Geomagnetic Storm Period Research Articles

Investigation of Thermospheric Response to Geomagnetic Storms Using GITM‐OVATION Prime and ‐FTA Model With Comparison to GOLD and SABER Observations

AbstractGlobal Ionosphere Thermosphere Model (GITM) results have been compared with measurements from Global‐scale observations of the limb and disk (GOLD) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). For the first time, GOLD‐derived exospheric temperature and column‐integrated ratio measurements have been used to validate GITM model results. We examine two geomagnetic storm events for which we drive GITM with space weather conditions to understand how well the model reproduces the thermospheric responses to geomagnetic activity. In this paper, a recently developed auroral model, the Feature Tracking of Aurora (FTA) model, has been employed to calculate auroral electron precipitation in GITM (GITM w/FTA), and results are compared with the OVATION prime (OP) driven GITM model (GITM w/OP). GITM w/FTA simulated temperature, neutral density, and nitric oxide (NO) density are generally higher compared to the GITM w/OP model. During the geomagnetic storm, the GITM model and GOLD‐derived exospheric temperature agree between and N latitude in the equatorial region. GOLD measurements show strong peaks on either side of the equator during the geomagnetic storm period, which is also observed in our model results. The NO cooling peaks estimated by GITM models are 20 km lower than SABER observations during geomagnetic storms. GITM w/FTA better matches SABER observations than GITM w/OP except at low latitudes during storm time. Our model‐model/data comparisons show that improved auroral models are needed to better capture the thermospheric variations during geomagnetic storms.

Effects of Superthermal Plasmas on Hiss Wave‐Driven Scattering Loss of Radiation Belt Electrons

AbstractPlasmaspheric hiss plays an important role in the loss of radiation belt electrons via cyclotron resonant interactions. The cold plasma approximation is widely used in the evaluation of hiss‐driven electron losses, which however can break down during disturbed periods of geomagnetic storms and substorms. The kappa particle velocity distribution, characterized by a pronounced high‐energy tail, is well‐established to model the profile of superthermal plasma under disturbed geomagnetic conditions. In the present study, by calculating the electron bounce‐averaged pitch angle diffusion coefficients with kappa plasma dispersion relations, we investigate the sensitivity of hiss‐induced cyclotron‐resonant electron scattering loss to the spectral index κ under a variety of superthermal plasma conditions. Our results demonstrate that, with increasing κ, the diffusion coefficients of ∼20–100 keV radiation belt electrons significantly decrease at lower pitch angles and increase at higher pitch angles. In contrast, for electrons at higher energies, the diffusion coefficients tend to increase at lower pitch angles and decrease at relatively higher pitch angles. We also find that decrease of L‐shell and increase of α* and temperature anisotropy tend to weaken the hiss‐driven pitch angle scattering efficiency of electrons at energies from tens to hundreds of keV with a dip at ∼30–50 keV, while the scattering of higher energy electrons can be enhanced. This study confirms the important role of superthermal plasmas in the hiss‐driven electron loss processes and should be carefully incorporated in future modeling of radiation belt electron dynamics.

Assessment of global and regional UPD for BDS/GNSS PPP-AR at low latitudes during quiet and geomagnetic storm periods

The resolution of ambiguity (AR) is of paramount importance for the precise point positioning (PPP) technique, as it enables the reduction of convergence duration and the improvement of positioning accuracy. Uncalibrated phase delay (UPD) is a key factor in ambiguity fixation. We investigate the difference between different scale UPD estimates which are obtained from MGEX and YNCORS stations in PPP-AR performance during quiet and geomagnetic storm periods. The conclusion is supported by two sets of experiments which indicate that regional UPD estimates offer higher stability and accuracy. In the quiet period, the average time to first fix (TTFF) of the regional UPD-based PPP-AR is enhanced by 35.75% compared with the global UPD-based PPP-AR, the N-direction accuracy is enhanced by 60.32%, the E-direction accuracy is decreased by 6.36%, the U-direction accuracy is decreased by 56.14%, and the convergence rate is enhanced by 7.5% to reach 100%. During the period of geomagnetic storm, the average initialization time of regional UPD-based PPP-AR is 32.05% faster than the average initialization time of global UPD-based PPP-AR. the N-direction accuracy is enhanced by 90.32%, the E-direction accuracy is decreased by 61.11%, the U-direction accuracy is enhanced by 55.18%, and the convergence rate is enhanced by 6.67%. Additionally, the TTFF of PPP-AR based on regional UPD is significantly shorter and more stable. The difference may be due to the regional UPD absorbing part of the common error caused by the geomagnetic storm, which results in a greater enhancement in the accuracy and stability of the regional UPD product during the storm.

