Solar wind energy is continuously deposited in the magnetosphere-ionosphere-thermosphere system, causing significant modifications primarily in the high latitude ionosphere. These variations are reflected most instantaneously in the ionospheric electron density (Ne) or in the total electron content (TEC). The drivers of ionospheric variability at high latitudes are not yet fully understood. This variability due to solar wind-magnetosphere-ionosphere coupling could be investigated under winter conditions, while ionization from EUV radiation is minimal, and ionization mostly comes from the coupling processes. This study characterizes the contributions of ionospheric drivers to winter TEC variability. We present a quantitative evaluation of the respective impact of the convection and particle precipitation processes on the TEC variability. We use comprehensive datasets of IGS and EISCAT TEC measurements, alongside merging electric field (Em) calculated from solar wind parameters. We apply a lagged correlation method covering the wintertime to assess the temporal and spatial characteristics of ionospheric response. EISCAT UHF Incoherent Scatter Radar campaigns that consist of several days of continuous measurements are used to estimate the ionospheric response time to the solar wind in the E- and F-region separately and to identify the relevant coupling processes. Our results reveal that the highest correlation between IGS TEC and Em is at a lag time of approximate to 2 h. The EISCAT results show distinctions between the E- and F-region ionosphere responses. In the E-region ionosphere, shorter delays of approximate to 71 min are observed. We suggest that the E-region TEC is driven by auroral particle precipitation during substorm processes, and the delay can be attributed to the loading and unloading times of the magnetosphere. In the F-region, the delays are longer with approximate to 101 min, indicating the effect of polar cap plasma convection, because this duration matches well with the duration of quiet time plasma convection across the polar cap. Under certain conditions, where the F-region is driven by dense polar cap patches and associated convection features, the delay in the F-region can be as short as 90 min. We find that the overall TEC response of approximate to 2 h originates mainly due to the F-region processes, where the electron density is modulated strongly by the convection of the plasma.

The ability of space-based infrastructure to provide essential and sustained benefits to humanity in critical areas such as communications, Earth observation, technology development, navigation, and space exploration is increasingly threatened by the growing amount of orbital debris. A deliberate, urgent, and sustained effort must be made to resolve the problem of space debris and to ensure a risk-free utilisation and sustainability of the space environment. In this paper, we review the concept and appropriate technologies for orbital sustainability in low Earth orbit (LEO) and provide model-based space situational awareness (SSA) for LEO debris. We simulate the long-term evolution of the orbital decay of eight catalogued LEO objects due to space weather-enhanced atmospheric drag, as a function of solar-geophysical indices during Jan-Jun 2024, using the ephemeris data-assisted calibration (EDAC) method. The simulated mean heights and orbit decay rates of the objects compared well with their historical orbital data, although slight deviations were observed depending on the objects’ altitudes. The objects between 500 and 600 km altitude experienced an 8-fold drag effect compared to objects between 600 and 700 km altitude. We also investigated the short-term enhancement of aerodynamic drag during the severe geomagnetic storm of 10–11 May 2024 and found that the storm increased the objects’ orbit decay rates by 233–266% during its main phase, with up to 7-fold relative impact for a group separation of about 60 km. The impact levels were strongly influenced by storm-driven thermospheric density enhancements at the object altitudes, in combination with object-specific orbital dynamics, ballistic properties, and operational characteristics. We also showed that the long-term evolution of atmospheric drag-induced orbital decay on the objects obtained from both EDAC simulated results and the objects’ historical data were also consistent with the signature of solar cycle variation. The results demonstrate significant improvement in drag modeling and that the simulation of a long-term drag impact for maintaining reliable SSA for LEO objects is achievable.

