Minimum Dst Research Articles

Extreme Responses of the Ionospheric Radial Currents to the Main Phase of the Super Geomagnetic Storm on 10 May 2024

AbstractOn 10 May 2024, a super geomagnetic storm occurred with a minimum Dst index of −412 nT. This study investigates the behavior of the ionospheric radial current (IRC) during the main phase of this storm using data from Swarm A and simulations from the Thermosphere‐Ionosphere Electrodynamics General Circulation Model (TIEGCM). At dawn, the IRC exhibits distinct temporal variations: a strong outward flow of 14 nA/m2 between 18:00 and 20:00 UT and an inward flow of −15 nA/m2 by 24:00 UT. At dusk, the IRC starts with an inward value of −6 nA/m2 and rapidly reverses to an outward flow peaking at 15 nA/m2 between 22:00 and 24:00 UT. The dawn‐dusk asymmetry of the IRC is primarily influenced by the merging electric field (Em). Increasing Em penetrates to low latitudes, establishing an eastward (dusk) or westward (dawn) electric field and enhancing the outward (dusk) or inward (dawn) IRC through meridional Hall currents. Model results indicate that the strong polarity changes in dawn IRC are linked to local disturbed zonal winds (). Which are eastward at dawn and westward at other magnetic local times (MLT). The eastward/westward generate outward/inward F‐layer dynamo currents, driving the disturbed vertical electric field () in opposite direction. The significant outward reversal of dusk ∆IRC could be attribute to the rapid enhancement of disturbed Pedersen conductivity (). Due to nonzero geomagnetic declination, eastward/westward corresponds to an increase/decrease in .

Study of Evolution and Geo-effectiveness of Coronal Mass Ejection–Coronal Mass Ejection Interactions Using Magnetohydrodynamic Simulations with SWASTi Framework

Abstract The geo-effectiveness of coronal mass ejections (CMEs) is a critical area of study in space weather, particularly in the lesser-explored domain of CME–CME interactions and their geomagnetic consequences. This study leverages the Space Weather Adaptive SimulaTion framework to perform 3D MHD simulation of a range of CME–CME interaction scenarios within realistic solar wind conditions. The focus is on the dynamics of the initial magnetic flux, speed, density, and tilt of CMEs, and their individual and combined impacts on the disturbance storm time (Dst) index. Additionally, the kinematic, magnetic, and structural impacts on the leading CME, as well as the mixing of both CMEs, are analyzed. Time-series in situ studies are conducted through virtual spacecraft positioned along three different longitudes at 1 au. Our findings reveal that CME–CME interactions are nonuniform along different longitudes, due to the inhomogeneous ambient solar wind conditions. A significant increase in the momentum and kinetic energy of the leading CME is observed due to collisions with the trailing CME, along with the formation of reverse shocks in cases of strong interaction. These reverse shocks lead to complex wave patterns inside CME2, which can prolong the storm recovery phase. Furthermore, we observe that the minimum Dst value decreases with an increase in the initial density, tilt, and speed of the trailing CME.

Prediction of Geoeffective CMEs Using SOHO Images and Deep Learning

The application of machine learning to the study of coronal mass ejections (CMEs) and their impacts on Earth has seen significant growth recently. Understanding and forecasting CME geoeffectiveness are crucial for protecting infrastructure in space and ensuring the resilience of technological systems on Earth. Here we present GeoCME, a deep-learning framework designed to predict, deterministically or probabilistically, whether a CME event that arrives at Earth will cause a geomagnetic storm. A geomagnetic storm is defined as a disturbance of the Earth’s magnetosphere during which the minimum Dst index value is less than −50 nT. GeoCME is trained on observations from the instruments including LASCO C2, EIT, and MDI on board the Solar and Heliospheric Observatory (SOHO), focusing on a dataset that includes 136 halo/partial halo CMEs in Solar Cycle 23. Using ensemble and transfer learning techniques, GeoCME is capable of extracting features hidden in the SOHO observations and making predictions based on the learned features. Our experimental results demonstrate the good performance of GeoCME, achieving a Matthew’s correlation coefficient of 0.807 and a true skill statistics score of 0.714 when the tool is used as a deterministic prediction model. When the tool is used as a probabilistic forecasting model, it achieves a Brier score of 0.094 and a Brier skill score of 0.493. These results are promising, showing that the proposed GeoCME can help enhance our understanding of CME-triggered solar-terrestrial interactions.

