitor data are publicly available from https://www.nmdb.eu/nest/ .

Authors=Park, Jong-Sun; Shi, Quan Qi; Troshichev, Oleg A.; Kim, Khan-Hyuk; Shue, Jih-Hong; Pitkanen, Timo; Zhang, Hui
Title=Statistical Features of Polar Cap North and South Indices in Response to Interplanetary and Terrestrial Conditions: A Revisit, 2024, doi:10.1029/2024SW003856, ID=27837882
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =The near-Earth interplanetary data used in this study are the time-shifted (from a solar wind monitor to the Earth’s bow shock nose) IMF data in GSM coordinates provided by the OMNI database (King Papitashvili, 2005). In this study, we consider the time delay of the merging electric field to be transferred from the nominal bow shock nose to the polar caps (i.e., the time lag of ionospheric electric field-associated ground magnetic perturbations in response to E KL ) by shifting the OMNI IMF data in time to +20 min (O. Troshichev Janzhura, 2012a). The time-shifted 1-min OMNI data are also resampled to 1-hr cadence using boxcar averages. In other words, we take 1-hr boxcar averages starting at each hour (e.g., 01:00-02:00 UT) for the PC indices and starting 20 min prior to the corresponding time (e.g., 00:40-01:40 UT) for the IMF data.
Sample usage ( BODY ) =Data Availability Statement OMNI IMF data are available at https://omniweb.gsfc.nasa.gov/ . PC indices were obtained from https://pcindex.org/ .

Authors=Hu, Jiahui; Lopez Rubio, Aurora; Chartier, Alex; McDonald, Sarah; Datta-Barua, Seebany
Title=Quantification of Representation Error in the Neutral Winds and Ion Drifts Using Data Assimilation, 2024, doi:10.1029/2023SW003609, ID=29028992
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =Pignalberi et al. ( 2019) also ingest global TEC measurements to update the background model International Reference Ionosphere (IRI). Galkin et al. ( 2012) developed IRI Real-Time Assimilative Mapping (IRTAM), which also updates IRI in real time but by ingesting Global Ionospheric Radio Observatory (GIRO) data.

Authors=Li, Ke; Zhang, Donghe; Zeng, Yi; Tian, Yaoyu; Dai, Guofeng; Liu, Zhizhao; Yang, Guanglin; Sun, Shuji; Li, Guozhu; Hao, Yongqiang; Xiao, Zuo
Title=Revisiting the Ionospheric Disturbances Over Low Latitude Region of China During Super Typhoon Hato, 2024, doi:10.1029/2023SW003694, ID=29029005
journal=Space Weather
Keywords found:omniweb
Sample usage ( BODY ) =The solar and geomagnetic indices, such as Dst index, were downloaded from https://omniweb.gsfc.nasa.gov and https://wdc.kugi.kyoto-u.ac.jp . GNSS TEC data in hdf5 format was derived from the GNSS observations raw data provided by Crustal Movement Observation Network of China (CMONOC) ( https://opendata.pku.edu.cn/dataverse/HatoGNSSTEC ).

Authors=Maharana, Anwesha; Cramer, W. Douglas; Samara, Evangelia; Scolini, Camilla; Raeder, Joachim; Poedts, Stefaan
Title=Employing the Coupled EUHFORIA-OpenGGCM Model to Predict CME Geoeffectiveness, 2024, doi:10.1029/2023SW00371510.48550/arXiv.2403.19873, ID=29029012
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =Comparing the in situ measurements from ACE (Chiu et al., 1998), Wind (Ogilvie Desch, 1997), and OMNI database ( https://omniweb.gsfc.nasa.gov/ ) during 14-17 July 2012, we found that Wind had the best data, that is, without any gaps or anomaly.

Authors=Rich, Frederick J.; Califf, Samuel; Loto’aniu, Paul T. M.; Coakley, Monica; Krimchansky, Alexander; Singer, Howard J.
Title=Intersatellite Comparisons of GOES Magnetic Field Measurements, 2024, doi:10.1029/2023SW003736, ID=29029019
journal=Space Weather
Keywords found:space physics data facility, omniweb
Sample usage ( BODY ) =Inputs to the model include geomagnetic indices and measurements of the interplanetary environment acquired from the NASA Space Physics Data Facility OMNIWEB ( https://omniweb.gsfc.nasa.gov/ ). We started the study using the models described by Tsyganenko ( 1989) (hereafter referred to as T89) and Tsyganenko and Sitnov ( 2005) (hereafter referred to as TS05).

Authors=Jiang, Jia-Nan; Zou, Zi-Ming; Lu, Yang; Zhong, Jia; Wang, Yong; Ma, Yu-Zhang; Zhao, Bian-Long
Title=A Superposed Epoch Analysis of Auroral Oval Coverage During Substorms Using Deep Learning-Based Segmentation Models, 2024, doi:10.1029/2023SW003764, ID=29029028
journal=Space Weather
Keywords found:spdf, omni, omniweb
Sample usage ( BODY ) =We used the Polar UVI team’s studio software ( https://figshare.com/articles/dataset/POLAR UVI calibration toolkit/5197084) to generate images from.cdf files ( https://spdf.gsfc.nasa.gov/pub/data/polar/uvi/ ). The software can execute standard calibrations, corrections, and coordinate transformations (Germany et al., 1997; Lummerzheim Lilensten, 1994).
Sample usage ( BODY ) =The IMF data were obtained from the OMNI website ( https://omniweb.gsfc.nasa.gov/form/omni_min.html ). Because the IMF data in OMNI are given at the nose of the magnetopause, there is a certain propagation delay for the IMF affecting the aurora in the ionosphere.

Authors=Pignalberi, Alessio; Cesaroni, Claudio; Pietrella, Marco; Pezzopane, Michael; Spogli, Luca; Marcocci, Carlo; Pica, Emanuele
Title=Ionospheric Nowcasting Over Italy Through Data Assimilation: A Synergy Between IRI UP and IONORING, 2024, doi:10.1029/2023SW003838, ID=29029040
journal=Space Weather
Keywords found:space physics data facility, omniweb, iri, international reference ionosphere
Sample usage ( BODY ) =Magnetic and solar activity indices used in this study were downloaded from NASA’s Space Physics Data Facility of the Goddard Space Flight Center through the OMNIWeb Data Explorer website ( https://omniweb.gsfc.nasa.gov/form/dx1.html ).
Sample usage ( BODY ) =Dst , Kp , and F 10.7 indices were downloaded from the OMNIWeb Data Explorer NASA portal at https://omniweb.gsfc.nasa.gov/form/dx1.html .
Sample usage ( ACK ) =The authors are also grateful to Giorgiana De Franceschi for the fruitful discussions about the improvements of the IONORING algorithm. The IRI team is acknowledged for developing and maintaining the IRI model and for giving access to the corresponding Fortran code via the IRI website ( http://irimodel.org/ ).
Sample usage ( BODY ) =(Panel (b)) Map of updated fo F2 values by IRI UP after assimilating the IG 12 eff map of Figure 6b. (Panel (c)) Map of residuals between IRI UP (panel (b)) and IRI (panel (a)) fo F2 values.
Sample usage ( ABSTRACT ) =Despite the crucial contribution of empirical models like the International Reference Ionosphere (IRI), their limitations in predicting ionospheric variability, especially under geomagnetically disturbed conditions, are acknowledged.
Sample usage ( TITLE ) =Ionospheric Nowcasting Over Italy Through Data Assimilation: A Synergy Between IRI UP and IONORING
Sample usage ( BODY ) =While empirical climatological models of the ionosphere, such as the International Reference Ionosphere (IRI) model (Bilitza et al., 2022), play a crucial role, they may fall short in predicting all ionospheric variability, particularly under disturbed geomagnetic conditions (Miro’ Amarante et al., 2007; Pignalberi et al., 2016).

Authors=Pan, Qian; Xiong, Chao; Luhr, Hermann; Smirnov, Artem; Huang, Yuyang; Xu, Chunyu; Yang, Xu; Zhou, Yunliang; Hu, Yang
Title=Machine Learning Based Modeling of Thermospheric Mass Density, 2024, doi:10.1029/2023SW003844, ID=29029041
journal=Space Weather
Keywords found:omni
Sample usage ( BODY ) =In addition to the thermospheric mass density, a variety of geomagnetic and solar activity related indices have also been used to develop the MBiLE model, which can be accessed at the website of OMNI ( https://spdf.gsfc.nasa.gov/pub/data/**omni**/low\_res\_omni/ ). In total, there are 62 parameters used as inputs, and the details are shown in the Table A1 of the Appendix.