We investigate the high-latitude Joule heating in a recently developed high-resolution configuration of the WACCM-X whole-atmosphere model coupled to the MAGE model. Model resolution and geomagnetic forcing effects during the severe (K-p>8) geomagnetic storm on 24 August 2005 are analyzed, distinguishing storm peak and recovery conditions. The Joule heating energy in MAGE-coupled runs is 71.7%-121.7% higher compared to Heelis- and Weimer-driven WACCM-X runs, due to stronger convection electric fields. Due to the higher Joule heating, the column-integrated O/N-2 ratio is significantly lower in MAGE-coupled runs, potentially correcting a previously observed overestimation of the WACCM-X model. The distribution of modeled Joule heating rates with geomagnetic latitude is affected by the coupling to MAGE as well. The high-resolution model shows distinctly different thermospheric dynamics in response to the geomagnetic storm, leading to a lower neutral particle density over the polar region during storm recovery compared to the coarse-resolution model. The altered thermospheric dynamics causes a 50% higher Joule heating up to about 120 km and lower Joule heating at F region altitudes, in turn affecting the thermospheric neutral density. Despite the overall lower Joule heating rates in the high-resolution model run, the neutral gas heating rate is higher compared to the coarse-resolution run, leading to slightly lower O/N(2 )ratios. The electron density is affected on meso-scales, especially in the area of the auroral oval, by the increase in model resolution, which causes strong local variations of Joule heating estimates between the high- and coarse-resolution model runs. Plain Language Summary Resistive heating, also known as Joule heating, is the fundamental process of light bulbs. Interestingly, it is also of high importance for the interaction of the Earth system and its space environment. The Joule heating of the Earth's atmosphere above 100 km altitude occurs mainly at auroral latitudes and is a main source of so-called "space weather impacts" on human society. Two of the main challenges for space weather forecasts are the accurate modeling of the high-latitude electrodynamics, that is the currents responsible for Joule heating, and so-called meso-scale processes (atmospheric processes with a size of about 20-2,000 km), which are highly important for how the atmosphere reacts to Joule heating. A new high-resolution atmosphere-ionosphere model run coupled to a physical high-latitude electrodynamics model promises to improve on both of these problems. We investigate the model run more closely to distinguish the respective effects of physics-based modeling of high-latitude electrodynamics and the high-resolution model configuration. On a global scale, the modeling of high-latitude electrodynamics has a stronger impact on space weather modeling. However, the high-resolution model configuration significantly affects the thermospheric dynamics and the mesoscale ionosphere, both causing distinct changes to the representation of space weather processes as well.

The growing constellation of low-Earth-orbit satellites allows us to characterize the thermosphere-ionosphere system (TI). One of the most valuable LEO measurements are accelerometer derived neutral density estimates, which play a central role in satellite drag estimations, TI modeling, and space weather operations. Despite their importance, the measurement uncertainty of satellite-derived neutral density for most LEO missions remains unknown. In this study, we use a data assimilation (DA) based framework to diagnose the observation uncertainty directly from neutral density measurements.Using the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics model (CTIPe) and TIDA, the TI Ensemble Kalman filter data assimilation scheme, we perform controlled experiments with varied assumed uncertainties. Two complementary diagnostics are applied: the Desroziers method, which estimates the effective observation uncertainty required for a self-consistent DA system, and an ensemble-spread method, which isolates the true measurement error by removing model-projected variability from the innovation variance.We apply both diagnostics to CHAMP, Swarm A/B/C, and GRACE-A/B across low and high solar-activity periods. Results confirm the expected 10–15% uncertainty for CHAMP during quiet conditions, while GRACE (15–35%) and Swarm (25–50%) exhibit larger values, reflecting differences in altitude, solar activity, instrument characteristics, and thermospheric variability. The two methods provide complementary perspectives and the limit of the estimated uncertainty range: Desroziers quantifies the upper bound, and the ensemble-spread method provides the lower bound uncertainty. The framework provides a pathway to systematically quantify uncertainty in current and upcoming LEO missions, supporting improved density models, drag prediction, and space weather services.

The solar wind (SW) passing the Earth is an important driver of electrodynamic processes in the Earth’s magnetosphere–ionosphere–thermosphere (MIT) system. Since SW observations near Earth (at the bow shock) are very sparse, research and operational applications typically rely on measurements of SW monitors at the Lagrange point L1. The data of these monitors, which provide almost continuous datasets, need to be propagated in time to the bow shock conditions in order to be most useful for MIT studies. The most widely used data source for propagated SW data is provided by OMNIWeb. Near-Earth (NE) SW observations are highly relevant for the validation of the propagated SW estimates. This work uses the NE SW observations to propose a novel method for the estimation of the SW propagation delay. It is based on careful data assessment and a complex combination of correlation analysis and validation metrics. The developed algorithm generates a large dataset of 53,880 events in the period from 22 December 2017 to 30 April 2024, which provides the SW delay along with a list of metrics indicating the quality of the match between the SW structures at L1 and the bow shock. This dataset shows higher reliability in the SW delay estimates than the OMNIWeb data because it focuses on the comparison of structures in the SW. Using the dataset of the period from December 2017 to February 2018, the statistically estimated delay in comparison with the OMNIWeb data reveals that approximately 50% of the delays are computed very accurately with less than 5 min uncertainty, and 80% of the OMNIWeb data delay is reasonably accurate with less than 10 min difference from the statistically estimated delay, providing the best match. However, more than 5% of the OMNIWeb data shows large differences of more than 20 min from the dataset. Thus, it can be concluded that in many cases, the uncertainty in the OMNIWeb delay estimate is larger than the value provided with the data. The generated dataset of SW delay estimates provides an ideal foundation for validating and improving solar wind propagation models.

