Characteristics of temporal and spatial variation of the electron density in the plasmasphere and ionosphere during the May 2024 super geomagnetic storm

Characteristics of temporal and spatial variation of the electron density in the plasmasphere and ionosphere during the May 2024 super geomagnetic storm | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Characteristics of temporal and spatial variation of the electron density in the plasmasphere and ionosphere during the May 2024 super geomagnetic storm Atsuki Shinbori, Naritoshi Kitamura, Kazuhiro Yamamoto, Atsushi Kumamoto, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6818022/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Nov, 2025 Read the published version in Earth, Planets and Space → Version 1 posted 5 You are reading this latest preprint version Abstract The spatial distribution of electron density in the ionosphere exhibits notable variability and undergoes considerable changes during storms and substorms driven by solar wind disturbances. Electron density variations and irregularities can cause total signal blackouts during strong scintillation periods and enhance satellite positioning errors. We analyzed Global Navigation Satellite System (GNSS) - total electron content (TEC) and Arase satellite observation data to elucidate the characteristics of the electron density variation in the plasmasphere and ionosphere during the May 2024 super storm. To identify the electron density variation in the ionosphere, we calculated the ratio of the TEC difference (rTEC), which is defined as the difference from the 10-quiet-day average TEC normalized by the average value. Additionally, we estimated the electron density in the plasmasphere and inner magnetosphere from the upper frequency limit of the upper hybrid resonance (UHR) waves observed by the Arase satellite. Consequently, an L-t plot of the electron density showed that the plasmasphere contracted from L = 7.0 to L = 1.5 within 9 h after a sudden commencement. During the storm recovery phase, the plasmapause gradually shifted to a higher L-shell. The electron density in the plasmasphere recovered the geomagnetically quiet-time level on a 4-day scale. The timescale of the plasmaspheric refilling was much longer than that of other coronal mass ejection (CME)-driven storms during the Arase era. The rTEC in the Northern Hemisphere showed that an enhancement in the rTEC value occurred at high latitudes (60°–70° in magnetic latitude (MLAT)) in the daytime (10–14 in magnetic local time (MLT)), approximately 1 h after the storm onset. Subsequently, a tongue of ionization (TOI) formed in the polar cap owing to the enhancement of two-cell convection in the high-latitude ionosphere. The rTEC was globally depleted during the storm recovery phase. The depletion indicates the occurrence of a negative storm owing to a neutral composition (O/N 2 ) change driven by the energy input from the magnetosphere in the high-latitude thermosphere. The coincidence of the long refilling timescale of the plasmasphere and the depletion of the rTEC suggests that a strong negative storm impedes plasmaspheric refilling. May 2024 super geomagnetic storm electron density variation in the plasmasphere and ionosphere GNSS-TEC Arase satellite plasmaspheric refilling process negative storm neutral composition plasma convection storm-enhanced density tongue of ionization. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction The Earth’s ionosphere is formed by partial ionization of the upper atmosphere owing to solar extreme ultraviolet (EUV) radiation and the precipitation of high-energy particles from the magnetosphere. The spatial distribution of electron density in the ionosphere varies strongly depending on latitude, local time, season, and solar activity. Furthermore, it changes considerably during geomagnetic storms and substorms driven by solar wind disturbances (e.g., Balan et al., 2010 ). Because electron density variations and irregularities can cause total signal blackouts during strong scintillation periods and enhance satellite positioning errors (Choudhary et al., 2013 ; Klobuchar, 1987 ), understanding the physical mechanism of electron density variation in the ionosphere during geomagnetic storms is essential for space weather prediction. When solar wind dynamic pressure enhancement with strong southward interplanetary magnetic field (IMF) reaches the dayside magnetopause, the merging process between the Earth’s magnetic field and IMF results in the transfer of solar wind energy into the magnetosphere and increased ionospheric currents and convection electric fields between the magnetosphere and high-latitude ionosphere (Fuller-Rowell et al., 1994 ). Part of the enhanced convection electric field is instantaneously transmitted from the polar region to the equatorial ionosphere (e.g., Kikuchi et al., 1978 ; Tsuji et al., 2012 ), and the eastward component of the electric field in the daytime sector generates a storm-enhanced density (SED) phenomenon (e.g., Foster, 1993 ; Shinbori et al., 2020 ) and enhances the fountain effect (e.g., Tsurutani et al., 2008 ). Storm-time intense ionospheric currents lead to Joule heating and upward and equatorward neutral winds in the auroral region (Blanc and Richmond, 1980 ). Neutral winds in the thermosphere reduce the O/N 2 ratio, and the composition change expands from high latitudes to the equator (e.g., Cai et al., 2023 ; Kim et al., 2023 ; Wang et al., 2010 ). Therefore, through various physical processes, geomagnetic storms lead to increases and decreases in electron density in the ionosphere, which are classified as positive and negative storms, respectively (e.g., Kumar and Parkinson, 2017 ; Prölss, 2013 ). By analyzing the long-term Global Navigation Satellite System (GNSS) total electron content (TEC) from 2000 to 2019, Shinbori et al. ( 2022 ) clarified the statistical behavior of electron density variations in the ionosphere during the main and recovery phases of geomagnetic storms. They reviewed the response of the ionospheric electron density to geomagnetic storms. At low-latitudes and midlatitudes, the ionospheric cold plasmas in the F2 region diffuse along the magnetic field lines, forming a plasmasphere in the inner magnetosphere. The spatial distribution of the equatorial plasma density gradually decreases with increasing L-values, and the plasma density sharply decreases at approximately L = 4–6. This sharp depletion of plasma density is called a plasmapause (Carpenter, 1966 ). The plasmapause forms near the competition region between the co-rotation and convection electric fields in the inner magnetosphere (Nishida, 1966 ). When the dawn-to-dusk convection electric field is significantly enhanced during the main phase of geomagnetic storms, the plasmapause tends to deform toward the Earth and the Sun in the nighttime and daytime sectors, respectively, and the plasmasphere is eroded (e.g., Chappell et al., 1970 ; Oya and Ono, 1987 ; Shinbori et al., 2005 ). During the recovery phase of geomagnetic storms, the convection electric field decreases, and the region where the co-rotation electric field is dominant extends to the inner magnetosphere. During this period, the plasmasphere recovers to a geomagnetically quiet level for several days through plasmaspheric refilling processes (e.g., Singh et al. 2011 ). Furthermore, because the spatial distribution of plasma density in the plasmasphere influences the generation and propagation of plasma waves and the interaction between charged particles and plasma waves, identification of the physical mechanisms of plasma density variation in the inner magnetosphere during geomagnetic storms is essential for understanding the behavior of radiation belts and ring current particles (e.g., Baker et al., 1994 ; Singh et al. 2011 ). The temporal variation and global structure of plasma density were intensively investigated using data from the plasmasphere using the IMAGE EUV (Inner Magnetopause to Aurora Global Experiment Extreme Ultraviolet Imager) instrument (e.g., Goldstein, 2004 , 2006 ; Moldwin et al., 2016 ; Sandel et al., 2003 ). Based on a comparison between GPS-TEC and IMAGE EUV observations during a geomagnetic storm, Foster et al. (2002) found that SED plumes in the ionosphere connect plasmaspheric plumes in the magnetosphere through magnetic field lines. Plasmaspheric plume formation and erosion are caused by an enhanced subauroral polarization stream (SAPS) and convection electric fields (Goldstein et al., 2005 ). Shinbori et al. ( 2021 ) analyzed long-term GNSS-TEC and electron density data obtained from the Arase satellite from March 23, 2017, to May 31, 2020. They showed that the midlatitude trough formed at almost the same location as the plasmapause during the main phase of geomagnetic storms. Therefore, numerous past studies have investigated the response of the plasmasphere and ionosphere to geomagnetic storms through integrated data analysis of ground and satellite observations. However, because such geomagnetic storms with a disturbance storm-time (Dst) minimum of − 300 to − 500 nT occur only a few times during one solar cycle (McPherron, 1991 ), the behavior of the plasmasphere and ionosphere during super geomagnetic storms remains insufficiently understood. A super geomagnetic storm occurred on May 10–11, 2024, with a maximum Kp value of 9 and a minimum horizontal symmetric disturbance (SYM-H) value of − 518 nT and was the most intense storm in the past 20 years. Hayakawa et al. ( 2025 ) briefly reviewed various types of plasma phenomena at the solar surface and in Earth’s magnetosphere using ground and satellite observation data during a super geomagnetic storm. Several recent studies have shown initial results of the temporal and spatial variation of the magnetosphere, plasmasphere, ionosphere, and thermosphere during the storm event. These include a significant increase in thermospheric infrared radiation level (Mlynczak et al., 2024 ), the poleward motion of the equatorial ionization anomaly (EIA) crests (Karan et al., 2024 ), midlatitude plasma bubbles (Sun et al., 2024), notable changes in thermospheric composition and temperature (Evans et al., 2024 ), strong SED in the American longitude sector (Aa et al., 2024 ), strong tongue of ionization (TOI) in the Northern Hemisphere (Themens et al., 2024 ), low-latitude aurora over Japan (Nanjo and Shiokawa, 2024 ; Kataoka et al., 2024 ), and high-frequency electromagnetic ion cyclotron (EMIC) waves in the regions close to the Earth (Jun et al., 2025 ). For the response of the plasmasphere to the May 2024 super geomagnetic storm, Pierrard et al. ( 2025 ) reported a slow recovery of the plasmasphere based on a 3D dynamic model of the plasmasphere; however, in situ observations on the temporal variation of plasma density in the plasmasphere in the equatorial plane of the magnetosphere remain lacking. In this study, we elucidated the characteristics of the electron density variation in the plasmasphere and ionosphere during the May 2024 super geomagnetic storm based on an integrated data analysis of GNSS-TEC and Arase satellite data, together with solar wind data and geomagnetic indices. 2. Observation data and analysis method 2.1 Solar wind and geomagnetic index data To investigate an overview of the solar-terrestrial environment during the May 2024 super geomagnetic storm, we used high-resolution OMNI data of the By and Bz components of the IMF in geocentric solar magnetic (GSM) coordinates, solar wind proton density and flow speed with a time resolution of 1 min provided by the National Aeronautics and Space Administration (NASA) Coordinated Data Analysis Web (CDAWeb) ( https://cdaweb.sci.gsfc.nasa.gov/index.html/ ), the Auroral Electrojet (AE) index (World Data Center for Geomagnetism, Kyoto et al., 2015 ) and the SYM-H index (Iyemori, 1990 ; Iyemori and Rao, 1996 ; World Data Center for Geomagnetism, Kyoto et al., 2022 ) provided by the World Data Center for Geomagnetism, Kyoto University ( http://wdc.kugi.kyoto-u.ac.jp/index.html ). To identify the geomagnetically quiet days, we referred to a list of geomagnetically quiet and disturbed days provided by the German Research Center for Geosciences ( https://www.gfz-potsdam.de/en/kp-index/ ). We also obtained the Kp index from the same provider to analyze the dependence of the plasmapause location on geomagnetic activities. 2.2 Arase satellite observation data To investigate the temporal and spatial variation of the electron density in the plasmasphere and inner magnetosphere and determine the plasmapause location, we analyzed electron density data with a time resolution of 1 min derived from in situ plasma wave measurements (the upper frequency limit of upper hybrid resonance (UHR) waves) obtained by the high-frequency analyzer (HFA) (Kumamoto et al., 2018 ) of the plasma wave experiment (PWE) instrument (Kasahara et al., 2018a ) onboard the Arase satellite (Miyoshi et al., 2018a ). Additionally, we used the magnetic field data obtained using a magnetic field instrument (MGF) (Matsuoka et al., 2018a ) to derive the electron density from the UHR frequency. The magnetospheric electron density was calculated based on a previously described comprehensive method by Shinbori et al. ( 2021 , 2023 ). An empirical plasma density model of the magnetosphere has also been developed using the high-accuracy electron density data from the Arase satellite derived in this way (Watanabe et al., 2024 ). In this study, we identified the plasmapause location as a depression in the electron density by a factor of three or more within a short radial distance (DL < 0.5, L: L-value) following the method proposed by Carpenter and Anderson ( 1992 ). 2.3 GNSS-TEC data To compare the ionospheric electron density with the magnetospheric electron density observed by the Arase satellite, we used GNSS-TEC data with a time resolution of 30 s obtained from receiver-independent exchange format (RINEX) files provided by more than 50 institutes and universities. These data providers are available from the GNSS-TEC database ( https://stdb2.isee.nagoya-u.ac.jp/GPS/GPS-TEC/gnss_provider_list.html ). For our analysis, we calculated the TEC values based on the carrier phase difference between L1 (1575.42 MHz) and L2 (1227.60 MHz) and adjusted them to the TEC values calculated using their pseudoranges (Jakowski et al., 1996 ; Otsuka et al., 2002 ; Shinbori et al., 2020 ). Grid data in the network common data format (netCDF) and quick-look plots are available on the GNSS-TEC database website ( https://stdb2.isee.nagoya-u.ac.jp/GPS/GPS-TEC/ ). In this study, we used the ratio of the TEC difference (rTEC) (Shinbori et al., 2020 ) to investigate the deviation from the geomagnetically quiet-time TEC value. The rTEC value was defined as the ratio of the difference between the TEC and the average TEC values of 10 quiet days to the quiet-day TEC value. The rTEC was calculated using the following equation: $$\:R=\frac{\delta\:I}{\stackrel{-}{I}}=\frac{I-\stackrel{-}{I}}{\stackrel{-}{I}}$$ where the variables \(\:R\) , \(\:I\) , \(\:\stackrel{-}{I}\) , and \(\:\delta\:I\) are the rTEC, TEC, average TEC values of 10 quiet days, and the difference between the TEC and average TEC values, respectively. 