Uncovering the Drivers of Responsive Ionospheric Dynamics to Severe Space Weather Conditions: A Coordinated Multi-Instrumental Approach

Uncovering the Drivers of Responsive Ionospheric Dynamics to Severe Space Weather Conditions: A Coordinated Multi‐ Instrumental Approach Andrés Calabia 1 , Nadia Imtiaz 2 , David Altadill 3 , Yury Yasyukevich 4 , Antoni Segarra 3 , Fabricio S. Prol 5 , Binod Adhikari 6 , Luis del Peral 1 , Maria Dolores Rodriguez Frias 1,7 , and Iñigo Molina 8 1 Department of Physics and Mathematics, University of Alcala, Alcalá de Henares, Spain, 2 Theoretical Physics Division, Pakistan Institute of Nuclear Science and Technology, Islamabad, Pakistan, 3 Observatori de l’Ebre (OE), CSIC ‐ Universitat Ramon Llull, Roquetes, Spain, 4 Institute of Solar‐Terrestrial Physics of Siberian Branch of Russian Academy of Sciences, Irkutsk, Russia, 5 Department of Navigation and Positioning, Finnish Geospatial Research Institute, National Land Survey of Finland, Espoo, Finland, 6 Department of Physics, St. Xavier's College, Tribhuvan University, Kathmandu, Nepal, 7 C.L.P.U. (Centro de Láseres Pulsados), Salamanca, Spain, 8 School of Land Surveying, Geodesy and Mapping Engineering, Universidad Politécnica de Madrid, Madrid, Spain Abstract Space‐weather conditions can often have a detrimental impact on satellite communications and limited experimental data has made it challenging to understand the complex processes that occur in the upper atmosphere. To overcome this challenge, we utilized a coordinated multi‐instrumental dataset consisting of GNSS airglow remote sensing, ionosonde, magnetometer, and in‐situ satellite data to investigate plasma depletions. We present a case study focused on the geomagnetic storm that occurred on 27 February 2014. During the storm, GNSS positioning errors exceeded undisturbed levels by at least 2 times, and ionospheric corrections reached amplitudes of up to ±20 m at the Rabat station. We identified 3 large depletions that were most likely generated by sudden vertical ionospheric drifts that began at approximately 17:00 UTC at sunset in Morocco and the southern regions of Spain. These drifts reached ∼500 m/s and lasted until 22:00 UTC. The observed depletions propagated to the northeast, as seen through ionosonde echoes and ground‐based airglow images. Satellite limb‐images revealed an ionospheric uplift of about 100 km due to the storm, consistent with ionosondes in Spain. The observed local anomalies may be influenced by variations in equatorial electric current flows, which are correlated with fluctuations in ground‐based magnetometer data. These variations are likely a result of the effects of the inner radiation belt on the development of plasma bubbles in the African longitude sector. Sudden enhancements in upward E ×B drift caused ionospheric uplift to higher altitudes, enhancing the “fountain effect” and shifting the Equatorial Ionospheric Anomaly crests to higher latitudes. 1. Introduction The ionosphere is a region in the upper atmosphere extending from approximately 50 km to 2,000 km above the Earth’s surface that is formed mainly through photoionization by solar radiation. Irregular variations in the ionosphere can significantly impact radio communications satellite operation and navigation, Positioning‐ Navigation‐Timing (PNT), Global Navigation Satellite Systems (GNSS), Earth’s Remote Sensing, and numerous other applications that rely on the propagation of radio waves. Equatorial Plasma Bubbles (EPBs) refer to regions of depleted plasma with respect to the background ionosphere, and are the main form of ionospheric irregularities in the equatorial F‐region (Kelley, 1989). EPBs are transitory events whose dynamics are not yet fully understood, and existing models struggle to accurately represent the actual variations that occur in practical applications like GNSS and PNT. EPBs can have a significant negative impact on radio‐based technologies, like communications, navigation, and other space weather applications. EPBs can irregularly scatter and refract irregularly the radio wave signals traversing through them, causing rapid changes in signal amplitude and phase known as scintillations (Hargreaves, 1992), resulting in anomalous fading or distortion of electromagnetic signals. Scintillation can occur when the ionosphere is disturbed by solar and geomagnetic activity, particularly during geomagnetic storms, when the Earth’s magnetic field is distorted by highly variable solar activity. Recently, several studies have provided valuable insights into the behavior of EPBs under different conditions and their interactions with various RESEARCH ARTICLE 10.1029/2023JA031862 Key Points: •Large plasma depletions at midlatitude ionosphere during February 2014 storm were studied using coordinated multi‐instrumental dataset •Ionospheric corrections reached amplitudes of up to ±20 m at GNSS sensors in Morocco •Plasma depletions propagate in the North‐East direction, and storm‐time enhanced E ×B drift caused an uplift of the ionosphere of 100 km Supporting Information: Supporting Information may be found in the online version of this article. Correspondence to: A. Calabia, [email protected]; [email protected] Citation: Calabia, A., Imtiaz, N., Altadill, D., Yasyukevich, Y., Segarra, A., Prol, F. S., et al. (2024). Uncovering the drivers of responsive ionospheric dynamics to severe space weather conditions: A coordinated multi‐instrumental approach. Journal of Geophysical Research: Space Physics, 129, e2023JA031862. https://doi.org/10. 1029/2023JA031862 Received 6 JULY 2023 Accepted 15 FEB 2024 Author Contributions: Conceptualization: Andrés Calabia Data curation: Andrés Calabia Formal analysis: Andrés Calabia Funding acquisition: Andrés Calabia, Luis del Peral, Maria Dolores Rodriguez Frias Investigation: Andrés Calabia, Nadia Imtiaz, David Altadill, Yury Yasyukevich, Antoni Segarra, Fabricio S. Prol, Binod Adhikari, Luis del Peral, Maria Dolores Rodriguez Frias, Iñigo Molina Methodology: Andrés Calabia Project administration: Andrés Calabia ©2024. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. CALABIA ET AL. 1 of 24 geophysical factors. The research conducted by Wu et al. (2021) focused on the unusual evolution of EPBs during a geomagnetically quiet night. They found that variations in ionospheric plasma vertical drift and zonal wind were key factors in this unusual evolution. Santos et al. (2016) investigated the zonal drift reversal of EPBs during storm time over the Brazilian region. Their findings highlighted the role of disturbance Hall electric fields in causing this reversal. Smith and Heelis (2017) studied the variations in the occurrence and spatial scale of EPBs in relation to local time, longitude, season, and solar activity. Their research revealed that EPBs occur late in local time, primarily after midnight in all longitude sectors during solar minimum conditions. It is well known that the Sun’s high‐energy ultraviolet and X‐ray radiation ionizes neutral molecules in the air, creating an electrically conductive atmosphere, particularly during midday hours. Additionally, the Sun’s light heats up the atmosphere, which generates winds that power an ionospheric dynamo, creating electric currents. The Equatorial Electro‐Jet (EEJ), an eastward electric field that appears along the magnetic equator at an altitude of approximately 100 km from dawn to dusk, results from this electric current flow (Chapman, 1951; Richmond, 1973). After the plasma became lifted up across the horizontal magnetic field lines over the magnetic dip equator by the vertical E ×B plasma drift, gravitational forces parallel to Earth’s magnetic field, along with plasma pressure gradients, cause plasma to move at approximately ±15–20° dip latitude. This process results in the formation of the Equatorial Ionospheric Anomaly (EIA). The EIA is characterized not only by a trough region over the dip equator (Duncan, 1960), but also by the two crests located at approximately ±15–20° dip latitude. The exact position of these crests can vary depending on magnetic activity. During geomagnetic storms, an equatorial eastward prompt penetration electric field (PPEF) subsequently enhances the vertical E ×B plasma drift, creating strong variations in the system. While the Pre‐Reversal Enhancement (PRE) is an everyday phenomenon, triggered by sunset conditions, it becomes particularly amplified during storm‐time variations. This amplification is especially noticeable at the sunset equator, where the PRE deepens at the EIA trough and generates localized plasma depletions in low‐latitude regions (Rishbeth, 1971). The eastward PPEF during storms further enhances this effect. Despite the advancements in ionospheric modeling (Radicella, 2009; Bilitza et al., 2022; Qian et al., 2014; Huba et al., 2000), existing models used in practical applications are unable to represent small structures such as plasma depletions that may only span a few hundred kilometers (see Figure S1 in Supporting Information S1). However, modern measurement techniques are capable of sensing and estimating the dynamics of small ionospheric features (Martinis et al., 2018), such as ground‐based all‐sky cameras that measure electromagnetic radiation in the ultraviolet, visible, or infrared range. Other techniques include ionosonde (Gilli et al., 2018; Jerez et al., 2020), GNSS receivers (Socola & Rodrigues, 2022; Yu & Liu, 2021), radio telescopes (Mangla & Datta, 2023), and space‐based sensors, such as Global‐scale Observations of Limb and Disk (GOLD) of National Aeronautics and Space Administration (NASA) (e.g., Eastes et al. (2020)) that can measure EPBs. Ionospheric irregularities can manifest as spread F in ionograms, EPBs in radar maps, and traveling ionospheric disturbances (TIDs) in optical images and Total Electron Content (TEC) maps (Bowman, 1991; Kelley & Fukao, 1991; Ding et al., 2011). These irregularities can occur with spatial scales ranging from meters to several thousands of kilometers. Numerous studies have demonstrated that various instability mechanisms are responsible for the generation of plasma irregularities. The global climatology of ionospheric irregularities is primarily influenced by solar activity and magnetic field topology (Liu, Hernández‐Pajares, et al., 2021; Liu, Zhou, et al., 2021). Given the importance of understanding the impact of the ionosphere on countless applications, this work aims to contribute to a better understanding of space weather coupling phenomena in the upper atmosphere through the analysis and characterization of localized plasma depletions. We utilize data from a range of sources, including GNSS, airglow remote sensing, ionosonde, magnetometers, and in‐situ satellite data, to investigate the possible drivers of responsive ionospheric dynamics to the geomagnetic storm of 27 February 2014. In particular, this work focuses on the following aspects: •Investigating ionospheric variability through multi‐instrument data and analyzing the localized processes that result from the interaction between the solar wind‐magnetosphere and the ionosphere, specifically the characterization of localized plasma depletions for this particular case. •Analyzing the potential of advanced sensing instruments to map the ionospheric disturbances during geomagnetic storms, with particular interest in EPBs. Resources: Andrés Calabia, David Altadill Software: Andrés Calabia Supervision: Andrés Calabia, David Altadill, Luis del Peral, Maria Dolores Rodriguez Frias Validation: Andrés Calabia Visualization: Andrés Calabia Writing – original draft: Andrés Calabia Writing – review & editing: Andrés Calabia, Nadia Imtiaz, David Altadill, Yury Yasyukevich, Antoni Segarra, Fabricio S. Prol, Binod Adhikari, Luis del Peral, Maria Dolores Rodriguez Frias, Iñigo Molina Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 2 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License •Characterizing the behavior of radio signals as they pass through the ionosphere and detecting anomalies is crucial to understanding the patterns and temporal variations associated with these EPBs and their contributions to practical applications. In the following section, we introduce the data and methods used in our study. We then present the results of our analyses in Section 3and discuss the implications of our findings in Section 4. In the final section, we will provide our conclusions and present hypotheses based on our experimental results. 2. Data, Products, and Models for the Analysis To carry forward this investigation, we use a variety of data, products, models, and indices related to the Sun– Earth connection. Particularly, these data include solar wind (SW), Interplanetary Magnetic Field (IMF) components, Interplanetary Electric Field (IEF) zonal East–West component (Ey), and geomagnetic activity indices such as the amplitude planetary index (Am) of geomagnetic variation, the Northern Polar Cap index (PCN), the Auroral Electrojet (AE) index, and the symmetric disturbance in the horizontal intensity of the magnetic field vector (SYM‐H, ASY‐D, and ASY‐H). The solar wind parameters and PCN index are obtained from the NASA OMNI website (http://omniweb.gsfc. nasa.gov/), the Am index (Mayaud et al., 2023) is obtained from the EOST (École and Observatoire des Sciences de la Terre) (https://eost.unistra.fr/en/eost/eost), and the AE (Davis & Sugiura, 1966) and SYM‐H (Zhao et al., 2021) indices are obtained from the World Data Center Kyoto (https://wdc.kugi.kyoto‐u.ac.jp/). These websites provide information on the derivation and meaning of the different data and indices. For instance, while the SYM‐H index measures the ring current