Authors=Zhao, Jingmin; Feng, Xueshang
Title=Prediction of Solar Coronal Structures Using Fourier Neural Operators Based on the Solar Photospheric Magnetic Field Observation, 2024, doi:10.1029/2024SW003875, ID=29029047
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =It is worth noting that the difference between the maximum and minimum values observed by the model and OMNI varies at different CRs, and the numerical MHD model shows similar performance.
Sample usage ( ABSTRACT ) =From 1 to 20Rs, the SSIM values for the number density and radial speed surpass 0.9. Relative to OMNI observations, the mean absolute percentage error for the radial speed generated from the FNO-SC model does not exceed 0.25.
Sample usage ( BODY ) =The hourly-averaged OMNI data is acquired from the OMNIWeb portal ( http://omniweb.gsfc.nasa.gov ). The data sets and codes utilized in this research are available in the database of the National Space Science Data Center ( https://doi.org/10.57760/sciencedb.15192 ).

Authors=Lin, Rong; Luo, Zhekai; He, Jiansen; Xie, Lun; Hou, Chuanpeng; Chen, Shuwei
Title=Prediction of Solar Wind Speed Through Machine Learning From Extrapolated Solar Coronal Magnetic Field, 2024, doi:10.1029/2023SW003561, ID=29161632
journal=Space Weather
Keywords found:spdf, space physics data facility, omni, omniweb
Sample usage ( ACK ) =Acknowledgments The authors are grateful to the teams of OMNI and GONG for providing the data, and the teams of pfsspy for developing the program.
Sample usage ( BODY ) =The OMNI database is supported by NASA’s Space Physics Data Facility (SPDF).
Sample usage ( BODY ) =The data are available at https://omniweb.gsfc.nasa.gov . We use hourly OMNI SW speed data from September 2006 to November 2020.

Authors=Karan, Deepak Kumar; Martinis, Carlos R.; Eastes, Richard W.; Daniell, Robert E.; McClintock, William E.; Huang, Chao-Song
Title=GOLD Observations of Equatorial Plasma Bubbles Reaching Mid-Latitudes During the 23 April 2023 Geomagnetic Storm, 2024, doi:10.1029/2023SW003847, ID=29161635
journal=Space Weather
Keywords found:spdf, omni, omniweb
Sample usage ( BODY ) =The solar wind parameters and geomagnetic indices are taken from the NASA GSFC SPDF OMNI website ( https://omniweb.gsfc.nasa.gov/form/omni_min.html ).

Authors=Eastwood, J. P.; Brown, P.; Magnes, W.; Carr, C. M.; Agu, M.; Baughen, R.; Berghofer, G.; Hodgkins, J.; Jernej, I.; Mostl, C.; Oddy, T.; Strickland, A.; Vitkova, A.
Title=The Vigil Magnetometer for Operational Space Weather Services From the Sun-Earth L5 Point, 2024, doi:10.1029/2024SW003867, ID=29161643
journal=Space Weather
Keywords found:cdaweb, space physics data facility
Sample usage ( BODY ) =Data Availability Statement The STEREO data used in this manuscript are available from NASA’s Space Physics Data Facility at the Coordinated Data Analysis Web (CDAWeb) https://cdaweb.gsfc.nasa.gov/ and were analyzed using the software package PySPEDAS (Grimes et al., 2022).

Authors=Cruz, Alfredo A.; Siddalingappa, Rashmi; Mehta, Piyush M.; Morley, Steven K.; Godinez, Humberto C.; Jordanova, Vania K.
Title=Reduced-Order Probabilistic Emulation of Physics-Based Ring Current Models: Application to RAM-SCB Particle Flux, 2024, doi:10.1029/2023SW003706, ID=29161651
journal=Space Weather
Keywords found:space physics data facility, omni, omniweb
Sample usage ( BODY ) =To create the data sets, we used NASA’s space physics data facility OMNIWeb database (OMNIWeb, 2020), focusing on solar wind and geomagnetic data spanning 2000-2020, with a 1-min cadence.
Sample usage ( BODY ) =The decision to retrieve velocity components in GSE coordinates, rather than GSM coordinates, is constrained by the fact that the OMNI web interface provides velocity components in GSE. We note the coordinate systems to help any users of the open data associated with this work avoid the pitfalls of incorrect coordinate system assumptions.

Authors=Wang, Qiushuo; Yue, Chao; Li, Jinxing; Bortnik, Jacob; Ma, Donglai; Jun, Chae-Woo
Title=Modeling the Dynamic Global Distribution of the Ring Current Oxygen Ions Using Artificial Neural Network Technique, 2024, doi:10.1029/2023SW003779, ID=29161652
journal=Space Weather
Keywords found:cdaweb
Sample usage ( BODY ) =The 1-min resolution Sym/Asy indices used in this study are obtained from the Coordinated Data Analysis Web (CDAWeb). SME is the SuperMAG version of Auroral Electrojet (AE) index, which is typically an indication of particle injections during substorms.

Authors=Yin, Qianfeng; Pham, Kevin H.; Chen, Junjie; Zhang, Binzheng
Title=Validation of Simulated Statistical Characteristics of Magnetosphere-Ionosphere Coupling in Global Geospace Simulations Over an Entire Carrington Rotation, 2024, doi:10.1029/2023SW003749, ID=29161653
journal=Space Weather
Keywords found:cdaweb, omni
Sample usage ( BODY ) =A subset of the upstream SW/IMF observations during the Carrington Rotation event extracted from the OMNI data set via the CDAWeb ( https://cdaweb.gsfc.nasa.gov/ ) are shown in Figure 2, the data selected in this study has a strong continuity including variations of the solar wind speed, number density, IMF B y and B z components.

Authors=Wang, Jianhang; Xiang, Zheng; Ni, Binbin; Guo, Deyu; Liu, Yangxizi; Dong, Junhu; Hu, Jingle; Guo, Haozhi
Title=Influences of Solar Wind Parameters on Energetic Electron Fluxes at Geosynchronous Orbit Revealed by the Deep SHAP Method, 2024, doi:10.1029/2024SW003880, ID=29162055
journal=Space Weather
Keywords found:cdaweb, omniweb
Sample usage ( BODY ) =Data Availability Statement The electron fluxes data from GOES-15 are available at https://cdaweb.gsfc.nasa.gov . The solar wind parameters used in this study are obtained from the OMNIWeb database ( http://omniweb.gsfc.nasa.gov ).
Sample usage ( BODY ) =The solar wind parameters used in this study are obtained from the OMNIWeb database ( http://omniweb.gsfc.nasa.gov ). The ANN model can be found at https://doi.org/10.1016/j.asr.2022.10.013 .

Authors=Li, Min; Yuan, Yunbin; Zhang, Ting; Xu, Hanying; Huo, Xingliang; Zhang, Wenyao
Title=Investigation of the Contribution of Five Broadcast Ionospheric Models (GPSK, NTCMG, NEQG, BDGIM, and BDSK) and IRTG to GNSS Positioning During Different Solar Activities in Solar Cycle 25, 2024, doi:10.1029/2023SW003829, ID=29542096
journal=Space Weather
Keywords found:omniweb
Sample usage ( BODY ) =The F10.7 and Kp indices are obtained from the website https://omniweb.gsfc.nasa.gov/form/dx1.html .

Authors=Holland, K. M.; Nykyri, H. K.; Ma, X.; Wing, S.
Title=Comparing Information Theory Analysis With Cross-Correlation and Minimum Variance Analysis of the Solar Wind Structures, 2024, doi:10.1029/2024SW003870, ID=29542128
journal=Space Weather
Keywords found:omni
Sample usage ( BODY ) =Currently, magnetic field and plasma data from spacecraft at the Earth-Sun Lagrange point 1 (EL-1) (ACE, DSCOVR, Wind) are used to predict IMF and solar wind that is impacting the Earth. OMNI is a virtual observatory (King Papitashvili, 2005), where EL-1 data (from ACE and Wind) is advected to the bow shock nose to predict the solar wind and IMF properties, before it interacts with Earth’s magnetosphere.

Authors=Ren, Xiaochen; Zhao, Biqiang; Ren, Zhipeng; Wang, Yan; Xiong, Bo
Title=Deep Learning-Based Prediction of Global Ionospheric TEC During Storm Periods: Mixed CNN-BiLSTM Method, 2024, doi:10.1029/2024SW003877, ID=29542129
journal=Space Weather
Keywords found:international reference ionosphere
Sample usage ( BODY ) =The Time Empirical Ionospheric Correction Model (STORM) (Araujo-Pradere Fuller-Rowell, 2002; Araujo-Pradere et al., 2002), proposed in the International Reference Ionosphere, simulates the evolution process of storm time foF2 based on its nonlinear dependence on the integrated time history of ap, considering different latitudes and seasons (Araujo-Pradere et al., 2004).

Authors=Wang, Haoran; Liu, Haijun; Yuan, Jing; Le, Huijun; Shan, Weifeng; Li, Liangchao
Title=MAOOA-Residual-Attention-BiConvLSTM: An Automated Deep Learning Framework for Global TEC Map Prediction, 2024, doi:10.1029/2024SW003954, ID=29542139
journal=Space Weather
Keywords found:iri
Sample usage ( BODY ) =TEC predicting model 1 Table Deep Learning Models and Hyper-Parameter Optimization Methods in TEC Prediction Type Model Prediction content or results Hyper-parameter optimization methods Time series models ED-LSTM (Xiong et al., 2021) ED-LSTM was used to predict TEC of 15 stations in China, and the prediction effect was better than LSTM, DNN, ARIMA and IRI-2016. Grid search ED-LSTM (Xiong et al., 2022) The TEC prediction performance ( R 2 = 0.9105, RMSE = 2.6759) of the encoder-decoder model of LSTM at five sites in China is lower than that of DNN, RF, SVM, ARIMA and DT.