Machine learning based storm time modeling of ionospheric vertical total electron content over Ethiopia

Geomagnetic storms can cause variations in the ionization levels of the ionosphere, which is commonly studied using the total electron content (TEC). TEC is a crucial parameter to identify the possible effects of ionospheric variations on satellite communication and navigation. This paper assesses the performance of light gradient boosting machine (LGB) and deep neural network (DNN) machine learning algorithms in modeling ionospheric vertical TEC (VTEC) during geomagnetic disturbances. GPS VTEC data for years 2011–2016 from 13 dual-frequency receiver stations over Ethiopia was utilized. Input parameters for the models were derived from the factors that influence VTEC, such as time, location, geomagnetic activity, solar activity, solar wind, and the interplanetary magnetic field. The LGB model improved the predictions of the DNN model from root mean squared error (RMSE), mean absolute percentage error (MAPE), and R2 values of 5.45 TECU, 21%, and 0.93 to 4.98 TECU, 18%, and 0.94 on the testing data, respectively. The two machine learning models significantly outperformed the International Reference Ionosphere (IRI 2020) model during the selected geomagnetic storm periods. This study could provide insight into the impacts of ionosphere variations on satellite communication and navigation systems in the low-latitude ionospheric region.

Comparison of geomagnetic storm and non-storm periods mid-latitude Pc1 pulsations characteristics

Pc1 pulsations are infrequently observed at mid-latitude ground stations. Previous studies have shown that these pulsations near the ground are commonly observed during dawn and geomagnetic storms, particularly in the storm recovery phase. However, few studies have directly compared the characteristics of Pc1 pulsations during storm and non-storm times using long-term ground-based data. In this study, we conducted a comparative analysis of storm-related and non-storm-related Pc1 pulsations detected at a mid-latitude ground station located at Bohyun mountain in Korea (BOH, L ~ 1.34). Our findings reveal notable distinctions between the two groups. Pc1 pulsations during the non-storm period exhibit a sharper peak in the local time distribution of the occurrence, relatively well indicating daytime wave power attenuation during propagation. Additionally, during the non-storm period, Pc1 pulsations show relatively lower frequencies (0.6~1 Hz) with predominantly linear polarization. In contrast, storm-related Pc1 pulsations exhibit higher and broader frequencies (up to 3 Hz) with more frequent left-handed polarizations. These results suggest that storm-related Pc1 pulsations might originate from a more diverse range of spatial sources.

A Community Ionosphere‐Thermosphere Observing System Simulation Experiment (OSSE) Tool: Geospace Dynamics Constellation Example

AbstractObserving System Simulation Experiments (OSSEs) provide an effective way to evaluate the impact of assimilating data from a specific observing system on hindcasting, nowcasting, and forecasting of environmental systems. The NSF NCAR's Data Assimilation (DA) Research Testbed/Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model (DART/TIEGCM) tool, to be hosted at the NASA Community Coordinated Modeling Center, serves as a valuable and accessible community resource for quantitatively evaluating the impact of observations from both current and future ionosphere‐thermosphere (IT) observing systems. This study demonstrates the utility of DART/TIEGCM as an IT OSSE tool, using synthetic observations simulated using a currently planned NASA Geospace Dynamics Constellation (GDC) observing system design. Five sets of OSSEs are carried out to compare the effects of assimilating various combinations of prospective GDC observations (e.g., neutral temperature, neutral wind, neutral composition, atomic oxygen ion density, and ion and electron temperature) during a major geomagnetic storm period of the St Patrick's Day Storm on 17 March 2013. The maximum error reduction in neutral temperature and atomic ion oxygen density is 24.6% and 43.3% compared to the control experiment. These OSSEs indicate the benefits of coupled IT DA approaches implemented in DART/TIEGCM to maximize the impact of multi‐parameter IT observations, such as those expected from the GDC mission. Although more work is required to draw any definitive conclusion on the GDC data impact, the study provides an illustrative example of how the DART/TIEGCM community tool can be used to evaluate observational impacts of planned or existing missions for geospace research and applications.

