Kp Index Research Articles

How geomagnetic storms affect the loss of Starlink satellites in February 2022?

Abstract On February 8, 2022, approximately 40 of the 49 Starlink satellites were reported to have lost altitude, leading to atmospheric re-entry. SpaceX reported that the orbital decay on Starlink satellites was considered to be linked to a geomagnetic storm that was initiated on February 3, 2022. We attempted to analyze the cause of orbital decay by sampling all Starlink satellites registered in the SpaceTrack database and then tracing some space weather parameters and species density variations in the thermospheric layer. We employed the solar wind and IMF Bz to see their impact on geomagnetic activity. Moreover, we also analyzed the electric field Ey, Dst, AE, and Ap indices in addition to the solar EUV flux to see their impact on the Starlink satellite environment. We discovered three geomagnetic substorms during the analysis period: two successive substorms on February 4 and 5, and one additional substorm on February 10. We inferred that magnetic substroms significantly affected species densities, mainly O, O2, and N2, around some Starlink satellites, leading to an increase in atmospheric drag. There was a time delay between the substorms and orbital decay on Starlink satellites. However, some Starlink satellites were not affected by geomagnetic substorms due to insignificant changes in their environment. The reason for this is that, despite having lower altitudes, all decaying Starlinks were located in the midnight-dawn sector, in which the drift of ionospheric currents was predominantly driven by westward electrojets. On the other hand, all non-decaying Starlink satellites that had higher altitudes resided in the dusk–midnight sector of magnetic local time, where the impact of substorms insignificantly affected their altitudes. Graphical Abstract

Non-contrast CT attenuation value of renal papilla is a novel predictor of recurrence in kidney stone disease

In calcium stone formers, most stones grow attached to Randall’s plaque, which can be identified by measuring the computed tomography (CT) attenuation value of renal papilla. We hypothesized that the CT attenuation value of renal papilla can predict the severity (recurrent or multiple stone former) and recurrence of the stone disease. We retrospectively reviewed the charts of 180 calcium oxalate stone formers who underwent non-contrast CT and 24-hour urine chemistry in our hospital between September 2012 and November 2021. Two observers independently measured the Hounsfield unit (HU) of the renal papilla and classified the patients into the low-HU and the high-HU value groups according to the median value (38.9 HU). The proportion of recurrent and multiple stone formers were similar between the low-HU group and the high-HU group (70.0% vs. 65.6%, 71.1% vs. 74.2%, respectively). There were also no significant differences in urinary volume, urinary excretions of each constituent, or AP(CaOx) index between the two groups. On the other hand, the recurrence rate in the high-HU value group (0.10 events/person/year) was significantly higher than that in the low-HU value group (0 events/person/year, p = 0.03). Multivariate analysis revealed that high-HU value was an independent predictor of stone recurrence (OR 1.90, 95% CI 1.00-3.64, p = 0.04) as well as medical prophylaxis. The results of this study suggest that HU value of renal papilla is a useful predictor of recurrence of stone disease.

Investigating the drivers of long-term trends in the upper atmosphere over Rome across four decades

The nature of the long-term changes in the upper atmosphere morphology at mid-latitude remains a subject of debate, particularly regarding whether these changes are purely driven by geomagnetic and solar activities or whether forcing from the lower atmosphere, such as CO2 variations, may play a role. To contribute to this debate, we investigate the nature of the long-term trends of the ionospheric and thermospheric parameters by leveraging on ionosonde data digitally recorded at the Rome Observatory since 1976. The following parameters have been investigated under sunlit conditions (12:00 Local Time): critical frequency of the F1 layer (foF1); critical frequency of the F2 layer (foF2), atomic oxygen concentration at 300 km ([O]); ratio between atomic oxygen and molecular nitrogen concentrations at 300 km altitude ([O]/[N2]); exospheric temperature (Tex); thermospheric density at 300 km (ρ). The ionospheric parameters are manually scaled from digital ionograms, whereas thermospheric parameters are retrieved using the THERmospheric parameters from IONosonde observations (THERION) method, which utilises ionosonde observations and a physical model of the ionospheric F region. To investigate the influence of the solar and geomagnetic activity on long term variations, we consider the solar radio flux at 10.7 cm (F10.7) and the geomagnetic disturbance index Ap. To identify the various frequency/period components of the time series under consideration and identify the trends, we leverage the high scale/time resolution offered by the Fast Iterative Filtering (FIF) algorithm. A regression analysis of thermosphere/ionosphere parameters against geomagnetic/solar activity indices has then been conducted to investigate the drivers of long-term variability. Our findings reveal that the identified trends are predominantly controlled by external drivers, particularly long-term solar and geomagnetic activity variations.. The adopted methodology, based on regression modelling, demonstrates that variability in F10.7 and Ap accounts for nearly all of the observed changes, with the exception of atomic oxygen ([O]), which displays a slightly higher unexplained variability (~7%). The inclusion of CO2 concentration as an additional driver improves the regression model for [O]. However, the effect remains statistically limited, indicating that the impact of CO2 on thermospheric cooling might be of little significance. Further studies with extended time series are necessary to better quantify this relationship and evaluate its importance. These results highlight the predominant influence of solar and geomagnetic activity in determining upper atmosphere long-term trends at mid-latitudes.