3. Analysis results 3.1 An overview of the May 2024 super geomagnetic storm Figure 1 shows the temporal variation in the By and Bz components of the IMF in GSM coordinates, solar wind proton density, flow speed, and geomagnetic indices (AU, AL, and SYM-H) for the time interval between May 10 and 15, 2024. Solar radiation was relatively high when the F10.7 index (Tapping, 2013 ) reached 220–230 solar flux units (sfu; 1 sfu = 10 − 22 W/m 2 /Hz). Multiple CMEs associated with the flare activity erupted from Active Region 13664 and hit the Earth’s magnetosphere at ∼17:03 UT on May 10, triggering the super geomagnetic storm over the following three days. The By and Bz components of the IMF were highly perturbed with peak-to-peak amplitudes of 67 and 50.18 nT, respectively, after the passage of the interplanetary shock (Figs. 1 a and b). The Bz component of the IMF showed multiple negative excursions, and the first major dip occurred between 19:00 and 22:30 UT on May 10, with a minimum value of − 43.43 nT at 22:12 UT. Subsequently, the Bz component changed from negative to positive. The second major dip occurred between 23:46 UT on May 10 and 05:00 UT on May 11, with a minimum value of − 47.85 nT recorded at 00:36 UT. After the arrival of the interplanetary shock, the solar wind density and flow speed showed a sudden increase up to 56 cm − 3 and 713 km/s, respectively (Figs. 1 c and d). Subsequently, the solar wind density fluctuated with large amplitudes until 12:00 UT on 12 May. The solar wind speed reached a maximum (1026 km/s) at 17:12 UT on May 12. As shown in Fig. 1 g, the SYM-H index increased suddenly within a few minutes at 17:05 UT on May 10, indicating the occurrence of a geomagnetic sudden commencement (SC) caused by the sudden compression of the magnetosphere (Fig. 1 g). The SC amplitude was 74 nT. Subsequently, the SYM-H index showed a monotonic decrease down to − 518 nT at 02:14 UT on May 11, which was associated with the development of a ring current in the inner magnetosphere. Following the main phase of the geomagnetic storm, the SYM-H index gradually increased over several days owing to the decay of the ring current. During the storm period, the AU and AL indices were highly perturbed with peak values of ~ 1800 and ~ − 3700 nT, respectively, in association with the enhancement of auroral electrojet caused by the development of the high-latitude convection and the occurrence of substorms (Figs. 1 e and f). In addition, the SYM-H index revealed that this storm event was the second-largest geomagnetic storm during the period of the archive of the SYM-H index since 1981. 3.2 Characteristics of electron density variation in the inner magnetosphere and plasmasphere observed by the Arase satellite To investigate the characteristics of the temporal and spatial variation of electron density in the inner magnetosphere and plasmasphere during the May 2024 super geomagnetic storm, we analyzed electron density data obtained from Arase satellite observations. Figure 2 shows the time-series plots of the SYM-H index and average electron density in an L-value range of 2.5–3.0 for the in- and out-bound passes and L-t diagrams of the electron density for the in- and out-bound passes during May 7–21, 2024. The L-value (McIlwain, 1961 ) was calculated using the International Geomagnetic Reference Field (IGRF) 13 model (Alken et al., 2021 ). During this period, the Arase satellite flowed in the dawn-side and dusk-side inner magnetosphere for out- and in-bound passes, respectively (Fig. 2 f). As shown in Figs. 2 b and 2 d, the high-density region (Ne > 300 cm − 3 ) contracted from L = 4.0 to L = 2.5 within a day for both in- and out-bound passes after the onset (17:05 UT on May 10) of the geomagnetic storm. The average electron density in an L-value range of 2.5–3.0 also showed a large depletion of one order of magnitude (Figs. 2 c and 2 d). The electron density variation indicates that the plasmasphere was eroded owing to the strong enhancement of the convection electric field in the magnetosphere during the geomagnetic storm. Furthermore, an enhanced electron density region appeared in the higher-L-value region (L > 6.0) for several passes during the main and early recovery phases of the geomagnetic storm. The electron density in this region (L > 6.0) was two or three orders of magnitude larger than that during other periods. This observation indicated that the Arase satellite crossed the magnetopause and traversed the magnetosheath region. Because the electron density in the magnetosheath is beyond the scope of this study, the details of this region will be discussed in another study. After the early recovery phase of the geomagnetic storm, the high-density region gradually expanded to the outer region (L = 4.0) over 3–4 days. As the plasmasphere expanded radially, the average electron density gradually increased to the level of the pre-storm phase (Figs. 2 c and 2 d). After May 16, the SYM-H index showed the occurrence of small geomagnetic storms with amplitudes of 80–100 nT (Fig. 2 a). After these storm events, the average electron density decreased by a factor of five or more and recovered to the pre-storm phase level within a day. 3.3 Location of the plasmapause in the inner magnetosphere As shown in Fig. 2 , we observed a large electron density depletion in the inner magnetosphere and shrinkage of the plasmasphere during the May 2024 super geomagnetic storm. Here, we analyze the temporal variation in the location of the plasmapause in the inner magnetosphere on May 1–31, 2024, including periods of other geomagnetic storms. Figure 3 shows the temporal variations in Kp and SYM-H indices and the location of the plasmapause. In Fig. 3 c, the location of the plasmapause rapidly moved to a lower L-value from 7.0 to 1.5 after the onset of the May 2024 super geomagnetic storm. This plasmapause motion indicates that the plasma sphere contracted significantly, owing to the enhancement of the magnetospheric convection electric field. During geomagnetic storms, the Kp value reached 9 (Fig. 1 a). After the onset of the geomagnetic storm recovery phase, the plasmapause slowly moved to a higher L-value from 1.5 to 4.0. This observation indicates that the plasmasphere tends to recover its quiet-time level owing to the plasmaspheric refilling process. The recovery time of the plasmasphere was much longer than that of other geomagnetic storm events, as indicated by the red arrows in Fig. 3 b. As shown in Fig. 3 , the location of the plasmapause tended to shift to lower L-values as geomagnetic activity increased. To investigate the dependence of Kp on the location of the plasmapause, we analyzed the relationship between the location of the plasmapause and the Kp index using the method proposed by Moldwin et al. ( 2002 ). We used the maximum Kp value 12 h prior to the plasmapause observation. The Kp value was defined as Kp (max12). Figure 4 shows the location of the plasmapause as a function of Kp (max12) for both in- and out-bound passes. Figure 4 shows an evident trend of decreasing L-values with increasing Kp; however, the plasmapause location tends to scatter for lower Kp values (Kp < 4). From the least-squares linear regression of all Lpp identified by the Arase satellite, the following relationship provides the plasmapause location for both in- and out-bound passes. $$\:Lpp=\left(5.58\pm\:0.148\right)-\left(0.420\pm\:0.040\right)*Kp\:\left(max12\right)$$ The coefficient of determination (R) was 0.64. The standard deviation of the observations for this line was approximately 0.967 Lpp. 3.4 Temporal and spatial variation of electron density in the ionosphere obtained by the GNSS-TEC technique Figure 5 shows a time-series plot of the SYM-H index and polar maps of rTEC in the Northern Hemisphere in Altitude-Adjusted Corrected Geomagnetic (AACGM) coordinates (Shepherd, 2014 ). The time of each polar map corresponds to that indicated by the dotted vertical lines in Fig. 5 a. Before the onset of the SC of the May 2024 geomagnetic storm, the spatial distribution of rTEC was almost homogeneous, with an rTEC value of approximately 0.0 near the geomagnetically quiet level (Fig. 5 b). Approximately 1 h after the onset of SC, an evident enhancement of rTEC appeared in the daytime (10–14 MLT) ionosphere in the MLAT range of 50–70° (Fig. 5 c). This enhancement corresponds to the SED phenomenon, which is caused by the uplift of the ionosphere in a sunlit region owing to the enhancement of the convection electric field. As the geomagnetic storm developed, the rTEC enhancement region extended to other MLTs and magnetic latitudes within a few hours (Fig. 5 d). In Fig. 5 d, an apparent depletion of rTEC with a narrow latitudinal structure appears as a region equatorward of the weak enhancement of rTEC associated with an auroral oval in the dusk-to-midnight sectors. This rTEC depletion corresponded to a midlatitude trough. In this case, the center of rTEC depletion was located at approximately 45° (MLAT). Additionally, an rTEC enhancement with a plume-like structure was observed in the polar cap region, which connects to an SED plume in the midlatitude ionosphere (Fig. 5 e). This rTEC enhancement corresponds to a TOI phenomenon associated with the enhancement of two-cell convection in the polar cap region during the main phase of a geomagnetic storm. During this period, the auroral oval and midlatitude trough locations moved to much lower latitudes of 50° and 40° (MLAT), respectively, in the midnight sector. After the onset of the geomagnetic storm recovery phase, the TOI structure disappeared in the polar cap region, and the enhanced rTEC region associated with the SED phenomenon decreased in the midlatitude ionosphere (Fig. 5 f). Instead, a significant depletion of the rTEC appeared from high to low latitudes over a wide range of MLTs. This phenomenon corresponds to a negative storm caused by an enhancement in the recombination process owing to a neutral composition change in the thermosphere. The negative storm peaked at 18:00 UT on May 11 (Fig. 5 h) and gradually weakened with time (Figs. 5 i and j). This phenomenon was observed at least until the late recovery phase of the geomagnetic storm (Fig. 5 j). 4. Discussion 4.1 Characteristics of the temporal and spatial variation of GNSS-TEC from the high- to low-latitude ionosphere As shown in Fig. 5 , the rTEC enhancement corresponding to the SED phenomenon appeared with an amplitude of ˃ 0.5 at high latitudes (50° ≤ MLAT ≤ 75°) on the dayside (10–14 MLT) approximately 1 h after the onset of the geomagnetic storm. The time difference between the onset of rTEC enhancement and geomagnetic storms is almost consistent with that reported in previous studies (e.g., Sori et al., 2019 ; Shinbori et al., 2020 ). As the geomagnetic storm developed, this structure extended to lower latitudes over a wide range of MLTs. The strong SED suggests that the eastward electric field penetrates to the mid- and low-latitude ionosphere and drives the vertical \(\:E\times\:B\) drift of the F-region plasma in the sunlit region (e.g., David et al., 2011 ; Liu et al., 2016 ; Lu et al., 2019 ; Sori et al., 2019 ; Shinbori et al., 2020 ). Based on a statistical analysis of the global TEC data for several geomagnetic storms that occurred in different seasons, Coster et al. ( 2017 ) showed that SED phenomena frequently occurred during or near the equinoxes and that the SED amplitude became the minimum near the solstices. Furthermore, by analyzing 663 geomagnetic storm events over 20 years (2000–2019), Shinbori et al. ( 2022 ) found that the amplitudes of the SED base and plume tended to be small around the summer solstice in the Northern Hemisphere. However, the present study showed that the SED phenomenon had a large rTEC amplitude of ˃ 1.0 during the May 2024 super geomagnetic storm. The occurrence of the strong SED phenomenon in summer differs from the seasonal dependence of positive storms at midlatitudes, as reported in previous studies (Buonsanto, 1999 ; Mendillo, 2006 ; Prölss, 1995 ). An exceptionally strong convection electric field likely imposed on the entire ionosphere (Aa et al., 2024 ) caused a strong SED during the main phase of the super geomagnetic storm. In the polar cap, a strong rTEC enhancement appeared with a stream-like structure during the main phase of the geomagnetic storm (Fig. 5 e). This rTEC structure corresponded to the TOI phenomenon generated by enhanced two-cell convection at high latitudes (e.g., David et al., 2011 ; Heelis, 2017 ; Knudsen, 1974 ; Sato, 1959 ; Sato and Rourke, 1964 ; Sojka et al., 1994 ). Using the Thermosphere–Ionosphere–Electrodynamics General Circulation Model (TIE-GCM), Liu et al. ( 2016 ) showed that the amplitude of the TOI phenomenon is much larger in winter than in other seasons and that the midlatitude SED as a source of TOI is also enhanced significantly in winter. The rTEC amplitude in the midlatitude ionosphere on the dayside was much larger than the statistical analysis results of the rTEC during geomagnetic storms, as shown by Shinbori et al. ( 2022 ). Despite the summer in the Northern Hemisphere, the TOI amplitude reached more than 1.0 in rTEC. Themens et al. ( 2024 ) also reported a strong TOI phenomenon in the polar cap during the May 2024 super geomagnetic storm. The characteristics of the strong TOI phenomenon in the polar cap differ from the seasonal dependence of the TOI amplitude reported in previous studies (e.g., Sojka et al., 1994 ; David et al., 2011 ; Shinbori et al., 2022 ). Therefore, the strong SED on the dayside allows much more plasma transport from the midlatitude ionosphere to the polar cap, forming a strong TOI phenomenon. After the onset of the recovery phase of the geomagnetic storm, a strong negative storm occurred in the polar cap as well as in low-latitude regions (Figs. 5 f–j). The rTEC depletion associated with the negative storm reached 50–90% of the geomagnetically quiet-time level. This phenomenon lasted for more than two days. Themens et al. ( 2024 ) also reported the strong negative storm occurrence in the Northern Hemisphere. Furthermore, they observed a strong depletion of the electron density in the F-region of the ionosphere or a disappearance of the F2-layer at high latitudes using the European Incoherent Scatter Radar (EISCAT) Svalbard radar and the Poker Flat Incoherent Scatter Radar (PFISR) observation data. By analyzing neutral composition data obtained from NASA's Global-scale Observations of the Limb and Disk (GOLD) mission, Evans et al. ( 2024 ) showed that the O/N 2 ratio and thermospheric temperatures decreased and increased, respectively, by 50% during the recovery phase of a geomagnetic storm. Based on a modeling study, Sojka et al. ( 1994 ) demonstrated that substantial ion outflow and thermospheric heating occurred during the initial and main phases of a super geomagnetic storm on March 13–15, 1989. From the results of previous studies, a severe and long-lasting negative storm is driven by a neutral composition change owing to the changes in thermospheric circulation associated with intense auroral and Joule heating during a super geomagnetic storm. The quantitative evaluation of the neutral composition change in the thermosphere will be examined using a global atmosphere-ionosphere coupling model in the future study. 