Bézier Cubics and Neural Network Agreement along a Moderate Geomagnetic Storm

The discussion models the IRI-2012 TEC map over a moderate geomagnetic storm period (5 days) in February 2015 and compares the yield of the models. The models are constructed with the help of cubic Bézier curves and machine learning. In a sense, the comparison of a classical and mechanical approach with a modern and computer-based one is a considerable experience for the paper. The parametric curve approach governs models of piecewise continuous Bézier cubics, while the models employ only the TEC map. The design is separated into curve components at every five-hour curvature point, and each component is handled independently. Instead of the traditional least squares method for finding control points of cubics, it utilizes the mean of every five-hour of the piecewise curves of the TEC data. Accordingly, the prediction error can be controlled at a rate that can compete with the modern network approach. In the network model, 120 hours of the solar wind parameters and the TEC map of the storm are processed. The reliability of the network model is assessed by the (R) correlation coefficient and mean square error. In modeling the TEC map with the classical approach, the mean absolute error is 0.0901% and the correlation coefficient (R) score is 99.9%. The R score of the network model is 99.6%, and the mean square error is 0.71958 (TECU) (at epoch 47). The results agree with the literature.

Response Time of Joule Heating Rate and Nitric Oxide Cooling Emission During Geomagnetic Storms: Correlated Ground‐Based and Satellite Observations

AbstractJoule heating is the primary source of the high latitude thermospheric energy dissipation during geomagnetic storm period. The nitric oxide (NO) emission at 5.3 μm accounts for the majority of Joule heating energy due to its radiative nature. It is the dominating cooling agent above 100 km that effectively regulates the thermospheric temperature. We studied the relationship between the response time of NO cooling emission and Joule heating rate during geomagnetic storm periods by using the NO emission observations by Sounding of Atmosphere using Broadband Emission Radiometry (SABER) onboard NASA’s Thermosphere‐Ionosphere‐Mesosphere Energetics and Dynamics (TIMED) satellite and the Joule heating rate measured by the European incoherent scatter (EISCAT) radar over Tromsø (geographic:69.59°N, 19.22°E), Norway, and the thermosphere‐ionosphere‐electrodynamics general circulation model (TIEGCM) simulation. We selected seven geomagnetic storms during which there were continuous measurements of the Pederson conductivity and electric fields when the TIMED/SABER satellite was in the northview mode. The TIEGCM gives a fair description of NO cooling. However, it was found that the Joule heating rates obtained with the TIEGCM often do not show good agreement with those from EISCAT observations. The Joule heating rate peaks with 3–7 hr of storm' onset. The NO cooling flux takes longer time to respond to the energy input during storm period. The fastest response of the NO cooling emission to the Joule heating rate is found during the strongest storm. The weakest storm does not have the longest response time. No correlation between the response time of NO cooling flux with respect to the Joule heating rate and storm’s intensity was observed.

Diurnal Response of CO2 Radiative Cooling to September 7-9, 2017 Storm

The solar and magnetospheric energy deposition into Earth’s high latitude region modulates the magnetosphere-ionospherethermosphere system during geomagnetic storm periods. One of the impacts of geomagnetic storm is the significant thermosphere temperature increment. This temperature increase is regulated by radiative cooling emissions via CO2 at 15 µm and NO 5.3 µm. We utilized CO2 15 µm radiative emissions observations by SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) instrument onboard NASA’s TIMED (Thermosphere Ionosphere Mesosphere Energetics Dynamics) satellite, to investigate the diurnal response during September 7-9, 2017 storm. The volume emission rate of CO2 emission, in the altitude of 100-140 km, is integrated vertically to estimate cooling flux. The geomagnetic storm induced a significant enhancement in CO2 emission across all latitudes and altitudes considered. While the storm typically has stronger impacts on high latitudes, the response in CO2 emission was notably stronger in mid and low latitude regions both during day and night. The nighttime value is generally lower, with a faster response time, as compared to the day time counterpart. Further a strong hemispheric asymmetry is observed both during day and night. This study highlights a complex interplay of solar and magnetospheric influences on the diurnal variation of Earth's upper atmosphere.