Air Temperature Variations Analysis of the Hualian M6.9 Earthquake

This study examines the three-dimensional layered air temperature variations associated with the Hualian M6.9 earthquake, which occurred on 18 September 2022, using data from the National Center for Environmental Prediction (NCEP) and extracting background information for air temperature through tidal forces. Changes in air temperature stratification revealed that near the epicenter, temperature anomalies began on 12 September and peaked on 13 September, with pronounced increases in magnitude and area. These anomalies followed a seismic thermal anomaly pattern, i.e., one with greater amplitude and a wider range near the land surface, decreasing with altitude until they dissipated, while the other exhibited high atmospheric temperature anomalies, i.e., the upper atmospheric warming exceeded that near the land surface, likely due to meteorological factors. Stable weather conditions and a low geomagnetic Kp index and Dst index during the research period supported the reliability of these findings. The deformation field recorded by InSAR reflects crustal deformation directly caused by fault slip and stress accumulation; moreover, the area with significantly higher air temperature coincides with the areas with the most concentrated deformation.

Impact of different solar extreme ultraviolet (EUV) proxies and Ap index on hmF2 trend analysis

Abstract. Long-term trend estimation in the peak height of the F2 layer, hmF2, needs the previous filtering of much stronger natural variations such as those linked to the diurnal, seasonal, and solar activity cycles. If not filtered, they need to be included in the model used to estimate the trend. The same happens with the maximum ionospheric electron density that occurs in this layer, NmF2, which is usually analyzed through the F2 layer critical frequency, foF2. While diurnal and seasonal variations can be easily managed, filtering the effects of solar activity presents more challenges, as does the influence of geomagnetic activity. However, recent decades have shown that geomagnetic activity may not significantly impact trend assessments. On the other hand, the choice of solar activity proxies for filtering has been shown to influence trend values in foF2, potentially altering even the trend's sign. This study examines the impact of different solar activity proxies on hmF2 trend estimations using data updated to 2022, including the ascending phase of solar cycle 25, and explores the effect of including the Ap index as a filtering factor. The results obtained based on two mid-latitude stations are also comparatively analyzed to those obtained for foF2. The main findings indicate that the squared correlation coefficient, r2, between hmF2 and solar proxies, regardless of the model used or the inclusion of the Ap index, is consistently lower than in the corresponding foF2 cases. This lower r2 value in hmF2 suggests a greater amount of unexplained variance, indicating that there is significant room for improvement in these models. However, in terms of trend values, foF2 shows greater variability depending on the proxy used, whereas the inclusion or exclusion of the Ap index does not significantly affect these trends. This suggests that foF2 trends are more sensitive to the choice of solar activity proxy. In contrast, hmF2 trends, while generally negative, exhibit greater stability than foF2 trends.

Variations of Equatorial Plasma Bubbles Behaviour in Southeast Asia: Insights from Geomagnetically Quiet Days

Abstract The present study aims to investigate the behaviour of equatorial plasma bubbles (EPBs) during quiet days in Southeast Asia (SEA). The behaviour of EPB was determined by observing their number (n) and zonal drift velocity (VE) from 2011 to 2013. The variation of the n and VE during quiet days was investigated monthly and seasonally each year. Three networks which are Malaysia Real-Time Kinematics GNSS Network (MyRTKnet), Sumatran GPS Array networks (SuGAr) and International GNSS Service (IGS) in SEA that consists of 127 receivers were utilized to collect the high-density GPS data. The data were then used to generate the zonal keogram of the rate of total electron content index (ROTI) to estimate n and VE. From the observed data, there were 376 days characterized as geomagnetically quiet according to the Kp index, with a total of 2592 EPBs observed using ROTI keogram. The highest VE was found to be ∼126 m/s during the equinox, while the lowest was ∼65 m/s in December solstice. In addition, the maximum and minimum n throughout the period were 1937 during the equinox and 163 in December solstice, respectively. While a distinct diurnal pattern emerged for n throughout 2011 until 2013, a clear diurnal pattern of VE was only evident in 2013. This observation suggests a potential link between the year with a diurnal VE pattern and the continuous presence of EPB.

