Quantifying Contributions of External Drivers to the Global Ionospheric State by Xing Meng, Olga P. Verkhoglyadova

“…By computing normalized transfer entropy on 18 years of GIM TEC, F10.7, solar wind, and lower atmospheric data, we obtain the predictive information transfer from the present drivers to the global ionospheric state at various future times. …”
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Analysis of Long‐Term GIC Measurements in Transformers in Austria by D. Albert, P. Schachinger, R. L. Bailey, H. Renner, G. Achleitner

“…Abstract Geomagnetically induced currents (GICs), a result of solar wind interaction with the Earth's magnetic field and the resistive ground, are known to flow in power transmission grids, where they can lead to transformer damage and grid operation problems. …”
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Sustainable Energy Transitions: Overcoming Negative Externalities by U. Yе. Pysmenna, G. S. Trypolska

“…Transitions to more clean and low-carbon energy systems using energy technologies such as solar, wind, small hydro, biomass, waste management, e-vehicles are in the scope of this paper. …”
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Investigating the Trip of a Transformer in Sweden During the 24 April 2023 Storm by A. P. Dimmock, V. Lanabere, A. Johlander, L. Rosenqvist, E. Yordanova, S. Buchert, S. Molenkamp, J. Setréus

“…In this paper, we investigate this event by studying the solar wind properties as well as geomagnetic disturbances. …”
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Uncertainty Analysis of Energy Production for a 3 × 50 MW AC Photovoltaic Project Based on Solar Resources by Irfan Jamil, Jinquan Zhao, Li Zhang, Syed Furqan Rafique, Rehan Jamil

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The Time-Series Production Simulation in Cost Management of New Energy Grid Connection Under the Internet of Things by Shurui Wang

“…The model considers different types of new energy resources, including solar, wind, and a time-series production simulation method is employed to simulate the energy production process. …”
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Development of a High‐Latitude Convection Model by Application of Machine Learning to SuperDARN Observations by W. A. Bristow, C. A. Topliff, M. B. Cohen

“…The features used to train the model were the interplanetary magnetic field components Bx, By, and Bz; the solar wind velocity, vsw; the auroral indices, Au and Al; and the geomagnetic index, SYM‐H. …”
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GOLD Mission's Observation About the Geomagnetic Storm Effects on the Nighttime Equatorial Ionization Anomaly (EIA) and Equatorial Plasma Bubbles (EPB) During a Solar Minimum Equin... by Deepak Kumar Karan, Richard W. Eastes, Robert E. Daniell, Carlos R. Martinis, William E. McClintock

“…On 27 September the solar wind conditions were favorable for prompt penetration electric fields to influence the equatorial ionosphere over extended longitudes. …”
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Time‐Lagged Effects of Ionospheric Response to Severe Geomagnetic Storms on GNSS Kinematic Precise Point Positioning by Zhe Yang, Y. T. Jade Morton

“…The study discusses these time lag effects concerning the intensity of various ionospheric disturbances triggered by the interactions among the solar wind, magnetosphere, and ionosphere during geomagnetic storms. …”
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Prediction of Radiation Belts Electron Fluxes at a Low Earth Orbit Using Neural Networks With PROBA‐V/EPT Data by Edith Botek, Viviane Pierrard, Alexandre Winant

“…Different combinations of time series inputs involving Solar Wind and geomagnetic data are tested, based on previous knowledge of their impact onto the high energy radiation fluxes. …”
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Solar Origins of August 26, 2018 Geomagnetic Storm: Responses of the Interplanetary Medium and Equatorial/Low‐Latitude Ionosphere to the Storm by A. O. Akala, O. J. Oyedokun, P. O. Amaechi, K. G. Simi, A. Ogwala, O. A. Arowolo