Different Effects of a Super Storm on Atmospheric Electric Fields at Different Latitudes

Geomagnetic storms have a significant impact on Earth’s magnetosphere and ionosphere, as well as on the global atmospheric circuit. This study focuses on investigating the anomalous variations in the vertical atmospheric electric field at eight mid-latitude and low-latitude stations during a mega-geomagnetic storm on 24 April 2023. The majority of stations observed vertical atmospheric electric field increases, while only three nearby stations exhibited vertical atmospheric electric field decreases. The analysis revealed that vertical atmospheric electric field changes ranged from 19 to 370 V/m, and the time differences between extreme vertical atmospheric electric field values and the minimum Dst value ranged from 0 to 5.3 h. Other response patterns to this super magnetic storm at different latitudes are summarized, and the physical mechanisms of different effects of magnetic storms on the electric fields of stations at different latitudes are also discussed.

Storm-time variability of terrestrial hydrogen exosphere: kinetic simulation results

Recent studies of TWINS Lyman-α observations have reported an increase in geocoronal column brightness during geomagnetic storms, indicating enhanced exospheric hydrogen atom density (NH). This suggests a complex role of exospheric neutrals in determining storm-time magnetosphere dynamics and their energy release through charge-exchange processes. We developed a Model for Analyzing Terrestrial Exosphere (MATE) to investigate storm-time exospheric behaviors and their physical drivers. MATE traces test hydrogen atoms backward in time from locations in the exosphere to a nominal exobase altitude of 500 km, employing Newtonian mechanics with gravitational force. The model then calculates the phase-space densities (PSDs) of test hydrogen atoms at the exobase using the Maxwellian distribution with physics-based exobase conditions from the TIMEGCM upper atmosphere model. MATE maps PSDs at the exobase to the exosphere using Liouville’s Theorem under collisionless assumptions and derives NH by integrating the PSDs across velocity space. We conducted MATE simulation before, during, and after a minor geomagnetic storm from 12 to 18 June 2008, and compared the model results with NH estimates from the TWINS geocorona data. MATE reproduces storm-time density enhancements soon after the minimum Dst is reached, matching well with a general trend of TWINS NH estimates. The results suggest that upper atmospheric heating during a geomagnetic storm increases the number of ballistic and escaping hydrogen atoms entering the exosphere from the exobase, thereby boosting NH. However, the magnitude of modeled NH mismatches the TWINS NH estimates. The potential mechanisms of this density discrepancy include the physics excluded in the MATE model — such as neutral-neutral collisions, neutral-plasma charge exchange, solar radiation pressure, and photoionization — as well as the higher exobase hydrogen density of TIMEGCM compared to typical empirical values, which will be addressed in future.

Assessment of Seasonal Distribution and Characterisation of Geomagnetic Storm Occurrence during Solar Cycles 21–24

Geomagnetic storms (GMSs) are an important space weather phenomenon that poses serious threats to the advancement of space technology, power transmission lines, oil pipelines, and other infrastructure. This study investigates seasonal patterns of GMSs due to recent reports on the prominence of large storms (Dst ? -50 nT) during equinox conditions. Hourly Dst index data provided by the World Data Center, Kyoto, Japan, for solar cycles 21–24 (1976–2019) were employed. Storm occurrences in each solar cycle considered were identified using the minimum Dst value. The identified storms were categorized and analyzed statistically. Results revealed that storm occurrence varied from month to month, season to season, and solar cycle to solar cycle based on storm categories. Furthermore, the observed seasonal distribution of GMS occurrence decreases in the following order: autumn, spring, winter, and summer. This indicates that equinox conditions are more likely to have GMSs, consistent with the Russell-McPherron effect, compared to solstice conditions. The findings suggest that the distribution and characterization of storm occurrence vary seasonally due to solar activity. The insights on storm occurrence, distribution, and characterization may serve as a guide to space scientists to avert the impacts of GMSs while exploring space.