Ground and Space-based response of the ionosphere during the geomagnetic storm of 02–06 November 2021 over the low-latitudes across different longitudes

The strong geomagnetic storm of class G3 that occurred on 03 November 2021 (Dst min = −118 nT, Kp = 8) was the first of this class recorded during the ascending phase of solar cycle 25. In this study, we examined the response of the ionosphere during the geomagnetic storm period from 02–06 November 2021 using the Total Electron Content (TEC) observations from a chain of Global Navigation Satellite System (GNSS) receiver stations in five longitudinal sectors i.e, Asian, East-African, West-African, South-American, and Pacific-west sectors, in the low-latitudes and space-based Swarm satellite electron density, Ne and TEC measurements. The Rate of Change of TEC Index (ROTI) was derived from the ground and space based TEC measurements to examine the occurrence of ionospheric irregularities. The Rate of change of electron density index (RODI) was also derived from Swarm Ne measurements to identify the occurrence of ionospheric irregularities at Swarm altitudes. A positive ionospheric storm effect was observed in all the longitudinal sectors considered in this study. A clear hemispherical asymmetry, with higher VTEC in the northern hemisphere was observed. The determining factors for ionospheric responses to this storm are; local time of the storm’s onset, local time of storm’s minimum SYM-H, and changes in thermospheric O/N2 ratio. These geomagnetic storm effects were discussed in terms of the Prompt Penetration Electric Field (PPEF) storm induced wind lifting effect and Disturbance Dynamo Electric Field (DDEF). The geomagnetic storm inhibited the occurrence of ionospheric irregularities in all the sectors, during the main phase, except for three IGS receiver stations in South American sector. Overall, a longitudinal dependence of the enhancement/inhibition of ionospheric irregularities was observed. The generation of post-sunset irregularities was attributed to the local time occurrence of maximum ring current, PPEF and DDEF.

Trailing Equatorial Plasma Bubble Occurrences at a Low-Latitude Location through Multi-GNSS Slant TEC Depletions during the Strong Geomagnetic Storms in the Ascending Phase of the 25th Solar Cycle

The equatorial plasma bubbles (EPBs) are depleted plasma density regions in the ionosphere occurring during the post-sunset hours, associated with the signal fading and scintillation signatures in the trans-ionospheric radio signals. Severe scintillations may critically affect the performance of dynamic systems relying on global navigation satellite system (GNSS)-based services. Furthermore, the occurrence of scintillations in the equatorial and low latitudes can be triggered or inhibited during space weather events. In the present study, the possible presence of the EPBs during the geomagnetic storm periods under the 25th solar cycle is investigated using the GNSS-derived total electron content (TEC) depletion characteristics at a low-latitude equatorial ionization anomaly location, i.e., KL University, Guntur (Geographic 16°26′N, 80°37′E and dip 22°32′) in India. The detrended TEC with a specific window size is used to capture the characteristic depletion signatures, indicating the possible presence of the EPBs. Moreover, the TEC depletions, amplitude (S4) and phase scintillation (σφ) indices from multi-constellation GNSS signals are probed to verify the vulnerability of the signals towards the scintillation effects over the region. Observations confirm that all GNSS constellations witness TEC depletions between 15:00 UT and 18:00 UT, which is in good agreement with the recorded scintillation indices. We report characteristic depletion depths (22 to 45 TECU) and depletion times (28 to 48 min) across different constellations confirming the triggering of EPBs during the geomagnetic storm event on 23 April 2023. Unlikely, but the other storm events evidently inhibited TEC depletion, confirming suppressed EPBs. The results suggest that TEC depletions from the traditional geodetic GNSS stations could be used to substantiate the EPB characteristics for developing regional as well as global scintillation mitigation strategies.

Properties of the Variability of the Maximum Density of the F2-Layer over Almaty at Different Levels of Solar and Geomagnetic Activity