Effect of Climatological Factors on the Horizontal Accuracy of Photogrammetric Products Obtained with UAV.

The use of UAVs (drones) and photogrammetry has gained attention in recent years in the construction industry, allowing information to be obtained from a given area without having direct contact with the area, and thus, being a more efficient alternative in terms of time and costs when compared to a traditional topographic survey. Due to the increase in the use of UAVs for photogrammetry, an investigation is proposed to determine the influence of a non-controllable component in photogrammetric flights: the weather. Factors such as brightness, temperature, wind, KP index, and solar radiation affect the precision and quality of the images to be used in photogrammetry. This research determines which factors are most influential in these results through a varied database obtained over a year. In this way, the moments with the most favorable conditions for a photogrammetric flight in climates such as that of the city of Lima or similar are established. A total of 448 flights carried out over a year were analyzed, collecting climatic data such as air temperature, speed and wind direction, solar radiation, and KP index. The flights, which were carried out with a Mavic 2 Pro UAV, were carried out at 100 m high and with a camera at 90° to obtain detailed information on the works.

A new control strategy of direct exergy balance for coal-fired power plants: Fundamentals and performance evaluation

In order to facilitate the increasing penetration of grid-connected renewable power, coal-fired power plants should operate more and more flexibly. Most of the-state-of-the-art control strategies, which are mainly based on the idea of direct energy balance, cannot perform well when coal-fired power plants change load with high load cycling ramp rate. To enhance the operational flexibility of coal-fired power plants, the control idea of the direct exergy balance is proposed in this study, which directly characterizes the work capacity balance between the boiler and the steam turbine. The new control strategy of direct exergy balance emphasizes the feedback of the deviation between the turbine exergy demand signal and the boiler exergy signal. Dynamic models of a reference power plant were developed and validated, and performances of control strategies based on direct energy balance and direct exergy balance were evaluated and compared. In the 50 %–75 % load cycling process of the reference power plant, the control strategy of direct exergy balance demonstrated markedly improvements in the load cycling ramp rate (29.2 % relatively), the load cycling comprehensive index Kp (39.4 %), and reduction in the maximum deviations (28.2 %), overshoots (59.8 %), and cumulative deviations (28.7 %) of the key thermal parameters. In conclusion, the control strategy of direct exergy balance significantly strengthens the control performance during rapid load cycling processes and attains a notable enhancement in operational flexibility and a slight improvement in energy efficiency of coal-fired power plant.

Automatically Detected CSES Ionospheric Precursors Before Part of the Strong Aftershocks of the 23 January 2024 Wushi MS 7.1 Earthquake in Northwest China

Earthquake prediction is still a large challenge worldwide so far. In this paper, an automatic detection method was put into service immediately after the Wushi MS 7.1 earthquake on 23 January 2024 to weekly detect possible CSES (China Seismo-Electromagnetic Satellite) precursory information before impending aftershocks. An electron perturbation with an enhanced magnitude of 38.3% was first detected on 24 January 2024 at night orbit 33175 and the corresponding variations in different plasma parameters measured at this orbit presented a typical feature of electron depletion or plasma bubble with an abrupt decrease and then an increase after one minute. The Kp index was also checked during this period and the values reached 3.7 once on 23 and 24 January, which indicates that these ionospheric variations probably originated from solar activities instead of three strong aftershocks with a magnitude more than five in the following three days. However, uncertainties still exist. Then, an electron perturbation with amplitude of 24.6%, as well as an O+ one of 27.3%, was successfully searched automatically at the same revisiting orbit 33251 on 3 February 2024 in a magnetically quiet period. These two plasma variations, as well as ones of other ionospheric parameters, were characterized by highly synchronous properties, which increase the availability as seismic precursors. However, no obvious variations were observed at other revisiting orbits or other orbits near the aftershock areas during this period. An aftershock with magnitude of MS 5.3 and the strongest one of MS 5.8 took place on 24 and 25 February, respectively, 20 days after and 1000 km away.

