Results 131 to 140 of about 18,554 (245)
Abstract On 20 January 2024, a deep‐focus earthquake (Mw 6.6, depth 607 km) struck near Tarauacá, Brazil, within the subducted South America Nazca Plate. Although it produced no surface damage, the event generated clear co‐seismic ionospheric disturbances (CSIDs) detectable in GNSS‐based Total Electron Content (TEC) data from the Brazilian RBMC network.
Oluwasegun M. Adebayo +3 more
wiley +1 more source
Solar sources of geomagnetic storms
Because geomagnetic storms can have important effects on communications and electrical power distribution, an ability to predict these storms has considerable value. We have recently come to understand that coronal mass ejections (CMEs) cause most large geomagnetic storms during the most active part of the solar cycle [Gosling et al., 1991].
openaire +1 more source
GOES‐R Series X‐Ray Sensor (XRS): 2. On‐Orbit Measurements and Calibrations
Abstract An X‐Ray Sensor (XRS) has been onboard each of the National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellites (GOES) since 1975. XRS measures full‐disk soft X‐ray irradiance in two wavelength bands, 0.05–0.4 nm and 0.1–0.8 nm.
Janet L. Machol +17 more
wiley +1 more source
Thermospheric Heating and Cooling Times During Geomagnetic Storms, Including Extreme Events [PDF]
We present the first quantitative calculations of thermospheric heating and cooling times for geomagnetic storms of different intensity, including extreme events.
Oliveira, Denny M., Zesta, Eftyhia
core +1 more source
Abstract This study presents a cross‐comparison of mesosphere and lower thermosphere (MLT) neutral temperatures between 88 and 110 km measured by ICON/Michelson Interferometer for Global High‐resolution Thermospheric Imaging (MIGHTI) and Thermosphere Ionosphere Mesosphere Energetics and Dynamics/Sounding of the Atmosphere using Broadband Emission ...
Manbharat Dhadly +4 more
wiley +1 more source
We solve the problem of recognizing geomagnetic storms from matrix time series of observations with the URAGAN muon hodoscope, using deep learning neural networks.
Getmanov V. G. +5 more
doaj +1 more source
Solar Wind‐Magnetosphere‐Ionosphere Coupling During the October 2024 Storms
Abstract Two geomagnetic storms occurred in October 2024 (Oct 6‐9 and 10–12), driven by the impact of a series of interplanetary coronal mass ejections on the magnetosphere. The first was a moderate storm, with peak Sym‐H near −150 nT, whereas the second was intense, Sym‐H reaching −340 nT.
S. E. Milan +9 more
wiley +1 more source
Validation of VERB‐3D Simulation Results in Response to the COSPAR ISWAT Challenge
Abstract In response to the first long‐term simulation challenge issued by the COSPAR International Space Weather Action Team (ISWAT) G3‐04 team (“Internal Charging Effects and the Relevant Space Environment”), we evaluate the performance of the Versatile Electron Radiation Belt‐3D model by simulating the radiation belt electron dynamics for the entire
Xingzhi Lyu +6 more
wiley +1 more source
A Fully Connected Neural Network for Fast Estimation of Quasi‐Linear Diffusion Coefficients
Abstract Wave–particle interactions are a fundamental driver of electron radiation belt dynamics. Quantifying their effects through quasi‐linear theory requires diffusion coefficients, but their direct evaluation involves nested integrations and is computationally expensive, limiting their use in real‐time applications.
Mengli Tan +4 more
wiley +1 more source
The State of Solar Wind Heavy Ions in Interplanetary Coronal Mass Ejection–Driven Geomagnetic Storms
During geomagnetic storms, which are the primary periods for heavy ions from the solar wind to enter Earth’s magnetospheric space, the charge state of solar wind heavy ions during these storms has significant implications for studying the distribution ...
Cong Wang, Fei He, Xiaoxin Zhang
doaj +1 more source

