The thermospheric neutral density response to the 7–9 September 2017 storms is investigated based on the Swarm satellite observations and the thermosphere-ionosphere-electrodynamic general circulation model (TIEGCM) simulation. The Swarm data depicted a prominent interhemispheric asymmetry (IHA) in the afternoon sector during the second storm, a feature that was yet explained. Driven by realistic high-latitude electric potential and electron precipitation patterns, the TIEGCM is able to reproduce the observed storm-time neutral density response. The TIEGCM simulation reveals that the differences in the traveling atmospheric disturbances (TADs) is largely responsible for the observed IHA in the neutral mass density response at low and middle latitudes, whereas the difference in mean molecular mass between the two hemispheres may contribute to the IHA in neutral density at higher latitudes. The IHAs in TADs and mean molecular mass are attributed to the IHA in Joule heating dissipation on the night and dawn sides.

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On 3 February 2022, at 18:13 UTC, SpaceX launched and a short time later deployed 49 Starlink satellites at an orbit altitude between 210 and 320 km. The satellites were meant to be further raised to 550 km. However, the deployment took place during the main phase of a moderate geomagnetic storm, and another moderate storm occurred on the next day. The resulting increase in atmospheric drag led to 38 out of the 49 satellites reentering the atmosphere in the following days. In this work, we use both observations and simulations to perform a detailed investigation of the thermospheric conditions during this storm. Observations at higher altitudes, by Swarm-A (∼438 km, 09/21 Local Time [LT]) and the Gravity Recovery and Climate Experiment Follow-On (∼505 km, 06/18 LT) missions show that during the main phase of the storms the neutral mass density increased by 110% and 120%, respectively. The storm-time enhancement extended to middle and low latitudes and was stronger in the northern hemisphere. To further investigate the thermospheric variations, we used six empirical and first-principle numerical models. We found the models captured the upper and lower thermosphere changes, however, their simulated density enhancements differ by up to 70%. Further, the models showed that at the low orbital altitudes of the Starlink satellites (i.e., 200–300 km) the global averaged storm-time density enhancement reached up to ∼35%–60%. Although such storm effects are far from the largest, they seem to be responsible for the reentry of the 38 satellites.

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Although the knowledge of the gravity of the Earth has improved considerably with CHAMP, GRACE, and GOCE (see appendices for a list of abbreviations) satellite missions, the geophysical community has identified the need for the continued monitoring of the time-variable component with the purpose of estimating the hydrological and glaciological yearly cycles and long-term trends. Currently, the GRACE-FO satellites are the sole dedicated provider of these data, while previously the GRACE mission fulfilled that role for 15 years. There is a data gap spanning from July 2017 to May 2018 between the end of the GRACE mission and start the of GRACE-FO, while the Swarm satellites have collected gravimetric data with their GPS receivers since December 2013. We present high-quality gravity field models (GFMs) from Swarm data that constitute an alternative and independent source of gravimetric data, which could help alleviate the consequences of the 10-month gap between GRACE and GRACE-FO, as well as the short gaps in the existing GRACE and GRACE-FO monthly time series. The geodetic community has realized that the combination of different gravity field solutions is superior to any individual model and set up the Combination Service of Time-variable Gravity Fields (COST-G) under the umbrella of the International Gravity Field Service (IGFS), part of the International Association of Geodesy (IAG). We exploit this fact and deliver the highest-quality monthly GFMs, resulting from the combination of four different gravity field estimation approaches. All solutions are unconstrained and estimated independently from month to month. We tested the added value of including kinematic baselines (KBs) in our estimation of GFMs and conclude that there is no significant improvement. The non-gravitational accelerations measured by the accelerometer on board Swarm C were also included in our processing to determine if this would improve the quality of the GFMs, but we observed that is only the case when the amplitude of the non-gravitational accelerations is higher than during the current quiet period in solar activity Using GRACE data for comparison, we demonstrate that the geophysical signal in the Swarm GFMs is largely restricted to spherical harmonic degrees below 12. A 750 km smoothing radius is suitable to retrieve the temporal variations in Earth's gravity field over land areas since mid-2015 with roughly 4 cm equivalent water height (EWH) agreement with respect to GRACE. Over ocean areas, we illustrate that a more intense smoothing with 3000 km radius is necessary to resolve large-scale gravity variations, which agree with GRACE roughly at the level of 1 cm EWH, while at these spatial scales the GRACE observes variations with amplitudes between 0.3 and 1 cm EWH. The agreement with GRACE and GRACE-FO over nine selected large basins under analysis is 0.91 cm, 0.76 cm yr-1, and 0.79 in terms of temporal mean, trend, and correlation coefficient, respectively. The Swarm monthly models are distributed on a quarterly basis at ESA's Earth Swarm Data Access (at https://swarm-diss.eo.esa.int/, last access: 5 June 2020, follow Level2longterm and then EGF) and at the International Centre for Global Earth Models (http://icgem.gfz-potsdam.de/series/02_COST-G/Swarm, last access: 5 June 2020), as well as identified with the DOI https://doi.org/10.5880/ICGEM.2019.006 (Encarnacao et al., 2019).