4.2 Characteristics of the electron density variation in the plasmasphere and inner magnetosphere As shown in Fig. 2 , the Arase satellite successfully performed in situ plasma wave observations in the inner magnetosphere and plasmasphere during the May 2024 super geomagnetic storm, and we had the opportunity to investigate the spatial and temporal variation of the electron density above the topside ionosphere. The present study showed that the high-density region of electron density in the inner magnetosphere shrank significantly after the onset of the geomagnetic storm (Figs. 2 b and d) and that the plasmapause location moved abruptly from L = 7.0 to L = 1.5 (Fig. 3 ). These results indicate that the plasmasphere was eroded owing to the strong enhancement of convection electric fields in the inner magnetosphere during the main phase of the geomagnetic storm (e.g., Nishida, 1966 ). By analyzing IMAGE EUV image data, Baker et al. (2004) showed that the plasmapause location was within L = 2.0, and at some MLTs, it was at L = 1.5 during the Halloween super geomagnetic storm. For this superstorm event, in situ observations of the plasma density were not conducted in the equatorial plane of the inner magnetosphere. In the present study, we succeeded in detecting a low L-shell plasmapause during the May 2024 super geomagnetic storm using Arase satellite observation data. The IMAGE and Arase satellite observations suggest that such an extremely small plasmasphere occurs only during the strongest geomagnetic storms. Using the BSPM plasmasphere-ionosphere model, Pierrard et al. ( 2025 ) investigated the spatial and temporal variations in plasma density in the plasmasphere during the geomagnetic storm of May 2024. Their results showed that the plasmapause locations were approximately 2.3 Re in the post-midnight sector and 5 Re at the endpoint of the plasmaspheric plume in the afternoon. The average location of the calculated plasmapause was 3 Re. Furthermore, Pierrard et al. ( 2025 ) analyzed the magnetic field and plasma observations of low-Earth orbiting satellites and showed that the plasmapause location at the altitude of the topside ionosphere abruptly moved to a lower L-value from 4.0 to 1.8 within a few hours. The Arase and Swarm satellite observations showed that the plasmasphere shrank more deeply than expected by the BSPM plasmasphere-ionosphere model. After the onset of the recovery phase of the geomagnetic storm, the high-density region of electron density moved slowly outward, and the electron density at L = 2.5–3.0 recovered the geomagnetic quiet-time level for more than three days (Figs. 2 c and e). This result indicates that plasmaspheric refilling is much slower than the typical timescale of two days required to refill the geomagnetically quiet-time level of plasma density in the plasmasphere (e.g., Pierrard et al., 2021 ). The following subsection discusses the possible causes for this slow refilling process. Because different types of plasma waves are generated inside and outside the plasmapause, and they accelerate and scatter energetic particles on the radiation belts (e.g., Ripoll et al., 2023 ), the plasmapause location is important for understanding the electromagnetic and particle environments during geomagnetic storms in the context of cross-energy coupling (Miyoshi et al., 2013 , 2018). During this event, the plasmapause shrank deep into the inner magnetosphere for a long time (Figs. 2 and 3 ). This result suggests that the response of high-energy particles in the inner magnetosphere differs from that in typical cases. Unusual electron belts appeared in the lower L-value region after the May 2024 super geomagnetic storm, and a strong enhancement of the high-energy proton flux from 9.5 to 13 MeV occurred in the southern part of the South Atlantic Anomaly (Pierrard et al., 2024 ). 4.3 Slow recovery of the plasmasphere after the May 2024 storm As shown in Figs. 2 and 3 , the plasmasphere required more than three days to recover the geomagnetically quiet-time level after the onset of the May 2024 geomagnetic storm. The timescale of the plasmaspheric refilling process is believed to be much longer than that of other geomagnetic storm events, as indicated by the red arrows in Fig. 3 . To clarify the slow refilling of the plasmasphere during the May 2024 geomagnetic storm, we statistically examined the timescale of plasmaspheric refilling for 92 CME-driven geomagnetic storm events from March 2017 to December 2024. A list of geomagnetic storm events is presented in Table 1 . Figure 6 shows the scatter plot of the time constant of the plasmaspheric refilling at L = 2.5–3.0 as a function of the period and minimum SYM-H value. Here, the time constant is defined as the time difference between the start of the electron density depletion and the time taken to reach the electron density before the onset of the geomagnetic storm. In Fig. 6 , most geomagnetic storm events show that the time constant is distributed within 2 d regardless of the size of the geomagnetic storms. The time constant of the May 2024 geomagnetic storm was much longer than those of the other geomagnetic storms, except for several events (August 2018, April 2023, and October 2024). These events appeared to contribute to the prevention of plasmaspheric refilling. Table 1 List of 92 CME-type geomagnetic storms and timescale of the plasmaspheric refilling for the in- and out-bound passes. N/A means that we could not identify the plasmapause location with Arase electron density data. Storm peak for each event Timescale of the plasmaspheric refilling [day] Event # Date UT SYM-H of peak [nT] In-bound Out-bound 1 2017/4/4 7:10 -49 1.18 0.79 2 2017/5/28 7:13 -142 1.18 2.37 3 2017/7/16 13:17 -66 0.79 1.58 4 2017/9/8 0:53 -145 2.37 2.59 5 2017/9/13 0:08 -62 0.62 1.02 6 2018/3/10 4:17 -47 0.79 N/A 7 2018/8/26 7:11 -206 2.20 2.36 8 2019/5/11 3:00 -56 N/A N/A 9 2019/5/14 6:22 -70 0.79 0.79 10 2020/4/20 12:27 -66 0.79 N/A 11 2020/10/5 20:25 -32 0.79 0.79 12 2021/5/12 14:15 -56 1.18 N/A 13 2021/5/27 8:47 -46 0.79 N/A 14 2021/8/27 23:23 -84 0.79 0.79 15 2021/9/17 20:47 -66 N/A N/A 16 2021/10/12 14:34 -70 0.79 0.79 17 2021/10/18 0:59 -70 0.79 1.18 18 2021/11/4 12:44 -118 0.79 1.18 19 2021/11/29 2:29 -28 0.79 N/A 20 2022/2/3 10:55 -80 1.18 1.18 21 2022/2/10 17:27 -65 0.37 0.37 22 2022/3/12 5:51 -57 0.79 N/A 23 2022/3/13 23:36 -114 1.18 1.18 24 2022/4/2 6:26 -55 1.97 1.97 25 2022/4/8 0:49 -38 N/A N/A 26 2022/4/10 6:41 -66 N/A 1.58 27 2022/4/14 22:36 -84 1.13 N/A 28 2024/2/11 6:28 -19 1.18 N/A 29 2024/3/3 17:57 -126 0.78 1.17 30 2024/3/21 19:33 -80 0.78 1.14 31 2024/3/24 16:14 -167 0.78 1.17 32 2024/4/16 21:27 -75 1.17 0.61 33 2024/4/19 19:15 -135 2.00 2.35 34 2023/3/24 2:19 -167 2.36 2.36 35 2023/4/24 4:03 -233 2.75 3.93 36 2023/5/6 5:03 -106 N/A 1.96 37 2023/5/8 1:35 -25 1.59 N/A 38 2023/5/10 6:10 -8 1.18 1.18 39 2023/5/20 6:48 -77 1.18 1.18 40 2023/7/14 5:11 -42 0.62 N/A 41 2023/7/16 23:37 -59 1.18 1.18 42 2023/7/26 4:31 -42 0.79 0.79 43 2023/8/2 10:44 -33 1.18 N/A 44 2023/8/5 4:59 -87 1.18 1.18 45 2023/9/2 9:54 -71 1.57 0.78 46 2023/9/19 2:50 -96 1.57 2.35 47 2023/9/25 2:23 -73 1.18 1.57 48 2023/10/21 7:02 -105 1.57 0.78 49 2023/11/4 23:06 -59 1.18 1.57 50 2023/11/5 16:54 -189 1.96 1.18 51 2023/11/13 1:36 -41 N/A 0.37 52 2023/12/1 13:30 -136 0.62 1.18 53 2023/12/2 0:20 -104 1.18 1.18 54 2023/12/14 8:14 -80 0.78 0.62 55 2023/12/16 0:58 -39 1.18 1.18 56 2023/12/17 16:18 -92 0.78 0.78 57 2024/2/11 16:48 -27 1.18 0.78 58 2024/2/25 9:15 -31 1.18 0.78 59 2024/3/3 18:00 -128 1.17 0.78 60 2024/3/21 19:35 -81 0.62 0.62 61 2024/3/24 16:16 -170 0.78 0.78 62 2024/4/16 21:28 -76 1.17 1.17 63 2024/4/19 19:14 -135 0.78 0.78 64 2024/4/26 16:15 -50 1.17 1.17 65 2024/5/3 5:44 -65 0.62 0.62 66 2024/5/6 1:12 -66 0.78 0.78 67 2024/5/11 2:24 -518 3.77 3.52 68 2024/5/16 10:37 -103 N/A 0.70 69 2024/5/17 23:04 -108 0.78 0.37 70 2024/6/4 9:31 -30 1.59 0.78 71 2024/6/11 3:43 -53 1.17 1.17 72 2024/6/16 12:02 -40 0.78 1.17 73 2024/6/23 18:12 -27 0.62 1.59 74 2024/6/26 11:35 -27 0.62 0.62 75 2024/6/28 12:06 -119 1.17 1.17 76 2024/7/5 4:45 -23 1.17 1.57 77 2024/7/26 6:09 -56 1.17 0.78 78 2024/7/30 11:16 -54 0.78 0.78 79 2024/8/4 17:04 -118 1.17 1.17 80 2024/8/12 16:04 -212 1.17 1.96 81 2024/8/17 22:24 -38 N/A 0.62 82 2024/8/28 5:36 -90 1.56 1.96 83 2024/8/31 2:20 -80 1.17 1.17 84 2024/9/12 13:49 -129 1.17 1.95 85 2024/9/17 4:24 -144 0.78 0.78 86 2024/9/24 10:45 -38 0.61 0.78 87 2024/10/8 7:44 -155 2.34 2.74 88 2024/10/10 23:14 -390 3.13 2.74 89 2024/10/26 21:01 -23 0.61 1.17 90 2024/10/28 10:44 -14 1.17 0.61 91 2024/11/9 12:37 -109 1.17 2.34 92 2024/12/17 6:30 -44 1.56 0.78 The timescale to refill the plasmasphere to the geomagnetically quiet-time level depends on the amount of supply of light ions (H + ) from the topside ionosphere through H-O + charge exchange \(\:H+{O}^{+}\rightleftharpoons\:{H}^{+}+O\) (e.g., Banks and Kockarts, 1973 ; Richards and Torr, 1985 ; Stancil et al., 1999 ; Krall and Huba, 2019 ). The H-O + reaction rate depends on the neutral hydrogen temperature, \(\:{T}_{n}\) , the number density of neutral hydrogen, \(\:{n}_{H}\) , and the number density of ionized oxygen, \(\:{n}_{{O}^{+}}\) (Richards and Torr, 1985 ). This result indicates that a large depletion in the density of ionized oxygen, \(\:{n}_{{O}^{+}}\) causes a decrease in the H-O + reaction rate. However, using the Naval Research Laboratory Sami2 model, Krall and Huba ( 2019 ) showed that the H + refilling rates tended to increase with oxygen density for low solar activity (F 10.7 180). Their findings indicated that the plasmaspheric refilling process becomes slower for high solar activity owing to the enhancement of the neutral oxygen density in the topside ionosphere. For the May 2024 super geomagnetic storm, a strong and long-lasting negative storm occurred from the polar cap to the low-latitude ionosphere, and the rTEC value decreased by 50–90%. In addition, we confirmed that such strong negative storms occurred during the geomagnetic storms in August 2018, April 2023, and October 2024 (not shown here). The occurrence of a strong negative storm indicates that the neutral composition ratio [O]/[N 2 ] in the thermosphere decreases because of changes in the thermospheric circulation associated with strong auroral and Joule heating during geomagnetic storms. A large depletion in [O]/[N 2 ] occurred during the recovery phase of a geomagnetic storm (Evans et al., 2024 ). The decreased O + density in the topside ionosphere is believed to reduce the H-O + reaction rate, causing a slow refilling process. Future studies should clarify the effect of negative storms on the plasmaspheric refilling process using a plasmasphere-ionosphere-atmosphere coupling model. 5. Conclusions To elucidate the temporal and spatial variation in electron density in the plasmasphere and ionosphere during the May 2024 super geomagnetic storm, we analyzed GNSS-TEC and Arase satellite observation data. Consequently, the L-t plot of the electron density revealed contraction of the plasmasphere from L = 7.0 to L = 1.5 within 9 h of the onset of the geomagnetic storm. The location of the plasmapause tended to move to a lower L-value with increasing geomagnetic activity and scatter for lower Kp values (Kp < 4). After the onset of the geomagnetic storm recovery phase, the plasmapause slowly moved to a higher L-value. It recovered the level of geomagnetically quiet times over four days. The timescale of the plasmaspheric refilling was significantly longer than that of normal/typical CME-driven geomagnetic storms. Several polar maps of rTEC in the Northern Hemisphere in geomagnetic coordinates show that an enhancement of the rTEC value occurred at high latitude (60°–70° MLAT) in the daytime (10–14 MLT) approximately 1 h after the storm onset. As geomagnetic storms developed, the enhanced rTEC region extended in the MLAT and MLT directions. Subsequently, a TOI phenomenon occurred in the polar cap owing to the enhancement of two-cell convection in the high-latitude ionosphere. During the recovery phase of the geomagnetic storm, the spatial distribution of the rTEC decreased significantly from high to low latitudes. This depletion suggests the occurrence of a negative storm owing to a neutral composition (O/N 2 ) change driven by the energy input from the magnetosphere in the high-latitude thermosphere. Therefore, a strong negative storm impedes the plasmaspheric refilling process in the topside ionosphere and delays the recovery of the plasmasphere during super geomagnetic storms. Abbreviations AACGM: Altitude-adjusted corrected geomagnetic AE: Auroral Electrojet CDAWeb: Coordinated data analysis web CME: Coronal mass ejection Dst: Disturbance storm-time EISCAT: European incoherent scatter radar EMIC: Electromagnetic ion cyclotron EUV: Extreme ultraviolet SC: Geomagnetic sudden commencement GSM: Geocentric solar magnetic GNSS: Global navigation satellite system GOLD: Global-scale observations of the limb and disk HFA: High-frequency analyzer IGRF: International geomagnetic reference field IMF: Interplanetary magnetic field IMAGE EUV: Inner magnetopause to aurora global experiment extreme ultraviolet imager MLAT: Magnetic latitude MGF: Magnetic field instrument MLT: Magnetic local time NASA: National Aeronautics and Space Administration netCDF: Network common data format PFISR: Poker Flat Incoherent Scatter Radar PWE: Plasma wave experiment RINEX: Receiver-independent exchange format SAPS: Subauroral polarization stream SED: Storm-enhanced density TEC: Total electron content rTEC: Ratio of the TEC difference TIE-GCM: Thermosphere-Ionosphere-Electrodynamics General Circulation Model TOI: Tongue of ionization UHR: Upper-hybrid resonance Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials 50 data providers provided the receiver-independent exchange format data used for GNSS-TEC processing. These data are listed on the GNSS-TEC database website (http://stdb2.isee.nagoya-u.ac.jp/GPS/GPS-TEC/gnss_provider_list.html). This study used the PWE/HFA L2 v01_02 (Kasahara et al., 2018b), PWE/HFA L3 v05_09 (Kasahara et al., 2021), MGF-L2 v04.05 (Matsuoka et al., 2018b), orbit L2 v04 (Miyoshi et al., 2018c), and orbit L3 v01 (Miyoshi et al., 2018d) data. These Arase satellite observation data were obtained from the ERG Science Center website operated by ISAS/JAXA and ISEE/Nagoya University (https://ergsc.isee.nagoya-u.ac.jp/index.shtml.en, Miyoshi, et al., 2018b). The geomagnetic indices were provided by the World Data Center for Geomagnetism, Kyoto University (https://wdc.kugi.kyoto-u.ac.jp/). The high-resolution OMNI data (Papitashvili et al., 2020) were obtained from the National Aeronautics and Space Administration Coordinated Data Analysis Web (https://cdaweb.sci.gsfc.nasa.gov/index.html/). The Kp index and quiet/disturbed day list were provided by the GFZ German Research Centre for Geosciences (https://www.gfz-potsdam.de/en/kp-index/). Competing interests The authors have no competing interests to disclose. Funding This work was supported by a JSPS KAKENHI Grant No. 18KK0099, 23K22555, 24K07112, and 24K00898. Yuichi Otsuka (coauthor) was also supported by a MEXT/JSPS KAKENHI Grant No. 15H05815, 16H06286, 16H05736, 20H00197, 20H01959, 20K14546, JP21H01144, JSPS Bilateral Joint Research Projects no. JPJSBP120226504, JPJSBP120247202, and JSPS Core-to-Core Program, B. Asia-Africa Science Platforms. Shoya Matsuda (coauthor) was supported by JSPS KAKENHI (Grant No. 20K14546). Yoshizumi Miyoshi (coauthor) was supported by JSPS KAKENHI (Grant Nos. 22K21345, 23H01229, 22H00173, 21H04526, and 22KK0046). The coauthor (Takuya Sori) was supported by a JSPS KAKENHI Grant no. 24KJ0125. Authors' contributions A.S. reviewed a significant portion of the data analysis and wrote the manuscript. Y.O., M.N., and S.P. gathered worldwide GNSS data and developed the method to derive GNSS-TEC data along with A.S., K.Y., M.T., and Y.M. oversaw the production of the datasets and discussed their interpretations. I.S. and Y.M. oversaw the ERG project and discussed the interpretation of the event. Y.K. led the development and operation of PWE with the contribution of S.M., A.K., and F.T. A.M. led the development and operation of MGF. N.K. and T.S. discussed the interpretation of the ionosphere dynamics and plasmasphere during this event. K.Y. curated the Arase-MGF data, created new software used in the work, and commented on the manuscript. All authors have read and approved the final version of the manuscript. Acknowledgements We used the Inter-University Upper Atmosphere Observation NETwork (IUGONET) database (IUGONET Type-A) (Tanaka et al., 2022) and Data Analysis Software (iUgonet Data Analysis Software (UDAS): Tanaka et al., 2013, and Space Physics Environment Data Analysis System (SPEDAS): Angelopoulos et al., 2019). The GNSS data were collected and processed using the National Institute of Information and Communications Technology Science Cloud. Data from the Exploration of Energization and Radiation in Geospace (ERG) (Arase) satellite were obtained from the ERG Science Center website operated by the Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, and the Institute for Space-Earth Environmental Research, Nagoya University (https://ergsc.isee.nagoya-u.ac.jp/index.shtml.en). Authors' information Affiliations: 1. Institute for Space-Earth Environmental Research, Nagoya University, Nagoya 464-8601, Japan. Atsuki Shinbori*, Naritoshi Kitamura, Kazuhiro Yamamoto, Yuichi Otsuka, and Yoshizumi Miyoshi 2. National Institute of Information and Communications Technology, Koganei, Tokyo 184-8795, Japan. Septi Perwitasari and Michi Nishioka 3. Department of Geophysics, Tohoku University; Aoba-ku, Sendai, 980-8578, Japan. Atsushi Kumamoto 4. Planetary Plasma and Atmospheric Research Center, Tohoku University; Aoba-ku, Sendai, 980-8578, Japan. Fuminori Tsuchiya 5. Graduate School of Natural Science and Technology, Kanazawa University; Kakuma-machi, Kanazawa, 920-1192, Japan. Shoya Matsuda and Yoshiya Kasahara 6. Word Data Center for Geomagnetism, Graduate School of Science, Kyoto University; Sakyo-ku, Kyoto, 606-8502, Japan. Ayako Matsuoka 7. Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, Chuou-ku, Sagamihara, 252-5210, Japan. Iku Shinohara 8. Kyushu Institute of Technology; Sensui-cho, Tobata-ku, Kitakyushu-shi, Fukuoka, 804-8550, Japan. Mariko Teramoto 9. 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Iyemori (2022), Mid-latitude Geomagnetic Indices ASY and SYM (ASY/SYM Indices), doi:10.14989/267216. Supplementary Files graphicalabstract.png Cite Share Download PDF Status: Published Journal Publication published 20 Nov, 2025 Read the published version in Earth, Planets and Space → Version 1 posted Editorial decision: Minor Revision 19 Aug, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers invited by journal 16 Jun, 2025 Editor assigned by journal 10 Jun, 2025 First submitted to journal 04 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Uji Campus","correspondingAuthor":false,"prefix":"","firstName":"Takuya","middleName":"","lastName":"Sori","suffix":""},{"id":472162037,"identity":"596877af-8d9b-479d-bf11-35af97be08b6","order_by":10,"name":"Yuichi Otsuka","email":"","orcid":"","institution":"Nagoya Daigaku - Higashiyama Campus: Nagoya Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Yuichi","middleName":"","lastName":"Otsuka","suffix":""},{"id":472162038,"identity":"b5d0ec44-39bc-48fa-ae8e-a3c41b597031","order_by":11,"name":"Michi Nishioka","email":"","orcid":"","institution":"NICT Applied Electromagnetic Research Institute: Kokuritsu Kenkyu Kaihatsu Hojin Joho Tsushin Kenkyu Kiko Sogo Test Bed Kenkyu Kaihatsu Suishin Center Innovation Center","correspondingAuthor":false,"prefix":"","firstName":"Michi","middleName":"","lastName":"Nishioka","suffix":""},{"id":472162039,"identity":"ea3d2e42-4dfd-4616-b9c9-9ec25988c99d","order_by":12,"name":"Septi Perwitasari","email":"","orcid":"","institution":"NICT Applied Electromagnetic Research Institute: Kokuritsu Kenkyu Kaihatsu Hojin Joho Tsushin Kenkyu Kiko Sogo Test Bed Kenkyu Kaihatsu Suishin Center Innovation Center","correspondingAuthor":false,"prefix":"","firstName":"Septi","middleName":"","lastName":"Perwitasari","suffix":""},{"id":472162040,"identity":"239a7798-3d47-42b5-bc23-f770a8361e9c","order_by":13,"name":"Yoshizumi Miyoshi","email":"","orcid":"","institution":"Nagoya Daigaku - Higashiyama Campus: Nagoya Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Yoshizumi","middleName":"","lastName":"Miyoshi","suffix":""},{"id":472162041,"identity":"f93e37de-b838-49f9-8533-06a4b9b30383","order_by":14,"name":"Iku Shinohara","email":"","orcid":"","institution":"JAXA Sagamihara: Uchu Koku Kenkyu Kaihatsu Kiko - Sagamihara Campus","correspondingAuthor":false,"prefix":"","firstName":"Iku","middleName":"","lastName":"Shinohara","suffix":""}],"badges":[],"createdAt":"2025-06-04 08:22:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6818022/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6818022/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40623-025-02317-3","type":"published","date":"2025-11-20T15:57:26+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84883144,"identity":"93a3429d-5d58-422d-8702-91beabcdbda1","added_by":"auto","created_at":"2025-06-18 11:14:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":293269,"visible":true,"origin":"","legend":"\u003cp\u003eTime-series plot of (a) IMF By, (b) IMF Bz, (c) solar wind proton density, (d) solar wind flow speed, (e) AU index, (f) AL index, and (g) SYM-H index in the time interval between May 10 and 15, 2024. The time resolution of all data is 1 min, and the coordinate system of the IMF data is GSM coordinates.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6818022/v1/3382fef9fba54a0951ee7613.png"},{"id":84883145,"identity":"c85bf739-5fe7-46b6-9288-f6d823cf3357","added_by":"auto","created_at":"2025-06-18 11:14:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":314598,"visible":true,"origin":"","legend":"\u003cp\u003eTime-series plot of (a) SYM-H index, L-t diagrams of (b) and (d) electron density in the inner magnetosphere observed by the Arase satellite for the in- and out-band passes, and time-series plots of (c) and (e) average electron density in an L-value range of 2.5–3.0 for the in- and out-band passes during May 7–21, 2024. The bottom parameters show the time and the location of the Arase satellite. Panel (f) shows the configuration of the Arase satellite orbit in solar magnetic (SM) coordinates.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6818022/v1/4bad141d47efca4ccff080e4.png"},{"id":84883146,"identity":"fe099582-b996-4a6c-a35f-1d5aa7900d28","added_by":"auto","created_at":"2025-06-18 11:14:11","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":339990,"visible":true,"origin":"","legend":"\u003cp\u003eTime-series plot of (a) Kp index, (b) SYM-H index, and (c) location of the plasmapause observed by the Arase satellite during May 1–31, 2024. The notation ‘Lpp’ represents the L-value of the plasmapause location.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6818022/v1/fb28f8498928768d6c4708aa.jpeg"},{"id":84883637,"identity":"e5cdaa35-a09b-4402-a4f2-99ac40e8875a","added_by":"auto","created_at":"2025-06-18 11:22:11","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":220724,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between the location of the plasmapause and geomagnetic activities (Kp [max12]) observed during May 1–31, 2024. The red line is a linear regression line between the Kp (max12) and Lpp values.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6818022/v1/be3b844a0054e40502cb759b.jpeg"},{"id":84883639,"identity":"a8ee00e8-3666-4a29-b2b9-d4c7e122ca1b","added_by":"auto","created_at":"2025-06-18 11:22:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":444793,"visible":true,"origin":"","legend":"\u003cp\u003eTime-series plot of (a) SYM-H index and (b)–(j) polar map of rTEC in AACGM coordinates during May 10–13, 2024. The rTEC value is indicated by the color code in a range of –1.0 to 1.0. The vertical dotted lines in panel (a) are the times of each polar map. The purple and black curves in panels (b)–(j) show the sunset terminator at 105 and 300 km altitude, respectively.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6818022/v1/a8a25fc6af40c780ba7fa411.png"},{"id":84883638,"identity":"63587165-59de-4ca4-8d14-5070521f8ded","added_by":"auto","created_at":"2025-06-18 11:22:11","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":327923,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plot of the timescale of the plasmaspheric refilling as a function of the period and the minimum SYM-H value. The triangles and circles indicate events observed for the in- and out-bound passes, respectively.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6818022/v1/820c3ef8f4c8caba7914497b.jpeg"},{"id":96650090,"identity":"0f0e5381-ddf6-4545-823a-6b546f94d914","added_by":"auto","created_at":"2025-11-24 16:07:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3601086,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6818022/v1/f8f7859d-f12a-4907-8b34-c242d44b5bb1.pdf"},{"id":84883641,"identity":"e351ec19-6cad-4d40-89af-6e57327364f0","added_by":"auto","created_at":"2025-06-18 11:22:11","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":229953,"visible":true,"origin":"","legend":"","description":"","filename":"graphicalabstract.png","url":"https://assets-eu.researchsquare.com/files/rs-6818022/v1/0e8bd545f8b504ef2c796cac.png"}],"financialInterests":"","formattedTitle":"Characteristics of temporal and spatial variation of the electron density in the plasmasphere and ionosphere during the May 2024 super geomagnetic storm","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe Earth\u0026rsquo;s ionosphere is formed by partial ionization of the upper atmosphere owing to solar extreme ultraviolet (EUV) radiation and the precipitation of high-energy particles from the magnetosphere. The spatial distribution of electron density in the ionosphere varies strongly depending on latitude, local time, season, and solar activity. Furthermore, it changes considerably during geomagnetic storms and substorms driven by solar wind disturbances (e.g., Balan et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Because electron density variations and irregularities can cause total signal blackouts during strong scintillation periods and enhance satellite positioning errors (Choudhary et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Klobuchar, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1987\u003c/span\u003e), understanding the physical mechanism of electron density variation in the ionosphere during geomagnetic storms is essential for space weather prediction.\u003c/p\u003e \u003cp\u003eWhen solar wind dynamic pressure enhancement with strong southward interplanetary magnetic field (IMF) reaches the dayside magnetopause, the merging process between the Earth\u0026rsquo;s magnetic field and IMF results in the transfer of solar wind energy into the magnetosphere and increased ionospheric currents and convection electric fields between the magnetosphere and high-latitude ionosphere (Fuller-Rowell et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Part of the enhanced convection electric field is instantaneously transmitted from the polar region to the equatorial ionosphere (e.g., Kikuchi et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1978\u003c/span\u003e; Tsuji et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and the eastward component of the electric field in the daytime sector generates a storm-enhanced density (SED) phenomenon (e.g., Foster, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Shinbori et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and enhances the fountain effect (e.g., Tsurutani et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Storm-time intense ionospheric currents lead to Joule heating and upward and equatorward neutral winds in the auroral region (Blanc and Richmond, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1980\u003c/span\u003e). Neutral winds in the thermosphere reduce the O/N\u003csub\u003e2\u003c/sub\u003e ratio, and the composition change expands from high latitudes to the equator (e.g., Cai et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Therefore, through various physical processes, geomagnetic storms lead to increases and decreases in electron density in the ionosphere, which are classified as positive and negative storms, respectively (e.g., Kumar and Parkinson, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Pr\u0026ouml;lss, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). By analyzing the long-term Global Navigation Satellite System (GNSS) total electron content (TEC) from 2000 to 2019, Shinbori et al. (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) clarified the statistical behavior of electron density variations in the ionosphere during the main and recovery phases of geomagnetic storms. They reviewed the response of the ionospheric electron density to geomagnetic storms.\u003c/p\u003e \u003cp\u003eAt low-latitudes and midlatitudes, the ionospheric cold plasmas in the F2 region diffuse along the magnetic field lines, forming a plasmasphere in the inner magnetosphere. The spatial distribution of the equatorial plasma density gradually decreases with increasing L-values, and the plasma density sharply decreases at approximately L\u0026thinsp;=\u0026thinsp;4\u0026ndash;6. This sharp depletion of plasma density is called a plasmapause (Carpenter, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1966\u003c/span\u003e). The plasmapause forms near the competition region between the co-rotation and convection electric fields in the inner magnetosphere (Nishida, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1966\u003c/span\u003e). When the dawn-to-dusk convection electric field is significantly enhanced during the main phase of geomagnetic storms, the plasmapause tends to deform toward the Earth and the Sun in the nighttime and daytime sectors, respectively, and the plasmasphere is eroded (e.g., Chappell et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1970\u003c/span\u003e; Oya and Ono, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Shinbori et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). During the recovery phase of geomagnetic storms, the convection electric field decreases, and the region where the co-rotation electric field is dominant extends to the inner magnetosphere. During this period, the plasmasphere recovers to a geomagnetically quiet level for several days through plasmaspheric refilling processes (e.g., Singh et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Furthermore, because the spatial distribution of plasma density in the plasmasphere influences the generation and propagation of plasma waves and the interaction between charged particles and plasma waves, identification of the physical mechanisms of plasma density variation in the inner magnetosphere during geomagnetic storms is essential for understanding the behavior of radiation belts and ring current particles (e.g., Baker et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Singh et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe temporal variation and global structure of plasma density were intensively investigated using data from the plasmasphere using the IMAGE EUV (Inner Magnetopause to Aurora Global Experiment Extreme Ultraviolet Imager) instrument (e.g., Goldstein, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Moldwin et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Sandel et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Based on a comparison between GPS-TEC and IMAGE EUV observations during a geomagnetic storm, Foster et al. (2002) found that SED plumes in the ionosphere connect plasmaspheric plumes in the magnetosphere through magnetic field lines. Plasmaspheric plume formation and erosion are caused by an enhanced subauroral polarization stream (SAPS) and convection electric fields (Goldstein et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Shinbori et al. (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) analyzed long-term GNSS-TEC and electron density data obtained from the Arase satellite from March 23, 2017, to May 31, 2020. They showed that the midlatitude trough formed at almost the same location as the plasmapause during the main phase of geomagnetic storms. Therefore, numerous past studies have investigated the response of the plasmasphere and ionosphere to geomagnetic storms through integrated data analysis of ground and satellite observations. However, because such geomagnetic storms with a disturbance storm-time (Dst) minimum of \u0026minus;\u0026thinsp;300 to \u0026minus;\u0026thinsp;500 nT occur only a few times during one solar cycle (McPherron, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), the behavior of the plasmasphere and ionosphere during super geomagnetic storms remains insufficiently understood.