Quantifying adiabatic motion in the outer radiation belt and ring current with invariant matching

Adiabatic motion is a fundamental reversible process for geomagnetically trapped particle populations, including particles comprising the ring current and radiation belts. During adiabatic motion, a particle’s trajectory in configuration space responds to sufficiently slow changes in the magnetospheric magnetic field. Previous research has highlighted expected patterns in adiabatic motion, such as radial motion or the Dst effect. In this work, we introduce a method we call Invariant Matching for quantifying adiabatic motion between a pair of magnetospheres. This method can be applied to both simulation and semi-empirical magnetic field models, is computationally efficient, and in particular does not require tracing the particle trajectories. In this work, we use the Tsyganenko et al., Journal of Geophysical Research: Space Physics, 2005, 110 (TS05) magnetic field model, and present adiabatic motion between a storm commencement, the time of the storm’s Dst minimum, and a nominal recovery time. We also analyze adiabatic motion which occurs in response to enhancements of individual major current systems (including the ring current, Chapman-Ferraro current, Birkeland current, and tail current). Our methodology yields vector fields quantifying the displacement of mirror points throughout the magnetosphere, prepared in a way appropriate for application to both outer radiation belt and ring current populations.

How Solar Wind Controls the Recovery Phase Morphology of Intense Magnetic Storms

AbstractGeomagnetic storms are critical space weather phenomena resulting from the interaction between the solar wind and the Earth's magnetosphere. However, most studies focus on the main phase of magnetic storms, leaving the morphology of the recovery phase an open question. In this study, we analyze 82 intense magnetic storms with the minimum Dst index ≤ −100 nT between 1995 and 2018, finding that these storms can be classified into two distinct types: one‐stage recovery storms that exhibit a single rapid exponential recovery and two‐stage recovery storms that are characterized by a rapid exponential recovery in the early recovery phase and a slow linear recovery in the later recovery phase. We find that the two‐stage recovery storms are dominant, accounting for approximately 60% of the events. Interestingly, the proportion of two‐stage recovery storms peaks during solar minimum. The two‐stage recovery storms tend to be accompanied by more Alfvén waves with long‐duration and intense southward interplanetary magnetic fields. In addition, we find that the decay rate of the Dst index in the later recovery phase is correlated with the average BZ of the interplanetary magnetic field when the solar wind has a high degree of Alfvénicity. Overall, our results shed new light on the recovery phase morphology of intense magnetic storms and highlight the role of Alfvén waves in this process.

Sub-daily solar wind-magnetosphere energy transfer during major geomagnetic storms of solar cycle 23

The solar wind-magnetosphere energy transfer is one major way of quantifying the impacts of space weather on the Earth's environment. Studies on solar wind-magnetosphere energy transfer in terms of sub-daily time scales are quite sparse. Consequently, in order to investigate storm-time characteristics of the solar wind-magnetosphere energy transfer at a 4-hourly time scale over solar cycle 23, a total of 85 major geomagnetic storms (Dst ≤ −100 nT) were categorized into bins, using the points of minimum Dst values as reference points. Additionally, the monthly statistics of the storms occurrences over the solar cycle was carried out. The statistics followed a semi-annual periodicity, with a lesser peak in the months of May and August, and a major peak in October and November. Furthermore, the energy dissipated was estimated by the summation of aurora precipitation, Joule heating, and the ring current injection. Overall, from the data analyzed, we observed storm-time intensification of energy transfer. The magnetosphere received the highest energy during the time interval 0400–0800 UT (0900–1300 LT in the American sector, and most impactful there), while the lowest energy transfer was recorded between 0000 and 0400 UT (0200–0600 LT in the African/European sector, and least impactful there). We observed a synchrony between the energy dissipated and energy input for the storms’ main phases. Generally, storms driven by a composite of two Interplanetary Coronal Mass Ejections (ICMEs) transients transferred highest energy into the magnetosphere, while those driven by Co-rotating Interaction Regions (CIRs) transferred lowest energy.