Authors=Waghule, Bhagyashree; Knipp, D. J.; Gannon, J. L.; Billet, D.; Vines, S. K.; Goldstein, J.
Title=What Drove the GICs >10 A During the 17 March 2013 Event at Mantsala? A Novel Framework for Distinguishing the Magnetospheric Sources, 2024, doi:10.1029/2024SW003980, ID=29542143
journal=Space Weather
Keywords found:cdaweb, omni, omniweb
Sample usage ( BODY ) =TWINS data are accessible to the public at https://cdaweb.gsfc.nasa.gov/ . Fitted SuperDARN data can be downloaded from Globus, instructions of which are provided here: https://superdarn.ca/data-products .
Sample usage ( BODY ) =The solar wind data is retrieved from OMNIWeb ( https://omniweb.gsfc.nasa.gov/form/omni_min.html ). TWINS data are accessible to the public at https://cdaweb.gsfc.nasa.gov/ .
Sample usage ( ACK ) =page=acknowledgement ) and SuperDARN network of radars ; the AMPERE team and the Science Data Center for providing data products derived from the Iridium Communications constellation, enabled by support from the NSF; TWINS team for ENA data; and OMNIWeb for the solar wind data and derived products. SuperMAG data from the European sector were central to our findings hence we acknowledge INTERMAGNET, Alan Thomson; IMAGE, PI Liisa Juusola; FMI, PI Liisa Juusola; Sodankyla Geophysical Observatory, PI Tero Raita; UiT the Arctic University of Norway, Tromso Geophysical Observatory, PI Magnar G.

Authors=Tulasi Ram, S.; Ankita, M.; Nilam, B.; Gurubaran, S.; Nair, Manoj; Seemala, Gopi K.; Brahmanandam, P. S.; Dimri, A. P.
Title=Empirical Model of Equatorial ElectroJet (EEJ) Using Long-Term Observations From the Indian Sector, 2024, doi:10.1029/2024SW003988, ID=29542147
journal=Space Weather
Keywords found:space physics data facility, omni
Sample usage ( ACK ) =Acknowledgments We acknowledge NASA’s Space Physics Data Facility for making F10.7 data available from the OMNI web interface and World Data Center for Geomagnetism, Kyoto University for SymH index data.
Sample usage ( BODY ) =Data Availability Statement The F10.7 solar flux data is downloaded from OMNI web interface of NASA’s Space Physics Data Facility ( https://spdf.gsfc.nasa.gov/pub/data/**omni**/low\_res\_omni/ .

Authors=Girgis, Kirolosse M.; Hada, Tohru; Yoshikawa, Akimasa; Matsukiyo, Shuichi; Chian, Abraham C. -L.; Echer, Ezequiel
Title=Inner Radiation Belt Simulations During the Successive Geomagnetic Storm Event of February 2022, 2024, doi:10.1029/2023SW003789, ID=29542195
journal=Space Weather
Keywords found:omniweb
Sample usage ( BODY ) =Input Conditions Figure 1 illustrates the solar wind data, the Interplanetary Magnetic Field (IMF), and the Dst index, obtained from the OMNIWeb database and the WDC at Kyoto University, respectively. 1 Figure The figure displays the IMF conditions, the solar wind dynamic pressure, and the Dst index from 2 to 10 February, 2022.

Authors=Forsythe, Victoriya V.; McDonald, Sarah E.; Dymond, Kenneth F.; Fritz, Bruce A.; Burrell, Angeline G.; Zawdie, Katherine A.; Drob, Douglas P.; Burleigh, Meghan R.; Hickey, Dustin A.; Metzler, Christopher A.; Kuhl, David D.; Hodyss, Daniel; Hughes, Joe H.
Title=ANCHOR: Global Parametrized Ionospheric Data Assimilation, 2024, doi:10.1029/2023SW003803, ID=29542201
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =Climatological models, such as the International Reference Ionosphere (IRI) (Bilitza et al., 2022; Forsythe et al., 2024), provide good estimates of the electron density for a given time and solar activity level.

Authors=Chen, Yan-Shen; Chen, Chia-Hung; Yang, Ming; Chu, Feng-Yu
Title=Evaluate the Impact of Regional Ionospheric Data Assimilation Model on Precise Point Positioning, 2024, doi:10.1029/2024SW003858, ID=30803207
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =After data assimilation by EnKF/IRI, the RMSE values of IRI decrease significantly and are overall below 5 TECu (red line, nowcast).
Sample usage ( ABSTRACT ) =The study further evaluates the performance of both static PPP with the ionospheric information using commonly used models such as Klobuchar and International Reference Ionosphere (IRI), as well as a global ionospheric data assimilation model. Compared to the default IRI, the data assimilated IRI model can improve the overall ionospheric total electron content by approximately 83%.
Sample usage ( BODY ) =For this purpose, we develop a regional ionospheric data assimilation model with high spatial resolution (25 km) by employing the ensemble Kalman filter (EnKF) to combin the International Reference Ionosphere (IRI) (Bilitza, 2001) and total electron density (TEC) observations around Taiwan, called EnKF/IRI hereafter.

Authors=Chen, Weixin; Fu, Song; Ma, Xin; Ni, Binbin; Guo, Deyu; Zhang, Qiongyue; Tong, Xiangyuan; Zhao, Yibo; Cao, Xing; Xiang, Zheng; Lei, Yuan
Title=Quantifying the Spatiotemporal Evolution of Radiation Belt Electrons Scattered by Lower Band Chorus Waves: An Integrated Model, 2024, doi:10.1029/2024SW003876, ID=30803218
journal=Space Weather
Keywords found:spdf, omni, omniweb
Sample usage ( BODY ) =These 11 input parameters with 1 min resolution are obtained from the OMNI website (SPDF - OMNIWeb Service ( nasa.gov )) (King Papitashvili, 2005) and the World Data Center for Geomagnetism, Kyoto ( https://wdc.kugi.kyoto-u.ac.jp/index.html ).
.
Authors=Collado-Villaverde, Armando; Munoz, Pablo; Cid, Consuelo
Title=Comment on “Prediction of the SYM-H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification” by Abduallah et al. (2024), 2024, doi:10.1029/2024SW003909, ID=30803242
journal=Space Weather
Keywords found:cdaweb, spdf, space physics data facility, omni, omniweb
Sample usage ( BODY ) =Database The first concern to be considered is the data used in the study: the paper does not specify which of the multiple data sets available on the CDAWeb is used to retrieve the input features. For instance, referenced works (Collado-Villaverde et al., 2021; Iong et al., 2022; Siciliano et al., 2021) specify which data sets are used to retrieve the different parameters, such as the OMNI_HRO_5MIN for the indices values, AC_H3_MFI for the IMF data or the AC_H0_SWE for the plasma features.
Sample usage ( BODY ) =Data Availability Statement The solar wind, IMF and derived parameters along with the SYM-H index data are available through NASA’s Space Physics Data Facility (SPDF) Coordinated Data Analysis Web (CDAWeb) https://cdaweb.gsfc.nasa.gov/index.html .
Sample usage ( BODY ) =For instance, referenced works (Collado-Villaverde et al., 2021; Iong et al., 2022; Siciliano et al., 2021) specify which data sets are used to retrieve the different parameters, such as the OMNI_HRO_5MIN for the indices values, AC_H3_MFI for the IMF data or the AC_H0_SWE for the plasma features. It is crucial to specify the data set used because some of them undergo an extensive post-processing and are compiled from multiple spacecraft sources. Such case is the definitive OMNI High-Resolution data (OMNI HRO), which provides the same data as previous repositories but with some temporal delay, making it unusable for real-time forecasting systems, which is a must have for a model that aims to be operationalized.
Sample usage ( BODY ) =Moreover, in the Data Availability Statement of the paper, the link ( https://omniweb.gsfc.nasa.gov/ow.html ) points to the “Hourly Near-Earth solar wind magnetic field and plasma data, energetic proton fluxes (>1 to >60 MeV), and geomagnetic and solar activity indices,” which only provides hourly, daily, 27-day and yearly averaged resolution data.

Authors=Smirnov, Artem; Shprits, Yuri; Luhr, Hermann; Pignalberi, Alessio; Xiong, Chao
Title=Calibration of Swarm Plasma Densities Overestimation Using Neural Networks, 2024, doi:10.1029/2024SW003925, ID=30803245
journal=Space Weather
Keywords found:omniweb, iri
Sample usage ( BODY ) =The F10.7 index was downloaded from the OMNIWeb database omniweb.gsfc.nasa.gov . The Hp30 index is provided by GFZ Potsdam https://kp.gfz-potsdam.de/hp30-hp60 .
Sample usage ( BODY ) =Swarm LP data are frequently used for modeling of the topside ionosphere (e.g., Bilitza Xiong, 2021; Pezzopane et al., 2024), and the calibrated LP observations may contribute to the improvement of the widely used ionospheric models, such as the IRI (Bilitza et al., 2022). Furthermore, the combined interpretation of the developed calibration model in combination with other models or observations can give useful hints about the ion composition and the dynamics of the topside ionosphere.