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The CHAMP and GOCE satellites provided high-resolution thermosphere data between 2000 and 2013, improving our knowledge of atmosphere dynamics in the thermosphere-ionosphere region. However, the currently available data sets contain inconsistencies with each other and with external data sets and models, arising to a large extent from errors in the modelling of aerodynamic forces. Improved processing of the wind data for the two satellites would benefit the further development and validation of thermosphere models and improve current understanding of atmospheric dynamics and long-term trends. The first step to remove inconsistencies has been the development of high-fidelity models of the satellite surface geometry. Next, an improved characterization of the collisions between atmospheric particles and satellite surfaces is necessary. In this article, the effect of varying the energy accommodation coefficient, which is a key parameter for describing gas-surface interactions (GSI) is investigated. For past versions of the thermosphere density and wind data from these satellites a value of the energy accommodation coefficient of α_E=0.93 was selected. The satellite accelerometer measurements, from which the thermospheric data are derived, have now been reprocessed using high-fidelity geometries and a wide range of α_E values. Lowering the α_E value used in the processing leads to an increase in the lift over drag ratio for those satellite panels that are inclined to the flow. This changes the direction of the modelled acceleration, and therefore the interpretation of the measured acceleration in terms of wind. The wrong choice of α_E therefore leads to the introduction of satellite attitude-dependent wind errors. For the CHAMP and GOCE satellites, we have found that values of the energy accommodation coefficient significantly lower than 0.93 (0.85 for CHAMP and 0.82 for GOCE) result in increased consistency of the wind data. A comparison between the two missions and an overview of the influence on the results of filtering for solar activity and seasonal and diurnal variations is presented.

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Recently, the horizontal and vertical cross wind at 225- to 295-km altitude were derived from linear acceleration measurements of the Gravity field and steady-state Ocean Circulation Explorer satellite. The vertical component of these wind data is compared to wind data derived from the mass spectrometers of the Atmosphere Explorer C and E and Dynamics Explorer 2 satellites. From a statistical analysis of the 120-s moving-window standard deviation of the vertical wind (σ(V_z)), no consistent discrepancy is found between the accelerometer-derived and the mass spectrometer-derived data. The validated Gravity field and steady-state Ocean Circulation Explorer data are then used to investigate the influence of several parameters and indices on the vertical wind activity. To this end, the probability distribution of σ(V_z) is plotted after distributing the data over bins of the parameter under investigation. The vertical wind is found to respond strongly to geomagnetic activity at high latitudes, although the response settles around a maximum standard deviation of 50 m/s at an Auroral Electrojet index of 800. The dependence on magnetic local time changes with magnetic latitude, peaking around 4:30 over the polar cap and around 01:30 and 13:30 in the auroral oval. Seasonal effects only become visible at low to middle latitudes, revealing a peak wind variability in both local summer and winter. The vertical wind is not affected by the solar activity level.