intensity, the Am index is susceptible to any geophysical current system, including magnetopause currents, field‐aligned currents, or auroral electrojet. The ring current is mainly generated by pressure gradient and magnetic curvature drift. The IEF East–West component (Ey = − Vx ×Bz; where Vx is the x component of the solar wind velocity and Bz is the z component of the IMF) moves the plasma in the magnetosphere from the tail to Earth, and helps to provide the seed population for the ring current. The Polar Cap index measures the transpolar convection of magnetospheric plasma and embedded magnetic fields driven by the interaction with the solar wind, and the merging electric field (Em) assumes that there is an equal magnitude of the electric field in the solar wind, the magnetosheath, and on the magnetospheric sides of the magnetopause (Kan & Lee, 1979): Em =VSW  B2 y+B2 z √sin2(θ 2)(1) In this equation, By and Bz are the IMF components, V SW is the solar wind speed, and θ is the IMF clock angle in geocentric solar magnetospheric (GSM) coordinates. We use predictive ionospheric models to investigate abrupt ionospheric anomalies during geomagnetic storms, the empirical model developed at Calabia and Jin (2019,2020), which is based on a lower‐dimensional reduction of vertical Total Electron Content (vTEC) data from 2003 to 2018, and the International Reference Ionosphere (IRI‐2020) model (Bilitza et al., 2022), which specifies monthly averages of electron density, ion composition, electron temperature, and ion temperature in the altitude range of 50–2,000 km. The model of Calabia and Jin provides estimates of vertical Total Electron Content (vTEC) for any specified epoch with a spatial resolution of 2.5° in geographical latitude and 5° in geographical longitude. Furthermore, it provides the flexibility for users to adjust parameters related to solar and magnetospheric forcing, as well as annual and Local Solar Time (LST) cycles. For our experiment, we set the model to a constant quiet geomagnetic contribution (Am =6) and the results are compared with the IRI‐2020. It’s important to note that some attenuation may occur due to missing contributions from the full plasmasphere (Jin et al., 2021). We also use the post‐processed UQRG Global Ionospheric Maps (GIMs) of vertical Total Electron Content (vTEC) provided by the Universitat Politècnica de Catalunya (UPC) (Hernández‐Pajares et al., 2009; Liu, Hernández‐Pajares, et al., 2021; Liu, Zhou, et al., 2021). UQRG GIMs‐vTEC are provided with a latitude range of 87.5°S to 87.5°N in steps of 2.5°, with a longitude range of 180°W to 180°E in steps of 5°, and with a temporal resolution of 15 min; the highest accuracy in high‐time‐resolution (Wielgosz et al., 2021). The GIMs of vTEC from the International GNSS Service (IGS) network (Hernández‐Pajares et al., 1999) are available at 30‐min temporal resolution and spatial resolution of 2.5° by 5° in latitude and longitude, respectively, and are Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 3 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License provided in IONEX (IONosphere map EXchange) format at the Crustal Dynamics Data Information System (CDDIS) Goddard Space Flight Center (GSFC) NASA website (https://cddis.nasa.gov/index.html). We also analyze the observations of airglow emissions, which are crucial for monitoring ionospheric structures and irregularities, using all‐sky wide‐angle Visible Imaging Spectrometers (VIS). As it is known, the OI 630.0 nm nightglow emission can be used as a tool to study plasma structures and dynamics in the ionosphere. EPBs can be visualized as a dark band region due to a decrease in the OI 630 nm emission intensity, which indicates the depletion of electron density. However, plasma blobs or enhanced plasma density regions appear as quasi‐oval‐ bright regions in the OI 630.0 nm emission (Adebayo et al., 2023). The images used in this study were obtained from Malki et al. (2018). These images were captured at approximately 15‐minute intervals, starting from 21:00 Universal Time Coordinated (UTC) on 27 February 2014, and ending at 00:50 UTC on 28 February 2014. On the other hand, the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) instrument onboard the Defense Meteorological Satellite Program (DMSP) F18 spacecraft (Paxton et al., 2002) is also employed to obtain imaging data. We use the 135.6 nm wavelength, the ionized nitrogen line, whose resulting nightglow intensities can be related to the square of the ionospheric electron density (Tinsley & Bittencourt, 1975; Meier, 1991). To estimate the ionospheric maximum related to the ionospheric F2‐layer electron density peak (NmF2), the SSUSI nighttime non‐auroral F‐region algorithm is used to convert airglow measurements from nighttime latitudes outside the aurora region. The data can be downloaded from Paxton et al. (2002), and the image strips are made along orbits. The rotation of the Earth samples one strip from each orbit leg, and each strip is temporally separated by approximately 90 min. The use of NmF2 is convenient because it can estimate vTEC using the ionospheric slab thickness ratio (Davies, 1990; Pignalberi et al., 2022). When estimating TEC from NmF2, slab thickness is subjected to diurnal, annual, latitudinal, and storm‐time influences (Davies & Liu, 1991; Stankov & Warnant, 2009), and these must be considered. We use also data recorded by ionosondes which allow to detect ionospheric plasma bubbles by monitoring the well‐known range and frequency spread F phenomena in the ionograms. For this work, we use the DPS4D ionosonde data (Reinisch et al., 2009) provided by the Ebro Observatory (EB040), located at 40.80°N 0.50°E, and the DGS256 ionosonde data provided by the El Arenosillo Observatory (EA036), located at 37.27°N 6.94°W. These data were either obtained from the instrument operators directly or from the Global Ionosphere Radio Observatory repository (GIRO) (Reinisch & Galkin, 2011). The ionosonde ionograms allow to measure several ionospheric characteristics, such as the Maximum Useable Frequency (MUF), which is the highest frequency that can be used for radio communications between two locations at certain distance (typically 3,000 km), as well as to estimate the vertical electron density profile. The GNSS Rate Of TEC Index (ROTI) (Pi et al., 1997) reflects the rate of change in TEC, which can be used to quantify the severity of ionospheric plasma depletions. Recent research has shown that GNSS ROTI can also detect ionospheric irregularities caused by small‐scale plasma bubbles in the ionosphere (Liu et al., 2019; Yang & Liu, 2016). The ROTI is a standard deviation of the rate of TEC over a 5‐min period. We retrieved ROTI maps through SIMuRG (https://simurg.iszf.irk.ru) (Yasyukevich et al., 2020) to detect ionospheric plasma bubbles. To estimate