Authors=Pan, Yang; Jin, Mingwu; Zhang, Shun-Rong; Wing, Simon; Deng, Yue
Title=Neural Network Models for Ionospheric Electron Density Prediction at a Fixed Altitude Using Neural Architecture Search, 2024, doi:10.1029/2024SW003945, ID=30803248
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =For example, a global model, international reference ionosphere (IRI) (Bilitza, 2001) and IRI-2016 (Bilitza et al., 2017), takes primarily ionosonde observations to generate 3D distributions of ionospheric parameters.

Authors=Dietrich, Nicholas; Matsuo, Tomoko; Lin, Chi-Yen; diLorenzo, Brandon; Chien-Hung Lin, Charles; Fang, Tzu-Wei
Title=Evaluating Radio Occultation (RO) Constellation Designs Using Observing System Simulation Experiments (OSSEs) for Ionospheric Specification, 2024, doi:10.1029/2024SW003958, ID=30803253
journal=Space Weather
Keywords found:iri
Sample usage ( BODY ) =Yue, Schreiner, Kuo, et al. ( 2014) performed an OSSE study prior to the launch of F7/C2, assessing the multiple planned RO EDPs from F7/C2 using NeQuick model as the nature run and assimilating EDPs into the empirical ionospheric model IRI. Lee et al. ( 2013) assimilated synthetic F7/C2 EDPs into a coupled ionosphere-thermosphere (I-T) physics-based model, and saw global improvements in electron density states over previous F3/C EDPs.

Authors=Simms, L. E.; Ganushkina, N. Y.; van de Kamp, M.; Liemohn, M. W.
Title=Predicting Geostationary (GOES) 4.1-30 keV Electron Flux Over All MLT Using LEEMYR Regression Models, 2024, doi:10.1029/2024SW003962, ID=30803257
journal=Space Weather
Keywords found:omniweb
Sample usage ( BODY ) =Solar wind parameters (solar wind velocity V , number density N , pressure P , IMF B y and B z ), and magnetic indices (Kp and Dst) were obtained from OMNIWeb web with 1 hr resolution and data time-shifted to the bow shock nose ( https://omniweb.gsfc.nasa.gov/form/dx1.html ).

Authors=Oliveira, Denny M.; Allen, Robert C.; Alves, Livia R.; Blake, Sean P.; Carter, Brett A.; Chakrabarty, Dibyendu; D’Angelo, Giulia; Delano, Kevin; Echer, Ezequiel; Ferradas, Cristian P.; Finley, Matt G.; Gallardo-Lacourt, Bea; Gershman, Dan; Gjerloev, Jesper W.; Habarulema, John Bosco; Hartinger, Michael D.; Hajra, Rajkumar; Hayakawa, Hisashi; Juusola, Liisa; Laundal, Karl M.; Leamon, Robert J.; Madelaire, Michael; Martinez-Ledesma, Miguel; McIntosh, Scott M.; Miyoshi, Yoshizumi; Moldwin, Mark B.; Nahayo, Emmanuel; Nandy, Dibyendu; Nilam, Bhosale; Nykyri, Katariina; Paterson, William R.; Piersanti, Mirko; Pietropaolo, Ermanno; Rodger, Craig J.; Shah, Trunali; Smith, Andy W.; Srivastava, Nandita; Tsurutani, Bruce T.; Ram, S. Tulasi; Upton, Lisa A.; Veenadhari, Bhaskara; Vidal-Luengo, Sergio; Viljanen, Ari; Vines, Sarah K.; Yadav, Vipin K.; Yee, Jeng-Hwa; Weygand, James W.; Zesta, Eftyhia
Title=Predicting Interplanetary Shock Occurrence for Solar Cycle 25: Opportunities and Challenges in Space Weather Research, 2024, doi:10.1029/2024SW003964, ID=30803260
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =The F10.7 solar index data used in Supporting Information S1 (daily and yearly data from January 1964 to December 2023) were downloaded from the NASA OMNI website ( https://omniweb.gsfc.nasa.gov/form/dx1.html ).

Authors=van de Kamp, M.; Ganushkina, N.; Simms, L.; Liemohn, M.
Title=Drivers for Geostationary 2-200 keV Electron Fluxes as Observed at GOES Satellites, 2024, doi:10.1029/2024SW003984, ID=30803270
journal=Space Weather
Keywords found:space physics data facility, omni, omniweb
Sample usage ( BODY ) =The data on the solar wind, and of the magnetic index SymH were provided by the OMNIWeb service of the Space Physics Data Facility at the Goddard Space Flight Center, and obtained from their high resolution data page (NASA, 2024b).
Sample usage ( BODY ) =Stepanov et al. ( 2021) checked the cross-correlation function between a parameter similar to e obtained from OMNI, and the THEMIS plasma sheet electron flux at 31 and 93 keV in the midnight sector at various distances from Earth.
Sample usage ( ACK ) =We gratefully acknowledge NOAA for use of the GOES data, NASA for use of the OMNIWeb solar wind data, and the SuperMAG collaborators (SuperMAG, 2024a) for the SuperMAG index data.
Sample usage ( BODY ) =Solar wind parameters and magnetic indices were downloaded from OMNIWeb at 5 min resolution for the entire period of January 2010 - December 2023.

Authors=Li, Yaxian; Chen, Gang; Zhang, Shaodong; Huang, Kaiming; Gong, Wanlin; Zhang, Min
Title=Observational Evidence for the Neutral Wind Responses in the Mid-Latitude Lower Thermosphere to the Strong Geomagnetic Activity, 2024, doi:10.1029/2023SW003830, ID=31224669
journal=Space Weather
Keywords found:omniweb
Sample usage ( BODY ) =The IMF Bz, SYM-H, AE, and Kp indices are obtained from the OMNIWeb Data Explorer ( https://omniweb.gsfc.nasa.gov/form/omni_min_def.html , https://omniweb.gsfc.nasa.gov/form/dx1.html ).

Authors=Ruck, Joshua J.; Themens, David R.; Ponomarenko, Pasha; Burrell, Angeline G.; Kunduri, Bharat; Ruohoniemi, J. Michael; Elvidge, Sean
Title=On the Use of SuperDARN Ground Backscatter Measurements for Ionospheric Propagation Model Validation, 2024, doi:10.1029/2024SW00391610.22541/essoar.171052485.58279509/v1, ID=31224703
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =Transmission frequency is set to 10.8 MHz . 2D ionospheric grids are generated using the IRI once every 15 min and linearly interpolated down to the minutely resolution of the SuperDARN data.
Sample usage ( ABSTRACT ) =This technique is demonstrated by validating the International Reference Ionosphere (IRI) 2016 for January and June in both 2014 and 2018. LE RMS errors of 100-400 km and 400-800 km are observed for winter and summer months, respectively.
Sample usage ( BODY ) =We then perform an example assessment of the International Reference Ionosphere 2016 (IRI-2016) using this method, including analysis of LE variations in Sections 3.1 and 3.2, comparison of echo elevation-range distributions in Section 3.3, testing of simulated backscatter using ionosonde driven peak density parameters in Section 3.4, and diagnosis of model errors in Section 3.5 using echo elevation-range distributions simulated with offsets to NmF2, hmF2 and the interferometer calibration parameter, T diff .

Authors=Yang, Zhe; Morton, Y. T. Jade
Title=Time-Lagged Effects of Ionospheric Response to Severe Geomagnetic Storms on GNSS Kinematic Precise Point Positioning, 2024, doi:10.1029/2024SW003946, ID=31224719
journal=Space Weather
Keywords found:space physics data facility, omniweb
Sample usage ( BODY ) =The interplanetary parameters and geomagnetic indices are available at the NASA/GSFC’s Space Physics Data Facility’s OMNIWeb ( https://omniweb.gsfc.nasa.gov/index.html ) service, and the World Data Center ( http://wdc.kugi.kyoto-u.ac.jp/index.html ).

Authors=Li, Wenbo; Liu, Libo; Chen, Yiding; Zhou, Yi-Jia; Le, Huijun; Zhang, Ruilong
Title=Interplanetary Influence on Thermospheric Mass Density: Insights From Deep Learning Analyses, 2024, doi:10.1029/2024SW003952, ID=31224735
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =The IEI, solar activity, and geomagnetic activity index can be accessed at the OMNI web ( https://omniweb.gsfc.nasa.gov ). The DL model code are available from zenodo.org (Li Liu, 2024).