Empirical Model of SSUSI‐Derived Auroral Ionization Rates

AbstractWe present an empirical model for auroral (90–150 km) electron–ion pair production rates, ionization rates for short, derived from Special Sensor Ultraviolet Spectrographic Imager electron energy and flux data. Using the Fang et al. (2010, https://doi.org/10.1029/2010gl045406) parametrization for mono‐energetic electrons, and the NRLMSISE‐00 neutral atmosphere model (Picone et al., 2002, https://doi.org/10.1029/2002ja009430), the calculated ionization rate profiles are binned in 2‐hr magnetic local time and 3.6°geomagnetic latitude to yield time series of ionization rates at 5‐km altitude steps. We fit each of these time series to the geomagnetic indices Kp, PC, and Ap, the 81‐day averaged solar radio flux index, and a constant term. The resulting empirical model can easily be incorporated into coupled chemistry–climate models to include particle precipitation effects.

Detrimental impact of solar and geomagnetic activity on plasma B-complex vitamins in the VA normative aging study cohort

It has been hypothesized that ultraviolet (UV) radiation can lead to depletion of plasma folate and B12 vitamin, but few studies have investigated effects of other parameters of solar and geomagnetic activity (SGA). We investigated the association between four SGA parameters—interplanetary magnetic field (IMF), sunspot number (SSN), Kp index, and ground shortwave solar radiation (SWR)—and three plasma B-complex vitamins—folate, B6, and B12—in 910 participants from the Normative Aging Study (NAS) between 1998 and 2017. Mixed-effects regression models were used for 1- to 28-moving day averages of SGA exposure, adjusted for covariates. We compared the impact of SGA in individuals under higher and lower B-complex supplementation (> or < 50th quartile). Our findings show that increases in solar activity variables IMF and SSN were found to be significantly associated with decreases in B12 vitamin. IMF and SSN were associated with decrease in folate levels, especially in individuals under higher levels of B-complex supplementation. No associations were found for SWR and Kp index. To our knowledge, this is the first study that demonstrated the detrimental impact of solar activity on plasma B12 and folate in a large cohort. These findings have clinical implications during periods of high solar activity.

Contraband classification method for X-ray security images considering sample imbalance

X-ray security image contraband classification is widely used to assist in maintaining aviation and transportation security. This paper suggests an end-to-end X-ray security inspection image classification method that takes sample imbalance into account in order to address the issues of different scales of contraband in X-ray images, challenging samples, and unbalanced positive and negative samples inherent in passenger baggage security inspection. The feature fusion module is used to enhance the model's ability to express picture edge and texture features while the multi-scale feature extraction network is used to capture the features of numerous sorts of illegal goods with various scales. Based on the cost-sensitive idea, the loss function is designed to solve the problem of dataset imbalance, and improve the classification accuracy of difficult samples. experimental results of the subset constructed on the public dataset SIXray show that the proposed method improves the mean AP index by compared with the current optimal end-to-end classification model, especially for hard-to-classify samples such as scissors, the AP index has a significant improvement effect.

Estimating the drift velocity of plasma bubbles in airglow images using the scale invariant feature transform and the speeded up robust feature algorithms

Equatorial plasma bubbles (EPBs) are ionospheric irregularities that can significantly impact radio communication, causing signal scintillation that leads to signal loss and error in position calculations. In this study, we introduced a new technique to estimate the eastward and northward drift velocities of the EPB from ASI data by tracking the Scale Invariant Feature Transform (SIFT) and the Speeded Up Robust Features (SURF) points. The technique has been tested by studying multiple EPBs events detected over the Brazilian sector during the autumn equinox, spring equinox and summer solstice. The chosen events occurred during quiet nights (Kp index ≤ 3) and were observable through two All-Sky imager (ASI) stations. Moreover, the study shows the performance of the technique under different circumstances. It achieves optimal performance on clear-sky nights; however, cloud presence within the ASI field of view increases the error within the estimated values. The estimated velocities were found to be within the range reported by previous studies in the Brazilian sector.