\u003c/p\u003e \u003cp\u003eA super geomagnetic storm occurred on May 10\u0026ndash;11, 2024, with a maximum Kp value of 9 and a minimum horizontal symmetric disturbance (SYM-H) value of \u0026minus;\u0026thinsp;518 nT and was the most intense storm in the past 20 years. Hayakawa et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) briefly reviewed various types of plasma phenomena at the solar surface and in Earth\u0026rsquo;s magnetosphere using ground and satellite observation data during a super geomagnetic storm. Several recent studies have shown initial results of the temporal and spatial variation of the magnetosphere, plasmasphere, ionosphere, and thermosphere during the storm event. These include a significant increase in thermospheric infrared radiation level (Mlynczak et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), the poleward motion of the equatorial ionization anomaly (EIA) crests (Karan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), midlatitude plasma bubbles (Sun et al., 2024), notable changes in thermospheric composition and temperature (Evans et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), strong SED in the American longitude sector (Aa et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), strong tongue of ionization (TOI) in the Northern Hemisphere (Themens et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), low-latitude aurora over Japan (Nanjo and Shiokawa, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kataoka et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and high-frequency electromagnetic ion cyclotron (EMIC) waves in the regions close to the Earth (Jun et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). For the response of the plasmasphere to the May 2024 super geomagnetic storm, Pierrard et al. (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) reported a slow recovery of the plasmasphere based on a 3D dynamic model of the plasmasphere; however, in situ observations on the temporal variation of plasma density in the plasmasphere in the equatorial plane of the magnetosphere remain lacking. In this study, we elucidated the characteristics of the electron density variation in the plasmasphere and ionosphere during the May 2024 super geomagnetic storm based on an integrated data analysis of GNSS-TEC and Arase satellite data, together with solar wind data and geomagnetic indices.\u003c/p\u003e"},{"header":"2. Observation data and analysis method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Solar wind and geomagnetic index data\u003c/h2\u003e \u003cp\u003eTo investigate an overview of the solar-terrestrial environment during the May 2024 super geomagnetic storm, we used high-resolution OMNI data of the By and Bz components of the IMF in geocentric solar magnetic (GSM) coordinates, solar wind proton density and flow speed with a time resolution of 1 min provided by the National Aeronautics and Space Administration (NASA) Coordinated Data Analysis Web (CDAWeb) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cdaweb.sci.gsfc.nasa.gov/index.html/\u003c/span\u003e\u003cspan address=\"https://cdaweb.sci.gsfc.nasa.gov/index.html/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), the Auroral Electrojet (AE) index (World Data Center for Geomagnetism, Kyoto et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and the SYM-H index (Iyemori, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Iyemori and Rao, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; World Data Center for Geomagnetism, Kyoto et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) provided by the World Data Center for Geomagnetism, Kyoto University (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://wdc.kugi.kyoto-u.ac.jp/index.html\u003c/span\u003e\u003cspan address=\"http://wdc.kugi.kyoto-u.ac.jp/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). To identify the geomagnetically quiet days, we referred to a list of geomagnetically quiet and disturbed days provided by the German Research Center for Geosciences (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gfz-potsdam.de/en/kp-index/\u003c/span\u003e\u003cspan address=\"https://www.gfz-potsdam.de/en/kp-index/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). We also obtained the Kp index from the same provider to analyze the dependence of the plasmapause location on geomagnetic activities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Arase satellite observation data\u003c/h2\u003e \u003cp\u003eTo investigate the temporal and spatial variation of the electron density in the plasmasphere and inner magnetosphere and determine the plasmapause location, we analyzed electron density data with a time resolution of 1 min derived from in situ plasma wave measurements (the upper frequency limit of upper hybrid resonance (UHR) waves) obtained by the high-frequency analyzer (HFA) (Kumamoto et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) of the plasma wave experiment (PWE) instrument (Kasahara et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e) onboard the Arase satellite (Miyoshi et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e). Additionally, we used the magnetic field data obtained using a magnetic field instrument (MGF) (Matsuoka et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e) to derive the electron density from the UHR frequency. The magnetospheric electron density was calculated based on a previously described comprehensive method by Shinbori et al. (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). An empirical plasma density model of the magnetosphere has also been developed using the high-accuracy electron density data from the Arase satellite derived in this way (Watanabe et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this study, we identified the plasmapause location as a depression in the electron density by a factor of three or more within a short radial distance (DL\u0026thinsp;\u0026lt;\u0026thinsp;0.5, L: L-value) following the method proposed by Carpenter and Anderson (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1992\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 GNSS-TEC data\u003c/h2\u003e \u003cp\u003eTo compare the ionospheric electron density with the magnetospheric electron density observed by the Arase satellite, we used GNSS-TEC data with a time resolution of 30 s obtained from receiver-independent exchange format (RINEX) files provided by more than 50 institutes and universities. These data providers are available from the GNSS-TEC database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://stdb2.isee.nagoya-u.ac.jp/GPS/GPS-TEC/gnss_provider_list.html\u003c/span\u003e\u003cspan address=\"https://stdb2.isee.nagoya-u.ac.jp/GPS/GPS-TEC/gnss_provider_list.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). For our analysis, we calculated the TEC values based on the carrier phase difference between L1 (1575.42 MHz) and L2 (1227.60 MHz) and adjusted them to the TEC values calculated using their pseudoranges (Jakowski et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Otsuka et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Shinbori et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Grid data in the network common data format (netCDF) and quick-look plots are available on the GNSS-TEC database website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://stdb2.isee.nagoya-u.ac.jp/GPS/GPS-TEC/\u003c/span\u003e\u003cspan address=\"https://stdb2.isee.nagoya-u.ac.jp/GPS/GPS-TEC/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). In this study, we used the ratio of the TEC difference (rTEC) (Shinbori et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) to investigate the deviation from the geomagnetically quiet-time TEC value. The rTEC value was defined as the ratio of the difference between the TEC and the average TEC values of 10 quiet days to the quiet-day TEC value. The rTEC was calculated using the following equation:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:R=\\frac{\\delta\\:I}{\\stackrel{-}{I}}=\\frac{I-\\stackrel{-}{I}}{\\stackrel{-}{I}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere the variables \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:R\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:I\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{I}\\)\u003c/span\u003e\u003c/span\u003e, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\delta\\:I\\)\u003c/span\u003e\u003c/span\u003e are the rTEC, TEC, average TEC values of 10 quiet days, and the difference between the TEC and average TEC values, respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Analysis results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 An overview of the May 2024 super geomagnetic storm\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the temporal variation in the By and Bz components of the IMF in GSM coordinates, solar wind proton density, flow speed, and geomagnetic indices (AU, AL, and SYM-H) for the time interval between May 10 and 15, 2024. Solar radiation was relatively high when the F10.7 index (Tapping, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) reached 220\u0026ndash;230 solar flux units (sfu; 1 sfu\u0026thinsp;=\u0026thinsp;10\u003csup\u003e\u0026minus;\u0026thinsp;22\u003c/sup\u003e W/m\u003csup\u003e2\u003c/sup\u003e/Hz). Multiple CMEs associated with the flare activity erupted from Active Region 13664 and hit the Earth\u0026rsquo;s magnetosphere at \u0026sim;17:03 UT on May 10, triggering the super geomagnetic storm over the following three days. The By and Bz components of the IMF were highly perturbed with peak-to-peak amplitudes of 67 and 50.18 nT, respectively, after the passage of the interplanetary shock (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea and b). The Bz component of the IMF showed multiple negative excursions, and the first major dip occurred between 19:00 and 22:30 UT on May 10, with a minimum value of \u0026minus;\u0026thinsp;43.43 nT at 22:12 UT. Subsequently, the Bz component changed from negative to positive. The second major dip occurred between 23:46 UT on May 10 and 05:00 UT on May 11, with a minimum value of \u0026minus;\u0026thinsp;47.85 nT recorded at 00:36 UT. After the arrival of the interplanetary shock, the solar wind density and flow speed showed a sudden increase up to 56 cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e and 713 km/s, respectively (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec and d). Subsequently, the solar wind density fluctuated with large amplitudes until 12:00 UT on 12 May. The solar wind speed reached a maximum (1026 km/s) at 17:12 UT on May 12.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg, the SYM-H index increased suddenly within a few minutes at 17:05 UT on May 10, indicating the occurrence of a geomagnetic sudden commencement (SC) caused by the sudden compression of the magnetosphere (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg). The SC amplitude was 74 nT. Subsequently, the SYM-H index showed a monotonic decrease down to \u0026minus;\u0026thinsp;518 nT at 02:14 UT on May 11, which was associated with the development of a ring current in the inner magnetosphere. Following the main phase of the geomagnetic storm, the SYM-H index gradually increased over several days owing to the decay of the ring current. During the storm period, the AU and AL indices were highly perturbed with peak values of ~\u0026thinsp;1800 and ~\u0026thinsp;\u0026minus;\u0026thinsp;3700 nT, respectively, in association with the enhancement of auroral electrojet caused by the development of the high-latitude convection and the occurrence of substorms (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee and f). In addition, the SYM-H index revealed that this storm event was the second-largest geomagnetic storm during the period of the archive of the SYM-H index since 1981.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.2 Characteristics of electron density variation in the inner magnetosphere and plasmasphere observed by the Arase satellite\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo investigate the characteristics of the temporal and spatial variation of electron density in the inner magnetosphere and plasmasphere during the May 2024 super geomagnetic storm, we analyzed electron density data obtained from Arase satellite observations. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the time-series plots of the SYM-H index and average electron density in an L-value range of 2.5\u0026ndash;3.0 for the in- and out-bound passes and L-t diagrams of the electron density for the in- and out-bound passes during May 7\u0026ndash;21, 2024. The L-value (McIlwain, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1961\u003c/span\u003e) was calculated using the International Geomagnetic Reference Field (IGRF) 13 model (Alken et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). During this period, the Arase satellite flowed in the dawn-side and dusk-side inner magnetosphere for out- and in-bound passes, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef). As shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed, the high-density region (Ne\u0026thinsp;\u0026gt;\u0026thinsp;300 cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e) contracted from L\u0026thinsp;=\u0026thinsp;4.0 to L\u0026thinsp;=\u0026thinsp;2.5 within a day for both in- and out-bound passes after the onset (17:05 UT on May 10) of the geomagnetic storm. The average electron density in an L-value range of 2.5\u0026ndash;3.0 also showed a large depletion of one order of magnitude (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). The electron density variation indicates that the plasmasphere was eroded owing to the strong enhancement of the convection electric field in the magnetosphere during the geomagnetic storm. Furthermore, an enhanced electron density region appeared in the higher-L-value region (L\u0026thinsp;\u0026gt;\u0026thinsp;6.0) for several passes during the main and early recovery phases of the geomagnetic storm. The electron density in this region (L\u0026thinsp;\u0026gt;\u0026thinsp;6.0) was two or three orders of magnitude larger than that during other periods. This observation indicated that the Arase satellite crossed the magnetopause and traversed the magnetosheath region. Because the electron density in the magnetosheath is beyond the scope of this study, the details of this region will be discussed in another study. After the early recovery phase of the geomagnetic storm, the high-density region gradually expanded to the outer region (L\u0026thinsp;=\u0026thinsp;4.0) over 3\u0026ndash;4 days. As the plasmasphere expanded radially, the average electron density gradually increased to the level of the pre-storm phase (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). After May 16, the SYM-H index showed the occurrence of small geomagnetic storms with amplitudes of 80\u0026ndash;100 nT (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). After these storm events, the average electron density decreased by a factor of five or more and recovered to the pre-storm phase level within a day.