Authors=Salinas, Cornelius Csar Jude H.; Wu, Dong L.; Swarnalingam, Nimalan; Emmons, Daniel; Qian, Liying
Title=Development of the Ionospheric E-Region Prompt Radio Occultation Based Electron Density (E-PROBED) Model, 2024, doi:10.1029/2024SW004037, ID=31224757
journal=Space Weather
Keywords found:omni, omniweb, iri, international reference ionosphere
Sample usage ( BODY ) =Hence, for E-PROBED’s first version, the F10.7 index is chosen because it is commonly used, and it is convenient to access through NASA OMNI’s website: https://omniweb.gsfc.nasa.gov/ . Figure 3 shows an algorithm diagram of the E-PROBED-1 SZA Component.
Sample usage ( BODY ) =This work compares E-PROBED with the E-region Ne simulated by IRI. IRI has an E-region component constructed using rocket sounding measurements. For more information on IRI, see Bilitza et al. ( 2022). This work runs IRI through a python wrapper.
Sample usage ( ABSTRACT ) =Finally, this work compares E-PROBED with E-region Ne simulated by the International Reference Ionosphere (IRI) and the Specified Dynamics—Whole Atmosphere Community Climate Model with Ionosphere/Thermosphere eXtension (SD-WACCM-X). One of the main differences amongst these models is on the simulation of variabilities that cannot be attributed to photoionization. IRI barely simulates any variability not driven by photoionization.
Sample usage ( BODY ) =All ISR data are gathered from the Madrigal database ( http://cedar.openmadrigal.org/ ) and processed using methods described in Themens et al. ( 2019). International Reference Ionosphere The IRI is recognized as the standard for the Earth’s ionosphere by the International Standardization Organization, the International Union of Radio Science, the Committee on Space Research, and the European Cooperation for Space Standardization.

Authors=Zhao, Lulu; Sokolov, Igor; Gombosi, Tamas; Lario, David; Whitman, Kathryn; Huang, Zhenguang; Toth, Gabor; Manchester, Ward; van der Holst, Bart; Sachdeva, Nishtha; Liu, Weihao
Title=Solar Wind With Field Lines and Energetic Particles (SOFIE) Model: Application to Historical Solar Energetic Particle Events, 2024, doi:10.1029/2023SW00372910.48550/arXiv.2309.16903, ID=31224918
journal=Space Weather
Keywords found:spdf, space physics data facility
Sample usage ( BODY ) =Data Availability Statement The in situ solar wind plasma properties used in this work are available in the Space Physics Data Facility https://spdf.gsfc.nasa.gov/ . The white-light image data is available in the SOHO/LASCO website https://lasco-www.nrl.navy.mil/index.php?

Authors=Sarp, Volkan; Yigit, Erdal; Kilcik, Ali
Title=Response of the Thermosphere-Ionosphere System to an X-Class Solar Flare: 30 March 2022 Case Study, 2024, doi:10.1029/2024SW003938, ID=31604648
journal=Space Weather
Keywords found:spdf
Sample usage ( BODY ) =Panels b, c, and d show the interplanetary magnetic field (IMF) B z ${B}_{z}$ vector, solar wind speed, and density, respectively, provided by NASA SPDF (King Papitashvili, 2020). Panel e shows Auroral Electrojet Upper (AU) and Lower (AL) indices in blue and red curve, respectively, provided by SuperMAG.

Authors=Vital, L. F. R.; Takahashi, H.; Barros, D.; Carmo, S. C.; Carrasco, A. J.; Wrasse, C. M.; Figueiredo, C. A. O. B.
Title=Seasonal and Solar Cycle Dependency of Relationship Between Equatorial Plasma Bubbles and Rayleigh-Taylor Instability Growth Rate, 2024, doi:10.1029/2024SW003959, ID=31604649
journal=Space Weather
Keywords found:space physics data facility, omniweb, iri, international reference ionosphere
Sample usage ( BODY ) =Data Availability Statement The Embrace/INPE Space Weather Program ( https://embracedata.inpe.br ) for providing the All-Sky images and DPS-4 ionosonde data, the IBGE for providing the satellite data (Rinex) ( https://geoftp.ibge.gov.br/informacoes\_sobre\_posicionamento\_geodesico/rbmc/ ), and NASA/GSFC’s Space Physics Data Facility’s OMNIWeb service for providing the solar radio flux of F10.7 ( https://omniweb.gsfc.nasa.gov/form/dx1.html ).
Sample usage ( BODY ) =The g R T ${\gamma }_{RT}$ was calculated by using Ionosonde data and atmospheric models such as the Ionosphere Reference Model (IRI), the Horizontal Wind Model (HWM), and the Mass Spectrometer Incoherent Scatter Model (MSIS).
Sample usage ( ABSTRACT ) =The gRT calculations were based on F-layer vertical drift (Vp) measurements obtained from the Sao Luis ionosonde (2.33degS, 44.2degW, dip angle: -0.5deg), the International Reference Ionosphere model (IRI-2016), Horizontal Wind Model (HWM-14), and Spectrometer Incoherent Scatter Model-2,000 (NRLMSISE-00).
Sample usage ( BODY ) =The local electron density n 0 $\left({n}_{0}\right)$ was provided by the International Reference Ionosphere, IRI-2016 (Bilitza et al., 2017). The last term R T ${R}_{T}$ represents the flux tube integrated recombination rate and has been neglected in the present study, that is, R T = 0 ${R}_{T}=0$ (Carter, Retterer, et al., 2014; Shinagawa et al., 2018).

Authors=Feng, Yinan; Chen, Yue; Lin, Youzuo
Title=PreMevE-MEO: Predicting Ultra-Relativistic Electrons Using Observations From GPS Satellites, 2024, doi:10.1029/2024SW00397510.48550/arXiv.2406.01463, ID=31604650
journal=Space Weather
Keywords found:cdaweb, omni
Sample usage ( ACK ) =We also want to acknowledge the PIs and instrument teams of LANL GEO ESP, RBSP REPT, and NOAA POES SEM2 for providing measurements and allowing us to use their data. Thanks to CDAWeb for providing OMNI data. The authors are very grateful for the valuable suggestions and feedback from the reviewer.

Authors=Liu, Terry Z.; Shi, Xueling; Hartinger, Michael D.; Angelopoulos, Vassilis; Rodger, Craig J.; Viljanen, Ari; Qi, Yi; Shi, Chen; Parry, Hannah; Mann, Ian; Cordell, Darcy; Madanian, Hadi; Mac Manus, Daniel H.; Dalzell, Michael; Cui, Ryan; MacMullin, Ryan; Young-Morris, Greg; Noel, Christian; Streifling, Jeffrey
Title=Global Observations of Geomagnetically Induced Currents Caused by an Extremely Intense Density Pulse During a Coronal Mass Ejection, 2024, doi:10.1029/2024SW003993, ID=31604657
journal=Space Weather
Keywords found:cdaweb
Sample usage ( BODY ) =Data Availability Statement THEMIS, MMS, and DSCOVR dataset are available at NASA’s Coordinated Data Analysis Web (CDAWeb, http://cdaweb.gsfc.nasa.gov/ ). KOMPSAT dataset is available at https://swe.ssa.esa.int/sosmag .

Authors=Collado-Villaverde, Armando; Munoz, Pablo; Cid, Consuelo
Title=Operational SYM-H Forecasting With Confidence Intervals Using Deep Neural Networks, 2024, doi:10.1029/2024SW004039, ID=31604669
journal=Space Weather
Keywords found:cdaweb, space physics data facility, omni
Sample usage ( BODY ) =All the data sets for the different features are downloaded from NASA’s Coordinated Data Analysis Web (CDAWeb). Regarding the SYM-H index, we use the OMNI_HRO_5MIN data set for the training and evaluation of the model.
Sample usage ( BODY ) =Data Availability Statement [Data set] The solar wind, IMF and derived parameters along with the SYM-H index data are available through NASA Space Physics Data Facility (CDAWeb) ( 2024). [Software] The predictions in csv format can be downloaded at Collado-Villaverde et al. ( 2024c).
Sample usage ( BODY ) =Regarding the SYM-H index, we use the OMNI_HRO_5MIN data set for the training and evaluation of the model.