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Thermospheric wind measurements obtained from linear non-gravitational accelerations of the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite show discrepancies when compared to ground-based measurements. In this paper the cross-wind is derived from both the linear and the angular accelerations using a newly developed iterative algorithm. The two resulting data sets are compared to test the validity of wind derived from angular accelerations and quantify the uncertainty in accelerometer-derived wind data. In general the difference is found to be less than 50 m/s vertically after high-pass filtering, and 100 m/s horizontally. A sensitivity analysis reveals that continuous thrusting is a major source of uncertainty in the torque-derived wind, as are the magnetic properties of the satellite. The energy accommodation coefficient is identified as a particularly promising parameter for improving the consistency of thermospheric cross-wind data sets in the future. The algorithm may be applied to obtain density and cross-wind from other satellite missions that lack accelerometer data, provided the attitude and orbit are known with sufficient accuracy.@en

It is generally assumed that horizontal wind velocities are independent of height above the F<span classCombining double low line"inline-formula">1</span> region (&gt;300km) due to the large molecular viscosity of the upper thermosphere. This assumption is used to compare two completely different methods of thermospheric neutral wind observation, using two distinct locations in the high-latitude Northern Hemisphere. The measurements are from ground-based Fabry-Perot interferometers (FPI) and from in situ accelerometer measurements onboard the challenging mini-satellite payload (CHAMP) satellite, which was in a near-polar orbit. The University College London (UCL) Kiruna Esrange Optical Platform Site (KEOPS) FPI is located in the vicinity of the auroral oval at the ESRANGE site near Kiruna, Sweden (67.8<span classCombining double low line"inline-formula">ĝ</span>N, 20.4<span classCombining double low line"inline-formula">ĝ</span>E). The UCL Longyearbyen FPI is a polar cap site, located at the Kjell Henriksen Observatory on Svalbard (78.1<span classCombining double low line"inline-formula">ĝ</span>N, 16.0<span classCombining double low line"inline-formula">ĝ</span>E). The comparison is carried out in a statistical sense, comparing a longer time series obtained during night-time hours in the winter months (DOY 300-65) with overflights of the CHAMP satellite between 2001 and 2007 over the observational sites, within <span classCombining double low line"inline-formula">±2</span><span classCombining double low line"inline-formula">ĝ</span> latitude (<span classCombining double low line"inline-formula">±230</span>km horizontal range). The FPI is assumed to measure the line-of-sight winds at a height of <span classCombining double low line"inline-formula">ĝ1/4240</span>km, i.e. the peak emission height of the atomic oxygen 630.0nm emission. The cross-track winds are derived from state-of-the-art precision accelerometer measurements at altitudes between <span classCombining double low line"inline-formula">ĝ1/4450</span>km (in 2001) and <span classCombining double low line"inline-formula">ĝ1/4350</span>km (in 2007), i.e. 100-200km above the FPI wind observations. We show that CHAMP wind values at high latitudes are typically 1.5 to 2 times larger than FPI winds. In addition to testing the consistency of the different measurement approaches, the study aims to clarify the effects of viscosity on the height dependence of thermospheric winds.

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During the last two decades, accelerometers on board of the CHAMP, GRACE, GOCE and Swarm satellites have provided high-resolution thermosphere density data to improve our knowledge on atmospheric dynamics and coupling processes in the thermosphere-ionosphere region. Most users of the data have focused on relative density variations. Scale differences between datasets and models have been largely neglected or removed using ad hoc scale factors. The origin of these scale differences arises from errors in the aerodynamic modelling, specifically in the modelling of the satellite outer surface geometry and of the gas-surface interactions. Therefore, the first step to remove the scale differences is to enhance the geometry modelling. This work forms the foundation for the future improvement of characterization of satellite aerodynamics and gas-surface interactions models at TU Delft, as well as for extending the use of sideways and angular accelerations in the aerodynamic analysis of accelerations and derivation of thermosphere datasets. Although work to improve geometry and aerodynamic force models by other authors has focused on CHAMP and GRACE, this paper includes the GOCE and Swarm satellites as well. In addition, it uses a density determination algorithm that is valid for arbitrary attitude orientations, enabling a validation making use of attitude manoeuvres. The results show an improvement in the consistency of density data between these four missions, and of data obtained before, during and after attitude manoeuvres of CHAMP and Swarm. The new models result in larger densities, compared to the previously used panel method. The largest average rescaling of density, by switching to the new geometry models is reached for Swarm at 32%, the smallest for GRACE at 5%. For CHAMP and GOCE, mean differences of 11% and 9% are obtained respectively. In this paper, an overview of the improvements and comparisons of data sets is provided together with an introduction to the next research phase on the gas-surface interactions.@en