Clinical and imaging predictors for the development of diabetes mellitus following a single episode of acute pancreatitis in youth

BackgroundAcute pancreatitis (AP) increases the risk of diabetes mellitus (DM). Our aim was to identify clinical, laboratory and imaging predictors of preDM/DM in youth post index AP. MethodsThis was a prospective cohort study of patients ≤21 years-old with an index admission for AP and follow up at 3 and/or 12 months. Clinical laboratory values, imaging findings, admission course, and plasma chemokine and cytokine measures collected at index admission were tested for association with preDM/DM development. A multivariable regression model was used to predict preDM/DM. ResultsAmong 187 enrolled participants, 137 (73 %) and 144 (77 %) underwent DM screening at 3 and 12 months respectively, and 137 (73 %) had imaging available. PreDM/DM occurred in 22/137 (16 %; preDM n = 21, DM n = 1) at 3 months and 23/144 (16 %; preDM n = 18, DM n = 5) participants at 12 months. Univariate associations with preDM/DM at 12 months included: severe AP (SAP) (52 % preDM/DM vs. 17 % no DM; p = 0.0008), median [IQR] IL-6 (910 pg/ml [618–3438] vs. 196 pg/ml [71–480], p < 0.05) and CRP (4.16 mg/L [1.67–10.7] vs. 1.55 mg/L [0.4–3.68], p = 0.1) at time of AP attack. The optimal multivariable model to predict preDM/DM included with clinical variables was severe acute pancreatitis (SAP), c reactive protein (CRP), interleukin-6 (IL-6), and age [AUC = 0.80; (0.70, 0.88)]. Including imaging markers, the ideal model included SAP, CRP, IL-6, subcutaneous fat area, age and presence of autoimmune disease with an AUC [0.82 (0.71, 0.90)]. ConclusionsDevelopment of preDM/DM following an index AP episode can be predicted by baseline AP severity, baseline CRP, IL-6 levels, and subcutaneous fat area.

Graph-enabled spatio-temporal transformer for ionospheric prediction

The ionosphere, crucial for satellite navigation and radio communication, is highly sensitive to solar and geomagnetic activities. Traditional ionospheric prediction models often struggle to capture its complexities. This paper introduces a Graph-Enabled Spatio-temporal transformer (GEST) model, designed to predict the Total electron content (TEC) in the ionosphere with higher accuracy. The GEST model innovatively integrates six dynamic space weather parameters, including the Kp index, and refines grid distances and weights in the Global ionospheric maps (GIM). Leveraging the efficiency of the Transformer architecture in processing spatio-temporal data, the GEST model adapts to varying ionospheric conditions and provides superior precision. Our evaluations, based on data from the Center for orbit determination in Europe (CODE), demonstrate that the GEST model significantly outperforms traditional methods and other intelligent algorithms such as conv-LSTM. It shows marked improvements in Mean absolute error (MAE), Root mean square error (RMSE), Pearson correlation coefficient (CC), and Mean absolute percentage error (MAPE), particularly during periods of intense solar and geomagnetic activity. These advancements highlight the GEST model’s substantial contributions to the field of ionospheric prediction technology, offering a robust tool for enhancing the reliability of satellite-based systems.

An investigation into the influence of solar flares and geomagnetic storms on the F2 layer of the ionosphere in Western Europe during March 2024

On March 23 and 24, 2024, the M-class and X-class solar storms significantly intensified. Subsequently, from March 24 to 26, the monitoring station’s Kp index notably increased, at times exceeding 8, indicating that a severe geomagnetic storm was occurring. During this period, the IGS Global Ionosphere Maps (GIMs) displayed a substantial decrease in Total Electron Content (TEC) in Western Europe due to the impact of the intense geomagnetic storms. To investigate this occurrence, data from the Lowell GIRO Data Center were utilized. The analysis revealed that a concentrated solar flare eruption on March 23, 2024, triggered geomagnetic storm events on Earth, causing significant ionospheric anomalies in Western European countries. Specifically, compared to typical levels, parameters such as foF2, m3000F2, and TEC values experienced significant reductions in Western European countries. Moreover, the hmF2 data exhibited higher values at night and lower values during the day, deviating from the expected diurnal pattern. Analysis of the Rate of TEC Index (ROTI) indicated varying effects of geomagnetic storms across different latitudes in Western Europe. Through detailed graphical analysis, this study elucidates the alterations in the ionosphere under geomagnetic storm conditions in Western Europe, shedding light on the dynamic behavior of the ionosphere during a specific timeframe.