The properties of the variability of the maximum density of the F2-layer Nm at different levels ofsolar and geomagnetic activity have been analyzed based on hourly data of the Almaty station (43.2° N, 104° E)for 1958–1988. The standard deviation σ(x) of the fluctuations of Nm relative to the quiet level(x = (Nm/Nm0 – 1) × 100, %) and the average shift of these fluctuations xave are used to characterize thisvariability. In this path, an empirical model of the F2-layer maximum density Nm0 for low geomagnetic activityhas been created. It has been found that the variability of Nm depends weakly on the level of solar activity.The dependence of the variability of Nm on geomagnetic activity is one of the main ones, along with thedependences of this variability on time of day and season. In general, the variance σ2(x) is smaller for quietconditions than for periods of high geomagnetic activity. However, during periods of high geomagnetic activity,a further increase in geomagnetic activity does not lead to an increase in the variance σ2(x). The saturationin the increase in the variance σ2(x) against the background of a continuing increase in geomagnetic activityand the absence of this saturation for the average shift xave seems to be a stable property of the variability ofthe mid-latitude ionosphere during periods of geomagnetic storms. This conclusion is based on an additionalanalysis of ionospheric variability according to data from the Irkutsk and Yamagawa stations, which arelocated about 10 degrees north and south of Almaty station, respectively.

Impact of ICME- and SIR/CIR-Driven Geomagnetic Storms on the Ionosphere over Hungary

We investigate the differences between the effects of geomagnetic storms due to Interplanetary Coronal Mass Ejections (ICME) and due to Stream Interaction Regions or Corotating Interaction Regions (SIR/CIR) on the ionospheric F2-layer during the maximum of solar cycle 24. We have created a unique list of the ICME- and SIR/CIR-driven geomagnetic storm events for the time interval between November 2012 and October 2014. Finally, 42 clear ICME and 34 clear SIR/CIR events were selected for this analysis. The individual geomagnetic storm periods were grouped by seasons, time of day, and local time of Dstmin and were analyzed using three different methods: linear correlation analysis using 4-h averages of foF2 parameters and the geomagnetic indices (1st), daily variation of deltafoF2 (2nd), and 3D plotting: geomagnetic indices vs. time vs. deltafoF2 (3rd). The main phase day of the ICME- and SIR/CIR-induced geomagnetic storms was our main focus. We used manually evaluated ionospheric foF2 parameters measured at the Sopron ionosonde station and the geomagnetic indices (Kp, Dst, and AE) for this analysis. We have found that in most cases, the variation of the Dst index is the best indicator of the impact caused in the F2 layer. We conclude as well that the representation of the data by the third method gives a better description of the ICME and SIR/CIR-triggered storm behavior. In addition, our investigation shows that the SIR/CIR-related perturbations can be predicted with greater accuracy with the second method.

Regional ionospheric TEC modeling during geomagnetic storm in August 2021- data fusion using multi-instrument observations

Regional ionospheric Total Electron Content (TEC) models are most significant to investigate the variability of ionosphere during all-weather conditions. Since the ground-based TEC measurements are not available in oceanic and polar regions, space-based observations are incorporated to increase the positional accuracy and reliability of Global Ionospheric TEC Maps (GIMs). Therefore, data fusion techniques are necessary to enhance the prediction capability of regional ionospheric models by considering multi-source data. In view of this, an attempt is made to investigate Equatorial Ionization Anomaly (EIA) structures in low-latitudinal Indian region using multi-instrument data. Data observations from background model CODEGIM, available International GNSS Service (IGS) stations in India, GNSS receivers at KLEF and Tripura stations, FORMOSAT/COSMIC radio occultation and SWARM during geomagnetic storm period August 26–28, 2021 are used for the study. Spherical Harmonics Function (SHF) of order 4 is employed along with Weighted Least Squares analysis (WLS), where separate weight constraint is computed for each data source. TEC maps of spatial resolution 5° x 5° and temporal resolution of 1 h are generated to illustrate the dynamic behavior of ionosphere. The standard deviation for 3 days is obtained as 0.42, 0.61 and 1.43 TECU respectively. TEC depletions and enhancements are observed on August 27 and 28, with mean values of 12.74 and 15.27 TECU respectively, demonstrating negative and positive storm effects.