Authors=Wang, R. C.; Jorgensen, Anders M.; Li, Dalin; Sun, Tianran; Yang, Zhen; Peng, Xiaodong
Title=An Adaptive X-Ray Dynamic Image Estimation Method Based on OMNI Solar Wind Parameters and SXI Simulated Observations, 2024, doi:10.1029/2024SW004040, ID=31604672
journal=Space Weather
Keywords found:spdf, space physics data facility, omni
Sample usage ( BODY ) =The OMNI database, maintained by NASA’s Space Physics Data Facility (SPDF), is an online data service (Papitashvili King, 2020). The database integrates solar wind parameters, magnetic field, and particle measurements at a 1-min time resolution.
Sample usage ( BODY ) =In this paper, we develop an approach for estimating the evolution on short time-scales based on longer-time integrations. 1 Figure Schematic of the observing geometry illustrating the changing observation position from a spacecraft (or the Moon), as well as changes in the magnetosheath state. This study will use OMNI data as well as output from an MHD model. The OMNI database, maintained by NASA’s Space Physics Data Facility (SPDF), is an online data service (Papitashvili King, 2020).
Sample usage ( ABSTRACT ) =Our study introduces a neural network method which is able to estimate the short-term dynamics during a long integration, driven by OMNI solar wind data and simulated soft X-ray images. Specifically, an adaptive X-ray image estimator and a spatio-temporal discriminator are used. It leverages X-ray models like Magnetohydrodynamic (MHD) and Jorgensen & Sun model, driven by OMNI data to provide high-temporal-resolution prior information on magnetosphere motion, with SXI observation images acting as a posterior constraint on the magnetosphere’s state.
Sample usage ( TITLE ) =An Adaptive X-Ray Dynamic Image Estimation Method Based on OMNI Solar Wind Parameters and SXI Simulated Observations

Authors=Zhang, Jiaojiao; Lan, Ailan; Yan, Jingye; Deng, Xiang; Wang, Wei; Li, Hang; Sun, Lingchen; Nan, Ying; Song, Xiaochao; Wang, Chi
Title=Development of the Chinese Dual Auroral Radar Network and Preliminary Results, 2024, doi:10.1029/2024SW004131, ID=31604676
journal=Space Weather
Keywords found:cdaweb, omni, omniweb
Sample usage ( ACK ) =SuperDARN is a network of radars funded by the national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, the United Kingdom, and the United States of America. We also acknowledge CDAWeb of the Goddard Space Flight Center for use of the solar wind data and SYM-H index from the OMNI database.
Sample usage ( ACK ) =We also acknowledge CDAWeb of the Goddard Space Flight Center for use of the solar wind data and SYM-H index from the OMNI database.
Sample usage ( BODY ) =The solar wind data and SYM-H index data were obtained from the OMNI database ( https://omniweb.gsfc.nasa.gov/ow.html ).

Authors=Dimmock, A. P.; Lanabere, V.; Johlander, A.; Rosenqvist, L.; Yordanova, E.; Buchert, S.; Molenkamp, S.; Setreus, J.
Title=Investigating the Trip of a Transformer in Sweden During the 24 April 2023 Storm, 2024, doi:10.1029/2024SW003948, ID=32070214
journal=Space Weather
Keywords found:omni
Sample usage ( BODY ) =This could also be used to check the timing of the OMNI and L1 data, which was not necessary in this study. We have performed the timing based on the second spike since this was when MMS was in the solar wind.

Authors=Smith, A. W.; Rae, I. J.; Forsyth, C.; Coxon, J. C.; Walach, M. -T.; Lao, C. J.; Bloomfield, D. S.; Reddy, S. A.; Coughlan, M. K.; Keesee, A.; Bentley, S.
Title=Space Weather Forecasts of Ground Level Space Weather in the UK: Evaluating Performance and Limitations, 2024, doi:10.1029/2024SW003973, ID=32070216
journal=Space Weather
Sample usage ( BODY ) =Another consideration with the use of the OMNI data is that it does not have a singular source, rather it is an amalgamation of data from several different spacecraft (ACE, DSCOVR, and WIND).
Sample usage ( BODY ) =We acknowledge and thank NASA GSFC’s Space Physics Data Facility’s OMNIWeb (or CDAWeb or ftp) service for the use of OMNI data ( https://omniweb.gsfc.nasa.gov ; Papitashvili King, 2020).

Authors=Wang, Xin; Ren, Tingling; Wang, Ronglan; Luo, Bingxian; Aa, Ercha; Cai, Lei; Li, Ming; Miao, Juan; Liu, Siqing; Gong, Jiancun
Title=Estimates of Spherical Satellite Drag Coefficients in the Upper Thermosphere During Different Geomagnetic Conditions, 2024, doi:10.1029/2024SW003974, ID=32070218
journal=Space Weather
Keywords found:omniweb
Sample usage ( BODY ) =The geomagnetic activity index SYM/H and the solar radiation proxy F10.7 are obtained from https://omniweb.gsfc.nasa.gov/form/dx1.html . The NRLMSISE-00 is from https://ccmc.gsfc.nasa.gov/ .

Authors=Vazifehkhah Hafteh, M.; Mahmoudian, A.; Yoshikawa, A.; Girgis, K.
Title=Mid-Latitude Study of Ionospheric Variation Over Iran Associated With Equatorial Ionization Anomaly (EIA), and Artificial Neural Networks Model Development, 2024, doi:10.1029/2024SW004032, ID=32070223
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =The Dst index, widely used as a measure of geomagnetic activity, was obtained from the OMNI website ( https://omniweb.gsfc.nasa.gov ). In each region, we removed one station and trained the model based on the data acquired from the remained stations within that region.

Authors=Wang, Xiaoyu; Ni, Binbin; Cao, Xing; Ma, Xin; Lei, Yuan; Dou, Xiankang
Title=Dynamic Responses of Outer Radiation Belt Electron Phase Space Densities to Geomagnetic Storms: A Statistical Analysis Based on Van Allen Probes Observations, 2024, doi:10.1029/2024SW004038, ID=32070224
journal=Space Weather
Keywords found:spdf, omni, omniweb
Sample usage ( BODY ) =Electron fluxes observed by ECT onboard Van Allen Probes are publicly available from https://spdf.gsfc.nasa.gov/pub/data/rbsp/ . Solar wind parameters and geomagnetic indexes are publicly available from https://omniweb.gsfc.nasa.gov/form/omni_min.html .
Sample usage ( BODY ) =Solar wind parameters and geomagnetic indexes are publicly available from https://omniweb.gsfc.nasa.gov/form/omni_min.html . The data we used in this present study can be obtained from https://doi.org/10.6084/m9.figshare.27060880.v1 (Wang, 2024).
Sample usage ( BODY ) =Data and Methodology Following the criteria of Reeves et al. ( 2003) and Turner et al. ( 2015), geomagnetic storm events are identified by using SYM-H index with 1 min resolution from OMNIWEB ( https://omniweb.gsfc.nasa.gov/ ) and the minima of SYM-H (SYM-Hmin) is less than or equal to -30 nT.

Authors=Li, Ke; Zhang, Donghe; Zeng, Yi; Tian, Yaoyu; Yang, Guanglin; Hao, Yongqiang
Title=Morphology and Climatology of Nighttime Periodic Ionospheric TEC Disturbances Associated With MSTIDs Over China, 2024, doi:10.1029/2024SW004041, ID=32070226
journal=Space Weather
Keywords found:omniweb
Sample usage ( ACK ) =Lars Hoffmann for providing AIRS/Aqua Observations data of GWs. We also thank the NASA OMNIWeb website for providing space weather data freely online.
Sample usage ( BODY ) =F10.7 index can be downloaded at https://omniweb.gsfc.nasa.gov .

Authors=Zhu, Qingyu; Lu, Gang; Vines, Sarah; Hairston, Marc
Title=Interhemispheric Asymmetry in the High-Latitude Neutral Density Variations During the 13-14 March 2022 Storm, 2024, doi:10.1029/2024SW004084, ID=32070232
journal=Space Weather
Keywords found:omniweb
Sample usage ( BODY ) =Data Availability Statement The IMF and SYM-H data can be found at https://omniweb.gsfc.nasa.gov . The Swarm-C neutral mass density data is available at https://swarm-diss.eo.esa.int/#swarm%2FLevel2daily%2FEntire\_mission\_data%2FDNS%2FACC%2FSat\_C and the GRACE-FO neutral mass density data is available at https://swarm-diss.eo.esa.int/#swarm%2FMultimission%2FGRACE-FO%2FDNS%2FSat\_1 .

Authors=Gonzalez-Esparza, J. A.; Sanchez-Garcia, E.; Sergeeva, M.; Corona-Romero, P.; Gonzalez-Mendez, L. X.; Valdes-Galicia, J. F.; Aguilar-Rodriguez, E.; Rodriguez-Martinez, M.; Ramirez-Pacheco, C.; Castellanos, C. I.; Pazos, M.; Mendoza, B.; Gatica-Acevedo, V. J.; Melgarejo-Morales, A.; Caraballo, R.; Andrade-Mascote, E.; Villanueva-Hernandez, P.; Bonifaz-Alfonzo, R.; Sierra, P.; Romero-Hernandez, E.; Peralta-Mendoza, I.; Perez-Tijerina, E.; Mejia-Ambriz, J. C.; Guerrero-Pena, C.; Caccavari, A.; Cifuentes-Nava, G.; Hernandez-Quintero, E.
Title=The Mother’s Day Geomagnetic Storm on 10 May 2024: Aurora Observations and Low Latitude Space Weather Effects in Mexico, 2024, doi:10.1029/2024SW004111, ID=32070235
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =The ionospheric profiles in Figure 9 (lower panels) reconstructed using the International Reference Ionosphere (IRI-2016) model (Bilitza et al., 2022) and regional sounding data from Mexart station in the center of Mexico show the positive ionospheric storm on 10 May and the negative on 11 May 2024.