Unusual Forbush Decreases and Geomagnetic Storms on 24 March, 2024 and 11 May, 2024

As the current solar cycle 25 progresses and moves towards solar maxima, solar activity is increasing and extreme space weather events are taking place. Two severe geomagnetic storms accompanied by two large Forbush decreases in galactic cosmic ray intensity were recorded in March and May, 2024. More precisely, on 24 March 2024, a G4 (according to the NOAA Space Weather Scale for Geomagnetic Storms) geomagnetic storm was registered, with the corresponding geomagnetic indices Kp and Dst equal to 8 and −130 nT, respectively. On the same day, the majority of ground-based neutron monitor stations recorded an unusual Forbush decrease. This event stands out from a typical Forbush decrease because of its high amplitude decrease phase and rapid recovery phase, i.e., 15% decrease and an extremely rapid recovery of 10% within 1.5 h, as recorded at the Oulu neutron monitor station. Furthermore, on 10–13 May 2024, an unusual G5 geomagnetic storm (geomagnetic indices Kp = 9 and Dst = −412 nT) was registered (the last G5 storm had been observed in 2003). In addition, the polar neutron monitor stations recorded a Ground Level Enhancement (GLE74) during the recovery phase of a large Forbush decrease of 15%, which started on 10 May 2024. In this study, a detailed analysis of these two severe events in regard to the accompanying solar activity, interplanetary conditions and solar energetic particle events is provided. Moreover, the results of the NKUA “GLE Alert++ system”, the NKUA/IZMIRAN “FD Precursory Signals” method and the NKUA “ap Prediction tool” concerning these events are presented.

Global Thermospheric Infrared Response to the Mother's Day Weekend Extreme Storm of 2024

AbstractEarth experienced the strongest geomagnetic storm in 20 years over 10–13 May 2024. The Ap and Dst geomagnetic indices were 273 and −291.94 nT on 11 May. The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on the Thermosphere‐Ionosphere‐Mesosphere Energetics and Dynamics satellite observed significant enhancement in thermospheric infrared emission at 15, 5.3, 4.3, and 1.27 μm. On 11 May the daily global power radiated by nitric oxide (NO) at 5.3 μm was 1.41 TW and by carbon dioxide (CO2) at 15 μm was 1.35 TW. These are the largest single day power values observed by SABER in 22 years and the first time the daily power radiated by NO exceeded that of CO2. The total infrared power (above background) radiated during the storm was 2.64 TW (2.28 × 1017 J). Significant enhancement in limb radiance observed at 4.3 μm (to 250 km tangent height) is likely indicative of NO + formation during the storm.

Analysis of TEC variations and prediction of TEC by RNN during Indonesian earthquakes occurred from 2004 to 2024 and comparison with IRI-2020 model

The Ionosphere, a crucial region of Earth’s atmosphere extending from approximately 50 to 1000 km above the Earth’s surface, plays a pivotal role in global communication, navigation, and satellite-based technologies. Among its various parameters, Total Electron Content (TEC) stands out as a key metric, representing the integrated electron density along a specific path through the ionosphere. This research focuses on analyzing TEC variations during Indonesian earthquakes between 2004 and 2024 using a Recurrent Neural Network (RNN) model. The study investigates the ionospheric response to seismic activity, particularly in Indonesia, a region prone to earthquakes due to its location within the Pacific Ring of Fire and complex tectonic setting involving multiple lithospheric plates. The RNN model, designed to predict TEC variations during earthquakes, utilizes data on solar and geomagnetic activity, including the Kp index, solar wind, and geomagnetic storm activity, obtained from the OMNIWEB data centre, along with TEC data from the IONOLAB data servers for the BAKO station in Cibinong, Indonesia. The earthquakes considered for observation include significant events such as the 2004 Indian Ocean earthquake and tsunami, the 2012 Wharton Basin earthquake, and subsequent seismic events up to 2024. Statistical metrics such as Mean Bias Deviation (MBD), Relative Error (REL_E), Absolute Error (ABS_E), and Root Mean Square Error (RMSE) are used to evaluate the predictive capability of the RNN model and compare it with the International Reference Ionosphere (IRI) 2020 model, a widely accepted empirical model for describing ionospheric parameters. The comparison reveals the performance of the RNN model in capturing TEC variations during seismic events, providing valuable insights for earthquake monitoring and early warning systems.

Analysis of solar plasma parameters during intense geomagnetic storm (SYM/H

We utilize numerous solar plasma and field parameters with geomagnetic indices for the geomagnetic storm in 25 solar cycles. Using Planetary index (Kp) having 3 h data, Dst index hourly data, Symmetric horizontal field (SYM/H) minute resolution data and solar plasma measurements from multiple satellites, examine the chain of significant events that occurred in the year 2023. Statical analysis of geomagnetic provisional activity Sym/H has better results than Kp index during various main phases of geomagnetic activity. The statistical correlation technique is used to examine the relationship between Interplanetary parameters and geomagnetic indices during major geomagnetic storms. This research improves our comprehension of solar–terrestrial interactions and provides valuable insights for enhancing space weather forecasting models.