ACCURACY ASSESSMENT OF PRECISE POINT POSITIONING WITH MULTI-CONSTELLATION GNSS DATA UNDER STRONG SOLAR BURST EFECTS

Solar variations modify a layer of the Earth’s upper atmosphere known as the ionosphere. This is of particular concern for the aviation sector because of the way its communications and navigation systems can be affected. At the same time, one of the most complex atmospheric effects is the response of ionospheric regions to geomagnetic storms. The ionospheric response during the same storm can vary in time in different locations, which can introduce significant errors/displacement (meters) in single-frequency relative GNSS positioning (DGNSS technology). The residual effect can be somewhat mitigated by using dual- or multi-frequency GNSS, but dual frequency is not a guarantee against degradation of relative observations results, especially during significant geomagnetic storms. In this regard, PPP absolute positioning technology can be effective. However, another atmospheric effect – ionospheric scintillation can have a significant impact on the accuracy of both GNSS positioning approaches. The main goal of this study was to analyze the effect of second-order ionospheric delay during geomagnetic storms and ionospheric scintillations on GNSS positioning using the PPP method. GNSS data corrected and uncorrected for higher-order ionospheric delay, respectively, were processed by the static PPP-AR method using the PRIDE-PPPAR ver.2.2.6 software for the selected periods of geomagnetic storms. From the analysis of the influence of second-order ionospheric errors, it follows that their values can reach almost 4 cm for first-frequency signals under different states of ionospheric disturbances for the GPS constellation and almost an order of magnitude less for the GNSS quadroconstellation. The appearance of stronger geomagnetic storms increases the second-order ionospheric errors by several millimeters.

The Four‐Dimensional Variational Neustrelitz Electron Density Assimilation Model: NEDAM

AbstractWith the development of the Global Navigation Satellite System (GNSS) and regional augmentation systems, the influence of the ionosphere on GNSS signals is becoming increasingly important. It is also of particular interest to retrieve the electron density distribution from GNSS observations. We have successfully developed a four‐dimensional variational assimilation scheme, the Neustrelitz Electron Density Assimilation Model (NEDAM), and verified NEDAM by a simulation study using a European ground‐based GNSS network. The performance of NEDAM is validated using two ionosondes and COSMIC‐1 radio occultation observations during the September 2017 geomagnetic storm period. The critical frequency of the F2 layer in NEDAM is much more accurate than that of a physics‐based model driven by observed geophysical indices or the Neustrelitz Electron Density Model (NEDM), when compared to data from two ionosondes. During the storm, the root mean square error of the F2‐layer critical frequency with respect to the two ionosondes is improved by 0.54 and 0.42 MHz, respectively. We also compare two co‐located electron density profiles from the COSMIC‐1 mission with NEDAM and NEDM. It is found that NEDAM is able to reconstruct well not only the peak density but also the peak density height, which is missing in the previous research.

Corotating Disturbances of the Solar Wind in the Monitoring Data of Interplanetary Scintillations: Simulation and Observation

A simple model has been proposed for the leading part of an interaction region between solar wind streams of different speeds. The model describes an increased plasma concentration as a spiral jet with a rectangular cross-section. Using this model, two-dimensional dynamic maps of interplanetary scintillation level distribution were calculated, which were specifically adapted to the configuration of the BSA LPI radio telescope. The model calculations were compared with the data from a series of observations of interplanetary scintillation during four geomagnetic storms in 2022 and 2023, caused by corotating disturbances. The calculations and observational data exhibit a qualitative correspondence. It has been shown that corotating disturbances manifest as scintillation enhancement three days before a geomagnetic storm, occurring at around 15:00–16:00 Moscow time. Over the next two days, the scintillation enhancement zone shifts to a later time, while there is no enhancement in the morning sector. During the actual geomagnetic storm period, there is an increase in night scintillations. This sequence of scintillation enhancement indicates that the disturbance approaches Earth from the eastern side while rotating with the Sun. The qualitative differences between the observational data for corotating and propagating large-scale disturbances are discussed.

Effects of Forcing Uncertainties on the Thermospheric and Ionospheric States During Geomagnetic Storm and Quiet Periods

AbstractUpper‐atmospheric weather prediction is subject to various types of forcing uncertainties. Understanding the sensitivity of the thermosphere and ionosphere to forcing uncertainties under different geomagnetic conditions is critical for space weather predictions. Ensemble simulations of a whole atmospheric model, the National Center for Atmospheric Research Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension (WACCM‐X), with various kinds of forcing perturbation is used to evaluate the upper atmosphere's response to the uncertainties of different forcings. Two kinds of forcing uncertainties are addressed: the lower atmospheric wave and tide forcing uncertainties and high‐latitude electric potential uncertainty. These uncertainties are estimated in different ways and applied to generate forcing perturbations in the WACCM‐X. WACCM‐X can simulate the upper atmosphere's response to the uncertainties of the lower atmospheric wave and tide forcings related to different lower atmospheric conditions. High‐latitude electric potential uncertainty is estimated based on the SuperMag and SuperDARN data through the Assimilative Mapping of Geospace Observations, which is applied to generate the forcing perturbation of high‐latitude electric potential in the WACCM‐X. The results show that the impact of high‐latitude electric potential uncertainty is significant globally during the 2013 St. Patrick's Day storm. The lower atmospheric wave and tide forcing uncertainties result in a global impact on the upper atmosphere in the model. The sensitivity of the upper atmosphere to both uncertainties is approximately the combination of the two individually, though the combined effects are not a linear sum, indicating non‐linearities in the ionosphere and thermosphere response to forcing uncertainties.