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Location of the plasmapause in the inner magnetosphere\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, we observed a large electron density depletion in the inner magnetosphere and shrinkage of the plasmasphere during the May 2024 super geomagnetic storm. Here, we analyze the temporal variation in the location of the plasmapause in the inner magnetosphere on May 1\u0026ndash;31, 2024, including periods of other geomagnetic storms. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the temporal variations in Kp and SYM-H indices and the location of the plasmapause. In Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, the location of the plasmapause rapidly moved to a lower L-value from 7.0 to 1.5 after the onset of the May 2024 super geomagnetic storm. This plasmapause motion indicates that the plasma sphere contracted significantly, owing to the enhancement of the magnetospheric convection electric field. During geomagnetic storms, the Kp value reached 9 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). After the onset of the geomagnetic storm recovery phase, the plasmapause slowly moved to a higher L-value from 1.5 to 4.0. This observation indicates that the plasmasphere tends to recover its quiet-time level owing to the plasmaspheric refilling process. The recovery time of the plasmasphere was much longer than that of other geomagnetic storm events, as indicated by the red arrows in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the location of the plasmapause tended to shift to lower L-values as geomagnetic activity increased. To investigate the dependence of Kp on the location of the plasmapause, we analyzed the relationship between the location of the plasmapause and the Kp index using the method proposed by Moldwin et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). We used the maximum Kp value 12 h prior to the plasmapause observation. The Kp value was defined as Kp (max12). Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the location of the plasmapause as a function of Kp (max12) for both in- and out-bound passes. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows an evident trend of decreasing L-values with increasing Kp; however, the plasmapause location tends to scatter for lower Kp values (Kp\u0026thinsp;\u0026lt;\u0026thinsp;4). From the least-squares linear regression of all Lpp identified by the Arase satellite, the following relationship provides the plasmapause location for both in- and out-bound passes.\u003c/p\u003e \u003cp\u003e \u003cdiv id=\"Equb\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:Lpp=\\left(5.58\\pm\\:0.148\\right)-\\left(0.420\\pm\\:0.040\\right)*Kp\\:\\left(max12\\right)$$\u003c/div\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe coefficient of determination (R) was 0.64. The standard deviation of the observations for this line was approximately 0.967 Lpp.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Temporal and spatial variation of electron density in the ionosphere obtained by the GNSS-TEC technique\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows a time-series plot of the SYM-H index and polar maps of rTEC in the Northern Hemisphere in Altitude-Adjusted Corrected Geomagnetic (AACGM) coordinates (Shepherd, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The time of each polar map corresponds to that indicated by the dotted vertical lines in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea. Before the onset of the SC of the May 2024 geomagnetic storm, the spatial distribution of rTEC was almost homogeneous, with an rTEC value of approximately 0.0 near the geomagnetically quiet level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Approximately 1 h after the onset of SC, an evident enhancement of rTEC appeared in the daytime (10\u0026ndash;14 MLT) ionosphere in the MLAT range of 50\u0026ndash;70\u0026deg; (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). This enhancement corresponds to the SED phenomenon, which is caused by the uplift of the ionosphere in a sunlit region owing to the enhancement of the convection electric field. As the geomagnetic storm developed, the rTEC enhancement region extended to other MLTs and magnetic latitudes within a few hours (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed). In Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed, an apparent depletion of rTEC with a narrow latitudinal structure appears as a region equatorward of the weak enhancement of rTEC associated with an auroral oval in the dusk-to-midnight sectors. This rTEC depletion corresponded to a midlatitude trough. In this case, the center of rTEC depletion was located at approximately 45\u0026deg; (MLAT). Additionally, an rTEC enhancement with a plume-like structure was observed in the polar cap region, which connects to an SED plume in the midlatitude ionosphere (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee). This rTEC enhancement corresponds to a TOI phenomenon associated with the enhancement of two-cell convection in the polar cap region during the main phase of a geomagnetic storm. During this period, the auroral oval and midlatitude trough locations moved to much lower latitudes of 50\u0026deg; and 40\u0026deg; (MLAT), respectively, in the midnight sector.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAfter the onset of the geomagnetic storm recovery phase, the TOI structure disappeared in the polar cap region, and the enhanced rTEC region associated with the SED phenomenon decreased in the midlatitude ionosphere (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ef). Instead, a significant depletion of the rTEC appeared from high to low latitudes over a wide range of MLTs. This phenomenon corresponds to a negative storm caused by an enhancement in the recombination process owing to a neutral composition change in the thermosphere. The negative storm peaked at 18:00 UT on May 11 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eh) and gradually weakened with time (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ei and j). This phenomenon was observed at least until the late recovery phase of the geomagnetic storm (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ej).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Characteristics of the temporal and spatial variation of GNSS-TEC from the high- to low-latitude ionosphere\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the rTEC enhancement corresponding to the SED phenomenon appeared with an amplitude of ˃ 0.5 at high latitudes (50\u0026deg; \u0026le; MLAT\u0026thinsp;\u0026le;\u0026thinsp;75\u0026deg;) on the dayside (10\u0026ndash;14 MLT) approximately 1 h after the onset of the geomagnetic storm. The time difference between the onset of rTEC enhancement and geomagnetic storms is almost consistent with that reported in previous studies (e.g., Sori et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Shinbori et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As the geomagnetic storm developed, this structure extended to lower latitudes over a wide range of MLTs. The strong SED suggests that the eastward electric field penetrates to the mid- and low-latitude ionosphere and drives the vertical \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:E\\times\\:B\\)\u003c/span\u003e\u003c/span\u003e drift of the F-region plasma in the sunlit region (e.g., David et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Lu et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sori et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Shinbori et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Based on a statistical analysis of the global TEC data for several geomagnetic storms that occurred in different seasons, Coster et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) showed that SED phenomena frequently occurred during or near the equinoxes and that the SED amplitude became the minimum near the solstices. Furthermore, by analyzing 663 geomagnetic storm events over 20 years (2000\u0026ndash;2019), Shinbori et al. (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found that the amplitudes of the SED base and plume tended to be small around the summer solstice in the Northern Hemisphere. However, the present study showed that the SED phenomenon had a large rTEC amplitude of ˃ 1.0 during the May 2024 super geomagnetic storm. The occurrence of the strong SED phenomenon in summer differs from the seasonal dependence of positive storms at midlatitudes, as reported in previous studies (Buonsanto, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Mendillo, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Pr\u0026ouml;lss, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). An exceptionally strong convection electric field likely imposed on the entire ionosphere (Aa et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) caused a strong SED during the main phase of the super geomagnetic storm.\u003c/p\u003e \u003cp\u003eIn the polar cap, a strong rTEC enhancement appeared with a stream-like structure during the main phase of the geomagnetic storm (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee). This rTEC structure corresponded to the TOI phenomenon generated by enhanced two-cell convection at high latitudes (e.g., David et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Heelis, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Knudsen, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1974\u003c/span\u003e; Sato, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1959\u003c/span\u003e; Sato and Rourke, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1964\u003c/span\u003e; Sojka et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Using the Thermosphere\u0026ndash;Ionosphere\u0026ndash;Electrodynamics General Circulation Model (TIE-GCM), Liu et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) showed that the amplitude of the TOI phenomenon is much larger in winter than in other seasons and that the midlatitude SED as a source of TOI is also enhanced significantly in winter. The rTEC amplitude in the midlatitude ionosphere on the dayside was much larger than the statistical analysis results of the rTEC during geomagnetic storms, as shown by Shinbori et al. (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Despite the summer in the Northern Hemisphere, the TOI amplitude reached more than 1.0 in rTEC. Themens et al. (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) also reported a strong TOI phenomenon in the polar cap during the May 2024 super geomagnetic storm. The characteristics of the strong TOI phenomenon in the polar cap differ from the seasonal dependence of the TOI amplitude reported in previous studies (e.g., Sojka et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; David et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Shinbori et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, the strong SED on the dayside allows much more plasma transport from the midlatitude ionosphere to the polar cap, forming a strong TOI phenomenon.\u003c/p\u003e \u003cp\u003eAfter the onset of the recovery phase of the geomagnetic storm, a strong negative storm occurred in the polar cap as well as in low-latitude regions (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ef\u0026ndash;j). The rTEC depletion associated with the negative storm reached 50\u0026ndash;90% of the geomagnetically quiet-time level. This phenomenon lasted for more than two days. Themens et al. (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) also reported the strong negative storm occurrence in the Northern Hemisphere. Furthermore, they observed a strong depletion of the electron density in the F-region of the ionosphere or a disappearance of the F2-layer at high latitudes using the European Incoherent Scatter Radar (EISCAT) Svalbard radar and the Poker Flat Incoherent Scatter Radar (PFISR) observation data. By analyzing neutral composition data obtained from NASA's Global-scale Observations of the Limb and Disk (GOLD) mission, Evans et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) showed that the O/N\u003csub\u003e2\u003c/sub\u003e ratio and thermospheric temperatures decreased and increased, respectively, by 50% during the recovery phase of a geomagnetic storm. Based on a modeling study, Sojka et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) demonstrated that substantial ion outflow and thermospheric heating occurred during the initial and main phases of a super geomagnetic storm on March 13\u0026ndash;15, 1989. From the results of previous studies, a severe and long-lasting negative storm is driven by a neutral composition change owing to the changes in thermospheric circulation associated with intense auroral and Joule heating during a super geomagnetic storm. The quantitative evaluation of the neutral composition change in the thermosphere will be examined using a global atmosphere-ionosphere coupling model in the future study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Characteristics of the electron density variation in the plasmasphere and inner magnetosphere\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the Arase satellite successfully performed in situ plasma wave observations in the inner magnetosphere and plasmasphere during the May 2024 super geomagnetic storm, and we had the opportunity to investigate the spatial and temporal variation of the electron density above the topside ionosphere. The present study showed that the high-density region of electron density in the inner magnetosphere shrank significantly after the onset of the geomagnetic storm (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb and d) and that the plasmapause location moved abruptly from L\u0026thinsp;=\u0026thinsp;7.0 to L\u0026thinsp;=\u0026thinsp;1.