Atmospheric gravity waves (GWs) are essential for the dynamics of the middle atmosphere. Recent studies have shown that these waves are also important for the thermosphere/ionosphere (T/I) system. Via vertical coupling, GWs can significantly influence the mean state of the T/I system. However, the penetration of GWs into the T/I system is not fully understood in modeling as well as observations. In the current study, we analyze the correlation between GW momentum fluxes observed in the middle atmosphere (30-90ĝ€km) and GW-induced perturbations in the T/I. In the middle atmosphere, GW momentum fluxes are derived from temperature observations of the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) satellite instrument. In the T/I, GW-induced perturbations are derived from neutral density measured by instruments on the Gravity field and Ocean Circulation Explorer (GOCE) and CHAllenging Minisatellite Payload (CHAMP) satellites. We find generally positive correlations between horizontal distributions at low altitudes (i.e., below 90ĝ€km) and horizontal distributions of GW-induced density fluctuations in the T/I (at 200ĝ€km and above). Two coupling mechanisms are likely responsible for these positive correlations: (1) fast GWs generated in the troposphere and lower stratosphere can propagate directly to the T/I and (2) primary GWs with their origins in the lower atmosphere dissipate while propagating upwards and generate secondary GWs, which then penetrate up to the T/I and maintain the spatial patterns of GW distributions in the lower atmosphere. The mountain-wave related hotspot over the Andes and Antarctic Peninsula is found clearly in observations of all instruments used in our analysis. Latitude-longitude variations in the summer midlatitudes are also found in observations of all instruments. These variations and strong positive correlations in the summer midlatitudes suggest that GWs with origins related to convection also propagate up to the T/I. Different processes which likely influence the vertical coupling are GW dissipation, possible generation of secondary GWs, and horizontal propagation of GWs. Limitations of the observations as well as of our research approach are discussed.

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This study is focused on improving the poorly understood seasonal dependence of northern high-latitude F region thermospheric winds under active geomagnetic conditions. The gaps in our understanding of the dynamic high-latitude thermosphere are largely due to the sparseness of thermospheric wind measurements. With current observational facilities, it is infeasible to construct a synoptic picture of thermospheric winds, but enough data with wide spatial and temporal coverage have accumulated to construct a meaningful statistical analysis. We use long-term data from eight ground-based and two space-based instruments to derive climatological wind patterns as a function of magnetic local time, magnetic latitude, and season. These diverse data sets possess different geometries and different spatial and solar activity coverage. The major challenge is to combine these disparate data sets into a coherent picture while overcoming the sampling limitations and biases among them. In our previous study (focused on quiet time winds), we found bias in the Gravity Field and Steady State Ocean Circulation Explorer (GOCE) cross-track winds. Here we empirically quantify the GOCE bias and use it as a correction profile for removing apparent bias before empirical wind formulation. The assimilated wind patterns exhibit all major characteristics of high-latitude neutral circulation. The latitudinal extent of duskside circulation expands almost 10^∘ from winter to summer. The dawnside circulation subsides from winter to summer. Disturbance winds derived from geomagnetic active and quiet winds show strong seasonal and latitudinal variability. Comparisons between wind patterns derived here and Disturbance Wind Model (DWM07) (which have no seasonal dependence) suggest that DWM07 is skewed toward summertime conditions.

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This paper presents measurements of the amplitudes and timings of the combined, annual, and semiannual variations of thermospheric neutral density, and a comparison of these density variations with measurements of the infrared emissions from carbon dioxide and nitric oxide in the thermosphere. The density values were obtained from measurements of the atmospheric drag experienced by the Challenging Minisatellite Payload, Gravity Recovery and Climate Experiment A, Gravity field and Ocean Circulation Explorer, and three Swarm satellites, while the optical emissions were measured with the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. These data span a time period of 16 years. A database containing global average densities that were derived from the orbits of about 5,000 objects (Emmert, 2009, https://doi.org/10.1029/2009JA014102, 2015b, https://doi.org/10.1002/2015JA021047) was employed for calibrating these density data. A comparison with the NRLMSISE-00 model was used to derive measurements of how much the density changes over time due to these seasonal variations. It is found that the seasonal density oscillations have significant variations in amplitude and timing. In order to test the practicality of using optical emissions as a monitoring tool, the SABER data were fit to the measured variations. Even the most simple fit that used only filtered carbon dioxide emissions had good correlations with the measured oscillations. However, the density oscillations were also well predicted by a simple Fourier series, contrary to original expectations. Nevertheless, measurements of the optical emissions from the thermosphere are expected to have a role in future understanding and prediction of the semiannual variations.