Response of ICON/MIGHTI Measured Low‐Mid Latitude OI630.0 and OI557.7 nm Dayglow Emissions to the 27 August 2021 Geomagnetic Storm

AbstractObservations from the Michelson Interferometer for Global High‐Resolution Thermospheric Imaging onboard the Ionospheric Connection Explorer spacecraft are used to study the response of OI630.0 and OI557.7 nm dayglow to a moderate geomagnetic storm on 27 August 2021. The storm reaches a minimum Dst index of −82 nT, significantly impacting the dayglow within the latitudinal range of approximately 20°N–42°N, where the dayglow observations are of good quality. During the geomagnetic storm, the OI630.0 dayglow intensity slightly increases, while the peak volume emission rate (VER) decreases, and the peak height rises noticeably. The F‐layer intensity, peak VER, and the entire‐layer intensity of OI557.7 dayglow decrease significantly. The rise in peak height is not noticeable for the OI557.7 dayglow. The VERs of the both dayglow emissions respond differently to the geomagnetic storm at different altitudes. The OI630.0 dayglow layer as a whole extends upward and rises in altitude. For dayglow averaged above 35°N, the OI630.0 dayglow VER increases above approximately 225 km but decreases below this altitude. The largest increase occurs near 300 km, reaching approximately 82.8%, while the largest decrease occurs around 160 km, reaching about −22.0%. The OI630.0 dayglow intensity increases by approximately 6.3%, the peak VER decreases by about −8.0%, and the peak height rises by approximately 16.3 km, corresponding to a 7.8% increase. The F‐layer intensity, peak VER, and the entire‐layer intensity of OI557.7 dayglow decrease by approximately −27.5%, −32.4% and −17.4%, respectively. The response of the dayglow also depends on longitude and is accompanied by a southward meridional wind.

The Extreme Space Weather Event of 1872 February: Sunspots, Magnetic Disturbance, and Auroral Displays

We review observations of solar activity, geomagnetic variation, and auroral visibility for the extreme geomagnetic storm on 1872 February 4. The extreme storm (referred to here as the Chapman–Silverman storm) apparently originated from a complex active region of moderate area (≈ 500 μsh) that was favorably situated near disk center (S19° E05°). There is circumstantial evidence for an eruption from this region at 9–10 UT on 1872 February 3, based on the location, complexity, and evolution of the region, and on reports of prominence activations, which yields a plausible transit time of ≈29 hr to Earth. Magnetograms show that the storm began with a sudden commencement at ≈14:27 UT and allow a minimum Dst estimate of ≤ −834 nT. Overhead aurorae were credibly reported at Jacobabad (British India) and Shanghai (China), both at 19.°9 in magnetic latitude (MLAT) and 24.°2 in invariant latitude (ILAT). Auroral visibility was reported from 13 locations with MLAT below ∣20∣° for the 1872 storm (ranging from ∣10.°0∣–∣19.°9∣ MLAT) versus one each for the 1859 storm (∣17.°3∣ MLAT) and the 1921 storm (∣16.°2∣ MLAT). The auroral extension and conservative storm intensity indicate a magnetic storm of comparable strength to the extreme storms of 1859 September (25.°1 ± 0.°5 ILAT and −949 ± 31 nT) and 1921 May (27.°1 ILAT and −907 ± 132 nT), which places the 1872 storm among the three largest magnetic storms yet observed.

Generation and evolution of post-sunset equatorial plasma bubbles in East and Southeast Asia during the July 2022 geomagnetic storm