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These results indicate that the plasmasphere was eroded owing to the strong enhancement of convection electric fields in the inner magnetosphere during the main phase of the geomagnetic storm (e.g., Nishida, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1966\u003c/span\u003e). By analyzing IMAGE EUV image data, Baker et al. (2004) showed that the plasmapause location was within L\u0026thinsp;=\u0026thinsp;2.0, and at some MLTs, it was at L\u0026thinsp;=\u0026thinsp;1.5 during the Halloween super geomagnetic storm. For this superstorm event, in situ observations of the plasma density were not conducted in the equatorial plane of the inner magnetosphere. In the present study, we succeeded in detecting a low L-shell plasmapause during the May 2024 super geomagnetic storm using Arase satellite observation data. The IMAGE and Arase satellite observations suggest that such an extremely small plasmasphere occurs only during the strongest geomagnetic storms. Using the BSPM plasmasphere-ionosphere model, Pierrard et al. (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) investigated the spatial and temporal variations in plasma density in the plasmasphere during the geomagnetic storm of May 2024. Their results showed that the plasmapause locations were approximately 2.3 Re in the post-midnight sector and 5 Re at the endpoint of the plasmaspheric plume in the afternoon. The average location of the calculated plasmapause was 3 Re. Furthermore, Pierrard et al. (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) analyzed the magnetic field and plasma observations of low-Earth orbiting satellites and showed that the plasmapause location at the altitude of the topside ionosphere abruptly moved to a lower L-value from 4.0 to 1.8 within a few hours. The Arase and Swarm satellite observations showed that the plasmasphere shrank more deeply than expected by the BSPM plasmasphere-ionosphere model.\u003c/p\u003e \u003cp\u003eAfter the onset of the recovery phase of the geomagnetic storm, the high-density region of electron density moved slowly outward, and the electron density at L\u0026thinsp;=\u0026thinsp;2.5\u0026ndash;3.0 recovered the geomagnetic quiet-time level for more than three days (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and e). This result indicates that plasmaspheric refilling is much slower than the typical timescale of two days required to refill the geomagnetically quiet-time level of plasma density in the plasmasphere (e.g., Pierrard et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The following subsection discusses the possible causes for this slow refilling process.\u003c/p\u003e \u003cp\u003eBecause different types of plasma waves are generated inside and outside the plasmapause, and they accelerate and scatter energetic particles on the radiation belts (e.g., Ripoll et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), the plasmapause location is important for understanding the electromagnetic and particle environments during geomagnetic storms in the context of cross-energy coupling (Miyoshi et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, 2018). During this event, the plasmapause shrank deep into the inner magnetosphere for a long time (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This result suggests that the response of high-energy particles in the inner magnetosphere differs from that in typical cases. Unusual electron belts appeared in the lower L-value region after the May 2024 super geomagnetic storm, and a strong enhancement of the high-energy proton flux from 9.5 to 13 MeV occurred in the southern part of the South Atlantic Anomaly (Pierrard et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Slow recovery of the plasmasphere after the May 2024 storm\u003c/h2\u003e \u003cp\u003eAs shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the plasmasphere required more than three days to recover the geomagnetically quiet-time level after the onset of the May 2024 geomagnetic storm. The timescale of the plasmaspheric refilling process is believed to be much longer than that of other geomagnetic storm events, as indicated by the red arrows in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. To clarify the slow refilling of the plasmasphere during the May 2024 geomagnetic storm, we statistically examined the timescale of plasmaspheric refilling for 92 CME-driven geomagnetic storm events from March 2017 to December 2024. A list of geomagnetic storm events is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the scatter plot of the time constant of the plasmaspheric refilling at L\u0026thinsp;=\u0026thinsp;2.5\u0026ndash;3.0 as a function of the period and minimum SYM-H value. Here, the time constant is defined as the time difference between the start of the electron density depletion and the time taken to reach the electron density before the onset of the geomagnetic storm. In Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, most geomagnetic storm events show that the time constant is distributed within 2 d regardless of the size of the geomagnetic storms. The time constant of the May 2024 geomagnetic storm was much longer than those of the other geomagnetic storms, except for several events (August 2018, April 2023, and October 2024). These events appeared to contribute to the prevention of plasmaspheric refilling.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of 92 CME-type geomagnetic storms and timescale of the plasmaspheric refilling for the in- and out-bound passes. N/A means that we could not identify the plasmapause location with Arase electron density data.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eStorm peak for each event\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eTimescale of the plasmaspheric refilling [day]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvent #\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSYM-H of peak [nT]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIn-bound\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOut-bound\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017/4/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7:10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017/5/28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7:13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017/7/16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13:17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017/9/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0:53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017/9/13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0:08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018/3/10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4:17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018/8/26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7:11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019/5/11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3:00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019/5/14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6:22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020/4/20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12:27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020/10/5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20:25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021/5/12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14:15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021/5/27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8:47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021/8/27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23:23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e 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align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2022/4/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0:49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2022/4/10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6:41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2022/4/14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22:36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/2/11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6:28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/3/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17:57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/3/21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19:33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/3/24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16:14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/4/16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21:27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/4/19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19:15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023/3/24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2:19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e 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align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023/9/25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2:23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023/10/21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7:02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023/11/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23:06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023/11/5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16:54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023/11/13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023/12/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13:30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023/12/2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0:20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023/12/14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8:14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023/12/16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0:58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023/12/17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16:18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e 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align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/5/11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2:24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/5/16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10:37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/5/17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23:04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/6/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9:31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/6/11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3:43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/6/16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12:02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/6/23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18:12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/6/26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11:35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/6/28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12:06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/7/5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4:45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/7/26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6:09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/7/30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11:16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/8/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17:04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/8/12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16:04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/8/17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22:24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/8/28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5:36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/8/31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2:20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/9/12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13:49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/9/17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4:24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/9/24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10:45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/10/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7:44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/10/10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23:14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/10/26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/10/28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10:44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/11/9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12:37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024/12/17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6:30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe timescale to refill the plasmasphere to the geomagnetically quiet-time level depends on the amount of supply of light ions (H\u003csup\u003e+\u003c/sup\u003e) from the topside ionosphere through H-O\u003csup\u003e+\u003c/sup\u003e charge exchange \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:H+{O}^{+}\\rightleftharpoons\\:{H}^{+}+O\\)\u003c/span\u003e\u003c/span\u003e (e.g., Banks and Kockarts, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1973\u003c/span\u003e; Richards and Torr, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Stancil et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Krall and Huba, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The H-O\u003csup\u003e+\u003c/sup\u003e reaction rate depends on the neutral hydrogen temperature, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{T}_{n}\\)\u003c/span\u003e\u003c/span\u003e, the number density of neutral hydrogen, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{n}_{H}\\)\u003c/span\u003e\u003c/span\u003e, and the number density of ionized oxygen, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{n}_{{O}^{+}}\\)\u003c/span\u003e\u003c/span\u003e (Richards and Torr, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). This result indicates that a large depletion in the density of ionized oxygen, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{n}_{{O}^{+}}\\)\u003c/span\u003e\u003c/span\u003e causes a decrease in the H-O\u003csup\u003e+\u003c/sup\u003e reaction rate. However, using the Naval Research Laboratory Sami2 model, Krall and Huba (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) showed that the H\u003csup\u003e+\u003c/sup\u003e refilling rates tended to increase with oxygen density for low solar activity (F\u003csub\u003e10.7\u003c/sub\u003e \u0026lt; 150) and that the refilling rates decreased slightly because of the enhancement of neutral oxygen density at high solar activity (F\u003csub\u003e10.7\u003c/sub\u003e \u0026gt; 180). Their findings indicated that the plasmaspheric refilling process becomes slower for high solar activity owing to the enhancement of the neutral oxygen density in the topside ionosphere. For the May 2024 super geomagnetic storm, a strong and long-lasting negative storm occurred from the polar cap to the low-latitude ionosphere, and the rTEC value decreased by 50\u0026ndash;90%. In addition, we confirmed that such strong negative storms occurred during the geomagnetic storms in August 2018, April 2023, and October 2024 (not shown here). The occurrence of a strong negative storm indicates that the neutral composition ratio [O]/[N\u003csub\u003e2\u003c/sub\u003e] in the thermosphere decreases because of changes in the thermospheric circulation associated with strong auroral and Joule heating during geomagnetic storms. A large depletion in [O]/[N\u003csub\u003e2\u003c/sub\u003e] occurred during the recovery phase of a geomagnetic storm (Evans et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The decreased O\u003csup\u003e+\u003c/sup\u003e density in the topside ionosphere is believed to reduce the H-O\u003csup\u003e+\u003c/sup\u003e reaction rate, causing a slow refilling process. Future studies should clarify the effect of negative storms on the plasmaspheric refilling process using a plasmasphere-ionosphere-atmosphere coupling model.