Given the impact the ionosphere electron density has on radio wave propagation, understanding, characterizing and predicting its behaviour and associated perturbations is of high importance. One type of perturbation commonly observed during geomagnetic storm events is the Large Scale Travelling Ionospheric Disturbance (LSTID). LSTIDs correspond to the ionospheric signature of large-scale atmospheric gravity waves that propagate in the thermosphere. Such waves, which are typically generated due to the input of energy from the solar wind into the Magnetosphere-Ionosphere-Thermosphere (MIT) system, are an essential component contributing to the development of ionospheric storms. Recently, the ATID index, which has been introduced for statistical analyses of TIDs, has been shown to correlate well with solar wind energy input in Europe in mid-latitude regions. The feasibility of predicting LSTIDs in this region has been demonstrated using a linear regression model. Here, an assessment of more advanced modelling approaches is presented to demonstrate their applicability and improvement of the predictions. This work applies methodologies based on artificial neural networks and multi-model ensembles. The persistence model is taken as a baseline for the performance assessment of the different methodologies. A given challenge for the generation of LSTID prediction models is the limited number of observations available. Still, the results show that all proposed methodologies outperform the baseline model when predicting the level of LSTID activity during geomagnetic storms over mid-latitude Europe for predictions beyond 1 h. The linear regression model shows in most cases the best performance among the investigated methodologies, evidencing that more complex techniques could not educe their capabilities in the application of LSTID prediction. For prediction times of 30 min, however, the ensemble of the linear regression and the persistence models presented the best performance overall. The presented assessment of LSTID prediction models/approaches contributes to the development of strategies for predicting LSTID activities over the European region and, it enhances the understanding of the strengths and limitations of different modelling methodologies for this use case.

Incoherent scatter radar measurements rely on the application of a priori parameters from empirical models to initialize the analysis of incoherent scatter spectra. Currently, there is a need to transform ionosphere models to enable reliable space weather predictions through data assimilation of observations. Very often the data assimilation relies on electron densities measured with incoherent scatter radars. Erroneous a priori parameters would lead to the assimilation of inaccurate and physically inconsistent data depending on the ionospheric model. It might therefore be beneficial to assimilate the entire radar spectrum and infer the plasma parameters from the assimilated spectrum by applying the a priori parameters as given by the model. To assess the potential assimilation of incoherent scatter spectra into models, we investigate synthetic EISCAT incoherent scatter spectra calculated from TIE-GCM results. At F1 region altitudes, the atomic-to-molecular ion ratio strongly affects the shape of the incoherent scatter spectrum. Since the vertical profiles of the atomic-to-molecular ion ratio are distinctly different in the EISCAT a priori model and TIE-GCM, the assimilation of single plasma parameters induces additional, unbalanced forces into the model. A similar problem arises in the E region due to different ion-neutral collision frequency profiles. These problems could be solved by assimilation of the entire incoherent scatter spectrum followed by an in-model evaluation of the plasma parameters. We demonstrate the effect of different a priori profiles on the spectral analysis and how the derived plasma parameters are changing when leveraging a more comprehensive approach of using forward modeling with TIE-GCM.