Authors=Tan, Mengli; Si, Xu; Teng, Shangchun; Wu, Xinming; Tao, Xin
Title=Comparative Analysis of TPA-LSTM and Transformer Models for Forecasting GEO Radiation Belt Electron Fluxes, 2024, doi:10.1029/2024SW004119, ID=32070237
journal=Space Weather
Keywords found:cdaweb, omni, omniweb
Sample usage ( BODY ) =Data Processing In this study, we use fluxes of radiation belt electrons observed by GOES-15 from 2011 to 2019, available from Coordinated Data Analysis Web ( https://cdaweb.gsfc.nasa.gov/pub/data/goes/ ). A forecast model is built for four different energy channels: 275 keV, 475 keV, > ${ >} $ 0.8 MeV, > ${ >} $ 2 MeV.
Sample usage ( BODY ) =Data Availability Statement The solar wind data and geomagnetic indices utilized in this study were obtained from the OMNI database ( https://omniweb.gsfc.nasa.gov/ ). Data on MLT and electron fluxes at GEO were obtained from the Geostationary Operational Environmental Satellite 15 (GOES 15), available through Coordinated Data Analysis Web ( https://cdaweb.gsfc.nasa.gov/pub/data/goes/ ).

Authors=Sun, Wenjie; Li, Guozhu; Ning, Baiqi; Hu, Lianhuan; Otsuka, Yuichi; Dai, Guofeng; Xie, Haiyong; Zhao, Xiukuan; Li, Yi; Shinbori, Atsuki; Nishioka, Michi; Perwitasari, Septi; Wang, Chi
Title=Monitoring of Ionospheric Variability Using the Low lAtitude Long Range Ionospheric raDar (LARID): Capabilities, Advantages and Limitations, 2024, doi:10.1029/2024SW004134, ID=32070239
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =The colored background shows the plasma frequencies calculated using the International Reference Ionosphere model (IRI-2016) at (middle) 350 km and (bottom) along ~19.2degN, respectively.

Authors=Staples, Frances; Kellerman, Adam; Green, Janet
Title=On the Performance of a Real-Time Electron Radiation Belt Specification Model, 2024, doi:10.1029/2024SW00395010.22541/essoar.171255574.43451511/v1, ID=32519754
journal=Space Weather
Keywords found:cdaweb, space physics data facility, omniweb
Sample usage ( BODY ) =Data Availability Statement Spacecraft data from GOES, MMS, THEMIS, and the Van Allen Probes are publicly available via the NASA/GSFC CDAWeb service (NASA, 2024a). Solar Wind data and Sym-H index are publicly available through the NASA/GSFC Space Physics Data Facility OMNIWeb service (NASA, 2024b) and Kp index is available via Matzka ( 2021).
Sample usage ( BODY ) =Solar Wind data and Sym-H index are publicly available through the NASA/GSFC Space Physics Data Facility OMNIWeb service (NASA, 2024b) and Kp index is available via Matzka ( 2021).

Authors=Edward-Inatimi, N. O.; Owens, M. J.; Barnard, L.; Turner, H.; Marsh, M.; Gonzi, S.; Lang, M.; Riley, P.
Title=Adapting Ensemble-Calibration Techniques to Probabilistic Solar-Wind Forecasting, 2024, doi:10.1029/2024SW004164, ID=32519768
journal=Space Weather
Keywords found:spdf, space physics data facility, omni, omniweb
Sample usage ( BODY ) =OMNI data are provided through NASA’s Space Physics Data Facility (SPDF). We here use 1-hr resolution data. HUXt Forecasts All hindcasts are generated using HUXt driven by the output of the MAS coronal model (Linker et al., 1999; Riley et al., 2012).
Sample usage ( BODY ) =The OMNI database is set of inter-calibrated near-Earth solar-wind observations (King Papitashvili, 2005). OMNI data are provided through NASA’s Space Physics Data Facility (SPDF).
Sample usage ( BODY ) =Data Availability Statement Verification data was sourced from OMNI solar-wind observations which can be found: https://omniweb.gsfc.nasa.gov/form/dx1.html . HUXt is an open-source solar-wind model available at: Owens and Barnard ( 2024).

Authors=Matthia, Daniel; Berger, Thomas
Title=Radiation Exposure and Shielding Effects on the Lunar Surface, 2024, doi:10.1029/2024SW004095, ID=32519782
journal=Space Weather
Keywords found:omni
Sample usage ( BODY ) =The radiation environment in space is composed mostly of the omni-present galactic cosmic radiation (GCR), which is modulated in its intensity during the solar activity cycle and which gives rise to a permanent background radiation that is strongest in free space but is also present in low-Earth orbit (LEO) and can even be measured on ground.

Authors=Wang, Ruyao; Wang, Jianhui; Liang, Tuo; Zhang, Huixiong
Title=Short-Term Prediction of the Dst Index and Estimation of Efficient Uncertainty Using a Hybrid Deep Learning Network, 2024, doi:10.1029/2024SW004002, ID=32519800
journal=Space Weather
Keywords found:spdf, space physics data facility, omni, omniweb
Sample usage ( BODY ) =Data Set The data set comprises hourly averages of solar wind parameters and the Dst index, obtained from NASA’s National Space Science Data Center OMNI database ( https://spdf.gsfc.nasa.gov ). Eight solar wind parameters were considered as external inputs, including the IMF, magnetic field Bz component, plasma speed, plasma speed x component, plasma temperature, plasma density, plasma pressure, and the electric field.
Sample usage ( BODY ) =Data Availability Statement We acknowledge the use of NASA/GSFC’s Space Physics Data Facility’s OMNIWeb service and OMNI data (NASA/GSFC, 2024). All the results have been made available on GitHub (Author, 2024a) and archived in Zenodo ( https://10.5281/zenodo.13165424 ).

Authors=Mischel, Simon; Kronberg, Elena A.; Escoubet, C. P.
Title=Evaluating Proton Intensities for the SMILE Mission, 2024, doi:10.1029/2024SW00393410.22541/essoar.171415897.71591373/v1, ID=32519818
journal=Space Weather
Keywords found:space physics data facility, omni, omniweb
Sample usage ( BODY ) =Additionally, we recognize the utilization of the OMNIWeb service and OMNI data from NASA/GSFC’s Space Physics Data Facility (King Papitashvili, 2005). The code and data set used to derive the linear regression model can be found via (Mischel et al., 2024).
Sample usage ( BODY ) =As predicting parameters for solar, solar wind and geomagnetic activity we used variables from the OMNI database ( https://omniweb.gsfc.nasa.gov/ ), see also King and Papitashvili ( 2005).
Sample usage ( ABSTRACT ) =To achieve this task we utilized 14 years of data sourced from the Cluster’s RAPID experiment and NASA’s OMNI database. This data was then aligned with the Solar wind-Magnetosphere-Ionosphere Link Explorer (SMILE) mission’s trajectory, to increase model accuracy in the relevant regions.

Authors=Madhanakumar, Mahith; Spicher, Andres; Vierinen, Juha; Oksavik, Kjellmar; Coster, Anthea J.; Huyghebaert, Devin Ray; Martin, Carley J.; Haggstrom, Ingemar; Paxton, Larry J.
Title=The Growth and Decay of Intense GNSS Amplitude and Phase Scintillation During Non-Storm Conditions, 2024, doi:10.1029/2024SW004108, ID=32519826
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =In this study, we make use of the poleward and equatorward auroral boundary locations obtained from the Auroral Environmental Data Record (EDR). OMNI In order to study the impact of Interplanetary Magnetic Field (IMF) on the ionospheric dynamics and hence on GNSS scintillation we make use of the 1-min high resolution OMNI data set timeshifted to the nose of Earth’s bow shock (King Papitashvili, 2005).
Sample usage ( ACK ) =The IMF and solar wind data are provided by the NASA OMNIWeb service. The SYMH and the AE indices (AL, AU, AE) used in this paper were provided by the WDC for Geomagnetism, Kyoto ( http://wdc.kugi.kyoto-u.ac.jp/wdc/Sec3.html ).