In the East and Southeast Asia, equatorial plasma bubbles (EPBs) mainly occur at post-sunset in equinoctial months. On 7–8 July 2022, a moderate geomagnetic storm occurred, with minimum Dst of −85 nT. This storm could trigger unseasonal post-sunset EPBs over the East/Southeast Asian sector. Observations from GNSS TEC/scintillation receivers, VHF coherent radar and ionosonde show that on 7 July, a few clusters of EPBs, which caused strong amplitude scintillations and significant TEC fluctuations, occurred over a wide latitude range, from low to middle latitudes up to ∼ 32°N. The EPB irregularities at middle latitudes drifted westward, with velocities of about 97 m/s. Before the generation of EPBs, apparent background ionospheric disturbances were detected. An abrupt rise of ionospheric F layer, with upward drifts of about 33 m/s was observed near sunset at low latitudes. It is suggested that the moderate geomagnetic storm was the main reason for the generation of unseasonal post-sunset EPBs. The prompt penetration of eastward electric field caused by the geomagnetic storm could lead to the abrupt rise of F layer near sunset and promote the growth of Rayleigh-Taylor instability. The background ionospheric disturbance could act as a seeding role for the unseasonal EPBs.

Contrasting Storm‐Time Radiation Belt Events With and Without Dropouts—The Importance of CME Shocks

AbstractThis study compares three different geomagnetic storms (designated as storms 1, 2, and 3) observed by NASA's Van Allen Probes within the spacecraft's first 50 days in orbit. These storms were Coronal Mass Ejection (CME)‐driven with minimum DST around −138, −100, and −106 nT, respectively. Storms 1 and 2 occurred following the arrival of fast‐forward shocks, which compressed the magnetopause inward to about 6.5 and 7.5 RE, respectively, as a result of the increase in solar wind dynamic pressure and density. The inward magnetopause motion helped contribute to a rapid depletion of MeV electrons across the entire outer belt. For the third storm, however, there was little or no dropout of MeV electrons in the heart of the outer belt during the storm main phase. This third storm was generated by a CME without an associated shock, and the magnetopause actually moved outward at the start of the storm, suppressing loss of electrons through the outer boundary. The study reveals that under certain solar wind driving conditions radiation belt electron dropouts may not occur, even during large geomagnetic storms (Dst_min < −100 nT).

A class of Bayesian machine learning model for forecasting Dst during intense geomagnetic storms

In this paper we apply a class of Bayesian machine learning model, Gaussian Process Regression, to the prediction of Dst index by using 80 intense geomagnetic storms data (Dst⩽-100nT) from 1995 to 2014. The purpose of this paper is to compare the performance of Gaussian process regression model with Support Vector Machine model combined together with Distance Correlation (DC-SVM) and Neural Network model combined together with Distance Correlation (DC-NN) (Lu et al., 2016). For comparison, we estimate the correlation coefficients (CC), the RMS errors, the absolute value of difference in minimum Dst (ΔDstmin) and the absolute value of difference in minimum time (ΔtDst) between observed Dst and predicted one.In order to compare the prediction effects and the generalizability of the three models to magnetic storm events, we combined 70 intense magnetic storm events and 10 super large magnetic storm events into one group. It is shown that DC-GPR model exhibits the better forecasting performance than by DC-SVM model and DC-NN model in magnetic storm. The CC, the RMS errors, the ΔDstmin , and the ΔtDst of GPR are 0.65, 35.45 nT, 16.12 nT and 1.16 h, respectively.

Properties of Forbush Decreases with AMS-02 Daily Proton Flux Data

A Forbush decrease (FD) is a sudden reduction of Galactic Cosmic Rays (GCRs) that is usually caused by intense solar wind transients, such as Interplanetary Coronal Mass Ejections (ICMEs) and Corotating Interaction Regions (CIRs). Using daily proton fluxes measured by AMS-02 between 2011 May and 2019 October, we identified 142 FD events with an automatic systematic analysis method. The properties of 47 FDs caused by ICMEs and of 54 FDs caused by CIRs were analyzed. We found that the rigidity dependence of the GCR flux decrease is generally better described by an exponential function for both ICME and CIR FDs. We also found that the FD Amplitude of ICME FDs has a moderate correlation with the minimum Dst index and a number of solar wind parameters, such as maximum temperature, pressure, and magnetic field. For CIR FD events, neither FD Amplitude nor Maximum Affected Rigidity had a significant correlation with solar wind parameters.