The mesosphere and lower thermosphere (MLT) comprise a highly variable region that forms the transition region between the middle and upper atmosphere. The variability of this region is driven by atmospheric waves transporting energy and momentum from the lower and middle atmosphere to MLT altitudes. These waves cover a wide range of temporal (minutes to days) and spatial (kilometers to planetary) scales. The upward propagation of atmospheric gravity waves and tides is one of the key processes at all latitudes that alters the state of the ionosphere–thermosphere system, and their vertical propagation depends crucially on the background mean winds. The TIMED Doppler Interferometer (TIDI) on board the Thermosphere-Ionosphere-Mesosphere-Energetics and Dynamics (TIMED) satellite observes neutral winds at the MLT using airglow emissions. We establish a TIDI mean wind climatology, compare our results with existing climatologies derived from local meteor radar observations, and discuss similarities and differences depending on local time and geographical latitude.

The ionosphere is a critical factor for the performance of a wide range of communication and navigation systems. Sudden significant changes in its electron density can cause degradations in the performance of these technical systems. The variability of the ionosphere is mainly driven by solar EUV radiation, but solar wind can also modify the ionosphere significantly for periods of geomagnetic storms. The modelling of the solar wind driven variability of the ionospheric electron density is still an open challenge because of the very complex nature of the ionosphere response to the solar wind input. This study presents an attempt to reproduce the variability of the Total Electron Content (TEC) during one of the most recent extreme geomagnetic storms, which occurred on 10 May 2024.18 years of TEC maps (2005-2023) provided by the International GNSS Service (IGS) are analysed for potential correlations with the popular geomagnetic index Kp. The analysis differentiates local and UT dependencies. The correlation results show a clear latitudinal dependence and hemispheric asymmetry. A linear regression model is generated for those conditions, where a significant correlation is detected. This statistical model is used to reproduce the storm in May 2024. The results are compared with the actual IGS TEC maps observed during the storm.

The ion-neutral collision frequency is a key parameter for the coupling of the neutral atmosphere and the ionosphere. Especially in the mesosphere lower-thermosphere (MLT), the collision frequency is crucial for multiple processes, e.g., Joule heating, neutral dynamo effects, and momentum transfer due to ion drag. Few approaches exist to directly infer ion-neutral collision frequency measurements in that altitude range. We apply the recently demonstrated difference spectrum fitting method to obtain the ion-neutral collision frequency from dual-frequency measurements with the EISCAT incoherent scatter radars in Troms & oslash;. A 60 h long EISCAT campaign was conducted in December 2022. Strong variations of nighttime ionization rates were observed with electron densities at 95 km altitude varying from Ne,95 similar to 109 to 1011m-3, which indicates varying levels of particle precipitation. A second EISCAT campaign was conducted on 16 May 2024, capturing a solar energetic particle (SEP) event, exhibiting constantly increased ionization due to particle precipitation in the lower E region: Ne,95 greater than or similar to 5x1010m-3. We demonstrate variations of the ion-neutral collision frequency profile that we interpret as neutral particle uplift due to particle precipitation heating. Assuming a rigid-sphere particle model, we derive neutral density profiles which indicate a significant variation of neutral gas density between about 90-110 km altitude that correlate with the estimated strength of particle precipitation. However, the change in ion-neutral collision frequencies cannot be conclusively linked to the particle precipitation impact, and alternative interpretations are discussed. We additionally test the sensitivity of the difference spectrum method to various a priori collision frequency profiles.

We systematically evaluate the high-latitude Joule heating of the recently released version 3.0 Thermosphere Ionosphere Electrodynamics General Circulation Model (TIE-GCM) by comparison to EISCAT incoherent scatter radar measurements. The model performance is examined using normalized root mean square deviations derived from test runs driven by different convection patterns from empirical and data-assimilated models. The following features are revealed: (a) Data-assimilated geomagnetic forcing improves the agreement between modeled and EISCAT-derived Joule heating rates by 8%, 28%, and 54% for low, moderate, and high geomagnetic activity. (b) Increasing model grid resolution from 2.5 degrees to 1.25 degrees leads to 20% higher Joule heating rates. (c) AMIE-driven runs better reproduce the magnitude of the Joule heating rates, AMGeO-driven runs the vertical profile. (d) Internal model time step resolution has no effect on the Joule heating rates.