the effect of ionospheric bubbles on GNSS performance, we calculate GNSS Precise Point Positioning (PPP) errors. We use the GAMP (GNSS Analysis software for multi‐constellation and multi‐frequency Precise positioning) open‐source software (Zhou et al., 2018) to compute geocentric coordinates X, Y, Z (WGS84) of GNSS ground‐based receivers. Receiver and satellite clock offsets are considered in the GAMP PPP solution by applying IGS precise satellite orbit and clock products and estimating the clock offset. Although we have selected a fixed station, we use the kinematic positioning mode for our analysis. The 22‐hr (2–24 hr) median of X, Y, and Z geodetic coordinates (WGS84) for the static ground receiver is considered as a reference position. The three‐dimensional positioning error is then calculated as the root‐mean‐square error between the reference and the position at each epoch. We also estimate prompt fluctuations in single‐frequency GNSS positioning caused by ionospheric irregularities by calculating the contribution of the ionospheric‐free combination (Hofmann‐Wellenhof et al., 2007). This method effectively removes the first‐order (up to 99.9%) ionospheric effect, which depends on the inverse square of the frequency. The receiver position is obtained from the observation file and estimated using broadcast orbits, pseudo‐range, and carrier phase measurements (Mahooti, 2019). To isolate short‐term scintillations caused by plasma depletions from global effects, we apply a 3‐min running median‐average filter. Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 4 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License We employ the method developed at Blanch et al. (2018) to identify EPBs over particular GNSS receivers. The algorithm makes use of GNSS data from the International GNSS Service (IGS) network, which is readily accessible via the CDDIS Data Center Website at ftp://cddis.gsfc.nasa.gov/pub/gps/ data/daily/. This detection tool provides us valuable information about the location, duration, depth, and total disturbance of plasma bubbles sensed at the ionospheric pierce point of the line of sight from a given GNSS satellite to a ground receiver. We use also the in‐situ ion vertical velocity and ion density provided by the C/NOFS satellite (Comberiate & Paxton, 2010), short for Communication/Navigation Outage Forecasting System, whose data is available at Heelis (2023). The C/NOFS satellite was placed into a low Earth orbit with a perigee of 405 km and an apogee of 853 km. This measurement will help us to understand the behavior of the ionosphere, affecting radio wave propagation, satellite communications, and space weather. We make use of SuperMAG magnetometer data, as presented in Gjerloev (2012), to estimate the variations of the EEJ in the area under investigation according to Equation 2(Forbes, 1981). The data is readily available at Gjerloev (2012), and Table 1lists the geomagnetic ground stations employed in this research. EEJ =ΔHeq −ΔHoff (2) In this equation, ΔH eq and ΔH off represent the differential horizontal magnetic field intensity (transient variation) for the stations located at the equatorial dip region and outside the equatorial region, respectively. We estimate the PPEF using the empirical model developed by the Cooperative Institute for Research in Environmental Sciences at the University of Colorado Boulder (http://geomag.colorado.edu). This model offers reliable estimations of the variations due to solar wind, which are then mapped along interplanetary electric field data collected by various satellites (Manoj et al., 2013). Finally, the Energetic Particle, Composition, and Thermal Plasma (ECT) investigation is a research effort supported by NASA, part of the broader Radiation Belt Storm Probes (RBSP) mission, which aims to improve our understanding of the Earth’s radiation belts and the processes that control their behavior. The RBSP‐ECT investigation focuses on measuring and characterizing the energetic particles and plasma that populate the Earth’s radiation belts (Baker et al., 2012). One of the key datasets produced by this investigation is the Relativistic Electron‐Proton Telescope (REPT) data. The REPT instrument is designed to measure and record the fluxes, energy spectra, and pitch angle distributions of electrons and protons in the radiation belts. The REPT data is particularly useful for studying the dynamics of the radiation belts and the relationship between the energetic particles and the complex electromagnetic fields that exist in this region of space. The data can also be used to improve models of the radiation belts and to develop strategies for mitigating the impact of space weather on spacecraft and humans in space. The RBSP‐ECT data are publicly available at the RBSP website (https://rbsp‐ect. newmexicoconsortium.org/rbsp_ect.php). 3. Results Figure 1presents the space weather conditions for the period from 24 February to 1 March 2014. We will focus on the moderate geomagnetic storm that occurred on 27–28 February, 2014. Figure 1a illustrates an enhanced proton flux (>10 MeV) due to an X4.9‐class flare that occurred on 25 February 2014, along with a halo Coronal Mass Ejection (CME) (Yashiro et al., 2004). Notably, this surge in proton flux surpassed the 10 cm −2 s −1 sr −1 warning level established by the Space Weather Prediction Center of the National Oceanic and Atmospheric Administration (NOAA). At around 10:00 UTC, a change in the Bz component (Figure 1c) from North to South triggered an increase in geomagnetic activity at high latitudes, as evidenced by the AE, and Am indices in Figures 1d and 1f. Subsequently, the SYM‐H and ASY‐H indices (Figures 1f and 1h) demonstrate the overall energy content of the particles responsible for the fluctuation of an electric current carried by charged particles (10–200 keV), trapped in the magnetosphere at an altitude of approximately 20,000 to 50,000 km. The shock associated with the CME, which reached a peak velocity of around 500 km/s (Figure 1e), arrived on Earth at approximately 16:50 UTC on 27 February 2014. This was reflected by an abrupt change in solar wind Table 1 Geomagnetic Observatories Used in This Study for the Estimation of the EEJ Code Name Country Latitude (°) Longitude (°) M. lat. (°) MBO Mbour Senegal 14.38 343.03 0.11 SPT San Pablo Toledo Spain 39.55 355.65 32.35 GUI Guimar Spain 28.32 343.57 14.17 Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 5 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License temperature, solar wind velocity, density, pressure, and IMF components. When the CME‐associated shock wave reached the magnetopause, the Sudden Storm Commencement (SSC) occurred as a result of the compression of the magnetosphere due to the high pressure of the solar wind, marking the beginning of the geomagnetic storm. During the initial phase of the storm, the plasma pressure reached a maximum value of approximately 12 nPa (Figure 1a), while the IMF Bz component reached a minimum value of approximately −10 nT. Note that Bx and By components of the IMF maintain small positive values of around 12 nT (Figure 1c). The Auroral Electrojet index AE exhibits peak values of 700 nT during the initial phase of the storm (Figure 1d). Figure 1. Physical parameters sensed within the Earth’s environment during a larger period of the geomagnetic storm of 27–28 February, 2014. From top to bottom, the graph shows (a) Proton Flux, (b) Plasma Pressure, (c) IMF components, (d) Auroral indices, (e) Solar Wind Speed, (f) ASY‐D, ‐H, and Am indices, (g) IEF Ey, Em, and Polar Cap index, and (h) SYM‐H index. The vertical dashed red line at 16:50 UTC on 27 February 2014, marks the Storm Sudden Commencement (SSC). Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 6 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License The storm‐time behavior of the geomagnetic parameters, such as ASY‐D, ASY‐H, and Am, is shown in Figure 1f, where it is evident that the three indices reach the maximum values of 100 nT, 80 nT, and 60 nT during the initial phase of the storm. Figure 1f depicts the storm‐time response of the IEF Ey component, PCN, and Em, where these three variables reached a maximum value of 5 mV/m during the initial phase of the storm. The main phase of the storm started on the same day at about 19:30 UTC, with a minimum value of the SYM‐H index of −101 nT at 23:25 UTC on 27 February. After 02:00 UTC on 28 February, the recovery phase started and required several days to return to the SYM‐H index to quiet conditions. Figure 2illustrate the vTEC GIMs estimated from the IRI‐2020 model (a and b), the model of Calabia and Jin (2020, 2019) (c and d), and the IGS post‐processed GIMs (e, and f) for 26 and 27 February 2014 at 20:00 UTC respectively. The IRI is a climatological model and its output shows no significant differences for similar epochs few days apart. Note the results of IRI are smaller than the GIMs and the Calabia and Jin (2020,2019) outputs. The IGS post‐processed GIMs and the Calabia and Jin (2020, 2019) model of vTEC provide better definition of the real spatial distribution. A more accurate representation of the real vTEC values is shown in Figure S1 in Supporting Information S1. In Figure S1 in Supporting Information S1, the UPC post‐processed UQRG GIMs are presented at a 30‐min interval starting from 20:30 UTC, demonstrating, in general, the incapacity to represent plasma depletions with structures of several kilometers in size. Figure 3depicts the GNSS ROTI over Morocco and the southern regions of Spain on 27 February 2014, from 20:30 to 23:00 UTC at 30‐min intervals. A high ROTI value indicates a strong fluctuation in the electron density in the ionosphere. In this figure, several areas with high ROTI values are observed. For instance, the elongated patch in Figure 3d is marked with a green dashed line and shows a sharp gradient in ROTI values, ranging from Figure 2. Ionosphere vTEC variations as predicted from the IRI‐2020 model (a) and (b), the model of Calabia and Jin (2020, 2019) (c) and (d), and the IGS post‐processed GIMs (e)–(f), for the 26 (a), (c) and (e) and 27 (b), (d) and (f) February 2014, at 22:00 UTC. A more accurate representation of the real vTEC values is available in the Figure S1 in Supporting Information S1 provided at the supporting information in this article. Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 7 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 0.2 to above 1 TECU/min. This gradient in ROTI indicates a significant irregularity potentially associated to a EPBs which will be discussed further. We can observe the evolution of the patch from 20:30 to 22:00 UTC, and then it returns to normal values. However, at regional scales defining the structure and dynamics of the plasma depletion may be challenging. For a global representation of ROTI, Figure S2 in Supporting Information S1 portrays high values and elongated shapes over Morocco and southern Spain between 21:00 and 22:00 UTC. It can be observed that over the southern areas of Spain, the ROTI index values exceed 0.5 TECU/min. Furthermore, note the limitations in covering the entire globe due to missing GNSS receivers in many parts of the world. Figure 4displays the GNSS corrections derived from the Ionospheric‐Free combination at the RABT GNSS ground receiver between 12:00 and 24:00 UTC from 26 to 28 February, 2014. Notably, on February 27th, large corrections commenced at around 19:50 UTC with values ranging from ±20 m, and then doubled to ±40 m at approximately 21:00 UTC. It is important to note the time delay of roughly 4 hr from the beginning of the SSC, which is further discussed in the following section. Supporting this observation, Figure S3 in Supporting Information S1 shows 3D errors in the study area when estimating GNSS PPP on 27 February 2014, from 20:30 to 23:00 UTC at 30‐min intervals, indicating errors up to 1 m during distinct phases of the storm in several receivers located in Morocco and southern regions of Spain. Each point marks a GNSS ground receiver. At 15:17 and 16:50 UTC, GNSS PPP errors are small and usually less than 20 cm (background level). At 18:30 UTC, PPP errors increased, showing the most significant amplitudes at the low latitude receivers. Then, using the algorithm Figure 3. Plasma variations as seen from GNSS ROTI maps for the geomagnetic storm of 27 February 2014 from (a) 20:30 to (f) 23:00 UTC, at intervals of 30 min. For a global representation of ROTI kindly refer to Figure S2 in Supporting Information S1. The Rabat GNSS station (RABT 33.82°N, 6.85°W) is indicated with a magenta dot and the alignment of the EPB is indicated with a green dashed line in (d). Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 8 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License developed by Blanch et al. (2018) to identify plasma depletions in the suspected area, we detected significant cases with plasma depletions larger than 5 TECU on the night of 26–28 February from the GNSS receivers in Rabat (RABT: 33.82°N, 6.85°W), Funchal (FUNC: 32.47°N, 16.91°W), La Palma (IPAL: 28.60°N, 17.89°W), and Mas Palomas (MAS1: 27.61°N, 15.63°W). Table 2presents the results of the algorithm. The data in Table 2 corresponds well with the GNSS peak corrections in Figure 4, where the plasma depletion in our area of study is detected between approximately 19:50 and 21:00 UTC at the RABT GNSS ground receiver. Figure 5depicts all‐sky images taken at the Oukaïmeden Observatory (31.2061°N, 7.8664°W) during the storm. A plasma depletion can be unambiguously identified in the images as a black shadow at around 5°W. Additionally, Malki et al. (2018) found a dynamic transient of the plasma depletion moving to the East at approximately 50 m/s. The authors attributed this mechanism to thermospheric equatorward winds originating from high latitudes during the storm, which propagate westward due to Coriolis force (Buonsanto, 1990). These results, Figure 4. Ionospheric corrections (3D distance to the 3‐min median running‐filter) estimated by Ionospheric‐free combination at RABT GNSS ground receiver from 12:00 to 24:00 UTC on (a) 26, (b) 27 and (c) 28 February 2014. The SSC on 27 February 2014 is marked with a red dashed line. The corrections due to EPB effects from 20:00 to 21:00 UTC on 27 February 2014 are highlighted with a green dashed circle. Table 2 Results of the EPB Detection Algorithm GNSS station GNSS Sat. ID Start time (UTC) Start lat. (°) Start long. (°) Peak time (UTC) Peak lat. (°) Peak long. (°) End time (UTC) End lat. (°) End long. (°) Max. depth (TECU) RABT PRN25 19:53 34.30 −8.53 20:25 35.14 −6.98 20:56 34.82 −7.79 −10.81 FUNC PRN31 01:22 ‐ ‐ 01:34 25.93 −16.48 01:40 26.71 −16.58 −18.72 FUNC PRN32 02:55 21.51 −17.30 03:11 25.05 −16.74 03:15 24.54 −16.81 −10.12 FUNC PRN32 03:23 26.01 −16.63 03:32 29.09 −16.40 04:01 27.02 −16.53 −10.15 IPAL PRN21 23:56 28.79 −15.74 00:04 29.49 −15.63 00:23 29.00 −15.72 −5.63 MAS1 PRN14 20:56 27.51 −17.00 21:28 24.97 −17.18 22:16 26.68 −17.01 −89.75 MAS1 PRN16 23:38 30.78 −21.12 23:44 30.70 −19.83 23:55 30.76 −20.64 −8.25 MAS1 PRN20 03:46 17.44 −20.08 03:53 20.39 −18.89 04:03 18.81 −19.52 −8.84 MAS1 PRN27 23:34 25.59 −20.67 23:53 27.03 −19.59 00:06 26.50 −20.00 −33.60 MAS1 PRN29 21:17 27.47 −15.08 21:52 28.64 −14.70 22:07 28.29 −14.86 −25.18 MAS1 PRN32 02:47 17.86 −16.41 02:53 21.50 −15.68 03:13 18.91 −16.17 −8.44 Note. The GNSS ground receivers are located at Rabat (RABT: 33.82°N, 6.85°W), Funchal (FUNC: 32.47°N, 16.91°W), La Palma (IPAL: 28.60°N, 17.89°W), and Mas Palomas (MAS1: 27.61°N, 15.63°W). Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 9 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 4. Discussion On 27 February 2014, sudden vertical ion drifts of approximately 500 m/s were observed between 18 and 19 UTC, coinciding with the presence of equatorial plasma bubbles detected by the C/NOFS satellite. These drifts, which were more pronounced during storm conditions, elevated ionospheric plasma to higher altitudes. However, it seems difficult for these small bubbles to drift up to the apex height of ∼3,000 km for L =1.5 R E (Martinis et al., 2015) to interact directly with the inner radiation belt. Instead, the close development of plasma bubbles, auroral features, and stable auroral red (SAR) arcs in geographic latitudes (Martinis et al., 2015) suggests an indirect influence. As it is well known (Huang et al., 2001; Burke, Gentile, et al., 2004, Burke, Huang, et al., 2004), equatorial plasma bubbles prefer to develop in the Atlantic longitude sector and also in the African longitude sector, where the large plasma depletion under study is located. This spatially close development occurred due to the unusually strong equatorward movement of the plasmapause. During the main phase of the storm, characterized by a long‐duration SYM‐H minimum, high‐energy protons in the inner radiation belt can become depleted but then regain their original state immediately in the recovery phase (Xu et al., 2019; He et al., 2023). The exact mechanisms behind this quick drop in high‐energy proton flux are still unknown, but nonadiabatic processes are suspected. Revisiting the whole process, it is known that the dayside neutral winds, in their natural configuration, generate an eastward electric field of approximately 1 mV/m. At the magnetic dip equator, this field produces a vertical E ×B drift, which moves negative ions and electrons up to the F‐layer and positive ions down to the E‐layer. The resultant vertical polarization electric field, created by charge separation, is approximately one order of magnitude larger than the eastward electric field that produced it (Anderson et al., 2002). The vertical polarization electric Figure 11. Ion density measured along the C/NOFS orbit path (see Figure 10) on 26–28 February 2014 between 18 and 22 LST and from 15°W to 15°E. From top to bottom, successive orbits within the ranges 16–17, 18–19, 20–22, and 22–23 UTC. The period when the Storm Sudden Commencement (SSC) occurs is marked with a red box. The red arrows mark the anomalies that occurred on 27 February. The black dashed‐dot boxes show an aggregation of three anomalies. Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 16 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License field, when combined with the northward geomagnetic field, creates an East–West drift and increases the East– West electrical conductivity along the geomagnetic dip‐equator. Therefore, at the evening terminator, the eastward electric field strengthens before reversing to a westward direction post‐sunset due to the Haerendel‐Eccles mechanism, which involves partial closure of the EEJ (Kelley et al., 2009). This process creates an upward current to meet the current continuity requirement of the F‐region dynamo in the pre‐zonal electric field reversal region (Prakash et al., 2009). The occurrence of plasma depletions during geomagnetic storms seems to be associated with sudden upward E ×B drifts generated by strong eastward electric field perturbations. But the E ×B drift developed within the plasma bubble is due to the interaction of the polarization E field developed due to gravitational Rayleigh‐Taylor (R‐T) plasma instability and the magnetic B field underlying the plasma bubble (Woodman & La Hoz, 1976; Fejer & Kelley, 1980; Li et al., 2021; Horvath & Lovell, 2021). The generalized R‐T instability has been widely accepted as the physical mechanism responsible for the generation of EPBs (Li et al., 2021). But how the factors, which seed the development of R‐T instability and control the dynamics of EPBs and resultant ionospheric scintillations, change on a short‐term basis are not clear (Li et al., 2021). This E×B drift can be upward or downward defining which way the plasma bubbles drift. Note that the upward E ×B developed over the dip equator and underlying the EIA is a different type of E ×B drift. This E ×B drift is the cross product of the equatorial eastward E field (a total E field including the E–F region dynamo E field and also, depending on the underlying geophysical conditions, the PPEF, DDEF, and the PRE E field) and the equatorial northward magnetic field producing and upward E ×B drift driving the plasma fountain (Anderson et al., 2002). Our explanation agrees with the findings of Tulasi Ram et al. (2008), where the LST dependence of the polarity and amplitude of electric fields (PPEF and DDEF) contributes to the development of spread‐F irregularities. In a study conducted by Ghosh et al. (2020), it was demonstrated that the eastward electric field of pre‐reversal Figure 12. Ion vertical velocity measured along the C/NOFS orbit path (see Figure 10) on 26–28 February 2014 between 18 and 22 LST and from 15°W to 15°E. From top to bottom, successive orbits within the ranges 16–17, 18–19, 20–22, and 22– 23 UTC. The period when the Storm Sudden Commencement (SSC) occurs is marked with a red box. The red arrows mark the anomalies that occurred on 27 February. The black dashed‐dot boxes show an aggregation of three anomalies. Figure 13a shows the C/NOFS ion velocity and LST along UTC. Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 17 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License enhancement can cause the F‐region at the magnetic equator to be lifted to higher altitudes through upward E ×B drift. However, when the up‐flowing plasma loses momentum, it flows down along the inclined magnetic field lines to higher latitudes due to gravitational and pressure gradient forces. Therefore, the flow of charged particles from the equatorial region is contingent upon the orientation of magnetic field lines, which are generally closed within equatorial regions. 5. Conclusions In this study, we have presented an accurate description and characterization of localized plasma depletions using the most advanced observational techniques and analyzed the relationships between these depletions to physical parameters such as solar wind, geomagnetic field, and electric currents. The geomagnetic storm of 27 and 28 February, 2014, occurred as a result of an X4.9 solar flare and halo CME. The CME resulted in an enhanced proton flux and produced a change in the IMF Bz component from North to South, which triggered an increase in geomagnetic activity at high latitudes, with the consequent fluctuation in the SYM‐H and ASY‐H indices. The storm’s main phase ended on the same day at about 23:00 UTC, with a minimum value of SYM‐H at −101 nT, and the recovery phase required several days to return to magnetically quiet conditions. We have also explored the advantages and challenges in integrating data from different observation systems, and how to combine different products to improve vTEC resolution for a better detail of small structures, specifically localized plasma Figure 13. From top to bottom, we show (a) C/NOFS ion velocity and LST, (b) differential horizontal magnetic field intensity, (c) the strength of the EEJ, (d) the PPEF, and (e) the SYM‐H during the geomagnetic storm that occurred on 27 February 2014. The Storm Sudden Commencement (SSC) is marked with a red dashed line. The possible correlation with the plasma depletions are marked with yellow circles. Similar to Figures 11 and 12, the group of 3 depletions is marked with green arrows. Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 18 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License depletions at sunset generated during geomagnetic storms. Finally, we have studied the possibilities offered by each observation system and what types of variables can be used to enhance existing empirical models for a better understanding of the coupled processes. In summary, our findings can be described as follows: 1. Small‐scale plasma depletions in the ionosphere have been identified in the area of study using the method of Blanch et al. (2018). The GNSS PPP errors estimated with GAMP exceed undisturbed level at least twice in several receivers (1 m), specifically from 20:30 to 23:00 UTC in Morocco and southern regions of Spain. Due to long PPP convergence, the effects lasted much longer than bubbles were observed. Our experiment with the RABT GNSS station has shown ionospheric corrections above ±20 m during the transient of a small‐scale plasma depletion over Morocco, while during quiet conditions, these corrections are an order of magnitude smaller. Figure 14. High latitude TEC variations during the geomagnetic storm of 27 February 2014. Differences between GNSS GIMs of TEC and the model of Calabia and Jin at approximately McIlwain L‐parameter (L‐Shell) of (a) and (e) 1.5, (b) and (d) 1.2, and (c) 1, for (a) and (b) the northern and (d)–(e) the southern hemisphere. The model was set at constant quiet geomagnetic contribution (Am =6). The red dashed line marks the SSC of the storm. We have marked with yellow ellipses the TEC enhancements at L‐Shell 1.5. Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 19 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 2. The TEC GIMs are unable to represent the small‐scale plasma depletions generated during the storm, and the empirical models only provide an averaged solution of the actual ionosphere. However, GNSS ROTI is an exceptional tool to detect sudden changes of the ionosphere at local scales, although the global coverage should be improved. Our experiment with GNSS ROTI over the study area has shown good spatial and temporal correlation to the structures detected by airglow images. 3. The space‐borne SSUSI airglow disc‐images have offered an excellent spatial resolution with similar results to that of all‐sky ground‐based cameras, but with the advantage of the global coverage. Moreover, the limited revisiting‐time of satellite airglow disc‐images can be improved with new satellite missions. However, all‐sky Figure 15. Top panel shows the SYM‐H index during the geomagnetic storm of 27 February 2014. Bottom panel shows the spin‐averaged differential proton flux at 21.25 MeV from RBSP‐ECT. The McIlwain L‐parameter (L‐Shell) is on the left vertical axis, and the approximated value in altitude is shown in the right vertical axis. The Storm Sudden Commencement (SSC) is marked with a vertical dashed red line. Table 4 Summary of the Data Used in This Study Instruments Technique Parameter Usability On‐board satellite instruments Solar and IMF Indices Solar Wind speed, Plasma pressure, IMF (Bx, By, Bz, Bt), IEF Ey, Em Physical conditions of the interplanetary medium Ground‐based magnetometers Geomagnetic Indices AE, Am, ASY‐D, ASY‐H, SYM‐H Physical conditions of the near‐Earth magnetic field Various IRI, IGS GIMs, Calabia and Jin (2020, 2019) Vertical TEC Smoothed solution of the global ionosphere Ground‐based all‐ sky camera Airglow VIS emissions OI 630.0 nm camera High spatial and temporal resolution. Discrete observatories. Space‐based All‐Sky Sensor Airglow UV emissions OI 135.6 nm camera High spatial resolution. Daily revisiting time. Global coverage. Ionosonde range‐time Ionogram Plasma Frequency Vertical profiles. Directional echoes. Ground GNSS ROTI 5‐min VTEC deviation Indicates sudden changes of the ionosphere at local scales Ground GNSS PPP 3D error Errors up to 1 m during storms Ground GNSS Dual versus single frequency Free‐Ionosphere Combination Corrections up to 20 m during storms C/NOFS In‐situ Ion Vertical Velocity and Density Strong