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eTo elucidate the temporal and spatial variation in electron density in the plasmasphere and ionosphere during the May 2024 super geomagnetic storm, we analyzed GNSS-TEC and Arase satellite observation data. Consequently, the L-t plot of the electron density revealed contraction of the plasmasphere from L\u0026thinsp;=\u0026thinsp;7.0 to L\u0026thinsp;=\u0026thinsp;1.5 within 9 h of the onset of the geomagnetic storm. The location of the plasmapause tended to move to a lower L-value with increasing geomagnetic activity and scatter for lower Kp values (Kp\u0026thinsp;\u0026lt;\u0026thinsp;4). After the onset of the geomagnetic storm recovery phase, the plasmapause slowly moved to a higher L-value. It recovered the level of geomagnetically quiet times over four days. The timescale of the plasmaspheric refilling was significantly longer than that of normal/typical CME-driven geomagnetic storms. Several polar maps of rTEC in the Northern Hemisphere in geomagnetic coordinates show that an enhancement of the rTEC value occurred at high latitude (60\u0026deg;\u0026ndash;70\u0026deg; MLAT) in the daytime (10\u0026ndash;14 MLT) approximately 1 h after the storm onset. As geomagnetic storms developed, the enhanced rTEC region extended in the MLAT and MLT directions. Subsequently, a TOI phenomenon occurred in the polar cap owing to the enhancement of two-cell convection in the high-latitude ionosphere. During the recovery phase of the geomagnetic storm, the spatial distribution of the rTEC decreased significantly from high to low latitudes. This depletion suggests the occurrence of a negative storm owing to a neutral composition (O/N\u003csub\u003e2\u003c/sub\u003e) change driven by the energy input from the magnetosphere in the high-latitude thermosphere. Therefore, a strong negative storm impedes the plasmaspheric refilling process in the topside ionosphere and delays the recovery of the plasmasphere during super geomagnetic storms.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAACGM: Altitude-adjusted corrected geomagnetic\u003c/p\u003e\n\u003cp\u003eAE: Auroral Electrojet\u003c/p\u003e\n\u003cp\u003eCDAWeb: Coordinated data analysis web\u003c/p\u003e\n\u003cp\u003eCME: Coronal mass ejection\u003c/p\u003e\n\u003cp\u003eDst: Disturbance storm-time\u003c/p\u003e\n\u003cp\u003eEISCAT: European incoherent scatter radar\u003c/p\u003e\n\u003cp\u003eEMIC: Electromagnetic ion cyclotron\u003c/p\u003e\n\u003cp\u003eEUV: Extreme ultraviolet\u003c/p\u003e\n\u003cp\u003eSC: Geomagnetic sudden commencement\u003c/p\u003e\n\u003cp\u003eGSM: Geocentric solar magnetic\u003c/p\u003e\n\u003cp\u003eGNSS:\u0026nbsp;Global navigation satellite system\u003c/p\u003e\n\u003cp\u003eGOLD: Global-scale observations of the limb and disk\u003c/p\u003e\n\u003cp\u003eHFA: High-frequency analyzer\u003c/p\u003e\n\u003cp\u003eIGRF: International geomagnetic reference field\u003c/p\u003e\n\u003cp\u003eIMF: Interplanetary magnetic field\u003c/p\u003e\n\u003cp\u003eIMAGE EUV: Inner magnetopause to aurora global experiment extreme ultraviolet imager\u003c/p\u003e\n\u003cp\u003eMLAT: Magnetic latitude\u003c/p\u003e\n\u003cp\u003eMGF: Magnetic field instrument\u003c/p\u003e\n\u003cp\u003eMLT: Magnetic local time\u003c/p\u003e\n\u003cp\u003eNASA: National Aeronautics and Space Administration\u003c/p\u003e\n\u003cp\u003enetCDF: Network common data format\u003c/p\u003e\n\u003cp\u003ePFISR: Poker Flat Incoherent Scatter Radar\u003c/p\u003e\n\u003cp\u003ePWE: Plasma wave experiment\u003c/p\u003e\n\u003cp\u003eRINEX: Receiver-independent exchange format\u003c/p\u003e\n\u003cp\u003eSAPS: Subauroral polarization stream\u003c/p\u003e\n\u003cp\u003eSED: Storm-enhanced density\u003c/p\u003e\n\u003cp\u003eTEC: Total electron content\u003c/p\u003e\n\u003cp\u003erTEC: Ratio of the TEC difference\u003c/p\u003e\n\u003cp\u003eTIE-GCM: Thermosphere-Ionosphere-Electrodynamics General Circulation Model\u003c/p\u003e\n\u003cp\u003eTOI: Tongue of ionization\u003c/p\u003e\n\u003cp\u003eUHR: Upper-hybrid resonance\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e50 data providers provided the receiver-independent exchange format data used for GNSS-TEC processing. These data are listed on the GNSS-TEC database website (http://stdb2.isee.nagoya-u.ac.jp/GPS/GPS-TEC/gnss_provider_list.html). This study used the PWE/HFA L2 v01_02 (Kasahara et al., 2018b), PWE/HFA L3 v05_09 (Kasahara et al., 2021), MGF-L2 v04.05 (Matsuoka et al., 2018b), orbit L2 v04 (Miyoshi et al., 2018c), and orbit L3 v01 (Miyoshi et al., 2018d) data. These Arase satellite observation data were obtained from the ERG Science Center website operated by ISAS/JAXA and ISEE/Nagoya University (https://ergsc.isee.nagoya-u.ac.jp/index.shtml.en, Miyoshi, et al., 2018b). The geomagnetic indices were provided by the World Data Center for Geomagnetism, Kyoto University (https://wdc.kugi.kyoto-u.ac.jp/). The high-resolution OMNI data (Papitashvili et al., 2020) were obtained from the National Aeronautics and Space Administration Coordinated Data Analysis Web (https://cdaweb.sci.gsfc.nasa.gov/index.html/). The Kp index and quiet/disturbed day list were provided by the GFZ German Research Centre for Geosciences (https://www.gfz-potsdam.de/en/kp-index/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by a JSPS KAKENHI Grant No. 18KK0099, 23K22555, 24K07112, and 24K00898. Yuichi Otsuka (coauthor) was also supported by\u0026nbsp;a MEXT/JSPS KAKENHI Grant No.\u0026nbsp;15H05815, 16H06286, 16H05736, 20H00197, 20H01959, 20K14546, JP21H01144, JSPS Bilateral Joint Research Projects no. JPJSBP120226504, JPJSBP120247202, and\u0026nbsp;JSPS Core-to-Core Program, B. Asia-Africa Science Platforms.\u0026nbsp;Shoya Matsuda\u0026nbsp;(coauthor)\u0026nbsp;was supported by JSPS KAKENHI (Grant No. 20K14546). Yoshizumi Miyoshi\u0026nbsp;(coauthor)\u0026nbsp;was supported by JSPS KAKENHI (Grant Nos. 22K21345, 23H01229, 22H00173, 21H04526,\u0026nbsp;and 22KK0046). The coauthor (Takuya Sori) was supported by a JSPS KAKENHI Grant no. 24KJ0125.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.S. reviewed a significant portion of the data analysis and wrote the manuscript. Y.O., M.N., and S.P. gathered worldwide GNSS data and developed the method to derive GNSS-TEC data along with A.S., K.Y., M.T., and Y.M. oversaw the production of the datasets and discussed their interpretations. I.S. and Y.M. oversaw the ERG project and discussed the interpretation of the event. Y.K. led the development and operation of PWE with the contribution of S.M., A.K., and F.T. A.M. led the development and operation of MGF. N.K. and T.S. discussed the interpretation of the ionosphere dynamics and plasmasphere during this event. K.Y. curated the Arase-MGF data, created new software used in the work, and commented on the manuscript. All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used the Inter-University Upper Atmosphere Observation NETwork (IUGONET) database (IUGONET Type-A) (Tanaka et al., 2022) and Data Analysis Software (iUgonet Data Analysis Software (UDAS): Tanaka et al., 2013, and Space Physics Environment Data Analysis System (SPEDAS): Angelopoulos et al., 2019). The GNSS data were collected and processed using the National Institute of Information and Communications Technology Science Cloud. Data from the Exploration of Energization and Radiation in Geospace (ERG) (Arase) satellite were obtained from the ERG Science Center website operated by the Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, and the Institute for Space-Earth Environmental Research, Nagoya University (https://ergsc.isee.nagoya-u.ac.jp/index.shtml.en).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAffiliations:\u003c/p\u003e\n\u003cp\u003e1. Institute for Space-Earth Environmental Research, Nagoya University, Nagoya 464-8601, Japan.\u003c/p\u003e\n\u003cp\u003eAtsuki Shinbori*, Naritoshi Kitamura, Kazuhiro Yamamoto, Yuichi Otsuka, and Yoshizumi Miyoshi\u003c/p\u003e\n\u003cp\u003e2. National Institute of Information and Communications Technology, Koganei, Tokyo 184-8795, Japan.\u003c/p\u003e\n\u003cp\u003eSepti Perwitasari and Michi Nishioka\u003c/p\u003e\n\u003cp\u003e3. Department of Geophysics, Tohoku University; Aoba-ku, Sendai, 980-8578, Japan.\u003c/p\u003e\n\u003cp\u003eAtsushi Kumamoto\u003c/p\u003e\n\u003cp\u003e4. Planetary Plasma and Atmospheric Research Center, Tohoku \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; University; Aoba-ku, Sendai, 980-8578, Japan.\u003c/p\u003e\n\u003cp\u003eFuminori Tsuchiya\u003c/p\u003e\n\u003cp\u003e5. Graduate School of Natural Science and Technology, Kanazawa University; Kakuma-machi, Kanazawa, 920-1192, Japan.\u003c/p\u003e\n\u003cp\u003eShoya Matsuda and Yoshiya Kasahara\u003c/p\u003e\n\u003cp\u003e6. Word Data Center for Geomagnetism, Graduate School of Science, Kyoto University; Sakyo-ku, Kyoto, 606-8502, Japan.\u003c/p\u003e\n\u003cp\u003eAyako Matsuoka\u003c/p\u003e\n\u003cp\u003e7. Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, Chuou-ku, Sagamihara, 252-5210, Japan.\u003c/p\u003e\n\u003cp\u003eIku Shinohara\u003c/p\u003e\n\u003cp\u003e8. Kyushu Institute of Technology; Sensui-cho, Tobata-ku, Kitakyushu-shi, Fukuoka, 804-8550, Japan.\u003c/p\u003e\n\u003cp\u003eMariko Teramoto\u003c/p\u003e\n\u003cp\u003e9. Research Institute for Sustainable Humanosphere, Kyoto University, Gokasyo, Uji, Kyoto, 611-0011, Japan.\u003c/p\u003e\n\u003cp\u003eTakuya Sori\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAa, E., Zhang, S.-R., Lei, J., Huang, F., Erickson, P. J., Coster, A. J., and Luo, B. (2024). Significant midlatitude plasma density peaks and dual‐hemisphere SED during the 10\u0026ndash;11 May 2024 super geomagnetic storm, \u003cem\u003eJ. Geophys. Res.\u003c/em\u003e, \u003cstrong\u003e129\u003c/strong\u003e, e2024JA033360, doi:10.1029/2024JA033360.\u003c/li\u003e\n\u003cli\u003eAlken, P., Th\u0026eacute;bault, E., Beggan, C. D., Amit, H., Aubert, J., Baerenzung, J., Bondar, T. N., Brown, W. J., Califf, S., Chambodut, A., Chulliat, A., Cox, G. A., Finlay, C. 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Kamei (2015), Geomagnetic AE index, doi:10.17593/15031-54800.\u003c/li\u003e\n\u003cli\u003eWorld Data Center for Geomagnetism, Kyoto, S. Imajo, A. Matsuoka, H. Toh, and T. Iyemori (2022), Mid-latitude Geomagnetic Indices ASY and SYM (ASY/SYM Indices), doi:10.14989/267216.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"earth-planets-and-space","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"epsp","sideBox":"Learn more about [Earth, Planets and Space](http://earth-planets-space.springeropen.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/epsp/default.aspx","title":"Earth, Planets and Space","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"May 2024 super geomagnetic storm, electron density variation in the plasmasphere and ionosphere, GNSS-TEC, Arase satellite, plasmaspheric refilling process, negative storm, neutral composition, plasma convection, storm-enhanced density, tongue of ionization.","lastPublishedDoi":"10.21203/rs.3.rs-6818022/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6818022/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe spatial distribution of electron density in the ionosphere exhibits notable variability and undergoes considerable changes during storms and substorms driven by solar wind disturbances. Electron density variations and irregularities can cause total signal blackouts during strong scintillation periods and enhance satellite positioning errors. We analyzed Global Navigation Satellite System (GNSS) - total electron content (TEC) and Arase satellite observation data to elucidate the characteristics of the electron density variation in the plasmasphere and ionosphere during the May 2024 super storm. To identify the electron density variation in the ionosphere, we calculated the ratio of the TEC difference (rTEC), which is defined as the difference from the 10-quiet-day average TEC normalized by the average value. Additionally, we estimated the electron density in the plasmasphere and inner magnetosphere from the upper frequency limit of the upper hybrid resonance (UHR) waves observed by the Arase satellite. Consequently, an L-t plot of the electron density showed that the plasmasphere contracted from L = 7.0 to L = 1.5 within 9 h after a sudden commencement. During the storm recovery phase, the plasmapause gradually shifted to a higher L-shell. The electron density in the plasmasphere recovered the geomagnetically quiet-time level on a 4-day scale. The timescale of the plasmaspheric refilling was much longer than that of other coronal mass ejection (CME)-driven storms during the Arase era. The rTEC in the Northern Hemisphere showed that an enhancement in the rTEC value occurred at high latitudes (60°–70° in magnetic latitude (MLAT)) in the daytime (10–14 in magnetic local time (MLT)), approximately 1 h after the storm onset. Subsequently, a tongue of ionization (TOI) formed in the polar cap owing to the enhancement of two-cell convection in the high-latitude ionosphere. The rTEC was globally depleted during the storm recovery phase. The depletion indicates the occurrence of a negative storm owing to a neutral composition (O/N\u003csub\u003e2\u003c/sub\u003e) change driven by the energy input from the magnetosphere in the high-latitude thermosphere. The coincidence of the long refilling timescale of the plasmasphere and the depletion of the rTEC suggests that a strong negative storm impedes plasmaspheric refilling.\u003c/p\u003e","manuscriptTitle":"Characteristics of temporal and spatial variation of the electron density in the plasmasphere and ionosphere during the May 2024 super geomagnetic storm","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-18 11:14:06","doi":"10.21203/rs.3.rs-6818022/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor Revision","date":"2025-08-20T00:30:55+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-06-17T14:42:37+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-16T19:00:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-10T13:02:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Earth, Planets and Space","date":"2025-06-04T04:21:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"earth-planets-and-space","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"epsp","sideBox":"Learn more about [Earth, Planets and Space](http://earth-planets-space.springeropen.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/epsp/default.aspx","title":"Earth, Planets and Space","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eaef0c00-decc-4e23-ad1e-20b8f362d3aa","owner":[],"postedDate":"June 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-24T16:00:43+00:00","versionOfRecord":{"articleIdentity":"rs-6818022","link":"https://doi.org/10.1186/s40623-025-02317-3","journal":{"identity":"earth-planets-and-space","isVorOnly":false,"title":"Earth, Planets and Space"},"publishedOn":"2025-11-20 15:57:26","publishedOnDateReadable":"November 20th, 2025"},"versionCreatedAt":"2025-06-18 11:14:06","video":"","vorDoi":"10.1186/s40623-025-02317-3","vorDoiUrl":"https://doi.org/10.1186/s40623-025-02317-3","workflowStages":[]},"version":"v1","identity":"rs-6818022","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6818022","identity":"rs-6818022","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}