Model simulations indicate that long-term changes in the thermosphere may influence the intensity of the ionospheric response to geomagnetic activity (GA). This study investigates the response of the peak electron density of the ionosphere () to GA and its consistency across different solar cycles (SCs) to identify any observable long-term variation. Hourly values of from six ionospheric stations located at midlatitudes in both hemispheres are examined from 1964 to 2019. Residuals of relative to a background model are analyzed for correlations with various GA indices to assess the ionospheric response to GA. Kp modified (Kpm) exhibits the highest absolute correlation with the residuals, indicating it as the most suitable index. The observed patterns align with the well-established storm-time characteristics at midlatitudes, showing a predominant negative response during summer morning hours and a positive response during winter afternoons. During summer, there is a marked negative response to GA with sufficiently high correlations for statistical analysis. However, no significant long-term changes in the relationship between and GA are identified within the Kpm range of 1-5. This is mainly attributed to the combination of small changes in concentration (compared to simulation results from models) and increasing solar wind forcing during SC 23 and 24 than previous SCs. During winter, very low correlation between and GA prohibits the analysis of any long-term changes in their relationship.

Abstract Joule heating is one of the main energy inputs into the thermosphere‐ionosphere system. Precise modeling of this process is essential for any space weather application. Existing thermosphere‐ionosphere models tend to underestimate the actual Joule heating rate quite significantly. The Thermosphere‐Ionosphere‐Electrodynamics General‐Circulation‐Model applies an empirical scaling factor of 1.5 for compensation. We calculate vertical profiles of Joule heating rates from approximately 2,220 hr of measurements with the EISCAT incoherent scatter radar and the corresponding model runs. We investigate model runs with the plasma convection driven by both the Heelis and the Weimer model. The required scaling of the Joule heating profiles is determined with respect to the Kp index, the Kan‐Lee merging electric field EKL, and the magnetic local time. Though the default scaling factor of 1.5 appears to be adequate on average, we find that the required scaling varies strongly with all three parameters ranging from 0.46 to ∼20 at geomagnetically disturbed and quiet times, respectively. Furthermore, the required scaling is significantly different in runs driven by the Heelis and Weimer model. Adjusting the scaling factor with respect to the Kp index, EKL, the magnetic local time, and the choice of convection model would reduce the difference between Joule heating rates calculated from measurement and model plasma parameters.

The solar wind continuously transfers energy into the Earth’s thermosphere-ionosphere system and variations in the solar wind properties modify the state of the system. The modifications are best visible during storm conditions when the ingestion of extreme amounts of solar wind energy into the thermosphere-ionosphere system causes global changes in thermosphere as well as large deviations in the ionospheric electron density from its quiet conditions. This study shows that there exists a persistent impact of the solar wind on the high-latitude electron density. A data set of 22 years of Total Electron Content (TEC) and 15 years of ionosonde data (critical frequency foF2 and height of maximum electron density hmF2) at Tromsø (70°N, 19°E) are used for correlation analyses with different solar wind parameters from OMNIWEB hourly “Near-Earth” solar wind magnetic field and plasma data. The results show that the ionospheric parameters systematically respond with an increase or decrease depending on local time, season, and solar cycle. TEC and foF2 increase with solar wind energy during winter night conditions and decrease with increasing solar wind energy during summer daytime. The summer negative ionospheric response is more intense during high solar activity conditions, while the winter positive ionospheric response is stronger during low solar activity. An anomaly is observed around 10 UT (noon) when TEC and foF2 respond with an increase during low solar activity conditions. Plasma convection, particle precipitation and Joule heating are the main drivers of the observed electron density changes at Tromsø. Local time, season, and solar cycle changes in the background ionosphere-thermosphere conditions lead to different effects of these driving processes. The results help to better understand the variability of the high-latitude electron density and show that solar wind forcing causes a systematic and persistent response of the ionosphere, which alternates depending on local time, season, and solar cycle.

AbstractThis study investigates the Brazilian low‐latitude ionospheric response to CIR/HSS‐driven geomagnetic storms during the declining phase of solar cycle 24, from 2016 to 2017. In this period the geomagnetic storms were mostly moderate, SymHmin ≈ −72 nT, AEmax ≈ 1580 nT, Vswmax ≈ 690 km/s and lasted, on average, for 6 days. We analyze the variations in Vertical Total Electron Content (VTEC) at three representative regions: bele, over the equatorial region; boav and cuib, at the northern and southern crests of the Equatorial Ionization Anomaly. Our findings reveal the role of High‐Speed Solar Wind Streams and Corotating Interaction Region—driven geomagnetic storms. The VTEC intensifications were up to 30 TECu, during the daytime and nighttime. Additionally, three categories of nighttime enhancements were observed and analyzed with distinct characteristics and levels of pre‐reversal strengthening; Depletions up to 20 TECu also occurred during the day and nighttime. The delay between the storm commencement and the positive and negative variations were, on average, 7 and 20 hours, respectively. We discuss the Prompt Penetration Electric Fields and Disturbance Dynamo Electric Fields following the magnetic reconnection between Earth's and interplanetary magnetic field, using observational data and modeling. Furthermore, this study presents catalogs of low‐latitude ionospheric storms, providing detailed information for space weather applications and ionospheric modeling.