Statistical comparison of time profiles of Forbush decreases associated with coronal mass ejections and streams from coronal holes in solar cycles 23–24

ABSTRACT In this paper, Forbush decrease (FD) profiles are compared for events associated with (i) coronal mass ejections from active regions accompanied by solar flares (AR CMEs), (ii) filament eruptions away from active regions (non-AR CMEs), and (iii) high-speed streams (HSSs) from coronal holes (CHs). FD profiles are described by time parameters that are delayed from an FD onset to the registration of maximum values of cosmic ray (CR) density variations, CR density hourly decrease, CR equatorial anisotropy, solar wind (SW) speed, interplanetary magnetic field (IMF) strength and minimum Dst index. Distributions of these parameters from 1997 to 2020 and within maxima and minima of the last solar cycles (SCs) were compared by statistical methods. The results obtained reveal that statistical properties of the time parameters depend both on the FD source and on the solar activity period. FDs associated with AR CMEs develop even at close values of SW parameters faster than those associated with non-AR CMEs and HSS from CHs. Differences between typical FD profiles for events associated with AR and non-AR CMEs are more significant when the interplanetary disturbance contains a magnetic cloud. The difference between FD profiles for events associated with AR and non-AR CMEs is less distinguishable within maximum SC 24 than within maximum SC 23. For FDs associated with HSS from CHs, the main phase durations and the time delays of maximal SW speed are longer within SC 23–24 minimum, while the time delays of maximal IMF strength differ insignificantly between 23–24 and 24–25 minima.

Effect of geomagnetic storms on l-band scintillation over Ilorin, Nigeria

A study on the effects of geomagnetic storms on l-band scintillation at Ilorin (latitude = 8.48 °N, longitude = 4.67 °E, Geomagnetic Latitude = 1.89 °S) is presented using newly available data. Three storms with minimum Dst<-100nT(i.e. the storm of April 24, 2012, the St. Patrick’s day storm of March 17, 2015 and the storm of October 13, 2016) were selected for the study based on the availability of data and the season of frequent occurrence of scintillation at Ilorin. The indices used are the ring current index (Dst), the auroral electroject activity index (AE), the horizontal component of the Interplanetary Magnetic Field (IMFBZ) and the ratio of the atomic to molecular neutral species. Results showed that the main phase of the April 24, 2012 caused little enhancement in scintillation during the pre-midnight period while scintillation was suppressed during the post-midnight period. However, scintillation was inhibited on the night of the main phase of the storm of March 17, 2015 and slightly inhibited on the night of the main phase of the storm of October 13, 2016. During the recovery phase, little enhancement was observed for the storm of October 13, 2016 while scintillation was inhibited for one day for the April, 24 2012 and for two successive days for the storm of March 17, 2015. The most interesting results was that of St. Patrick’s day storm of March 17, 2015 in which scintillation was inhibited for three successive days. The Prompt Penetration Electric Field which brings about enhancement of E × B lifting of ionization based on the local time of the minimum Dst is good enough to explain the observation during April 24, 2012 storm. Whereas, northward turning in IMFBZ values and decay in AE values which causes damping of E × B lifting of ionization were used in explaining observations during the storms of March 17, 2015 and October 13, 2016. In addition, significant reduction is seen in the ratio of the atomic to molecular neutral species especially during the storm of March 17, 2015 in which scintillation was inhibited during the main phase and the first two successive days of the recovery phase.

Assessment of the arrival signatures of the March 2012 CME–CME interaction event with respect to Mercury, Venus, Earth, STEREO-B, and Mars locations