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Satellite gravity field missions, such as CHAMP, GRACE, GOCE and GRACE-FO, are designed to make extremely accurate measurements in low Earth orbit of the (relative) motion of satellites, and proof masses inside these satellites, in order to infer information on the Earth’s gravity field. There are several mechanisms through which the thermosphere and ionosphere influence the way in which this motion is measured. The accelerometers, drag-free control system, dual-frequency radio-tracking systems, star cameras and magnetometers that are part of the payloads and platforms of the satellites, are to some extent also devices for active space weather monitoring. The space weather observations, which are considered an error source to be mitigated for the primary goal of gravity field determination, are a valuable source of information for studies of the thermosphere-ionosphere. For nearly two decades now, data from the accelerometers on board these gravity field missions have had a very large impact on studies of the thermosphere density and horizontal neutral wind. Accurate information on ionospheric electron content has been derived from dual-frequency satellite-to-satellite tracking systems as well. More recent developments are the derivation of vertical neutral wind from GOCE acceleration data and the calibration of platform magnetometer data, converted into ionospheric field-aligned current densities. Using these processing techniques, GOCE, GRACE and GRACE-FO can be turned into sources of valuable thermosphere-ionosphere data, that supplement dedicated missions such as Swarm, in terms of temporal and spatial coverage. To demonstrate the value of this data in the space weather and space physics domains, we provide comparisons of these data with other data sources, such as AMPERE, as well as with output of a global thermosphere-ionosphere general circulation model. It is noteworthy that satellite mission concepts for investigations of thermosphereionosphere coupling, that are currently under study, would carry similar devices and benefit from similar satellite platform designs and orbits as the current gravity field missions. It is clear that there is a large potential to increase this synergy today, and opportunity for dual-purpose missions in the future. We therefore conclude by providing recommendations in terms of instrumentation and data handling for present and future missions. @en

The Swarm mission flies a constellation of three identical satellites, which carry not only technologically advanced magnetometers but also other important and fundamental instruments, such as GPS receivers and accelerometers. The GPS data are mainly used for precise orbit determination (POD). In addition, a POD approach developed at TU Delft, converts Swarm GPS information into accelerations: the gravitational accelerations are modelled with high fidelity, whereas the non-gravitational accelerations are estimated with a Kalman filter strategy. The resulting GPSderived accelerations for all three Swarm satellites are converted directly into thermosphere neutral density data. The GPS-derived products also supplement the accelerometer-derived data of Swarm C. Furthermore, a combination of the non-gravitational acceleration derived from the GPS receiver and the measurements of the accelerometer for Swarm C resulted in the recently released accelerometer products. The latest improvements of the processing associated to the new high-fidelity geometry and the comparison between the GPS-only and accelerometer-derived data are presented in this work. Moreover, the most recent thermospheric neutral density data show signs of a very deep solar minimum, similar to the one in 2008. These data, together with their comparisons with several thermosphere models, are also included in the presentation. @en

The primary mechanism through which energy and momentum are transferred from the lower atmosphere to the thermosphere is through the generation and propagation of atmospheric waves. It is becoming increasingly evident that a few waves from the tropical wave spectrum preferentially propagate into the thermosphere and contribute to modify satellite drag. Two of the more prominent and well-established tropical waves are Kelvin waves: the eastward-propagating 3-day ultra-fast Kelvin wave (UFKW) and the eastward-propagating diurnal tide with zonal wave number 3 (DE3). In this work, Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperatures at 110 km and Gravity field and steady-state Ocean Circulation Explorer (GOCE) neutral densities and cross-track winds near 260 km are used to demonstrate vertical coupling in this height regime due to the UFKW and DE3. Significant inter- and intra-annual variability is found in DE3 and the UFKW, with evidence of latitudinal broadening and filtering of the latitude structures with height due to the effect of dissipation and mean winds. Additionally, anti-correlation between the vertical penetration of these waves to the middle thermosphere and solar activity level is established and explained through the effect of molecular dissipation.