This paper aims to provide an overview on recent advances in ionospheric modeling capabilities, with the emphasis in the efforts relevant to electron density variability. The discussion spans a wide range of model formulations (e.g., from purely empirical to physics-based ones and data-driven approaches) seeking for advances or gaps with regard to present challenges. This discussion is further supported by consideration of the models' assessment and accessibility, as well as scientific advances that may drive further improvements in our modeling capabilities. Giving the emphasis in the period from 2015 onwards, the ultimate goal of the present analysis is to comment on progress with respect to the COSPAR/ILWS Space Weather roadmap's considerations/recommendations for 2015–2025 as input to the roadmap’s update undertaken by the ISWAT/COSPAR action.

Estimating global and multi-level Thermosphere Neutral Density (TND) is important for studying coupling processes within the upper atmosphere, and for applications like orbit prediction. Models are applied for predicting TND changes, however, their performance can be improved by accounting for the simplicity of model structure and the sampling limitations of model inputs. In this study, a simultaneous Calibration and Data Assimilation (C/DA) algorithm is applied to integrate freely available CHAMP, GRACE, and Swarm derived TND measurements into the NRLMSISE-00 model. The improved model, called 'C/DA-NRLMSISE-00', and its outputs fit to these measured TNDs, are used to produce global TND fields at arbitrary altitudes (with the same vertical coverage as the NRLMSISE-00). Seven periods, between 2003-2020 that are associated with relatively high geomagnetic activity selected to investigate these fields, within which available models represent difficulties to provide reasonable TND estimates. Independent validations are performed with along-track TNDs that were not used within the C/DA framework, as well as with the outputs of other models such as the Jacchia-Bowman 2008 and the High Accuracy Satellite Drag Model. The numerical results indicate an average 52%, 50%, 56%, 25%, 47%, 54%, and 63% improvement in the Root Mean Squared Errors of the short term TND forecasts of C/DA-NRLMSISE00 compared to the along-track TND estimates of GRACE (2003, altitude 490 km), GRACE (2004, altitude 486 km), CHAMP (2008, altitude 343 km), GOCE (2010, altitude 270 km), Swarm-B (2015, altitude 520 km), Swarm-B (2017, altitude 514 km), and Swarm-B (2020, altitude 512 km), respectively.

Abstract Estimating global and multi-level Thermosphere Neutral Density (TND) is important for studying coupling processes within the upper atmosphere, and for applications like orbit prediction. Available models fall short in predicting realistic TND changes due to the simplicity of model structure or sampling limitations. In this study, a simultaneous Calibration and Data Assimilation (C/DA) algorithm is applied to integrate freely available CHAMP, GRACE, and Swarm derived TND measurements into the NRLMSISE-00 model. The improved model, called `C/DA-NRLMSISE-00', and its outputs fit to these measured TNDs, are used to produce global TND fields at arbitrary altitudes (with the same vertical coverage as the NRLMSISE-00). Seven periods, between 2003-2020 that are associated with relatively high geomagnetic activity selected to investigate these fields, within which available models represent difficulties to provide reasonable TND estimates. Independent validations are performed with along-track TNDs that were not used within the C/DA framework, as well as with the outputs of other models such as the Jacchia-Bowman 2008 and the High Accuracy Satellite Drag Model. The numerical results indicate an average 52%, 50%, 56%, 25%, 47%, 54%, and 63% improvement in the Root Mean Squared Errors of the short term TND forecasts of C/DA-NRLMSISE00 compared to the along-track TND estimates of GRACE (2003, altitude 490 km), GRACE (2004, altitude 486 km), CHAMP (2008, altitude 343 km), GOCE (2010, altitude 270 km), Swarm-B (2015, altitude 520 km), Swarm-B (2017, altitude 514 km), and Swarm-B (2020, altitude 512 km), respectively.