In March 2012, favorable positions of Mercury, Venus, Earth, Mars, and STEREO-B in the inner Solar System provided an opportunity to understand the global structure and the propagation of two coronal mass ejections (CMEs) across the inner Solar System. On 7 March 2012, the Sun ejected two very fast CMEs from the solar active region NOAA AR11489, which were accompanied by two X-class flares. Initialization and subsequent fast expansion from lower coronal heights of flux rope structures were detected as their early eruption signatures in Solar Dynamics Observatory (SDO) observations. White-light observations have been imaged using SOHO/LASCO and STEREO/SECCHI/COR2 and followed from 00:24 UT on 7 March 2012. We examined the kinematics of the reported CMEs and found a significant exchange of momentum and kinetic energy during the interaction, indicating that the collision was almost inelastic. Furthermore, we observed the arrival of this merged CME event at different distances in the inner Solar System and compared the arrival time with other models. The reported event arrived on Mercury at 04:30 UT; Venus, at 13:28 UT on 7 March 2012; and it took roughly 36 h to reach STEREO-B on 08 March, 03:36 UT. The arrivals at Mercury and Venus are observed in the magnetometer measurements onboard MESSENGER and Venus Express (VEx), respectively. A powerful interplanetary shock was observed on 08 March, 10:19 UT at Earth around 30 h after the two X-class flares and CMEs’ eruption. Subsequently, a south-directed interplanetary magnetic field (IMF) was observed on Earth, indicating the arrival of an interplanetary coronal mass ejection (ICME). This event caused the sudden storm commencement and development of one of the major intense geomagnetic storms of SC 24, with a minimum Dst value of −148 nT. The observations by the Mars Express (MEX) mission indicated the arrival of a merged CME ∼2.5 days after its initial observation at Sun. We have analyzed the evolution of these CMEs and their propagation in the inner heliosphere and arrival signatures at four planetary locations. The propagation and arrival signatures are compared to simulations using the WSA-ENLIL + Cone model and the drag-based model at various vantage points. The study showcases the importance of multi-vantage point observations in understanding the propagation of CMEs and their interactions.

Width of plasmaspheric plumes related to the level of geomagnetic storm intensity

Abstract. The plume is a plasma region in the magnetosphere that is detached from the main plasmasphere. It significantly contributes to the dynamic processes in both the inner and outer magnetosphere. In this paper, using Van Allen Probe A (VAP-A), the correlation between plume width and the level of geomagnetic storm intensity is studied. First, through the statistical analysis of all potential plume events, we find that there is almost no correlation between plume width and the level of geomagnetic storm intensity. However, for the plumes in the recovery phase after improved sifting, it seems that there is a negative correlation between the plume width and the absolute value of minimum Dst during a storm. Utilizing test particle simulations, we study the dynamic evolution patterns of plumes during two geomagnetic storms. The simulated structures of the two plasmaspheric plumes are roughly consistent with the structures observed by the Van Allen Probe A. This result suggests that the plasmaspheric particles escape quickly during intense geomagnetic storms, causing the width of the plume to be relatively narrow during the recovery phase of intense geomagnetic storms. These results are helpful for understanding the dynamic evolution of the plasmasphere and plume during geomagnetic storms.

Analysis of the Tsyganenko Magnetic Field Model Accuracy during Geomagnetic Storm Times Using the GOES Data

Because of the small number of spacecraft available in the Earth’s magnetosphere at any given time, it is not possible to obtain direct measurements of the fundamental quantities, such as the magnetic field and plasma density, with a spatial coverage necessary for studying, global magnetospheric phenomena. In such cases, empirical as well as physics-based models are proven to be extremely valuable. This requires not only having high fidelity and high accuracy models, but also knowing the weakness and strength of such models. In this study, we assess the accuracy of the widely used Tsyganenko magnetic field models, T96, T01, and T04, by comparing the calculated magnetic field with the ones measured in-situ by the GOES satellites during geomagnetically disturbed times. We first set the baseline accuracy of the models from a data-model comparison during the intervals of geomagnetically quiet times. During quiet times, we find that all three models exhibit a systematic error of about 10% in the magnetic field magnitude, while the error in the field vector direction is on average less than 1%. We then assess the model accuracy by a data-model comparison during twelve geomagnetic storm events. We find that the errors in both the magnitude and the direction are well maintained at the quiet-time level throughout the storm phase, except during the main phase of the storms in which the largest error can reach 15% on average, and exceed well over 70% in the worst case. Interestingly, the largest error occurs not at the Dst minimum but 2–3 hours before the minimum. Finally, the T96 model has consistently underperformed compared to the other models, likely due to the lack of computation for the effects of ring current. However, the T96 and T01 models are accurate enough for most of the time except for highly disturbed periods.