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Over the years, the linear accelerations measured by gravity missions have become an important source for thermospheric neutral density and horizontal wind data. By reducing the measured acceleration by models of thrust and radiation pressure, the aerodynamic acceleration remains, which is iteratively solved for the wind and density. A similar approach has now been taken to derive thermospheric wind from GOCE’s angular accelerations. In this case supplementary models were required for the magnetic torque (including attitude control) and gravity gradient torque. Because not all magnetic properties of GOCE were available to us, daily estimates were made of several magnetic dipoles on the satellite. On top of that a new iterative algorithm was developed that solves the residual force or torque for the neutral density and horizontal and vertical crosswind. The algorithm allows the use of any set of forces and torques. Horizontal winds derived from torques are found to agree up to a large extent with those derived from forces. Both the vertical force and the pitch torque reveal vertical wind signals near the poles. By combining wind data derived from forces with that derived from torques, a reliable vertical wind data set can be established. It is clear from the combined product that the vertical wind responds to increased geomagnetic activity. During geomagnetic storms, peak speeds are observed of up to 150 m/s upward and 100 m/s downward, a factor 5 smaller than the observed horizontal winds. Vertical wind structures are also spatially smaller than their horizontal counterparts, and therefore seem to have a more erratic nature. A correlation is occasionally found between horizontal and vertical wind peaks which is mostly lost when activity increases to high levels. Overall the newly derived data confirms the view that vertical wind structures are usually more local and short-lived than horizontal ones and might be a good indicator of small-scale wave activity. @en

Thermospheric temperature and density recovery during the 5 April 2010 geomagnetic storm has been investigated in this study. Neutral density recovery as revealed by Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) simulations was slower than observations from GOCE, CHAMP, and GRACE satellites, suggesting that the cooling processes may not be fully represented in the model. The NO radiative cooling rate in TIEGCM was also compared with TIMED/SABER measurements along satellite orbits during this storm period. It was found that the model overestimated the NO cooling rate at low latitudes and underestimated it at high latitudes. The effects of particle precipitation on NO number density and NO cooling rate at high latitudes were examined in detail. Model experiments showed that while NO number density and NO cooling rate do change with different specifications of the characteristic energy of auroral precipitating electrons, neutral temperature and density recovery remain more or less the same. The reaction rates of key NO chemistry were tested as well, and the NO number density between 110 and 150 km was found to be very sensitive to the reaction rate of N(²D) + O₂ → NO + O. A temperature-dependent reaction rate for this reaction proposed by Duff et al. (2003) brought the TIEGCM NO cooling rate at high latitudes closer to the SABER observations. With the temperature-dependent reaction rate, the neutral density recovery time became quite close to the observations in the high-latitude Southern Hemisphere. But model-data discrepancies still exist at low latitudes and in the Northern Hemisphere, which calls for further investigation.

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By using data from multiple instruments, we investigate ionospheric/thermospheric behavior during the period from 21 to 23 June 2015, when three interplanetary shocks (IS) of different intensities arrived at Earth. The first IS was registered at 16:45 UT on 21 June and caused ~50 nT increase in the SYM-H index. The second IS arrived at 5:45 UT on 22 June and induced an enhancement of the auroral/substorm activity that led to rapid increase of thermospheric neutral mass density and ionospheric vertical total electron content at high latitudes. Several hours later, topside electron content and electron density increased at low latitudes on the nightside. The third and much larger IS arrived at 18:30 UT on 22 June and initiated a major geomagnetic storm that lasted for many hours. The storm provoked significant effects in the thermosphere and ionosphere on both dayside and nightside. In the thermosphere, the dayside neutral mass density exceeded the quiet time levels by 300-500%, with stronger effects in the summer hemisphere. In the ionosphere, both positive and negative storm effects were observed on both dayside and nightside. We compared the ionospheric observations with simulations by the coupled Sami3 is Also a Model of the Ionosphere/Rice Convection Model (SAMI3/RCM) model. We find rather good agreement between the data and the model for the first phase of the storm, when the prompt penetration electric field (PPEF) was the principal driver. At the end of the storm main phase, when the ionospheric effects were, most likely, driven by a combination of PPEF and thermospheric winds, the modeling results agree less with the observations.

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