Authors=Moraes-Santos, S. P.; Candido, C. M. N.; Becker-Guedes, F.; Nava, B.; Klausner, V.; Borries, C.; Chingarandi, F. S.; Osanyin, T. O.
Title=Influence of Solar Wind High-Speed Streams on the Brazilian Low-Latitude Ionosphere During the Descending Phase of Solar Cycle 24, 2024, doi:10.1029/2024SW003873, ID=32519830
journal=Space Weather
Keywords found:spdf, omni, omniweb, iri, international reference ionosphere
Sample usage ( BODY ) =These interplanetary parameters were measured by instruments onboard the ACE satellite and provided by the SPDF OMNIWeb database ( https://omniweb.gsfc.nasa.gov/ ). They are the Solar wind speed, Vsw (km/s); the proton temperature, Tp (10 6 K); the proton density, Np (1/cm3); the dynamic pressure, P (nPa); the interplanetary magnetic field, IMF |B| and its components: Bx, By and Bz (nT); the interplanetary electric field Ey (mV/m) and the solar flux parameter/index, F10.7 (SFU), where 1 SFU = 10 -22 W/Hz m 2 (Tapping, 2013).
Sample usage ( BODY ) =Additionally, we utilized geomagnetic data provided by OMNI Web, which includes the symmetric H geomagnetic field component (SymH) in nT, the 3-hr planetary K from Potsdam, and the auroral electrojet index (AE) in nT.
Sample usage ( ACK ) =The authors gratefully acknowledge the OMNI data supplied by the GSFC/SPDF OMNIWeb interface at https://omniweb.gsfc.nasa.gov.We would like to express our sincere gratitude to the World Data Center for Geomagnetism, Kyoto, for providing the data on the five quietest days.
Sample usage ( BODY ) =The drifts calculated using magnetometer data were provided by Yizengaw et al. ( 2020). The drift model is in IRI model (Bilitza, 2018) and the code can be accessed at Fejer and Scherliess ( 1997b), Fejer and Scherliess ( 1997a).
Sample usage ( BODY ) =Both models are in the International Reference Ionosphere model 2020 (Bilitza, 2018; Bilitza et al., 2022).

Authors=Forsythe, Victoriya V.; Galkin, Ivan; McDonald, Sarah E.; Dymond, Kenneth F.; Fritz, Bruce A.; Burrell, Angeline G.; Zawdie, Katherine A.; Drob, Douglas P.
Title=PyIRTAM: A New Module of PyIRI for IRTAM Coefficients, 2024, doi:10.1029/2024SW00396510.22541/essoar.171838439.90097132/v1, ID=32519841
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =Introduction The International Reference Ionosphere (IRI) empirical model estimates the electron density in the ionosphere based on a climatological analysis of ionospheric electron density profiles (EDPs) over several decades. International Reference Ionosphere is the gold standard for the ionospheric community.
Sample usage ( ABSTRACT ) =PyIRI introduced a novel approach to the computation of the global and diurnal functions and their matrix multiplication with Consultative Committee on International Radio (CCIR) coefficients or the International Union of Radio Science (URSI) coefficients, that enabled this global approach for the density specification. Since the International Reference Ionosphere-based Real-Time Assimilative Model (IRTAM) produces coefficients in a similar format as CCIR/URSI coefficients, the PyIRI computational approach was extended to work with IRTAM coefficients.

Authors=Brandt, Daniel A.; Ridley, Aaron J.
Title=NEUVAC: Nonlinear Extreme Ultraviolet Irradiance Model for Aeronomic Calculations, 2024, doi:10.1029/2024SW00404310.22541/essoar.171995172.28471337/v1, ID=32519843
journal=Space Weather
Keywords found:iri, international reference ionosphere
Sample usage ( BODY ) =Even with the numerous modeling paradigms previously mentioned, the space weather community has continued to rely on proxies in operational situations; atmospheric models that see widespread use by the community, including the NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM) (Qian et al., 2014), the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics Model (CTIPe) (Codrescu et al., 2012), The Whole Atmosphere Community Climate Model (WACCM) (Liu et al., 2018), the Whole Atmosphere Model-Ionosphere Plasmasphere Electrodynamics Forecast System (WAM-IPE) (Akmaev et al., 2008; Maruyama et al., 2016; Zhan et al., 2024), and the International Reference Ionosphere (IRI) (Bilitza et al., 2022) all use either F10.7 directly, or use the EUVAC, HEUVAC, or HFG models driven by F10.7 to estimate EUV input into the upper atmosphere.

Authors=Tulasi Ram, S.; Veenadhari, B.; Dimri, A. P.; Bulusu, J.; Bagiya, M.; Gurubaran, S.; Parihar, N.; Remya, B.; Seemala, G.; Singh, Rajesh; Sripathi, S.; Singh, S. V.; Vichare, G.
Title=Super-Intense Geomagnetic Storm on 10-11 May 2024: Possible Mechanisms and Impacts, 2024, doi:10.1029/2024SW004126, ID=32519889
journal=Space Weather
Keywords found:cdaweb, spdf, space physics data facility, omni
Sample usage ( BODY ) =The magnetic field (Bz and By) data from the GOES-18 satellite at 10 Hz resolution are downloaded from https://cdaweb.gsfc.nasa.gov/pub/data/goes/goes18/ . The TEC map data from the worldwide GNSS receiver network are downloaded from the Madrigal database at Millstone Hill ( ).
Sample usage ( ACK ) =Acknowledgments The authors acknowledge the open data policy of NASA’s DSCOVR and GOES-18 data products. We also acknowledge NASA’s SPDF for the solar wind and the Madrigal database at Millstone Hill for worldwide GNSS-TEC data products.
Sample usage ( BODY ) =The SWDP, IMF Bz and Sym-H data of past geomagnetic storms are obtained from Omni web interface of NASA’s Space Physics Data Facility ( https://omniweb.gsfc.nasa.gov/form/omni\_min\_def.html ).

Authors=Lee, Wonseok; Song, In-Sun; Shim, Ja Soon; Liu, Guiping; Jee, Geonhwa
Title=The Impact of Lower Atmosphere Forecast Uncertainties on WACCM-X Prediction of Ionosphere-Thermosphere System During Geomagnetic Storms, 2024, doi:10.1029/2024SW004137, ID=32519943
journal=Space Weather
Keywords found:spdf, omniweb
Sample usage ( BODY ) =For the Weimer model, WACCM-X utilizes solar and geomagnetic indices obtained from NASA GSFC/SPDF OMNIweb interface ( https://omniweb.gsfc.nasa.gov/ow.html ). In this study, two geomagnetic storm cases are considered.

Authors=Meredith, Nigel P.; Cayton, Thomas E.; Cayton, Michael D.; Horne, Richard B.
Title=Strong Relativistic Electron Flux Events in GPS Orbit, 2024, doi:10.1029/2024SW004042, ID=32519958
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =This highlights the difficulty when trying to accurately compare the omni-directional fluxes from BDD-IIR with the spin-averaged fluxes from the Van Allen probes with differences being expected primarily due to the different nature of the data products and the different averaging times.
Sample usage ( BODY ) =The solar wind data, geomagnetic activity indices and sunspot numbers are available from the NASA GSFC OMNI website ( https://omniweb.gsfc.nasa.gov/ ). The results and data shown in this study can be downloaded from the UK Polar Data Centre at Meredith et al. ( 2024).

Authors=Householder, I. M.; Duderstadt, K. A.; Pettit, J. M.; Johnson, A. T.; Huang, C. -L.; Crew, A. B.; Klumpar, D. M.; Raeder, T.; Sample, J. G.; Shumko, M.; Smith, S. S.; Spence, H. E.
Title=Comparisons of Energetic Electron Observations Between FIREBIRD-II CubeSats and POES/MetOp Satellites From 2018 to 2020, 2024, doi:10.1029/2024SW00405610.22541/au.172124685.54018254/v1, ID=32519962
journal=Space Weather
Keywords found:sscweb
Sample usage ( BODY ) =Event Selection This study analyzes 64 conjunction events between FU3/FU4 and POES/MetOp, chosen to capture regions of peak precipitation using the Satellite Situation Center (SSCWeb). A conjunction is defined as the time and location when either FU3 or FU4 pass in close proximity to any of the five POES/MetOp satellites (NOAA-15, NOAA-18, NOAA-19, MetOp-1b, MetOp-2a).

Authors=Liu, Peng; Yokoyama, Tatsuhiro; Sori, Takuya; Yamamoto, Mamoru
Title=Channel Mixer Layer: Multimodal Fusion Toward Machine Reasoning for Spatiotemporal Predictive Learning of Ionospheric Total Electron Content, 2024, doi:10.1029/2024SW004121, ID=32519967
journal=Space Weather
Keywords found:omni, iri, international reference ionosphere
Sample usage ( BODY ) =In this research, a new standard data set with the largest scale, named as IonoElectron, is released where the global TEC maps and their corresponding external factors for diurnal, seasonal, spatial, solar and geomagnetic activity dependence provided by OMNI data set are packaged together and saved in the specified format of machine learning software for the high speed accessing.
Sample usage ( BODY ) =Function-based models such as International Reference Ionosphere (IRI, Rawer et al. ( 1978)) and NeQuick (Nava et al., 2008) always fit the spatiotemporal distribution of ionospheric parameters with the complex functions.

Authors=Carmo, C. S.; Dai, L.; Wrasse, C. M.; Barros, D.; Takahashi, H.; Figueiredo, C. A. O. B.; Wang, C.; Li, H.; Liu, Z.
Title=Ionospheric Response to the Extreme 2024 Mother’s Day Geomagnetic Storm Over the Latin American Sector, 2024, doi:10.1029/2024SW004054, ID=32519993
journal=Space Weather
Keywords found:omni, omniweb
Sample usage ( BODY ) =Additionally, IMF Bz and Ey data were accessed via OMNIWeb ( https://omniweb.gsfc.nasa.gov/form/omni_min.html ).