“…The storm was driven by an aggregation of weak Coronal Mass Ejection (CME) transients and Corotating Interaction Regions/High Speed Streams (CIR/HSSs). The solar wind energy which got transferred into the magnetosphere drove electrical currents, that penetrated down into the ionosphere to produce weak Prompt Penetration Electric Field (PPEF) (0.3 mV/m). …”
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Nanoscale characterization of space weathering in lunar samples by A. M. Grice, P. C. Stancil, M. Ghafariasl, S. Singh, S. Gamage, M. J. Schaible, Y. Abate, K. Lang, T. M. Orlando

“…Spatially localized 1050 cm−1/935 cm−1 band ratios in Nano-FTIR hyperspectral maps may further reflect impact-induced shock nanostructures, while shifts in silicate band positions indicate accumulated radiation damage at the nanoscale from prolonged space weathering due to micrometeorites, solar wind, energetic x-rays and cosmic ray bombardment. …”
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Review of Fast Solar Jets and Coronal Mass Ejections by Sima Zeighami, Ehsan Tavabi

“…Following the occurrence of these phenomenon in the Sun, the solar wind blows with greater speed and intensity and sends energetic charged particles into the space of the solar system. …”
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Models for plasmasphere and plasmatrough density and average ion mass including dependence on L, MLT, geomagnetic activity, and phase of the solar cycle by Richard E. Denton, Kazue Takahashi, David P. Hartley

“…Our models depend on position, the solar extreme ultraviolet (EUV) F10.7 flux, geomagnetic activity parameters such as Kp, AE, Dst, and the solar wind dynamic pressure. Formulas for M are presented with or without ne as an input parameter. …”
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Yield Function of the DOSimetry TELescope Count and Dose Rates Aboard the International Space Station by A. S. Caprotti, M. Brüdern, S. Burmeister, B. Heber, K. Herbst

“…The flux of these particles is altered by the magnetized solar wind in the heliosphere and the Earth's magnetic field. …”
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Modeling Ionospheric TEC Using Gradient Boosting Based and Stacking Machine Learning Techniques by Ayanew Nigusie, Ambelu Tebabal, Roman Galas

“…The models relied on input variables that represent solar activity, geomagnetic activity, season, time of the day, interplanetary magnetic field, and solar wind. The models were trained using the VTEC data from January 2011 to December 2018, excluding the testing data. …”
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Radiation Belt Model Including Semi‐Annual Variation and Solar Driving (Sentinel) by C. Katsavrias, S. Aminalragia‐Giamini, C. Papadimitriou, I. A. Daglis, I. Sandberg, P. Jiggens

“…In this paper, we present a new approach for radiation belt modeling using Machine Learning methods driven solely by Solar wind speed and pressure, Solar flux at 10.7 cm, and the angle controlling the Russell‐McPherron effect (θRM). …”
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Modeling Ring Current Proton Fluxes Using Artificial Neural Network and Van Allen Probe Measurements by Jinxing Li, Jacob Bortnik, Xiangning Chu, Donglai Ma, Sheng Tian, Chih‐Ping Wang, Jerry W. Manweiler, Louis J. Lanzerotti

“…The present study aims to specify a global and time‐varying distribution of ring current proton using geomagnetic indices and solar wind parameters with their history as input. We train an artificial neural network (ANN) model to reproduce proton fluxes measured by the Radiation Belt Storm Probes Ion Composition Experiment instrument onboard Van Allen Probes. …”
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Substorm‐Time Ground dB/dt Variations Controlled by Interplanetary Shock Impact Angles: A Statistical Study by Denny M. Oliveira, James M. Weygand, John C. Coxon, Eftyhia Zesta

“…We use a sub‐set of a shock data base with 237 events observed in the solar wind at L1 upstream of the Earth, and large arrays of ground magnetometers at stations located in North America and Greenland. …”
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Opening the Black Box of the Radiation Belt Machine Learning Model by Donglai Ma, Jacob Bortnik, Xiangning Chu, Seth G. Claudepierre, Qianli Ma, Adam Kellerman

“…The Outer RadIation belt Electron Neural net (ORIENT) model uses only solar wind conditions and geomagnetic indices as input features. …”
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