Global Ionospheric TEC Forecasting for Geomagnetic Storm Time Using a Deep Learning‐Based Multi‐Model Ensemble Method

AbstractIn recent years, deep learning has been extensively used for ionospheric total electron content (TEC) prediction, and many models can yield promising prediction results, particularly under quiet conditions. Owing to the ionosphere's intricate and dramatic changes during geomagnetic storms, the high‐reliable prediction of the storm‐time ionospheric TEC remains a challenging problem. In this study, we developed a new deep learning‐based multi‐model ensemble method (DLMEM) to forecast geomagnetic storm‐time ionospheric TEC that combines the Random Forest (RF) model, the Extreme Gradient Boosting (XGBoost) algorithm, and the Gated Recurrent Unit (GRU) network with the attention mechanism. Seven features in 170 geomagnetic storm events, including the three components Bx, By and Bz of interplanetary magnetic field (IMF), the Kp and Dst indices of geomagnetic activity data, the F10.7 index of solar activity data and global TEC data, were used for modeling. The test set results showed that the DLMEM model can reduce the root mean square errors (RMSE) by an average of 43.6% in comparison to our previously presented model Ion‐LSTM, especially during the recovery period of geomagnetic storms. Furthermore, compared to Ion‐LSTM, the RMSE values of the low‐, middle‐ and high‐latitude single‐station forecast TEC can be greatly decreased by 33%, 53% and 59%, respectively. It was shown that the new model allows for more precise short‐term global ionospheric forecasting during geomagnetic storms, enabling real‐time monitoring of ionospheric changes.

Ionospheric scintillation characteristics from GPS observations over Malaysian region after the 2011 Valentine’s day solar flare

Abstract Ionospheric scintillations due to plasma irregularities can severely affect the modern dynamic and technological systems whose operations rely on satellite-based navigation systems. We investigate the occurrence of ionospheric scintillation in the equatorial and low latitude region over Malaysia after the 2011 Valentine’s Day solar flare. A network of three Global Ionospheric Scintillation and Total Electron Content Monitor (GISTM) GSV4004B receivers with increasing latitudes from the magnetic equator were used to monitor ionospheric TEC, rate of change of TEC index (ROTI), and amplitude (S4) as well as phase (σ φ) scintillation indices. The results show a simultaneous sudden rise in S4 and σ φ along with a significant depletion of TEC at all three locations. However, the largest enhancement of scintillation indices accompanying a substantial TEC depletion is observed at the farthest low latitude station (UNIMAS) from the equator with values around 0.5, 0.3 rad, and 1 TECU, respectively. The corresponding values at the near-equatorial station (Langkawi; 0.4, 0.2 rad, and 3 TECU) and intermediate station (UKM; 0.45, 0.3 rad, and 5 TECU) are examined along with ROTI variations, confirming the simultaneous occurrence of kilometer-scale and sub kilometer scale irregularities during 17 and 18 February 2011. The radiation effects of the solar flare on the ionosphere were prominently recognized at the local nighttime hours (around 14:00 to 17:00 UT) coinciding with the equatorial prereversal enhancement (PRE) time to seed the equatorial plasma bubbles (EPBs) enhancement that resulted in ionospheric irregularities over the low latitudes. The significant TEC depletion seen in the signals from selected GPS satellites (PRNs 11, 19, 23, and 32) suggests plausible degradation in the performance of GPS-based services over the Malaysian region. The study provides an effective understanding of the post-flare ionospheric irregularities during an episode of minor geomagnetic storm period and aligns with the efforts for mitigating the scintillation effects in space-based radio services over low latitudes.