vertical ionospheric drift and density depletions during storms. Along orbit. Ground Magnetometer Differential magnetic field intensity EEJ E‐region electrodynamic processes RBSP‐REPT Trapped Radiation Measurement Data Electron and Proton Fluxes Energetic particle flux in Van Allen Belts Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 20 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License ground‐cameras can only provide discrete observations at localized emplacements and are highly sensitive to atmospheric meteorology. The vertical profiles of SSUSI data have shown a clear ionospheric uplift of approximately 100 km in altitude, and a drift of 3° in latitude. The altitude values are in good agreement with the ionosonde data. 4. The range‐time display of ionograms from EA036 and EB040 revealed the spread‐F and the subsequent recovery of the ionospheric layers. The ionograms recorded at EB040 on 28 February 2014 have provided an estimate of the 2D movement of the irregularity, and the presence of a plasma cavity, enabling us to better understand the behavior of the ionosphere during the storm. 5. During this intense geomagnetic storm, ionospheric depletions with elongated shapes were observed at mid‐ latitudes. The variations in the strength of the EEJ during the storm were closely related to changes in the Cowling conductivity and the ionospheric dynamo electric field. These changes were observed through variations in the SYM‐H index and the injection of PPEFs following the storm. 6. Our discussion of the potential relationship between equatorial electric current flow variations and ground‐ based magnetometer data suggests three distinct peaks correlate with three vertical ionospheric drift uplifts, three density depletions, and are also associated with the high‐resolution SYM‐H index. A multi‐instrumental dataset is essential to fully understand the complex processes that occur in the upper atmosphere of the near‐Earth environment. Each instrument provides valuable information that complements the data collected by the other instruments, allowing us to create a more complete picture of what is happening in the atmosphere. For example, in this study, we utilized GNSS, airglow remote sensing, ionosonde, magnetometer, and satellite data to investigate plasma depletions and their potential coupling mechanisms with space weather processes. Table 4provides a summary of the data used in this study and its usability. Each instrument provided unique insights into the nature of the storm and the resulting plasma depletions. Therefore, it is not advisable to exclude any of the instruments in the study of space weather conditions as each one provides a unique perspective, and additional instruments, such as radio interferometers, could be useful in further improving the accuracy of the dataset and the understanding of the phenomena observed. Conflict of Interest The authors declare no conflicts of interest relevant to this study. Data Availability Statement The physical parameters are freely available at Papitashvili and King (2020), at Mayaud et al. (2023), at Davis and Sugiura (1966), and at Zhao et al. (2021). Processing and analysis of the REPT data was supported by RBSP‐ECT investigation funded under NASA’s Prime contract no. NAS5‐01072. All RBSP‐ECT data are publicly available at Spence et al. (2013). The ionosonde data is provided by Ebro Observatory and by El Arenosillo Observatory. The ion vertical velocity and ion density from the C/NOFS satellite is available at Heelis (2023). The magnetometer data is available at Gjerloev (2012). The all‐sky VIS Imaging at 630.0 nm is from Malki et al. (2018). The SSUSI data is freely available at Paxton et al. (2002). The vTEC GIMs are available at Hernández‐Pajares et al. (2009). The vTEC model of Calabia and Jin (2020) is available at Calabia and Jin (2019), and the IRI‐2020 model is available at Bilitza et al. (2022). The GNSS ROTI data were retrieved by SIMuRG (Yasyukevich et al., 2020), which includes the following GNSS data providers: Pacific Northwest Geodetic Array (PANGA), Royal Observatory of Belgium, Instituto Tecnológico Agrario de Castilla y León, REseau NAtional GPS permanent (RENAG), Wuhan University, Austrian data center (BEV), Dutch Permanent GNSS Array (DPGA), Instituto Geográfico Nacional, the UNAVCO Facility (supported by the National Science Foundation (NSF) and NASA under NSF Cooperative Agreement No. EAR‐0735156), INGV – Rete Integrata Nazionale GPS, The Western Canada Deformation Array (WCDA), Scripps Orbit and Permanent Array Center, UCSD, Korea Astronomy and Space Institute, The African Geodetic Reference Frame (AFREF), CDDIS, Institute of Geodynamics, National Observatory of Athens, Institute of solar‐terrestrial physics SB RAS and Center for Common Use «Angara», Système d’Observation du Niveau des Eaux Littorales (SONEL) (Dow et al., 2009; Bruyninx et al., 2012; Yasyukevich et al., 2018). We acknowledge Dr. Zhou for providing GAMP open‐source software. Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 21 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Uncited Reference Hernández‐Pajares et al., 2009. References Adebayo, M. O., Pimenta, A. A., Savio, S., & Nyassor, P. K. (2023). Airglow imaging observations of plasma blobs: Merging and bifurcation during solar minimum over tropical region. Atmosphere,14(3), 514. https://doi.org/10.3390/atmos14030514 Anderson, D., Anghel, A., Yumoto, K., Ishitsuka, M., & Kudeki, E. (2002). 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We are immensely grateful for their invaluable feedback and revisions, which have greatly enriched this work. We acknowledge the research infrastructure and the access provider Ebro Observatory of the PITHIA‐NRF project (https://www.pithia‐nrf.eu/). The PITHIA‐ NRF project has received funding from European Union’s Horizon 2020 research and innovation program under grant agreement No 101007599. We also acknowledge the 2021 Giner de los Ríos Grant of the University of Alcalá, Madrid, Spain. The authors acknowledge the support of all the members of the Join Study Group 4: “Atmospheric Coupling Studies” of the International Association of Geodesy Global Geodetic Observing System Focus Area Geodetic Space Weather Research (https://ggos.org/about/ org/fa/geodetic‐space‐weather‐research/ groups/jsg1‐coupling‐processes/), and the Low Latitude Ionospheric Research Working Group (LLWG) of the Asia Oceania Geosciences Society (AOGS) Regional Advisory Committee (RAC) (https://aogsrac.org/working‐groups). Journal of Geophysical Research: Space Physics 10.1029/2023JA031862 CALABIA ET AL. 22 of 24 21699402, 2024, 3, Downloaded from https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JA031862 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [28/11/2025]. 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